Pediatric hospitalists play an increasingly significant role in perioperative pain management.¹ Advances in pediatric surgical comanagement may improve quality of care and reduce the length of hospitalization.² This review is based on queries of the PubMed and Cochrane databases between January 1, 2014, and July 15, 2019, using the search terms “perioperative pain management,” “postoperative pain,” “pediatric,” and “children.” In addition, the authors reviewed key position statements from the American Academy of Pediatrics (AAP), the American Pain Society (APS), the Centers for Disease Control and Prevention (CDC), and the Society of Hospital Medicine (SHM) regarding pain management.³ This update is intended to be relevant for practicing pediatric hospitalists, with a focus on recently expanded options for pain management and judicious opioid use in hospitalized children.

Postoperative pain management begins preoperatively according to the concept of the perioperative surgical home (PSH).⁴ The preoperative history should identify the patient’s previous positive (eg, good pain control) and negative (eg, adverse reactions) experiences with pain medications. Family and patient expectations should be discussed regarding types and sources of pain, pain duration, exacerbating/alleviating factors, and modalities available for realistic pain control because preoperative information can limit anxiety and improve outcomes. Pain specialists can perform risk assessments preoperatively and develop plans to address pharmacologic tolerance, withdrawal, and opioid-induced hyperalgesia after surgery.⁵ Children with chronic pain and on preoperative opioids may require more analgesia for a longer duration postoperatively. Early recognition of variability of patient’s pain perception and differences in responses to pain need to be clearly communicated across the disciplines in a collaborative model of care.

Children with medical complexity and/or cognitive, emotional, or behavioral impairments may benefit from preoperative psychosocial treatments and utilization of pain self-­management training and strategies that could further reduce anxiety and optimize postoperative care because patient and parental preoperative anxiety may be associated with adverse outcomes. Validated pain assessment tools like Revised FLACC (Face, Leg, Activity, Cry, and Consolability) Scale and Individualized Numeric Rating Scale could be particularly useful in children with limitations in communication or altered pain perception; therefore, medical teams and family members should discuss their utilization preoperatively.

Multimodal analgesia (MMA) is a strategy that synergistically uses pharmacologic and nonpharmacologic modalities to target pain at multiple points of the pain processing pathway (Table).⁶ MMA can optimize pain control by addressing different types of pain (eg, incisional pain, muscle spasm, or neuropathic pain), expedite recovery, reduce potential pharmacologic side effects, and decrease opioid consumption. Patients taking opioids are at an increased risk of developing opioid-related side effects such as respiratory depression, medication tolerance, and anxiety, with resultant longer hospital stay, increased readmissions, and higher costs of care.⁷ Treatment for postoperative pain should prioritize appropriately dosed and precisely scheduled MMA before opioid-focused analgesia with the goals of decreasing opioid-related adverse effects, intentional misuse, diversion, and accidental ingestions. The AAP, APS, CDC, and SHM endorse the use of MMA and recommend nonpharmacologic measures and regional anesthesia.^8,9 The most used modalities in MMA are discussed below.

Acetaminophen

Acetaminophen has central-acting analgesic and antipyretic properties and readily crosses the blood brain barrier, which makes it particularly useful in spine and neurological surgeries. Oral administration is preferred when feasible. The AAP recommends refraining from rectal administration of acetaminophen as analgesia in children because of concerns about toxic effects and erratic, variable absorption.¹⁰ A systematic review of six studies found no benefit in pain control between intravenous (IV) and oral (PO) administration of acetaminophen in adults.¹¹ There is a paucity of studies in children comparing PO with IV acetaminophen perioperative efficacy. Children may benefit from IV formulations in the early postoperative period, in cases with frequent nausea and vomiting, and in those with oral medication intolerance. Since infants have greater risk of respiratory depression from opioids, IV acetaminophen may have utility in this age group. Because of the cost associated with IV formulation, some institutions restrict IV acetaminophen. However, rapidly well-controlled pain and minimization of opioid-related side effects with shorter hospital stays may lower healthcare costs despite the cost of acetaminophen itself.

NSAIDs

NSAIDs possess anti-inflammatory properties through the inhibition of cyclooxygenase and blockade of prostaglandin production. NSAID risks include bleeding, renal and gastrointestinal toxicities, and potentially delayed wound and bone healing. Ketorolac is an NSAID that continues to be widely used with demonstrated opioid-sparing effects. Many retrospective studies including large numbers of pediatric patients have not demonstrated increased risks of bleeding nor poor wound healing with short postoperative use. A Cochrane review, however, concluded that there is insufficient data to either support or reject the efficacy or safety of ketorolac for postoperative pain treatment in children, mostly because of the very low quality of evidence.12

Regional Anesthesia

Regional anesthesia, which includes central (spinal/epidural/caudal) and peripheral blocks, decreases postoperative pain and opioid-associated side effects. Blocks typically consist of local anesthetic with or without the addition of adjuncts (eg, clonidine, dexamethasone). Regional anesthesia may also improve pulmonary function, compared with that of nonregional MMA use, in patients who have thoracic or upper abdominal surgeries. While having broad applications, the utility of regional anesthesia is greatest in preterm infants/neonates and in those with underlying respiratory pathology. A systematic review of randomized controlled trials demonstrated that regional anesthesia decreased opioid consumption and minimized postoperative pain with no significant complications attributed to its use.¹³ Additional studies are needed to better delineate specific surgical procedures and subpopulations of pediatric patients in which regional anesthesia may provide the most benefit.

Gabapentinoids

Children receiving gabapentinoids perioperatively have been shown to have fewer adverse reactions, decreased opioid consumption, and less anxiety, as well as improved pain scores. Gabapentin is increasingly being utilized for children with idiopathic scoliosis undergoing posterior spinal fusion, and there is some evidence for improving pain control and reducing opioid use. However, a recent systematic review found a paucity of data supporting its clinical use.¹⁴ Both gabapentin and pregabalin may further increase risks of respiratory depression, especially in synergy with opioids and benzodiazepines.

Opioids

Opioids should be used with caution in pediatric patients and are reserved primarily for the management of severe acute pain. The shortest duration of the lowest effective dose of opioids should be encouraged. Patient-controlled opioid analgesia (PCA) offers benefits when parenteral postoperative analgesia is indicated: It maximizes pain relief, minimizes risk of overdose, and improves psychological well-being through self-­administration of pain medicines. Basal-infusion PCA should not be routinely used because it is associated with nausea, vomiting, and respiratory depression without having superior analgesia compared with demand use only. Monitoring of side stream end-tidal capnography can readily detect respiratory depression, especially if opioids, benzodiazepines, gabapentinoids, and diphenhydramine are used concomitantly. Patient education regarding opioid use, side effects, safe storage, and disposal practices is imperative because significant amounts of opioids remain in households after completion of treatment for pain and because opioid diversion and accidental ingestions account for significant morbidity. Providers need to balance efficient pain management with opioid stewardship, complying with state and federal policies to limit harm related to opioid diversion.¹⁵

Nonpharmacological Modalities

The use of nonpharmacologic therapies, along with pharmacologic modalities, for perioperative pain management has been shown to decrease opioid use and opioid-related side effects. Trials of acupressure have demonstrated improvement in nausea and vomiting, sleep quality, and pain and anxiety scores. Nonpharmacologic treatments currently serve as a complementary approach for pain and anxiety management in the perioperative setting including acupuncture, acupressure, osteopathic manipulative treatment, massage, meditation, biofeedback, hypnotherapy, and physical/occupational, relaxation, cognitive-behavioral, chiropractic, music, and art therapies. The Joint Commission suggests consideration of such modalities by hospitals.

Pediatric hospitalists play an increasingly significant role in perioperative pain management.¹ Advances in pediatric surgical comanagement may improve quality of care and reduce the length of hospitalization.² This review is based on queries of the PubMed and Cochrane databases between January 1, 2014, and July 15, 2019, using the search terms “perioperative pain management,” “postoperative pain,” “pediatric,” and “children.” In addition, the authors reviewed key position statements from the American Academy of Pediatrics (AAP), the American Pain Society (APS), the Centers for Disease Control and Prevention (CDC), and the Society of Hospital Medicine (SHM) regarding pain management.³ This update is intended to be relevant for practicing pediatric hospitalists, with a focus on recently expanded options for pain management and judicious opioid use in hospitalized children.

Postoperative pain management begins preoperatively according to the concept of the perioperative surgical home (PSH).⁴ The preoperative history should identify the patient’s previous positive (eg, good pain control) and negative (eg, adverse reactions) experiences with pain medications. Family and patient expectations should be discussed regarding types and sources of pain, pain duration, exacerbating/alleviating factors, and modalities available for realistic pain control because preoperative information can limit anxiety and improve outcomes. Pain specialists can perform risk assessments preoperatively and develop plans to address pharmacologic tolerance, withdrawal, and opioid-induced hyperalgesia after surgery.⁵ Children with chronic pain and on preoperative opioids may require more analgesia for a longer duration postoperatively. Early recognition of variability of patient’s pain perception and differences in responses to pain need to be clearly communicated across the disciplines in a collaborative model of care.

Children with medical complexity and/or cognitive, emotional, or behavioral impairments may benefit from preoperative psychosocial treatments and utilization of pain self-­management training and strategies that could further reduce anxiety and optimize postoperative care because patient and parental preoperative anxiety may be associated with adverse outcomes. Validated pain assessment tools like Revised FLACC (Face, Leg, Activity, Cry, and Consolability) Scale and Individualized Numeric Rating Scale could be particularly useful in children with limitations in communication or altered pain perception; therefore, medical teams and family members should discuss their utilization preoperatively.

Multimodal analgesia (MMA) is a strategy that synergistically uses pharmacologic and nonpharmacologic modalities to target pain at multiple points of the pain processing pathway (Table).⁶ MMA can optimize pain control by addressing different types of pain (eg, incisional pain, muscle spasm, or neuropathic pain), expedite recovery, reduce potential pharmacologic side effects, and decrease opioid consumption. Patients taking opioids are at an increased risk of developing opioid-related side effects such as respiratory depression, medication tolerance, and anxiety, with resultant longer hospital stay, increased readmissions, and higher costs of care.⁷ Treatment for postoperative pain should prioritize appropriately dosed and precisely scheduled MMA before opioid-focused analgesia with the goals of decreasing opioid-related adverse effects, intentional misuse, diversion, and accidental ingestions. The AAP, APS, CDC, and SHM endorse the use of MMA and recommend nonpharmacologic measures and regional anesthesia.^8,9 The most used modalities in MMA are discussed below.

Acetaminophen

Acetaminophen has central-acting analgesic and antipyretic properties and readily crosses the blood brain barrier, which makes it particularly useful in spine and neurological surgeries. Oral administration is preferred when feasible. The AAP recommends refraining from rectal administration of acetaminophen as analgesia in children because of concerns about toxic effects and erratic, variable absorption.¹⁰ A systematic review of six studies found no benefit in pain control between intravenous (IV) and oral (PO) administration of acetaminophen in adults.¹¹ There is a paucity of studies in children comparing PO with IV acetaminophen perioperative efficacy. Children may benefit from IV formulations in the early postoperative period, in cases with frequent nausea and vomiting, and in those with oral medication intolerance. Since infants have greater risk of respiratory depression from opioids, IV acetaminophen may have utility in this age group. Because of the cost associated with IV formulation, some institutions restrict IV acetaminophen. However, rapidly well-controlled pain and minimization of opioid-related side effects with shorter hospital stays may lower healthcare costs despite the cost of acetaminophen itself.

NSAIDs

NSAIDs possess anti-inflammatory properties through the inhibition of cyclooxygenase and blockade of prostaglandin production. NSAID risks include bleeding, renal and gastrointestinal toxicities, and potentially delayed wound and bone healing. Ketorolac is an NSAID that continues to be widely used with demonstrated opioid-sparing effects. Many retrospective studies including large numbers of pediatric patients have not demonstrated increased risks of bleeding nor poor wound healing with short postoperative use. A Cochrane review, however, concluded that there is insufficient data to either support or reject the efficacy or safety of ketorolac for postoperative pain treatment in children, mostly because of the very low quality of evidence.12

Regional Anesthesia

Regional anesthesia, which includes central (spinal/epidural/caudal) and peripheral blocks, decreases postoperative pain and opioid-associated side effects. Blocks typically consist of local anesthetic with or without the addition of adjuncts (eg, clonidine, dexamethasone). Regional anesthesia may also improve pulmonary function, compared with that of nonregional MMA use, in patients who have thoracic or upper abdominal surgeries. While having broad applications, the utility of regional anesthesia is greatest in preterm infants/neonates and in those with underlying respiratory pathology. A systematic review of randomized controlled trials demonstrated that regional anesthesia decreased opioid consumption and minimized postoperative pain with no significant complications attributed to its use.¹³ Additional studies are needed to better delineate specific surgical procedures and subpopulations of pediatric patients in which regional anesthesia may provide the most benefit.

Gabapentinoids

Children receiving gabapentinoids perioperatively have been shown to have fewer adverse reactions, decreased opioid consumption, and less anxiety, as well as improved pain scores. Gabapentin is increasingly being utilized for children with idiopathic scoliosis undergoing posterior spinal fusion, and there is some evidence for improving pain control and reducing opioid use. However, a recent systematic review found a paucity of data supporting its clinical use.¹⁴ Both gabapentin and pregabalin may further increase risks of respiratory depression, especially in synergy with opioids and benzodiazepines.

Opioids

Opioids should be used with caution in pediatric patients and are reserved primarily for the management of severe acute pain. The shortest duration of the lowest effective dose of opioids should be encouraged. Patient-controlled opioid analgesia (PCA) offers benefits when parenteral postoperative analgesia is indicated: It maximizes pain relief, minimizes risk of overdose, and improves psychological well-being through self-­administration of pain medicines. Basal-infusion PCA should not be routinely used because it is associated with nausea, vomiting, and respiratory depression without having superior analgesia compared with demand use only. Monitoring of side stream end-tidal capnography can readily detect respiratory depression, especially if opioids, benzodiazepines, gabapentinoids, and diphenhydramine are used concomitantly. Patient education regarding opioid use, side effects, safe storage, and disposal practices is imperative because significant amounts of opioids remain in households after completion of treatment for pain and because opioid diversion and accidental ingestions account for significant morbidity. Providers need to balance efficient pain management with opioid stewardship, complying with state and federal policies to limit harm related to opioid diversion.¹⁵

Nonpharmacological Modalities

The use of nonpharmacologic therapies, along with pharmacologic modalities, for perioperative pain management has been shown to decrease opioid use and opioid-related side effects. Trials of acupressure have demonstrated improvement in nausea and vomiting, sleep quality, and pain and anxiety scores. Nonpharmacologic treatments currently serve as a complementary approach for pain and anxiety management in the perioperative setting including acupuncture, acupressure, osteopathic manipulative treatment, massage, meditation, biofeedback, hypnotherapy, and physical/occupational, relaxation, cognitive-behavioral, chiropractic, music, and art therapies. The Joint Commission suggests consideration of such modalities by hospitals.

Pediatric hospitalists play an increasingly significant role in perioperative pain management.¹ Advances in pediatric surgical comanagement may improve quality of care and reduce the length of hospitalization.² This review is based on queries of the PubMed and Cochrane databases between January 1, 2014, and July 15, 2019, using the search terms “perioperative pain management,” “postoperative pain,” “pediatric,” and “children.” In addition, the authors reviewed key position statements from the American Academy of Pediatrics (AAP), the American Pain Society (APS), the Centers for Disease Control and Prevention (CDC), and the Society of Hospital Medicine (SHM) regarding pain management.³ This update is intended to be relevant for practicing pediatric hospitalists, with a focus on recently expanded options for pain management and judicious opioid use in hospitalized children.

Postoperative pain management begins preoperatively according to the concept of the perioperative surgical home (PSH).⁴ The preoperative history should identify the patient’s previous positive (eg, good pain control) and negative (eg, adverse reactions) experiences with pain medications. Family and patient expectations should be discussed regarding types and sources of pain, pain duration, exacerbating/alleviating factors, and modalities available for realistic pain control because preoperative information can limit anxiety and improve outcomes. Pain specialists can perform risk assessments preoperatively and develop plans to address pharmacologic tolerance, withdrawal, and opioid-induced hyperalgesia after surgery.⁵ Children with chronic pain and on preoperative opioids may require more analgesia for a longer duration postoperatively. Early recognition of variability of patient’s pain perception and differences in responses to pain need to be clearly communicated across the disciplines in a collaborative model of care.

Children with medical complexity and/or cognitive, emotional, or behavioral impairments may benefit from preoperative psychosocial treatments and utilization of pain self-­management training and strategies that could further reduce anxiety and optimize postoperative care because patient and parental preoperative anxiety may be associated with adverse outcomes. Validated pain assessment tools like Revised FLACC (Face, Leg, Activity, Cry, and Consolability) Scale and Individualized Numeric Rating Scale could be particularly useful in children with limitations in communication or altered pain perception; therefore, medical teams and family members should discuss their utilization preoperatively.

Multimodal analgesia (MMA) is a strategy that synergistically uses pharmacologic and nonpharmacologic modalities to target pain at multiple points of the pain processing pathway (Table).⁶ MMA can optimize pain control by addressing different types of pain (eg, incisional pain, muscle spasm, or neuropathic pain), expedite recovery, reduce potential pharmacologic side effects, and decrease opioid consumption. Patients taking opioids are at an increased risk of developing opioid-related side effects such as respiratory depression, medication tolerance, and anxiety, with resultant longer hospital stay, increased readmissions, and higher costs of care.⁷ Treatment for postoperative pain should prioritize appropriately dosed and precisely scheduled MMA before opioid-focused analgesia with the goals of decreasing opioid-related adverse effects, intentional misuse, diversion, and accidental ingestions. The AAP, APS, CDC, and SHM endorse the use of MMA and recommend nonpharmacologic measures and regional anesthesia.^8,9 The most used modalities in MMA are discussed below.

Acetaminophen

Acetaminophen has central-acting analgesic and antipyretic properties and readily crosses the blood brain barrier, which makes it particularly useful in spine and neurological surgeries. Oral administration is preferred when feasible. The AAP recommends refraining from rectal administration of acetaminophen as analgesia in children because of concerns about toxic effects and erratic, variable absorption.¹⁰ A systematic review of six studies found no benefit in pain control between intravenous (IV) and oral (PO) administration of acetaminophen in adults.¹¹ There is a paucity of studies in children comparing PO with IV acetaminophen perioperative efficacy. Children may benefit from IV formulations in the early postoperative period, in cases with frequent nausea and vomiting, and in those with oral medication intolerance. Since infants have greater risk of respiratory depression from opioids, IV acetaminophen may have utility in this age group. Because of the cost associated with IV formulation, some institutions restrict IV acetaminophen. However, rapidly well-controlled pain and minimization of opioid-related side effects with shorter hospital stays may lower healthcare costs despite the cost of acetaminophen itself.

NSAIDs

NSAIDs possess anti-inflammatory properties through the inhibition of cyclooxygenase and blockade of prostaglandin production. NSAID risks include bleeding, renal and gastrointestinal toxicities, and potentially delayed wound and bone healing. Ketorolac is an NSAID that continues to be widely used with demonstrated opioid-sparing effects. Many retrospective studies including large numbers of pediatric patients have not demonstrated increased risks of bleeding nor poor wound healing with short postoperative use. A Cochrane review, however, concluded that there is insufficient data to either support or reject the efficacy or safety of ketorolac for postoperative pain treatment in children, mostly because of the very low quality of evidence.12

Regional Anesthesia

Regional anesthesia, which includes central (spinal/epidural/caudal) and peripheral blocks, decreases postoperative pain and opioid-associated side effects. Blocks typically consist of local anesthetic with or without the addition of adjuncts (eg, clonidine, dexamethasone). Regional anesthesia may also improve pulmonary function, compared with that of nonregional MMA use, in patients who have thoracic or upper abdominal surgeries. While having broad applications, the utility of regional anesthesia is greatest in preterm infants/neonates and in those with underlying respiratory pathology. A systematic review of randomized controlled trials demonstrated that regional anesthesia decreased opioid consumption and minimized postoperative pain with no significant complications attributed to its use.¹³ Additional studies are needed to better delineate specific surgical procedures and subpopulations of pediatric patients in which regional anesthesia may provide the most benefit.

Gabapentinoids

Children receiving gabapentinoids perioperatively have been shown to have fewer adverse reactions, decreased opioid consumption, and less anxiety, as well as improved pain scores. Gabapentin is increasingly being utilized for children with idiopathic scoliosis undergoing posterior spinal fusion, and there is some evidence for improving pain control and reducing opioid use. However, a recent systematic review found a paucity of data supporting its clinical use.¹⁴ Both gabapentin and pregabalin may further increase risks of respiratory depression, especially in synergy with opioids and benzodiazepines.

Opioids

Opioids should be used with caution in pediatric patients and are reserved primarily for the management of severe acute pain. The shortest duration of the lowest effective dose of opioids should be encouraged. Patient-controlled opioid analgesia (PCA) offers benefits when parenteral postoperative analgesia is indicated: It maximizes pain relief, minimizes risk of overdose, and improves psychological well-being through self-­administration of pain medicines. Basal-infusion PCA should not be routinely used because it is associated with nausea, vomiting, and respiratory depression without having superior analgesia compared with demand use only. Monitoring of side stream end-tidal capnography can readily detect respiratory depression, especially if opioids, benzodiazepines, gabapentinoids, and diphenhydramine are used concomitantly. Patient education regarding opioid use, side effects, safe storage, and disposal practices is imperative because significant amounts of opioids remain in households after completion of treatment for pain and because opioid diversion and accidental ingestions account for significant morbidity. Providers need to balance efficient pain management with opioid stewardship, complying with state and federal policies to limit harm related to opioid diversion.¹⁵

Nonpharmacological Modalities

The use of nonpharmacologic therapies, along with pharmacologic modalities, for perioperative pain management has been shown to decrease opioid use and opioid-related side effects. Trials of acupressure have demonstrated improvement in nausea and vomiting, sleep quality, and pain and anxiety scores. Nonpharmacologic treatments currently serve as a complementary approach for pain and anxiety management in the perioperative setting including acupuncture, acupressure, osteopathic manipulative treatment, massage, meditation, biofeedback, hypnotherapy, and physical/occupational, relaxation, cognitive-behavioral, chiropractic, music, and art therapies. The Joint Commission suggests consideration of such modalities by hospitals.

Amid the continued shift from fee-for-service toward value-based payment, policymakers such as the Centers for Medicare & Medicaid Services have initiated strategies to contain spending on episodes of care. This episode focus has led to nationwide implementation of payment models such as bundled payments, which hold hospitals accountable for quality and costs across procedure-­based (eg, coronary artery bypass surgery) and condition-­based (eg, congestive heart failure) episodes, which begin with hospitalization and encompass subsequent hospital and postdischarge care.

Simultaneously, Medicare has increased its emphasis on similarly designed episodes of care (eg, those spanning hospitalization and postdischarge care) using other strategies, such as public reporting and use of episode-based measures to evaluate hospital cost performance. In 2017, Medicare trialed the implementation of six Clinical Episode-Based Payment (CEBP) measures in the national Hospital Inpatient Quality Reporting Program in order to assess hospital and clinician spending on procedure and condition episodes.^1,2

CEBP measures reflect episode-specific spending, conveying “how expensive a hospital is” by capturing facility and professional payments for a given episode spanning between 3 days prior to hospitalization and 30 days following discharge. Given standard payment rates used in Medicare, the variation in episode spending reflects differences in quantity and type of services utilized within an episode. Medicare has specified episode-related services and designed CEBP measures via logic and definition rules informed by a combination of claims and procedures-based grouping, as well as by physician input. For example, the CEBP measure for cellulitis encompasses services related to diagnosing and treating the infection within the episode window, but not unrelated services such as eye exams for coexisting glaucoma. To increase clinical salience, CEBP measures are subdivided to reflect differing complexity when possible. For instance, cellulitis measures are divided into episodes with or without major complications or comorbidities and further subdivided into subtypes for episodes reflecting cellulitis in patients with diabetes, patients with decubitus ulcers, or neither.

CEBPs are similar to other spending measures used in payment programs, such as the Medicare Spending Per Beneficiary, but are more clinically relevant because their focus on episodes more closely reflects clinical practice. CEBPs and Medicare Spending Per Beneficiary have similar designs (eg, same episode windows) and purpose (eg, to capture the cost efficiency of hospital care).³ However, unlike CEBPs, Medicare Spending Per Beneficiary is a “global” measure that summarizes a hospital’s cost efficiency aggregated across all inpatient episodes rather than represent it based on specific conditions or procedures.⁴ The limitations of publicly reported global hospital measures—for instance, the poor correlation between hospital performance on distinct publicly reported quality measures⁵—highlight the potential utility of episode-specific spending measures such as CEBP.

Compared with episode-based payment models, initiatives such as CEBP measures have gone largely unstudied. However, they represent signals of Medicare’s growing commitment to addressing care episodes, tested without potentially tedious rulemaking required to change payment. In fact, publicly reported episode spending measures offer policymakers several interrelated benefits: the ability to rapidly evaluate performance at a large number of hospitals (eg, Medicare scaling up CEBP measures among all eligible hospitals nationwide), the option of leveraging publicly reported feedback to prompt clinical improvements (eg, by including CEBP measures in the Hospital Inpatient Quality Reporting Program), and the platform for developing and testing promising spending measures for subsequent use in formal payment models (eg, by using CEBP measures that possess large variation or cost-reduction opportunities in future bundled payment programs).

Despite these benefits, little is known about hospital performance on publicly reported episode-specific spending measures. We addressed this knowledge gap by providing what is, to our knowledge, the first nationwide description of hospital performance on such measures. We also evaluated which episode components accounted for spending variation in procedural vs condition episodes, examined whether CEBP measures can be used to effectively identify high- vs low-cost hospitals, and compared spending performance on CEBPs vs Medicare Spending Per Beneficiary.

Data and Study Sample

We utilized publicly available data from Hospital Compare, which include information about hospital-level CEBP and Medicare Spending Per Beneficiary performance for Medicare-­certified acute care hospitals nationwide.⁵ Our analysis evaluated the six CEBP measures tested by Medicare in 2017: three conditions (cellulitis, kidney/urinary tract infection [UTI], gastrointestinal hemorrhage) and three procedures (spinal fusion, cholecystectomy and common duct exploration, and aortic aneurysm repair). Per Medicare rules, CEBP measures are calculated only for hospitals with requisite volume for targeted conditions (minimum of 40 episodes) and procedures (minimum of 25 episodes) and are reported on Hospital Compare in risk-adjusted (eg, for age, hierarchical condition categories in alignment with existing Medicare methodology) and payment-­standardized form (ie, accounts for wage index, medical education, disproportionate share hospital payments) . Each CEBP encompasses episodes with or without major complications/comorbidities.

For each hospital, CEBP spending is reported as average total episode spending, as well as average spending on specific components. We grouped components into three groups: hospitalization, skilled nursing facility (SNF) use, and other (encompassing postdischarge readmissions, emergency department visits, and home health agency use), with a focus on SNF given existing evidence from episode-based payment models about the opportunity for savings from reduced SNF care. Hospital Compare also provides information about the national CEBP measure performance (ie, average spending for a given episode type among all eligible hospitals nationwide).

Hospital Groups

To evaluate hospitals’ CEBP performance for specific episode types, we categorized hospitals as either “below average spending” if their average episode spending was below the national average or “above average spending” if spending was above the national average. According to this approach, a hospital could have below average spending for some episodes but above average spending for others.

To compare hospitals across episode types simultaneously, we categorized hospitals as “low cost” if episode spending was below the national average for all applicable measures, “high cost” if episode spending was above the national average for all applicable measures, or “mixed cost” if episode spending was above the national average for some measures and below for others.

We also conducted sensitivity analyses using alternative hospital group definitions. For comparisons of specific episode types, we categorized hospitals as “high spending” (top quartile of average episode spending among eligible hospitals) or “other spending” (all others). For comparisons across all episode types, we focused on SNF care and categorized hospitals as “high SNF cost” (top quartile of episode spending attributed to SNF care) and “other SNF cost” (all others). We applied a similar approach to Medicare Spending Per Beneficiary, categorizing hospitals as either “low MSPB cost” if their episode spending was below the national average for Medicare Spending Per Beneficiary or “high MSPB cost” if not.

Statistical Analysis

We assessed variation by describing the distribution of total episode spending across eligible hospitals for each individual episode type, as well as the proportion of spending attributed to SNF care across all episode types. We reported the difference between the 10th and 90th percentile for each distribution to quantify variation. To evaluate how individual episode components contributed to overall spending variation, we used linear regression and applied analysis of variance to each episode component. Specifically, we regressed episode spending on each episode component (hospital, SNF, other) separately and used these results to generate predicted episode spending values for each hospital based on its value for each spending component. We then calculated the differen-ces (ie, residuals) between predicted and actual total episode spending values. We plotted residuals for each component, with lower residual plot variation (ie, a flatter curve) representing larger contribution of a spending component to overall spending variation.

Pearson correlation coefficients were used to assess within-­hospital CEBP correlation (ie, the extent to which performance was hospital specific). We evaluated if and how components of spending varied across hospitals by comparing spending groups (for individual episode types) and cost groups (for all episode types). To test the robustness of these categories, we conducted sensitivity analyses using high spending vs other spending groups (for individual episode types) and high SNF cost vs low SNF cost groups (for all episode types).

To assess concordance between CEBP and Medicare Spending Per Beneficiary, we cross tabulated hospital CEBP performance (high vs low vs mixed cost) and Medicare Spending Per Beneficiary performance (high vs low MSPB cost). This approached allowed us to quantify the number of hospitals that have concordant performance for both types of spending measures (ie, high cost or low cost on both) and the number with discordant performance (eg, high cost on one spending measure but low cost on the other). We used Pearson correlation coefficients to assess correlation between CEBP and Medicare Spending Per Beneficiary, with evaluation of CEBP performance in aggregate form (ie, hospitals’ average CEBP performance across all eligible episode types) and by individual episode types.

Chi-square and Kruskal-Wallis tests were used to compare categorical and continuous variables, respectively. To compare spending amounts, we evaluated the distribution of total episode spending (Appendix Figure 1) and used ordinary least squares regression with spending as the dependent variable and hospital group, episode components, and their interaction as independent variables. Because CEBP dollar amounts are reported through Hospital Compare on a risk-adjusted and payment-standardized basis, no additional adjustments were applied. Analyses were performed using SAS version 9.4 (SAS Institute; Cary, NC) and all tests of significance were two-tailed at alpha=0.05.

Of 3,129 hospitals, 1,778 achieved minimum thresholds and had CEBPs calculated for at least one of the six CEBP episode types.

Variation in CEBP Performance

For each episode type, spending varied across eligible hospitals (Appendix Figure 2). In particular, the difference between the 10th and 90th percentile values for cellulitis, kidney/UTI, and gastrointestinal hemorrhage were $2,873, $3,514, and $2,982, respectively. Differences were greater for procedural episodes of aortic aneurysm ($17,860), spinal fusion ($11,893), and cholecystectomy ($3,689). Evaluated across all episode types, the proportion of episode spending attributed to SNF care also varied across hospitals (Appendix Figure 3), with a difference of 24.7% between the 10th (4.5%) and 90th (29.2%) percentile values.

Residual plots demonstrated differences in which episode components accounted for variation in overall spending. For aortic aneurysm episodes, variation in the SNF episode component best explained variation in episode spending and thus had the lowest residual plot variation, followed by other and hospital components (Figure). Similar patterns were observed for spinal fusion and cholecystectomy episodes. In contrast, for cellulitis episodes, all three components had comparable residual-plot variation, which indicates that the variation in the components explained episode spending variation similarly (Figure)—a pattern reflected in kidney/UTI and gastrointestinal hemorrhage episodes.

Correlation in Performance on CEBP Measures

Across hospitals in our sample, within-hospital correlations were generally low (Appendix Table 1). In particular, correlations ranged from –0.079 (between performance on aortic aneurysm and kidney/UTI episodes) to 0.42 (between performance on kidney/UTI and cellulitis episodes), with a median correlation coefficient of 0.13. Within-hospital correlations ranged from 0.037 to 0.28 when considered between procedural episodes and from 0.33 to 0.42 when considered between condition episodes. When assessed among the subset of 1,294 hospitals eligible for at least two CEBP measures, correlations were very similar (ranging from –0.080 to 0.42). Additional analyses among hospitals with more CEBPs (eg, all six measures) yielded correlations that were similar in magnitude.

CEBP Performance by Hospital Groups

Overall spending on specific episode types varied across hospital groups (Table). Spending for aortic aneurysm episodes was $42,633 at hospitals with above average spending and $37,730 at those with below average spending, while spending for spinal fusion episodes was $39,231 at those with above average spending and $34,832 at those with below average spending. In comparison, spending at hospitals deemed above and below average spending for cellulitis episodes was $10,763 and $9,064, respectively, and $11,223 and $9,161 at hospitals deemed above and below average spending for kidney/UTI episodes, respectively.

Spending on specific episode components also differed by hospital group (Table). Though the magnitude of absolute spending amounts and differences varied by specific episode, hospitals with above average spending tended to spend more on SNF than did those with below average spending. For example, hospitals with above average spending for cellulitis episodes spent an average of $2,564 on SNF (24% of overall episode spending) vs $1,293 (14% of episode spending) among those with below average spending. Similarly, hospitals with above and below average spending for kidney/UTI episodes spent $4,068 (36% of episode spending) and $2,232 (24% of episode spending) on SNF, respectively (P < .001 for both episode types). Findings were qualitatively similar in sensitivity analyses (Appendix Table 2).

Among hospitals in our sample, we categorized 481 as high cost (27%), 452 as low cost (25%), and 845 as mixed cost (48%), with hospital groups distributed broadly nationwide (Appendix Figure 4). Evaluated on performance across all six episode types, hospital groups also demonstrated differences in spending by cost components (Table). In particular, spending in SNF ranged from 18.1% of overall episode spending among high-cost hospitals to 10.7% among mixed-cost hospitals and 9.2% among low-cost hospitals. Additionally, spending on hospitalization accounted for 83.3% of overall episode spending among low-cost hospitals, compared with 81.2% and 73.4% among mixed-cost and high-cost hospitals, respectively (P < .001). Comparisons were qualitatively similar in sensitivity analyses (Appendix Table 3).

Comparison of CEBP and Medicare Spending Per Beneficiary Performance

Correlation between Medicare Spending Per Beneficiary and aggregated CEBPs was 0.42 and, for individual episode types, ranged between 0.14 and 0.36 (Appendix Table 2). There was low concordance between hospital performance on CEBP and Medicare Spending Per Beneficiary. Across all eligible hospitals, only 16.3% (290/1778) had positive concordance between performance on the two measure types (ie, low cost for both), while 16.5% (293/1778) had negative concordance (ie, high cost for both). There was discordant performance in most instances (67.2%; 1195/1778), which reflecting favorable performance on one measure type but not the other.

To our knowledge, this study is the first to describe hospitals’ episode-specific spending performance nationwide. It demonstrated significant variation across hospitals driven by different episode components for different episode types. It also showed low correlation between individual episode spending measures and poor concordance between episode-specific and global hospital spending measures. Two practice and policy implications are noteworthy.

First, our findings corroborate and build upon evidence from bundled payment programs about the opportunity for hospitals to improve their cost efficiency. Findings from bundled payment evaluations of surgical episodes suggest that the major area for cost savings is in the reduction of institutional post-acute care use such as that of SNFs.^7-9 We demonstrated similar opportunity in a national sample of hospitals, finding that, for the three evaluated procedural CEBPs, SNF care accounted for more variation in overall episode spending than did other components. While variation may imply opportunity for greater efficiency and standardization, it is important to note that variation itself is not inherently problematic. Additional studies are needed to distinguish between warranted and unwarranted variation in procedural episodes, as well as identify strategies for reducing the latter.

Though bundled payment evaluations have predominantly emphasized procedural episodes, existing evidence suggests that participation in medical condition bundles has not been associated with cost savings or utilization changes.^7-15 Findings from our analysis of variance—that there appear to be smaller variation-reduction opportunities for condition episodes than for procedural episodes—offer insight into this issue. Existing episodes are initiated by hospitalization and extend into the postacute period, a design that may not afford substantial post-acute care savings opportunities for condition episodes. This is an important insight as policymakers consider how to best design condition-based episodes in the future (eg, whether to use non–hospital based episode triggers). Future work should evaluate whether our findings reflect inherent differences between condition and procedural episodes¹⁶ or whether interventions can still optimize SNF care for these episodes despite smaller variation.

Second, our results highlight the potential limitations of global performance measures such as Medicare Spending Per Beneficiary. As a general measure of hospital spending, Medicare Spending Per Beneficiary is based on the premise that hospitals can be categorized as high or low cost with consideration of all inpatient episodic care. However, our analyses suggest that hospitals may be high cost for certain episodes and low cost for others—a fact highlighted by the low correlation and high discordance observed between hospital CEBP and Medicare Spending Per Beneficiary performance. Because overarching measures may miss spending differen-ces related to underlying clinical scenarios, episode-specific spending measures would provide important perspective and complements to global measures for assessing hospital cost performance, particularly in an era of value-based payments. Policymakers should consider prioritizing the development and implementation of such measures.

Our study has limitations. First, it is descriptive in nature, and future work should evaluate the association between episode-­specific spending measure performance and clinical and quality outcomes. Second, we evaluated all CEBP-eligible hospitals nationwide to provide a broad view of episode-specific spending. However, future studies should assess performance among hospital subtypes, such as vertically integrated or safety-­net organizations, because they may be more or less able to perform on these spending measures. Third, though findings may not be generalizable to other clinical episodes, our results were qualitatively consistent across episode types and broadly consistent with evidence from episode-based payment models. Fourth, we analyzed cost from the perspective of utilization and did not incorporate price considerations, which may be more relevant for commercial insurers than it is for Medicare.

Nonetheless, the emergence of CEBPs reflects the ongoing shift in policymaker attention toward episode-specific spending. In particular, though further scale or use of CEBP measures has been put on hold amid other payment reform changes, their nationwide implementation in 2017 signals Medicare’s broad interest in evaluating all hospitals on episode-specific spending efficiency, in addition to other facets of spending, quality, safety, and patient experience. Importantly, such efforts complement other ongoing nationwide initiatives for emphasizing episode spending, such as use of episode-based cost measures within the Merit-Based Incentive Payment System¹⁷ to score clinicians and groups in part based on their episode-specific spending efficiency. Insight about episode spending performance could help hospitals prepare for environments with increasing focus on episode spending and as policymakers incorporate this perspective into quality and value-­based payment policies.

Amid the continued shift from fee-for-service toward value-based payment, policymakers such as the Centers for Medicare & Medicaid Services have initiated strategies to contain spending on episodes of care. This episode focus has led to nationwide implementation of payment models such as bundled payments, which hold hospitals accountable for quality and costs across procedure-­based (eg, coronary artery bypass surgery) and condition-­based (eg, congestive heart failure) episodes, which begin with hospitalization and encompass subsequent hospital and postdischarge care.

Simultaneously, Medicare has increased its emphasis on similarly designed episodes of care (eg, those spanning hospitalization and postdischarge care) using other strategies, such as public reporting and use of episode-based measures to evaluate hospital cost performance. In 2017, Medicare trialed the implementation of six Clinical Episode-Based Payment (CEBP) measures in the national Hospital Inpatient Quality Reporting Program in order to assess hospital and clinician spending on procedure and condition episodes.^1,2

CEBP measures reflect episode-specific spending, conveying “how expensive a hospital is” by capturing facility and professional payments for a given episode spanning between 3 days prior to hospitalization and 30 days following discharge. Given standard payment rates used in Medicare, the variation in episode spending reflects differences in quantity and type of services utilized within an episode. Medicare has specified episode-related services and designed CEBP measures via logic and definition rules informed by a combination of claims and procedures-based grouping, as well as by physician input. For example, the CEBP measure for cellulitis encompasses services related to diagnosing and treating the infection within the episode window, but not unrelated services such as eye exams for coexisting glaucoma. To increase clinical salience, CEBP measures are subdivided to reflect differing complexity when possible. For instance, cellulitis measures are divided into episodes with or without major complications or comorbidities and further subdivided into subtypes for episodes reflecting cellulitis in patients with diabetes, patients with decubitus ulcers, or neither.

CEBPs are similar to other spending measures used in payment programs, such as the Medicare Spending Per Beneficiary, but are more clinically relevant because their focus on episodes more closely reflects clinical practice. CEBPs and Medicare Spending Per Beneficiary have similar designs (eg, same episode windows) and purpose (eg, to capture the cost efficiency of hospital care).³ However, unlike CEBPs, Medicare Spending Per Beneficiary is a “global” measure that summarizes a hospital’s cost efficiency aggregated across all inpatient episodes rather than represent it based on specific conditions or procedures.⁴ The limitations of publicly reported global hospital measures—for instance, the poor correlation between hospital performance on distinct publicly reported quality measures⁵—highlight the potential utility of episode-specific spending measures such as CEBP.

Compared with episode-based payment models, initiatives such as CEBP measures have gone largely unstudied. However, they represent signals of Medicare’s growing commitment to addressing care episodes, tested without potentially tedious rulemaking required to change payment. In fact, publicly reported episode spending measures offer policymakers several interrelated benefits: the ability to rapidly evaluate performance at a large number of hospitals (eg, Medicare scaling up CEBP measures among all eligible hospitals nationwide), the option of leveraging publicly reported feedback to prompt clinical improvements (eg, by including CEBP measures in the Hospital Inpatient Quality Reporting Program), and the platform for developing and testing promising spending measures for subsequent use in formal payment models (eg, by using CEBP measures that possess large variation or cost-reduction opportunities in future bundled payment programs).

Despite these benefits, little is known about hospital performance on publicly reported episode-specific spending measures. We addressed this knowledge gap by providing what is, to our knowledge, the first nationwide description of hospital performance on such measures. We also evaluated which episode components accounted for spending variation in procedural vs condition episodes, examined whether CEBP measures can be used to effectively identify high- vs low-cost hospitals, and compared spending performance on CEBPs vs Medicare Spending Per Beneficiary.

Data and Study Sample

We utilized publicly available data from Hospital Compare, which include information about hospital-level CEBP and Medicare Spending Per Beneficiary performance for Medicare-­certified acute care hospitals nationwide.⁵ Our analysis evaluated the six CEBP measures tested by Medicare in 2017: three conditions (cellulitis, kidney/urinary tract infection [UTI], gastrointestinal hemorrhage) and three procedures (spinal fusion, cholecystectomy and common duct exploration, and aortic aneurysm repair). Per Medicare rules, CEBP measures are calculated only for hospitals with requisite volume for targeted conditions (minimum of 40 episodes) and procedures (minimum of 25 episodes) and are reported on Hospital Compare in risk-adjusted (eg, for age, hierarchical condition categories in alignment with existing Medicare methodology) and payment-­standardized form (ie, accounts for wage index, medical education, disproportionate share hospital payments) . Each CEBP encompasses episodes with or without major complications/comorbidities.

For each hospital, CEBP spending is reported as average total episode spending, as well as average spending on specific components. We grouped components into three groups: hospitalization, skilled nursing facility (SNF) use, and other (encompassing postdischarge readmissions, emergency department visits, and home health agency use), with a focus on SNF given existing evidence from episode-based payment models about the opportunity for savings from reduced SNF care. Hospital Compare also provides information about the national CEBP measure performance (ie, average spending for a given episode type among all eligible hospitals nationwide).

Hospital Groups

To evaluate hospitals’ CEBP performance for specific episode types, we categorized hospitals as either “below average spending” if their average episode spending was below the national average or “above average spending” if spending was above the national average. According to this approach, a hospital could have below average spending for some episodes but above average spending for others.

To compare hospitals across episode types simultaneously, we categorized hospitals as “low cost” if episode spending was below the national average for all applicable measures, “high cost” if episode spending was above the national average for all applicable measures, or “mixed cost” if episode spending was above the national average for some measures and below for others.

We also conducted sensitivity analyses using alternative hospital group definitions. For comparisons of specific episode types, we categorized hospitals as “high spending” (top quartile of average episode spending among eligible hospitals) or “other spending” (all others). For comparisons across all episode types, we focused on SNF care and categorized hospitals as “high SNF cost” (top quartile of episode spending attributed to SNF care) and “other SNF cost” (all others). We applied a similar approach to Medicare Spending Per Beneficiary, categorizing hospitals as either “low MSPB cost” if their episode spending was below the national average for Medicare Spending Per Beneficiary or “high MSPB cost” if not.

Statistical Analysis

We assessed variation by describing the distribution of total episode spending across eligible hospitals for each individual episode type, as well as the proportion of spending attributed to SNF care across all episode types. We reported the difference between the 10th and 90th percentile for each distribution to quantify variation. To evaluate how individual episode components contributed to overall spending variation, we used linear regression and applied analysis of variance to each episode component. Specifically, we regressed episode spending on each episode component (hospital, SNF, other) separately and used these results to generate predicted episode spending values for each hospital based on its value for each spending component. We then calculated the differen-ces (ie, residuals) between predicted and actual total episode spending values. We plotted residuals for each component, with lower residual plot variation (ie, a flatter curve) representing larger contribution of a spending component to overall spending variation.

Pearson correlation coefficients were used to assess within-­hospital CEBP correlation (ie, the extent to which performance was hospital specific). We evaluated if and how components of spending varied across hospitals by comparing spending groups (for individual episode types) and cost groups (for all episode types). To test the robustness of these categories, we conducted sensitivity analyses using high spending vs other spending groups (for individual episode types) and high SNF cost vs low SNF cost groups (for all episode types).

To assess concordance between CEBP and Medicare Spending Per Beneficiary, we cross tabulated hospital CEBP performance (high vs low vs mixed cost) and Medicare Spending Per Beneficiary performance (high vs low MSPB cost). This approached allowed us to quantify the number of hospitals that have concordant performance for both types of spending measures (ie, high cost or low cost on both) and the number with discordant performance (eg, high cost on one spending measure but low cost on the other). We used Pearson correlation coefficients to assess correlation between CEBP and Medicare Spending Per Beneficiary, with evaluation of CEBP performance in aggregate form (ie, hospitals’ average CEBP performance across all eligible episode types) and by individual episode types.

Chi-square and Kruskal-Wallis tests were used to compare categorical and continuous variables, respectively. To compare spending amounts, we evaluated the distribution of total episode spending (Appendix Figure 1) and used ordinary least squares regression with spending as the dependent variable and hospital group, episode components, and their interaction as independent variables. Because CEBP dollar amounts are reported through Hospital Compare on a risk-adjusted and payment-standardized basis, no additional adjustments were applied. Analyses were performed using SAS version 9.4 (SAS Institute; Cary, NC) and all tests of significance were two-tailed at alpha=0.05.

Of 3,129 hospitals, 1,778 achieved minimum thresholds and had CEBPs calculated for at least one of the six CEBP episode types.

Variation in CEBP Performance

For each episode type, spending varied across eligible hospitals (Appendix Figure 2). In particular, the difference between the 10th and 90th percentile values for cellulitis, kidney/UTI, and gastrointestinal hemorrhage were $2,873, $3,514, and $2,982, respectively. Differences were greater for procedural episodes of aortic aneurysm ($17,860), spinal fusion ($11,893), and cholecystectomy ($3,689). Evaluated across all episode types, the proportion of episode spending attributed to SNF care also varied across hospitals (Appendix Figure 3), with a difference of 24.7% between the 10th (4.5%) and 90th (29.2%) percentile values.

Residual plots demonstrated differences in which episode components accounted for variation in overall spending. For aortic aneurysm episodes, variation in the SNF episode component best explained variation in episode spending and thus had the lowest residual plot variation, followed by other and hospital components (Figure). Similar patterns were observed for spinal fusion and cholecystectomy episodes. In contrast, for cellulitis episodes, all three components had comparable residual-plot variation, which indicates that the variation in the components explained episode spending variation similarly (Figure)—a pattern reflected in kidney/UTI and gastrointestinal hemorrhage episodes.

Correlation in Performance on CEBP Measures

Across hospitals in our sample, within-hospital correlations were generally low (Appendix Table 1). In particular, correlations ranged from –0.079 (between performance on aortic aneurysm and kidney/UTI episodes) to 0.42 (between performance on kidney/UTI and cellulitis episodes), with a median correlation coefficient of 0.13. Within-hospital correlations ranged from 0.037 to 0.28 when considered between procedural episodes and from 0.33 to 0.42 when considered between condition episodes. When assessed among the subset of 1,294 hospitals eligible for at least two CEBP measures, correlations were very similar (ranging from –0.080 to 0.42). Additional analyses among hospitals with more CEBPs (eg, all six measures) yielded correlations that were similar in magnitude.

CEBP Performance by Hospital Groups

Overall spending on specific episode types varied across hospital groups (Table). Spending for aortic aneurysm episodes was $42,633 at hospitals with above average spending and $37,730 at those with below average spending, while spending for spinal fusion episodes was $39,231 at those with above average spending and $34,832 at those with below average spending. In comparison, spending at hospitals deemed above and below average spending for cellulitis episodes was $10,763 and $9,064, respectively, and $11,223 and $9,161 at hospitals deemed above and below average spending for kidney/UTI episodes, respectively.

Spending on specific episode components also differed by hospital group (Table). Though the magnitude of absolute spending amounts and differences varied by specific episode, hospitals with above average spending tended to spend more on SNF than did those with below average spending. For example, hospitals with above average spending for cellulitis episodes spent an average of $2,564 on SNF (24% of overall episode spending) vs $1,293 (14% of episode spending) among those with below average spending. Similarly, hospitals with above and below average spending for kidney/UTI episodes spent $4,068 (36% of episode spending) and $2,232 (24% of episode spending) on SNF, respectively (P < .001 for both episode types). Findings were qualitatively similar in sensitivity analyses (Appendix Table 2).

Among hospitals in our sample, we categorized 481 as high cost (27%), 452 as low cost (25%), and 845 as mixed cost (48%), with hospital groups distributed broadly nationwide (Appendix Figure 4). Evaluated on performance across all six episode types, hospital groups also demonstrated differences in spending by cost components (Table). In particular, spending in SNF ranged from 18.1% of overall episode spending among high-cost hospitals to 10.7% among mixed-cost hospitals and 9.2% among low-cost hospitals. Additionally, spending on hospitalization accounted for 83.3% of overall episode spending among low-cost hospitals, compared with 81.2% and 73.4% among mixed-cost and high-cost hospitals, respectively (P < .001). Comparisons were qualitatively similar in sensitivity analyses (Appendix Table 3).

Comparison of CEBP and Medicare Spending Per Beneficiary Performance

Correlation between Medicare Spending Per Beneficiary and aggregated CEBPs was 0.42 and, for individual episode types, ranged between 0.14 and 0.36 (Appendix Table 2). There was low concordance between hospital performance on CEBP and Medicare Spending Per Beneficiary. Across all eligible hospitals, only 16.3% (290/1778) had positive concordance between performance on the two measure types (ie, low cost for both), while 16.5% (293/1778) had negative concordance (ie, high cost for both). There was discordant performance in most instances (67.2%; 1195/1778), which reflecting favorable performance on one measure type but not the other.

To our knowledge, this study is the first to describe hospitals’ episode-specific spending performance nationwide. It demonstrated significant variation across hospitals driven by different episode components for different episode types. It also showed low correlation between individual episode spending measures and poor concordance between episode-specific and global hospital spending measures. Two practice and policy implications are noteworthy.

First, our findings corroborate and build upon evidence from bundled payment programs about the opportunity for hospitals to improve their cost efficiency. Findings from bundled payment evaluations of surgical episodes suggest that the major area for cost savings is in the reduction of institutional post-acute care use such as that of SNFs.^7-9 We demonstrated similar opportunity in a national sample of hospitals, finding that, for the three evaluated procedural CEBPs, SNF care accounted for more variation in overall episode spending than did other components. While variation may imply opportunity for greater efficiency and standardization, it is important to note that variation itself is not inherently problematic. Additional studies are needed to distinguish between warranted and unwarranted variation in procedural episodes, as well as identify strategies for reducing the latter.

Though bundled payment evaluations have predominantly emphasized procedural episodes, existing evidence suggests that participation in medical condition bundles has not been associated with cost savings or utilization changes.^7-15 Findings from our analysis of variance—that there appear to be smaller variation-reduction opportunities for condition episodes than for procedural episodes—offer insight into this issue. Existing episodes are initiated by hospitalization and extend into the postacute period, a design that may not afford substantial post-acute care savings opportunities for condition episodes. This is an important insight as policymakers consider how to best design condition-based episodes in the future (eg, whether to use non–hospital based episode triggers). Future work should evaluate whether our findings reflect inherent differences between condition and procedural episodes¹⁶ or whether interventions can still optimize SNF care for these episodes despite smaller variation.

Second, our results highlight the potential limitations of global performance measures such as Medicare Spending Per Beneficiary. As a general measure of hospital spending, Medicare Spending Per Beneficiary is based on the premise that hospitals can be categorized as high or low cost with consideration of all inpatient episodic care. However, our analyses suggest that hospitals may be high cost for certain episodes and low cost for others—a fact highlighted by the low correlation and high discordance observed between hospital CEBP and Medicare Spending Per Beneficiary performance. Because overarching measures may miss spending differen-ces related to underlying clinical scenarios, episode-specific spending measures would provide important perspective and complements to global measures for assessing hospital cost performance, particularly in an era of value-based payments. Policymakers should consider prioritizing the development and implementation of such measures.

Our study has limitations. First, it is descriptive in nature, and future work should evaluate the association between episode-­specific spending measure performance and clinical and quality outcomes. Second, we evaluated all CEBP-eligible hospitals nationwide to provide a broad view of episode-specific spending. However, future studies should assess performance among hospital subtypes, such as vertically integrated or safety-­net organizations, because they may be more or less able to perform on these spending measures. Third, though findings may not be generalizable to other clinical episodes, our results were qualitatively consistent across episode types and broadly consistent with evidence from episode-based payment models. Fourth, we analyzed cost from the perspective of utilization and did not incorporate price considerations, which may be more relevant for commercial insurers than it is for Medicare.

Nonetheless, the emergence of CEBPs reflects the ongoing shift in policymaker attention toward episode-specific spending. In particular, though further scale or use of CEBP measures has been put on hold amid other payment reform changes, their nationwide implementation in 2017 signals Medicare’s broad interest in evaluating all hospitals on episode-specific spending efficiency, in addition to other facets of spending, quality, safety, and patient experience. Importantly, such efforts complement other ongoing nationwide initiatives for emphasizing episode spending, such as use of episode-based cost measures within the Merit-Based Incentive Payment System¹⁷ to score clinicians and groups in part based on their episode-specific spending efficiency. Insight about episode spending performance could help hospitals prepare for environments with increasing focus on episode spending and as policymakers incorporate this perspective into quality and value-­based payment policies.

Amid the continued shift from fee-for-service toward value-based payment, policymakers such as the Centers for Medicare & Medicaid Services have initiated strategies to contain spending on episodes of care. This episode focus has led to nationwide implementation of payment models such as bundled payments, which hold hospitals accountable for quality and costs across procedure-­based (eg, coronary artery bypass surgery) and condition-­based (eg, congestive heart failure) episodes, which begin with hospitalization and encompass subsequent hospital and postdischarge care.

Simultaneously, Medicare has increased its emphasis on similarly designed episodes of care (eg, those spanning hospitalization and postdischarge care) using other strategies, such as public reporting and use of episode-based measures to evaluate hospital cost performance. In 2017, Medicare trialed the implementation of six Clinical Episode-Based Payment (CEBP) measures in the national Hospital Inpatient Quality Reporting Program in order to assess hospital and clinician spending on procedure and condition episodes.^1,2

CEBP measures reflect episode-specific spending, conveying “how expensive a hospital is” by capturing facility and professional payments for a given episode spanning between 3 days prior to hospitalization and 30 days following discharge. Given standard payment rates used in Medicare, the variation in episode spending reflects differences in quantity and type of services utilized within an episode. Medicare has specified episode-related services and designed CEBP measures via logic and definition rules informed by a combination of claims and procedures-based grouping, as well as by physician input. For example, the CEBP measure for cellulitis encompasses services related to diagnosing and treating the infection within the episode window, but not unrelated services such as eye exams for coexisting glaucoma. To increase clinical salience, CEBP measures are subdivided to reflect differing complexity when possible. For instance, cellulitis measures are divided into episodes with or without major complications or comorbidities and further subdivided into subtypes for episodes reflecting cellulitis in patients with diabetes, patients with decubitus ulcers, or neither.

CEBPs are similar to other spending measures used in payment programs, such as the Medicare Spending Per Beneficiary, but are more clinically relevant because their focus on episodes more closely reflects clinical practice. CEBPs and Medicare Spending Per Beneficiary have similar designs (eg, same episode windows) and purpose (eg, to capture the cost efficiency of hospital care).³ However, unlike CEBPs, Medicare Spending Per Beneficiary is a “global” measure that summarizes a hospital’s cost efficiency aggregated across all inpatient episodes rather than represent it based on specific conditions or procedures.⁴ The limitations of publicly reported global hospital measures—for instance, the poor correlation between hospital performance on distinct publicly reported quality measures⁵—highlight the potential utility of episode-specific spending measures such as CEBP.

Compared with episode-based payment models, initiatives such as CEBP measures have gone largely unstudied. However, they represent signals of Medicare’s growing commitment to addressing care episodes, tested without potentially tedious rulemaking required to change payment. In fact, publicly reported episode spending measures offer policymakers several interrelated benefits: the ability to rapidly evaluate performance at a large number of hospitals (eg, Medicare scaling up CEBP measures among all eligible hospitals nationwide), the option of leveraging publicly reported feedback to prompt clinical improvements (eg, by including CEBP measures in the Hospital Inpatient Quality Reporting Program), and the platform for developing and testing promising spending measures for subsequent use in formal payment models (eg, by using CEBP measures that possess large variation or cost-reduction opportunities in future bundled payment programs).

Despite these benefits, little is known about hospital performance on publicly reported episode-specific spending measures. We addressed this knowledge gap by providing what is, to our knowledge, the first nationwide description of hospital performance on such measures. We also evaluated which episode components accounted for spending variation in procedural vs condition episodes, examined whether CEBP measures can be used to effectively identify high- vs low-cost hospitals, and compared spending performance on CEBPs vs Medicare Spending Per Beneficiary.

Data and Study Sample

We utilized publicly available data from Hospital Compare, which include information about hospital-level CEBP and Medicare Spending Per Beneficiary performance for Medicare-­certified acute care hospitals nationwide.⁵ Our analysis evaluated the six CEBP measures tested by Medicare in 2017: three conditions (cellulitis, kidney/urinary tract infection [UTI], gastrointestinal hemorrhage) and three procedures (spinal fusion, cholecystectomy and common duct exploration, and aortic aneurysm repair). Per Medicare rules, CEBP measures are calculated only for hospitals with requisite volume for targeted conditions (minimum of 40 episodes) and procedures (minimum of 25 episodes) and are reported on Hospital Compare in risk-adjusted (eg, for age, hierarchical condition categories in alignment with existing Medicare methodology) and payment-­standardized form (ie, accounts for wage index, medical education, disproportionate share hospital payments) . Each CEBP encompasses episodes with or without major complications/comorbidities.

For each hospital, CEBP spending is reported as average total episode spending, as well as average spending on specific components. We grouped components into three groups: hospitalization, skilled nursing facility (SNF) use, and other (encompassing postdischarge readmissions, emergency department visits, and home health agency use), with a focus on SNF given existing evidence from episode-based payment models about the opportunity for savings from reduced SNF care. Hospital Compare also provides information about the national CEBP measure performance (ie, average spending for a given episode type among all eligible hospitals nationwide).

Hospital Groups

To evaluate hospitals’ CEBP performance for specific episode types, we categorized hospitals as either “below average spending” if their average episode spending was below the national average or “above average spending” if spending was above the national average. According to this approach, a hospital could have below average spending for some episodes but above average spending for others.

To compare hospitals across episode types simultaneously, we categorized hospitals as “low cost” if episode spending was below the national average for all applicable measures, “high cost” if episode spending was above the national average for all applicable measures, or “mixed cost” if episode spending was above the national average for some measures and below for others.

We also conducted sensitivity analyses using alternative hospital group definitions. For comparisons of specific episode types, we categorized hospitals as “high spending” (top quartile of average episode spending among eligible hospitals) or “other spending” (all others). For comparisons across all episode types, we focused on SNF care and categorized hospitals as “high SNF cost” (top quartile of episode spending attributed to SNF care) and “other SNF cost” (all others). We applied a similar approach to Medicare Spending Per Beneficiary, categorizing hospitals as either “low MSPB cost” if their episode spending was below the national average for Medicare Spending Per Beneficiary or “high MSPB cost” if not.

Statistical Analysis

We assessed variation by describing the distribution of total episode spending across eligible hospitals for each individual episode type, as well as the proportion of spending attributed to SNF care across all episode types. We reported the difference between the 10th and 90th percentile for each distribution to quantify variation. To evaluate how individual episode components contributed to overall spending variation, we used linear regression and applied analysis of variance to each episode component. Specifically, we regressed episode spending on each episode component (hospital, SNF, other) separately and used these results to generate predicted episode spending values for each hospital based on its value for each spending component. We then calculated the differen-ces (ie, residuals) between predicted and actual total episode spending values. We plotted residuals for each component, with lower residual plot variation (ie, a flatter curve) representing larger contribution of a spending component to overall spending variation.

Pearson correlation coefficients were used to assess within-­hospital CEBP correlation (ie, the extent to which performance was hospital specific). We evaluated if and how components of spending varied across hospitals by comparing spending groups (for individual episode types) and cost groups (for all episode types). To test the robustness of these categories, we conducted sensitivity analyses using high spending vs other spending groups (for individual episode types) and high SNF cost vs low SNF cost groups (for all episode types).

To assess concordance between CEBP and Medicare Spending Per Beneficiary, we cross tabulated hospital CEBP performance (high vs low vs mixed cost) and Medicare Spending Per Beneficiary performance (high vs low MSPB cost). This approached allowed us to quantify the number of hospitals that have concordant performance for both types of spending measures (ie, high cost or low cost on both) and the number with discordant performance (eg, high cost on one spending measure but low cost on the other). We used Pearson correlation coefficients to assess correlation between CEBP and Medicare Spending Per Beneficiary, with evaluation of CEBP performance in aggregate form (ie, hospitals’ average CEBP performance across all eligible episode types) and by individual episode types.

Chi-square and Kruskal-Wallis tests were used to compare categorical and continuous variables, respectively. To compare spending amounts, we evaluated the distribution of total episode spending (Appendix Figure 1) and used ordinary least squares regression with spending as the dependent variable and hospital group, episode components, and their interaction as independent variables. Because CEBP dollar amounts are reported through Hospital Compare on a risk-adjusted and payment-standardized basis, no additional adjustments were applied. Analyses were performed using SAS version 9.4 (SAS Institute; Cary, NC) and all tests of significance were two-tailed at alpha=0.05.

Of 3,129 hospitals, 1,778 achieved minimum thresholds and had CEBPs calculated for at least one of the six CEBP episode types.

Variation in CEBP Performance

For each episode type, spending varied across eligible hospitals (Appendix Figure 2). In particular, the difference between the 10th and 90th percentile values for cellulitis, kidney/UTI, and gastrointestinal hemorrhage were $2,873, $3,514, and $2,982, respectively. Differences were greater for procedural episodes of aortic aneurysm ($17,860), spinal fusion ($11,893), and cholecystectomy ($3,689). Evaluated across all episode types, the proportion of episode spending attributed to SNF care also varied across hospitals (Appendix Figure 3), with a difference of 24.7% between the 10th (4.5%) and 90th (29.2%) percentile values.

Residual plots demonstrated differences in which episode components accounted for variation in overall spending. For aortic aneurysm episodes, variation in the SNF episode component best explained variation in episode spending and thus had the lowest residual plot variation, followed by other and hospital components (Figure). Similar patterns were observed for spinal fusion and cholecystectomy episodes. In contrast, for cellulitis episodes, all three components had comparable residual-plot variation, which indicates that the variation in the components explained episode spending variation similarly (Figure)—a pattern reflected in kidney/UTI and gastrointestinal hemorrhage episodes.

Correlation in Performance on CEBP Measures

Across hospitals in our sample, within-hospital correlations were generally low (Appendix Table 1). In particular, correlations ranged from –0.079 (between performance on aortic aneurysm and kidney/UTI episodes) to 0.42 (between performance on kidney/UTI and cellulitis episodes), with a median correlation coefficient of 0.13. Within-hospital correlations ranged from 0.037 to 0.28 when considered between procedural episodes and from 0.33 to 0.42 when considered between condition episodes. When assessed among the subset of 1,294 hospitals eligible for at least two CEBP measures, correlations were very similar (ranging from –0.080 to 0.42). Additional analyses among hospitals with more CEBPs (eg, all six measures) yielded correlations that were similar in magnitude.

CEBP Performance by Hospital Groups

Overall spending on specific episode types varied across hospital groups (Table). Spending for aortic aneurysm episodes was $42,633 at hospitals with above average spending and $37,730 at those with below average spending, while spending for spinal fusion episodes was $39,231 at those with above average spending and $34,832 at those with below average spending. In comparison, spending at hospitals deemed above and below average spending for cellulitis episodes was $10,763 and $9,064, respectively, and $11,223 and $9,161 at hospitals deemed above and below average spending for kidney/UTI episodes, respectively.

Spending on specific episode components also differed by hospital group (Table). Though the magnitude of absolute spending amounts and differences varied by specific episode, hospitals with above average spending tended to spend more on SNF than did those with below average spending. For example, hospitals with above average spending for cellulitis episodes spent an average of $2,564 on SNF (24% of overall episode spending) vs $1,293 (14% of episode spending) among those with below average spending. Similarly, hospitals with above and below average spending for kidney/UTI episodes spent $4,068 (36% of episode spending) and $2,232 (24% of episode spending) on SNF, respectively (P < .001 for both episode types). Findings were qualitatively similar in sensitivity analyses (Appendix Table 2).

Among hospitals in our sample, we categorized 481 as high cost (27%), 452 as low cost (25%), and 845 as mixed cost (48%), with hospital groups distributed broadly nationwide (Appendix Figure 4). Evaluated on performance across all six episode types, hospital groups also demonstrated differences in spending by cost components (Table). In particular, spending in SNF ranged from 18.1% of overall episode spending among high-cost hospitals to 10.7% among mixed-cost hospitals and 9.2% among low-cost hospitals. Additionally, spending on hospitalization accounted for 83.3% of overall episode spending among low-cost hospitals, compared with 81.2% and 73.4% among mixed-cost and high-cost hospitals, respectively (P < .001). Comparisons were qualitatively similar in sensitivity analyses (Appendix Table 3).

Comparison of CEBP and Medicare Spending Per Beneficiary Performance

Correlation between Medicare Spending Per Beneficiary and aggregated CEBPs was 0.42 and, for individual episode types, ranged between 0.14 and 0.36 (Appendix Table 2). There was low concordance between hospital performance on CEBP and Medicare Spending Per Beneficiary. Across all eligible hospitals, only 16.3% (290/1778) had positive concordance between performance on the two measure types (ie, low cost for both), while 16.5% (293/1778) had negative concordance (ie, high cost for both). There was discordant performance in most instances (67.2%; 1195/1778), which reflecting favorable performance on one measure type but not the other.

To our knowledge, this study is the first to describe hospitals’ episode-specific spending performance nationwide. It demonstrated significant variation across hospitals driven by different episode components for different episode types. It also showed low correlation between individual episode spending measures and poor concordance between episode-specific and global hospital spending measures. Two practice and policy implications are noteworthy.

First, our findings corroborate and build upon evidence from bundled payment programs about the opportunity for hospitals to improve their cost efficiency. Findings from bundled payment evaluations of surgical episodes suggest that the major area for cost savings is in the reduction of institutional post-acute care use such as that of SNFs.^7-9 We demonstrated similar opportunity in a national sample of hospitals, finding that, for the three evaluated procedural CEBPs, SNF care accounted for more variation in overall episode spending than did other components. While variation may imply opportunity for greater efficiency and standardization, it is important to note that variation itself is not inherently problematic. Additional studies are needed to distinguish between warranted and unwarranted variation in procedural episodes, as well as identify strategies for reducing the latter.

Though bundled payment evaluations have predominantly emphasized procedural episodes, existing evidence suggests that participation in medical condition bundles has not been associated with cost savings or utilization changes.^7-15 Findings from our analysis of variance—that there appear to be smaller variation-reduction opportunities for condition episodes than for procedural episodes—offer insight into this issue. Existing episodes are initiated by hospitalization and extend into the postacute period, a design that may not afford substantial post-acute care savings opportunities for condition episodes. This is an important insight as policymakers consider how to best design condition-based episodes in the future (eg, whether to use non–hospital based episode triggers). Future work should evaluate whether our findings reflect inherent differences between condition and procedural episodes¹⁶ or whether interventions can still optimize SNF care for these episodes despite smaller variation.

Second, our results highlight the potential limitations of global performance measures such as Medicare Spending Per Beneficiary. As a general measure of hospital spending, Medicare Spending Per Beneficiary is based on the premise that hospitals can be categorized as high or low cost with consideration of all inpatient episodic care. However, our analyses suggest that hospitals may be high cost for certain episodes and low cost for others—a fact highlighted by the low correlation and high discordance observed between hospital CEBP and Medicare Spending Per Beneficiary performance. Because overarching measures may miss spending differen-ces related to underlying clinical scenarios, episode-specific spending measures would provide important perspective and complements to global measures for assessing hospital cost performance, particularly in an era of value-based payments. Policymakers should consider prioritizing the development and implementation of such measures.

Our study has limitations. First, it is descriptive in nature, and future work should evaluate the association between episode-­specific spending measure performance and clinical and quality outcomes. Second, we evaluated all CEBP-eligible hospitals nationwide to provide a broad view of episode-specific spending. However, future studies should assess performance among hospital subtypes, such as vertically integrated or safety-­net organizations, because they may be more or less able to perform on these spending measures. Third, though findings may not be generalizable to other clinical episodes, our results were qualitatively consistent across episode types and broadly consistent with evidence from episode-based payment models. Fourth, we analyzed cost from the perspective of utilization and did not incorporate price considerations, which may be more relevant for commercial insurers than it is for Medicare.

Nonetheless, the emergence of CEBPs reflects the ongoing shift in policymaker attention toward episode-specific spending. In particular, though further scale or use of CEBP measures has been put on hold amid other payment reform changes, their nationwide implementation in 2017 signals Medicare’s broad interest in evaluating all hospitals on episode-specific spending efficiency, in addition to other facets of spending, quality, safety, and patient experience. Importantly, such efforts complement other ongoing nationwide initiatives for emphasizing episode spending, such as use of episode-based cost measures within the Merit-Based Incentive Payment System¹⁷ to score clinicians and groups in part based on their episode-specific spending efficiency. Insight about episode spending performance could help hospitals prepare for environments with increasing focus on episode spending and as policymakers incorporate this perspective into quality and value-­based payment policies.

In 1996, internists Robert Wachter, MD, and Lee Goldman, MD, MPH, coined the term “hospitalist” and predicted an “emerging role in the American health care system.”¹ Pediatrics was not far behind: In 1999, Dr Wachter joined Paul Bellet, MD, in authoring an article describing the movement within pediatrics.² An accompanying editorial, coauthored by a pediatric hospitalist and an office-based practitioner, attempted to answer which was “better” for a hospitalized child: A practitioner who knew the child and family or a hospitalist who might be more knowledgeable about the disease, its inpatient management, and how to get things done in the hospital?³ The authors could not answer which model was better for an individual child with an invested primary pediatrician, but concluded that hospitalists have the potential to improve care for all children in the hospital—the future promise of Pediatric Hospital Medicine (PHM). This article traces the growth of PHM from 1996 to the present, highlighting developments that fueled the hospital movement in general and PHM in particular (Table).

In the 7 years after the article by Drs Wachter and Goldman, a series of regulations fostered the adoption of hospitalists in teaching hospitals. The first was the reissuance in 1997 of Intermediary Letter 372, which specifies the requirements for attending physicians to bill Medicare.⁴ The common practice of jotting “agree with above” and cosigning resident notes was no longer sufficient: Attendings had to document that they personally provided services to patients beyond those of residents. As a demonstration of enforcement, records at the Hospital of the University of Pennsylvania in Philadelphia were audited, and a bill for $30 million for overpayments and penalties was issued.⁴ Teaching hospitals took notice and instituted mechanisms to assure compliance with IL-372, not limited to patients insured by Medicare. The obvious effect on faculty was the requirement of considerably more time and involvement in direct patient care.

Later in the 1990s, the Accreditation Council for Graduate Medical Education (ACGME) introduced a new direction termed the Outcome Project, which led to two novel trainee competency domains: practice-based improvement and systems-based practice.⁵ The focus on quality improvement, patient safety, and systems was reinforced by two Institute of Medicine publications, To Err Is Human: Building a Safer Health System⁶ and Crossing the Quality Chasm: A New Health Care System for the 21st Century.⁷ Hospitalists had the opportunity to impact both patient care and the education of learners in two ways: Directly, by more actively participating in and closely supervising clinical care (per IL-372) and, indirectly, by improving hospital systems.

In 2003, the ACGME extended work hour restrictions implemented in New York State to the national level.⁸ The new requirements were intended to improve patient safety and increase trainee supervision, but also had the effect of reducing trainees’ clinical experience. While responses of teaching institutions varied, training program changes generated an increased role for hospitalists.⁹

These changes occurred on a backdrop of changing models of healthcare payment that provided incentive to shorten length of stay (LOS) and shift care from inpatient to ambulatory settings, which increased the acuity and complexity of hospitalized patients. The pressure to increase efficiency and decrease LOS affected faculty, residents, and practitioners in the community. Managing care of inpatients from a distance became more difficult; rounding more than once a day was often required and was disruptive and inefficient, particularly for community practitioners who might have only one or two patients in the hospital. Moreover, the hospital electronic medical record (EMR) became an additional barrier for many practitioners to continue to provide hospital-based care. Systems often differed from those used in their offices, and even when this was not the case, using and maintaining efficiency in the different components of the EMR was difficult. The conversion from paper to electronic documentation and ordering may have contributed to some practitioners relinquishing care of their patients to hospitalists.

The development of PHM was aided by support from three separate organizations, each with a different role: the Society of Hospital Medicine (SHM), the American Academy of Pediatrics (AAP), and the Academic Pediatric Association (APA). SHM was founded the year after the article by Drs Wachter and Goldman as the “National Association of Inpatient Physicians.” The name was changed to Society of Hospital Medicine in 2003 to reflect the evolving field of hospital medicine. While the organization is largely comprised of internists, a pediatrician has been on its board since 1998, and a pediatrics committee (now Special Interest Group, SIG) has been in existence since 1999. (Appendix Tables 1a and 1b; Appendix Figures 1a and 1b). In 2005, an SHM task force was formed to define PHM-specific Core Competencies that could serve as a basis for curriculum building and a definition of the field. These inaugural PHM Core Competencies were endorsed by all three societies; published in 2010 in SHM’s flagship journal, the Journal of Hospital Medicine¹⁰; and were recently revised to reflect changes to the field in the past decade.¹¹ SHM has provided valuable opportunities for hospitalists to develop knowledge and skills, particularly in matters related to healthcare operations and leadership, and it serves as a way to keep PHM connected with the larger hospital medicine community.

The AAP initiated its efforts to engage hospitalists in 1998 with the creation of a Provisional Section on Hospital Medicine (SOHM) that became a full section a year later. (Appendix Table 2; Appendix Figure 2) The SOHM listserv^®, created in 2000, became a major vehicle for communication among hospitalists—including individuals who are not members of the SOHM—with more than 4,000 subscribers currently. Of the SOHM achievements noted in the Table, one deserves special mention: In 2006, SOHM formally recognized the large number of hospitalists in community hospitals and established a subsection with Karen Kingry Olson, MD, as inaugural leader. Many of the hospitalists in these sites provide care not only to children on inpatient units but also in areas such as the nursery, delivery room, and emergency department, functioning “like water on pavement—filling all the cracks in the hospital,” as Eric Biondi, MD, MS, puts it.¹² It is a credit to the AAP and the PHM community that individuals from community hospitals have specifically been afforded leadership roles. SOHM membership has grown considerably from around 100 at inception to 2,700 in 2019. Participation in the AAP keeps PHM connected to the larger pediatrics community.

The APA established a Hospital and Inpatient Medicine SIG in 2001, the name of which was changed to Hospital Medicine SIG in 2004 (Appendix Table 3; Appendix Figure 3; Note: There had been an Inpatient General Pediatricians SIG in 1992, before the term hospitalist was coined, but it only met once.) In 2003, APA was the first national pediatrics organization to sponsor a PHM meeting. The meeting attracted 130 registrants and was considered successful enough to warrant another meeting in 2005, this time with SHM and AAP joining as cosponsors. In 2007, the triple-sponsored meetings became annual events, with 1,600 registrants at the 2019 meeting. The success of the initial meeting also caught the attention of APA leadership in another regard: a concern that the name of the organization might interfere with retaining hospitalists in the fold. In 2007, the Ambulatory Pediatric Association became the Academic Pediatric Association.¹³ Being connected with the APA affords PHM a connection to academic generalists and activities central to the APA, such as research and education.

In 2009, PHM leaders within SHM, APA, and AAP held a pivotal strategic planning “roundtable” to discuss the future of the field.¹⁴ A vision statement was developed, serving as a guide to the tasks needed to achieve the vision: “Pediatric hospitalists will transform the delivery of hospital care for children.” Five areas were considered: clinical, quality, research, workforce, and structure. Clinical practice was defined as including both “direct patient care and leadership of the inpatient service.” It was recognized that standardizing, disseminating, and increasing knowledge to improve clinical care was important, but so, too, was taking on leadership roles to improve systems and extend into areas such as sedation. Quality improvement was identified as the measure by which the value of PHM would be assessed. To further efforts in this area, a PHM Quality Improvement (QI) Collaborative work group was created. Research was clearly a necessary component to establish and advance the field. The Children’s Hospital Association had launched the Pediatric Health Information System (PHIS) database in 1993, and PHIS began to flourish as a research database when Samir Shah, MD, MSCE, and Matt Hall, PhD, headed the Research Groups in 2007. Discussions to form an independent research network began in 2001, and, in 2002, the Pediatric Research in Inpatient Settings network (PRIS) was launched, led by Christopher Landrigan, MD, MPH.¹⁵ The APA provided organization support in 2006, but a redesign was considered necessary to further move the research initiative forward.¹⁵ A Research Leadership Task Force was created, resulting in a new PRIS Network Executive Council, chaired by Rajendu Srivastava, MD, MPH, until 2016, when Karen Wilson, MD, MPH, became chair. Clinical and workforce issues focused on the need to supplement residency training with added skills and knowledge to practice as a pediatric hospitalist. An Education Task Force was created, charged with developing “an educational plan supporting the PHM Core Competencies and addressing hospitalist training needs, including the role as formal educators.” The task force was headed by Mary Ottolini, MD, MPH, MEd, who was aided by Jennifer Maniscalco, MD, MPH, MAcM. Regarding structure of PHM, the decision was made not to develop an independent society but to continue to function within and benefit from the resources of SHM, AAP, and APA, with a Joint Council on Pediatric Hospital Medicine (JCPHM). Established in 2011, the JCPHM included representatives of the AAP, APA, SHM, PRIS, VIP, community hospitals, and the Education Task Force. Erin Stucky Fisher, MD, MHM, served as the first chair. The JCPHM was replaced in the fall of 2016 by a Consortium on PHM, which consists of the chairs and chair elects of the AAP SOHM, the APA Hospital Medicine SIG, and the SHM pediatrics committee. The leadership rotates annually among the three organizations.

The American Board of Pediatrics (ABP) recognized the growing field of PHM and, through its foundation, commissioned a series of studies, the first of which was published in 2006 entitled “Hospitalists in children’s hospitals: What we know now and what we need to know.”¹⁶ It was not clear whether the PHM community would pursue subspecialty certification. The leaders of the 2009 “roundtable” meeting commissioned a Strategic Planning Committee (STP) led by Christopher Maloney, MD, PhD, and Suzanne Swanson Mendez, MD, to evaluate the best course of action: traditional ABP subspecialty certification, hospital medicine residency track (with or without additional fellowship), Recognition of Focused Practice (as implemented by the American Board of Internal Medicine and American Board of Family Medicine), mandatory mentorship program, or status quo with option for specialized training. There was considerable discussion of the alternatives in the PHM community. In 2012, the STP shared the results of Strengths-Weaknesses-Opportunities-Threats analyses—but did not issue a recommendation.¹⁷ The following year, a National PHM Leaders Conference was held to consider the various options. Participants concluded that the best path forward was to pursue subspecialty certification with a requirement for 2 years of fellowship (after a time-limited period for practice pathway eligibility). Two years of fellowship was a departure from the ABP’s standard 3 years, but seemed acceptable based on the expectation that the research component would be integrated with clinical activities (eg, QI), rather than separate bench research. The ABP Initiative on Subspecialty Clinical Training and Certification had recommended flexibility in the duration of fellowships,¹⁸ and PHM became the first discipline to take advantage of such flexibility. Following an 18-month review of multiple considerations, the ABP concluded that “children will be better served by establishing the discipline as a new subspecialty.”¹⁹

The decision to pursue subspecialty certification was not unanimously embraced by the PHM community, with particular concerns expressed regarding the impact on Med-Peds hospitalists and the future in community hospitals. These were considered by the individuals writing the formal proposal to the ABP, but have not been resolved. Moreover, criteria for eligibility for the certifying examination under the Practice Pathway (“grandparenting”) evoked controversy,²⁰ addressed by the ABP. ²¹ The first subspecialty certifying examination was ultimately administered to ~1,500 pediatric hospitalists in 2019.

It is clear that PHM has established itself as a field, with networks for research and quality improvement, more than 50 fellowship programs, divisions in prestigious departments of pediatrics and children’s hospitals, devoted journals and textbooks, and a well-attended annual meeting. PHM has set standards for the core competencies in PHM,^{11, 12} for pediatric hospitalist programs,^{22, 23} for coordinating the hospital care of children,^{24, 25} for the curricular framework of fellowships,²⁶ and for the Entrustable Professional Activities expected of a hospitalist.²⁷ The vision for the future is that continued efforts in research, quality and systems improvement, and clinical care will, in fact, result in significant benefits for all hospitalized children. Such was the promise of PHM in the 1990s and remains so in 2019.

Acknowledgments

For prompting the project: Rachel Marek. For additions, corrections, and confirmations: David Alexander, Niccole Alexander, Paul Bellet, David Bertoch, Douglas Carlson, Laura Degnon, Kimberly Durham, Barrett Fromme, Sandy Gage, Matthew Garber, Karen Jerardi, Christopher Landrigan, Gail McGuinness, Jennifer Maniscalco, Sandy Melzer, Vineeta Mittal, Karen Kingry Olson, Mary Ottolini, Jack Percelay, Kris Rehm, Michael Ruhlen, Samir Shah, Suzanne Woods, and David Zipes.

Disclosures

The authors have nothing to disclose.

In 1996, internists Robert Wachter, MD, and Lee Goldman, MD, MPH, coined the term “hospitalist” and predicted an “emerging role in the American health care system.”¹ Pediatrics was not far behind: In 1999, Dr Wachter joined Paul Bellet, MD, in authoring an article describing the movement within pediatrics.² An accompanying editorial, coauthored by a pediatric hospitalist and an office-based practitioner, attempted to answer which was “better” for a hospitalized child: A practitioner who knew the child and family or a hospitalist who might be more knowledgeable about the disease, its inpatient management, and how to get things done in the hospital?³ The authors could not answer which model was better for an individual child with an invested primary pediatrician, but concluded that hospitalists have the potential to improve care for all children in the hospital—the future promise of Pediatric Hospital Medicine (PHM). This article traces the growth of PHM from 1996 to the present, highlighting developments that fueled the hospital movement in general and PHM in particular (Table).

In the 7 years after the article by Drs Wachter and Goldman, a series of regulations fostered the adoption of hospitalists in teaching hospitals. The first was the reissuance in 1997 of Intermediary Letter 372, which specifies the requirements for attending physicians to bill Medicare.⁴ The common practice of jotting “agree with above” and cosigning resident notes was no longer sufficient: Attendings had to document that they personally provided services to patients beyond those of residents. As a demonstration of enforcement, records at the Hospital of the University of Pennsylvania in Philadelphia were audited, and a bill for $30 million for overpayments and penalties was issued.⁴ Teaching hospitals took notice and instituted mechanisms to assure compliance with IL-372, not limited to patients insured by Medicare. The obvious effect on faculty was the requirement of considerably more time and involvement in direct patient care.

Later in the 1990s, the Accreditation Council for Graduate Medical Education (ACGME) introduced a new direction termed the Outcome Project, which led to two novel trainee competency domains: practice-based improvement and systems-based practice.⁵ The focus on quality improvement, patient safety, and systems was reinforced by two Institute of Medicine publications, To Err Is Human: Building a Safer Health System⁶ and Crossing the Quality Chasm: A New Health Care System for the 21st Century.⁷ Hospitalists had the opportunity to impact both patient care and the education of learners in two ways: Directly, by more actively participating in and closely supervising clinical care (per IL-372) and, indirectly, by improving hospital systems.

In 2003, the ACGME extended work hour restrictions implemented in New York State to the national level.⁸ The new requirements were intended to improve patient safety and increase trainee supervision, but also had the effect of reducing trainees’ clinical experience. While responses of teaching institutions varied, training program changes generated an increased role for hospitalists.⁹

These changes occurred on a backdrop of changing models of healthcare payment that provided incentive to shorten length of stay (LOS) and shift care from inpatient to ambulatory settings, which increased the acuity and complexity of hospitalized patients. The pressure to increase efficiency and decrease LOS affected faculty, residents, and practitioners in the community. Managing care of inpatients from a distance became more difficult; rounding more than once a day was often required and was disruptive and inefficient, particularly for community practitioners who might have only one or two patients in the hospital. Moreover, the hospital electronic medical record (EMR) became an additional barrier for many practitioners to continue to provide hospital-based care. Systems often differed from those used in their offices, and even when this was not the case, using and maintaining efficiency in the different components of the EMR was difficult. The conversion from paper to electronic documentation and ordering may have contributed to some practitioners relinquishing care of their patients to hospitalists.

The development of PHM was aided by support from three separate organizations, each with a different role: the Society of Hospital Medicine (SHM), the American Academy of Pediatrics (AAP), and the Academic Pediatric Association (APA). SHM was founded the year after the article by Drs Wachter and Goldman as the “National Association of Inpatient Physicians.” The name was changed to Society of Hospital Medicine in 2003 to reflect the evolving field of hospital medicine. While the organization is largely comprised of internists, a pediatrician has been on its board since 1998, and a pediatrics committee (now Special Interest Group, SIG) has been in existence since 1999. (Appendix Tables 1a and 1b; Appendix Figures 1a and 1b). In 2005, an SHM task force was formed to define PHM-specific Core Competencies that could serve as a basis for curriculum building and a definition of the field. These inaugural PHM Core Competencies were endorsed by all three societies; published in 2010 in SHM’s flagship journal, the Journal of Hospital Medicine¹⁰; and were recently revised to reflect changes to the field in the past decade.¹¹ SHM has provided valuable opportunities for hospitalists to develop knowledge and skills, particularly in matters related to healthcare operations and leadership, and it serves as a way to keep PHM connected with the larger hospital medicine community.

The AAP initiated its efforts to engage hospitalists in 1998 with the creation of a Provisional Section on Hospital Medicine (SOHM) that became a full section a year later. (Appendix Table 2; Appendix Figure 2) The SOHM listserv^®, created in 2000, became a major vehicle for communication among hospitalists—including individuals who are not members of the SOHM—with more than 4,000 subscribers currently. Of the SOHM achievements noted in the Table, one deserves special mention: In 2006, SOHM formally recognized the large number of hospitalists in community hospitals and established a subsection with Karen Kingry Olson, MD, as inaugural leader. Many of the hospitalists in these sites provide care not only to children on inpatient units but also in areas such as the nursery, delivery room, and emergency department, functioning “like water on pavement—filling all the cracks in the hospital,” as Eric Biondi, MD, MS, puts it.¹² It is a credit to the AAP and the PHM community that individuals from community hospitals have specifically been afforded leadership roles. SOHM membership has grown considerably from around 100 at inception to 2,700 in 2019. Participation in the AAP keeps PHM connected to the larger pediatrics community.

The APA established a Hospital and Inpatient Medicine SIG in 2001, the name of which was changed to Hospital Medicine SIG in 2004 (Appendix Table 3; Appendix Figure 3; Note: There had been an Inpatient General Pediatricians SIG in 1992, before the term hospitalist was coined, but it only met once.) In 2003, APA was the first national pediatrics organization to sponsor a PHM meeting. The meeting attracted 130 registrants and was considered successful enough to warrant another meeting in 2005, this time with SHM and AAP joining as cosponsors. In 2007, the triple-sponsored meetings became annual events, with 1,600 registrants at the 2019 meeting. The success of the initial meeting also caught the attention of APA leadership in another regard: a concern that the name of the organization might interfere with retaining hospitalists in the fold. In 2007, the Ambulatory Pediatric Association became the Academic Pediatric Association.¹³ Being connected with the APA affords PHM a connection to academic generalists and activities central to the APA, such as research and education.

In 2009, PHM leaders within SHM, APA, and AAP held a pivotal strategic planning “roundtable” to discuss the future of the field.¹⁴ A vision statement was developed, serving as a guide to the tasks needed to achieve the vision: “Pediatric hospitalists will transform the delivery of hospital care for children.” Five areas were considered: clinical, quality, research, workforce, and structure. Clinical practice was defined as including both “direct patient care and leadership of the inpatient service.” It was recognized that standardizing, disseminating, and increasing knowledge to improve clinical care was important, but so, too, was taking on leadership roles to improve systems and extend into areas such as sedation. Quality improvement was identified as the measure by which the value of PHM would be assessed. To further efforts in this area, a PHM Quality Improvement (QI) Collaborative work group was created. Research was clearly a necessary component to establish and advance the field. The Children’s Hospital Association had launched the Pediatric Health Information System (PHIS) database in 1993, and PHIS began to flourish as a research database when Samir Shah, MD, MSCE, and Matt Hall, PhD, headed the Research Groups in 2007. Discussions to form an independent research network began in 2001, and, in 2002, the Pediatric Research in Inpatient Settings network (PRIS) was launched, led by Christopher Landrigan, MD, MPH.¹⁵ The APA provided organization support in 2006, but a redesign was considered necessary to further move the research initiative forward.¹⁵ A Research Leadership Task Force was created, resulting in a new PRIS Network Executive Council, chaired by Rajendu Srivastava, MD, MPH, until 2016, when Karen Wilson, MD, MPH, became chair. Clinical and workforce issues focused on the need to supplement residency training with added skills and knowledge to practice as a pediatric hospitalist. An Education Task Force was created, charged with developing “an educational plan supporting the PHM Core Competencies and addressing hospitalist training needs, including the role as formal educators.” The task force was headed by Mary Ottolini, MD, MPH, MEd, who was aided by Jennifer Maniscalco, MD, MPH, MAcM. Regarding structure of PHM, the decision was made not to develop an independent society but to continue to function within and benefit from the resources of SHM, AAP, and APA, with a Joint Council on Pediatric Hospital Medicine (JCPHM). Established in 2011, the JCPHM included representatives of the AAP, APA, SHM, PRIS, VIP, community hospitals, and the Education Task Force. Erin Stucky Fisher, MD, MHM, served as the first chair. The JCPHM was replaced in the fall of 2016 by a Consortium on PHM, which consists of the chairs and chair elects of the AAP SOHM, the APA Hospital Medicine SIG, and the SHM pediatrics committee. The leadership rotates annually among the three organizations.

The American Board of Pediatrics (ABP) recognized the growing field of PHM and, through its foundation, commissioned a series of studies, the first of which was published in 2006 entitled “Hospitalists in children’s hospitals: What we know now and what we need to know.”¹⁶ It was not clear whether the PHM community would pursue subspecialty certification. The leaders of the 2009 “roundtable” meeting commissioned a Strategic Planning Committee (STP) led by Christopher Maloney, MD, PhD, and Suzanne Swanson Mendez, MD, to evaluate the best course of action: traditional ABP subspecialty certification, hospital medicine residency track (with or without additional fellowship), Recognition of Focused Practice (as implemented by the American Board of Internal Medicine and American Board of Family Medicine), mandatory mentorship program, or status quo with option for specialized training. There was considerable discussion of the alternatives in the PHM community. In 2012, the STP shared the results of Strengths-Weaknesses-Opportunities-Threats analyses—but did not issue a recommendation.¹⁷ The following year, a National PHM Leaders Conference was held to consider the various options. Participants concluded that the best path forward was to pursue subspecialty certification with a requirement for 2 years of fellowship (after a time-limited period for practice pathway eligibility). Two years of fellowship was a departure from the ABP’s standard 3 years, but seemed acceptable based on the expectation that the research component would be integrated with clinical activities (eg, QI), rather than separate bench research. The ABP Initiative on Subspecialty Clinical Training and Certification had recommended flexibility in the duration of fellowships,¹⁸ and PHM became the first discipline to take advantage of such flexibility. Following an 18-month review of multiple considerations, the ABP concluded that “children will be better served by establishing the discipline as a new subspecialty.”¹⁹

The decision to pursue subspecialty certification was not unanimously embraced by the PHM community, with particular concerns expressed regarding the impact on Med-Peds hospitalists and the future in community hospitals. These were considered by the individuals writing the formal proposal to the ABP, but have not been resolved. Moreover, criteria for eligibility for the certifying examination under the Practice Pathway (“grandparenting”) evoked controversy,²⁰ addressed by the ABP. ²¹ The first subspecialty certifying examination was ultimately administered to ~1,500 pediatric hospitalists in 2019.

It is clear that PHM has established itself as a field, with networks for research and quality improvement, more than 50 fellowship programs, divisions in prestigious departments of pediatrics and children’s hospitals, devoted journals and textbooks, and a well-attended annual meeting. PHM has set standards for the core competencies in PHM,^{11, 12} for pediatric hospitalist programs,^{22, 23} for coordinating the hospital care of children,^{24, 25} for the curricular framework of fellowships,²⁶ and for the Entrustable Professional Activities expected of a hospitalist.²⁷ The vision for the future is that continued efforts in research, quality and systems improvement, and clinical care will, in fact, result in significant benefits for all hospitalized children. Such was the promise of PHM in the 1990s and remains so in 2019.

Acknowledgments

For prompting the project: Rachel Marek. For additions, corrections, and confirmations: David Alexander, Niccole Alexander, Paul Bellet, David Bertoch, Douglas Carlson, Laura Degnon, Kimberly Durham, Barrett Fromme, Sandy Gage, Matthew Garber, Karen Jerardi, Christopher Landrigan, Gail McGuinness, Jennifer Maniscalco, Sandy Melzer, Vineeta Mittal, Karen Kingry Olson, Mary Ottolini, Jack Percelay, Kris Rehm, Michael Ruhlen, Samir Shah, Suzanne Woods, and David Zipes.

Disclosures

The authors have nothing to disclose.

In 1996, internists Robert Wachter, MD, and Lee Goldman, MD, MPH, coined the term “hospitalist” and predicted an “emerging role in the American health care system.”¹ Pediatrics was not far behind: In 1999, Dr Wachter joined Paul Bellet, MD, in authoring an article describing the movement within pediatrics.² An accompanying editorial, coauthored by a pediatric hospitalist and an office-based practitioner, attempted to answer which was “better” for a hospitalized child: A practitioner who knew the child and family or a hospitalist who might be more knowledgeable about the disease, its inpatient management, and how to get things done in the hospital?³ The authors could not answer which model was better for an individual child with an invested primary pediatrician, but concluded that hospitalists have the potential to improve care for all children in the hospital—the future promise of Pediatric Hospital Medicine (PHM). This article traces the growth of PHM from 1996 to the present, highlighting developments that fueled the hospital movement in general and PHM in particular (Table).

In the 7 years after the article by Drs Wachter and Goldman, a series of regulations fostered the adoption of hospitalists in teaching hospitals. The first was the reissuance in 1997 of Intermediary Letter 372, which specifies the requirements for attending physicians to bill Medicare.⁴ The common practice of jotting “agree with above” and cosigning resident notes was no longer sufficient: Attendings had to document that they personally provided services to patients beyond those of residents. As a demonstration of enforcement, records at the Hospital of the University of Pennsylvania in Philadelphia were audited, and a bill for $30 million for overpayments and penalties was issued.⁴ Teaching hospitals took notice and instituted mechanisms to assure compliance with IL-372, not limited to patients insured by Medicare. The obvious effect on faculty was the requirement of considerably more time and involvement in direct patient care.

Later in the 1990s, the Accreditation Council for Graduate Medical Education (ACGME) introduced a new direction termed the Outcome Project, which led to two novel trainee competency domains: practice-based improvement and systems-based practice.⁵ The focus on quality improvement, patient safety, and systems was reinforced by two Institute of Medicine publications, To Err Is Human: Building a Safer Health System⁶ and Crossing the Quality Chasm: A New Health Care System for the 21st Century.⁷ Hospitalists had the opportunity to impact both patient care and the education of learners in two ways: Directly, by more actively participating in and closely supervising clinical care (per IL-372) and, indirectly, by improving hospital systems.

In 2003, the ACGME extended work hour restrictions implemented in New York State to the national level.⁸ The new requirements were intended to improve patient safety and increase trainee supervision, but also had the effect of reducing trainees’ clinical experience. While responses of teaching institutions varied, training program changes generated an increased role for hospitalists.⁹

These changes occurred on a backdrop of changing models of healthcare payment that provided incentive to shorten length of stay (LOS) and shift care from inpatient to ambulatory settings, which increased the acuity and complexity of hospitalized patients. The pressure to increase efficiency and decrease LOS affected faculty, residents, and practitioners in the community. Managing care of inpatients from a distance became more difficult; rounding more than once a day was often required and was disruptive and inefficient, particularly for community practitioners who might have only one or two patients in the hospital. Moreover, the hospital electronic medical record (EMR) became an additional barrier for many practitioners to continue to provide hospital-based care. Systems often differed from those used in their offices, and even when this was not the case, using and maintaining efficiency in the different components of the EMR was difficult. The conversion from paper to electronic documentation and ordering may have contributed to some practitioners relinquishing care of their patients to hospitalists.

The development of PHM was aided by support from three separate organizations, each with a different role: the Society of Hospital Medicine (SHM), the American Academy of Pediatrics (AAP), and the Academic Pediatric Association (APA). SHM was founded the year after the article by Drs Wachter and Goldman as the “National Association of Inpatient Physicians.” The name was changed to Society of Hospital Medicine in 2003 to reflect the evolving field of hospital medicine. While the organization is largely comprised of internists, a pediatrician has been on its board since 1998, and a pediatrics committee (now Special Interest Group, SIG) has been in existence since 1999. (Appendix Tables 1a and 1b; Appendix Figures 1a and 1b). In 2005, an SHM task force was formed to define PHM-specific Core Competencies that could serve as a basis for curriculum building and a definition of the field. These inaugural PHM Core Competencies were endorsed by all three societies; published in 2010 in SHM’s flagship journal, the Journal of Hospital Medicine¹⁰; and were recently revised to reflect changes to the field in the past decade.¹¹ SHM has provided valuable opportunities for hospitalists to develop knowledge and skills, particularly in matters related to healthcare operations and leadership, and it serves as a way to keep PHM connected with the larger hospital medicine community.

The AAP initiated its efforts to engage hospitalists in 1998 with the creation of a Provisional Section on Hospital Medicine (SOHM) that became a full section a year later. (Appendix Table 2; Appendix Figure 2) The SOHM listserv^®, created in 2000, became a major vehicle for communication among hospitalists—including individuals who are not members of the SOHM—with more than 4,000 subscribers currently. Of the SOHM achievements noted in the Table, one deserves special mention: In 2006, SOHM formally recognized the large number of hospitalists in community hospitals and established a subsection with Karen Kingry Olson, MD, as inaugural leader. Many of the hospitalists in these sites provide care not only to children on inpatient units but also in areas such as the nursery, delivery room, and emergency department, functioning “like water on pavement—filling all the cracks in the hospital,” as Eric Biondi, MD, MS, puts it.¹² It is a credit to the AAP and the PHM community that individuals from community hospitals have specifically been afforded leadership roles. SOHM membership has grown considerably from around 100 at inception to 2,700 in 2019. Participation in the AAP keeps PHM connected to the larger pediatrics community.

The APA established a Hospital and Inpatient Medicine SIG in 2001, the name of which was changed to Hospital Medicine SIG in 2004 (Appendix Table 3; Appendix Figure 3; Note: There had been an Inpatient General Pediatricians SIG in 1992, before the term hospitalist was coined, but it only met once.) In 2003, APA was the first national pediatrics organization to sponsor a PHM meeting. The meeting attracted 130 registrants and was considered successful enough to warrant another meeting in 2005, this time with SHM and AAP joining as cosponsors. In 2007, the triple-sponsored meetings became annual events, with 1,600 registrants at the 2019 meeting. The success of the initial meeting also caught the attention of APA leadership in another regard: a concern that the name of the organization might interfere with retaining hospitalists in the fold. In 2007, the Ambulatory Pediatric Association became the Academic Pediatric Association.¹³ Being connected with the APA affords PHM a connection to academic generalists and activities central to the APA, such as research and education.

In 2009, PHM leaders within SHM, APA, and AAP held a pivotal strategic planning “roundtable” to discuss the future of the field.¹⁴ A vision statement was developed, serving as a guide to the tasks needed to achieve the vision: “Pediatric hospitalists will transform the delivery of hospital care for children.” Five areas were considered: clinical, quality, research, workforce, and structure. Clinical practice was defined as including both “direct patient care and leadership of the inpatient service.” It was recognized that standardizing, disseminating, and increasing knowledge to improve clinical care was important, but so, too, was taking on leadership roles to improve systems and extend into areas such as sedation. Quality improvement was identified as the measure by which the value of PHM would be assessed. To further efforts in this area, a PHM Quality Improvement (QI) Collaborative work group was created. Research was clearly a necessary component to establish and advance the field. The Children’s Hospital Association had launched the Pediatric Health Information System (PHIS) database in 1993, and PHIS began to flourish as a research database when Samir Shah, MD, MSCE, and Matt Hall, PhD, headed the Research Groups in 2007. Discussions to form an independent research network began in 2001, and, in 2002, the Pediatric Research in Inpatient Settings network (PRIS) was launched, led by Christopher Landrigan, MD, MPH.¹⁵ The APA provided organization support in 2006, but a redesign was considered necessary to further move the research initiative forward.¹⁵ A Research Leadership Task Force was created, resulting in a new PRIS Network Executive Council, chaired by Rajendu Srivastava, MD, MPH, until 2016, when Karen Wilson, MD, MPH, became chair. Clinical and workforce issues focused on the need to supplement residency training with added skills and knowledge to practice as a pediatric hospitalist. An Education Task Force was created, charged with developing “an educational plan supporting the PHM Core Competencies and addressing hospitalist training needs, including the role as formal educators.” The task force was headed by Mary Ottolini, MD, MPH, MEd, who was aided by Jennifer Maniscalco, MD, MPH, MAcM. Regarding structure of PHM, the decision was made not to develop an independent society but to continue to function within and benefit from the resources of SHM, AAP, and APA, with a Joint Council on Pediatric Hospital Medicine (JCPHM). Established in 2011, the JCPHM included representatives of the AAP, APA, SHM, PRIS, VIP, community hospitals, and the Education Task Force. Erin Stucky Fisher, MD, MHM, served as the first chair. The JCPHM was replaced in the fall of 2016 by a Consortium on PHM, which consists of the chairs and chair elects of the AAP SOHM, the APA Hospital Medicine SIG, and the SHM pediatrics committee. The leadership rotates annually among the three organizations.

The American Board of Pediatrics (ABP) recognized the growing field of PHM and, through its foundation, commissioned a series of studies, the first of which was published in 2006 entitled “Hospitalists in children’s hospitals: What we know now and what we need to know.”¹⁶ It was not clear whether the PHM community would pursue subspecialty certification. The leaders of the 2009 “roundtable” meeting commissioned a Strategic Planning Committee (STP) led by Christopher Maloney, MD, PhD, and Suzanne Swanson Mendez, MD, to evaluate the best course of action: traditional ABP subspecialty certification, hospital medicine residency track (with or without additional fellowship), Recognition of Focused Practice (as implemented by the American Board of Internal Medicine and American Board of Family Medicine), mandatory mentorship program, or status quo with option for specialized training. There was considerable discussion of the alternatives in the PHM community. In 2012, the STP shared the results of Strengths-Weaknesses-Opportunities-Threats analyses—but did not issue a recommendation.¹⁷ The following year, a National PHM Leaders Conference was held to consider the various options. Participants concluded that the best path forward was to pursue subspecialty certification with a requirement for 2 years of fellowship (after a time-limited period for practice pathway eligibility). Two years of fellowship was a departure from the ABP’s standard 3 years, but seemed acceptable based on the expectation that the research component would be integrated with clinical activities (eg, QI), rather than separate bench research. The ABP Initiative on Subspecialty Clinical Training and Certification had recommended flexibility in the duration of fellowships,¹⁸ and PHM became the first discipline to take advantage of such flexibility. Following an 18-month review of multiple considerations, the ABP concluded that “children will be better served by establishing the discipline as a new subspecialty.”¹⁹

The decision to pursue subspecialty certification was not unanimously embraced by the PHM community, with particular concerns expressed regarding the impact on Med-Peds hospitalists and the future in community hospitals. These were considered by the individuals writing the formal proposal to the ABP, but have not been resolved. Moreover, criteria for eligibility for the certifying examination under the Practice Pathway (“grandparenting”) evoked controversy,²⁰ addressed by the ABP. ²¹ The first subspecialty certifying examination was ultimately administered to ~1,500 pediatric hospitalists in 2019.

It is clear that PHM has established itself as a field, with networks for research and quality improvement, more than 50 fellowship programs, divisions in prestigious departments of pediatrics and children’s hospitals, devoted journals and textbooks, and a well-attended annual meeting. PHM has set standards for the core competencies in PHM,^{11, 12} for pediatric hospitalist programs,^{22, 23} for coordinating the hospital care of children,^{24, 25} for the curricular framework of fellowships,²⁶ and for the Entrustable Professional Activities expected of a hospitalist.²⁷ The vision for the future is that continued efforts in research, quality and systems improvement, and clinical care will, in fact, result in significant benefits for all hospitalized children. Such was the promise of PHM in the 1990s and remains so in 2019.

Acknowledgments

For prompting the project: Rachel Marek. For additions, corrections, and confirmations: David Alexander, Niccole Alexander, Paul Bellet, David Bertoch, Douglas Carlson, Laura Degnon, Kimberly Durham, Barrett Fromme, Sandy Gage, Matthew Garber, Karen Jerardi, Christopher Landrigan, Gail McGuinness, Jennifer Maniscalco, Sandy Melzer, Vineeta Mittal, Karen Kingry Olson, Mary Ottolini, Jack Percelay, Kris Rehm, Michael Ruhlen, Samir Shah, Suzanne Woods, and David Zipes.

Disclosures

The authors have nothing to disclose.

Machine-learning is a type of artificial intelligence in which systems automatically learn and improve from experience without being explicitly programmed. Classification and Regression Tree (CART) analysis is a machine-learning algorithm that was developed to visually classify or segment populations into subgroups with similar characteristics and outcomes. CART analysis is a decision tree methodology that was initially developed in the 1960s for use in product marketing.¹ Since then, a number of health disciplines have used it to isolate patient subgroups from larger populations to guide clinical decision-making by better identifying those most likely to benefit.² The clinical utility of CART mirrors how most clinicians think, which is not in terms of coefficients (ie, regression output) but rather in terms of categories or classifications (eg, low vs high risk).

In this issue of the Journal of Hospital Medicine, Young and colleagues use classification trees to predict discharge placement (postacute care facility vs home) based on a patient’s hospital admission characteristics and mobility score. The resulting decision tree indicates that patients with the lowest mobility scores, as well as those 65 years and older, were most likely to be discharged to postacute care facilities.³ In this review, we orient the reader to the basics of CART analysis, discuss important intricacies, and weigh its pros, cons, and application as a statistical tool.

CART is a nonparametric (ie, makes no assumptions about data distribution) statistical tool that identifies subgroups within a population whose members share common characteristics as defined by the independent variables included in the model. CART analysis is unique in that it yields a visual output of the data in the form of a multisegmented structure that resembles the branches of a tree (Figure). CART analysis consists of four basic steps: (1) tree-building (including splitting criteria and estimation of classification error), (2) stopping the tree-building process, (3) tree “pruning,” and (4) tree selection.

In general, CART analysis begins with a single “node” or group, which contains the entire sample population. This is referred to as the “parent node.” The CART procedure simultaneously examines all available independent variables and selects one that results in two groups that are the most distinct with respect to the outcome variable of interest. In Young et al’s example, posthospital discharge placement is the outcome.³ This parent node then branches into two “child nodes” according to the independent variable that was selected. Within each of these “child nodes,” the tree-growing methodology recursively assesses each of the remaining independent variables to determine which will result in the best split according to the chosen splitting criterion.² Each subsequent “child node” will become a “parent node” to the two groups in which it splits. This process is repeated on the data in each subsequent “child node” and is stopped once a predefined stopping point is reached. Notably, while division into two groups is the most common application of CART modeling, there are models that can split data into more than two child nodes.

Since CART outcomes can be heavily dependent on the data being used (eg, electronic health records or administrative data), it is important to attempt to confirm results in a similar, but different, study cohort. Because obtaining separate data sources with similar cohorts can be difficult, many investigators using CART will utilize a “split sample approach” in which study data are split into separate training and validation sets.⁴ In the training set, which frequently comprises two-thirds of the available data, the algorithm is tested in exploratory analysis. Once the algorithm is defined and agreed upon, it is retested within a validation set, constructed from the remaining one-third of data. This approach, which Young et al utilize,³ allows for improved confidence and reduced risk of bias in the findings and allows for some degree of external validation. Further, the split sample approach supports more reliable measures of predictive accuracy: in Young et al’s case, the proportion of correctly classified patients discharged to a postacute care facility (sensitivity: 58%, 95% CI 49-68%) and the proportion of correctly classified patients discharged home (specificity: 84%, 95% CI 78-90%). Despite these advantages, the split sample approach is not universally used.

Classification Versus Regression Trees

While commonly grouped together, CARTs can be distinguished from one another based on the dependent, or outcome, variable. Categorical outcome variables require the use of a classification tree, while continuous outcomes utilize regression trees. Of note, the independent, or predictor, variables can be any combination of categorical or continuous variables. However, splitting at each node creates categorical output when using CART algorithms.

Splitting Criteria

The splitting of each node is based on reducing the degree of “impurity” (heterogeneity with respect to the outcome variable) within each node. For example, a node that has no impurity will have a zero error rate labeling its binary outcomes. While CART works well with categorical variables, continuous variables (eg, age) can also be assessed, though only with certain algorithms. Several different splitting criteria exist, each of which attempt to maximize the differences within each child node. While beyond the scope of this review, examples of popular splitting criteria are Gini, entropy, and minimum error.⁵

Stopping Rules

To manage the size of a tree, CART analysis allows for predefined stopping rules to minimize the extent of growth while also establishing a minimal degree of statistical difference between nodes that is considered meaningful. To accomplish this task, two stopping rules are often used. The first defines the minimum number of observations in child, or “terminal,” nodes. The second defines the maximum number of levels a tree may grow, thus allowing the investigator to decide the total number of predictor variables that can define a terminal node. While several other stopping rules exist, these are the most commonly utilized.

Pruning

To avoid missing important associations due to premature stoppage, investigators may use another mechanism to limit tree growth called “pruning.” For pruning, the first step is to grow a considerably large tree that includes many levels or nodes, possibly to the point where there are just a few observations per terminal node. Then, similar to the residual sum of squares in a regression, the investigator can calculate a misclassification cost (ie, goodness of fit) and select the tree with the smallest cost.² Of note, stopping rules and pruning can be used simultaneously.

Classification Error

Similar to other forms of statistical inference it remains important to understand the uncertainty within the inference. In regression modeling, for example, classification errors can be calculated using standard errors of the parameter estimates. In CART analysis, because random samples from a population may produce different trees, measures of variability can be more complicated. One strategy is to generate a tree from a test sample and then use the remaining data to calculate a measure of the misclassification cost (a measure of how much additional accuracy a split must add to the entire tree to warrant the additional complexity). Alternatively, a “k-fold cross-validation” can be performed in which the data is broken down into k subsets from which a tree is created using all data except for one of the subsets. The computed tree is then applied to the remaining subset to determine a misclassification cost. These classification costs are important as they also impact the stopping and pruning processes. Ultimately, a final tree, which best limits classification errors, is selected.

This method can be useful in multiple settings in which an investigator wants to characterize a subpopulation from a larger cohort. Adaptation of this could include, but is not limited to, risk stratification,⁶ diagnostics,⁷ and patient identification for medical interventions.⁸ Moreover, CART analysis has the added benefit of creating visually interpretable predictive models that can be utilized for front-line clinical decision making.^9,10

CART analysis has been shown to have several advantages over other commonly used modeling methods. First, it is a nonparametric model that can handle highly skewed data and does not require that the predictor, or predictors, takes on a predetermined form (allowing them to be constructed from the data). This is helpful as many clinical variables can have wide degrees of variance.

Unlike other modeling techniques, CART can identify higher-order interactions between multiple variables, meaning it can handle interactions that occur whenever one variable affects the nature of an interaction between two other variables. Further, CART can handle multiple correlated independent variables, something logistic regression models classically cannot do.

From a clinical standpoint, the “logic” of the visual-based CART output can be easier to interpret than the probabilistic output (eg, odds ratio) associated with logistic regression modeling, making it more practical, applicable, and easier for clinicians to adopt.^10,12 Finally, CART software is easy to use for those who do not have strong statistical backgrounds, and it is less resource intensive than other statistical methods.²

Despite these features, CART does have several disadvantages. First, due to the ease with which CART analysis can be performed, “data dredging” can be a significant concern. Its ideal use is with a priori consideration of independent variables.² Second, while CART is most beneficial in describing links and cutoffs between variables, it may not be useful for hypothesis testing.² Third, large data sets are needed to perform CART, especially if the investigator is using the split sample approach mentioned above.¹¹ Finally, while CART is the most utilized decision tree methodology, several other types of decision tree methods exist: C4.5, CRUISE, Quick, Unbiased, Efficient Statistical Trees, Chi-square-Automatic-Interaction-Detection, and others. Many of these allow for splitting into more than two groups and have other features that may be more advantageous to one’s analysis.¹³

Decision trees offer simple, interpretable results of multiple factors that can be easily applied to clinical scenarios. In this case, the authors specifically used classification tree analysis to take advantage of CART’s machine-learning ability to consider higher-order interactions to build their model—as they lacked a priori evidence to help guide them in traditional (ie, logistic regression) model construction. Furthermore, CART analysis created an output that logically and visually illustrates which combination of characteristics is most associated with discharge placement and can potentially be utilized to help facilitate discharge planning in future hospitalized patients. To sum up, this machine-learning methodology allowed the investigators to determine which variables taken together were the most suitable in predicting their outcome of interest and present these findings in a manner that busy clinicians can interpret and apply.

Machine-learning is a type of artificial intelligence in which systems automatically learn and improve from experience without being explicitly programmed. Classification and Regression Tree (CART) analysis is a machine-learning algorithm that was developed to visually classify or segment populations into subgroups with similar characteristics and outcomes. CART analysis is a decision tree methodology that was initially developed in the 1960s for use in product marketing.¹ Since then, a number of health disciplines have used it to isolate patient subgroups from larger populations to guide clinical decision-making by better identifying those most likely to benefit.² The clinical utility of CART mirrors how most clinicians think, which is not in terms of coefficients (ie, regression output) but rather in terms of categories or classifications (eg, low vs high risk).

In this issue of the Journal of Hospital Medicine, Young and colleagues use classification trees to predict discharge placement (postacute care facility vs home) based on a patient’s hospital admission characteristics and mobility score. The resulting decision tree indicates that patients with the lowest mobility scores, as well as those 65 years and older, were most likely to be discharged to postacute care facilities.³ In this review, we orient the reader to the basics of CART analysis, discuss important intricacies, and weigh its pros, cons, and application as a statistical tool.

CART is a nonparametric (ie, makes no assumptions about data distribution) statistical tool that identifies subgroups within a population whose members share common characteristics as defined by the independent variables included in the model. CART analysis is unique in that it yields a visual output of the data in the form of a multisegmented structure that resembles the branches of a tree (Figure). CART analysis consists of four basic steps: (1) tree-building (including splitting criteria and estimation of classification error), (2) stopping the tree-building process, (3) tree “pruning,” and (4) tree selection.

In general, CART analysis begins with a single “node” or group, which contains the entire sample population. This is referred to as the “parent node.” The CART procedure simultaneously examines all available independent variables and selects one that results in two groups that are the most distinct with respect to the outcome variable of interest. In Young et al’s example, posthospital discharge placement is the outcome.³ This parent node then branches into two “child nodes” according to the independent variable that was selected. Within each of these “child nodes,” the tree-growing methodology recursively assesses each of the remaining independent variables to determine which will result in the best split according to the chosen splitting criterion.² Each subsequent “child node” will become a “parent node” to the two groups in which it splits. This process is repeated on the data in each subsequent “child node” and is stopped once a predefined stopping point is reached. Notably, while division into two groups is the most common application of CART modeling, there are models that can split data into more than two child nodes.

Since CART outcomes can be heavily dependent on the data being used (eg, electronic health records or administrative data), it is important to attempt to confirm results in a similar, but different, study cohort. Because obtaining separate data sources with similar cohorts can be difficult, many investigators using CART will utilize a “split sample approach” in which study data are split into separate training and validation sets.⁴ In the training set, which frequently comprises two-thirds of the available data, the algorithm is tested in exploratory analysis. Once the algorithm is defined and agreed upon, it is retested within a validation set, constructed from the remaining one-third of data. This approach, which Young et al utilize,³ allows for improved confidence and reduced risk of bias in the findings and allows for some degree of external validation. Further, the split sample approach supports more reliable measures of predictive accuracy: in Young et al’s case, the proportion of correctly classified patients discharged to a postacute care facility (sensitivity: 58%, 95% CI 49-68%) and the proportion of correctly classified patients discharged home (specificity: 84%, 95% CI 78-90%). Despite these advantages, the split sample approach is not universally used.

Classification Versus Regression Trees

While commonly grouped together, CARTs can be distinguished from one another based on the dependent, or outcome, variable. Categorical outcome variables require the use of a classification tree, while continuous outcomes utilize regression trees. Of note, the independent, or predictor, variables can be any combination of categorical or continuous variables. However, splitting at each node creates categorical output when using CART algorithms.

Splitting Criteria

The splitting of each node is based on reducing the degree of “impurity” (heterogeneity with respect to the outcome variable) within each node. For example, a node that has no impurity will have a zero error rate labeling its binary outcomes. While CART works well with categorical variables, continuous variables (eg, age) can also be assessed, though only with certain algorithms. Several different splitting criteria exist, each of which attempt to maximize the differences within each child node. While beyond the scope of this review, examples of popular splitting criteria are Gini, entropy, and minimum error.⁵

Stopping Rules

To manage the size of a tree, CART analysis allows for predefined stopping rules to minimize the extent of growth while also establishing a minimal degree of statistical difference between nodes that is considered meaningful. To accomplish this task, two stopping rules are often used. The first defines the minimum number of observations in child, or “terminal,” nodes. The second defines the maximum number of levels a tree may grow, thus allowing the investigator to decide the total number of predictor variables that can define a terminal node. While several other stopping rules exist, these are the most commonly utilized.

Pruning

To avoid missing important associations due to premature stoppage, investigators may use another mechanism to limit tree growth called “pruning.” For pruning, the first step is to grow a considerably large tree that includes many levels or nodes, possibly to the point where there are just a few observations per terminal node. Then, similar to the residual sum of squares in a regression, the investigator can calculate a misclassification cost (ie, goodness of fit) and select the tree with the smallest cost.² Of note, stopping rules and pruning can be used simultaneously.

Classification Error

Similar to other forms of statistical inference it remains important to understand the uncertainty within the inference. In regression modeling, for example, classification errors can be calculated using standard errors of the parameter estimates. In CART analysis, because random samples from a population may produce different trees, measures of variability can be more complicated. One strategy is to generate a tree from a test sample and then use the remaining data to calculate a measure of the misclassification cost (a measure of how much additional accuracy a split must add to the entire tree to warrant the additional complexity). Alternatively, a “k-fold cross-validation” can be performed in which the data is broken down into k subsets from which a tree is created using all data except for one of the subsets. The computed tree is then applied to the remaining subset to determine a misclassification cost. These classification costs are important as they also impact the stopping and pruning processes. Ultimately, a final tree, which best limits classification errors, is selected.

This method can be useful in multiple settings in which an investigator wants to characterize a subpopulation from a larger cohort. Adaptation of this could include, but is not limited to, risk stratification,⁶ diagnostics,⁷ and patient identification for medical interventions.⁸ Moreover, CART analysis has the added benefit of creating visually interpretable predictive models that can be utilized for front-line clinical decision making.^9,10

CART analysis has been shown to have several advantages over other commonly used modeling methods. First, it is a nonparametric model that can handle highly skewed data and does not require that the predictor, or predictors, takes on a predetermined form (allowing them to be constructed from the data). This is helpful as many clinical variables can have wide degrees of variance.

Unlike other modeling techniques, CART can identify higher-order interactions between multiple variables, meaning it can handle interactions that occur whenever one variable affects the nature of an interaction between two other variables. Further, CART can handle multiple correlated independent variables, something logistic regression models classically cannot do.

From a clinical standpoint, the “logic” of the visual-based CART output can be easier to interpret than the probabilistic output (eg, odds ratio) associated with logistic regression modeling, making it more practical, applicable, and easier for clinicians to adopt.^10,12 Finally, CART software is easy to use for those who do not have strong statistical backgrounds, and it is less resource intensive than other statistical methods.²

Despite these features, CART does have several disadvantages. First, due to the ease with which CART analysis can be performed, “data dredging” can be a significant concern. Its ideal use is with a priori consideration of independent variables.² Second, while CART is most beneficial in describing links and cutoffs between variables, it may not be useful for hypothesis testing.² Third, large data sets are needed to perform CART, especially if the investigator is using the split sample approach mentioned above.¹¹ Finally, while CART is the most utilized decision tree methodology, several other types of decision tree methods exist: C4.5, CRUISE, Quick, Unbiased, Efficient Statistical Trees, Chi-square-Automatic-Interaction-Detection, and others. Many of these allow for splitting into more than two groups and have other features that may be more advantageous to one’s analysis.¹³

Decision trees offer simple, interpretable results of multiple factors that can be easily applied to clinical scenarios. In this case, the authors specifically used classification tree analysis to take advantage of CART’s machine-learning ability to consider higher-order interactions to build their model—as they lacked a priori evidence to help guide them in traditional (ie, logistic regression) model construction. Furthermore, CART analysis created an output that logically and visually illustrates which combination of characteristics is most associated with discharge placement and can potentially be utilized to help facilitate discharge planning in future hospitalized patients. To sum up, this machine-learning methodology allowed the investigators to determine which variables taken together were the most suitable in predicting their outcome of interest and present these findings in a manner that busy clinicians can interpret and apply.

Machine-learning is a type of artificial intelligence in which systems automatically learn and improve from experience without being explicitly programmed. Classification and Regression Tree (CART) analysis is a machine-learning algorithm that was developed to visually classify or segment populations into subgroups with similar characteristics and outcomes. CART analysis is a decision tree methodology that was initially developed in the 1960s for use in product marketing.¹ Since then, a number of health disciplines have used it to isolate patient subgroups from larger populations to guide clinical decision-making by better identifying those most likely to benefit.² The clinical utility of CART mirrors how most clinicians think, which is not in terms of coefficients (ie, regression output) but rather in terms of categories or classifications (eg, low vs high risk).

In this issue of the Journal of Hospital Medicine, Young and colleagues use classification trees to predict discharge placement (postacute care facility vs home) based on a patient’s hospital admission characteristics and mobility score. The resulting decision tree indicates that patients with the lowest mobility scores, as well as those 65 years and older, were most likely to be discharged to postacute care facilities.³ In this review, we orient the reader to the basics of CART analysis, discuss important intricacies, and weigh its pros, cons, and application as a statistical tool.

CART is a nonparametric (ie, makes no assumptions about data distribution) statistical tool that identifies subgroups within a population whose members share common characteristics as defined by the independent variables included in the model. CART analysis is unique in that it yields a visual output of the data in the form of a multisegmented structure that resembles the branches of a tree (Figure). CART analysis consists of four basic steps: (1) tree-building (including splitting criteria and estimation of classification error), (2) stopping the tree-building process, (3) tree “pruning,” and (4) tree selection.

In general, CART analysis begins with a single “node” or group, which contains the entire sample population. This is referred to as the “parent node.” The CART procedure simultaneously examines all available independent variables and selects one that results in two groups that are the most distinct with respect to the outcome variable of interest. In Young et al’s example, posthospital discharge placement is the outcome.³ This parent node then branches into two “child nodes” according to the independent variable that was selected. Within each of these “child nodes,” the tree-growing methodology recursively assesses each of the remaining independent variables to determine which will result in the best split according to the chosen splitting criterion.² Each subsequent “child node” will become a “parent node” to the two groups in which it splits. This process is repeated on the data in each subsequent “child node” and is stopped once a predefined stopping point is reached. Notably, while division into two groups is the most common application of CART modeling, there are models that can split data into more than two child nodes.

Since CART outcomes can be heavily dependent on the data being used (eg, electronic health records or administrative data), it is important to attempt to confirm results in a similar, but different, study cohort. Because obtaining separate data sources with similar cohorts can be difficult, many investigators using CART will utilize a “split sample approach” in which study data are split into separate training and validation sets.⁴ In the training set, which frequently comprises two-thirds of the available data, the algorithm is tested in exploratory analysis. Once the algorithm is defined and agreed upon, it is retested within a validation set, constructed from the remaining one-third of data. This approach, which Young et al utilize,³ allows for improved confidence and reduced risk of bias in the findings and allows for some degree of external validation. Further, the split sample approach supports more reliable measures of predictive accuracy: in Young et al’s case, the proportion of correctly classified patients discharged to a postacute care facility (sensitivity: 58%, 95% CI 49-68%) and the proportion of correctly classified patients discharged home (specificity: 84%, 95% CI 78-90%). Despite these advantages, the split sample approach is not universally used.

Classification Versus Regression Trees

While commonly grouped together, CARTs can be distinguished from one another based on the dependent, or outcome, variable. Categorical outcome variables require the use of a classification tree, while continuous outcomes utilize regression trees. Of note, the independent, or predictor, variables can be any combination of categorical or continuous variables. However, splitting at each node creates categorical output when using CART algorithms.

Splitting Criteria

The splitting of each node is based on reducing the degree of “impurity” (heterogeneity with respect to the outcome variable) within each node. For example, a node that has no impurity will have a zero error rate labeling its binary outcomes. While CART works well with categorical variables, continuous variables (eg, age) can also be assessed, though only with certain algorithms. Several different splitting criteria exist, each of which attempt to maximize the differences within each child node. While beyond the scope of this review, examples of popular splitting criteria are Gini, entropy, and minimum error.⁵

Stopping Rules

To manage the size of a tree, CART analysis allows for predefined stopping rules to minimize the extent of growth while also establishing a minimal degree of statistical difference between nodes that is considered meaningful. To accomplish this task, two stopping rules are often used. The first defines the minimum number of observations in child, or “terminal,” nodes. The second defines the maximum number of levels a tree may grow, thus allowing the investigator to decide the total number of predictor variables that can define a terminal node. While several other stopping rules exist, these are the most commonly utilized.

Pruning

To avoid missing important associations due to premature stoppage, investigators may use another mechanism to limit tree growth called “pruning.” For pruning, the first step is to grow a considerably large tree that includes many levels or nodes, possibly to the point where there are just a few observations per terminal node. Then, similar to the residual sum of squares in a regression, the investigator can calculate a misclassification cost (ie, goodness of fit) and select the tree with the smallest cost.² Of note, stopping rules and pruning can be used simultaneously.

Classification Error

Similar to other forms of statistical inference it remains important to understand the uncertainty within the inference. In regression modeling, for example, classification errors can be calculated using standard errors of the parameter estimates. In CART analysis, because random samples from a population may produce different trees, measures of variability can be more complicated. One strategy is to generate a tree from a test sample and then use the remaining data to calculate a measure of the misclassification cost (a measure of how much additional accuracy a split must add to the entire tree to warrant the additional complexity). Alternatively, a “k-fold cross-validation” can be performed in which the data is broken down into k subsets from which a tree is created using all data except for one of the subsets. The computed tree is then applied to the remaining subset to determine a misclassification cost. These classification costs are important as they also impact the stopping and pruning processes. Ultimately, a final tree, which best limits classification errors, is selected.

This method can be useful in multiple settings in which an investigator wants to characterize a subpopulation from a larger cohort. Adaptation of this could include, but is not limited to, risk stratification,⁶ diagnostics,⁷ and patient identification for medical interventions.⁸ Moreover, CART analysis has the added benefit of creating visually interpretable predictive models that can be utilized for front-line clinical decision making.^9,10

CART analysis has been shown to have several advantages over other commonly used modeling methods. First, it is a nonparametric model that can handle highly skewed data and does not require that the predictor, or predictors, takes on a predetermined form (allowing them to be constructed from the data). This is helpful as many clinical variables can have wide degrees of variance.

Unlike other modeling techniques, CART can identify higher-order interactions between multiple variables, meaning it can handle interactions that occur whenever one variable affects the nature of an interaction between two other variables. Further, CART can handle multiple correlated independent variables, something logistic regression models classically cannot do.

From a clinical standpoint, the “logic” of the visual-based CART output can be easier to interpret than the probabilistic output (eg, odds ratio) associated with logistic regression modeling, making it more practical, applicable, and easier for clinicians to adopt.^10,12 Finally, CART software is easy to use for those who do not have strong statistical backgrounds, and it is less resource intensive than other statistical methods.²

Despite these features, CART does have several disadvantages. First, due to the ease with which CART analysis can be performed, “data dredging” can be a significant concern. Its ideal use is with a priori consideration of independent variables.² Second, while CART is most beneficial in describing links and cutoffs between variables, it may not be useful for hypothesis testing.² Third, large data sets are needed to perform CART, especially if the investigator is using the split sample approach mentioned above.¹¹ Finally, while CART is the most utilized decision tree methodology, several other types of decision tree methods exist: C4.5, CRUISE, Quick, Unbiased, Efficient Statistical Trees, Chi-square-Automatic-Interaction-Detection, and others. Many of these allow for splitting into more than two groups and have other features that may be more advantageous to one’s analysis.¹³

Decision trees offer simple, interpretable results of multiple factors that can be easily applied to clinical scenarios. In this case, the authors specifically used classification tree analysis to take advantage of CART’s machine-learning ability to consider higher-order interactions to build their model—as they lacked a priori evidence to help guide them in traditional (ie, logistic regression) model construction. Furthermore, CART analysis created an output that logically and visually illustrates which combination of characteristics is most associated with discharge placement and can potentially be utilized to help facilitate discharge planning in future hospitalized patients. To sum up, this machine-learning methodology allowed the investigators to determine which variables taken together were the most suitable in predicting their outcome of interest and present these findings in a manner that busy clinicians can interpret and apply.

Over the last 15 years, studies have demonstrated the efficacy of small-bore chest tubes (SBCTs), or pigtail catheters (PCs, most commonly ≤14 French), in treating pneumothorax (PTX),^1-5 traumatic hemothorax (THTX), hemopneumothorax (HPTX),^6,7 parapneumonic effusions (PPEs),^8,9 pleural infections,¹⁰ and symptomatic malignant pleural effusions.¹¹ A randomized, controlled trial also showed that PC placement resulted in better pain scores, compared with large-bore chest tubes (LBCTs), for traumatic PTX.⁵ The British Thoracic Society does state that LBCTs may be needed for PTXs with very large air leaks, especially postoperatively. Further, LBCTs may be indicated if small-bore drainage fails, but otherwise they recommend PCs as first-line therapy for PTX, free flowing pleural effusions, and pleural infections.¹²

The Medical College of Wisconsin (MCW) provides hospitalist services to Froedtert Hospital, a large, tertiary care, teaching hospital in Milwaukee, Wisconsin. A subset of hospitalists started the bedside procedure service (BPS) in 2013. The BPS initially performed procedures within the traditional scope of internal medicine–trained physicians (eg, thoracentesis, paracentesis, lumbar puncture, and arthrocentesis). Because of hospital need, the BPS began to include procedures not traditionally performed by hospitalists, including bone marrow biopsies and nontunneled central access venous catheters. With the service’s low complication rate and high volume of procedures, it was sought by cardiothoracic (CT) surgery services to assist in PC placement as an alternative to interventional radiology (IR).

BPS Pigtail Catheter Training

CT surgery initially trained the BPS director in PC placement using the Seldinger technique in 2015. The director’s training period with CT surgery included direct observation by CT surgery providers for 5 PC placements. Prior to placing PCs, the director had performed approximately 400 ultrasound-guided thoracenteses. The BPS director then independently trained the remaining BPS and has placed or supervised over half of the service’s 124 PCs. Initial credentialing for each BPS physician requires 5 PC placements and 20 thoracenteses under direct supervision of credentialed BPS members. Credentialing is maintained by BPS physicians completing 3 PCs and 15 thoracenteses per year.

Newly credentialed providers are capable of independently placing most PCs. However, the requirements for credentialing are minimal and newly credentialed physicians still encounter PC placements with challenging factors not addressed in their training, such as anterior approach, small effusions, atypical effusion location, mild to moderate coagulopathy, recent therapeutic anticoagulation, and large body habitus. To address these challenges, the BPS has instituted an “on call” system. This system is typically staffed by the BPS director or associate director, already attending on a separate medical service. When needed, the “on call” physician will supervise the newer BPS members to ensure safety while the less experienced physician places the PC. Although rare, if an “on call” member is not available, then it is the practice of the BPS to recommend IR for PC placement.

BPS Operation

Daily BPS operation consists of one attending hospitalist, two internal medicine residents, and a third-year medical student. PCs are placed primarily (95%) by the attending on service under ultrasound guidance using the Seldinger technique with lidocaine for anesthetic. For all PC consults, the attending BPS physician reviews the indication prior to placement. If not a direct consult from surgical services, most PC consults are appropriate referrals to the service after the primary medicine service has consulted CT-surgery or p ulmonary consult teams. After review, the primary role of the BPS is assessing safety of PC placement, including whether the patient can tolerate PC placement without procedural sedation. The BPS’s additional standards for safe PC placement are listed in Table 1.

Additionally, it is not routine practice of the BPS to recommend PC placement when consulted for a thoracentesis. The exception to this rule is patients whose PPE sonographic imaging demonstrates loculation or septations. This is consistent with the latest review on pleural disease.¹³ In addition, the institution’s CT surgery services prefer to initially treat septated PPEs with PCs and fibrinolytic therapy rather than immediate video-assisted thoracoscopic surgery (VATS).

The BPS operates a partnership with CT surgery in which, after successful PC placement, CT surgery manages the PC immediately and until removal including the negative pressure applied and need for fibrinolytic therapy. CT surgery also determines if secondary therapy, commonly second PC or VATS, is required. After PC placement, a portable chest x-ray (CXR) is taken and then BPS follows the patient in person the following day to note any insertion-related complications (IRCs).

In this paper, data on the consults to the BPS for PC placement over a 2-year period are presented. Primary outcomes included numbers of and indications for PCs consulted—attempted or not attempted—consulting services, IRCs, unsuccessful attempts (UAs), and adverse outcomes (AOs). PC duration, fluid drainage, need for fibrinolytic therapy, or need for secondary therapy were not measured because these decisions were managed by the CT surgery service.

Institutional review board approval of this retrospective study was granted by MCW/Froedtert Hospital Institutional Review Board #5 on January 14, 2019 (MCW IRB #PRO00033496). Adult patients hospitalized at Froedtert Hospital whose primary team determined they would clinically benefit from a PC and consulted the BPS service for placement were included. There were no exclusion criteria.

The authors conducted a retrospective review of two secure BPS databases. The first database is a record of all procedure consults, while the second database contains information about all attempted PCs. Initial review of the BPS’s consult database found 142 PC consults. Consults were classified as “declined” or “attempted.” In addition to the database comparison, the authors performed a manual chart review on patients with documented complications (n = 6) to clarify sequela, those with unclear PC indication (n = 2), and to resolve the discrepancies between our two databases (n = 3). Finally, a brief chart review was performed to review procedures in the subsequent 48 hours after a declined PC consult (n = 18).

Complications fell into two categories, IRCs and UAs. IRCs were defined as unintentional PC placement into a location other than the pleural space or PC placement that resulted in an AO according to the judgement of the attending BPS physician. A UA was defined as an unsuccessfully attempted PC placement, with the BPS unable to pass a PC in the pleural space for any reason. An AO was defined as any escalation of care that could be related to the procedure within 24 hours of attempt/placement found in our databases and/or manual chart review (eg, emergent intubation, surgery, death).

Over a 2-year period, the BPS was consulted to place 142 PCs. After resolution of the 3 discrepancies, total consults remained 142, PC attempts totaled 124 (87.3%), and declined consults totaled 18 (12.7%).

The 18 declined consults were not performed for reasons relating to procedural safety. These included 15 (83.3%) for insufficient fluid depth, 1 (5.6%) poor window for PTX, and 1 (5.6%) patient unstable per BPS attending judgement. One (5.6%) final consult had a previous drain in same hemithorax that resumed functioning.

The manual chart review of procedures performed 48 hours after declined PC consults found only 3 of 17 (17.6%) patients received a PC within the subsequent 48 hours. The 18th patient was unable to be followed in our electronic medical record because his medical record number was recorded incorrectly.

The remaining 124 consults were deemed safe for PC placement. Indications for PC placement varied; the most common indications were complicated effusion (36.3%), large or recurrent effusions (21.8%), PTX (17%), and hemothorax (HTX; 17%). The most common teams who consulted the BPS for PC were medicine/hospitalists (42.7%) and CT surgery (40.3%).

There were 3 IRCs (Table 2) out of 124 attempted consults (2.4%). Of these cases, 2 patients had AOs. IRC patient No. 1 required a PC for PTX and developed a hemothorax from a right-sided mammary artery laceration. Emergent operative measures were taken, but unfortunately the patient died. IRC patient No. 2 was septic from pneumonia when a PC was placed for a complicated PPE. Unfortunately, the patient went into respiratory failure and required intubation. The postintubation computed tomography scan did note that the PC placed by the BPS likely terminated in the lower lobe of the right lung but without PTX. After a new PC was placed by IR, the patient received antibiotics, 3 days of ventilator support, and was discharged home. The authors believe that sepsis from pneumonia was the more probable cause of the respiratory failure in IRC patient No. 2 instead of the PC placement.

To our knowledge, this is the first report of the experience of procedure-focused hospitalists with PC placement in a partnership with CT surgery. We believe that, at high volume, tertiary care centers similar to Froedtert Hospital, internal medicine–trained, procedure-focused hospitalists can serve as adjuncts to surgery, pulmonary, and IR services in the placement of PCs in hospitalized patients that do not require procedural sedation.

Given the development of this service and the nature of its shared operations with CT surgery, we do not believe that the BPS has an appropriate comparison in the literature; however, the IRCs are similar to previous papers describing PC placement.^5-7,14 Notably, the IRC and AO rates were low, both 2.4%, which indicates safe placement of PCs. Kulvatunyou et al and Bauman et al reported on PC placement from a surgical perspective and reported IRC rates of 4%-10%.^5-7,14 These higher IRC rates likely have a few reasons. First, Kulvatunyou et al and Bauman et al did not use ultrasound guidance. Use of ultrasound guidance may have significantly lowered their IRC rate. Second, the definition of IRC used by Kulvatunyou et al and Bauman et al included dislodgements, but we do not believe this to be an IRC. Dislodgements can happen for several reasons, frequently a result of patient movement or forgetfulness, not because of improper placement. Third, the PCs with this BPS are placed primarily by attending physicians. Resident roles on our BPS in PC placement are primarily as assistants, whereas Kulvatunyou et al and Bauman et al note that both attendings and residents, under attending supervision, placed PCs; however, it is not clear what percentage of PCs were placed by attendings or residents in their studies. Finally, this BPS’s IRCs are self-reported, so they could be perceived as falsely low, but given the small number of physicians involved in the group and its standardized follow-up, we do not suspect this is truly contributing to the low rates.

Other complication rates regarding the use of wire-guided SBCTs and PCs range from 0% to 42%^15-20; however, several differences including tube size, physician training, and PC indication make these studies imperfect comparisons. The most notable difference in our opinion is the variable definition, or lack of definition, of a complication. One study did not define their complications,¹⁹ while other studies list subjective measures like pain,^16,20 cough,¹⁶ bleeding, ^16,20 and hematomas^4,15 as complications. We believe that the lack of consensus definition for PC complication or IRC contributes to the large range of complication rates in the literature. This problem is likely not unique to PC placement, but is instead true across all bedside procedures. In a shared-practice model between hospitalists and CT surgeons, we believe the definition of IRC in this paper is adequate in capturing most complications. The only complication we are currently unable to track well is infection. We consider other items discussed previously, such as pain, cough (often from lung re-expansion), minor bleeding, and even small hematomas, to be a part of the procedure and not a complication.

Finally, regarding the IRCs and associated death, this was a tragic event. Complications for all of the BPS’s procedures are infrequent (0.35% over the same time period) and reviewed between the BPS director and the attending who performed the procedure; in addition, given this mortality, the case was reviewed immediately in detail with our CT surgery colleagues. On review, it was easy to determine that the operator had found a clear lung tip and sonographic signs of PTX; however, CXR review did demonstrate a medial placement of the PC. This was judged to be a poor placement location (even with imaging demonstrating PTX in that area) given the well-known “triangle of safety” defined by the British Thoracic Society.¹²

After review, the primary emphasis for PC placement was safe location. The BPS now strives to place PCs for PTX only in the “triangle of safety.” The BPS believe that most PTXs can be addressed with this placement. In the rare case of a PTX requiring an anterior approach, only the BPS director currently places apical PCs for PTX while on service or “on call.” He discusses the placement with pulmonary and CT surgery directly to determine that the PC is of absolute necessity.

Given the focus on appropriate location, no formal changes were made to the procedural imaging practice described in Table 1. We realize that vascular imaging would seem necessary after this patient’s mammary artery laceration; however, safe location, in addition to the BPS’s current image requirements, is believed to minimize this risk. We feel the imaging criteria align with recommendation No. 5 of the Society of Hospital Medicine’s Position Statement for Ultrasound Guidance for Adult Thoracentesis.²¹ Some BPS members use vascular ultrasound imaging to confirm absence of vascularity, but it is not required and occasionally not possible, such as in the occasional case of PTX with subcutaneous emphysema.

The UA rate is low without a natural comparator in the literature. It is important to clarify the difference between the UAs and the frequently mentioned “failure rate” (FR) in Kulvatunyou et al and Bauman et al^6,7,14 We classify UAs as the inability, for any reason, to access the pleural space and insert a PC. At this stage, these UAs appear to reflect the service’s new experience with PC placement and inability to provide procedural sedation. Kulvatunyou et al and Bauman et al’s FR is defined as an initial PC successfully placed into the pleural space that then required a second PC or intervention (frequently VATS) to resolve the PTX or retained HTX.

We believe calculating the failure rate will be helpful in demonstrating the value of our BPS and our shared-practice model. We look forward to publishing this and other future research, including determination of the cost and time saved by the BPS for PCs and other procedures.

Limitations of this study include its retrospective nature, results from a single center’s experience, and lack of a comparison group.

Our institution feels that there is great benefit in having a BPS operated by procedure-focused hospitalists. It would also be important to determine if our model can be replicated by another institution.

Acknowledgments

The authors thank CT surgery for helping to develop this shared-practice model and to both CT surgery and IR physicians here at the Medical College of Wisconsin and Froedtert Hospital who assist us with both IRCs and UAs of pigtail catheters.

The authors also thank Dr. Ricardo Franco-Sadud for his oversight and thoughtful improvements to the paper.

Over the last 15 years, studies have demonstrated the efficacy of small-bore chest tubes (SBCTs), or pigtail catheters (PCs, most commonly ≤14 French), in treating pneumothorax (PTX),^1-5 traumatic hemothorax (THTX), hemopneumothorax (HPTX),^6,7 parapneumonic effusions (PPEs),^8,9 pleural infections,¹⁰ and symptomatic malignant pleural effusions.¹¹ A randomized, controlled trial also showed that PC placement resulted in better pain scores, compared with large-bore chest tubes (LBCTs), for traumatic PTX.⁵ The British Thoracic Society does state that LBCTs may be needed for PTXs with very large air leaks, especially postoperatively. Further, LBCTs may be indicated if small-bore drainage fails, but otherwise they recommend PCs as first-line therapy for PTX, free flowing pleural effusions, and pleural infections.¹²

The Medical College of Wisconsin (MCW) provides hospitalist services to Froedtert Hospital, a large, tertiary care, teaching hospital in Milwaukee, Wisconsin. A subset of hospitalists started the bedside procedure service (BPS) in 2013. The BPS initially performed procedures within the traditional scope of internal medicine–trained physicians (eg, thoracentesis, paracentesis, lumbar puncture, and arthrocentesis). Because of hospital need, the BPS began to include procedures not traditionally performed by hospitalists, including bone marrow biopsies and nontunneled central access venous catheters. With the service’s low complication rate and high volume of procedures, it was sought by cardiothoracic (CT) surgery services to assist in PC placement as an alternative to interventional radiology (IR).

BPS Pigtail Catheter Training

CT surgery initially trained the BPS director in PC placement using the Seldinger technique in 2015. The director’s training period with CT surgery included direct observation by CT surgery providers for 5 PC placements. Prior to placing PCs, the director had performed approximately 400 ultrasound-guided thoracenteses. The BPS director then independently trained the remaining BPS and has placed or supervised over half of the service’s 124 PCs. Initial credentialing for each BPS physician requires 5 PC placements and 20 thoracenteses under direct supervision of credentialed BPS members. Credentialing is maintained by BPS physicians completing 3 PCs and 15 thoracenteses per year.

Newly credentialed providers are capable of independently placing most PCs. However, the requirements for credentialing are minimal and newly credentialed physicians still encounter PC placements with challenging factors not addressed in their training, such as anterior approach, small effusions, atypical effusion location, mild to moderate coagulopathy, recent therapeutic anticoagulation, and large body habitus. To address these challenges, the BPS has instituted an “on call” system. This system is typically staffed by the BPS director or associate director, already attending on a separate medical service. When needed, the “on call” physician will supervise the newer BPS members to ensure safety while the less experienced physician places the PC. Although rare, if an “on call” member is not available, then it is the practice of the BPS to recommend IR for PC placement.

BPS Operation

Daily BPS operation consists of one attending hospitalist, two internal medicine residents, and a third-year medical student. PCs are placed primarily (95%) by the attending on service under ultrasound guidance using the Seldinger technique with lidocaine for anesthetic. For all PC consults, the attending BPS physician reviews the indication prior to placement. If not a direct consult from surgical services, most PC consults are appropriate referrals to the service after the primary medicine service has consulted CT-surgery or p ulmonary consult teams. After review, the primary role of the BPS is assessing safety of PC placement, including whether the patient can tolerate PC placement without procedural sedation. The BPS’s additional standards for safe PC placement are listed in Table 1.

Additionally, it is not routine practice of the BPS to recommend PC placement when consulted for a thoracentesis. The exception to this rule is patients whose PPE sonographic imaging demonstrates loculation or septations. This is consistent with the latest review on pleural disease.¹³ In addition, the institution’s CT surgery services prefer to initially treat septated PPEs with PCs and fibrinolytic therapy rather than immediate video-assisted thoracoscopic surgery (VATS).

The BPS operates a partnership with CT surgery in which, after successful PC placement, CT surgery manages the PC immediately and until removal including the negative pressure applied and need for fibrinolytic therapy. CT surgery also determines if secondary therapy, commonly second PC or VATS, is required. After PC placement, a portable chest x-ray (CXR) is taken and then BPS follows the patient in person the following day to note any insertion-related complications (IRCs).

In this paper, data on the consults to the BPS for PC placement over a 2-year period are presented. Primary outcomes included numbers of and indications for PCs consulted—attempted or not attempted—consulting services, IRCs, unsuccessful attempts (UAs), and adverse outcomes (AOs). PC duration, fluid drainage, need for fibrinolytic therapy, or need for secondary therapy were not measured because these decisions were managed by the CT surgery service.

Institutional review board approval of this retrospective study was granted by MCW/Froedtert Hospital Institutional Review Board #5 on January 14, 2019 (MCW IRB #PRO00033496). Adult patients hospitalized at Froedtert Hospital whose primary team determined they would clinically benefit from a PC and consulted the BPS service for placement were included. There were no exclusion criteria.

The authors conducted a retrospective review of two secure BPS databases. The first database is a record of all procedure consults, while the second database contains information about all attempted PCs. Initial review of the BPS’s consult database found 142 PC consults. Consults were classified as “declined” or “attempted.” In addition to the database comparison, the authors performed a manual chart review on patients with documented complications (n = 6) to clarify sequela, those with unclear PC indication (n = 2), and to resolve the discrepancies between our two databases (n = 3). Finally, a brief chart review was performed to review procedures in the subsequent 48 hours after a declined PC consult (n = 18).

Complications fell into two categories, IRCs and UAs. IRCs were defined as unintentional PC placement into a location other than the pleural space or PC placement that resulted in an AO according to the judgement of the attending BPS physician. A UA was defined as an unsuccessfully attempted PC placement, with the BPS unable to pass a PC in the pleural space for any reason. An AO was defined as any escalation of care that could be related to the procedure within 24 hours of attempt/placement found in our databases and/or manual chart review (eg, emergent intubation, surgery, death).

Over a 2-year period, the BPS was consulted to place 142 PCs. After resolution of the 3 discrepancies, total consults remained 142, PC attempts totaled 124 (87.3%), and declined consults totaled 18 (12.7%).

The 18 declined consults were not performed for reasons relating to procedural safety. These included 15 (83.3%) for insufficient fluid depth, 1 (5.6%) poor window for PTX, and 1 (5.6%) patient unstable per BPS attending judgement. One (5.6%) final consult had a previous drain in same hemithorax that resumed functioning.

The manual chart review of procedures performed 48 hours after declined PC consults found only 3 of 17 (17.6%) patients received a PC within the subsequent 48 hours. The 18th patient was unable to be followed in our electronic medical record because his medical record number was recorded incorrectly.

The remaining 124 consults were deemed safe for PC placement. Indications for PC placement varied; the most common indications were complicated effusion (36.3%), large or recurrent effusions (21.8%), PTX (17%), and hemothorax (HTX; 17%). The most common teams who consulted the BPS for PC were medicine/hospitalists (42.7%) and CT surgery (40.3%).

There were 3 IRCs (Table 2) out of 124 attempted consults (2.4%). Of these cases, 2 patients had AOs. IRC patient No. 1 required a PC for PTX and developed a hemothorax from a right-sided mammary artery laceration. Emergent operative measures were taken, but unfortunately the patient died. IRC patient No. 2 was septic from pneumonia when a PC was placed for a complicated PPE. Unfortunately, the patient went into respiratory failure and required intubation. The postintubation computed tomography scan did note that the PC placed by the BPS likely terminated in the lower lobe of the right lung but without PTX. After a new PC was placed by IR, the patient received antibiotics, 3 days of ventilator support, and was discharged home. The authors believe that sepsis from pneumonia was the more probable cause of the respiratory failure in IRC patient No. 2 instead of the PC placement.

To our knowledge, this is the first report of the experience of procedure-focused hospitalists with PC placement in a partnership with CT surgery. We believe that, at high volume, tertiary care centers similar to Froedtert Hospital, internal medicine–trained, procedure-focused hospitalists can serve as adjuncts to surgery, pulmonary, and IR services in the placement of PCs in hospitalized patients that do not require procedural sedation.

Given the development of this service and the nature of its shared operations with CT surgery, we do not believe that the BPS has an appropriate comparison in the literature; however, the IRCs are similar to previous papers describing PC placement.^5-7,14 Notably, the IRC and AO rates were low, both 2.4%, which indicates safe placement of PCs. Kulvatunyou et al and Bauman et al reported on PC placement from a surgical perspective and reported IRC rates of 4%-10%.^5-7,14 These higher IRC rates likely have a few reasons. First, Kulvatunyou et al and Bauman et al did not use ultrasound guidance. Use of ultrasound guidance may have significantly lowered their IRC rate. Second, the definition of IRC used by Kulvatunyou et al and Bauman et al included dislodgements, but we do not believe this to be an IRC. Dislodgements can happen for several reasons, frequently a result of patient movement or forgetfulness, not because of improper placement. Third, the PCs with this BPS are placed primarily by attending physicians. Resident roles on our BPS in PC placement are primarily as assistants, whereas Kulvatunyou et al and Bauman et al note that both attendings and residents, under attending supervision, placed PCs; however, it is not clear what percentage of PCs were placed by attendings or residents in their studies. Finally, this BPS’s IRCs are self-reported, so they could be perceived as falsely low, but given the small number of physicians involved in the group and its standardized follow-up, we do not suspect this is truly contributing to the low rates.

Other complication rates regarding the use of wire-guided SBCTs and PCs range from 0% to 42%^15-20; however, several differences including tube size, physician training, and PC indication make these studies imperfect comparisons. The most notable difference in our opinion is the variable definition, or lack of definition, of a complication. One study did not define their complications,¹⁹ while other studies list subjective measures like pain,^16,20 cough,¹⁶ bleeding, ^16,20 and hematomas^4,15 as complications. We believe that the lack of consensus definition for PC complication or IRC contributes to the large range of complication rates in the literature. This problem is likely not unique to PC placement, but is instead true across all bedside procedures. In a shared-practice model between hospitalists and CT surgeons, we believe the definition of IRC in this paper is adequate in capturing most complications. The only complication we are currently unable to track well is infection. We consider other items discussed previously, such as pain, cough (often from lung re-expansion), minor bleeding, and even small hematomas, to be a part of the procedure and not a complication.

Finally, regarding the IRCs and associated death, this was a tragic event. Complications for all of the BPS’s procedures are infrequent (0.35% over the same time period) and reviewed between the BPS director and the attending who performed the procedure; in addition, given this mortality, the case was reviewed immediately in detail with our CT surgery colleagues. On review, it was easy to determine that the operator had found a clear lung tip and sonographic signs of PTX; however, CXR review did demonstrate a medial placement of the PC. This was judged to be a poor placement location (even with imaging demonstrating PTX in that area) given the well-known “triangle of safety” defined by the British Thoracic Society.¹²

After review, the primary emphasis for PC placement was safe location. The BPS now strives to place PCs for PTX only in the “triangle of safety.” The BPS believe that most PTXs can be addressed with this placement. In the rare case of a PTX requiring an anterior approach, only the BPS director currently places apical PCs for PTX while on service or “on call.” He discusses the placement with pulmonary and CT surgery directly to determine that the PC is of absolute necessity.

Given the focus on appropriate location, no formal changes were made to the procedural imaging practice described in Table 1. We realize that vascular imaging would seem necessary after this patient’s mammary artery laceration; however, safe location, in addition to the BPS’s current image requirements, is believed to minimize this risk. We feel the imaging criteria align with recommendation No. 5 of the Society of Hospital Medicine’s Position Statement for Ultrasound Guidance for Adult Thoracentesis.²¹ Some BPS members use vascular ultrasound imaging to confirm absence of vascularity, but it is not required and occasionally not possible, such as in the occasional case of PTX with subcutaneous emphysema.

The UA rate is low without a natural comparator in the literature. It is important to clarify the difference between the UAs and the frequently mentioned “failure rate” (FR) in Kulvatunyou et al and Bauman et al^6,7,14 We classify UAs as the inability, for any reason, to access the pleural space and insert a PC. At this stage, these UAs appear to reflect the service’s new experience with PC placement and inability to provide procedural sedation. Kulvatunyou et al and Bauman et al’s FR is defined as an initial PC successfully placed into the pleural space that then required a second PC or intervention (frequently VATS) to resolve the PTX or retained HTX.

We believe calculating the failure rate will be helpful in demonstrating the value of our BPS and our shared-practice model. We look forward to publishing this and other future research, including determination of the cost and time saved by the BPS for PCs and other procedures.

Limitations of this study include its retrospective nature, results from a single center’s experience, and lack of a comparison group.

Our institution feels that there is great benefit in having a BPS operated by procedure-focused hospitalists. It would also be important to determine if our model can be replicated by another institution.

Acknowledgments

The authors thank CT surgery for helping to develop this shared-practice model and to both CT surgery and IR physicians here at the Medical College of Wisconsin and Froedtert Hospital who assist us with both IRCs and UAs of pigtail catheters.

The authors also thank Dr. Ricardo Franco-Sadud for his oversight and thoughtful improvements to the paper.

Over the last 15 years, studies have demonstrated the efficacy of small-bore chest tubes (SBCTs), or pigtail catheters (PCs, most commonly ≤14 French), in treating pneumothorax (PTX),^1-5 traumatic hemothorax (THTX), hemopneumothorax (HPTX),^6,7 parapneumonic effusions (PPEs),^8,9 pleural infections,¹⁰ and symptomatic malignant pleural effusions.¹¹ A randomized, controlled trial also showed that PC placement resulted in better pain scores, compared with large-bore chest tubes (LBCTs), for traumatic PTX.⁵ The British Thoracic Society does state that LBCTs may be needed for PTXs with very large air leaks, especially postoperatively. Further, LBCTs may be indicated if small-bore drainage fails, but otherwise they recommend PCs as first-line therapy for PTX, free flowing pleural effusions, and pleural infections.¹²

The Medical College of Wisconsin (MCW) provides hospitalist services to Froedtert Hospital, a large, tertiary care, teaching hospital in Milwaukee, Wisconsin. A subset of hospitalists started the bedside procedure service (BPS) in 2013. The BPS initially performed procedures within the traditional scope of internal medicine–trained physicians (eg, thoracentesis, paracentesis, lumbar puncture, and arthrocentesis). Because of hospital need, the BPS began to include procedures not traditionally performed by hospitalists, including bone marrow biopsies and nontunneled central access venous catheters. With the service’s low complication rate and high volume of procedures, it was sought by cardiothoracic (CT) surgery services to assist in PC placement as an alternative to interventional radiology (IR).

BPS Pigtail Catheter Training

CT surgery initially trained the BPS director in PC placement using the Seldinger technique in 2015. The director’s training period with CT surgery included direct observation by CT surgery providers for 5 PC placements. Prior to placing PCs, the director had performed approximately 400 ultrasound-guided thoracenteses. The BPS director then independently trained the remaining BPS and has placed or supervised over half of the service’s 124 PCs. Initial credentialing for each BPS physician requires 5 PC placements and 20 thoracenteses under direct supervision of credentialed BPS members. Credentialing is maintained by BPS physicians completing 3 PCs and 15 thoracenteses per year.

Newly credentialed providers are capable of independently placing most PCs. However, the requirements for credentialing are minimal and newly credentialed physicians still encounter PC placements with challenging factors not addressed in their training, such as anterior approach, small effusions, atypical effusion location, mild to moderate coagulopathy, recent therapeutic anticoagulation, and large body habitus. To address these challenges, the BPS has instituted an “on call” system. This system is typically staffed by the BPS director or associate director, already attending on a separate medical service. When needed, the “on call” physician will supervise the newer BPS members to ensure safety while the less experienced physician places the PC. Although rare, if an “on call” member is not available, then it is the practice of the BPS to recommend IR for PC placement.

BPS Operation

Daily BPS operation consists of one attending hospitalist, two internal medicine residents, and a third-year medical student. PCs are placed primarily (95%) by the attending on service under ultrasound guidance using the Seldinger technique with lidocaine for anesthetic. For all PC consults, the attending BPS physician reviews the indication prior to placement. If not a direct consult from surgical services, most PC consults are appropriate referrals to the service after the primary medicine service has consulted CT-surgery or p ulmonary consult teams. After review, the primary role of the BPS is assessing safety of PC placement, including whether the patient can tolerate PC placement without procedural sedation. The BPS’s additional standards for safe PC placement are listed in Table 1.

Additionally, it is not routine practice of the BPS to recommend PC placement when consulted for a thoracentesis. The exception to this rule is patients whose PPE sonographic imaging demonstrates loculation or septations. This is consistent with the latest review on pleural disease.¹³ In addition, the institution’s CT surgery services prefer to initially treat septated PPEs with PCs and fibrinolytic therapy rather than immediate video-assisted thoracoscopic surgery (VATS).

The BPS operates a partnership with CT surgery in which, after successful PC placement, CT surgery manages the PC immediately and until removal including the negative pressure applied and need for fibrinolytic therapy. CT surgery also determines if secondary therapy, commonly second PC or VATS, is required. After PC placement, a portable chest x-ray (CXR) is taken and then BPS follows the patient in person the following day to note any insertion-related complications (IRCs).

In this paper, data on the consults to the BPS for PC placement over a 2-year period are presented. Primary outcomes included numbers of and indications for PCs consulted—attempted or not attempted—consulting services, IRCs, unsuccessful attempts (UAs), and adverse outcomes (AOs). PC duration, fluid drainage, need for fibrinolytic therapy, or need for secondary therapy were not measured because these decisions were managed by the CT surgery service.

Institutional review board approval of this retrospective study was granted by MCW/Froedtert Hospital Institutional Review Board #5 on January 14, 2019 (MCW IRB #PRO00033496). Adult patients hospitalized at Froedtert Hospital whose primary team determined they would clinically benefit from a PC and consulted the BPS service for placement were included. There were no exclusion criteria.

The authors conducted a retrospective review of two secure BPS databases. The first database is a record of all procedure consults, while the second database contains information about all attempted PCs. Initial review of the BPS’s consult database found 142 PC consults. Consults were classified as “declined” or “attempted.” In addition to the database comparison, the authors performed a manual chart review on patients with documented complications (n = 6) to clarify sequela, those with unclear PC indication (n = 2), and to resolve the discrepancies between our two databases (n = 3). Finally, a brief chart review was performed to review procedures in the subsequent 48 hours after a declined PC consult (n = 18).

Complications fell into two categories, IRCs and UAs. IRCs were defined as unintentional PC placement into a location other than the pleural space or PC placement that resulted in an AO according to the judgement of the attending BPS physician. A UA was defined as an unsuccessfully attempted PC placement, with the BPS unable to pass a PC in the pleural space for any reason. An AO was defined as any escalation of care that could be related to the procedure within 24 hours of attempt/placement found in our databases and/or manual chart review (eg, emergent intubation, surgery, death).

Over a 2-year period, the BPS was consulted to place 142 PCs. After resolution of the 3 discrepancies, total consults remained 142, PC attempts totaled 124 (87.3%), and declined consults totaled 18 (12.7%).

The 18 declined consults were not performed for reasons relating to procedural safety. These included 15 (83.3%) for insufficient fluid depth, 1 (5.6%) poor window for PTX, and 1 (5.6%) patient unstable per BPS attending judgement. One (5.6%) final consult had a previous drain in same hemithorax that resumed functioning.

The manual chart review of procedures performed 48 hours after declined PC consults found only 3 of 17 (17.6%) patients received a PC within the subsequent 48 hours. The 18th patient was unable to be followed in our electronic medical record because his medical record number was recorded incorrectly.

The remaining 124 consults were deemed safe for PC placement. Indications for PC placement varied; the most common indications were complicated effusion (36.3%), large or recurrent effusions (21.8%), PTX (17%), and hemothorax (HTX; 17%). The most common teams who consulted the BPS for PC were medicine/hospitalists (42.7%) and CT surgery (40.3%).

There were 3 IRCs (Table 2) out of 124 attempted consults (2.4%). Of these cases, 2 patients had AOs. IRC patient No. 1 required a PC for PTX and developed a hemothorax from a right-sided mammary artery laceration. Emergent operative measures were taken, but unfortunately the patient died. IRC patient No. 2 was septic from pneumonia when a PC was placed for a complicated PPE. Unfortunately, the patient went into respiratory failure and required intubation. The postintubation computed tomography scan did note that the PC placed by the BPS likely terminated in the lower lobe of the right lung but without PTX. After a new PC was placed by IR, the patient received antibiotics, 3 days of ventilator support, and was discharged home. The authors believe that sepsis from pneumonia was the more probable cause of the respiratory failure in IRC patient No. 2 instead of the PC placement.

To our knowledge, this is the first report of the experience of procedure-focused hospitalists with PC placement in a partnership with CT surgery. We believe that, at high volume, tertiary care centers similar to Froedtert Hospital, internal medicine–trained, procedure-focused hospitalists can serve as adjuncts to surgery, pulmonary, and IR services in the placement of PCs in hospitalized patients that do not require procedural sedation.

Given the development of this service and the nature of its shared operations with CT surgery, we do not believe that the BPS has an appropriate comparison in the literature; however, the IRCs are similar to previous papers describing PC placement.^5-7,14 Notably, the IRC and AO rates were low, both 2.4%, which indicates safe placement of PCs. Kulvatunyou et al and Bauman et al reported on PC placement from a surgical perspective and reported IRC rates of 4%-10%.^5-7,14 These higher IRC rates likely have a few reasons. First, Kulvatunyou et al and Bauman et al did not use ultrasound guidance. Use of ultrasound guidance may have significantly lowered their IRC rate. Second, the definition of IRC used by Kulvatunyou et al and Bauman et al included dislodgements, but we do not believe this to be an IRC. Dislodgements can happen for several reasons, frequently a result of patient movement or forgetfulness, not because of improper placement. Third, the PCs with this BPS are placed primarily by attending physicians. Resident roles on our BPS in PC placement are primarily as assistants, whereas Kulvatunyou et al and Bauman et al note that both attendings and residents, under attending supervision, placed PCs; however, it is not clear what percentage of PCs were placed by attendings or residents in their studies. Finally, this BPS’s IRCs are self-reported, so they could be perceived as falsely low, but given the small number of physicians involved in the group and its standardized follow-up, we do not suspect this is truly contributing to the low rates.

Other complication rates regarding the use of wire-guided SBCTs and PCs range from 0% to 42%^15-20; however, several differences including tube size, physician training, and PC indication make these studies imperfect comparisons. The most notable difference in our opinion is the variable definition, or lack of definition, of a complication. One study did not define their complications,¹⁹ while other studies list subjective measures like pain,^16,20 cough,¹⁶ bleeding, ^16,20 and hematomas^4,15 as complications. We believe that the lack of consensus definition for PC complication or IRC contributes to the large range of complication rates in the literature. This problem is likely not unique to PC placement, but is instead true across all bedside procedures. In a shared-practice model between hospitalists and CT surgeons, we believe the definition of IRC in this paper is adequate in capturing most complications. The only complication we are currently unable to track well is infection. We consider other items discussed previously, such as pain, cough (often from lung re-expansion), minor bleeding, and even small hematomas, to be a part of the procedure and not a complication.

Finally, regarding the IRCs and associated death, this was a tragic event. Complications for all of the BPS’s procedures are infrequent (0.35% over the same time period) and reviewed between the BPS director and the attending who performed the procedure; in addition, given this mortality, the case was reviewed immediately in detail with our CT surgery colleagues. On review, it was easy to determine that the operator had found a clear lung tip and sonographic signs of PTX; however, CXR review did demonstrate a medial placement of the PC. This was judged to be a poor placement location (even with imaging demonstrating PTX in that area) given the well-known “triangle of safety” defined by the British Thoracic Society.¹²

After review, the primary emphasis for PC placement was safe location. The BPS now strives to place PCs for PTX only in the “triangle of safety.” The BPS believe that most PTXs can be addressed with this placement. In the rare case of a PTX requiring an anterior approach, only the BPS director currently places apical PCs for PTX while on service or “on call.” He discusses the placement with pulmonary and CT surgery directly to determine that the PC is of absolute necessity.

Given the focus on appropriate location, no formal changes were made to the procedural imaging practice described in Table 1. We realize that vascular imaging would seem necessary after this patient’s mammary artery laceration; however, safe location, in addition to the BPS’s current image requirements, is believed to minimize this risk. We feel the imaging criteria align with recommendation No. 5 of the Society of Hospital Medicine’s Position Statement for Ultrasound Guidance for Adult Thoracentesis.²¹ Some BPS members use vascular ultrasound imaging to confirm absence of vascularity, but it is not required and occasionally not possible, such as in the occasional case of PTX with subcutaneous emphysema.

The UA rate is low without a natural comparator in the literature. It is important to clarify the difference between the UAs and the frequently mentioned “failure rate” (FR) in Kulvatunyou et al and Bauman et al^6,7,14 We classify UAs as the inability, for any reason, to access the pleural space and insert a PC. At this stage, these UAs appear to reflect the service’s new experience with PC placement and inability to provide procedural sedation. Kulvatunyou et al and Bauman et al’s FR is defined as an initial PC successfully placed into the pleural space that then required a second PC or intervention (frequently VATS) to resolve the PTX or retained HTX.

We believe calculating the failure rate will be helpful in demonstrating the value of our BPS and our shared-practice model. We look forward to publishing this and other future research, including determination of the cost and time saved by the BPS for PCs and other procedures.

Limitations of this study include its retrospective nature, results from a single center’s experience, and lack of a comparison group.

Our institution feels that there is great benefit in having a BPS operated by procedure-focused hospitalists. It would also be important to determine if our model can be replicated by another institution.

Acknowledgments

The authors thank CT surgery for helping to develop this shared-practice model and to both CT surgery and IR physicians here at the Medical College of Wisconsin and Froedtert Hospital who assist us with both IRCs and UAs of pigtail catheters.

The authors also thank Dr. Ricardo Franco-Sadud for his oversight and thoughtful improvements to the paper.

Readmission rates are used as metrics for care quality and reimbursement, with penalties applied to hospitals with higher than expected rates¹ and up to 30% of pediatric readmissions deemed potentially preventable.² There is a paucity of information on how to prevent pediatric readmissions,³ yet pediatric hospitals are tasked with implementing interventions for readmission reduction.

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial in which patients discharged from hospital medicine and neuroscience services at a single institution were randomized to receive a single home visit from a registered nurse (RN) within 96 hours of discharge.⁴ RNs completed a structured nurse visit designed specifically for the trial. Lists of “red flags” or warning signs associated with common diagnoses were provided to assist RNs in standardizing education about when to seek additional care. The hypothesis was that the postdischarge visits would result in lower reutilization rates (unplanned readmissions, emergency department [ED] visits, and urgent care visits).⁵

Unexpectedly, children randomized to receive the postdischarge nurse visit had higher rates of 30-day unplanned healthcare reutilization, with children randomly assigned to the intervention demonstrating higher odds of 30-day healthcare use (OR 1.33; 95% CI 1.003-1.76).⁴ We sought to understand perspectives on these unanticipated findings by obtaining input from relevant stakeholders. There were 2 goals for the qualitative analysis: first, to understand possible explanations of the increased reutilization finding; second, to elicit suggestions for improving the nurse visit intervention.

We selected an in-depth qualitative approach, using interviews and focus groups to explore underlying explanations for the increase in 30-day unplanned healthcare reutilization among those randomized to receive the postdischarge nurse visit during the H2O trial.⁴ Input was sought from 4 stakeholder groups—parents, primary care physicians (PCPs), hospital medicine physicians, and home care RNs—in an effort to triangulate data sources and elicit rich and diverse opinions. Approval was obtained from the Institutional Review Board prior to conducting the study.

Recruitment
Parents

Because we conducted interviews approximately 1 year after the trial’s conclusion, we purposefully selected families who were enrolled in the latter portion of the H2O trial in order to enhance recall. Beginning with the last families in the study, we sequentially contacted families in reverse order. We contacted 10 families in each of 4 categories (intervention/reutilization, intervention/no reutilization, control/reutilization, control/no reutilization). A total of 3 attempts were made by telephone to contact each family. Participants received a grocery store gift card for participating in the study.

Primary Care Physicians

We conducted focus groups with a purposive sample of physicians recruited from 2 community practices and 1 hospital-­owned practice.

Hospital Medicine Physicians

We conducted focus groups with a purposive sample of physicians from our Division of Hospital Medicine. There was a varying level of knowledge of the original trial; however, none of the participants were collaborators in the trial.

Home Care RNs

We conducted focus groups with a subset of RNs who were involved with trial visits. All RNs were members of the pediatric home care division associated with the hospital with specific training in caring for patients at home.

Data Collection

The study team designed question guides for each stakeholder group (Appendix 1). While questions were tailored for specific stakeholders, all guides included the following topics: benefits and challenges of nurse visits, suggestions for improving the intervention in future trials, and reactions to the trial results (once presented to participants). Only the results of the intention-to-treat (ITT) analysis were shared with stakeholders because ITT is considered the gold standard for trial analysis and allows easy understanding of the results.

A single investigator (A.L.) conducted parental interviews by telephone. Focus groups for PCPs, hospital medicine physicians, and RN groups were held at practice locations in private conference rooms and were conducted by trained moderators (S.N.S., A.L., and H.T.C.). Moderators probed responses to the open-ended questions to delve deeply into issues. The question guides were modified in an iterative fashion to include new concepts raised during interviews or focus groups. All interviews and focus groups were recorded and transcribed verbatim with all identifiable information redacted.

Data Analysis

During multiple cycles of inductive thematic analysis,⁶ we examined, discussed, interpreted, and organized responses to the open-ended questions,^6,7 analyzing each stakeholder group separately. First, transcripts were shared with and reviewed by the entire multidisciplinary team (12 members) which included hospital medicine physicians, PCPs, home care nursing leaders, a nurse scientist, a parent representative, research coordinators, and a qualitative research methodologist. Second, team members convened to discuss overall concepts and ideas and created the preliminary coding frameworks. Third, a smaller subgroup (research coordinator [A.L]., hospital medicine physician [S.R.], parent representative [M.M.], and qualitative research methodologist [S.N.S.]), refined the unique coding framework for each stakeholder group and then independently applied codes to participant comments. This subgroup met regularly to reach consensus about the assigned codes and to further refine the codebooks. The codes were organized into major and minor themes based on recurring patterns in the data and the salience or emphasis given by participants. The subgroup’s work was reviewed and discussed on an ongoing basis by the entire multidisciplinary team. Triangulation of the data was achieved in multiple ways. The preliminary results were shared in several forums, and feedback was solicited and incorporated. Two of 4 members of the subgroup analytic team were not part of the trial planning or data collection, providing a potentially broader perspective. All coding decisions were maintained in an electronic database, and an audit trail was created to document codebook revisions.

A total of 33 parents participated in the interviews (intervention/readmit [8], intervention/no readmit [8], control/readmit [8], and control/no readmit [9]). Although we selected families from all 4 categories, we were not able to explore qualitative differences between these groups because of the relatively low numbers of participants. Parent data was very limited as interviews were brief and “control” parents had not received the intervention. Three focus groups were held with PCPs (7 participants in total), 2 focus groups were held with hospital medicine physicians (12 participants), and 2 focus groups were held with RNs (10 participants).

Goal 1: Explanation of Reutilization Rates

During interviews and focus groups, the results of the H2O trial were discussed, and stakeholders were asked to comment on potential explanations of the findings. 4 major themes and 5 minor themes emerged from analysis of the transcripts (summarized in Table 1).

Theme 1: Appropriateness of Patient Reutilization

Hospital medicine physicians and home care RNs questioned whether the reutilization events were clinically indicated. RNs wondered whether children who reutilized the ED were also readmitted to the hospital; many perceived that if the child was ill enough to be readmitted, then the ED revisit was warranted (Table 2). Parents commented on parental decision-making and changes in clinical status of the child leading to reutilization (Table 2).

Theme 2: Impact of Red Flags/Warning Sign Instructions on Family’s Reutilization Decisions

Theme 3: Hospital-Affiliated RNs “Directing Traffic” Back to Hospital

Both physician groups were concerned that, because the study was conducted by hospital-employed nurses, families might have been more likely to reaccess care at the hospital. Thus, the connection with the hospital was strengthened in the H2O model, potentially at the expense of the connection with PCPs. Physicians hypothesized that families might “still feel part of the medical system,” so families would return to the hospital if there was a problem. PCPs emphasized that there may have been straightforward situations that could have been handled appropriately in the outpatient office (Table 2).

Theme 4: Home Visit RNs Had a Low Threshold for Escalating Care

Parents and PCPs hypothesized that RNs are more conservative and, therefore, would have had a low threshold to refer back to the hospital if there were concerns in the home. One parent commented: “I guess, nurses are just by trade accustomed to erring on the side of caution and medical intervention instead of letting time take its course. … They’re more apt to say it’s better off to go to the hospital and have everything be fine” (Table 2).

Minor Themes

Participants also explained reutilization in ways that coalesced into 5 minor themes: (1) families receiving a visit might perceive that their child was sicker; (2) patients in the control group did not reutilize enough; (3) receiving more education on a child’s illness drives reutilization; (4) provider access issues; and (5) variability of RN experience may determine whether escalated care. Supportive quotations found in Appendix 2.

We directly asked parents if they would want a nurse home visit in the future after discussing the results of the study. Almost all of the parents in the intervention group and most of the parents in the control group were in favor of receiving a visit, even knowing that patients who had received a visit were more likely to reutilize care.

Goal 2: Suggestions for Improving Intervention Design

Three major themes and 3 minor themes were related to improving the design of the intervention (Table 1).

Theme 1: Need for Improved Postdischarge Communication

All stakeholder groups highlighted postdischarge communication as an area that could be improved. Parents were frustrated with regard to attempts to connect with inpatient physicians after discharge. PCPs suggested developing pathways for the RN to connect with the primary care office as opposed to the hospital. Hospital medicine physicians discussed a lack of consensus regarding patient ownership following discharge and were uncertain about what types of postdischarge symptoms PCPs would be comfortable managing. RNs described specific situations when they had difficulty contacting a physician to escalate care (Table 3).

Theme 2: Individualizing Home Visits—One Size Does Not Fit All

All stakeholder groups also encouraged “individualization” of home visits according to patient and family characteristics, diagnosis, and both timing and severity of illness. PCPs recommended visits only for certain diagnoses. Hospital medicine physicians voiced similar sentiments as the PCPs and added that worrisome family dynamics during a hospitalization, such as a lack of engagement with the medical team, might also warrant a visit. RNs suggested visits for those families with more concerns, for example, those with young children or children recovering from an acute respiratory illness (Table 3).

Theme 3: Providing Context for and Framing of Red Flags

Physicians and nurses suggested providing more context to “red flag” instructions and education. RNs emphasized that some families seemed to benefit from the opportunity to discuss their postdischarge concerns with a medical professional. Others appreciated concrete written instructions that spelled out how to respond in certain situations (Table 3).

Minor Themes

Three minor themes were revealed regarding intervention design improvement (Table 1): (1) streamlining the discharge process; (2) improving the definition of the scope and goal of intervention; and (3) extending inpatient team expertise post discharge. Supportive quotations can be found in Appendix 3.

When stakeholders were asked about why postdischarge RN visits led to increased postdischarge urgent healthcare visits, they questioned the appropriateness of the reutilization events, wondered about the lack of context for the warning signs that nurses provided families as part of the intervention, worried that families were encouraged to return to the hospital because of the ties of the trial to the hospital, and suggested that RNs had a low threshold to refer patients back to the hospital. When asked about how to design an improved nurse visit to better support families, stakeholders emphasized improving communication, individualizing the visit, and providing context around the red-flag discussion, enabling more nuanced instructions about how to respond to specific events.

A synthesis of themes suggests that potential drivers for increased utilization rates may lie in the design and goals of the initial project. The intervention was designed to support families and enhance education after discharge, with components derived from pretrial focus groups with families after a hospital discharge.⁸ The intervention was not designed to divert patients from the ED nor did it enhance access to the PCP. A second trial of the intervention adapted to a phone call also failed to decrease reutilization rates.⁹ Both physician stakeholder groups perceived that the intervention directed traffic back to the hospital because of the intervention design. Coupled with the perception that the red flags may have changed a family’s threshold for seeking care and/or that an RN may be more apt to refer back to care, this failure to push utilization to the primary care office may explain the unexpected trial results. Despite the stakeholders’ perception of enhanced connection back to the hospital as a result of the nurse visit, in analysis of visit referral patterns, a referral was made directly back to the ED in only 4 of the 651 trial visits (Tubbs-Cooley H, Riddle SR, Gold JM, et al.; under review. Pediatric clinical and social concerns identified by home visit nurses in the immediate postdischarge period 2020).

Both H2O trials demonstrated improved recall of red flags by parents who received the intervention, which may be important given the stakeholders’ perspectives that the red flags may not have been contextualized well enough. Yet neither trial demonstrated any differences in postdischarge coping or time to return to normal routine. In interviews with parents, despite the clearly stated results of increased reutilization, intervention parents endorsed a desire for a home visit in the future, raising the possibility that our outcome measures did not capture parents’ priorities adequately.

When asked to recommend design improvements of the intervention, 2 major themes (improvement in communication and individualization of visits) were discussed by all stakeholder groups, providing actionable information to modify or create new interventions. Focus groups with clinicians suggested that communication challenges may have influenced reutilization likelihood during the postdischarge period. RNs expressed uncertainty about who to call with problems or questions at the time of a home visit. This was compounded by difficulty reaching physicians. Both hospital medicine physicians and PCPs identified system challenges including questions of patient ownership, variable PCP practice communication preferences, and difficulty in identifying a partnered staff member (on either end of the inpatient-outpatient continuum) who was familiar with a specific patient. While the communication issues raised may reflect difficulties in our local healthcare system, there is broad evidence of postdischarge communication challenges. In adults, postdischarge communication failures between home health staff and physicians are associated with an increased risk of readmission.¹⁰ The real or perceived lack of communication between inpatient and outpatient providers can add to parental confusion post discharge.¹¹ Although there have been efforts to improve the reliability of communication across this gulf,^12,13 it is not clear whether changes to discharge communication could help to avoid pediatric reutilization events.¹⁴

The theme of individualization of the home nurse visit is consistent with evidence regarding the impact of focusing the intervention on patients with specific diagnoses or demographics. In adults, reduced reutilization associated with postdischarge home nurse visits has been described in specific populations such as patients with heart failure and chronic obstructive pulmonary disease.¹⁵ Impact of home nurse visits on patients within diagnosis-specific populations with certain demographics (such as advanced age) has also been described.¹⁶ In the pediatric population, readmission rates vary widely by diagnosis.¹⁷ A systematic review of interventions to reduce pediatric readmissions found increased impact of discharge interventions in specific populations (asthma, oncology, and NICU).³

Next steps may lie in interventions in targeted populations that function as part of a care continuum bridging the patient from the inpatient to the outpatient setting. A home nurse visit as part of this discharge structure may prove to have more impact on reducing reutilization. One population which accounts for a large proportion of readmissions and where there has been recent focus on discharge transition of care has been children with medical complexity.¹⁸ This group was largely excluded from the H2O trial. Postdischarge home nurse visits in this population have been found to be feasible and address many questions and problems, but the effect on readmission is less clear.¹⁹ Family priorities and preferences related to preparation for discharge, including family engagement, respect for discharge readiness, and goal of returning to normal routines, may be areas on which to focus with future interventions in this population.²⁰ In summary, although widespread postdischarge interventions (home nurse visit⁴ and nurse telephone call⁹) have not been found to be effective, targeting interventions to specific populations by diagnosis or demographic factors may prove to be more effective in reducing pediatric reutilization.

There were several strengths to this study. This qualitative approach allowed us to elucidate potential explanations for the H2O trial results from multiple perspectives. The multidisciplinary composition of our analytic team and the use of an iterative process sparked diverse contributions in a dynamic, ongoing discussion and interpretation of our data.

This study should be considered in the context of several limitations. For families and RNs, there was a time lag between participation in the trial and participation in the qualitative study call or focus group which could lead to difficulty recalling details. Only families who received the intervention could give opinions on their experience of the nurse visit, while families in the control group were asked to hypothesize. Focus groups with hospital medicine physicians and PCPs were purposive samples, and complete demographic information of participants was not collected.

Key stakeholders reflecting on a postdischarge RN visit trial suggested multiple potential explanations for the unexpected increase in reutilization in children randomized to the intervention. Certain participants questioned whether all reutilization events were appropriate or necessary. Others expressed concerns that the H2O intervention lacked context and directed children back to the hospital instead of the PCP. Parents, PCPs, hospital medicine physicians, and RNs all suggested that future transition-focused interventions should enhance postdischarge communication, strengthen connection to the PCP, and be more effectively tailored to the needs of the individual patient and family.

Acknowledgments

Collaborators: H2O Trial Study Group: Joanne Bachus, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Monica L Borell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lenisa V Chang, MA, PhD; Patricia Crawford, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sarah A Ferris, BA, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Judy A Heilman BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Jane C Khoury, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen Lawley, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lynne O’Donnell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Hadley S Sauers-Ford, MPH, Department of Pediatrics, UC Davis Health, Sacramento, California; Anita N Shah, DO, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lauren G Solan, MD, Med, University of Rochester, Rochester, New York; Heidi J Sucharew, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen P Sullivan, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Christine M White, MD, MAT, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio.

Readmission rates are used as metrics for care quality and reimbursement, with penalties applied to hospitals with higher than expected rates¹ and up to 30% of pediatric readmissions deemed potentially preventable.² There is a paucity of information on how to prevent pediatric readmissions,³ yet pediatric hospitals are tasked with implementing interventions for readmission reduction.

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial in which patients discharged from hospital medicine and neuroscience services at a single institution were randomized to receive a single home visit from a registered nurse (RN) within 96 hours of discharge.⁴ RNs completed a structured nurse visit designed specifically for the trial. Lists of “red flags” or warning signs associated with common diagnoses were provided to assist RNs in standardizing education about when to seek additional care. The hypothesis was that the postdischarge visits would result in lower reutilization rates (unplanned readmissions, emergency department [ED] visits, and urgent care visits).⁵

Unexpectedly, children randomized to receive the postdischarge nurse visit had higher rates of 30-day unplanned healthcare reutilization, with children randomly assigned to the intervention demonstrating higher odds of 30-day healthcare use (OR 1.33; 95% CI 1.003-1.76).⁴ We sought to understand perspectives on these unanticipated findings by obtaining input from relevant stakeholders. There were 2 goals for the qualitative analysis: first, to understand possible explanations of the increased reutilization finding; second, to elicit suggestions for improving the nurse visit intervention.

We selected an in-depth qualitative approach, using interviews and focus groups to explore underlying explanations for the increase in 30-day unplanned healthcare reutilization among those randomized to receive the postdischarge nurse visit during the H2O trial.⁴ Input was sought from 4 stakeholder groups—parents, primary care physicians (PCPs), hospital medicine physicians, and home care RNs—in an effort to triangulate data sources and elicit rich and diverse opinions. Approval was obtained from the Institutional Review Board prior to conducting the study.

Recruitment
Parents

Because we conducted interviews approximately 1 year after the trial’s conclusion, we purposefully selected families who were enrolled in the latter portion of the H2O trial in order to enhance recall. Beginning with the last families in the study, we sequentially contacted families in reverse order. We contacted 10 families in each of 4 categories (intervention/reutilization, intervention/no reutilization, control/reutilization, control/no reutilization). A total of 3 attempts were made by telephone to contact each family. Participants received a grocery store gift card for participating in the study.

Primary Care Physicians

We conducted focus groups with a purposive sample of physicians recruited from 2 community practices and 1 hospital-­owned practice.

Hospital Medicine Physicians

We conducted focus groups with a purposive sample of physicians from our Division of Hospital Medicine. There was a varying level of knowledge of the original trial; however, none of the participants were collaborators in the trial.

Home Care RNs

We conducted focus groups with a subset of RNs who were involved with trial visits. All RNs were members of the pediatric home care division associated with the hospital with specific training in caring for patients at home.

Data Collection

The study team designed question guides for each stakeholder group (Appendix 1). While questions were tailored for specific stakeholders, all guides included the following topics: benefits and challenges of nurse visits, suggestions for improving the intervention in future trials, and reactions to the trial results (once presented to participants). Only the results of the intention-to-treat (ITT) analysis were shared with stakeholders because ITT is considered the gold standard for trial analysis and allows easy understanding of the results.

A single investigator (A.L.) conducted parental interviews by telephone. Focus groups for PCPs, hospital medicine physicians, and RN groups were held at practice locations in private conference rooms and were conducted by trained moderators (S.N.S., A.L., and H.T.C.). Moderators probed responses to the open-ended questions to delve deeply into issues. The question guides were modified in an iterative fashion to include new concepts raised during interviews or focus groups. All interviews and focus groups were recorded and transcribed verbatim with all identifiable information redacted.

Data Analysis

During multiple cycles of inductive thematic analysis,⁶ we examined, discussed, interpreted, and organized responses to the open-ended questions,^6,7 analyzing each stakeholder group separately. First, transcripts were shared with and reviewed by the entire multidisciplinary team (12 members) which included hospital medicine physicians, PCPs, home care nursing leaders, a nurse scientist, a parent representative, research coordinators, and a qualitative research methodologist. Second, team members convened to discuss overall concepts and ideas and created the preliminary coding frameworks. Third, a smaller subgroup (research coordinator [A.L]., hospital medicine physician [S.R.], parent representative [M.M.], and qualitative research methodologist [S.N.S.]), refined the unique coding framework for each stakeholder group and then independently applied codes to participant comments. This subgroup met regularly to reach consensus about the assigned codes and to further refine the codebooks. The codes were organized into major and minor themes based on recurring patterns in the data and the salience or emphasis given by participants. The subgroup’s work was reviewed and discussed on an ongoing basis by the entire multidisciplinary team. Triangulation of the data was achieved in multiple ways. The preliminary results were shared in several forums, and feedback was solicited and incorporated. Two of 4 members of the subgroup analytic team were not part of the trial planning or data collection, providing a potentially broader perspective. All coding decisions were maintained in an electronic database, and an audit trail was created to document codebook revisions.

A total of 33 parents participated in the interviews (intervention/readmit [8], intervention/no readmit [8], control/readmit [8], and control/no readmit [9]). Although we selected families from all 4 categories, we were not able to explore qualitative differences between these groups because of the relatively low numbers of participants. Parent data was very limited as interviews were brief and “control” parents had not received the intervention. Three focus groups were held with PCPs (7 participants in total), 2 focus groups were held with hospital medicine physicians (12 participants), and 2 focus groups were held with RNs (10 participants).

Goal 1: Explanation of Reutilization Rates

During interviews and focus groups, the results of the H2O trial were discussed, and stakeholders were asked to comment on potential explanations of the findings. 4 major themes and 5 minor themes emerged from analysis of the transcripts (summarized in Table 1).

Theme 1: Appropriateness of Patient Reutilization

Hospital medicine physicians and home care RNs questioned whether the reutilization events were clinically indicated. RNs wondered whether children who reutilized the ED were also readmitted to the hospital; many perceived that if the child was ill enough to be readmitted, then the ED revisit was warranted (Table 2). Parents commented on parental decision-making and changes in clinical status of the child leading to reutilization (Table 2).

Theme 2: Impact of Red Flags/Warning Sign Instructions on Family’s Reutilization Decisions

Theme 3: Hospital-Affiliated RNs “Directing Traffic” Back to Hospital

Both physician groups were concerned that, because the study was conducted by hospital-employed nurses, families might have been more likely to reaccess care at the hospital. Thus, the connection with the hospital was strengthened in the H2O model, potentially at the expense of the connection with PCPs. Physicians hypothesized that families might “still feel part of the medical system,” so families would return to the hospital if there was a problem. PCPs emphasized that there may have been straightforward situations that could have been handled appropriately in the outpatient office (Table 2).

Theme 4: Home Visit RNs Had a Low Threshold for Escalating Care

Parents and PCPs hypothesized that RNs are more conservative and, therefore, would have had a low threshold to refer back to the hospital if there were concerns in the home. One parent commented: “I guess, nurses are just by trade accustomed to erring on the side of caution and medical intervention instead of letting time take its course. … They’re more apt to say it’s better off to go to the hospital and have everything be fine” (Table 2).

Minor Themes

Participants also explained reutilization in ways that coalesced into 5 minor themes: (1) families receiving a visit might perceive that their child was sicker; (2) patients in the control group did not reutilize enough; (3) receiving more education on a child’s illness drives reutilization; (4) provider access issues; and (5) variability of RN experience may determine whether escalated care. Supportive quotations found in Appendix 2.

We directly asked parents if they would want a nurse home visit in the future after discussing the results of the study. Almost all of the parents in the intervention group and most of the parents in the control group were in favor of receiving a visit, even knowing that patients who had received a visit were more likely to reutilize care.

Goal 2: Suggestions for Improving Intervention Design

Three major themes and 3 minor themes were related to improving the design of the intervention (Table 1).

Theme 1: Need for Improved Postdischarge Communication

All stakeholder groups highlighted postdischarge communication as an area that could be improved. Parents were frustrated with regard to attempts to connect with inpatient physicians after discharge. PCPs suggested developing pathways for the RN to connect with the primary care office as opposed to the hospital. Hospital medicine physicians discussed a lack of consensus regarding patient ownership following discharge and were uncertain about what types of postdischarge symptoms PCPs would be comfortable managing. RNs described specific situations when they had difficulty contacting a physician to escalate care (Table 3).

Theme 2: Individualizing Home Visits—One Size Does Not Fit All

All stakeholder groups also encouraged “individualization” of home visits according to patient and family characteristics, diagnosis, and both timing and severity of illness. PCPs recommended visits only for certain diagnoses. Hospital medicine physicians voiced similar sentiments as the PCPs and added that worrisome family dynamics during a hospitalization, such as a lack of engagement with the medical team, might also warrant a visit. RNs suggested visits for those families with more concerns, for example, those with young children or children recovering from an acute respiratory illness (Table 3).

Theme 3: Providing Context for and Framing of Red Flags

Physicians and nurses suggested providing more context to “red flag” instructions and education. RNs emphasized that some families seemed to benefit from the opportunity to discuss their postdischarge concerns with a medical professional. Others appreciated concrete written instructions that spelled out how to respond in certain situations (Table 3).

Minor Themes

Three minor themes were revealed regarding intervention design improvement (Table 1): (1) streamlining the discharge process; (2) improving the definition of the scope and goal of intervention; and (3) extending inpatient team expertise post discharge. Supportive quotations can be found in Appendix 3.

When stakeholders were asked about why postdischarge RN visits led to increased postdischarge urgent healthcare visits, they questioned the appropriateness of the reutilization events, wondered about the lack of context for the warning signs that nurses provided families as part of the intervention, worried that families were encouraged to return to the hospital because of the ties of the trial to the hospital, and suggested that RNs had a low threshold to refer patients back to the hospital. When asked about how to design an improved nurse visit to better support families, stakeholders emphasized improving communication, individualizing the visit, and providing context around the red-flag discussion, enabling more nuanced instructions about how to respond to specific events.

A synthesis of themes suggests that potential drivers for increased utilization rates may lie in the design and goals of the initial project. The intervention was designed to support families and enhance education after discharge, with components derived from pretrial focus groups with families after a hospital discharge.⁸ The intervention was not designed to divert patients from the ED nor did it enhance access to the PCP. A second trial of the intervention adapted to a phone call also failed to decrease reutilization rates.⁹ Both physician stakeholder groups perceived that the intervention directed traffic back to the hospital because of the intervention design. Coupled with the perception that the red flags may have changed a family’s threshold for seeking care and/or that an RN may be more apt to refer back to care, this failure to push utilization to the primary care office may explain the unexpected trial results. Despite the stakeholders’ perception of enhanced connection back to the hospital as a result of the nurse visit, in analysis of visit referral patterns, a referral was made directly back to the ED in only 4 of the 651 trial visits (Tubbs-Cooley H, Riddle SR, Gold JM, et al.; under review. Pediatric clinical and social concerns identified by home visit nurses in the immediate postdischarge period 2020).

Both H2O trials demonstrated improved recall of red flags by parents who received the intervention, which may be important given the stakeholders’ perspectives that the red flags may not have been contextualized well enough. Yet neither trial demonstrated any differences in postdischarge coping or time to return to normal routine. In interviews with parents, despite the clearly stated results of increased reutilization, intervention parents endorsed a desire for a home visit in the future, raising the possibility that our outcome measures did not capture parents’ priorities adequately.

When asked to recommend design improvements of the intervention, 2 major themes (improvement in communication and individualization of visits) were discussed by all stakeholder groups, providing actionable information to modify or create new interventions. Focus groups with clinicians suggested that communication challenges may have influenced reutilization likelihood during the postdischarge period. RNs expressed uncertainty about who to call with problems or questions at the time of a home visit. This was compounded by difficulty reaching physicians. Both hospital medicine physicians and PCPs identified system challenges including questions of patient ownership, variable PCP practice communication preferences, and difficulty in identifying a partnered staff member (on either end of the inpatient-outpatient continuum) who was familiar with a specific patient. While the communication issues raised may reflect difficulties in our local healthcare system, there is broad evidence of postdischarge communication challenges. In adults, postdischarge communication failures between home health staff and physicians are associated with an increased risk of readmission.¹⁰ The real or perceived lack of communication between inpatient and outpatient providers can add to parental confusion post discharge.¹¹ Although there have been efforts to improve the reliability of communication across this gulf,^12,13 it is not clear whether changes to discharge communication could help to avoid pediatric reutilization events.¹⁴

The theme of individualization of the home nurse visit is consistent with evidence regarding the impact of focusing the intervention on patients with specific diagnoses or demographics. In adults, reduced reutilization associated with postdischarge home nurse visits has been described in specific populations such as patients with heart failure and chronic obstructive pulmonary disease.¹⁵ Impact of home nurse visits on patients within diagnosis-specific populations with certain demographics (such as advanced age) has also been described.¹⁶ In the pediatric population, readmission rates vary widely by diagnosis.¹⁷ A systematic review of interventions to reduce pediatric readmissions found increased impact of discharge interventions in specific populations (asthma, oncology, and NICU).³

Next steps may lie in interventions in targeted populations that function as part of a care continuum bridging the patient from the inpatient to the outpatient setting. A home nurse visit as part of this discharge structure may prove to have more impact on reducing reutilization. One population which accounts for a large proportion of readmissions and where there has been recent focus on discharge transition of care has been children with medical complexity.¹⁸ This group was largely excluded from the H2O trial. Postdischarge home nurse visits in this population have been found to be feasible and address many questions and problems, but the effect on readmission is less clear.¹⁹ Family priorities and preferences related to preparation for discharge, including family engagement, respect for discharge readiness, and goal of returning to normal routines, may be areas on which to focus with future interventions in this population.²⁰ In summary, although widespread postdischarge interventions (home nurse visit⁴ and nurse telephone call⁹) have not been found to be effective, targeting interventions to specific populations by diagnosis or demographic factors may prove to be more effective in reducing pediatric reutilization.

There were several strengths to this study. This qualitative approach allowed us to elucidate potential explanations for the H2O trial results from multiple perspectives. The multidisciplinary composition of our analytic team and the use of an iterative process sparked diverse contributions in a dynamic, ongoing discussion and interpretation of our data.

This study should be considered in the context of several limitations. For families and RNs, there was a time lag between participation in the trial and participation in the qualitative study call or focus group which could lead to difficulty recalling details. Only families who received the intervention could give opinions on their experience of the nurse visit, while families in the control group were asked to hypothesize. Focus groups with hospital medicine physicians and PCPs were purposive samples, and complete demographic information of participants was not collected.

Key stakeholders reflecting on a postdischarge RN visit trial suggested multiple potential explanations for the unexpected increase in reutilization in children randomized to the intervention. Certain participants questioned whether all reutilization events were appropriate or necessary. Others expressed concerns that the H2O intervention lacked context and directed children back to the hospital instead of the PCP. Parents, PCPs, hospital medicine physicians, and RNs all suggested that future transition-focused interventions should enhance postdischarge communication, strengthen connection to the PCP, and be more effectively tailored to the needs of the individual patient and family.

Acknowledgments

Collaborators: H2O Trial Study Group: Joanne Bachus, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Monica L Borell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lenisa V Chang, MA, PhD; Patricia Crawford, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sarah A Ferris, BA, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Judy A Heilman BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Jane C Khoury, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen Lawley, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lynne O’Donnell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Hadley S Sauers-Ford, MPH, Department of Pediatrics, UC Davis Health, Sacramento, California; Anita N Shah, DO, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lauren G Solan, MD, Med, University of Rochester, Rochester, New York; Heidi J Sucharew, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen P Sullivan, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Christine M White, MD, MAT, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio.

Readmission rates are used as metrics for care quality and reimbursement, with penalties applied to hospitals with higher than expected rates¹ and up to 30% of pediatric readmissions deemed potentially preventable.² There is a paucity of information on how to prevent pediatric readmissions,³ yet pediatric hospitals are tasked with implementing interventions for readmission reduction.

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial in which patients discharged from hospital medicine and neuroscience services at a single institution were randomized to receive a single home visit from a registered nurse (RN) within 96 hours of discharge.⁴ RNs completed a structured nurse visit designed specifically for the trial. Lists of “red flags” or warning signs associated with common diagnoses were provided to assist RNs in standardizing education about when to seek additional care. The hypothesis was that the postdischarge visits would result in lower reutilization rates (unplanned readmissions, emergency department [ED] visits, and urgent care visits).⁵

Unexpectedly, children randomized to receive the postdischarge nurse visit had higher rates of 30-day unplanned healthcare reutilization, with children randomly assigned to the intervention demonstrating higher odds of 30-day healthcare use (OR 1.33; 95% CI 1.003-1.76).⁴ We sought to understand perspectives on these unanticipated findings by obtaining input from relevant stakeholders. There were 2 goals for the qualitative analysis: first, to understand possible explanations of the increased reutilization finding; second, to elicit suggestions for improving the nurse visit intervention.

We selected an in-depth qualitative approach, using interviews and focus groups to explore underlying explanations for the increase in 30-day unplanned healthcare reutilization among those randomized to receive the postdischarge nurse visit during the H2O trial.⁴ Input was sought from 4 stakeholder groups—parents, primary care physicians (PCPs), hospital medicine physicians, and home care RNs—in an effort to triangulate data sources and elicit rich and diverse opinions. Approval was obtained from the Institutional Review Board prior to conducting the study.

Recruitment
Parents

Because we conducted interviews approximately 1 year after the trial’s conclusion, we purposefully selected families who were enrolled in the latter portion of the H2O trial in order to enhance recall. Beginning with the last families in the study, we sequentially contacted families in reverse order. We contacted 10 families in each of 4 categories (intervention/reutilization, intervention/no reutilization, control/reutilization, control/no reutilization). A total of 3 attempts were made by telephone to contact each family. Participants received a grocery store gift card for participating in the study.

Primary Care Physicians

We conducted focus groups with a purposive sample of physicians recruited from 2 community practices and 1 hospital-­owned practice.

Hospital Medicine Physicians

We conducted focus groups with a purposive sample of physicians from our Division of Hospital Medicine. There was a varying level of knowledge of the original trial; however, none of the participants were collaborators in the trial.

Home Care RNs

We conducted focus groups with a subset of RNs who were involved with trial visits. All RNs were members of the pediatric home care division associated with the hospital with specific training in caring for patients at home.

Data Collection

The study team designed question guides for each stakeholder group (Appendix 1). While questions were tailored for specific stakeholders, all guides included the following topics: benefits and challenges of nurse visits, suggestions for improving the intervention in future trials, and reactions to the trial results (once presented to participants). Only the results of the intention-to-treat (ITT) analysis were shared with stakeholders because ITT is considered the gold standard for trial analysis and allows easy understanding of the results.

A single investigator (A.L.) conducted parental interviews by telephone. Focus groups for PCPs, hospital medicine physicians, and RN groups were held at practice locations in private conference rooms and were conducted by trained moderators (S.N.S., A.L., and H.T.C.). Moderators probed responses to the open-ended questions to delve deeply into issues. The question guides were modified in an iterative fashion to include new concepts raised during interviews or focus groups. All interviews and focus groups were recorded and transcribed verbatim with all identifiable information redacted.

Data Analysis

During multiple cycles of inductive thematic analysis,⁶ we examined, discussed, interpreted, and organized responses to the open-ended questions,^6,7 analyzing each stakeholder group separately. First, transcripts were shared with and reviewed by the entire multidisciplinary team (12 members) which included hospital medicine physicians, PCPs, home care nursing leaders, a nurse scientist, a parent representative, research coordinators, and a qualitative research methodologist. Second, team members convened to discuss overall concepts and ideas and created the preliminary coding frameworks. Third, a smaller subgroup (research coordinator [A.L]., hospital medicine physician [S.R.], parent representative [M.M.], and qualitative research methodologist [S.N.S.]), refined the unique coding framework for each stakeholder group and then independently applied codes to participant comments. This subgroup met regularly to reach consensus about the assigned codes and to further refine the codebooks. The codes were organized into major and minor themes based on recurring patterns in the data and the salience or emphasis given by participants. The subgroup’s work was reviewed and discussed on an ongoing basis by the entire multidisciplinary team. Triangulation of the data was achieved in multiple ways. The preliminary results were shared in several forums, and feedback was solicited and incorporated. Two of 4 members of the subgroup analytic team were not part of the trial planning or data collection, providing a potentially broader perspective. All coding decisions were maintained in an electronic database, and an audit trail was created to document codebook revisions.

A total of 33 parents participated in the interviews (intervention/readmit [8], intervention/no readmit [8], control/readmit [8], and control/no readmit [9]). Although we selected families from all 4 categories, we were not able to explore qualitative differences between these groups because of the relatively low numbers of participants. Parent data was very limited as interviews were brief and “control” parents had not received the intervention. Three focus groups were held with PCPs (7 participants in total), 2 focus groups were held with hospital medicine physicians (12 participants), and 2 focus groups were held with RNs (10 participants).

Goal 1: Explanation of Reutilization Rates

During interviews and focus groups, the results of the H2O trial were discussed, and stakeholders were asked to comment on potential explanations of the findings. 4 major themes and 5 minor themes emerged from analysis of the transcripts (summarized in Table 1).

Theme 1: Appropriateness of Patient Reutilization

Hospital medicine physicians and home care RNs questioned whether the reutilization events were clinically indicated. RNs wondered whether children who reutilized the ED were also readmitted to the hospital; many perceived that if the child was ill enough to be readmitted, then the ED revisit was warranted (Table 2). Parents commented on parental decision-making and changes in clinical status of the child leading to reutilization (Table 2).

Theme 2: Impact of Red Flags/Warning Sign Instructions on Family’s Reutilization Decisions

Theme 3: Hospital-Affiliated RNs “Directing Traffic” Back to Hospital

Both physician groups were concerned that, because the study was conducted by hospital-employed nurses, families might have been more likely to reaccess care at the hospital. Thus, the connection with the hospital was strengthened in the H2O model, potentially at the expense of the connection with PCPs. Physicians hypothesized that families might “still feel part of the medical system,” so families would return to the hospital if there was a problem. PCPs emphasized that there may have been straightforward situations that could have been handled appropriately in the outpatient office (Table 2).

Theme 4: Home Visit RNs Had a Low Threshold for Escalating Care

Parents and PCPs hypothesized that RNs are more conservative and, therefore, would have had a low threshold to refer back to the hospital if there were concerns in the home. One parent commented: “I guess, nurses are just by trade accustomed to erring on the side of caution and medical intervention instead of letting time take its course. … They’re more apt to say it’s better off to go to the hospital and have everything be fine” (Table 2).

Minor Themes

Participants also explained reutilization in ways that coalesced into 5 minor themes: (1) families receiving a visit might perceive that their child was sicker; (2) patients in the control group did not reutilize enough; (3) receiving more education on a child’s illness drives reutilization; (4) provider access issues; and (5) variability of RN experience may determine whether escalated care. Supportive quotations found in Appendix 2.

We directly asked parents if they would want a nurse home visit in the future after discussing the results of the study. Almost all of the parents in the intervention group and most of the parents in the control group were in favor of receiving a visit, even knowing that patients who had received a visit were more likely to reutilize care.

Goal 2: Suggestions for Improving Intervention Design

Three major themes and 3 minor themes were related to improving the design of the intervention (Table 1).

Theme 1: Need for Improved Postdischarge Communication

All stakeholder groups highlighted postdischarge communication as an area that could be improved. Parents were frustrated with regard to attempts to connect with inpatient physicians after discharge. PCPs suggested developing pathways for the RN to connect with the primary care office as opposed to the hospital. Hospital medicine physicians discussed a lack of consensus regarding patient ownership following discharge and were uncertain about what types of postdischarge symptoms PCPs would be comfortable managing. RNs described specific situations when they had difficulty contacting a physician to escalate care (Table 3).

Theme 2: Individualizing Home Visits—One Size Does Not Fit All

All stakeholder groups also encouraged “individualization” of home visits according to patient and family characteristics, diagnosis, and both timing and severity of illness. PCPs recommended visits only for certain diagnoses. Hospital medicine physicians voiced similar sentiments as the PCPs and added that worrisome family dynamics during a hospitalization, such as a lack of engagement with the medical team, might also warrant a visit. RNs suggested visits for those families with more concerns, for example, those with young children or children recovering from an acute respiratory illness (Table 3).

Theme 3: Providing Context for and Framing of Red Flags

Physicians and nurses suggested providing more context to “red flag” instructions and education. RNs emphasized that some families seemed to benefit from the opportunity to discuss their postdischarge concerns with a medical professional. Others appreciated concrete written instructions that spelled out how to respond in certain situations (Table 3).

Minor Themes

Three minor themes were revealed regarding intervention design improvement (Table 1): (1) streamlining the discharge process; (2) improving the definition of the scope and goal of intervention; and (3) extending inpatient team expertise post discharge. Supportive quotations can be found in Appendix 3.

When stakeholders were asked about why postdischarge RN visits led to increased postdischarge urgent healthcare visits, they questioned the appropriateness of the reutilization events, wondered about the lack of context for the warning signs that nurses provided families as part of the intervention, worried that families were encouraged to return to the hospital because of the ties of the trial to the hospital, and suggested that RNs had a low threshold to refer patients back to the hospital. When asked about how to design an improved nurse visit to better support families, stakeholders emphasized improving communication, individualizing the visit, and providing context around the red-flag discussion, enabling more nuanced instructions about how to respond to specific events.

A synthesis of themes suggests that potential drivers for increased utilization rates may lie in the design and goals of the initial project. The intervention was designed to support families and enhance education after discharge, with components derived from pretrial focus groups with families after a hospital discharge.⁸ The intervention was not designed to divert patients from the ED nor did it enhance access to the PCP. A second trial of the intervention adapted to a phone call also failed to decrease reutilization rates.⁹ Both physician stakeholder groups perceived that the intervention directed traffic back to the hospital because of the intervention design. Coupled with the perception that the red flags may have changed a family’s threshold for seeking care and/or that an RN may be more apt to refer back to care, this failure to push utilization to the primary care office may explain the unexpected trial results. Despite the stakeholders’ perception of enhanced connection back to the hospital as a result of the nurse visit, in analysis of visit referral patterns, a referral was made directly back to the ED in only 4 of the 651 trial visits (Tubbs-Cooley H, Riddle SR, Gold JM, et al.; under review. Pediatric clinical and social concerns identified by home visit nurses in the immediate postdischarge period 2020).

Both H2O trials demonstrated improved recall of red flags by parents who received the intervention, which may be important given the stakeholders’ perspectives that the red flags may not have been contextualized well enough. Yet neither trial demonstrated any differences in postdischarge coping or time to return to normal routine. In interviews with parents, despite the clearly stated results of increased reutilization, intervention parents endorsed a desire for a home visit in the future, raising the possibility that our outcome measures did not capture parents’ priorities adequately.

When asked to recommend design improvements of the intervention, 2 major themes (improvement in communication and individualization of visits) were discussed by all stakeholder groups, providing actionable information to modify or create new interventions. Focus groups with clinicians suggested that communication challenges may have influenced reutilization likelihood during the postdischarge period. RNs expressed uncertainty about who to call with problems or questions at the time of a home visit. This was compounded by difficulty reaching physicians. Both hospital medicine physicians and PCPs identified system challenges including questions of patient ownership, variable PCP practice communication preferences, and difficulty in identifying a partnered staff member (on either end of the inpatient-outpatient continuum) who was familiar with a specific patient. While the communication issues raised may reflect difficulties in our local healthcare system, there is broad evidence of postdischarge communication challenges. In adults, postdischarge communication failures between home health staff and physicians are associated with an increased risk of readmission.¹⁰ The real or perceived lack of communication between inpatient and outpatient providers can add to parental confusion post discharge.¹¹ Although there have been efforts to improve the reliability of communication across this gulf,^12,13 it is not clear whether changes to discharge communication could help to avoid pediatric reutilization events.¹⁴

The theme of individualization of the home nurse visit is consistent with evidence regarding the impact of focusing the intervention on patients with specific diagnoses or demographics. In adults, reduced reutilization associated with postdischarge home nurse visits has been described in specific populations such as patients with heart failure and chronic obstructive pulmonary disease.¹⁵ Impact of home nurse visits on patients within diagnosis-specific populations with certain demographics (such as advanced age) has also been described.¹⁶ In the pediatric population, readmission rates vary widely by diagnosis.¹⁷ A systematic review of interventions to reduce pediatric readmissions found increased impact of discharge interventions in specific populations (asthma, oncology, and NICU).³

Next steps may lie in interventions in targeted populations that function as part of a care continuum bridging the patient from the inpatient to the outpatient setting. A home nurse visit as part of this discharge structure may prove to have more impact on reducing reutilization. One population which accounts for a large proportion of readmissions and where there has been recent focus on discharge transition of care has been children with medical complexity.¹⁸ This group was largely excluded from the H2O trial. Postdischarge home nurse visits in this population have been found to be feasible and address many questions and problems, but the effect on readmission is less clear.¹⁹ Family priorities and preferences related to preparation for discharge, including family engagement, respect for discharge readiness, and goal of returning to normal routines, may be areas on which to focus with future interventions in this population.²⁰ In summary, although widespread postdischarge interventions (home nurse visit⁴ and nurse telephone call⁹) have not been found to be effective, targeting interventions to specific populations by diagnosis or demographic factors may prove to be more effective in reducing pediatric reutilization.

There were several strengths to this study. This qualitative approach allowed us to elucidate potential explanations for the H2O trial results from multiple perspectives. The multidisciplinary composition of our analytic team and the use of an iterative process sparked diverse contributions in a dynamic, ongoing discussion and interpretation of our data.

This study should be considered in the context of several limitations. For families and RNs, there was a time lag between participation in the trial and participation in the qualitative study call or focus group which could lead to difficulty recalling details. Only families who received the intervention could give opinions on their experience of the nurse visit, while families in the control group were asked to hypothesize. Focus groups with hospital medicine physicians and PCPs were purposive samples, and complete demographic information of participants was not collected.

Key stakeholders reflecting on a postdischarge RN visit trial suggested multiple potential explanations for the unexpected increase in reutilization in children randomized to the intervention. Certain participants questioned whether all reutilization events were appropriate or necessary. Others expressed concerns that the H2O intervention lacked context and directed children back to the hospital instead of the PCP. Parents, PCPs, hospital medicine physicians, and RNs all suggested that future transition-focused interventions should enhance postdischarge communication, strengthen connection to the PCP, and be more effectively tailored to the needs of the individual patient and family.

Acknowledgments

Collaborators: H2O Trial Study Group: Joanne Bachus, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Monica L Borell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lenisa V Chang, MA, PhD; Patricia Crawford, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sarah A Ferris, BA, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Judy A Heilman BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Jane C Khoury, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen Lawley, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lynne O’Donnell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Hadley S Sauers-Ford, MPH, Department of Pediatrics, UC Davis Health, Sacramento, California; Anita N Shah, DO, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lauren G Solan, MD, Med, University of Rochester, Rochester, New York; Heidi J Sucharew, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen P Sullivan, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Christine M White, MD, MAT, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio.

A correction has been made to the Figure. A dosage was incorrect in the Orderset 1.1 (1/1/16-3/19/17) box. The figure listed Insulin 19 Units IV x 1 and should have been Insulin 10 Units IV x 1. Below is the corrected figure..

A correction has been made to the Figure. A dosage was incorrect in the Orderset 1.1 (1/1/16-3/19/17) box. The figure listed Insulin 19 Units IV x 1 and should have been Insulin 10 Units IV x 1. Below is the corrected figure..

A correction has been made to the Figure. A dosage was incorrect in the Orderset 1.1 (1/1/16-3/19/17) box. The figure listed Insulin 19 Units IV x 1 and should have been Insulin 10 Units IV x 1. Below is the corrected figure..

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

A 5-year old boy is admitted to the hospital for a bowel clean-out after presenting with abdominal pain and having an abdominal x-ray that demonstrated a “moderate stool burden.” After ingestion of the bowel prep, he develops worsening abdominal cramping and diarrhea. Upon reviewing the bowel history with his mother afterward, the team learns that he has had a bowel movement every 1-2 days as usual and has been having soft stools without any straining, pain, or blood present.

Functional constipation is a common clinical problem in pediatrics and constitutes a large number of admissions into hospitals and visits to clinics and emergency departments. In the United States, up to 36% of children are affected.Associated healthcare costs for children with constipation are estimated at $5.9 billion per year, which is $3.9 billion more than the general pediatric population without constipation.¹ In 2011, American children aged 17 years and younger had more than 270,000 visits to the emergency department for constipation.² As many as 70% of children who are given a diagnosis of constipation in the emergency department have an abdominal x-ray completed.³ The carcinogenic effects of radiation from radiography are well known. Unnecessary imaging places the child at risk for these effects while adding to the overall cost of medical care.⁴

The overall utilization of diagnostic imaging is increasing in pediatric emergency departments.⁴ When questioning why this is the case, one should consider the method of problem solving used by most physicians. After formulating initial hypotheses based on available information, prior knowledge, and experience, physicians aim to obtain additional data to confirm or reject each hypothesis.⁵Despite evidence that abdominal x-ray findings correlate poorly with clinical severity of constipation, radiography is widely available and may be thought of as a cheap and noninvasive means to further investigate. Physicians may believe that an x-ray will allow for quantification of stool in the colon, thereby supporting or refuting one of the hypotheses. In this way, an x-ray can be thought of as a confirmatory test for constipation. In children that have a history of constipation, physicians may seek to obtain an x-ray to assess for the severity of constipation or for improvement from a previous image.

A 2017 study surveyed 24 pediatric gastroenterologists after 72 patient encounters and found that the most common cause for obtaining an abdominal x-ray was for evaluation of stool burden (70%).⁵ Other reasons included assessing the need for a bowel clean-out (35%), diagnosing fecal impaction (27%), finding the cause for abdominal pain (24%), and demonstrating stool burden to a family (14%). This same study found that most of the polled providers used an abdominal x-ray to assess for constipation, and nearly half changed their management based on the findings. The study found that confidence levels were significantly higher after obtaining an x-ray, which likely indicates an internal need to boost the level of confidence in diagnosis and therapy.⁵

Many systematic reviews and retrospective studies have investigated the efficacy of abdominal x-rays for diagnosing constipation. One retrospective review involving 160 children with defecation complaints assessed the accuracy of different radiologic scoring methods in identifying children with constipation.⁶ Three pediatric gastroenterologists and 1 pediatric radiologist blindly applied 4 scoring methods: colonic transit time, Leech score, Barr score, and fecal loading. The results showed that all x-ray scoring methods had low sensitivity for diagnosing constipation, variable specificity, and low interobserver reproducibility of scores.⁶ There was also poor ability to differentiate between patients with constipation and nonretentive fecal incontinence. Fecal loading had the worst performance in differentiating between these 2. Greater than 20% of children with clinically diagnosed constipation had normal Barr and Leech scores.⁶ Another systematic review also found no evidence for a diagnostic association between clinical symptoms of constipation and fecal loading on abdominal x-rays.⁷ In this study, the sensitivity and specificity of the x-ray were as low as 61% and 55%, respectively, which indicate poor overall diagnostic accuracy. Abdominal x-rays are subjective, not standardized, and represent a single observation in time. The amount of fecal loading seen on imaging is subject to daily variation depending on the timing of last food intake and timing of last defecation. There is a large variance in interpretation of fecal loading, and any stool seen on an x-ray does not rule out another potential diagnosis causing abdominal pain.

In 2014, the North American Society for Pediatric Gastroenterology, Hepatology, & Nutrition (NASPGHAN) and the European Society for Paediatric Gastroenterology, Hepatology, and Nutrition (ESPGHAN) released joint clinical guidelines that the evidence supports not obtaining an abdominal x-ray to diagnose functional constipation.⁸ Similarly, the National Institute for Health and Care Excellence (NICE) stated that abdominal x-rays should not be recommended as an additional test for constipation in children.⁹ These groups advocate for diagnosing functional constipation clinically by using a careful history and physical exam.

The primary patient harm associated with abdominal x-rays is radiation exposure. While the amount of radiation in a single x-ray is low, children with constipation tend to have frequent revisits, significantly more than children with other common chronic conditions (eg, asthma and migraine headaches).¹⁰In accordance with an “As Low As Reasonably Achievable” (ALARA) concept for radiation dose, all imaging should be limited to studies that will contribute to patient care.⁴ The low sensitivity and specificity of abdominal x-rays in identifying constipation challenges whether any new information is being obtained from the imaging. Frequent visits and repeated unnecessary radiographs mean increased exposure to radiation and higher healthcare costs. Moreover, abdominal x-rays in the pediatric emergency room have been associated with missed diagnoses, false reassurance of constipation, more frequent admissions into the hospital, and longer hospital stays.

One multicenter retrospective cohort study that included approximately 282,000 children diagnosed with constipation found that children who received an abdominal x-ray were twice as likely to return to the emergency department with a clinically significant alternate diagnosis (0.33% vs 0.17%). The 2 most common missed diagnoses were acute appendicitis and intussusception.³ Another retrospective study that included about 3,700 children also found that x-rays were performed more frequently in children who were misdiagnosed than in those who did not have a significant alternate diagnosis (75% vs 46%).¹¹ In this case, both of these groups had a similar amount of stool on the x-rays as determined by the mean Leech scores. While this study identified an association between abdominal x-ray use and misdiagnoses, a causative effect was not necessarily discovered between the 2. The authors felt that even relatively large amounts of stool on an x-ray should not discount serious causes of abdominal pain or tenderness.¹¹ A third retrospective study determined that children who received an abdominal x-ray and were diagnosed with constipation were significantly more likely to be admitted to the hospital, further raising healthcare costs.¹² In this study, having an x-ray reduced the odds of being discharged home by about half. They also found that abdominal x-rays could be avoided if digital rectal exams were performed.¹²

Functional constipation is a clinical diagnosis based on a thorough collection of history and a complete physical exam in children of all ages, including digital examination of the rectum to assess for fecal impaction, if necessary.

The Rome IV criteria for chronic constipation can be helpful and includes at least 2 of the following features for at least 1 month in infants up to 4 years of age: 2 or fewer stools per week, history of excessive stool retention, history of painful or hard bowel movements, history of large-diameter stools, and presence of a large fecal mass in the rectum.¹³ In children who are toilet trained, 2 additional criteria may be used: at least 1 episode of fecal incontinence per week after being toilet-trained and history of large-diameter stools that may obstruct the toilet.¹³

The NASPGHAN and ESPGHAN joint guidelines from 2014 state that, while constipation is based on history and physical exam, a major role of the history and physical exam is to exclude other disorders that also present with difficulty in defecation.⁸ This can help identify red-flag features or complications and guide further investigation. While evidence did not support routine use of a digital rectal exam in diagnosing constipation, the guidelines stated that a rectal exam (visual and digital) helps to evaluate for anorectal malformations, anal stenosis, rectal tone, distension, erythema, skin tags, anal fissures, or a fecal mass.⁸ Digital rectal exams may be helpful in patients who do not immediately meet at least 2 historical features of the Rome IV criteria.

In regard to history, approximately 0.4%-20% of healthy children without constipation have at least 1 clinical feature listed above. Therefore, the use of a single clinical finding to diagnose constipation, such as decreased bowel frequency, can result in an inappropriate diagnosis. Children experience large variations in stool output depending on diet, genetics, and environmental factors.¹⁰ The usual pattern of bowel habits in humans range from 3 times daily to every 3 days.¹⁴ Importantly, there are times to order an abdominal x-ray for patients with abdominal pain. The NASPGHAN and ESPGHAN joint guidelines recommend obtaining abdominal x-rays to evaluate children who have concerning features, such as previous abdominal surgeries, known genetic conditions or malformations, bilious emesis, or severe abdominal distension.⁸

• Functional constipation should be diagnosed based purely on a thorough history and physical examination, including a rectal exam
• Abdominal x-rays (ordered for any reason) should not be used to diagnose or assess for functional constipation

Performing abdominal x-rays to assess for pediatric functional constipation is not beneficial and potentially harmful to patients. Multiple retrospective studies revealed no diagnostic association between clinical symptoms or severity of constipation and findings on abdominal radiography. X-rays have very low sensitivity and specificity for diagnosing constipation. In the pediatric emergency department, abdominal x-rays completed for patients diagnosed with constipation have been associated with missed diagnoses, false reassurance of constipation, more frequent admissions into the hospital, longer hospital stays, higher healthcare costs, and unnecessary radiation exposure. The NICE as well as 2014 NASPGHAN and ESPGHAN clinical guidelines recommend against obtaining x-rays to diagnose constipation. The most effective way to diagnose functional constipation in children is with a thorough collection of history and physical exam. In the introductory case, the boy received an osmotic laxative based on abdominal x-ray findings, which resulted in the adverse effect of diarrhea. This case demonstrates how using abdominal x-rays to assess for constipation can be misleading and emphasizes the importance of collecting a thorough history and physical exam.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason^™”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason^™” topics by emailing TWDFNR@hospitalmedicine.org.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

A 5-year old boy is admitted to the hospital for a bowel clean-out after presenting with abdominal pain and having an abdominal x-ray that demonstrated a “moderate stool burden.” After ingestion of the bowel prep, he develops worsening abdominal cramping and diarrhea. Upon reviewing the bowel history with his mother afterward, the team learns that he has had a bowel movement every 1-2 days as usual and has been having soft stools without any straining, pain, or blood present.

Functional constipation is a common clinical problem in pediatrics and constitutes a large number of admissions into hospitals and visits to clinics and emergency departments. In the United States, up to 36% of children are affected.Associated healthcare costs for children with constipation are estimated at $5.9 billion per year, which is $3.9 billion more than the general pediatric population without constipation.¹ In 2011, American children aged 17 years and younger had more than 270,000 visits to the emergency department for constipation.² As many as 70% of children who are given a diagnosis of constipation in the emergency department have an abdominal x-ray completed.³ The carcinogenic effects of radiation from radiography are well known. Unnecessary imaging places the child at risk for these effects while adding to the overall cost of medical care.⁴

The overall utilization of diagnostic imaging is increasing in pediatric emergency departments.⁴ When questioning why this is the case, one should consider the method of problem solving used by most physicians. After formulating initial hypotheses based on available information, prior knowledge, and experience, physicians aim to obtain additional data to confirm or reject each hypothesis.⁵Despite evidence that abdominal x-ray findings correlate poorly with clinical severity of constipation, radiography is widely available and may be thought of as a cheap and noninvasive means to further investigate. Physicians may believe that an x-ray will allow for quantification of stool in the colon, thereby supporting or refuting one of the hypotheses. In this way, an x-ray can be thought of as a confirmatory test for constipation. In children that have a history of constipation, physicians may seek to obtain an x-ray to assess for the severity of constipation or for improvement from a previous image.

A 2017 study surveyed 24 pediatric gastroenterologists after 72 patient encounters and found that the most common cause for obtaining an abdominal x-ray was for evaluation of stool burden (70%).⁵ Other reasons included assessing the need for a bowel clean-out (35%), diagnosing fecal impaction (27%), finding the cause for abdominal pain (24%), and demonstrating stool burden to a family (14%). This same study found that most of the polled providers used an abdominal x-ray to assess for constipation, and nearly half changed their management based on the findings. The study found that confidence levels were significantly higher after obtaining an x-ray, which likely indicates an internal need to boost the level of confidence in diagnosis and therapy.⁵

Many systematic reviews and retrospective studies have investigated the efficacy of abdominal x-rays for diagnosing constipation. One retrospective review involving 160 children with defecation complaints assessed the accuracy of different radiologic scoring methods in identifying children with constipation.⁶ Three pediatric gastroenterologists and 1 pediatric radiologist blindly applied 4 scoring methods: colonic transit time, Leech score, Barr score, and fecal loading. The results showed that all x-ray scoring methods had low sensitivity for diagnosing constipation, variable specificity, and low interobserver reproducibility of scores.⁶ There was also poor ability to differentiate between patients with constipation and nonretentive fecal incontinence. Fecal loading had the worst performance in differentiating between these 2. Greater than 20% of children with clinically diagnosed constipation had normal Barr and Leech scores.⁶ Another systematic review also found no evidence for a diagnostic association between clinical symptoms of constipation and fecal loading on abdominal x-rays.⁷ In this study, the sensitivity and specificity of the x-ray were as low as 61% and 55%, respectively, which indicate poor overall diagnostic accuracy. Abdominal x-rays are subjective, not standardized, and represent a single observation in time. The amount of fecal loading seen on imaging is subject to daily variation depending on the timing of last food intake and timing of last defecation. There is a large variance in interpretation of fecal loading, and any stool seen on an x-ray does not rule out another potential diagnosis causing abdominal pain.

In 2014, the North American Society for Pediatric Gastroenterology, Hepatology, & Nutrition (NASPGHAN) and the European Society for Paediatric Gastroenterology, Hepatology, and Nutrition (ESPGHAN) released joint clinical guidelines that the evidence supports not obtaining an abdominal x-ray to diagnose functional constipation.⁸ Similarly, the National Institute for Health and Care Excellence (NICE) stated that abdominal x-rays should not be recommended as an additional test for constipation in children.⁹ These groups advocate for diagnosing functional constipation clinically by using a careful history and physical exam.

The primary patient harm associated with abdominal x-rays is radiation exposure. While the amount of radiation in a single x-ray is low, children with constipation tend to have frequent revisits, significantly more than children with other common chronic conditions (eg, asthma and migraine headaches).¹⁰In accordance with an “As Low As Reasonably Achievable” (ALARA) concept for radiation dose, all imaging should be limited to studies that will contribute to patient care.⁴ The low sensitivity and specificity of abdominal x-rays in identifying constipation challenges whether any new information is being obtained from the imaging. Frequent visits and repeated unnecessary radiographs mean increased exposure to radiation and higher healthcare costs. Moreover, abdominal x-rays in the pediatric emergency room have been associated with missed diagnoses, false reassurance of constipation, more frequent admissions into the hospital, and longer hospital stays.

One multicenter retrospective cohort study that included approximately 282,000 children diagnosed with constipation found that children who received an abdominal x-ray were twice as likely to return to the emergency department with a clinically significant alternate diagnosis (0.33% vs 0.17%). The 2 most common missed diagnoses were acute appendicitis and intussusception.³ Another retrospective study that included about 3,700 children also found that x-rays were performed more frequently in children who were misdiagnosed than in those who did not have a significant alternate diagnosis (75% vs 46%).¹¹ In this case, both of these groups had a similar amount of stool on the x-rays as determined by the mean Leech scores. While this study identified an association between abdominal x-ray use and misdiagnoses, a causative effect was not necessarily discovered between the 2. The authors felt that even relatively large amounts of stool on an x-ray should not discount serious causes of abdominal pain or tenderness.¹¹ A third retrospective study determined that children who received an abdominal x-ray and were diagnosed with constipation were significantly more likely to be admitted to the hospital, further raising healthcare costs.¹² In this study, having an x-ray reduced the odds of being discharged home by about half. They also found that abdominal x-rays could be avoided if digital rectal exams were performed.¹²

Functional constipation is a clinical diagnosis based on a thorough collection of history and a complete physical exam in children of all ages, including digital examination of the rectum to assess for fecal impaction, if necessary.

The Rome IV criteria for chronic constipation can be helpful and includes at least 2 of the following features for at least 1 month in infants up to 4 years of age: 2 or fewer stools per week, history of excessive stool retention, history of painful or hard bowel movements, history of large-diameter stools, and presence of a large fecal mass in the rectum.¹³ In children who are toilet trained, 2 additional criteria may be used: at least 1 episode of fecal incontinence per week after being toilet-trained and history of large-diameter stools that may obstruct the toilet.¹³

The NASPGHAN and ESPGHAN joint guidelines from 2014 state that, while constipation is based on history and physical exam, a major role of the history and physical exam is to exclude other disorders that also present with difficulty in defecation.⁸ This can help identify red-flag features or complications and guide further investigation. While evidence did not support routine use of a digital rectal exam in diagnosing constipation, the guidelines stated that a rectal exam (visual and digital) helps to evaluate for anorectal malformations, anal stenosis, rectal tone, distension, erythema, skin tags, anal fissures, or a fecal mass.⁸ Digital rectal exams may be helpful in patients who do not immediately meet at least 2 historical features of the Rome IV criteria.

In regard to history, approximately 0.4%-20% of healthy children without constipation have at least 1 clinical feature listed above. Therefore, the use of a single clinical finding to diagnose constipation, such as decreased bowel frequency, can result in an inappropriate diagnosis. Children experience large variations in stool output depending on diet, genetics, and environmental factors.¹⁰ The usual pattern of bowel habits in humans range from 3 times daily to every 3 days.¹⁴ Importantly, there are times to order an abdominal x-ray for patients with abdominal pain. The NASPGHAN and ESPGHAN joint guidelines recommend obtaining abdominal x-rays to evaluate children who have concerning features, such as previous abdominal surgeries, known genetic conditions or malformations, bilious emesis, or severe abdominal distension.⁸

• Functional constipation should be diagnosed based purely on a thorough history and physical examination, including a rectal exam
• Abdominal x-rays (ordered for any reason) should not be used to diagnose or assess for functional constipation

Performing abdominal x-rays to assess for pediatric functional constipation is not beneficial and potentially harmful to patients. Multiple retrospective studies revealed no diagnostic association between clinical symptoms or severity of constipation and findings on abdominal radiography. X-rays have very low sensitivity and specificity for diagnosing constipation. In the pediatric emergency department, abdominal x-rays completed for patients diagnosed with constipation have been associated with missed diagnoses, false reassurance of constipation, more frequent admissions into the hospital, longer hospital stays, higher healthcare costs, and unnecessary radiation exposure. The NICE as well as 2014 NASPGHAN and ESPGHAN clinical guidelines recommend against obtaining x-rays to diagnose constipation. The most effective way to diagnose functional constipation in children is with a thorough collection of history and physical exam. In the introductory case, the boy received an osmotic laxative based on abdominal x-ray findings, which resulted in the adverse effect of diarrhea. This case demonstrates how using abdominal x-rays to assess for constipation can be misleading and emphasizes the importance of collecting a thorough history and physical exam.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason^™”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason^™” topics by emailing TWDFNR@hospitalmedicine.org.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

A 5-year old boy is admitted to the hospital for a bowel clean-out after presenting with abdominal pain and having an abdominal x-ray that demonstrated a “moderate stool burden.” After ingestion of the bowel prep, he develops worsening abdominal cramping and diarrhea. Upon reviewing the bowel history with his mother afterward, the team learns that he has had a bowel movement every 1-2 days as usual and has been having soft stools without any straining, pain, or blood present.

Functional constipation is a common clinical problem in pediatrics and constitutes a large number of admissions into hospitals and visits to clinics and emergency departments. In the United States, up to 36% of children are affected.Associated healthcare costs for children with constipation are estimated at $5.9 billion per year, which is $3.9 billion more than the general pediatric population without constipation.¹ In 2011, American children aged 17 years and younger had more than 270,000 visits to the emergency department for constipation.² As many as 70% of children who are given a diagnosis of constipation in the emergency department have an abdominal x-ray completed.³ The carcinogenic effects of radiation from radiography are well known. Unnecessary imaging places the child at risk for these effects while adding to the overall cost of medical care.⁴

The overall utilization of diagnostic imaging is increasing in pediatric emergency departments.⁴ When questioning why this is the case, one should consider the method of problem solving used by most physicians. After formulating initial hypotheses based on available information, prior knowledge, and experience, physicians aim to obtain additional data to confirm or reject each hypothesis.⁵Despite evidence that abdominal x-ray findings correlate poorly with clinical severity of constipation, radiography is widely available and may be thought of as a cheap and noninvasive means to further investigate. Physicians may believe that an x-ray will allow for quantification of stool in the colon, thereby supporting or refuting one of the hypotheses. In this way, an x-ray can be thought of as a confirmatory test for constipation. In children that have a history of constipation, physicians may seek to obtain an x-ray to assess for the severity of constipation or for improvement from a previous image.

A 2017 study surveyed 24 pediatric gastroenterologists after 72 patient encounters and found that the most common cause for obtaining an abdominal x-ray was for evaluation of stool burden (70%).⁵ Other reasons included assessing the need for a bowel clean-out (35%), diagnosing fecal impaction (27%), finding the cause for abdominal pain (24%), and demonstrating stool burden to a family (14%). This same study found that most of the polled providers used an abdominal x-ray to assess for constipation, and nearly half changed their management based on the findings. The study found that confidence levels were significantly higher after obtaining an x-ray, which likely indicates an internal need to boost the level of confidence in diagnosis and therapy.⁵

Many systematic reviews and retrospective studies have investigated the efficacy of abdominal x-rays for diagnosing constipation. One retrospective review involving 160 children with defecation complaints assessed the accuracy of different radiologic scoring methods in identifying children with constipation.⁶ Three pediatric gastroenterologists and 1 pediatric radiologist blindly applied 4 scoring methods: colonic transit time, Leech score, Barr score, and fecal loading. The results showed that all x-ray scoring methods had low sensitivity for diagnosing constipation, variable specificity, and low interobserver reproducibility of scores.⁶ There was also poor ability to differentiate between patients with constipation and nonretentive fecal incontinence. Fecal loading had the worst performance in differentiating between these 2. Greater than 20% of children with clinically diagnosed constipation had normal Barr and Leech scores.⁶ Another systematic review also found no evidence for a diagnostic association between clinical symptoms of constipation and fecal loading on abdominal x-rays.⁷ In this study, the sensitivity and specificity of the x-ray were as low as 61% and 55%, respectively, which indicate poor overall diagnostic accuracy. Abdominal x-rays are subjective, not standardized, and represent a single observation in time. The amount of fecal loading seen on imaging is subject to daily variation depending on the timing of last food intake and timing of last defecation. There is a large variance in interpretation of fecal loading, and any stool seen on an x-ray does not rule out another potential diagnosis causing abdominal pain.

In 2014, the North American Society for Pediatric Gastroenterology, Hepatology, & Nutrition (NASPGHAN) and the European Society for Paediatric Gastroenterology, Hepatology, and Nutrition (ESPGHAN) released joint clinical guidelines that the evidence supports not obtaining an abdominal x-ray to diagnose functional constipation.⁸ Similarly, the National Institute for Health and Care Excellence (NICE) stated that abdominal x-rays should not be recommended as an additional test for constipation in children.⁹ These groups advocate for diagnosing functional constipation clinically by using a careful history and physical exam.

The primary patient harm associated with abdominal x-rays is radiation exposure. While the amount of radiation in a single x-ray is low, children with constipation tend to have frequent revisits, significantly more than children with other common chronic conditions (eg, asthma and migraine headaches).¹⁰In accordance with an “As Low As Reasonably Achievable” (ALARA) concept for radiation dose, all imaging should be limited to studies that will contribute to patient care.⁴ The low sensitivity and specificity of abdominal x-rays in identifying constipation challenges whether any new information is being obtained from the imaging. Frequent visits and repeated unnecessary radiographs mean increased exposure to radiation and higher healthcare costs. Moreover, abdominal x-rays in the pediatric emergency room have been associated with missed diagnoses, false reassurance of constipation, more frequent admissions into the hospital, and longer hospital stays.

One multicenter retrospective cohort study that included approximately 282,000 children diagnosed with constipation found that children who received an abdominal x-ray were twice as likely to return to the emergency department with a clinically significant alternate diagnosis (0.33% vs 0.17%). The 2 most common missed diagnoses were acute appendicitis and intussusception.³ Another retrospective study that included about 3,700 children also found that x-rays were performed more frequently in children who were misdiagnosed than in those who did not have a significant alternate diagnosis (75% vs 46%).¹¹ In this case, both of these groups had a similar amount of stool on the x-rays as determined by the mean Leech scores. While this study identified an association between abdominal x-ray use and misdiagnoses, a causative effect was not necessarily discovered between the 2. The authors felt that even relatively large amounts of stool on an x-ray should not discount serious causes of abdominal pain or tenderness.¹¹ A third retrospective study determined that children who received an abdominal x-ray and were diagnosed with constipation were significantly more likely to be admitted to the hospital, further raising healthcare costs.¹² In this study, having an x-ray reduced the odds of being discharged home by about half. They also found that abdominal x-rays could be avoided if digital rectal exams were performed.¹²

Functional constipation is a clinical diagnosis based on a thorough collection of history and a complete physical exam in children of all ages, including digital examination of the rectum to assess for fecal impaction, if necessary.

The Rome IV criteria for chronic constipation can be helpful and includes at least 2 of the following features for at least 1 month in infants up to 4 years of age: 2 or fewer stools per week, history of excessive stool retention, history of painful or hard bowel movements, history of large-diameter stools, and presence of a large fecal mass in the rectum.¹³ In children who are toilet trained, 2 additional criteria may be used: at least 1 episode of fecal incontinence per week after being toilet-trained and history of large-diameter stools that may obstruct the toilet.¹³

The NASPGHAN and ESPGHAN joint guidelines from 2014 state that, while constipation is based on history and physical exam, a major role of the history and physical exam is to exclude other disorders that also present with difficulty in defecation.⁸ This can help identify red-flag features or complications and guide further investigation. While evidence did not support routine use of a digital rectal exam in diagnosing constipation, the guidelines stated that a rectal exam (visual and digital) helps to evaluate for anorectal malformations, anal stenosis, rectal tone, distension, erythema, skin tags, anal fissures, or a fecal mass.⁸ Digital rectal exams may be helpful in patients who do not immediately meet at least 2 historical features of the Rome IV criteria.

In regard to history, approximately 0.4%-20% of healthy children without constipation have at least 1 clinical feature listed above. Therefore, the use of a single clinical finding to diagnose constipation, such as decreased bowel frequency, can result in an inappropriate diagnosis. Children experience large variations in stool output depending on diet, genetics, and environmental factors.¹⁰ The usual pattern of bowel habits in humans range from 3 times daily to every 3 days.¹⁴ Importantly, there are times to order an abdominal x-ray for patients with abdominal pain. The NASPGHAN and ESPGHAN joint guidelines recommend obtaining abdominal x-rays to evaluate children who have concerning features, such as previous abdominal surgeries, known genetic conditions or malformations, bilious emesis, or severe abdominal distension.⁸

• Functional constipation should be diagnosed based purely on a thorough history and physical examination, including a rectal exam
• Abdominal x-rays (ordered for any reason) should not be used to diagnose or assess for functional constipation

Performing abdominal x-rays to assess for pediatric functional constipation is not beneficial and potentially harmful to patients. Multiple retrospective studies revealed no diagnostic association between clinical symptoms or severity of constipation and findings on abdominal radiography. X-rays have very low sensitivity and specificity for diagnosing constipation. In the pediatric emergency department, abdominal x-rays completed for patients diagnosed with constipation have been associated with missed diagnoses, false reassurance of constipation, more frequent admissions into the hospital, longer hospital stays, higher healthcare costs, and unnecessary radiation exposure. The NICE as well as 2014 NASPGHAN and ESPGHAN clinical guidelines recommend against obtaining x-rays to diagnose constipation. The most effective way to diagnose functional constipation in children is with a thorough collection of history and physical exam. In the introductory case, the boy received an osmotic laxative based on abdominal x-ray findings, which resulted in the adverse effect of diarrhea. This case demonstrates how using abdominal x-rays to assess for constipation can be misleading and emphasizes the importance of collecting a thorough history and physical exam.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason^™”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason^™” topics by emailing TWDFNR@hospitalmedicine.org.

A 19-year-old man with Duchenne Muscular Dystrophy (DMD) presented to the Emergency Department (ED) for left knee pain after ejection from his motorized wheelchair at a low velocity. In the ED, he developed increasing respiratory distress.

When addressing a new problem in a patient with a chronic condition, it is crucial to first understand the chronic condition and then consider whether the presenting symptoms relate to that condition or stem from an unrelated inciting event.

Patients with DMD are at risk of pulmonary complications relating to their underlying disease. For instance, dysphagia and ineffective cough can predispose them to recurrent aspiration pneumonitis and/or pneumonia, whereas decreased lung compliance (from scoliosis, atelectasis, and/or pulmonary fibrosis) and respiratory muscle weakness can progress to ventilatory failure. In addition, patients with DMD are at risk for pulmonary thromboembolism in the setting of immobility. Patients with DMD may also develop congestive heart failure resulting from myocardial fibrosis and nonischemic cardiomyopathy.

The ejection from his wheelchair signals potential trauma-associated conditions that could explain his respiratory distress. Respiratory complications of blunt thoracic trauma include pulmonary contusion, pneumothorax, flail chest (resulting from fractured ribs), and acute respiratory distress syndrome (ARDS). Lower extremity injury can result in venous thrombosis and pulmonary thromboembolism. While classically associated with long bone fractures, fat embolism syndrome (FES) may rarely occur with rib fractures and soft-tissue trauma. Respiratory compromise may also result from cervical spinal cord injury or severe anemia from trauma-associated hemorrhage.

Additional past medical history included growth hormone deficiency, migraine headaches, osteoporosis secondary to chronic steroid use, cardiac fibrosis of the inferolateral wall and septum with a baseline left ventricular ejection fraction of 65%, and atrial fibrillation. His medications included calcium carbonate, vitamin D, omeprazole, lisinopril, metoprolol, prednisone, escitalopram, and testosterone. Physical examination revealed an ill-appearing obese man in respiratory distress. Temperature was 37.3°C, heart rate was 102 beats per minute (bpm), blood pressure was 110/74 mm Hg. His oxygen saturation was 93% with a respiratory rate of 25 breaths per minute while breathing ambient air. His lung sounds were clear, and his heart was without murmur. The left knee was diffusely tender to palpation without specific point tenderness. Strength was 2/5 with flexion and extension at the bilateral knees and hips and 3/5 flexion and extension at the bilateral elbows. He reported this level of weakness was his baseline. Radiographs revealed a minimally displaced Salter Harris II fracture (fracture line through the metaphysis and growth plate) of the left distal femur. His fracture was splinted early in his ED course. During his ED evaluation, the patient had acute worsening of tachycardia to 130 bpm, increased respiratory rate of 34 breaths per minute, and hypoxemia with an oxygen saturation of 83% on ambient air. He was placed on 3 L/min of oxygen via nasal cannula with improvement in his oxygen saturation to 90%. A chest radiograph was unremarkable, without evidence of pneumothorax, effusion, or pneumonia. The patient was admitted to the hospital.

The acute onset of tachypnea, tachycardia, and hypoxia, accompanied by a clear lung exam and normal chest radiograph, increases the likelihood of a pulmonary embolism. Obesity, testosterone therapy, and trauma increase his susceptibility to venous thromboembolism, while a distal femur fracture increases his risk for FES. Acute pulmonary aspiration often presents with initially absent or subtle radiographic findings. An arterial blood gas analysis would determine the presence and extent of an alveolar-arterial (A-a) gradient; a normal A-a gradient is seen in hypoventilation, while an elevated A-a gradient is seen in conditions affecting gas exchange, including pulmonary emboli and alveolar filling processes. His hypoxemia only partially corrects with supplemental oxygen, raising the possibility of capillary or anatomic shunting. Capillary shunting may occur with atelectasis, aspiration/pneumonia and pulmonary edema, whereas anatomic shunting can be intra-cardiac (eg, patent foramen ovale or septic defect) or intrapulmonary (eg, arteriovenous malformations). Patients with pulmonary emboli may also develop right-to-left shunting because of increased pulmonary vascular resistance, although hypoxemia with pulmonary emboli largely relates to ventilation/perfusion mismatch and decreased level of mixed venous blood oxygen (PvO₂).

This patient’s complex medical history warrants a broadened differential with consideration of his cardiac history, including myocardial fibrosis and arrhythmia, and the impact of exposure to steroids on his immune and musculoskeletal systems. He has a history of atrial fibrillation, and an electrocardiogram is warranted to determine the underlying rhythm. Prolonged periods of rapid ventricular response may lead to tachycardia-induced cardiomyopathy. Myocardial fibrosis may progress despite use of angiotensin-converting enzyme inhibitors and is associated with systolic and/or diastolic dysfunction, although neither the examination findings provided nor the chest radiograph are suggestive of decompensated heart failure. Chronic exposure to corticosteroids (used in DMD to improve muscle strength and function) may predispose to numerous infectious and metabolic complications. Up to 10%-15% of patients with Pneumocystis jirovecii pneumonia may present with a normal chest radiograph. Acute adrenal insufficiency can present with tachycardia, weakness, and respiratory distress, so recent prednisone dose changes or interruptions should be assessed.

The patient’s respiratory status worsened. In light of his complex medical history, he was transferred to a children’s hospital for a higher level of care with a presumptive diagnosis of aspiration pneumonia. Upon reassessment at the new facility, the patient reported an ongoing and severe headache since his initial injury. NSAIDs had been given prior to transfer. His exam continued to be significant for tachycardia, tachypnea, and hypoxemia. His cardiac and lung examinations were otherwise normal. A comprehensive metabolic panel, procalcitonin, complete blood count with differential, and lactate were normal; his C-reactive protein (CRP) was 46.8 mg/dL (Normal <8 mg/dL). A computed tomography (CT) angiogram of the chest revealed small multifocal nodular ground-glass opacities, especially in the lower lobes, concerning for microatelectasis, multifocal pneumonia, or aspiration pneumonia. After consultation with pediatric pulmonology consultants, antimicrobials were held during the initial phase of work-up.

CRP elevation is nonspecific and signals the presence of focal or systemic inflammation and is often elevated to a milder extent in obese patients with DMD. While normal procalcitonin argues against bacterial pneumonia, the precise level can be informative, and serial procalcitonin values may be more helpful than a single value. Although antecedent respiratory symptoms were not mentioned, viral or fungal pneumonia can present insidiously. An occult malignancy may be incidentally discovered when patients present for unrelated issues, although this and other sources of elevated CRP (eg, exacerbation of an autoimmune disease or drug reaction) remain less likely given the acuity of his presentation. Acute pulmonary embolism may be associated with a systemic inflammatory response and elevation in CRP.

In addition to the radiographic differential diagnosis already presented, the appearance of multifocal opacifications with hypoxemia raises the possibility of pulmonary infarcts or noncardiogenic pulmonary edema.

On hospital day 2, the patient continued to complain of “the worst headache of his life” as well as blurry vision and seeing “dark spots.” His headache did not improve with NSAIDs. A noncontrast CT scan of the head was normal. Neurology was consulted. Given his symptoms, history of migraines, stable neurological examination, and normal head CT, he was diagnosed with migraines and administered fluids, prochlorperazine, diphenhydramine, ondansetron, and NSAIDs. His headache continued and he continued to require supplemental oxygen.

The combination of hypoxemia, severe headache, and vision changes remains consistent with systemic emboli caused by thromboembolism or fat embolism. Headache assessment must also involve screening for “red flags,” which include sudden onset, antecedent head trauma, systemic illness (eg, fever or meningismus), focal neurologic findings, papilledema, changes with position or Valsalva, and immunosuppression. Although primary headache syndromes (eg, migraines or tension and cluster headache) may be triggered in the setting of trauma and systemic illness, “the worst headache of my life” is a concerning symptom that warrants urgent attention. While this invokes the possibility of a subarachnoid hemorrhage (SAH), headache severity is nonspecific, and rapid onset (ie, thunderclap headache) would be more suggestive. After 6 hours of symptoms, the sensitivity of head CT for detecting SAH declines, and lumbar puncture would be warranted to evaluate for xanthochromia.

His blurry vision and dark spots require testing of visual acuity and visual fields, as well as fundoscopic examination to assess for embolic phenomena or papilledema. Migraine is classically associated with “positive” or scintillating scotomata, although dark spots may occur. The presence of horizontal diplopia would indicate a cranial nerve VI palsy, which can occur with increased intracranial pressure. Visual-field cuts may also present as blurry vision, and monocular vs binocular deficits signal whether the issue is anterior or involving/posterior to the optic chiasm, respectively. Magnetic resonance imaging (MRI) may reveal the presence or sequelae of cerebral emboli (eg, fat emboli), including vasogenic edema.

Dilated fundus examination revealed Purtscher retinopathy: bilateral cotton-wool spots and larger areas of retinal whitening (Purtscher flecken).

Typical findings of Purtscher retinopathy include Purtscher flecken, cotton-wool spots, retinal hemorrhage, and optic disc edema. Purtscher retinopathy is classically associated with severe head trauma. Without associated head trauma, the term “Purtscher-like retinopathy” is used. Conditions that can cause Purtscher-like retinopathy include pancreatitis, vasculitis, microangiopathy, chronic renal failure, and systemic embolization. The most likely source of systemic embolization remains fat emboli stemming from his femur fracture. Treatment of FES is largely supportive.

The possibility of fat emboli had been repeatedly raised by the patient’s mother since admission. While providers had considered this a possibility, it was discounted early on because of the minor nature of the patient’s orthopedic trauma, the lack of clear radiographic evidence for pulmonary emboli on chest CT, and the normal head CT. The findings on the ophthalmologist’s fundoscopic examination led the primary team to reconsider FES, along with thromboemboli and pancreatitis. Lipase was normal. MRI of the brain with contrast revealed >20 microinfarcts in the bilateral hemispheres, left corpus callosum, and bilateral basal ganglia. The CT angiogram of the chest was rereviewed; the pediatric radiologists suggested that microinfarcts could explain the patchy small ground glass opacities seen in the lungs. A transthoracic echocardiogram and electrocardiogram were normal. The diagnosis of FES was made, and the patient was started on aspirin and enoxaparin prophylaxis. His headache and respiratory status improved, and he was discharged home with close follow-up.

FES is a rare complication associated with long bone fractures and orthopedic manipulation.^1,2 The exact mechanism of fat emboli production is unknown, but two theories prevail. The mechanical theory states that an outside mechanical source causes bone marrow contents or adipose tissue contents to be dislodged into the circulation where they travel through the venous circulation to become embedded in the lungs.^1,2 These fragments may also migrate to the arterial circulation, through a patent foramen ovale or intrapulmonary shunts, leading to end organ damage.^1,2 The biochemical theory suggests that fat emboli in the venous circulation precipitate an inflammatory and prothrombotic cascade that triggers fibrin production, platelet aggregation, and release of free fatty acids into the circulation, predisposing patients to develop multifocal systemic emboli.¹

Although the classic triad in FES includes respiratory symptoms, rash, and CNS symptoms, all three findings are only present in 1%-29% of cases.^1,2 Respiratory abnormalities, ranging from tachypnea and dyspnea to ARDS and hypoxic respiratory failure, occur in up to 75% of patients with FES.¹ Central nervous system (CNS) complications, including headache, confusion, coma, seizures, and death caused by cerebral ischemia, occur in up to 86% of patients.^1,2 Petechiae may occur in 20%-60% of patients and are usually located on nondependent regions of the body such as the head, neck, and chest.

• FES is a rare condition that most commonly manifests with respiratory, neurological, and cutaneous findings.
• Patients with Duchenne’s Muscular Dystrophy are likely at increased risk for FES even with minor trauma; this makes wheelchair restraints and safe transfers fundamental.
• Patients with medical complexity and their caregivers are key members of the diagnostic team.

A 19-year-old man with Duchenne Muscular Dystrophy (DMD) presented to the Emergency Department (ED) for left knee pain after ejection from his motorized wheelchair at a low velocity. In the ED, he developed increasing respiratory distress.

When addressing a new problem in a patient with a chronic condition, it is crucial to first understand the chronic condition and then consider whether the presenting symptoms relate to that condition or stem from an unrelated inciting event.

Patients with DMD are at risk of pulmonary complications relating to their underlying disease. For instance, dysphagia and ineffective cough can predispose them to recurrent aspiration pneumonitis and/or pneumonia, whereas decreased lung compliance (from scoliosis, atelectasis, and/or pulmonary fibrosis) and respiratory muscle weakness can progress to ventilatory failure. In addition, patients with DMD are at risk for pulmonary thromboembolism in the setting of immobility. Patients with DMD may also develop congestive heart failure resulting from myocardial fibrosis and nonischemic cardiomyopathy.

The ejection from his wheelchair signals potential trauma-associated conditions that could explain his respiratory distress. Respiratory complications of blunt thoracic trauma include pulmonary contusion, pneumothorax, flail chest (resulting from fractured ribs), and acute respiratory distress syndrome (ARDS). Lower extremity injury can result in venous thrombosis and pulmonary thromboembolism. While classically associated with long bone fractures, fat embolism syndrome (FES) may rarely occur with rib fractures and soft-tissue trauma. Respiratory compromise may also result from cervical spinal cord injury or severe anemia from trauma-associated hemorrhage.

Additional past medical history included growth hormone deficiency, migraine headaches, osteoporosis secondary to chronic steroid use, cardiac fibrosis of the inferolateral wall and septum with a baseline left ventricular ejection fraction of 65%, and atrial fibrillation. His medications included calcium carbonate, vitamin D, omeprazole, lisinopril, metoprolol, prednisone, escitalopram, and testosterone. Physical examination revealed an ill-appearing obese man in respiratory distress. Temperature was 37.3°C, heart rate was 102 beats per minute (bpm), blood pressure was 110/74 mm Hg. His oxygen saturation was 93% with a respiratory rate of 25 breaths per minute while breathing ambient air. His lung sounds were clear, and his heart was without murmur. The left knee was diffusely tender to palpation without specific point tenderness. Strength was 2/5 with flexion and extension at the bilateral knees and hips and 3/5 flexion and extension at the bilateral elbows. He reported this level of weakness was his baseline. Radiographs revealed a minimally displaced Salter Harris II fracture (fracture line through the metaphysis and growth plate) of the left distal femur. His fracture was splinted early in his ED course. During his ED evaluation, the patient had acute worsening of tachycardia to 130 bpm, increased respiratory rate of 34 breaths per minute, and hypoxemia with an oxygen saturation of 83% on ambient air. He was placed on 3 L/min of oxygen via nasal cannula with improvement in his oxygen saturation to 90%. A chest radiograph was unremarkable, without evidence of pneumothorax, effusion, or pneumonia. The patient was admitted to the hospital.

The acute onset of tachypnea, tachycardia, and hypoxia, accompanied by a clear lung exam and normal chest radiograph, increases the likelihood of a pulmonary embolism. Obesity, testosterone therapy, and trauma increase his susceptibility to venous thromboembolism, while a distal femur fracture increases his risk for FES. Acute pulmonary aspiration often presents with initially absent or subtle radiographic findings. An arterial blood gas analysis would determine the presence and extent of an alveolar-arterial (A-a) gradient; a normal A-a gradient is seen in hypoventilation, while an elevated A-a gradient is seen in conditions affecting gas exchange, including pulmonary emboli and alveolar filling processes. His hypoxemia only partially corrects with supplemental oxygen, raising the possibility of capillary or anatomic shunting. Capillary shunting may occur with atelectasis, aspiration/pneumonia and pulmonary edema, whereas anatomic shunting can be intra-cardiac (eg, patent foramen ovale or septic defect) or intrapulmonary (eg, arteriovenous malformations). Patients with pulmonary emboli may also develop right-to-left shunting because of increased pulmonary vascular resistance, although hypoxemia with pulmonary emboli largely relates to ventilation/perfusion mismatch and decreased level of mixed venous blood oxygen (PvO₂).

This patient’s complex medical history warrants a broadened differential with consideration of his cardiac history, including myocardial fibrosis and arrhythmia, and the impact of exposure to steroids on his immune and musculoskeletal systems. He has a history of atrial fibrillation, and an electrocardiogram is warranted to determine the underlying rhythm. Prolonged periods of rapid ventricular response may lead to tachycardia-induced cardiomyopathy. Myocardial fibrosis may progress despite use of angiotensin-converting enzyme inhibitors and is associated with systolic and/or diastolic dysfunction, although neither the examination findings provided nor the chest radiograph are suggestive of decompensated heart failure. Chronic exposure to corticosteroids (used in DMD to improve muscle strength and function) may predispose to numerous infectious and metabolic complications. Up to 10%-15% of patients with Pneumocystis jirovecii pneumonia may present with a normal chest radiograph. Acute adrenal insufficiency can present with tachycardia, weakness, and respiratory distress, so recent prednisone dose changes or interruptions should be assessed.

The patient’s respiratory status worsened. In light of his complex medical history, he was transferred to a children’s hospital for a higher level of care with a presumptive diagnosis of aspiration pneumonia. Upon reassessment at the new facility, the patient reported an ongoing and severe headache since his initial injury. NSAIDs had been given prior to transfer. His exam continued to be significant for tachycardia, tachypnea, and hypoxemia. His cardiac and lung examinations were otherwise normal. A comprehensive metabolic panel, procalcitonin, complete blood count with differential, and lactate were normal; his C-reactive protein (CRP) was 46.8 mg/dL (Normal <8 mg/dL). A computed tomography (CT) angiogram of the chest revealed small multifocal nodular ground-glass opacities, especially in the lower lobes, concerning for microatelectasis, multifocal pneumonia, or aspiration pneumonia. After consultation with pediatric pulmonology consultants, antimicrobials were held during the initial phase of work-up.

CRP elevation is nonspecific and signals the presence of focal or systemic inflammation and is often elevated to a milder extent in obese patients with DMD. While normal procalcitonin argues against bacterial pneumonia, the precise level can be informative, and serial procalcitonin values may be more helpful than a single value. Although antecedent respiratory symptoms were not mentioned, viral or fungal pneumonia can present insidiously. An occult malignancy may be incidentally discovered when patients present for unrelated issues, although this and other sources of elevated CRP (eg, exacerbation of an autoimmune disease or drug reaction) remain less likely given the acuity of his presentation. Acute pulmonary embolism may be associated with a systemic inflammatory response and elevation in CRP.

In addition to the radiographic differential diagnosis already presented, the appearance of multifocal opacifications with hypoxemia raises the possibility of pulmonary infarcts or noncardiogenic pulmonary edema.

On hospital day 2, the patient continued to complain of “the worst headache of his life” as well as blurry vision and seeing “dark spots.” His headache did not improve with NSAIDs. A noncontrast CT scan of the head was normal. Neurology was consulted. Given his symptoms, history of migraines, stable neurological examination, and normal head CT, he was diagnosed with migraines and administered fluids, prochlorperazine, diphenhydramine, ondansetron, and NSAIDs. His headache continued and he continued to require supplemental oxygen.

The combination of hypoxemia, severe headache, and vision changes remains consistent with systemic emboli caused by thromboembolism or fat embolism. Headache assessment must also involve screening for “red flags,” which include sudden onset, antecedent head trauma, systemic illness (eg, fever or meningismus), focal neurologic findings, papilledema, changes with position or Valsalva, and immunosuppression. Although primary headache syndromes (eg, migraines or tension and cluster headache) may be triggered in the setting of trauma and systemic illness, “the worst headache of my life” is a concerning symptom that warrants urgent attention. While this invokes the possibility of a subarachnoid hemorrhage (SAH), headache severity is nonspecific, and rapid onset (ie, thunderclap headache) would be more suggestive. After 6 hours of symptoms, the sensitivity of head CT for detecting SAH declines, and lumbar puncture would be warranted to evaluate for xanthochromia.

His blurry vision and dark spots require testing of visual acuity and visual fields, as well as fundoscopic examination to assess for embolic phenomena or papilledema. Migraine is classically associated with “positive” or scintillating scotomata, although dark spots may occur. The presence of horizontal diplopia would indicate a cranial nerve VI palsy, which can occur with increased intracranial pressure. Visual-field cuts may also present as blurry vision, and monocular vs binocular deficits signal whether the issue is anterior or involving/posterior to the optic chiasm, respectively. Magnetic resonance imaging (MRI) may reveal the presence or sequelae of cerebral emboli (eg, fat emboli), including vasogenic edema.

Dilated fundus examination revealed Purtscher retinopathy: bilateral cotton-wool spots and larger areas of retinal whitening (Purtscher flecken).

Typical findings of Purtscher retinopathy include Purtscher flecken, cotton-wool spots, retinal hemorrhage, and optic disc edema. Purtscher retinopathy is classically associated with severe head trauma. Without associated head trauma, the term “Purtscher-like retinopathy” is used. Conditions that can cause Purtscher-like retinopathy include pancreatitis, vasculitis, microangiopathy, chronic renal failure, and systemic embolization. The most likely source of systemic embolization remains fat emboli stemming from his femur fracture. Treatment of FES is largely supportive.

The possibility of fat emboli had been repeatedly raised by the patient’s mother since admission. While providers had considered this a possibility, it was discounted early on because of the minor nature of the patient’s orthopedic trauma, the lack of clear radiographic evidence for pulmonary emboli on chest CT, and the normal head CT. The findings on the ophthalmologist’s fundoscopic examination led the primary team to reconsider FES, along with thromboemboli and pancreatitis. Lipase was normal. MRI of the brain with contrast revealed >20 microinfarcts in the bilateral hemispheres, left corpus callosum, and bilateral basal ganglia. The CT angiogram of the chest was rereviewed; the pediatric radiologists suggested that microinfarcts could explain the patchy small ground glass opacities seen in the lungs. A transthoracic echocardiogram and electrocardiogram were normal. The diagnosis of FES was made, and the patient was started on aspirin and enoxaparin prophylaxis. His headache and respiratory status improved, and he was discharged home with close follow-up.

FES is a rare complication associated with long bone fractures and orthopedic manipulation.^1,2 The exact mechanism of fat emboli production is unknown, but two theories prevail. The mechanical theory states that an outside mechanical source causes bone marrow contents or adipose tissue contents to be dislodged into the circulation where they travel through the venous circulation to become embedded in the lungs.^1,2 These fragments may also migrate to the arterial circulation, through a patent foramen ovale or intrapulmonary shunts, leading to end organ damage.^1,2 The biochemical theory suggests that fat emboli in the venous circulation precipitate an inflammatory and prothrombotic cascade that triggers fibrin production, platelet aggregation, and release of free fatty acids into the circulation, predisposing patients to develop multifocal systemic emboli.¹

Although the classic triad in FES includes respiratory symptoms, rash, and CNS symptoms, all three findings are only present in 1%-29% of cases.^1,2 Respiratory abnormalities, ranging from tachypnea and dyspnea to ARDS and hypoxic respiratory failure, occur in up to 75% of patients with FES.¹ Central nervous system (CNS) complications, including headache, confusion, coma, seizures, and death caused by cerebral ischemia, occur in up to 86% of patients.^1,2 Petechiae may occur in 20%-60% of patients and are usually located on nondependent regions of the body such as the head, neck, and chest.

• FES is a rare condition that most commonly manifests with respiratory, neurological, and cutaneous findings.
• Patients with Duchenne’s Muscular Dystrophy are likely at increased risk for FES even with minor trauma; this makes wheelchair restraints and safe transfers fundamental.
• Patients with medical complexity and their caregivers are key members of the diagnostic team.

A 19-year-old man with Duchenne Muscular Dystrophy (DMD) presented to the Emergency Department (ED) for left knee pain after ejection from his motorized wheelchair at a low velocity. In the ED, he developed increasing respiratory distress.

When addressing a new problem in a patient with a chronic condition, it is crucial to first understand the chronic condition and then consider whether the presenting symptoms relate to that condition or stem from an unrelated inciting event.

Patients with DMD are at risk of pulmonary complications relating to their underlying disease. For instance, dysphagia and ineffective cough can predispose them to recurrent aspiration pneumonitis and/or pneumonia, whereas decreased lung compliance (from scoliosis, atelectasis, and/or pulmonary fibrosis) and respiratory muscle weakness can progress to ventilatory failure. In addition, patients with DMD are at risk for pulmonary thromboembolism in the setting of immobility. Patients with DMD may also develop congestive heart failure resulting from myocardial fibrosis and nonischemic cardiomyopathy.

The ejection from his wheelchair signals potential trauma-associated conditions that could explain his respiratory distress. Respiratory complications of blunt thoracic trauma include pulmonary contusion, pneumothorax, flail chest (resulting from fractured ribs), and acute respiratory distress syndrome (ARDS). Lower extremity injury can result in venous thrombosis and pulmonary thromboembolism. While classically associated with long bone fractures, fat embolism syndrome (FES) may rarely occur with rib fractures and soft-tissue trauma. Respiratory compromise may also result from cervical spinal cord injury or severe anemia from trauma-associated hemorrhage.

Additional past medical history included growth hormone deficiency, migraine headaches, osteoporosis secondary to chronic steroid use, cardiac fibrosis of the inferolateral wall and septum with a baseline left ventricular ejection fraction of 65%, and atrial fibrillation. His medications included calcium carbonate, vitamin D, omeprazole, lisinopril, metoprolol, prednisone, escitalopram, and testosterone. Physical examination revealed an ill-appearing obese man in respiratory distress. Temperature was 37.3°C, heart rate was 102 beats per minute (bpm), blood pressure was 110/74 mm Hg. His oxygen saturation was 93% with a respiratory rate of 25 breaths per minute while breathing ambient air. His lung sounds were clear, and his heart was without murmur. The left knee was diffusely tender to palpation without specific point tenderness. Strength was 2/5 with flexion and extension at the bilateral knees and hips and 3/5 flexion and extension at the bilateral elbows. He reported this level of weakness was his baseline. Radiographs revealed a minimally displaced Salter Harris II fracture (fracture line through the metaphysis and growth plate) of the left distal femur. His fracture was splinted early in his ED course. During his ED evaluation, the patient had acute worsening of tachycardia to 130 bpm, increased respiratory rate of 34 breaths per minute, and hypoxemia with an oxygen saturation of 83% on ambient air. He was placed on 3 L/min of oxygen via nasal cannula with improvement in his oxygen saturation to 90%. A chest radiograph was unremarkable, without evidence of pneumothorax, effusion, or pneumonia. The patient was admitted to the hospital.

The acute onset of tachypnea, tachycardia, and hypoxia, accompanied by a clear lung exam and normal chest radiograph, increases the likelihood of a pulmonary embolism. Obesity, testosterone therapy, and trauma increase his susceptibility to venous thromboembolism, while a distal femur fracture increases his risk for FES. Acute pulmonary aspiration often presents with initially absent or subtle radiographic findings. An arterial blood gas analysis would determine the presence and extent of an alveolar-arterial (A-a) gradient; a normal A-a gradient is seen in hypoventilation, while an elevated A-a gradient is seen in conditions affecting gas exchange, including pulmonary emboli and alveolar filling processes. His hypoxemia only partially corrects with supplemental oxygen, raising the possibility of capillary or anatomic shunting. Capillary shunting may occur with atelectasis, aspiration/pneumonia and pulmonary edema, whereas anatomic shunting can be intra-cardiac (eg, patent foramen ovale or septic defect) or intrapulmonary (eg, arteriovenous malformations). Patients with pulmonary emboli may also develop right-to-left shunting because of increased pulmonary vascular resistance, although hypoxemia with pulmonary emboli largely relates to ventilation/perfusion mismatch and decreased level of mixed venous blood oxygen (PvO₂).

This patient’s complex medical history warrants a broadened differential with consideration of his cardiac history, including myocardial fibrosis and arrhythmia, and the impact of exposure to steroids on his immune and musculoskeletal systems. He has a history of atrial fibrillation, and an electrocardiogram is warranted to determine the underlying rhythm. Prolonged periods of rapid ventricular response may lead to tachycardia-induced cardiomyopathy. Myocardial fibrosis may progress despite use of angiotensin-converting enzyme inhibitors and is associated with systolic and/or diastolic dysfunction, although neither the examination findings provided nor the chest radiograph are suggestive of decompensated heart failure. Chronic exposure to corticosteroids (used in DMD to improve muscle strength and function) may predispose to numerous infectious and metabolic complications. Up to 10%-15% of patients with Pneumocystis jirovecii pneumonia may present with a normal chest radiograph. Acute adrenal insufficiency can present with tachycardia, weakness, and respiratory distress, so recent prednisone dose changes or interruptions should be assessed.

The patient’s respiratory status worsened. In light of his complex medical history, he was transferred to a children’s hospital for a higher level of care with a presumptive diagnosis of aspiration pneumonia. Upon reassessment at the new facility, the patient reported an ongoing and severe headache since his initial injury. NSAIDs had been given prior to transfer. His exam continued to be significant for tachycardia, tachypnea, and hypoxemia. His cardiac and lung examinations were otherwise normal. A comprehensive metabolic panel, procalcitonin, complete blood count with differential, and lactate were normal; his C-reactive protein (CRP) was 46.8 mg/dL (Normal <8 mg/dL). A computed tomography (CT) angiogram of the chest revealed small multifocal nodular ground-glass opacities, especially in the lower lobes, concerning for microatelectasis, multifocal pneumonia, or aspiration pneumonia. After consultation with pediatric pulmonology consultants, antimicrobials were held during the initial phase of work-up.

CRP elevation is nonspecific and signals the presence of focal or systemic inflammation and is often elevated to a milder extent in obese patients with DMD. While normal procalcitonin argues against bacterial pneumonia, the precise level can be informative, and serial procalcitonin values may be more helpful than a single value. Although antecedent respiratory symptoms were not mentioned, viral or fungal pneumonia can present insidiously. An occult malignancy may be incidentally discovered when patients present for unrelated issues, although this and other sources of elevated CRP (eg, exacerbation of an autoimmune disease or drug reaction) remain less likely given the acuity of his presentation. Acute pulmonary embolism may be associated with a systemic inflammatory response and elevation in CRP.

In addition to the radiographic differential diagnosis already presented, the appearance of multifocal opacifications with hypoxemia raises the possibility of pulmonary infarcts or noncardiogenic pulmonary edema.

On hospital day 2, the patient continued to complain of “the worst headache of his life” as well as blurry vision and seeing “dark spots.” His headache did not improve with NSAIDs. A noncontrast CT scan of the head was normal. Neurology was consulted. Given his symptoms, history of migraines, stable neurological examination, and normal head CT, he was diagnosed with migraines and administered fluids, prochlorperazine, diphenhydramine, ondansetron, and NSAIDs. His headache continued and he continued to require supplemental oxygen.

The combination of hypoxemia, severe headache, and vision changes remains consistent with systemic emboli caused by thromboembolism or fat embolism. Headache assessment must also involve screening for “red flags,” which include sudden onset, antecedent head trauma, systemic illness (eg, fever or meningismus), focal neurologic findings, papilledema, changes with position or Valsalva, and immunosuppression. Although primary headache syndromes (eg, migraines or tension and cluster headache) may be triggered in the setting of trauma and systemic illness, “the worst headache of my life” is a concerning symptom that warrants urgent attention. While this invokes the possibility of a subarachnoid hemorrhage (SAH), headache severity is nonspecific, and rapid onset (ie, thunderclap headache) would be more suggestive. After 6 hours of symptoms, the sensitivity of head CT for detecting SAH declines, and lumbar puncture would be warranted to evaluate for xanthochromia.

His blurry vision and dark spots require testing of visual acuity and visual fields, as well as fundoscopic examination to assess for embolic phenomena or papilledema. Migraine is classically associated with “positive” or scintillating scotomata, although dark spots may occur. The presence of horizontal diplopia would indicate a cranial nerve VI palsy, which can occur with increased intracranial pressure. Visual-field cuts may also present as blurry vision, and monocular vs binocular deficits signal whether the issue is anterior or involving/posterior to the optic chiasm, respectively. Magnetic resonance imaging (MRI) may reveal the presence or sequelae of cerebral emboli (eg, fat emboli), including vasogenic edema.

Dilated fundus examination revealed Purtscher retinopathy: bilateral cotton-wool spots and larger areas of retinal whitening (Purtscher flecken).

Typical findings of Purtscher retinopathy include Purtscher flecken, cotton-wool spots, retinal hemorrhage, and optic disc edema. Purtscher retinopathy is classically associated with severe head trauma. Without associated head trauma, the term “Purtscher-like retinopathy” is used. Conditions that can cause Purtscher-like retinopathy include pancreatitis, vasculitis, microangiopathy, chronic renal failure, and systemic embolization. The most likely source of systemic embolization remains fat emboli stemming from his femur fracture. Treatment of FES is largely supportive.

The possibility of fat emboli had been repeatedly raised by the patient’s mother since admission. While providers had considered this a possibility, it was discounted early on because of the minor nature of the patient’s orthopedic trauma, the lack of clear radiographic evidence for pulmonary emboli on chest CT, and the normal head CT. The findings on the ophthalmologist’s fundoscopic examination led the primary team to reconsider FES, along with thromboemboli and pancreatitis. Lipase was normal. MRI of the brain with contrast revealed >20 microinfarcts in the bilateral hemispheres, left corpus callosum, and bilateral basal ganglia. The CT angiogram of the chest was rereviewed; the pediatric radiologists suggested that microinfarcts could explain the patchy small ground glass opacities seen in the lungs. A transthoracic echocardiogram and electrocardiogram were normal. The diagnosis of FES was made, and the patient was started on aspirin and enoxaparin prophylaxis. His headache and respiratory status improved, and he was discharged home with close follow-up.

FES is a rare complication associated with long bone fractures and orthopedic manipulation.^1,2 The exact mechanism of fat emboli production is unknown, but two theories prevail. The mechanical theory states that an outside mechanical source causes bone marrow contents or adipose tissue contents to be dislodged into the circulation where they travel through the venous circulation to become embedded in the lungs.^1,2 These fragments may also migrate to the arterial circulation, through a patent foramen ovale or intrapulmonary shunts, leading to end organ damage.^1,2 The biochemical theory suggests that fat emboli in the venous circulation precipitate an inflammatory and prothrombotic cascade that triggers fibrin production, platelet aggregation, and release of free fatty acids into the circulation, predisposing patients to develop multifocal systemic emboli.¹

Although the classic triad in FES includes respiratory symptoms, rash, and CNS symptoms, all three findings are only present in 1%-29% of cases.^1,2 Respiratory abnormalities, ranging from tachypnea and dyspnea to ARDS and hypoxic respiratory failure, occur in up to 75% of patients with FES.¹ Central nervous system (CNS) complications, including headache, confusion, coma, seizures, and death caused by cerebral ischemia, occur in up to 86% of patients.^1,2 Petechiae may occur in 20%-60% of patients and are usually located on nondependent regions of the body such as the head, neck, and chest.

• FES is a rare condition that most commonly manifests with respiratory, neurological, and cutaneous findings.
• Patients with Duchenne’s Muscular Dystrophy are likely at increased risk for FES even with minor trauma; this makes wheelchair restraints and safe transfers fundamental.
• Patients with medical complexity and their caregivers are key members of the diagnostic team.

This article is the first in a series on maternal mortality.

“You’re in really bad shape, kid. I don’t know if you’re gonna live through the night. I’m going to do everything I can to save your life, but the truth is you might die.”

If Timoria McQueen Saba imagined the words she would hear in the moments after she gave birth, those likely weren’t among them. But then she started to bleed. The energy around her shifted; she felt the urgency and intensity in the room, and she could see it – reflected from the television monitor over her bed – in the faces of her care team. After her husband and newborn daughter were led from the room, she did, in fact, hear those words.

They were spoken by a surgeon called in after efforts to control the bleeding failed – emetic words that joined forces with her hemorrhaging and confusion and fear, and as she began to vomit, her eyelids felt heavy. She fought to keep them open, sensing that if she closed them they might never open again.

In 2018 alone, similar words perhaps were spoken to the 658 U.S. women who suffered maternal complications and whose eyes never did open again. This is the latest official maternal mortality data from the Centers for Disease Control and Prevention.

Ms. Saba’s eyes, however, remained open through her birth trauma and through the PTSD that followed. A fierce advocate for maternal health, she shares her story often, as she did during a panel discussion at the American College of Obstetricians and Gynecologists’ annual meeting in May 2019, in an effort to improve outcomes for other women and families.

But her story unfolded nearly a decade ago and those eyes still are seeing women die from childbirth. Despite her efforts and the efforts of countless other individuals and organizations working to improve maternal outcomes, the new CDC data show that the United States has the highest maternal mortality rate of any similarly wealthy industrialized nation.

“I cannot believe I’m still talking about this issue,” Ms. Saba told a standing-room-only crowd and her copanelists Neel T. Shah, MD, and Charles S. Johnson IV, whose wife, Kira, died in 2016 during surgery for bleeding complications following the birth of their second child. “If all the people who I’d written to had just listened maybe once and tried to propel my message forward back then, Charles would be in a much better situation and so would his children.”

Mr. Johnson said that for 10 hours he and other family members pleaded for help for Kira, a healthy, vibrant women he described as “sunshine personified.”

She showed signs of postpartum bleeding after delivering a healthy baby boy by C-section, but a “STAT CT” order went unheeded for hours before she was finally taken for surgery.

“You’re walking down this corridor, you get to this point, these double doors open, and you just can’t go any further – and that was the last time I saw my wife alive,” he said. “When they took Kira back into the operating room, there were three-and-a-half liters of blood in her abdomen, and her heart stopped immediately.

Kira Johnson died April 13, 2016.

“I’m not here to tell you what I think, I’m here to tell you what I know, and that’s that Kira deserved so much better, and that Kira’s not alone, and that women all over this country deserve so much better.”

The U.S. maternal mortality crisis

Dr. Shah, an ob.gyn. at Beth Israel Deaconess Medical Center and director of the Delivery Decisions Initiative at Harvard Medical School’s Ariadne Labs, both in Boston, where he has “been on this mission to improve safety in childbirth for years now,” echoed Ms. Saba’s dismay regarding the pace of progress.

“It’s not just about the present, it’s about the future, it’s about the pact that every generation ought to have with the next one to leave things at least as well as they found them. And when it comes to the health of our moms in this country, we are not doing that,” he said. “An American mom today is 50% more likely to die in childbirth than her own mother was, and 3-4 times more likely to die if she’s black than if she’s white.”

Indeed, the data released Jan. 30 by the CDC’s National Center for Health Statistics (NCHS) – the first on maternal mortality released by the agency since 2007 – show a U.S. maternal mortality rate of 17.4 maternal deaths per 100,000 live births in 2018.

The rate is higher than the 12.7 per 100,000 live births reported in 2007, but the increase is attributable mostly to changes in data collection and reporting methods. In 2003, “a consensus process recommended that all states add a standardized ‘checkbox’ to improve the identification of maternal deaths,” and implementation wasn’t complete until 2017 as “funding, technology, and state laws allowed,” meaning 2018 was the first year that data were reported in a standardized fashion across states, the CDC explained in a press release.

The data demonstrate ongoing wide racial/ethnic disparities: the maternal mortality rates for non-Hispanic black women, non-Hispanic white women, and Hispanic women were 37.1, 14.7, and 11.8 per 100,000 live births, consistent with earlier data.

Further, the rates for women aged 40 years and over were nearly eightfold higher than for those under age 25 years (81.9 vs. 10.6 per 100,000 live births).

CDC officials noted, however, that inconsistencies in reporting still leave some question about the accuracy of the data, stating in the release that “NCHS has identified instances where application of the checkbox information according to coding rules led to misclassification of maternal deaths.”

The agency is making changes in rules and reporting to ensure greater accuracy, but the numbers nevertheless reveal a startling truth: “The United States is the most dangerous place to deliver a baby in the industrialized world.”

 

Progress and challenges

Rebekah Gee, MD, an ob.gyn. who served for 4 years as Secretary of the Louisiana Department of Health before leaving the position in January, made that statement during another panel discussion at ACOG 2019 – The President’s Panel: Maternal Mortality: Progress Toward Prevention – which was moderated by Lisa M. Hollier, MD, now the immediate past president of ACOG.

Texas Children&#039;s Hospital

That’s not to say progress hasn’t been or can’t be made, Dr. Gee said.

In fact, quality improvement measures she facilitated in Louisiana led to a 25% reduction in infant mortality and a 10% reduction in neonatal intensive care unit admissions, demonstrating the potential for improvement with such initiatives, but addressing maternal issues is a greater challenge, she said.

“I think part of the sad truth is that we really focus on babies first, not moms ... and that needs to change,” Dr. Gee said.

Dr. Hollier focused much of her attention during her tenure as ACOG president on doing just that, particularly through an emphasis on heart disease, which is the leading cause of U.S. maternal deaths in pregnancy and the postpartum period.

In an interview, she shared her thoughts on the progress achieved and the work that remains.

ACOG was instrumental in the enactment of the Preventing Maternal Deaths Act of 2018, which appropriated funding for Enhancing Reviews and Surveillance to Eliminate Maternal Mortality (ERASE MM), a CDC initiative to support state-based maternal mortality review committees, said Dr. Hollier, professor of obstetrics and gynecology at Baylor College of Medicine, Houston.

“The really great news is that almost immediately after passage of the legislation, the CDC put out the notice of the funding opportunity, and they were able to provide 24 awards supporting 25 states,” she said.

ERASE MM will enhance state data collection and availability and enable a level of data sharing that “will really add strength and depth to reporting from the maternal mortality review committees, which really provides us with the best information we have to truly understand the causes, the contributing factors, and the strategies that can be put in place to prevent future maternal deaths.”

Further, the Alliance for Innovation on Maternal Health (AIM) program, a cooperative agreement with the Health Resources and Services Administration (HRSA) Maternal and Child Health Bureau to improve safety and outcomes through evidence-based patient safety bundles, was extended, and in May 2019, ACOG updated its guidance on managing cardiac contributors to maternal mortality, releasing its “Pregnancy and Heart Disease” Practice Bulletin, she said.

Dr. Hollier continues in her quest for improved maternal outcomes. She is slated to deliver a keynote address at the American College of Cardiology/World Congress of Cardiology conference March 28 in Chicago.

“I’m so excited ... to talk about the new guidelines that we’ve put out and to really talk about how cardiologists and ob.gyns. can work together to improve women’s health outcomes,” she said, adding that she already is seeing a strengthening of such partnerships.

A number of academic institutions are developing “pregnancy heart teams” to identify and care for women who have or develop heart disease during pregnancy.

“This type of collaboration ... is going to be essential to address mortality from cardiovascular causes and from cardiomyopathy, which accounts for about 25% of all maternal mortality,” she said. “The next area where we really need some buy-in is from our emergency physicians.”

Enhanced collaboration with emergency physicians and other specialties present opportunities to better identify and address pregnancy-related complications and sequelae, she said.

“Women are dying because they’re not being diagnosed,” she added. “We have to raise that level of awareness – it’s just absolutely critical.”
 

Identifying and addressing drivers of the crisis

Dr. Gee further emphasized the importance of addressing maternal health, noting that for every woman who dies from maternal causes, 100 experience maternal morbidity.

“It’s startling and it’s scary,” she said. “We are looking at this not just as a problem of outcomes, but a problem of racial inequity and racial bias and implicit bias.”

When she and her team assessed maternal mortality in Louisiana, they looked specifically at whether each death could have been prevented if, for example, blood was given sooner, cardiomyopathy was recognized sooner, or hypertension was treated on time.

“When we looked at these numbers ... when we looked at white women, 9% of the time we could have done better with our medical care; with black women, 59% of the time we could have saved her life with better care,” said Dr Gee, who is a gratis assistant professor of obstetrics and gynecology at Louisiana State University, New Orleans. “And if that doesn’t convince you that racial bias is an incredibly important thing to address – that we need to have a conversation about and address at a national level – I don’t know what would.”

In fact, numerous health, societal, socioeconomic, and other factors – some known, some yet to be identified, and many inter-related – are among the drivers of the U.S. maternal mortality crisis. In the coming months, an Ob.Gyn. News team will examine several of these drivers in depth. We’ll look specifically at the role of racism and bias, and at urban-rural disparities in access and outcomes – especially for women of color and indigenous women. We’ll address the scope and impact of each, successes and failures in addressing the problems, and ongoing initiatives.

Follow us for insights from experts, researchers, practicing physicians, and patients and families affected by the maternal mortality crisis, and stay with us through coverage of ACOG 2020 for perspective on what, specifically, ob.gyns. can do about it.

Mr. Johnson proposed a starting point:

“Here’s the good news – you guys ready for this? We can fix this,” he said, adding that the solution starts with “speaking Timoria’s name ... speaking the name of Kira Dixon Johnson ... speaking the names of these women and then asking the people that are around you, ‘What are we prepared to do to make sure that this doesn’t happen to other women.’ ”

sworcester@mdedge.com

This article is the first in a series on maternal mortality.

“You’re in really bad shape, kid. I don’t know if you’re gonna live through the night. I’m going to do everything I can to save your life, but the truth is you might die.”

If Timoria McQueen Saba imagined the words she would hear in the moments after she gave birth, those likely weren’t among them. But then she started to bleed. The energy around her shifted; she felt the urgency and intensity in the room, and she could see it – reflected from the television monitor over her bed – in the faces of her care team. After her husband and newborn daughter were led from the room, she did, in fact, hear those words.

They were spoken by a surgeon called in after efforts to control the bleeding failed – emetic words that joined forces with her hemorrhaging and confusion and fear, and as she began to vomit, her eyelids felt heavy. She fought to keep them open, sensing that if she closed them they might never open again.

In 2018 alone, similar words perhaps were spoken to the 658 U.S. women who suffered maternal complications and whose eyes never did open again. This is the latest official maternal mortality data from the Centers for Disease Control and Prevention.

Ms. Saba’s eyes, however, remained open through her birth trauma and through the PTSD that followed. A fierce advocate for maternal health, she shares her story often, as she did during a panel discussion at the American College of Obstetricians and Gynecologists’ annual meeting in May 2019, in an effort to improve outcomes for other women and families.

But her story unfolded nearly a decade ago and those eyes still are seeing women die from childbirth. Despite her efforts and the efforts of countless other individuals and organizations working to improve maternal outcomes, the new CDC data show that the United States has the highest maternal mortality rate of any similarly wealthy industrialized nation.

“I cannot believe I’m still talking about this issue,” Ms. Saba told a standing-room-only crowd and her copanelists Neel T. Shah, MD, and Charles S. Johnson IV, whose wife, Kira, died in 2016 during surgery for bleeding complications following the birth of their second child. “If all the people who I’d written to had just listened maybe once and tried to propel my message forward back then, Charles would be in a much better situation and so would his children.”

Mr. Johnson said that for 10 hours he and other family members pleaded for help for Kira, a healthy, vibrant women he described as “sunshine personified.”

She showed signs of postpartum bleeding after delivering a healthy baby boy by C-section, but a “STAT CT” order went unheeded for hours before she was finally taken for surgery.

“You’re walking down this corridor, you get to this point, these double doors open, and you just can’t go any further – and that was the last time I saw my wife alive,” he said. “When they took Kira back into the operating room, there were three-and-a-half liters of blood in her abdomen, and her heart stopped immediately.

Kira Johnson died April 13, 2016.

“I’m not here to tell you what I think, I’m here to tell you what I know, and that’s that Kira deserved so much better, and that Kira’s not alone, and that women all over this country deserve so much better.”

The U.S. maternal mortality crisis

Dr. Shah, an ob.gyn. at Beth Israel Deaconess Medical Center and director of the Delivery Decisions Initiative at Harvard Medical School’s Ariadne Labs, both in Boston, where he has “been on this mission to improve safety in childbirth for years now,” echoed Ms. Saba’s dismay regarding the pace of progress.

“It’s not just about the present, it’s about the future, it’s about the pact that every generation ought to have with the next one to leave things at least as well as they found them. And when it comes to the health of our moms in this country, we are not doing that,” he said. “An American mom today is 50% more likely to die in childbirth than her own mother was, and 3-4 times more likely to die if she’s black than if she’s white.”

Indeed, the data released Jan. 30 by the CDC’s National Center for Health Statistics (NCHS) – the first on maternal mortality released by the agency since 2007 – show a U.S. maternal mortality rate of 17.4 maternal deaths per 100,000 live births in 2018.

The rate is higher than the 12.7 per 100,000 live births reported in 2007, but the increase is attributable mostly to changes in data collection and reporting methods. In 2003, “a consensus process recommended that all states add a standardized ‘checkbox’ to improve the identification of maternal deaths,” and implementation wasn’t complete until 2017 as “funding, technology, and state laws allowed,” meaning 2018 was the first year that data were reported in a standardized fashion across states, the CDC explained in a press release.

The data demonstrate ongoing wide racial/ethnic disparities: the maternal mortality rates for non-Hispanic black women, non-Hispanic white women, and Hispanic women were 37.1, 14.7, and 11.8 per 100,000 live births, consistent with earlier data.

Further, the rates for women aged 40 years and over were nearly eightfold higher than for those under age 25 years (81.9 vs. 10.6 per 100,000 live births).

CDC officials noted, however, that inconsistencies in reporting still leave some question about the accuracy of the data, stating in the release that “NCHS has identified instances where application of the checkbox information according to coding rules led to misclassification of maternal deaths.”

The agency is making changes in rules and reporting to ensure greater accuracy, but the numbers nevertheless reveal a startling truth: “The United States is the most dangerous place to deliver a baby in the industrialized world.”

 

Progress and challenges

Rebekah Gee, MD, an ob.gyn. who served for 4 years as Secretary of the Louisiana Department of Health before leaving the position in January, made that statement during another panel discussion at ACOG 2019 – The President’s Panel: Maternal Mortality: Progress Toward Prevention – which was moderated by Lisa M. Hollier, MD, now the immediate past president of ACOG.

Texas Children&#039;s Hospital

That’s not to say progress hasn’t been or can’t be made, Dr. Gee said.

In fact, quality improvement measures she facilitated in Louisiana led to a 25% reduction in infant mortality and a 10% reduction in neonatal intensive care unit admissions, demonstrating the potential for improvement with such initiatives, but addressing maternal issues is a greater challenge, she said.

“I think part of the sad truth is that we really focus on babies first, not moms ... and that needs to change,” Dr. Gee said.

Dr. Hollier focused much of her attention during her tenure as ACOG president on doing just that, particularly through an emphasis on heart disease, which is the leading cause of U.S. maternal deaths in pregnancy and the postpartum period.

In an interview, she shared her thoughts on the progress achieved and the work that remains.

ACOG was instrumental in the enactment of the Preventing Maternal Deaths Act of 2018, which appropriated funding for Enhancing Reviews and Surveillance to Eliminate Maternal Mortality (ERASE MM), a CDC initiative to support state-based maternal mortality review committees, said Dr. Hollier, professor of obstetrics and gynecology at Baylor College of Medicine, Houston.

“The really great news is that almost immediately after passage of the legislation, the CDC put out the notice of the funding opportunity, and they were able to provide 24 awards supporting 25 states,” she said.

ERASE MM will enhance state data collection and availability and enable a level of data sharing that “will really add strength and depth to reporting from the maternal mortality review committees, which really provides us with the best information we have to truly understand the causes, the contributing factors, and the strategies that can be put in place to prevent future maternal deaths.”

Further, the Alliance for Innovation on Maternal Health (AIM) program, a cooperative agreement with the Health Resources and Services Administration (HRSA) Maternal and Child Health Bureau to improve safety and outcomes through evidence-based patient safety bundles, was extended, and in May 2019, ACOG updated its guidance on managing cardiac contributors to maternal mortality, releasing its “Pregnancy and Heart Disease” Practice Bulletin, she said.

Dr. Hollier continues in her quest for improved maternal outcomes. She is slated to deliver a keynote address at the American College of Cardiology/World Congress of Cardiology conference March 28 in Chicago.

“I’m so excited ... to talk about the new guidelines that we’ve put out and to really talk about how cardiologists and ob.gyns. can work together to improve women’s health outcomes,” she said, adding that she already is seeing a strengthening of such partnerships.

A number of academic institutions are developing “pregnancy heart teams” to identify and care for women who have or develop heart disease during pregnancy.

“This type of collaboration ... is going to be essential to address mortality from cardiovascular causes and from cardiomyopathy, which accounts for about 25% of all maternal mortality,” she said. “The next area where we really need some buy-in is from our emergency physicians.”

Enhanced collaboration with emergency physicians and other specialties present opportunities to better identify and address pregnancy-related complications and sequelae, she said.

“Women are dying because they’re not being diagnosed,” she added. “We have to raise that level of awareness – it’s just absolutely critical.”
 

Identifying and addressing drivers of the crisis

Dr. Gee further emphasized the importance of addressing maternal health, noting that for every woman who dies from maternal causes, 100 experience maternal morbidity.

“It’s startling and it’s scary,” she said. “We are looking at this not just as a problem of outcomes, but a problem of racial inequity and racial bias and implicit bias.”

When she and her team assessed maternal mortality in Louisiana, they looked specifically at whether each death could have been prevented if, for example, blood was given sooner, cardiomyopathy was recognized sooner, or hypertension was treated on time.

“When we looked at these numbers ... when we looked at white women, 9% of the time we could have done better with our medical care; with black women, 59% of the time we could have saved her life with better care,” said Dr Gee, who is a gratis assistant professor of obstetrics and gynecology at Louisiana State University, New Orleans. “And if that doesn’t convince you that racial bias is an incredibly important thing to address – that we need to have a conversation about and address at a national level – I don’t know what would.”

In fact, numerous health, societal, socioeconomic, and other factors – some known, some yet to be identified, and many inter-related – are among the drivers of the U.S. maternal mortality crisis. In the coming months, an Ob.Gyn. News team will examine several of these drivers in depth. We’ll look specifically at the role of racism and bias, and at urban-rural disparities in access and outcomes – especially for women of color and indigenous women. We’ll address the scope and impact of each, successes and failures in addressing the problems, and ongoing initiatives.

Follow us for insights from experts, researchers, practicing physicians, and patients and families affected by the maternal mortality crisis, and stay with us through coverage of ACOG 2020 for perspective on what, specifically, ob.gyns. can do about it.

Mr. Johnson proposed a starting point:

“Here’s the good news – you guys ready for this? We can fix this,” he said, adding that the solution starts with “speaking Timoria’s name ... speaking the name of Kira Dixon Johnson ... speaking the names of these women and then asking the people that are around you, ‘What are we prepared to do to make sure that this doesn’t happen to other women.’ ”

sworcester@mdedge.com

This article is the first in a series on maternal mortality.

“You’re in really bad shape, kid. I don’t know if you’re gonna live through the night. I’m going to do everything I can to save your life, but the truth is you might die.”

If Timoria McQueen Saba imagined the words she would hear in the moments after she gave birth, those likely weren’t among them. But then she started to bleed. The energy around her shifted; she felt the urgency and intensity in the room, and she could see it – reflected from the television monitor over her bed – in the faces of her care team. After her husband and newborn daughter were led from the room, she did, in fact, hear those words.

They were spoken by a surgeon called in after efforts to control the bleeding failed – emetic words that joined forces with her hemorrhaging and confusion and fear, and as she began to vomit, her eyelids felt heavy. She fought to keep them open, sensing that if she closed them they might never open again.

In 2018 alone, similar words perhaps were spoken to the 658 U.S. women who suffered maternal complications and whose eyes never did open again. This is the latest official maternal mortality data from the Centers for Disease Control and Prevention.

Ms. Saba’s eyes, however, remained open through her birth trauma and through the PTSD that followed. A fierce advocate for maternal health, she shares her story often, as she did during a panel discussion at the American College of Obstetricians and Gynecologists’ annual meeting in May 2019, in an effort to improve outcomes for other women and families.

But her story unfolded nearly a decade ago and those eyes still are seeing women die from childbirth. Despite her efforts and the efforts of countless other individuals and organizations working to improve maternal outcomes, the new CDC data show that the United States has the highest maternal mortality rate of any similarly wealthy industrialized nation.

“I cannot believe I’m still talking about this issue,” Ms. Saba told a standing-room-only crowd and her copanelists Neel T. Shah, MD, and Charles S. Johnson IV, whose wife, Kira, died in 2016 during surgery for bleeding complications following the birth of their second child. “If all the people who I’d written to had just listened maybe once and tried to propel my message forward back then, Charles would be in a much better situation and so would his children.”

Mr. Johnson said that for 10 hours he and other family members pleaded for help for Kira, a healthy, vibrant women he described as “sunshine personified.”

She showed signs of postpartum bleeding after delivering a healthy baby boy by C-section, but a “STAT CT” order went unheeded for hours before she was finally taken for surgery.

“You’re walking down this corridor, you get to this point, these double doors open, and you just can’t go any further – and that was the last time I saw my wife alive,” he said. “When they took Kira back into the operating room, there were three-and-a-half liters of blood in her abdomen, and her heart stopped immediately.

Kira Johnson died April 13, 2016.

“I’m not here to tell you what I think, I’m here to tell you what I know, and that’s that Kira deserved so much better, and that Kira’s not alone, and that women all over this country deserve so much better.”

The U.S. maternal mortality crisis

Dr. Shah, an ob.gyn. at Beth Israel Deaconess Medical Center and director of the Delivery Decisions Initiative at Harvard Medical School’s Ariadne Labs, both in Boston, where he has “been on this mission to improve safety in childbirth for years now,” echoed Ms. Saba’s dismay regarding the pace of progress.

“It’s not just about the present, it’s about the future, it’s about the pact that every generation ought to have with the next one to leave things at least as well as they found them. And when it comes to the health of our moms in this country, we are not doing that,” he said. “An American mom today is 50% more likely to die in childbirth than her own mother was, and 3-4 times more likely to die if she’s black than if she’s white.”

Indeed, the data released Jan. 30 by the CDC’s National Center for Health Statistics (NCHS) – the first on maternal mortality released by the agency since 2007 – show a U.S. maternal mortality rate of 17.4 maternal deaths per 100,000 live births in 2018.

The rate is higher than the 12.7 per 100,000 live births reported in 2007, but the increase is attributable mostly to changes in data collection and reporting methods. In 2003, “a consensus process recommended that all states add a standardized ‘checkbox’ to improve the identification of maternal deaths,” and implementation wasn’t complete until 2017 as “funding, technology, and state laws allowed,” meaning 2018 was the first year that data were reported in a standardized fashion across states, the CDC explained in a press release.

The data demonstrate ongoing wide racial/ethnic disparities: the maternal mortality rates for non-Hispanic black women, non-Hispanic white women, and Hispanic women were 37.1, 14.7, and 11.8 per 100,000 live births, consistent with earlier data.

Further, the rates for women aged 40 years and over were nearly eightfold higher than for those under age 25 years (81.9 vs. 10.6 per 100,000 live births).

CDC officials noted, however, that inconsistencies in reporting still leave some question about the accuracy of the data, stating in the release that “NCHS has identified instances where application of the checkbox information according to coding rules led to misclassification of maternal deaths.”

The agency is making changes in rules and reporting to ensure greater accuracy, but the numbers nevertheless reveal a startling truth: “The United States is the most dangerous place to deliver a baby in the industrialized world.”

 

Progress and challenges

Rebekah Gee, MD, an ob.gyn. who served for 4 years as Secretary of the Louisiana Department of Health before leaving the position in January, made that statement during another panel discussion at ACOG 2019 – The President’s Panel: Maternal Mortality: Progress Toward Prevention – which was moderated by Lisa M. Hollier, MD, now the immediate past president of ACOG.

Texas Children&#039;s Hospital

That’s not to say progress hasn’t been or can’t be made, Dr. Gee said.

In fact, quality improvement measures she facilitated in Louisiana led to a 25% reduction in infant mortality and a 10% reduction in neonatal intensive care unit admissions, demonstrating the potential for improvement with such initiatives, but addressing maternal issues is a greater challenge, she said.

“I think part of the sad truth is that we really focus on babies first, not moms ... and that needs to change,” Dr. Gee said.

Dr. Hollier focused much of her attention during her tenure as ACOG president on doing just that, particularly through an emphasis on heart disease, which is the leading cause of U.S. maternal deaths in pregnancy and the postpartum period.

In an interview, she shared her thoughts on the progress achieved and the work that remains.

ACOG was instrumental in the enactment of the Preventing Maternal Deaths Act of 2018, which appropriated funding for Enhancing Reviews and Surveillance to Eliminate Maternal Mortality (ERASE MM), a CDC initiative to support state-based maternal mortality review committees, said Dr. Hollier, professor of obstetrics and gynecology at Baylor College of Medicine, Houston.

“The really great news is that almost immediately after passage of the legislation, the CDC put out the notice of the funding opportunity, and they were able to provide 24 awards supporting 25 states,” she said.

ERASE MM will enhance state data collection and availability and enable a level of data sharing that “will really add strength and depth to reporting from the maternal mortality review committees, which really provides us with the best information we have to truly understand the causes, the contributing factors, and the strategies that can be put in place to prevent future maternal deaths.”

Further, the Alliance for Innovation on Maternal Health (AIM) program, a cooperative agreement with the Health Resources and Services Administration (HRSA) Maternal and Child Health Bureau to improve safety and outcomes through evidence-based patient safety bundles, was extended, and in May 2019, ACOG updated its guidance on managing cardiac contributors to maternal mortality, releasing its “Pregnancy and Heart Disease” Practice Bulletin, she said.

Dr. Hollier continues in her quest for improved maternal outcomes. She is slated to deliver a keynote address at the American College of Cardiology/World Congress of Cardiology conference March 28 in Chicago.

“I’m so excited ... to talk about the new guidelines that we’ve put out and to really talk about how cardiologists and ob.gyns. can work together to improve women’s health outcomes,” she said, adding that she already is seeing a strengthening of such partnerships.

A number of academic institutions are developing “pregnancy heart teams” to identify and care for women who have or develop heart disease during pregnancy.

“This type of collaboration ... is going to be essential to address mortality from cardiovascular causes and from cardiomyopathy, which accounts for about 25% of all maternal mortality,” she said. “The next area where we really need some buy-in is from our emergency physicians.”

Enhanced collaboration with emergency physicians and other specialties present opportunities to better identify and address pregnancy-related complications and sequelae, she said.

“Women are dying because they’re not being diagnosed,” she added. “We have to raise that level of awareness – it’s just absolutely critical.”
 

Identifying and addressing drivers of the crisis

Dr. Gee further emphasized the importance of addressing maternal health, noting that for every woman who dies from maternal causes, 100 experience maternal morbidity.

“It’s startling and it’s scary,” she said. “We are looking at this not just as a problem of outcomes, but a problem of racial inequity and racial bias and implicit bias.”

When she and her team assessed maternal mortality in Louisiana, they looked specifically at whether each death could have been prevented if, for example, blood was given sooner, cardiomyopathy was recognized sooner, or hypertension was treated on time.

“When we looked at these numbers ... when we looked at white women, 9% of the time we could have done better with our medical care; with black women, 59% of the time we could have saved her life with better care,” said Dr Gee, who is a gratis assistant professor of obstetrics and gynecology at Louisiana State University, New Orleans. “And if that doesn’t convince you that racial bias is an incredibly important thing to address – that we need to have a conversation about and address at a national level – I don’t know what would.”

In fact, numerous health, societal, socioeconomic, and other factors – some known, some yet to be identified, and many inter-related – are among the drivers of the U.S. maternal mortality crisis. In the coming months, an Ob.Gyn. News team will examine several of these drivers in depth. We’ll look specifically at the role of racism and bias, and at urban-rural disparities in access and outcomes – especially for women of color and indigenous women. We’ll address the scope and impact of each, successes and failures in addressing the problems, and ongoing initiatives.

Follow us for insights from experts, researchers, practicing physicians, and patients and families affected by the maternal mortality crisis, and stay with us through coverage of ACOG 2020 for perspective on what, specifically, ob.gyns. can do about it.

Mr. Johnson proposed a starting point:

“Here’s the good news – you guys ready for this? We can fix this,” he said, adding that the solution starts with “speaking Timoria’s name ... speaking the name of Kira Dixon Johnson ... speaking the names of these women and then asking the people that are around you, ‘What are we prepared to do to make sure that this doesn’t happen to other women.’ ”

sworcester@mdedge.com