Tara Lagu, MD, MPH

Increasing use of emergency departments (EDs) throughout the United States has become a focus of national healthcare policy and reform efforts. ED growth continues to outpace population growth, with the Institute of Medicine describing our ED systems as fragmented, overburdened, and at the breaking point.[1] Associations between ED crowding and patient dissatisfaction, delays in treatment, medical errors, and patient mortality speak to the urgency of systems improvements.[2] One major factor contributing to ED volumes is the growing number of hospital admissions that begin in EDs. From 1993 to 2006, the proportion of hospitalizations originating in EDs increased from 33.5% to 43.8%, with more than 17 million hospital admissions originating in EDs annually.[3, 4] Despite these challenges, discussions about alternative approaches to hospital admission remain at the periphery of healthcare policy conversations.

Direct admission to the hospital, defined as hospitalization without first receiving care in the hospital's ED, is an alternative approach to hospital admission, and may be a vehicle to both observation and inpatient hospital stays. Direct admissions account for 25% of all nonelective pediatric hospitalizations and 15% of nonelective adult hospitalizations in the United States.[5, 6] This admission approach was considerably more common in the past, facilitated by primary care providers (PCPs) or specialists who provided both outpatient and hospital‐based care for their patients.[4] However, as the number of hospitalists in the United States has grown over the last 30 years, the number of direct admissions has decreased concurrently. In fact, from 2003 to 2009, the number of direct admissions from clinics and physicians' offices decreased by a total of 1.6 million.[4] Although this decline is undoubtedly multifactorial, hospitalists may have contributed, both deliberately and inadvertently, to the shifting epidemiology of hospital admissions. Although many factors influence the source of hospital admissions and admission processes, direct admission has 2 important prerequisites: patients require timely access to outpatient providers for acute care, and hospitals, in partnership with outpatient‐based clinics and practices, require systems to safely and efficiently facilitate admissions without ED involvement. However, we know little about hospital admission systems, developed in the era of hospital medicine, to facilitate admissions independent of the ED.

Direct admission offers a number of potential benefits for both patients and healthcare delivery systems including reductions in the number of sites and providers of care, improved communication and coordination between outpatient and hospital‐based healthcare providers, greater patient and referring physician satisfaction, and reduced ED volumes and subsequent costs.[7] However, there are also risks and potential harms associated with direct admission, including potential delays in initial evaluation and management, inconsistent admission processes, and difficulties determining direct admission appropriateness, all of which could adversely impact patient safety and quality of care.[7, 8, 9] One study of adults with sepsis found that direct admission was associated with increased mortality compared to ED admission, which the authors speculated to be related to less timely care.[9] Similarly, a study of unscheduled adult hospitalizations found that patients admitted directly had higher mortality for time‐sensitive conditions such as acute myocardial infarction and sepsis than patients admitted through EDs, differences not observed among adults admitted with pneumonia, asthma, cellulitis, and several other common, yet frequently less emergent, reasons for hospitalization.[8] Among children with pneumonia, the most common reason for pediatric hospitalization, direct admission has been associated with significantly lower costs than admissions originating in the ED, with no significant differences in rates of transfer to the intensive care unit or hospital readmission.[10]

There is significant variation across both diagnoses and hospitals in rates of direct admission, raising questions about the contextual factors unique to hospital medicine programs that perform a substantial proportion of direct admissions.[5] This variation also highlights opportunities to identify the populations, conditions, and systems that facilitate safe and effective direct admissions. Certainly, direct admission is unlikely to be appropriate for all populations or conditions. Patients requiring emergent care or rapid diagnostic imaging are likely to receive more timely care in the ED; sepsis, acute myocardial infarction, and trauma are but a few examples of conditions for which rapid ED care decreases morbidity and mortality. Similarly, patients for whom the need for hospitalization is uncertainfor example, dehydration, asthmamay be more appropriate for initial ED management followed by re‐evaluation to inform the need for hospitalization. Finally, patients for whom the admitting diagnosis is uncertain and who require consultation for several subspecialists may be more efficiently evaluated in EDs. In our national survey of pediatric direct admission guidelines, less than one‐third of hospitals reported having formal criteria to assess the appropriateness of direct admissions, and respondents' perspectives regarding populations and diagnoses appropriate for this admission approach varied considerably.[7] These results point to the need for further research and quality‐improvement initiatives to inform the development of direct admission guidelines and protocols.

During the last decade, hospitals' discharge processes have been the focus of tremendous research, policy, and quality improvement efforts. The phrase transition of care is now widely understood to describe the changes in patient care that begin with discharge planning and conclude when patients' have established care at home or another healthcare facility. Transitions of care have been a focus of the Journal of Hospital Medicine since its inception, including publication of the Transitions of Care Consensus Policy Statement in 2009, as well as numerous other studies highlighting both risks associated with transitions of care as well as methods to address these.[11, 12, 13, 14, 15, 16] Similar to hospital discharge, hospital admission is an inherent feature of every hospitalization, and admission and discharge processes share many commonalities. Both involve transitions in sites of care, and handoffs between healthcare providers. Most involve changes in medical therapies, including both the addition of new medications and changes to existing treatments. Moreover, both are associated with significant stress to patients and their families. As a result, hospital admissions expose patients to many of same risks that have been the focus of hospital discharge reform: unstructured patient handoffs, poor communication between healthcare providers, and costly, inefficient care. The Society of Hospital Medicine has been a leader in articulating the importance of patient‐centered, clinically relevant medication reconciliation across the healthcare continuum.[17] However, with the exception of this important work, research and policy focused on understanding and improving transitions of care into the hospital have received disproportionately little attention.

To facilitate research and quality improvement efforts focused on hospital admission, we suggest that the transitions of care framework, typically discussed in the context of hospital discharge, be expanded to reflect the different origins of hospitalizations and multiple transitions that can be experienced by patients as they enter the hospital. A broadening of the transitions of care framework to incorporate hospital admissions brings numerous questions previously addressed in hospital‐to‐home transitions to the forefront. How do transitions into the hospital impact patients and healthcare systems? When is direct admission safe and effective, and how does this vary across conditions and hospital settings? What protocols and tools might optimize the associated transitions and reduce the risks of error and harm? There are numerous stakeholders who will undoubtedly bring diverse perspectives to these questionspatients and their families, hospital‐based healthcare providers, PCPs and specialists, ED physicians, and payors.

Increasing ED volumes, long wait times, and rising ED costs speak to the importance of better understanding hospital admission alternatives and the associated risks and benefits. Encouraging more direct admissions may be a solution, but evidence to guide best practices must precede this. The growing presence of round‐the‐clock pediatric and adult hospitalists across the country creates unique opportunities to transform hospital admission systems for the vast number of patients who do not require emergent care. The Affordable Care Act's expansion of insurance coverage and incentivized coordinated care within patient‐centered medical homes creates a unique opportunity for this broadened view of transitions of care. This suggests that the time is ripe for pursuing strategies that will both improve patients' transitions from outpatient to inpatient care and reduce stress on our overburdened emergency departments.

Disclosure: Dr. Lagu was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. She has received consulting fees from the Institute for Healthcare Improvement, under contract to the Centers for Medicare and Medicaid Services (CMS), for her work on a project to help health systems achieve disability competence, and from the Island Peer Review Organization, under contract to CMS, for her work on development of episodes of care for CMS payment purposes (both unrelated to the current work). Dr. Leyenaar was supported by grant number K08HS024133 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. The authors report no conflicts of interest.

Increasing use of emergency departments (EDs) throughout the United States has become a focus of national healthcare policy and reform efforts. ED growth continues to outpace population growth, with the Institute of Medicine describing our ED systems as fragmented, overburdened, and at the breaking point.[1] Associations between ED crowding and patient dissatisfaction, delays in treatment, medical errors, and patient mortality speak to the urgency of systems improvements.[2] One major factor contributing to ED volumes is the growing number of hospital admissions that begin in EDs. From 1993 to 2006, the proportion of hospitalizations originating in EDs increased from 33.5% to 43.8%, with more than 17 million hospital admissions originating in EDs annually.[3, 4] Despite these challenges, discussions about alternative approaches to hospital admission remain at the periphery of healthcare policy conversations.

Direct admission to the hospital, defined as hospitalization without first receiving care in the hospital's ED, is an alternative approach to hospital admission, and may be a vehicle to both observation and inpatient hospital stays. Direct admissions account for 25% of all nonelective pediatric hospitalizations and 15% of nonelective adult hospitalizations in the United States.[5, 6] This admission approach was considerably more common in the past, facilitated by primary care providers (PCPs) or specialists who provided both outpatient and hospital‐based care for their patients.[4] However, as the number of hospitalists in the United States has grown over the last 30 years, the number of direct admissions has decreased concurrently. In fact, from 2003 to 2009, the number of direct admissions from clinics and physicians' offices decreased by a total of 1.6 million.[4] Although this decline is undoubtedly multifactorial, hospitalists may have contributed, both deliberately and inadvertently, to the shifting epidemiology of hospital admissions. Although many factors influence the source of hospital admissions and admission processes, direct admission has 2 important prerequisites: patients require timely access to outpatient providers for acute care, and hospitals, in partnership with outpatient‐based clinics and practices, require systems to safely and efficiently facilitate admissions without ED involvement. However, we know little about hospital admission systems, developed in the era of hospital medicine, to facilitate admissions independent of the ED.

Direct admission offers a number of potential benefits for both patients and healthcare delivery systems including reductions in the number of sites and providers of care, improved communication and coordination between outpatient and hospital‐based healthcare providers, greater patient and referring physician satisfaction, and reduced ED volumes and subsequent costs.[7] However, there are also risks and potential harms associated with direct admission, including potential delays in initial evaluation and management, inconsistent admission processes, and difficulties determining direct admission appropriateness, all of which could adversely impact patient safety and quality of care.[7, 8, 9] One study of adults with sepsis found that direct admission was associated with increased mortality compared to ED admission, which the authors speculated to be related to less timely care.[9] Similarly, a study of unscheduled adult hospitalizations found that patients admitted directly had higher mortality for time‐sensitive conditions such as acute myocardial infarction and sepsis than patients admitted through EDs, differences not observed among adults admitted with pneumonia, asthma, cellulitis, and several other common, yet frequently less emergent, reasons for hospitalization.[8] Among children with pneumonia, the most common reason for pediatric hospitalization, direct admission has been associated with significantly lower costs than admissions originating in the ED, with no significant differences in rates of transfer to the intensive care unit or hospital readmission.[10]

There is significant variation across both diagnoses and hospitals in rates of direct admission, raising questions about the contextual factors unique to hospital medicine programs that perform a substantial proportion of direct admissions.[5] This variation also highlights opportunities to identify the populations, conditions, and systems that facilitate safe and effective direct admissions. Certainly, direct admission is unlikely to be appropriate for all populations or conditions. Patients requiring emergent care or rapid diagnostic imaging are likely to receive more timely care in the ED; sepsis, acute myocardial infarction, and trauma are but a few examples of conditions for which rapid ED care decreases morbidity and mortality. Similarly, patients for whom the need for hospitalization is uncertainfor example, dehydration, asthmamay be more appropriate for initial ED management followed by re‐evaluation to inform the need for hospitalization. Finally, patients for whom the admitting diagnosis is uncertain and who require consultation for several subspecialists may be more efficiently evaluated in EDs. In our national survey of pediatric direct admission guidelines, less than one‐third of hospitals reported having formal criteria to assess the appropriateness of direct admissions, and respondents' perspectives regarding populations and diagnoses appropriate for this admission approach varied considerably.[7] These results point to the need for further research and quality‐improvement initiatives to inform the development of direct admission guidelines and protocols.

During the last decade, hospitals' discharge processes have been the focus of tremendous research, policy, and quality improvement efforts. The phrase transition of care is now widely understood to describe the changes in patient care that begin with discharge planning and conclude when patients' have established care at home or another healthcare facility. Transitions of care have been a focus of the Journal of Hospital Medicine since its inception, including publication of the Transitions of Care Consensus Policy Statement in 2009, as well as numerous other studies highlighting both risks associated with transitions of care as well as methods to address these.[11, 12, 13, 14, 15, 16] Similar to hospital discharge, hospital admission is an inherent feature of every hospitalization, and admission and discharge processes share many commonalities. Both involve transitions in sites of care, and handoffs between healthcare providers. Most involve changes in medical therapies, including both the addition of new medications and changes to existing treatments. Moreover, both are associated with significant stress to patients and their families. As a result, hospital admissions expose patients to many of same risks that have been the focus of hospital discharge reform: unstructured patient handoffs, poor communication between healthcare providers, and costly, inefficient care. The Society of Hospital Medicine has been a leader in articulating the importance of patient‐centered, clinically relevant medication reconciliation across the healthcare continuum.[17] However, with the exception of this important work, research and policy focused on understanding and improving transitions of care into the hospital have received disproportionately little attention.

To facilitate research and quality improvement efforts focused on hospital admission, we suggest that the transitions of care framework, typically discussed in the context of hospital discharge, be expanded to reflect the different origins of hospitalizations and multiple transitions that can be experienced by patients as they enter the hospital. A broadening of the transitions of care framework to incorporate hospital admissions brings numerous questions previously addressed in hospital‐to‐home transitions to the forefront. How do transitions into the hospital impact patients and healthcare systems? When is direct admission safe and effective, and how does this vary across conditions and hospital settings? What protocols and tools might optimize the associated transitions and reduce the risks of error and harm? There are numerous stakeholders who will undoubtedly bring diverse perspectives to these questionspatients and their families, hospital‐based healthcare providers, PCPs and specialists, ED physicians, and payors.

Increasing ED volumes, long wait times, and rising ED costs speak to the importance of better understanding hospital admission alternatives and the associated risks and benefits. Encouraging more direct admissions may be a solution, but evidence to guide best practices must precede this. The growing presence of round‐the‐clock pediatric and adult hospitalists across the country creates unique opportunities to transform hospital admission systems for the vast number of patients who do not require emergent care. The Affordable Care Act's expansion of insurance coverage and incentivized coordinated care within patient‐centered medical homes creates a unique opportunity for this broadened view of transitions of care. This suggests that the time is ripe for pursuing strategies that will both improve patients' transitions from outpatient to inpatient care and reduce stress on our overburdened emergency departments.

Disclosure: Dr. Lagu was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. She has received consulting fees from the Institute for Healthcare Improvement, under contract to the Centers for Medicare and Medicaid Services (CMS), for her work on a project to help health systems achieve disability competence, and from the Island Peer Review Organization, under contract to CMS, for her work on development of episodes of care for CMS payment purposes (both unrelated to the current work). Dr. Leyenaar was supported by grant number K08HS024133 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. The authors report no conflicts of interest.

Increasing use of emergency departments (EDs) throughout the United States has become a focus of national healthcare policy and reform efforts. ED growth continues to outpace population growth, with the Institute of Medicine describing our ED systems as fragmented, overburdened, and at the breaking point.[1] Associations between ED crowding and patient dissatisfaction, delays in treatment, medical errors, and patient mortality speak to the urgency of systems improvements.[2] One major factor contributing to ED volumes is the growing number of hospital admissions that begin in EDs. From 1993 to 2006, the proportion of hospitalizations originating in EDs increased from 33.5% to 43.8%, with more than 17 million hospital admissions originating in EDs annually.[3, 4] Despite these challenges, discussions about alternative approaches to hospital admission remain at the periphery of healthcare policy conversations.

Direct admission to the hospital, defined as hospitalization without first receiving care in the hospital's ED, is an alternative approach to hospital admission, and may be a vehicle to both observation and inpatient hospital stays. Direct admissions account for 25% of all nonelective pediatric hospitalizations and 15% of nonelective adult hospitalizations in the United States.[5, 6] This admission approach was considerably more common in the past, facilitated by primary care providers (PCPs) or specialists who provided both outpatient and hospital‐based care for their patients.[4] However, as the number of hospitalists in the United States has grown over the last 30 years, the number of direct admissions has decreased concurrently. In fact, from 2003 to 2009, the number of direct admissions from clinics and physicians' offices decreased by a total of 1.6 million.[4] Although this decline is undoubtedly multifactorial, hospitalists may have contributed, both deliberately and inadvertently, to the shifting epidemiology of hospital admissions. Although many factors influence the source of hospital admissions and admission processes, direct admission has 2 important prerequisites: patients require timely access to outpatient providers for acute care, and hospitals, in partnership with outpatient‐based clinics and practices, require systems to safely and efficiently facilitate admissions without ED involvement. However, we know little about hospital admission systems, developed in the era of hospital medicine, to facilitate admissions independent of the ED.

Direct admission offers a number of potential benefits for both patients and healthcare delivery systems including reductions in the number of sites and providers of care, improved communication and coordination between outpatient and hospital‐based healthcare providers, greater patient and referring physician satisfaction, and reduced ED volumes and subsequent costs.[7] However, there are also risks and potential harms associated with direct admission, including potential delays in initial evaluation and management, inconsistent admission processes, and difficulties determining direct admission appropriateness, all of which could adversely impact patient safety and quality of care.[7, 8, 9] One study of adults with sepsis found that direct admission was associated with increased mortality compared to ED admission, which the authors speculated to be related to less timely care.[9] Similarly, a study of unscheduled adult hospitalizations found that patients admitted directly had higher mortality for time‐sensitive conditions such as acute myocardial infarction and sepsis than patients admitted through EDs, differences not observed among adults admitted with pneumonia, asthma, cellulitis, and several other common, yet frequently less emergent, reasons for hospitalization.[8] Among children with pneumonia, the most common reason for pediatric hospitalization, direct admission has been associated with significantly lower costs than admissions originating in the ED, with no significant differences in rates of transfer to the intensive care unit or hospital readmission.[10]

There is significant variation across both diagnoses and hospitals in rates of direct admission, raising questions about the contextual factors unique to hospital medicine programs that perform a substantial proportion of direct admissions.[5] This variation also highlights opportunities to identify the populations, conditions, and systems that facilitate safe and effective direct admissions. Certainly, direct admission is unlikely to be appropriate for all populations or conditions. Patients requiring emergent care or rapid diagnostic imaging are likely to receive more timely care in the ED; sepsis, acute myocardial infarction, and trauma are but a few examples of conditions for which rapid ED care decreases morbidity and mortality. Similarly, patients for whom the need for hospitalization is uncertainfor example, dehydration, asthmamay be more appropriate for initial ED management followed by re‐evaluation to inform the need for hospitalization. Finally, patients for whom the admitting diagnosis is uncertain and who require consultation for several subspecialists may be more efficiently evaluated in EDs. In our national survey of pediatric direct admission guidelines, less than one‐third of hospitals reported having formal criteria to assess the appropriateness of direct admissions, and respondents' perspectives regarding populations and diagnoses appropriate for this admission approach varied considerably.[7] These results point to the need for further research and quality‐improvement initiatives to inform the development of direct admission guidelines and protocols.

During the last decade, hospitals' discharge processes have been the focus of tremendous research, policy, and quality improvement efforts. The phrase transition of care is now widely understood to describe the changes in patient care that begin with discharge planning and conclude when patients' have established care at home or another healthcare facility. Transitions of care have been a focus of the Journal of Hospital Medicine since its inception, including publication of the Transitions of Care Consensus Policy Statement in 2009, as well as numerous other studies highlighting both risks associated with transitions of care as well as methods to address these.[11, 12, 13, 14, 15, 16] Similar to hospital discharge, hospital admission is an inherent feature of every hospitalization, and admission and discharge processes share many commonalities. Both involve transitions in sites of care, and handoffs between healthcare providers. Most involve changes in medical therapies, including both the addition of new medications and changes to existing treatments. Moreover, both are associated with significant stress to patients and their families. As a result, hospital admissions expose patients to many of same risks that have been the focus of hospital discharge reform: unstructured patient handoffs, poor communication between healthcare providers, and costly, inefficient care. The Society of Hospital Medicine has been a leader in articulating the importance of patient‐centered, clinically relevant medication reconciliation across the healthcare continuum.[17] However, with the exception of this important work, research and policy focused on understanding and improving transitions of care into the hospital have received disproportionately little attention.

To facilitate research and quality improvement efforts focused on hospital admission, we suggest that the transitions of care framework, typically discussed in the context of hospital discharge, be expanded to reflect the different origins of hospitalizations and multiple transitions that can be experienced by patients as they enter the hospital. A broadening of the transitions of care framework to incorporate hospital admissions brings numerous questions previously addressed in hospital‐to‐home transitions to the forefront. How do transitions into the hospital impact patients and healthcare systems? When is direct admission safe and effective, and how does this vary across conditions and hospital settings? What protocols and tools might optimize the associated transitions and reduce the risks of error and harm? There are numerous stakeholders who will undoubtedly bring diverse perspectives to these questionspatients and their families, hospital‐based healthcare providers, PCPs and specialists, ED physicians, and payors.

Increasing ED volumes, long wait times, and rising ED costs speak to the importance of better understanding hospital admission alternatives and the associated risks and benefits. Encouraging more direct admissions may be a solution, but evidence to guide best practices must precede this. The growing presence of round‐the‐clock pediatric and adult hospitalists across the country creates unique opportunities to transform hospital admission systems for the vast number of patients who do not require emergent care. The Affordable Care Act's expansion of insurance coverage and incentivized coordinated care within patient‐centered medical homes creates a unique opportunity for this broadened view of transitions of care. This suggests that the time is ripe for pursuing strategies that will both improve patients' transitions from outpatient to inpatient care and reduce stress on our overburdened emergency departments.

Disclosure: Dr. Lagu was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. She has received consulting fees from the Institute for Healthcare Improvement, under contract to the Centers for Medicare and Medicaid Services (CMS), for her work on a project to help health systems achieve disability competence, and from the Island Peer Review Organization, under contract to CMS, for her work on development of episodes of care for CMS payment purposes (both unrelated to the current work). Dr. Leyenaar was supported by grant number K08HS024133 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. The authors report no conflicts of interest.

Patient experience has become a major component of the Center for Medicare and Medicaid Services Value‐Based Purchasing initiative.[1] Hospitals have therefore focused quality improvement (QI) efforts on this area.[2] Hospital performance in the realm of patient experience is generally determined using systematic surveys with closed‐ended questions, but patient‐generated narrative feedback can help hospitals identify the components of care that contribute to patient satisfaction and or are in need of improvement.[3] Online narrative responses posted by patients on rating websites or social media have been criticized because they may not be representative of the population,[4] but they also have some advantages.[5] Any patient may leave a comment, not just those who are selected for a survey. Patients may also experience benefits through the act of sharing their story with others. Moreover, most US hospitals use some form of social media,[6] which they can theoretically use to self‐collect narrative data online. To realize the full potential of patient‐generated online narratives, we need a clearer understanding of the best practices for collecting and using these narratives. We therefore solicited patient feedback on the Facebook page of a large tertiary academic medical center to determine whether it is feasible to use social media platforms for learning about and improving hospital quality.

METHODS

Baystate Medical Center (BMC) is a tertiary care medical center in western Massachusetts. We identified key BMC stakeholders in the areas of QI and public affairs. Noting that patients have expressed interest in leaving comments via social media,[7] the group opted to perform a pilot study to obtain patient narratives via a Facebook prompt (Facebook is a social media site used by an estimated 58% of US adults[8]). The BMC public affairs department delivered a press release to the local media describing a 3‐week period during which patients were invited to leave narrative feedback on the BMC Facebook wall. The BMC Institutional Review Board deemed that this study did not constitute human subjects research.

During March 2014 (March 10, 2014March 24, 2014), we posted (once a week) an open‐ended prompt on BMC's Facebook wall. The prompt was designed to elicit novel descriptions of patient experience that could help to drive QI. It read: We want to hear about your experiences. In the comment section below, please tell us what we do well and how we can improve your care. Because of concerns about the potential reputational risks of allowing open feedback on a public social media page, the prompt also reminded patients of the social media ground rules: there should be no mention of specific physicians, nurses, or other caregivers by name (for liability reasons); and patients should not include details about their medical history (for privacy reasons).

We collected all posts to preserve comments and used directed qualitative content analysis to examine them.[9] Two research team members[3, 10, 11] independently coded the responses. Starting with an a priori codebook that was developed during a previous study,[3] they amended the codebook through an iterative process to incorporate new concepts. After independently coding all blocks of text, the coders reviewed their coding selections and resolved discrepancies through discussion. We then performed second‐level coding, in which codes were organized into major pertinent themes. We reviewed the coded text after applying secondary codes in order to check for accuracy of coding and theme assignment as well as completeness of second‐level coding. We calculated percent agreement, defined as both raters scoring a block of text with the same code divided by total number of codes. We also calculated the Spearman correlation between the 2 reviewers. We used descriptive statistics to assess the frequency of select codes and themes (see Supporting Information, Appendix 1 and Appendix 2, in the online version of this article).[9, 12, 13]

RESULTS

Over a 3‐week study period, 47 comments were submitted by 37 respondents. This yielded 148 codable statements (Table 1). Despite limited information on respondents, we ascertained from Facebook that 32 (86%) were women and 5 (14%) were men.

From coded text, several broad themes were identified (see Table 1 for representative quotes): (1) comments about staff (17/37 respondents, 45.9%). These included positive descriptions of efficiency, caring behavior, good training, and good communication, whereas negative comments included descriptions of unfriendliness, apparent lack of caring, inattentiveness, poor training, unprofessional behavior, and poor communication; (2) comments about specific departments (22/37, 59.5%); (3) comments on technical aspects of care, including perceived errors, incorrect diagnoses, and inattention to pain control (9/37, 24.3%); and (4) comments describing the hospital physical plant, parking, and amenities (9/37, 24.3%). There were a few miscellaneous comments that did not fit into these broad themes, such as expressions of gratitude for our solicitation of narratives. Percent agreement between coders was 80% and Spearman's Rho was 0.82 (p<0.001).

A small number (n=3) of respondents repeatedly made comments over the 3‐week period, accounting for 30% (45/148) of codes. These repetitive commenters tended to dominate the Facebook conversation, at times describing the same experience more than once.

DISCUSSION

In this study evaluating the potential utility of social media as a hospital QI tool, several broad themes emerged. From these themes, we identified several areas that could be deemed as QI targets, including: training staff to be more responsive and sensitive to patients needs and concerns, improving patient and visitor parking, and reducing emergency department waiting times. However, the insight gained from solicited Facebook comments was similar to feedback gained from more traditional approaches of soliciting patient perspectives on care, such as patient experience surveys.[14]

Our findings should be viewed in the context of prior work focused on patient narratives in healthcare. Greaves et al. used sentiment analysis to describe the content of nearly 200,000 tweets (comments posted on the social networking website Twitter) sent to National Health Service (NHS) hospitals.[15] Themes were similar to those found in our study: (1) interaction with staff, (2) environment and facilities, and (3) issues of access and timeliness of service. Notably, these themes mirrored prior work examining narratives at NHS hospitals[3] and were similar to domains of commonly used surveys of patient experience.[14] The authors noted that there were issues with the signal to noise ratio (only about 10% of tweets were about quality) and the enforced brevity of Twitter (tweets must be 140 characters or less). These limitations suggest that using Twitter to identify QI targets would be difficult.

In contrast to Greaves et al., we chose to solicit feedback on our hospital's Facebook page. Facebook does not have Twitter's enforced brevity, allowing for more detailed narratives. In addition, we did not encounter the signal‐to‐noise problem, because our prompt was designed to request feedback that was relevant to recent experiences of care. However, a few respondents dominated the conversation, supporting the hypothesis that those most likely to comment may be the patients or families who have had the best or worst experiences. In the future, we will attempt to address this limitation and reduce the influence of repeat commenters by changing our prompt (eg, Please tell us about your experience, but please do not post descriptions of the same experience more than once.).

This pilot demonstrated some of the previously described benefits of online narratives.[5] First, there appears to be value in allowing patients to share their experiences and to read the experiences of others (as indicated in a few grateful patients comments). Second, soliciting online narratives offers a way for hospitals to demonstrate a commitment to transparency. Third, in contrast to closed‐ended survey questions, narrative comments help to identify why patients were satisfied or unsatisfied with their care. Although some surveys with closed‐ended questions also allow for narratives, these comments may or may not be carefully reviewed by the hospital. Using social media to solicit and respond to comments enhances existing methods for evaluating patient experience by engaging patients in a public space, which increases the likelihood that hospitals will attempt to improve care in response.

Notably, none of the identified areas for improvement could be considered novel QI targets for BMC. For example, our hospital has been very focused on training staff around patient experience, and emergency department wait times are the focus of a system‐wide improvement effort called Patient Progress.

This study has other limitations. We conducted this study over a 3‐week time period in a single center and on a single social media site whose members may not be representative of the overall patient population at BMC. Although we do not know how generalizable our findings are (in terms of identifying QI targets), we feel that we have demonstrated how using social media to collect data on patient experience is feasible and could be informative for other hospitals in other locations. It is possible that we did not allow the experiment to run long enough; a longer time or broader outreach (eg, a handout given to every discharged patient over a longer period) may be needed to allow patients adequate opportunity to comment. Of note, we did not specifically examine responses by time period, but it does seem, in post hoc analysis, that after 2 weeks of data collection we reached theoretical saturation with no new themes emerging in the third week (eg, third‐week comments included I heart your nurses. and Love Baystate but hate the ER.). More work is also needed that includes a broader range of social media platforms and more participating hospitals.

In conclusion, the opportunity to provide feedback on Facebook has the potential to engage and empower patients, and hospitals can use these online narratives to help to drive improvement efforts. Yet potential benefits must be weighed against reputational risks, a lack of representative respondents, and the paucity of novel QI targets obtained in this study.

Disclosures: Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. The authors report no conflicts of interest.

Patient experience has become a major component of the Center for Medicare and Medicaid Services Value‐Based Purchasing initiative.[1] Hospitals have therefore focused quality improvement (QI) efforts on this area.[2] Hospital performance in the realm of patient experience is generally determined using systematic surveys with closed‐ended questions, but patient‐generated narrative feedback can help hospitals identify the components of care that contribute to patient satisfaction and or are in need of improvement.[3] Online narrative responses posted by patients on rating websites or social media have been criticized because they may not be representative of the population,[4] but they also have some advantages.[5] Any patient may leave a comment, not just those who are selected for a survey. Patients may also experience benefits through the act of sharing their story with others. Moreover, most US hospitals use some form of social media,[6] which they can theoretically use to self‐collect narrative data online. To realize the full potential of patient‐generated online narratives, we need a clearer understanding of the best practices for collecting and using these narratives. We therefore solicited patient feedback on the Facebook page of a large tertiary academic medical center to determine whether it is feasible to use social media platforms for learning about and improving hospital quality.

METHODS

Baystate Medical Center (BMC) is a tertiary care medical center in western Massachusetts. We identified key BMC stakeholders in the areas of QI and public affairs. Noting that patients have expressed interest in leaving comments via social media,[7] the group opted to perform a pilot study to obtain patient narratives via a Facebook prompt (Facebook is a social media site used by an estimated 58% of US adults[8]). The BMC public affairs department delivered a press release to the local media describing a 3‐week period during which patients were invited to leave narrative feedback on the BMC Facebook wall. The BMC Institutional Review Board deemed that this study did not constitute human subjects research.

During March 2014 (March 10, 2014March 24, 2014), we posted (once a week) an open‐ended prompt on BMC's Facebook wall. The prompt was designed to elicit novel descriptions of patient experience that could help to drive QI. It read: We want to hear about your experiences. In the comment section below, please tell us what we do well and how we can improve your care. Because of concerns about the potential reputational risks of allowing open feedback on a public social media page, the prompt also reminded patients of the social media ground rules: there should be no mention of specific physicians, nurses, or other caregivers by name (for liability reasons); and patients should not include details about their medical history (for privacy reasons).

We collected all posts to preserve comments and used directed qualitative content analysis to examine them.[9] Two research team members[3, 10, 11] independently coded the responses. Starting with an a priori codebook that was developed during a previous study,[3] they amended the codebook through an iterative process to incorporate new concepts. After independently coding all blocks of text, the coders reviewed their coding selections and resolved discrepancies through discussion. We then performed second‐level coding, in which codes were organized into major pertinent themes. We reviewed the coded text after applying secondary codes in order to check for accuracy of coding and theme assignment as well as completeness of second‐level coding. We calculated percent agreement, defined as both raters scoring a block of text with the same code divided by total number of codes. We also calculated the Spearman correlation between the 2 reviewers. We used descriptive statistics to assess the frequency of select codes and themes (see Supporting Information, Appendix 1 and Appendix 2, in the online version of this article).[9, 12, 13]

RESULTS

Over a 3‐week study period, 47 comments were submitted by 37 respondents. This yielded 148 codable statements (Table 1). Despite limited information on respondents, we ascertained from Facebook that 32 (86%) were women and 5 (14%) were men.

From coded text, several broad themes were identified (see Table 1 for representative quotes): (1) comments about staff (17/37 respondents, 45.9%). These included positive descriptions of efficiency, caring behavior, good training, and good communication, whereas negative comments included descriptions of unfriendliness, apparent lack of caring, inattentiveness, poor training, unprofessional behavior, and poor communication; (2) comments about specific departments (22/37, 59.5%); (3) comments on technical aspects of care, including perceived errors, incorrect diagnoses, and inattention to pain control (9/37, 24.3%); and (4) comments describing the hospital physical plant, parking, and amenities (9/37, 24.3%). There were a few miscellaneous comments that did not fit into these broad themes, such as expressions of gratitude for our solicitation of narratives. Percent agreement between coders was 80% and Spearman's Rho was 0.82 (p<0.001).

A small number (n=3) of respondents repeatedly made comments over the 3‐week period, accounting for 30% (45/148) of codes. These repetitive commenters tended to dominate the Facebook conversation, at times describing the same experience more than once.

DISCUSSION

In this study evaluating the potential utility of social media as a hospital QI tool, several broad themes emerged. From these themes, we identified several areas that could be deemed as QI targets, including: training staff to be more responsive and sensitive to patients needs and concerns, improving patient and visitor parking, and reducing emergency department waiting times. However, the insight gained from solicited Facebook comments was similar to feedback gained from more traditional approaches of soliciting patient perspectives on care, such as patient experience surveys.[14]

Our findings should be viewed in the context of prior work focused on patient narratives in healthcare. Greaves et al. used sentiment analysis to describe the content of nearly 200,000 tweets (comments posted on the social networking website Twitter) sent to National Health Service (NHS) hospitals.[15] Themes were similar to those found in our study: (1) interaction with staff, (2) environment and facilities, and (3) issues of access and timeliness of service. Notably, these themes mirrored prior work examining narratives at NHS hospitals[3] and were similar to domains of commonly used surveys of patient experience.[14] The authors noted that there were issues with the signal to noise ratio (only about 10% of tweets were about quality) and the enforced brevity of Twitter (tweets must be 140 characters or less). These limitations suggest that using Twitter to identify QI targets would be difficult.

In contrast to Greaves et al., we chose to solicit feedback on our hospital's Facebook page. Facebook does not have Twitter's enforced brevity, allowing for more detailed narratives. In addition, we did not encounter the signal‐to‐noise problem, because our prompt was designed to request feedback that was relevant to recent experiences of care. However, a few respondents dominated the conversation, supporting the hypothesis that those most likely to comment may be the patients or families who have had the best or worst experiences. In the future, we will attempt to address this limitation and reduce the influence of repeat commenters by changing our prompt (eg, Please tell us about your experience, but please do not post descriptions of the same experience more than once.).

This pilot demonstrated some of the previously described benefits of online narratives.[5] First, there appears to be value in allowing patients to share their experiences and to read the experiences of others (as indicated in a few grateful patients comments). Second, soliciting online narratives offers a way for hospitals to demonstrate a commitment to transparency. Third, in contrast to closed‐ended survey questions, narrative comments help to identify why patients were satisfied or unsatisfied with their care. Although some surveys with closed‐ended questions also allow for narratives, these comments may or may not be carefully reviewed by the hospital. Using social media to solicit and respond to comments enhances existing methods for evaluating patient experience by engaging patients in a public space, which increases the likelihood that hospitals will attempt to improve care in response.

Notably, none of the identified areas for improvement could be considered novel QI targets for BMC. For example, our hospital has been very focused on training staff around patient experience, and emergency department wait times are the focus of a system‐wide improvement effort called Patient Progress.

This study has other limitations. We conducted this study over a 3‐week time period in a single center and on a single social media site whose members may not be representative of the overall patient population at BMC. Although we do not know how generalizable our findings are (in terms of identifying QI targets), we feel that we have demonstrated how using social media to collect data on patient experience is feasible and could be informative for other hospitals in other locations. It is possible that we did not allow the experiment to run long enough; a longer time or broader outreach (eg, a handout given to every discharged patient over a longer period) may be needed to allow patients adequate opportunity to comment. Of note, we did not specifically examine responses by time period, but it does seem, in post hoc analysis, that after 2 weeks of data collection we reached theoretical saturation with no new themes emerging in the third week (eg, third‐week comments included I heart your nurses. and Love Baystate but hate the ER.). More work is also needed that includes a broader range of social media platforms and more participating hospitals.

In conclusion, the opportunity to provide feedback on Facebook has the potential to engage and empower patients, and hospitals can use these online narratives to help to drive improvement efforts. Yet potential benefits must be weighed against reputational risks, a lack of representative respondents, and the paucity of novel QI targets obtained in this study.

Disclosures: Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. The authors report no conflicts of interest.

Patient experience has become a major component of the Center for Medicare and Medicaid Services Value‐Based Purchasing initiative.[1] Hospitals have therefore focused quality improvement (QI) efforts on this area.[2] Hospital performance in the realm of patient experience is generally determined using systematic surveys with closed‐ended questions, but patient‐generated narrative feedback can help hospitals identify the components of care that contribute to patient satisfaction and or are in need of improvement.[3] Online narrative responses posted by patients on rating websites or social media have been criticized because they may not be representative of the population,[4] but they also have some advantages.[5] Any patient may leave a comment, not just those who are selected for a survey. Patients may also experience benefits through the act of sharing their story with others. Moreover, most US hospitals use some form of social media,[6] which they can theoretically use to self‐collect narrative data online. To realize the full potential of patient‐generated online narratives, we need a clearer understanding of the best practices for collecting and using these narratives. We therefore solicited patient feedback on the Facebook page of a large tertiary academic medical center to determine whether it is feasible to use social media platforms for learning about and improving hospital quality.

METHODS

Baystate Medical Center (BMC) is a tertiary care medical center in western Massachusetts. We identified key BMC stakeholders in the areas of QI and public affairs. Noting that patients have expressed interest in leaving comments via social media,[7] the group opted to perform a pilot study to obtain patient narratives via a Facebook prompt (Facebook is a social media site used by an estimated 58% of US adults[8]). The BMC public affairs department delivered a press release to the local media describing a 3‐week period during which patients were invited to leave narrative feedback on the BMC Facebook wall. The BMC Institutional Review Board deemed that this study did not constitute human subjects research.

During March 2014 (March 10, 2014March 24, 2014), we posted (once a week) an open‐ended prompt on BMC's Facebook wall. The prompt was designed to elicit novel descriptions of patient experience that could help to drive QI. It read: We want to hear about your experiences. In the comment section below, please tell us what we do well and how we can improve your care. Because of concerns about the potential reputational risks of allowing open feedback on a public social media page, the prompt also reminded patients of the social media ground rules: there should be no mention of specific physicians, nurses, or other caregivers by name (for liability reasons); and patients should not include details about their medical history (for privacy reasons).

We collected all posts to preserve comments and used directed qualitative content analysis to examine them.[9] Two research team members[3, 10, 11] independently coded the responses. Starting with an a priori codebook that was developed during a previous study,[3] they amended the codebook through an iterative process to incorporate new concepts. After independently coding all blocks of text, the coders reviewed their coding selections and resolved discrepancies through discussion. We then performed second‐level coding, in which codes were organized into major pertinent themes. We reviewed the coded text after applying secondary codes in order to check for accuracy of coding and theme assignment as well as completeness of second‐level coding. We calculated percent agreement, defined as both raters scoring a block of text with the same code divided by total number of codes. We also calculated the Spearman correlation between the 2 reviewers. We used descriptive statistics to assess the frequency of select codes and themes (see Supporting Information, Appendix 1 and Appendix 2, in the online version of this article).[9, 12, 13]

RESULTS

Over a 3‐week study period, 47 comments were submitted by 37 respondents. This yielded 148 codable statements (Table 1). Despite limited information on respondents, we ascertained from Facebook that 32 (86%) were women and 5 (14%) were men.

From coded text, several broad themes were identified (see Table 1 for representative quotes): (1) comments about staff (17/37 respondents, 45.9%). These included positive descriptions of efficiency, caring behavior, good training, and good communication, whereas negative comments included descriptions of unfriendliness, apparent lack of caring, inattentiveness, poor training, unprofessional behavior, and poor communication; (2) comments about specific departments (22/37, 59.5%); (3) comments on technical aspects of care, including perceived errors, incorrect diagnoses, and inattention to pain control (9/37, 24.3%); and (4) comments describing the hospital physical plant, parking, and amenities (9/37, 24.3%). There were a few miscellaneous comments that did not fit into these broad themes, such as expressions of gratitude for our solicitation of narratives. Percent agreement between coders was 80% and Spearman's Rho was 0.82 (p<0.001).

A small number (n=3) of respondents repeatedly made comments over the 3‐week period, accounting for 30% (45/148) of codes. These repetitive commenters tended to dominate the Facebook conversation, at times describing the same experience more than once.

DISCUSSION

In this study evaluating the potential utility of social media as a hospital QI tool, several broad themes emerged. From these themes, we identified several areas that could be deemed as QI targets, including: training staff to be more responsive and sensitive to patients needs and concerns, improving patient and visitor parking, and reducing emergency department waiting times. However, the insight gained from solicited Facebook comments was similar to feedback gained from more traditional approaches of soliciting patient perspectives on care, such as patient experience surveys.[14]

Our findings should be viewed in the context of prior work focused on patient narratives in healthcare. Greaves et al. used sentiment analysis to describe the content of nearly 200,000 tweets (comments posted on the social networking website Twitter) sent to National Health Service (NHS) hospitals.[15] Themes were similar to those found in our study: (1) interaction with staff, (2) environment and facilities, and (3) issues of access and timeliness of service. Notably, these themes mirrored prior work examining narratives at NHS hospitals[3] and were similar to domains of commonly used surveys of patient experience.[14] The authors noted that there were issues with the signal to noise ratio (only about 10% of tweets were about quality) and the enforced brevity of Twitter (tweets must be 140 characters or less). These limitations suggest that using Twitter to identify QI targets would be difficult.

In contrast to Greaves et al., we chose to solicit feedback on our hospital's Facebook page. Facebook does not have Twitter's enforced brevity, allowing for more detailed narratives. In addition, we did not encounter the signal‐to‐noise problem, because our prompt was designed to request feedback that was relevant to recent experiences of care. However, a few respondents dominated the conversation, supporting the hypothesis that those most likely to comment may be the patients or families who have had the best or worst experiences. In the future, we will attempt to address this limitation and reduce the influence of repeat commenters by changing our prompt (eg, Please tell us about your experience, but please do not post descriptions of the same experience more than once.).

This pilot demonstrated some of the previously described benefits of online narratives.[5] First, there appears to be value in allowing patients to share their experiences and to read the experiences of others (as indicated in a few grateful patients comments). Second, soliciting online narratives offers a way for hospitals to demonstrate a commitment to transparency. Third, in contrast to closed‐ended survey questions, narrative comments help to identify why patients were satisfied or unsatisfied with their care. Although some surveys with closed‐ended questions also allow for narratives, these comments may or may not be carefully reviewed by the hospital. Using social media to solicit and respond to comments enhances existing methods for evaluating patient experience by engaging patients in a public space, which increases the likelihood that hospitals will attempt to improve care in response.

Notably, none of the identified areas for improvement could be considered novel QI targets for BMC. For example, our hospital has been very focused on training staff around patient experience, and emergency department wait times are the focus of a system‐wide improvement effort called Patient Progress.

This study has other limitations. We conducted this study over a 3‐week time period in a single center and on a single social media site whose members may not be representative of the overall patient population at BMC. Although we do not know how generalizable our findings are (in terms of identifying QI targets), we feel that we have demonstrated how using social media to collect data on patient experience is feasible and could be informative for other hospitals in other locations. It is possible that we did not allow the experiment to run long enough; a longer time or broader outreach (eg, a handout given to every discharged patient over a longer period) may be needed to allow patients adequate opportunity to comment. Of note, we did not specifically examine responses by time period, but it does seem, in post hoc analysis, that after 2 weeks of data collection we reached theoretical saturation with no new themes emerging in the third week (eg, third‐week comments included I heart your nurses. and Love Baystate but hate the ER.). More work is also needed that includes a broader range of social media platforms and more participating hospitals.

In conclusion, the opportunity to provide feedback on Facebook has the potential to engage and empower patients, and hospitals can use these online narratives to help to drive improvement efforts. Yet potential benefits must be weighed against reputational risks, a lack of representative respondents, and the paucity of novel QI targets obtained in this study.

Disclosures: Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. The authors report no conflicts of interest.

Ascites is the most common complication of cirrhosis leading to hospital admission.[1] Approximately 12% of hospitalized patients who present with decompensated cirrhosis and ascites have spontaneous bacterial peritonitis (SBP); half of these patients do not present with abdominal pain, fever, nausea, or vomiting.[2] Guidelines published by the American Association for the Study of Liver Diseases (AASLD) recommend paracentesis for all hospitalized patients with cirrhosis and ascites and also recommend long‐term antibiotic prophylaxis for survivors of an SBP episode.[3] Despite evidence that in‐hospital mortality is reduced in those patients who receive paracentesis in a timely manner,[4, 5] only 40% to 60% of eligible patients receive paracentesis.[4, 6, 7] We aimed to describe clinical predictors of paracentesis and use of antibiotics following an episode of SBP in patients with decompensated cirrhosis and ascites.

METHODS

We conducted a retrospective cohort study of adults admitted to a single tertiary care center between January 1, 2009 and December 31, 2009.⁷ We included patients with an International Classification of Diseases, Ninth Revision discharge code consistent with decompensated cirrhosis who met clinical criteria for decompensated cirrhosis (see Supporting Figure 1 in the online version of this article) [7] and had enough ascitic fluid to be sampled under imaging guidance. We collected presenting vital signs, laboratory data (within 24 hours of admission), evidence of infection other than SBP (eg, urinary infection, pneumonia), results of peritoneal fluid analysis (defining SBP as 250 polymorphonuclear leukocytes), and use of antibiotic therapy. Our statistical analysis calculated summary statistics as means, medians, and proportions. Furthermore, we used multiple logistic regression to examine the association between predictors and receipt of paracentesis, including age, sex, and clinical measures associated with paracentesis at P0.20 using the Fisher exact test. Alpha was set at 0.05 (2‐sided) for all comparisons.

RESULTS

We identified 193 admissions for 103 patients with decompensated cirrhosis and ascites (Table 1). Of these, 41% (80/193) received diagnostic paracentesis. Mean/standard deviation for age was 53.6/12.4 years; 71% of patients were male and 63% were English speaking. Common comorbidities included diabetes mellitus (33%), psychiatric diagnosis (29%), substance abuse (18%), and renal failure (17%). Excluding SBP, 31% of patients had another documented infection. Gastroenterology was consulted in 50% of the admissions. Fever was present in 27% of patients, elevated white blood cell (WBC) count (ie, WBC >11 k/mm³) was present in 27% of patients, International Normalized Ratio (INR) was elevated (>1.1) in 92% of patients, and 16% of patients had a platelet count of <50,000/mm³. Patients who received paracentesis were less likely to have a fever on presentation (19% vs 32%, P=0.06), low (ie, <50,000/mm³) platelet count (11% vs 19%, P=0.14), or concurrent gastrointestinal (GI) bleed (6% vs 16%, P=0.05). In a multiple logistic regression model including characteristics associated at P0.2 with paracentesis, fever, low platelet count, and concurrent GI bleeding were associated with decreased odds of receiving paracentesis (Appendix 1).

Of the patients who received paracentesis (n=80), 14% were diagnosed with SBP. Of these, 55% received prophylaxis on discharge. Among the patients who did not receive paracentesis (n=113), 38 (34%) received antibiotics for another documented infection (eg, pneumonia), and 25 patients (22%) received antibiotics with no other documented infection or evidence of variceal bleeding. Of these 25 patients who were presumed to be empirically treated for SBP (Figure 1), only 20% were prescribed prophylactic antibiotics on discharge.

Figure 1

CONCLUSION

We found that many patients with decompensated cirrhosis and ascites did not receive paracentesis when hospitalized, which is similar to previously published data.[4, 6, 7] Clinical evidence of infection, such as fever or elevated WBC count, did not increase the odds of receiving paracentesis. Many patients treated for SBP were not discharged on prophylaxis.

This study is limited by its small single‐center design. We could only use data from 1 year (2009), because study data collection was part of a quality‐improvement project that took place for that year only. We did not adjust for the number of red blood cells in the ascitic fluid samples. We were also unable to determine the timing of gastroenterology consultation (whether it was done prior to paracentesis), admission venue (floor vs intensive care), or patient history of SBP.

Despite these limitations, there are important implications. First, the decision to perform paracentesis was not associated with symptoms of infection, although some clinical factors (eg, low platelets or GI bleeding) were associated with reduced odds of receiving paracentesis. Second, a majority of patients treated for SBP did not receive prophylactic antibiotics at discharge. These findings suggest a clear opportunity to increase awareness and acceptance of AASLD guidelines among hospital medicine practitioners. Quality‐improvement efforts should focus on the education of providers, and future research should identify barriers to paracentesis at both the practitioner and system levels (eg, availability of interventional radiology). Checklists or decision support within electronic order entry systems may also help reduce the low rates of paracentesis seen in our and prior studies.[4, 6, 7]

Disclosures: Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Drs. Lagu, Ghaoui, and Brooling had full access to all of the data in the study. They take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Ghaoui, and Brooling conceived of the study. Dr. Ghaoui acquired the data. Ms. Friderici carried out the statistical analyses. Drs. Lagu, Ghaoui, Brooling, Lindenauer, and Ms. Friderici analyzed and interpreted the data, drafted the manuscript, and critically reviewed the manuscript for important intellectual content. The authors report no conflicts of interest.

Ascites is the most common complication of cirrhosis leading to hospital admission.[1] Approximately 12% of hospitalized patients who present with decompensated cirrhosis and ascites have spontaneous bacterial peritonitis (SBP); half of these patients do not present with abdominal pain, fever, nausea, or vomiting.[2] Guidelines published by the American Association for the Study of Liver Diseases (AASLD) recommend paracentesis for all hospitalized patients with cirrhosis and ascites and also recommend long‐term antibiotic prophylaxis for survivors of an SBP episode.[3] Despite evidence that in‐hospital mortality is reduced in those patients who receive paracentesis in a timely manner,[4, 5] only 40% to 60% of eligible patients receive paracentesis.[4, 6, 7] We aimed to describe clinical predictors of paracentesis and use of antibiotics following an episode of SBP in patients with decompensated cirrhosis and ascites.

METHODS

We conducted a retrospective cohort study of adults admitted to a single tertiary care center between January 1, 2009 and December 31, 2009.⁷ We included patients with an International Classification of Diseases, Ninth Revision discharge code consistent with decompensated cirrhosis who met clinical criteria for decompensated cirrhosis (see Supporting Figure 1 in the online version of this article) [7] and had enough ascitic fluid to be sampled under imaging guidance. We collected presenting vital signs, laboratory data (within 24 hours of admission), evidence of infection other than SBP (eg, urinary infection, pneumonia), results of peritoneal fluid analysis (defining SBP as 250 polymorphonuclear leukocytes), and use of antibiotic therapy. Our statistical analysis calculated summary statistics as means, medians, and proportions. Furthermore, we used multiple logistic regression to examine the association between predictors and receipt of paracentesis, including age, sex, and clinical measures associated with paracentesis at P0.20 using the Fisher exact test. Alpha was set at 0.05 (2‐sided) for all comparisons.

RESULTS

We identified 193 admissions for 103 patients with decompensated cirrhosis and ascites (Table 1). Of these, 41% (80/193) received diagnostic paracentesis. Mean/standard deviation for age was 53.6/12.4 years; 71% of patients were male and 63% were English speaking. Common comorbidities included diabetes mellitus (33%), psychiatric diagnosis (29%), substance abuse (18%), and renal failure (17%). Excluding SBP, 31% of patients had another documented infection. Gastroenterology was consulted in 50% of the admissions. Fever was present in 27% of patients, elevated white blood cell (WBC) count (ie, WBC >11 k/mm³) was present in 27% of patients, International Normalized Ratio (INR) was elevated (>1.1) in 92% of patients, and 16% of patients had a platelet count of <50,000/mm³. Patients who received paracentesis were less likely to have a fever on presentation (19% vs 32%, P=0.06), low (ie, <50,000/mm³) platelet count (11% vs 19%, P=0.14), or concurrent gastrointestinal (GI) bleed (6% vs 16%, P=0.05). In a multiple logistic regression model including characteristics associated at P0.2 with paracentesis, fever, low platelet count, and concurrent GI bleeding were associated with decreased odds of receiving paracentesis (Appendix 1).

Of the patients who received paracentesis (n=80), 14% were diagnosed with SBP. Of these, 55% received prophylaxis on discharge. Among the patients who did not receive paracentesis (n=113), 38 (34%) received antibiotics for another documented infection (eg, pneumonia), and 25 patients (22%) received antibiotics with no other documented infection or evidence of variceal bleeding. Of these 25 patients who were presumed to be empirically treated for SBP (Figure 1), only 20% were prescribed prophylactic antibiotics on discharge.

Figure 1

CONCLUSION

We found that many patients with decompensated cirrhosis and ascites did not receive paracentesis when hospitalized, which is similar to previously published data.[4, 6, 7] Clinical evidence of infection, such as fever or elevated WBC count, did not increase the odds of receiving paracentesis. Many patients treated for SBP were not discharged on prophylaxis.

This study is limited by its small single‐center design. We could only use data from 1 year (2009), because study data collection was part of a quality‐improvement project that took place for that year only. We did not adjust for the number of red blood cells in the ascitic fluid samples. We were also unable to determine the timing of gastroenterology consultation (whether it was done prior to paracentesis), admission venue (floor vs intensive care), or patient history of SBP.

Despite these limitations, there are important implications. First, the decision to perform paracentesis was not associated with symptoms of infection, although some clinical factors (eg, low platelets or GI bleeding) were associated with reduced odds of receiving paracentesis. Second, a majority of patients treated for SBP did not receive prophylactic antibiotics at discharge. These findings suggest a clear opportunity to increase awareness and acceptance of AASLD guidelines among hospital medicine practitioners. Quality‐improvement efforts should focus on the education of providers, and future research should identify barriers to paracentesis at both the practitioner and system levels (eg, availability of interventional radiology). Checklists or decision support within electronic order entry systems may also help reduce the low rates of paracentesis seen in our and prior studies.[4, 6, 7]

Disclosures: Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Drs. Lagu, Ghaoui, and Brooling had full access to all of the data in the study. They take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Ghaoui, and Brooling conceived of the study. Dr. Ghaoui acquired the data. Ms. Friderici carried out the statistical analyses. Drs. Lagu, Ghaoui, Brooling, Lindenauer, and Ms. Friderici analyzed and interpreted the data, drafted the manuscript, and critically reviewed the manuscript for important intellectual content. The authors report no conflicts of interest.

Ascites is the most common complication of cirrhosis leading to hospital admission.[1] Approximately 12% of hospitalized patients who present with decompensated cirrhosis and ascites have spontaneous bacterial peritonitis (SBP); half of these patients do not present with abdominal pain, fever, nausea, or vomiting.[2] Guidelines published by the American Association for the Study of Liver Diseases (AASLD) recommend paracentesis for all hospitalized patients with cirrhosis and ascites and also recommend long‐term antibiotic prophylaxis for survivors of an SBP episode.[3] Despite evidence that in‐hospital mortality is reduced in those patients who receive paracentesis in a timely manner,[4, 5] only 40% to 60% of eligible patients receive paracentesis.[4, 6, 7] We aimed to describe clinical predictors of paracentesis and use of antibiotics following an episode of SBP in patients with decompensated cirrhosis and ascites.

METHODS

We conducted a retrospective cohort study of adults admitted to a single tertiary care center between January 1, 2009 and December 31, 2009.⁷ We included patients with an International Classification of Diseases, Ninth Revision discharge code consistent with decompensated cirrhosis who met clinical criteria for decompensated cirrhosis (see Supporting Figure 1 in the online version of this article) [7] and had enough ascitic fluid to be sampled under imaging guidance. We collected presenting vital signs, laboratory data (within 24 hours of admission), evidence of infection other than SBP (eg, urinary infection, pneumonia), results of peritoneal fluid analysis (defining SBP as 250 polymorphonuclear leukocytes), and use of antibiotic therapy. Our statistical analysis calculated summary statistics as means, medians, and proportions. Furthermore, we used multiple logistic regression to examine the association between predictors and receipt of paracentesis, including age, sex, and clinical measures associated with paracentesis at P0.20 using the Fisher exact test. Alpha was set at 0.05 (2‐sided) for all comparisons.

RESULTS

We identified 193 admissions for 103 patients with decompensated cirrhosis and ascites (Table 1). Of these, 41% (80/193) received diagnostic paracentesis. Mean/standard deviation for age was 53.6/12.4 years; 71% of patients were male and 63% were English speaking. Common comorbidities included diabetes mellitus (33%), psychiatric diagnosis (29%), substance abuse (18%), and renal failure (17%). Excluding SBP, 31% of patients had another documented infection. Gastroenterology was consulted in 50% of the admissions. Fever was present in 27% of patients, elevated white blood cell (WBC) count (ie, WBC >11 k/mm³) was present in 27% of patients, International Normalized Ratio (INR) was elevated (>1.1) in 92% of patients, and 16% of patients had a platelet count of <50,000/mm³. Patients who received paracentesis were less likely to have a fever on presentation (19% vs 32%, P=0.06), low (ie, <50,000/mm³) platelet count (11% vs 19%, P=0.14), or concurrent gastrointestinal (GI) bleed (6% vs 16%, P=0.05). In a multiple logistic regression model including characteristics associated at P0.2 with paracentesis, fever, low platelet count, and concurrent GI bleeding were associated with decreased odds of receiving paracentesis (Appendix 1).

Of the patients who received paracentesis (n=80), 14% were diagnosed with SBP. Of these, 55% received prophylaxis on discharge. Among the patients who did not receive paracentesis (n=113), 38 (34%) received antibiotics for another documented infection (eg, pneumonia), and 25 patients (22%) received antibiotics with no other documented infection or evidence of variceal bleeding. Of these 25 patients who were presumed to be empirically treated for SBP (Figure 1), only 20% were prescribed prophylactic antibiotics on discharge.

Figure 1

CONCLUSION

We found that many patients with decompensated cirrhosis and ascites did not receive paracentesis when hospitalized, which is similar to previously published data.[4, 6, 7] Clinical evidence of infection, such as fever or elevated WBC count, did not increase the odds of receiving paracentesis. Many patients treated for SBP were not discharged on prophylaxis.

This study is limited by its small single‐center design. We could only use data from 1 year (2009), because study data collection was part of a quality‐improvement project that took place for that year only. We did not adjust for the number of red blood cells in the ascitic fluid samples. We were also unable to determine the timing of gastroenterology consultation (whether it was done prior to paracentesis), admission venue (floor vs intensive care), or patient history of SBP.

Despite these limitations, there are important implications. First, the decision to perform paracentesis was not associated with symptoms of infection, although some clinical factors (eg, low platelets or GI bleeding) were associated with reduced odds of receiving paracentesis. Second, a majority of patients treated for SBP did not receive prophylactic antibiotics at discharge. These findings suggest a clear opportunity to increase awareness and acceptance of AASLD guidelines among hospital medicine practitioners. Quality‐improvement efforts should focus on the education of providers, and future research should identify barriers to paracentesis at both the practitioner and system levels (eg, availability of interventional radiology). Checklists or decision support within electronic order entry systems may also help reduce the low rates of paracentesis seen in our and prior studies.[4, 6, 7]

Disclosures: Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Drs. Lagu, Ghaoui, and Brooling had full access to all of the data in the study. They take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Ghaoui, and Brooling conceived of the study. Dr. Ghaoui acquired the data. Ms. Friderici carried out the statistical analyses. Drs. Lagu, Ghaoui, Brooling, Lindenauer, and Ms. Friderici analyzed and interpreted the data, drafted the manuscript, and critically reviewed the manuscript for important intellectual content. The authors report no conflicts of interest.

Antipsychotic (AP) medications are often used in the hospitalized geriatric population for the treatment of delirium.[1] Because of adverse events associated with APs, efforts have been made to reduce their use in hospitalized elders,[2] but it is not clear if these recommendations have been widely adopted. We studied the use of APs in a cohort of hospitalized elders to better understand why APs are started and how often they are continued on discharge.

METHODS

We conducted a retrospective cohort study of patients aged 65 years or older admitted to a tertiary care hospital between October 1, 2012 and September 31, 2013. Using Stata's (StataCorp., College Station, TX) sample command,[3] we included a subset of randomly selected inpatients who received more than 1 dose of oral APs (determined using the electronic medication administration summary). We excluded patients admitted under observation status or to the psychiatric service, those who were on APs prior to admission, and those who only received prochloperazine for nausea. Using prior literature to identify terms frequently used to describe delirium (Figure 1), we created an algorithm and a chart abstraction form (see Supporting Information, Appendix 1, in the online version of this article).[4] We tested these instruments in a preliminary chart review involving 30 patients. Disagreements were discussed with coauthors and resolved through consensus, resulting in some algorithm changes (eg, excluding a large number of patients who received only 1 dose of haloperidol postoperatively, because we hypothesized that this use could be a prophylactic measure).[5] Two investigators extracted the remaining charts independently. We used descriptive statistics and performed cross‐tabulations on the selected variables.

Figure 1

RESULTS

Of 12,817 geriatric hospitalizations during the study period, 1120 (9%) were treated with antipsychotics. We randomly selected 300 of these for extraction: 54% were male, and 67% were admitted to the medical service (Table 1). The inpatient mortality rate was 10% (30/300). The most frequent indication for AP use was delirium (83%, 249/300). Only 35% of delirious patients received a formal assessment with the Confusion Assessment Method (CAM). The most commonly used atypical antipsychotic was quetiapine (86%); 55% received more than 1 antipsychotic medication during hospitalization, and 48% (143/297) of patients were continued on APs at discharge (excluding 3 patients transferred to other acute care hospitals).

Approximately 45% (134/300) had documented or suspected dementia, and 30% (89/300) were physically restrained during the hospital stay. Consultations with geriatrics were obtained in 40% (120/300) of the cases and with psychiatry in 10% (29/300) of the cases. Neurology is rarely consulted for delirium in our institution; thus, we did not collect data on those referrals. Electrocardiography (ECG) (recommended for patients at high cardiac risk[6]) was performed in 88% (265/300) of patients prior to AP administration and 52% (157/300) after. The corrected QT interval exceeded 500 ms in 15% (41/265) of patients prior to AP administration and 25% (39/157) after. Although few patients (12%) were admitted from nursing facilities, 66% (199/300) were eventually discharged to skilled nursing facilities (SNFs) or rehabilitation facilities; most of these patients (117/199, 59%) received AP treatment, compared to 38% of patients discharged to home (26/68).

DISCUSSION

In a cohort of hospitalized elders, we found that 9% were treated with APs. Most received APs for perceived delirium; in‐hospital ECG monitoring was suboptimal. Half of the patients started on APs remained on them at discharge; those discharged to SNFs were more likely to receive ongoing AP treatment.

Our study is limited by its retrospective, single‐center design, a lack of inter‐rater reliability measurement (although our training process was designed to standardize extraction methods), and the infrequent use of formal CAM assessment. Additionally, we were unable to determine how frequently APs were initiated in the intensive care unit. Any retrospective study is limited by the difficulty of distinguishing delirium from the behavioral and psychiatric symptoms of dementia, but we identified delirium using standard terms described in previous literature.

Our study also has a number of important implications. Because of a reported association between the use of APs and risk of death in the postacute setting,[7] national provider organizations have called for a reduction in AP initiation in hospitalized elders.[2] However, this study indicates that APs continue to be prescribed for delirium, which may be attributed to the lack of behavioral modification options in most hospitals, such as acute care for elders (ACE) units and hospital elder life programs (HELP).[8, 9] Our findings suggest that this problem would be further amplified in hospitals that lack access to geriatrics expertise.

Without alternative behavioral options, patients are at risk for prolonged delirium, which is associated with significant suffering and subsequent risk of further cognitive impairment and death.[10] Although evidence for the efficacy of APs in the treatment of delirium is limited and inconclusive, no better pharmacologic options exist. Hospitals that wish to reduce use of APs should therefore consider investing in environmental interventions (eg, ACE units, HELP), which lower the incidence of delirium and could, in turn, decrease the prescription and continuation of antipsychotics.[8, 9]

Antipsychotic (AP) medications are often used in the hospitalized geriatric population for the treatment of delirium.[1] Because of adverse events associated with APs, efforts have been made to reduce their use in hospitalized elders,[2] but it is not clear if these recommendations have been widely adopted. We studied the use of APs in a cohort of hospitalized elders to better understand why APs are started and how often they are continued on discharge.

METHODS

We conducted a retrospective cohort study of patients aged 65 years or older admitted to a tertiary care hospital between October 1, 2012 and September 31, 2013. Using Stata's (StataCorp., College Station, TX) sample command,[3] we included a subset of randomly selected inpatients who received more than 1 dose of oral APs (determined using the electronic medication administration summary). We excluded patients admitted under observation status or to the psychiatric service, those who were on APs prior to admission, and those who only received prochloperazine for nausea. Using prior literature to identify terms frequently used to describe delirium (Figure 1), we created an algorithm and a chart abstraction form (see Supporting Information, Appendix 1, in the online version of this article).[4] We tested these instruments in a preliminary chart review involving 30 patients. Disagreements were discussed with coauthors and resolved through consensus, resulting in some algorithm changes (eg, excluding a large number of patients who received only 1 dose of haloperidol postoperatively, because we hypothesized that this use could be a prophylactic measure).[5] Two investigators extracted the remaining charts independently. We used descriptive statistics and performed cross‐tabulations on the selected variables.

Figure 1

RESULTS

Of 12,817 geriatric hospitalizations during the study period, 1120 (9%) were treated with antipsychotics. We randomly selected 300 of these for extraction: 54% were male, and 67% were admitted to the medical service (Table 1). The inpatient mortality rate was 10% (30/300). The most frequent indication for AP use was delirium (83%, 249/300). Only 35% of delirious patients received a formal assessment with the Confusion Assessment Method (CAM). The most commonly used atypical antipsychotic was quetiapine (86%); 55% received more than 1 antipsychotic medication during hospitalization, and 48% (143/297) of patients were continued on APs at discharge (excluding 3 patients transferred to other acute care hospitals).

Approximately 45% (134/300) had documented or suspected dementia, and 30% (89/300) were physically restrained during the hospital stay. Consultations with geriatrics were obtained in 40% (120/300) of the cases and with psychiatry in 10% (29/300) of the cases. Neurology is rarely consulted for delirium in our institution; thus, we did not collect data on those referrals. Electrocardiography (ECG) (recommended for patients at high cardiac risk[6]) was performed in 88% (265/300) of patients prior to AP administration and 52% (157/300) after. The corrected QT interval exceeded 500 ms in 15% (41/265) of patients prior to AP administration and 25% (39/157) after. Although few patients (12%) were admitted from nursing facilities, 66% (199/300) were eventually discharged to skilled nursing facilities (SNFs) or rehabilitation facilities; most of these patients (117/199, 59%) received AP treatment, compared to 38% of patients discharged to home (26/68).

DISCUSSION

In a cohort of hospitalized elders, we found that 9% were treated with APs. Most received APs for perceived delirium; in‐hospital ECG monitoring was suboptimal. Half of the patients started on APs remained on them at discharge; those discharged to SNFs were more likely to receive ongoing AP treatment.

Our study is limited by its retrospective, single‐center design, a lack of inter‐rater reliability measurement (although our training process was designed to standardize extraction methods), and the infrequent use of formal CAM assessment. Additionally, we were unable to determine how frequently APs were initiated in the intensive care unit. Any retrospective study is limited by the difficulty of distinguishing delirium from the behavioral and psychiatric symptoms of dementia, but we identified delirium using standard terms described in previous literature.

Our study also has a number of important implications. Because of a reported association between the use of APs and risk of death in the postacute setting,[7] national provider organizations have called for a reduction in AP initiation in hospitalized elders.[2] However, this study indicates that APs continue to be prescribed for delirium, which may be attributed to the lack of behavioral modification options in most hospitals, such as acute care for elders (ACE) units and hospital elder life programs (HELP).[8, 9] Our findings suggest that this problem would be further amplified in hospitals that lack access to geriatrics expertise.

Without alternative behavioral options, patients are at risk for prolonged delirium, which is associated with significant suffering and subsequent risk of further cognitive impairment and death.[10] Although evidence for the efficacy of APs in the treatment of delirium is limited and inconclusive, no better pharmacologic options exist. Hospitals that wish to reduce use of APs should therefore consider investing in environmental interventions (eg, ACE units, HELP), which lower the incidence of delirium and could, in turn, decrease the prescription and continuation of antipsychotics.[8, 9]

Antipsychotic (AP) medications are often used in the hospitalized geriatric population for the treatment of delirium.[1] Because of adverse events associated with APs, efforts have been made to reduce their use in hospitalized elders,[2] but it is not clear if these recommendations have been widely adopted. We studied the use of APs in a cohort of hospitalized elders to better understand why APs are started and how often they are continued on discharge.

METHODS

We conducted a retrospective cohort study of patients aged 65 years or older admitted to a tertiary care hospital between October 1, 2012 and September 31, 2013. Using Stata's (StataCorp., College Station, TX) sample command,[3] we included a subset of randomly selected inpatients who received more than 1 dose of oral APs (determined using the electronic medication administration summary). We excluded patients admitted under observation status or to the psychiatric service, those who were on APs prior to admission, and those who only received prochloperazine for nausea. Using prior literature to identify terms frequently used to describe delirium (Figure 1), we created an algorithm and a chart abstraction form (see Supporting Information, Appendix 1, in the online version of this article).[4] We tested these instruments in a preliminary chart review involving 30 patients. Disagreements were discussed with coauthors and resolved through consensus, resulting in some algorithm changes (eg, excluding a large number of patients who received only 1 dose of haloperidol postoperatively, because we hypothesized that this use could be a prophylactic measure).[5] Two investigators extracted the remaining charts independently. We used descriptive statistics and performed cross‐tabulations on the selected variables.

Figure 1

RESULTS

Of 12,817 geriatric hospitalizations during the study period, 1120 (9%) were treated with antipsychotics. We randomly selected 300 of these for extraction: 54% were male, and 67% were admitted to the medical service (Table 1). The inpatient mortality rate was 10% (30/300). The most frequent indication for AP use was delirium (83%, 249/300). Only 35% of delirious patients received a formal assessment with the Confusion Assessment Method (CAM). The most commonly used atypical antipsychotic was quetiapine (86%); 55% received more than 1 antipsychotic medication during hospitalization, and 48% (143/297) of patients were continued on APs at discharge (excluding 3 patients transferred to other acute care hospitals).

Approximately 45% (134/300) had documented or suspected dementia, and 30% (89/300) were physically restrained during the hospital stay. Consultations with geriatrics were obtained in 40% (120/300) of the cases and with psychiatry in 10% (29/300) of the cases. Neurology is rarely consulted for delirium in our institution; thus, we did not collect data on those referrals. Electrocardiography (ECG) (recommended for patients at high cardiac risk[6]) was performed in 88% (265/300) of patients prior to AP administration and 52% (157/300) after. The corrected QT interval exceeded 500 ms in 15% (41/265) of patients prior to AP administration and 25% (39/157) after. Although few patients (12%) were admitted from nursing facilities, 66% (199/300) were eventually discharged to skilled nursing facilities (SNFs) or rehabilitation facilities; most of these patients (117/199, 59%) received AP treatment, compared to 38% of patients discharged to home (26/68).

DISCUSSION

In a cohort of hospitalized elders, we found that 9% were treated with APs. Most received APs for perceived delirium; in‐hospital ECG monitoring was suboptimal. Half of the patients started on APs remained on them at discharge; those discharged to SNFs were more likely to receive ongoing AP treatment.

Our study is limited by its retrospective, single‐center design, a lack of inter‐rater reliability measurement (although our training process was designed to standardize extraction methods), and the infrequent use of formal CAM assessment. Additionally, we were unable to determine how frequently APs were initiated in the intensive care unit. Any retrospective study is limited by the difficulty of distinguishing delirium from the behavioral and psychiatric symptoms of dementia, but we identified delirium using standard terms described in previous literature.

Our study also has a number of important implications. Because of a reported association between the use of APs and risk of death in the postacute setting,[7] national provider organizations have called for a reduction in AP initiation in hospitalized elders.[2] However, this study indicates that APs continue to be prescribed for delirium, which may be attributed to the lack of behavioral modification options in most hospitals, such as acute care for elders (ACE) units and hospital elder life programs (HELP).[8, 9] Our findings suggest that this problem would be further amplified in hospitals that lack access to geriatrics expertise.

Without alternative behavioral options, patients are at risk for prolonged delirium, which is associated with significant suffering and subsequent risk of further cognitive impairment and death.[10] Although evidence for the efficacy of APs in the treatment of delirium is limited and inconclusive, no better pharmacologic options exist. Hospitals that wish to reduce use of APs should therefore consider investing in environmental interventions (eg, ACE units, HELP), which lower the incidence of delirium and could, in turn, decrease the prescription and continuation of antipsychotics.[8, 9]

Proton pump inhibitors (PPIs) are commonly used to treat acid‐related disorders but are associated with an increased risk of pneumonia and Clostridium difficile‐associated diarrhea.[1, 2] Initiation of PPIs in hospitalized patients should therefore be limited to specific clinical situations, such as upper gastrointestinal bleeding or stress ulcer prophylaxis in the critically ill.[3] Prior studies suggest significant overuse of PPIs in hospitalized patients exists,[4, 5, 6, 7] but these were published before the widespread implementation of local and national quality improvement efforts targeted at reducing PPI use in medical inpatients (eg, Society of Hospital Medicine's Choosing Wisely list[8]). We aimed to determine the frequency of inappropriate use of PPIs in a contemporary cohort of hospitalized patients in a tertiary care academic medical center.

METHODS

We conducted a retrospective cohort study of 297 patients admitted to a tertiary care center hospitalist service comprised of teaching and nonteaching medical patients who were not critically ill, were admitted between January 1, 2012 and March 31, 2012, and received a PPI during their hospital stay. Three internists used American College of Gastroenterology and the American Society for Gastrointestinal Endoscopy and prior studies to develop criteria to identify appropriate and inappropriate PPI use (Table 1).[4, 5, 6, 7] Appropriate indications included gastrointestinal (GI) bleeding, esophagitis, gastritis, gastroesophageal reflux (GERD), and continuation of home PPI (abrupt discontinuation can trigger reflux symptoms).[9] We extracted the medical records of included patients, applying our prespecified criteria to determine whether use was appropriate. In patients in whom PPI was a continued home medication, we also extracted 2 years of data prior to the index date to determine if the medication was started during a prior hospital admission and, if so, whether this initiation was appropriate. We used descriptive statistics and [2] tests to compare patient characteristics and indications for PPI use.

RESULTS

Of 297 patients, the mean age was 64.4 years (standard deviation 16.3 years), most were white (69%), and 56% were women (Table 2). PPI use was appropriate in 231 (78%, 95% confidence interval: 72.6%‐82.4%) patients. Of these, a majority (172, 75%) of patients received a PPI because it was a continued home medication. Only 40 of the 172 patients had the medication started during a recent hospitalization, and in half of those cases (20) the PPI use was appropriate.

The second most common appropriate diagnosis was GERD (31%), followed by history of GI bleeding (19%) and treatment for esophagitis or gastritis (18%). Among the 66 patients receiving a PPI inappropriately, the majority of patients (56%) had no documented reason for PPI use, and only 11 patients (17%) were receiving PPI for stress ulcer prophylaxis (Figure 1). Five patients (8%) were treated prophylactically because of steroid or anticoagulant use. We observed no differences in age, gender, race, or reason for admission between the patients treated appropriately versus inappropriately.

Figure 1

DISCUSSION

In a contemporary cohort, chronic PPI use prior to admission was the most common reason PPIs were prescribed in the hospital. About 20% of hospitalized patients were started on a PPI for an inappropriate indication, the majority of whom lacked documentation concerning the reason for use. Among patients treated inappropriately, 36% were discharged on acid‐suppressive therapy.

The prior literature has reported a much higher percentages of unnecessary PPI use in hospitalized patients.[4, 5, 6, 7] Gupta et al. found that 70% of patients admitted to an internal medicine service received acid‐suppressive therapy, 73% of whom were treated unnecessarily.[5] Similarly, Nardino et al. found that 65% of acid‐suppressive therapy in hospitalized medical patients was not indicated.[4] If we had excluded patients on home PPIs from our study cohort, we would have found a higher rate of inappropriate use due to a smaller overall patient population. However, we chose to include these patients because they represented the vast majority of hospitalist‐prescribed PPIs. Notably, most of these prior prescriptions were not written during a recent hospital stay, indicating that the majority were initiated by outpatient physicians.

Our study is limited by its small sample size, single‐center design, and inability to determine the indications for outpatient PPI use. Still, it has important implications. Prior work has suggested that focusing efforts on PPI overuse may be premature in the absence of valid risk‐prediction models defining the patient populations that most benefit from PPI therapy.[10] Our work additionally suggests that hospital rates of inappropriate initiation may be relatively low, perhaps because hospitalist culture and practice have been affected by both local and national quality improvement efforts and by evidence dissemination.[8] Quality improvement efforts focused on reducing inpatient PPI use are likely to reveal diminishing returns, as admitting hospitalists are unlikely to abruptly discontinue PPIs prescribed in the outpatient setting.[9] Hospitalists should be encouraged to assess and document the need for PPIs during admission, hospitalization, and discharge processes. However, future efforts to reduce PPI overuse among hospitalized patients should predominately be focused on reducing inappropriate chronic PPI use in the outpatient setting.

Proton pump inhibitors (PPIs) are commonly used to treat acid‐related disorders but are associated with an increased risk of pneumonia and Clostridium difficile‐associated diarrhea.[1, 2] Initiation of PPIs in hospitalized patients should therefore be limited to specific clinical situations, such as upper gastrointestinal bleeding or stress ulcer prophylaxis in the critically ill.[3] Prior studies suggest significant overuse of PPIs in hospitalized patients exists,[4, 5, 6, 7] but these were published before the widespread implementation of local and national quality improvement efforts targeted at reducing PPI use in medical inpatients (eg, Society of Hospital Medicine's Choosing Wisely list[8]). We aimed to determine the frequency of inappropriate use of PPIs in a contemporary cohort of hospitalized patients in a tertiary care academic medical center.

METHODS

We conducted a retrospective cohort study of 297 patients admitted to a tertiary care center hospitalist service comprised of teaching and nonteaching medical patients who were not critically ill, were admitted between January 1, 2012 and March 31, 2012, and received a PPI during their hospital stay. Three internists used American College of Gastroenterology and the American Society for Gastrointestinal Endoscopy and prior studies to develop criteria to identify appropriate and inappropriate PPI use (Table 1).[4, 5, 6, 7] Appropriate indications included gastrointestinal (GI) bleeding, esophagitis, gastritis, gastroesophageal reflux (GERD), and continuation of home PPI (abrupt discontinuation can trigger reflux symptoms).[9] We extracted the medical records of included patients, applying our prespecified criteria to determine whether use was appropriate. In patients in whom PPI was a continued home medication, we also extracted 2 years of data prior to the index date to determine if the medication was started during a prior hospital admission and, if so, whether this initiation was appropriate. We used descriptive statistics and [2] tests to compare patient characteristics and indications for PPI use.

RESULTS

Of 297 patients, the mean age was 64.4 years (standard deviation 16.3 years), most were white (69%), and 56% were women (Table 2). PPI use was appropriate in 231 (78%, 95% confidence interval: 72.6%‐82.4%) patients. Of these, a majority (172, 75%) of patients received a PPI because it was a continued home medication. Only 40 of the 172 patients had the medication started during a recent hospitalization, and in half of those cases (20) the PPI use was appropriate.

The second most common appropriate diagnosis was GERD (31%), followed by history of GI bleeding (19%) and treatment for esophagitis or gastritis (18%). Among the 66 patients receiving a PPI inappropriately, the majority of patients (56%) had no documented reason for PPI use, and only 11 patients (17%) were receiving PPI for stress ulcer prophylaxis (Figure 1). Five patients (8%) were treated prophylactically because of steroid or anticoagulant use. We observed no differences in age, gender, race, or reason for admission between the patients treated appropriately versus inappropriately.

Figure 1

DISCUSSION

In a contemporary cohort, chronic PPI use prior to admission was the most common reason PPIs were prescribed in the hospital. About 20% of hospitalized patients were started on a PPI for an inappropriate indication, the majority of whom lacked documentation concerning the reason for use. Among patients treated inappropriately, 36% were discharged on acid‐suppressive therapy.

The prior literature has reported a much higher percentages of unnecessary PPI use in hospitalized patients.[4, 5, 6, 7] Gupta et al. found that 70% of patients admitted to an internal medicine service received acid‐suppressive therapy, 73% of whom were treated unnecessarily.[5] Similarly, Nardino et al. found that 65% of acid‐suppressive therapy in hospitalized medical patients was not indicated.[4] If we had excluded patients on home PPIs from our study cohort, we would have found a higher rate of inappropriate use due to a smaller overall patient population. However, we chose to include these patients because they represented the vast majority of hospitalist‐prescribed PPIs. Notably, most of these prior prescriptions were not written during a recent hospital stay, indicating that the majority were initiated by outpatient physicians.

Our study is limited by its small sample size, single‐center design, and inability to determine the indications for outpatient PPI use. Still, it has important implications. Prior work has suggested that focusing efforts on PPI overuse may be premature in the absence of valid risk‐prediction models defining the patient populations that most benefit from PPI therapy.[10] Our work additionally suggests that hospital rates of inappropriate initiation may be relatively low, perhaps because hospitalist culture and practice have been affected by both local and national quality improvement efforts and by evidence dissemination.[8] Quality improvement efforts focused on reducing inpatient PPI use are likely to reveal diminishing returns, as admitting hospitalists are unlikely to abruptly discontinue PPIs prescribed in the outpatient setting.[9] Hospitalists should be encouraged to assess and document the need for PPIs during admission, hospitalization, and discharge processes. However, future efforts to reduce PPI overuse among hospitalized patients should predominately be focused on reducing inappropriate chronic PPI use in the outpatient setting.

Proton pump inhibitors (PPIs) are commonly used to treat acid‐related disorders but are associated with an increased risk of pneumonia and Clostridium difficile‐associated diarrhea.[1, 2] Initiation of PPIs in hospitalized patients should therefore be limited to specific clinical situations, such as upper gastrointestinal bleeding or stress ulcer prophylaxis in the critically ill.[3] Prior studies suggest significant overuse of PPIs in hospitalized patients exists,[4, 5, 6, 7] but these were published before the widespread implementation of local and national quality improvement efforts targeted at reducing PPI use in medical inpatients (eg, Society of Hospital Medicine's Choosing Wisely list[8]). We aimed to determine the frequency of inappropriate use of PPIs in a contemporary cohort of hospitalized patients in a tertiary care academic medical center.

METHODS

We conducted a retrospective cohort study of 297 patients admitted to a tertiary care center hospitalist service comprised of teaching and nonteaching medical patients who were not critically ill, were admitted between January 1, 2012 and March 31, 2012, and received a PPI during their hospital stay. Three internists used American College of Gastroenterology and the American Society for Gastrointestinal Endoscopy and prior studies to develop criteria to identify appropriate and inappropriate PPI use (Table 1).[4, 5, 6, 7] Appropriate indications included gastrointestinal (GI) bleeding, esophagitis, gastritis, gastroesophageal reflux (GERD), and continuation of home PPI (abrupt discontinuation can trigger reflux symptoms).[9] We extracted the medical records of included patients, applying our prespecified criteria to determine whether use was appropriate. In patients in whom PPI was a continued home medication, we also extracted 2 years of data prior to the index date to determine if the medication was started during a prior hospital admission and, if so, whether this initiation was appropriate. We used descriptive statistics and [2] tests to compare patient characteristics and indications for PPI use.

RESULTS

Of 297 patients, the mean age was 64.4 years (standard deviation 16.3 years), most were white (69%), and 56% were women (Table 2). PPI use was appropriate in 231 (78%, 95% confidence interval: 72.6%‐82.4%) patients. Of these, a majority (172, 75%) of patients received a PPI because it was a continued home medication. Only 40 of the 172 patients had the medication started during a recent hospitalization, and in half of those cases (20) the PPI use was appropriate.

The second most common appropriate diagnosis was GERD (31%), followed by history of GI bleeding (19%) and treatment for esophagitis or gastritis (18%). Among the 66 patients receiving a PPI inappropriately, the majority of patients (56%) had no documented reason for PPI use, and only 11 patients (17%) were receiving PPI for stress ulcer prophylaxis (Figure 1). Five patients (8%) were treated prophylactically because of steroid or anticoagulant use. We observed no differences in age, gender, race, or reason for admission between the patients treated appropriately versus inappropriately.

Figure 1

DISCUSSION

In a contemporary cohort, chronic PPI use prior to admission was the most common reason PPIs were prescribed in the hospital. About 20% of hospitalized patients were started on a PPI for an inappropriate indication, the majority of whom lacked documentation concerning the reason for use. Among patients treated inappropriately, 36% were discharged on acid‐suppressive therapy.

The prior literature has reported a much higher percentages of unnecessary PPI use in hospitalized patients.[4, 5, 6, 7] Gupta et al. found that 70% of patients admitted to an internal medicine service received acid‐suppressive therapy, 73% of whom were treated unnecessarily.[5] Similarly, Nardino et al. found that 65% of acid‐suppressive therapy in hospitalized medical patients was not indicated.[4] If we had excluded patients on home PPIs from our study cohort, we would have found a higher rate of inappropriate use due to a smaller overall patient population. However, we chose to include these patients because they represented the vast majority of hospitalist‐prescribed PPIs. Notably, most of these prior prescriptions were not written during a recent hospital stay, indicating that the majority were initiated by outpatient physicians.

Our study is limited by its small sample size, single‐center design, and inability to determine the indications for outpatient PPI use. Still, it has important implications. Prior work has suggested that focusing efforts on PPI overuse may be premature in the absence of valid risk‐prediction models defining the patient populations that most benefit from PPI therapy.[10] Our work additionally suggests that hospital rates of inappropriate initiation may be relatively low, perhaps because hospitalist culture and practice have been affected by both local and national quality improvement efforts and by evidence dissemination.[8] Quality improvement efforts focused on reducing inpatient PPI use are likely to reveal diminishing returns, as admitting hospitalists are unlikely to abruptly discontinue PPIs prescribed in the outpatient setting.[9] Hospitalists should be encouraged to assess and document the need for PPIs during admission, hospitalization, and discharge processes. However, future efforts to reduce PPI overuse among hospitalized patients should predominately be focused on reducing inappropriate chronic PPI use in the outpatient setting.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.