The combination of decreasing hospital lengths of stay and increasing age and comorbidity of the United States population is a principal driver of the increased use of postacute care in the US.^1-3 Postacute care refers to care in long-term acute care hospitals, inpatient rehabilitation facilities, skilled nursing facilities (SNFs), and care provided by home health agencies after an acute hospitalization. In 2016, 43% of Medicare beneficiaries received postacute care after hospital discharge at the cost of $60 billion annually; nearly half of these received care in an SNF.⁴ Increasing recognition of the significant cost and poor outcomes of postacute care led to payment reforms, such as bundled payments, that incentivized less expensive forms of postacute care and improvements in outcomes.^5-9 Early evaluations suggested that hospitals are sensitive to these reforms and responded by significantly decreasing SNF utilization.^10,11 It remains unclear whether this was safe and effective.

In this context, increased attention to how hospital clinicians and hospitalized patients decide whether to use postacute care (and what form to use) is appropriate since the effect of payment reforms could negatively impact vulnerable populations of older adults without adequate protection.¹² Suboptimal decision-making can drive both overuse and inappropriate underuse of this expensive medical resource. Initial evidence suggests that patients and clinicians are poorly equipped to make high-quality decisions about postacute care, with significant deficits in both the decision-making process and content.^13-16 While these gaps are important to address, they may only be part of the problem. The fields of cognitive psychology and behavioral economics have revealed new insights into decision-making, demonstrating that people deviate from rational decision-making in predictable ways, termed decision heuristics, or cognitive biases.¹⁷ This growing field of research suggests heuristics or biases play important roles in decision-making and determining behavior, particularly in situations where there may be little information provided and the patient is stressed, tired, and ill—precisely like deciding on postacute care.¹⁸ However, it is currently unknown whether cognitive biases are at play when making hospital discharge decisions.

We sought to identify the most salient heuristics or cognitive biases patients may utilize when making decisions about postacute care at the end of their hospitalization and ways clinicians may contribute to these biases. The overall goal was to derive insights for improving postacute care decision-making.

Study Design

We conducted a secondary analysis on interviews with hospital and SNF clinicians as well as patients and their caregivers who were either leaving the hospital for an SNF or newly arrived in an SNF from the hospital to understand if cognitive biases were present and how they manifested themselves in a real-world clinical context.¹⁹ These interviews were part of a larger qualitative study that sought to understand how clinicians, patients, and their caregivers made decisions about postacute care, particularly related to SNFs.^13,14 This study represents the analysis of all our interviews, specifically examining decision-making bias. Participating sites, clinical roles, and both patient and caregiver characteristics (Table 1) in our cohort have been previously described.^13,14

Analysis

We used a team-based approach to framework analysis, which has been used in other decision-making studies¹⁴, including those measuring cognitive bias.²⁰ A limitation in cognitive bias research is the lack of a standardized list or categorization of cognitive biases. We reviewed prior systematic^17,21 and narrative reviews^18,22, as well as prior studies describing examples of cognitive biases playing a role in decision-making about therapy²⁰ to construct a list of possible cognitive biases to evaluate and narrow these a priori to potential biases relevant to the decision about postacute care based on our prior work (Table 2).

We applied this framework to analyze transcripts through an iterative process of deductive coding and reviewing across four reviewers (ML, RA, AL, CL) and a hospitalist physician with expertise leading qualitative studies (REB).

Intercoder consensus was built through team discussion by resolving points of disagreement.²³ Consistency of coding was regularly checked by having more than one investigator code individual manuscripts and comparing coding, and discrepancies were resolved through team discussion. We triangulated the data (shared our preliminary results) using a larger study team, including an expert in behavioral economics (SRG), physicians at study sites (EC, RA), and an anthropologist with expertise in qualitative methods (CL). We did this to ensure credibility (to what extent the findings are credible or believable) and confirmability of findings (ensuring the findings are based on participant narratives rather than researcher biases).

We reviewed a total of 105 interviews with 25 hospital clinicians, 20 SNF clinicians, 21 patients and 14 caregivers in the hospital, and 15 patients and 10 caregivers in the SNF setting (Table 1). We found authority bias/halo effect; default/status quo bias, anchoring bias, and framing was commonly present in decision-making about postacute care in a SNF, whereas there were few if any examples of ambiguity aversion, availability heuristic, confirmation bias, optimism bias, or false consensus effect (Table 2).

Authority Bias/Halo Effect

While most patients deferred to their inpatient teams when it came to decision-making, this effect seemed to differ across VA and non-VA settings. Veterans expressed a higher degree of potential authority bias regarding the VA as an institution, whereas older adults in non-VA settings saw physicians as the authority figure making decisions in their best interests.

Veterans expressed confidence in the VA regarding both whether to go to a SNF and where to go:

“The VA wouldn’t license [an SNF] if they didn’t have a good reputation for care, cleanliness, things of that nature” (Veteran, VA CLC)

“I just knew the VA would have my best interests at heart” (Veteran, VA CLC)

Their caregivers expressed similar confidence:

“I’m not gonna decide [on whether the patient they care for goes to postacute care], like I told you, that’s totally up to the VA. I have trust and faith in them…so wherever they send him, that’s where he’s going” (Caregiver, VA hospital)

In some cases, this perspective was closer to the halo effect: a positive experience with the care provider or the care team led the decision-makers to believe that their recommendations about postacute care would be similarly positive.

“I think we were very trusting in the sense that whatever happened the last time around, he survived it…they took care of him…he got back home, and he started his life again, you know, so why would we question what they’re telling us to do? (Caregiver, VA hospital)

In contrast to Veterans, non-Veteran patients seemed to experience authority bias when it came to the inpatient team.

“Well, I’d like to know more about the PTs [Physical Therapists] there, but I assume since they were recommended, they will be good.” (Patient, University hospital)

This perspective was especially apparent when it came to physicians:

“The level of trust that they [patients] put in their doctor is gonna outweigh what anyone else would say.” (Clinical liaison, SNF)

“[In response to a question about influences on the decision to go to rehab] I don’t…that’s not my decision to make, that’s the doctor’s decision.” (Patient, University hospital)

“They said so…[the doctor] said I needed to go to rehab, so I guess I do because it’s the doctor’s decision.” (Patient, University hospital)

Default/Status quo Bias

In a related way, patients and caregivers with exposure to a SNF seemed to default to the same SNF with which they had previous experience. This bias seems to be primarily related to knowing what to expect.

“He thinks it’s [a particular SNF] the right place for him now…he was there before and he knew, again, it was the right place for him to be” (Caregiver, VA hospital)

“It’s the only one I’ve ever been in…but they have a lot of activities; you have a lot of freedom, staff was good” (Patient, VA hospital)

“I’ve been [to this SNF] before and I kind of know what the program involves…so it was kind of like going home, not, going home is the wrong way to put it…I mean coming here is like something I know, you know, I didn’t need anybody to explain it to me.” (Patient, VA hospital)

“Anybody that’s been to [SNF], that would be their choice to go back to, and I guess I must’ve liked it that first time because I asked to go back again.” (Patient, University hospital)

Anchoring Bias

While anchoring bias was less frequent, it came up in two domains: first, related to costs of care, and second, related to facility characteristics. Costs came up most frequently for Veterans who preferred to move their care to the VA for cost reasons, which appeared in these cases to overshadow other considerations:

“I kept emphasizing that the VA could do all the same things at a lot more reasonable price. The whole purpose of having the VA is for the Veteran, so that…we can get the healthcare that we need at a more reasonable [sic] or a reasonable price.” (Veteran, CLC)

“I think the CLC [VA SNF] is going to take care of her probably the same way any other facility of its type would, unless she were in a private facility, but you know, that costs a lot more money.” (Caregiver, VA hospital)

Patients occasionally had striking responses to particular characteristics of SNFs, regardless of whether this was a central feature or related to their rehabilitation:

“The social worker comes and talks to me about the nursing home where cats are running around, you know, to infect my leg or spin their little cat hairs into my lungs and make my asthma worse…I’m going to have to beg the nurses or the aides or the family or somebody to clean the cat…” (Veteran, VA hospital)

Framing

Framing was the strongest theme among clinician interviews in our sample. Clinicians most frequently described the SNF as a place where patients could recover function (a positive frame), explaining risks (eg, rehospitalization) associated with alternative postacute care options besides the SNF in great detail.

“Aside from explaining the benefits of going and…having that 24-hour care, having the therapies provided to them [the patients], talking about them getting stronger, phrasing it in such a way that patients sometimes are more agreeable, like not calling it a skilled nursing facility, calling it a rehab you know, for them to get physically stronger so they can be the most independent that they can once they do go home, and also explaining … we think that this would be the best plan to prevent them from coming back to the hospital, so those are some of the things that we’ll mention to patients to try and educate them and get them to be agreeable for placement.” (Social worker, University hospital)

Clinicians avoided negative associations with “nursing home” (even though all SNFs are nursing homes) and tended to use more positive frames such as “rehabilitation facility.”

“Use the word rehab….we definitely use the word rehab, to get more therapy, to go home; it’s not a, we really emphasize it’s not a nursing home, it’s not to go to stay forever.” (Physical therapist, safety-net hospital)

Clinicians used a frame of “safety” when discussing the SNF and used a frame of “risk” when discussing alternative postacute care options such as returning home. We did not find examples of clinicians discussing similar risks in going to a SNF even for risks, such as falling, which exist in both settings.

“I’ve talked to them primarily on an avenue of safety because I think people want and they value independence, they value making sure they can get home, but you know, a lot of the times they understand safety is, it can be a concern and outlining that our goal is to make sure that they’re safe and they stay home, and I tend to broach the subject saying that our therapists believe that they might not be safe at home in the moment, but they have potential goals to be safe later on if we continue therapy. I really highlight safety being the major driver of our discussion.” (Physician, VA hospital)

In some cases, framing was so overt that other risk-mitigating options (eg, home healthcare) are not discussed.

“I definitely tend to explain the ideal first. I’m not going to bring up home care when we really think somebody should go to rehab, however, once people say I don’t want to do that, I’m not going, then that’s when I’m like OK, well, let’s talk to the doctors, but we can see about other supports in the home.” (Social worker, VA hospital)

In a large sample of patients and their caregivers, as well as multidisciplinary clinicians at three different hospitals and three SNFs, we found authority bias/halo effect and framing biases were most common and seemed most impactful. Default/status quo bias and anchoring bias were also present in decision-making about a SNF. The combination of authority bias/halo effect and framing biases could synergistically interact to augment the likelihood of patients accepting a SNF for postacute care. Patients who had been to a SNF before seemed more likely to choose the SNF they had experienced previously even if they had no other postacute care experiences, and could be highly influenced by isolated characteristics of that facility (such as the physical environment or cost of care).

It is important to mention that cognitive biases do not necessarily have a negative impact: indeed, as Kahneman and Tversky point out, these are useful heuristics from “fast” thinking that are often effective.²⁴ For example, clinicians may be trying to act in the best interests of the patient when framing the decision in terms of regaining function and averting loss of safety and independence. However, the evidence base regarding the outcomes of an SNF versus other postacute options is not robust, and this decision-making is complex. While this decision was most commonly framed in terms of rehabilitation and returning home, the fact that only about half of patients have returned to the community by 100 days⁴ was not discussed in any interview. In fact, initial evidence suggests replacing the SNF with home healthcare in patients with hip and knee arthroplasty may reduce costs without worsening clinical outcomes.⁶ However, across a broader population, SNFs significantly reduce 30-day readmissions when directly compared with home healthcare, but other clinical outcomes are similar.²⁵ This evidence suggests that the “right” postacute care option for an individual patient is not clear, highlighting a key role biases may play in decision-making. Further, the nebulous concept of “safety” could introduce potential disparities related to social determinants of health.¹² The observed inclination to accept an SNF with which the individual had prior experience may be influenced by the acceptability of this choice because of personal factors or prior research, even if it also represents a bias by limiting the consideration of current alternatives.

Our findings complement those of others in the literature which have also identified profound gaps in discharge decision-making among patients and clinicians,^13-16,26-31 though to our knowledge the role of cognitive biases in these decisions has not been explored. This study also addresses gaps in the cognitive bias literature, including the need for real-world data rather than hypothetical vignettes,¹⁷ and evaluation of treatment and management decisions rather than diagnoses, which have been more commonly studied.²¹

These findings have implications for both individual clinicians and healthcare institutions. In the immediate term, these findings may serve as a call to discharging clinicians to modulate language and “debias” their conversations with patients about care after discharge.^18,22 Shared decision-making requires an informed choice by patients based on their goals and values; framing a decision in a way that puts the clinician’s goals or values (eg, safety) ahead of patient values (eg, independence and autonomy) or limits disclosure (eg, a “rehab” is a nursing home) in the hope of influencing choice may be more consistent with framing bias and less with shared decision-making.¹⁴ Although controversy exists about the best way to “debias” oneself,³² self-awareness of bias is increasingly recognized across healthcare venues as critical to improving care for vulnerable populations.³³ The use of data rather than vignettes may be a useful debiasing strategy, although the limitations of currently available data (eg, capturing nursing home quality) are increasingly recognized.³⁴ From a policy and health system perspective, cognitive biases should be integrated into the development of decision aids to facilitate informed, shared, and high-quality decision-making that incorporates patient values, and perhaps “nudges” from behavioral economics to assist patients in choosing the right postdischarge care for them. Such nudges use principles of framing to influence care without restricting choice.³⁵ As the science informing best practice regarding postacute care improves, identifying the “right” postdischarge care may become easier and recommendations more evidence-based.³⁶

Strengths of the study include a large, diverse sample of patients, caregivers, and clinicians in both the hospital and SNF setting. Also, we used a team-based analysis with an experienced team and a deep knowledge of the data, including triangulation with clinicians to verify results. However, all hospitals and SNFs were located in a single metropolitan area, and responses may vary by region or population density. All three hospitals have housestaff teaching programs, and at the time of the interviews all three community SNFs were “five-star” facilities on the Nursing Home Compare website; results may be different at community hospitals or other SNFs. Hospitalists were the only physician group sampled in the hospital as they provide the majority of inpatient care to older adults; geriatricians, in particular, may have had different perspectives. Since we intended to explore whether cognitive biases were present overall, we did not evaluate whether cognitive biases differed by role or subgroup (by clinician type, patient, or caregiver), but this may be a promising area to explore in future work. Many cognitive biases have been described, and there are likely additional biases we did not identify. To confirm the generalizability of these findings, they should be studied in a larger, more generalizable sample of respondents in future work.

Cognitive biases play an important role in patient decision-making about postacute care, particularly regarding SNF care. As postacute care undergoes a transformation spurred by payment reforms, it is more important than ever to ensure that patients understand their choices at hospital discharge and can make a high-quality decision consistent with their goals.

The combination of decreasing hospital lengths of stay and increasing age and comorbidity of the United States population is a principal driver of the increased use of postacute care in the US.^1-3 Postacute care refers to care in long-term acute care hospitals, inpatient rehabilitation facilities, skilled nursing facilities (SNFs), and care provided by home health agencies after an acute hospitalization. In 2016, 43% of Medicare beneficiaries received postacute care after hospital discharge at the cost of $60 billion annually; nearly half of these received care in an SNF.⁴ Increasing recognition of the significant cost and poor outcomes of postacute care led to payment reforms, such as bundled payments, that incentivized less expensive forms of postacute care and improvements in outcomes.^5-9 Early evaluations suggested that hospitals are sensitive to these reforms and responded by significantly decreasing SNF utilization.^10,11 It remains unclear whether this was safe and effective.

In this context, increased attention to how hospital clinicians and hospitalized patients decide whether to use postacute care (and what form to use) is appropriate since the effect of payment reforms could negatively impact vulnerable populations of older adults without adequate protection.¹² Suboptimal decision-making can drive both overuse and inappropriate underuse of this expensive medical resource. Initial evidence suggests that patients and clinicians are poorly equipped to make high-quality decisions about postacute care, with significant deficits in both the decision-making process and content.^13-16 While these gaps are important to address, they may only be part of the problem. The fields of cognitive psychology and behavioral economics have revealed new insights into decision-making, demonstrating that people deviate from rational decision-making in predictable ways, termed decision heuristics, or cognitive biases.¹⁷ This growing field of research suggests heuristics or biases play important roles in decision-making and determining behavior, particularly in situations where there may be little information provided and the patient is stressed, tired, and ill—precisely like deciding on postacute care.¹⁸ However, it is currently unknown whether cognitive biases are at play when making hospital discharge decisions.

We sought to identify the most salient heuristics or cognitive biases patients may utilize when making decisions about postacute care at the end of their hospitalization and ways clinicians may contribute to these biases. The overall goal was to derive insights for improving postacute care decision-making.

Study Design

We conducted a secondary analysis on interviews with hospital and SNF clinicians as well as patients and their caregivers who were either leaving the hospital for an SNF or newly arrived in an SNF from the hospital to understand if cognitive biases were present and how they manifested themselves in a real-world clinical context.¹⁹ These interviews were part of a larger qualitative study that sought to understand how clinicians, patients, and their caregivers made decisions about postacute care, particularly related to SNFs.^13,14 This study represents the analysis of all our interviews, specifically examining decision-making bias. Participating sites, clinical roles, and both patient and caregiver characteristics (Table 1) in our cohort have been previously described.^13,14

Analysis

We used a team-based approach to framework analysis, which has been used in other decision-making studies¹⁴, including those measuring cognitive bias.²⁰ A limitation in cognitive bias research is the lack of a standardized list or categorization of cognitive biases. We reviewed prior systematic^17,21 and narrative reviews^18,22, as well as prior studies describing examples of cognitive biases playing a role in decision-making about therapy²⁰ to construct a list of possible cognitive biases to evaluate and narrow these a priori to potential biases relevant to the decision about postacute care based on our prior work (Table 2).

We applied this framework to analyze transcripts through an iterative process of deductive coding and reviewing across four reviewers (ML, RA, AL, CL) and a hospitalist physician with expertise leading qualitative studies (REB).

Intercoder consensus was built through team discussion by resolving points of disagreement.²³ Consistency of coding was regularly checked by having more than one investigator code individual manuscripts and comparing coding, and discrepancies were resolved through team discussion. We triangulated the data (shared our preliminary results) using a larger study team, including an expert in behavioral economics (SRG), physicians at study sites (EC, RA), and an anthropologist with expertise in qualitative methods (CL). We did this to ensure credibility (to what extent the findings are credible or believable) and confirmability of findings (ensuring the findings are based on participant narratives rather than researcher biases).

We reviewed a total of 105 interviews with 25 hospital clinicians, 20 SNF clinicians, 21 patients and 14 caregivers in the hospital, and 15 patients and 10 caregivers in the SNF setting (Table 1). We found authority bias/halo effect; default/status quo bias, anchoring bias, and framing was commonly present in decision-making about postacute care in a SNF, whereas there were few if any examples of ambiguity aversion, availability heuristic, confirmation bias, optimism bias, or false consensus effect (Table 2).

Authority Bias/Halo Effect

While most patients deferred to their inpatient teams when it came to decision-making, this effect seemed to differ across VA and non-VA settings. Veterans expressed a higher degree of potential authority bias regarding the VA as an institution, whereas older adults in non-VA settings saw physicians as the authority figure making decisions in their best interests.

Veterans expressed confidence in the VA regarding both whether to go to a SNF and where to go:

“The VA wouldn’t license [an SNF] if they didn’t have a good reputation for care, cleanliness, things of that nature” (Veteran, VA CLC)

“I just knew the VA would have my best interests at heart” (Veteran, VA CLC)

Their caregivers expressed similar confidence:

“I’m not gonna decide [on whether the patient they care for goes to postacute care], like I told you, that’s totally up to the VA. I have trust and faith in them…so wherever they send him, that’s where he’s going” (Caregiver, VA hospital)

In some cases, this perspective was closer to the halo effect: a positive experience with the care provider or the care team led the decision-makers to believe that their recommendations about postacute care would be similarly positive.

“I think we were very trusting in the sense that whatever happened the last time around, he survived it…they took care of him…he got back home, and he started his life again, you know, so why would we question what they’re telling us to do? (Caregiver, VA hospital)

In contrast to Veterans, non-Veteran patients seemed to experience authority bias when it came to the inpatient team.

“Well, I’d like to know more about the PTs [Physical Therapists] there, but I assume since they were recommended, they will be good.” (Patient, University hospital)

This perspective was especially apparent when it came to physicians:

“The level of trust that they [patients] put in their doctor is gonna outweigh what anyone else would say.” (Clinical liaison, SNF)

“[In response to a question about influences on the decision to go to rehab] I don’t…that’s not my decision to make, that’s the doctor’s decision.” (Patient, University hospital)

“They said so…[the doctor] said I needed to go to rehab, so I guess I do because it’s the doctor’s decision.” (Patient, University hospital)

Default/Status quo Bias

In a related way, patients and caregivers with exposure to a SNF seemed to default to the same SNF with which they had previous experience. This bias seems to be primarily related to knowing what to expect.

“He thinks it’s [a particular SNF] the right place for him now…he was there before and he knew, again, it was the right place for him to be” (Caregiver, VA hospital)

“It’s the only one I’ve ever been in…but they have a lot of activities; you have a lot of freedom, staff was good” (Patient, VA hospital)

“I’ve been [to this SNF] before and I kind of know what the program involves…so it was kind of like going home, not, going home is the wrong way to put it…I mean coming here is like something I know, you know, I didn’t need anybody to explain it to me.” (Patient, VA hospital)

“Anybody that’s been to [SNF], that would be their choice to go back to, and I guess I must’ve liked it that first time because I asked to go back again.” (Patient, University hospital)

Anchoring Bias

While anchoring bias was less frequent, it came up in two domains: first, related to costs of care, and second, related to facility characteristics. Costs came up most frequently for Veterans who preferred to move their care to the VA for cost reasons, which appeared in these cases to overshadow other considerations:

“I kept emphasizing that the VA could do all the same things at a lot more reasonable price. The whole purpose of having the VA is for the Veteran, so that…we can get the healthcare that we need at a more reasonable [sic] or a reasonable price.” (Veteran, CLC)

“I think the CLC [VA SNF] is going to take care of her probably the same way any other facility of its type would, unless she were in a private facility, but you know, that costs a lot more money.” (Caregiver, VA hospital)

Patients occasionally had striking responses to particular characteristics of SNFs, regardless of whether this was a central feature or related to their rehabilitation:

“The social worker comes and talks to me about the nursing home where cats are running around, you know, to infect my leg or spin their little cat hairs into my lungs and make my asthma worse…I’m going to have to beg the nurses or the aides or the family or somebody to clean the cat…” (Veteran, VA hospital)

Framing

Framing was the strongest theme among clinician interviews in our sample. Clinicians most frequently described the SNF as a place where patients could recover function (a positive frame), explaining risks (eg, rehospitalization) associated with alternative postacute care options besides the SNF in great detail.

“Aside from explaining the benefits of going and…having that 24-hour care, having the therapies provided to them [the patients], talking about them getting stronger, phrasing it in such a way that patients sometimes are more agreeable, like not calling it a skilled nursing facility, calling it a rehab you know, for them to get physically stronger so they can be the most independent that they can once they do go home, and also explaining … we think that this would be the best plan to prevent them from coming back to the hospital, so those are some of the things that we’ll mention to patients to try and educate them and get them to be agreeable for placement.” (Social worker, University hospital)

Clinicians avoided negative associations with “nursing home” (even though all SNFs are nursing homes) and tended to use more positive frames such as “rehabilitation facility.”

“Use the word rehab….we definitely use the word rehab, to get more therapy, to go home; it’s not a, we really emphasize it’s not a nursing home, it’s not to go to stay forever.” (Physical therapist, safety-net hospital)

Clinicians used a frame of “safety” when discussing the SNF and used a frame of “risk” when discussing alternative postacute care options such as returning home. We did not find examples of clinicians discussing similar risks in going to a SNF even for risks, such as falling, which exist in both settings.

“I’ve talked to them primarily on an avenue of safety because I think people want and they value independence, they value making sure they can get home, but you know, a lot of the times they understand safety is, it can be a concern and outlining that our goal is to make sure that they’re safe and they stay home, and I tend to broach the subject saying that our therapists believe that they might not be safe at home in the moment, but they have potential goals to be safe later on if we continue therapy. I really highlight safety being the major driver of our discussion.” (Physician, VA hospital)

In some cases, framing was so overt that other risk-mitigating options (eg, home healthcare) are not discussed.

“I definitely tend to explain the ideal first. I’m not going to bring up home care when we really think somebody should go to rehab, however, once people say I don’t want to do that, I’m not going, then that’s when I’m like OK, well, let’s talk to the doctors, but we can see about other supports in the home.” (Social worker, VA hospital)

In a large sample of patients and their caregivers, as well as multidisciplinary clinicians at three different hospitals and three SNFs, we found authority bias/halo effect and framing biases were most common and seemed most impactful. Default/status quo bias and anchoring bias were also present in decision-making about a SNF. The combination of authority bias/halo effect and framing biases could synergistically interact to augment the likelihood of patients accepting a SNF for postacute care. Patients who had been to a SNF before seemed more likely to choose the SNF they had experienced previously even if they had no other postacute care experiences, and could be highly influenced by isolated characteristics of that facility (such as the physical environment or cost of care).

It is important to mention that cognitive biases do not necessarily have a negative impact: indeed, as Kahneman and Tversky point out, these are useful heuristics from “fast” thinking that are often effective.²⁴ For example, clinicians may be trying to act in the best interests of the patient when framing the decision in terms of regaining function and averting loss of safety and independence. However, the evidence base regarding the outcomes of an SNF versus other postacute options is not robust, and this decision-making is complex. While this decision was most commonly framed in terms of rehabilitation and returning home, the fact that only about half of patients have returned to the community by 100 days⁴ was not discussed in any interview. In fact, initial evidence suggests replacing the SNF with home healthcare in patients with hip and knee arthroplasty may reduce costs without worsening clinical outcomes.⁶ However, across a broader population, SNFs significantly reduce 30-day readmissions when directly compared with home healthcare, but other clinical outcomes are similar.²⁵ This evidence suggests that the “right” postacute care option for an individual patient is not clear, highlighting a key role biases may play in decision-making. Further, the nebulous concept of “safety” could introduce potential disparities related to social determinants of health.¹² The observed inclination to accept an SNF with which the individual had prior experience may be influenced by the acceptability of this choice because of personal factors or prior research, even if it also represents a bias by limiting the consideration of current alternatives.

Our findings complement those of others in the literature which have also identified profound gaps in discharge decision-making among patients and clinicians,^13-16,26-31 though to our knowledge the role of cognitive biases in these decisions has not been explored. This study also addresses gaps in the cognitive bias literature, including the need for real-world data rather than hypothetical vignettes,¹⁷ and evaluation of treatment and management decisions rather than diagnoses, which have been more commonly studied.²¹

These findings have implications for both individual clinicians and healthcare institutions. In the immediate term, these findings may serve as a call to discharging clinicians to modulate language and “debias” their conversations with patients about care after discharge.^18,22 Shared decision-making requires an informed choice by patients based on their goals and values; framing a decision in a way that puts the clinician’s goals or values (eg, safety) ahead of patient values (eg, independence and autonomy) or limits disclosure (eg, a “rehab” is a nursing home) in the hope of influencing choice may be more consistent with framing bias and less with shared decision-making.¹⁴ Although controversy exists about the best way to “debias” oneself,³² self-awareness of bias is increasingly recognized across healthcare venues as critical to improving care for vulnerable populations.³³ The use of data rather than vignettes may be a useful debiasing strategy, although the limitations of currently available data (eg, capturing nursing home quality) are increasingly recognized.³⁴ From a policy and health system perspective, cognitive biases should be integrated into the development of decision aids to facilitate informed, shared, and high-quality decision-making that incorporates patient values, and perhaps “nudges” from behavioral economics to assist patients in choosing the right postdischarge care for them. Such nudges use principles of framing to influence care without restricting choice.³⁵ As the science informing best practice regarding postacute care improves, identifying the “right” postdischarge care may become easier and recommendations more evidence-based.³⁶

Strengths of the study include a large, diverse sample of patients, caregivers, and clinicians in both the hospital and SNF setting. Also, we used a team-based analysis with an experienced team and a deep knowledge of the data, including triangulation with clinicians to verify results. However, all hospitals and SNFs were located in a single metropolitan area, and responses may vary by region or population density. All three hospitals have housestaff teaching programs, and at the time of the interviews all three community SNFs were “five-star” facilities on the Nursing Home Compare website; results may be different at community hospitals or other SNFs. Hospitalists were the only physician group sampled in the hospital as they provide the majority of inpatient care to older adults; geriatricians, in particular, may have had different perspectives. Since we intended to explore whether cognitive biases were present overall, we did not evaluate whether cognitive biases differed by role or subgroup (by clinician type, patient, or caregiver), but this may be a promising area to explore in future work. Many cognitive biases have been described, and there are likely additional biases we did not identify. To confirm the generalizability of these findings, they should be studied in a larger, more generalizable sample of respondents in future work.

Cognitive biases play an important role in patient decision-making about postacute care, particularly regarding SNF care. As postacute care undergoes a transformation spurred by payment reforms, it is more important than ever to ensure that patients understand their choices at hospital discharge and can make a high-quality decision consistent with their goals.

The combination of decreasing hospital lengths of stay and increasing age and comorbidity of the United States population is a principal driver of the increased use of postacute care in the US.^1-3 Postacute care refers to care in long-term acute care hospitals, inpatient rehabilitation facilities, skilled nursing facilities (SNFs), and care provided by home health agencies after an acute hospitalization. In 2016, 43% of Medicare beneficiaries received postacute care after hospital discharge at the cost of $60 billion annually; nearly half of these received care in an SNF.⁴ Increasing recognition of the significant cost and poor outcomes of postacute care led to payment reforms, such as bundled payments, that incentivized less expensive forms of postacute care and improvements in outcomes.^5-9 Early evaluations suggested that hospitals are sensitive to these reforms and responded by significantly decreasing SNF utilization.^10,11 It remains unclear whether this was safe and effective.

In this context, increased attention to how hospital clinicians and hospitalized patients decide whether to use postacute care (and what form to use) is appropriate since the effect of payment reforms could negatively impact vulnerable populations of older adults without adequate protection.¹² Suboptimal decision-making can drive both overuse and inappropriate underuse of this expensive medical resource. Initial evidence suggests that patients and clinicians are poorly equipped to make high-quality decisions about postacute care, with significant deficits in both the decision-making process and content.^13-16 While these gaps are important to address, they may only be part of the problem. The fields of cognitive psychology and behavioral economics have revealed new insights into decision-making, demonstrating that people deviate from rational decision-making in predictable ways, termed decision heuristics, or cognitive biases.¹⁷ This growing field of research suggests heuristics or biases play important roles in decision-making and determining behavior, particularly in situations where there may be little information provided and the patient is stressed, tired, and ill—precisely like deciding on postacute care.¹⁸ However, it is currently unknown whether cognitive biases are at play when making hospital discharge decisions.

We sought to identify the most salient heuristics or cognitive biases patients may utilize when making decisions about postacute care at the end of their hospitalization and ways clinicians may contribute to these biases. The overall goal was to derive insights for improving postacute care decision-making.

Study Design

We conducted a secondary analysis on interviews with hospital and SNF clinicians as well as patients and their caregivers who were either leaving the hospital for an SNF or newly arrived in an SNF from the hospital to understand if cognitive biases were present and how they manifested themselves in a real-world clinical context.¹⁹ These interviews were part of a larger qualitative study that sought to understand how clinicians, patients, and their caregivers made decisions about postacute care, particularly related to SNFs.^13,14 This study represents the analysis of all our interviews, specifically examining decision-making bias. Participating sites, clinical roles, and both patient and caregiver characteristics (Table 1) in our cohort have been previously described.^13,14

Analysis

We used a team-based approach to framework analysis, which has been used in other decision-making studies¹⁴, including those measuring cognitive bias.²⁰ A limitation in cognitive bias research is the lack of a standardized list or categorization of cognitive biases. We reviewed prior systematic^17,21 and narrative reviews^18,22, as well as prior studies describing examples of cognitive biases playing a role in decision-making about therapy²⁰ to construct a list of possible cognitive biases to evaluate and narrow these a priori to potential biases relevant to the decision about postacute care based on our prior work (Table 2).

We applied this framework to analyze transcripts through an iterative process of deductive coding and reviewing across four reviewers (ML, RA, AL, CL) and a hospitalist physician with expertise leading qualitative studies (REB).

Intercoder consensus was built through team discussion by resolving points of disagreement.²³ Consistency of coding was regularly checked by having more than one investigator code individual manuscripts and comparing coding, and discrepancies were resolved through team discussion. We triangulated the data (shared our preliminary results) using a larger study team, including an expert in behavioral economics (SRG), physicians at study sites (EC, RA), and an anthropologist with expertise in qualitative methods (CL). We did this to ensure credibility (to what extent the findings are credible or believable) and confirmability of findings (ensuring the findings are based on participant narratives rather than researcher biases).

We reviewed a total of 105 interviews with 25 hospital clinicians, 20 SNF clinicians, 21 patients and 14 caregivers in the hospital, and 15 patients and 10 caregivers in the SNF setting (Table 1). We found authority bias/halo effect; default/status quo bias, anchoring bias, and framing was commonly present in decision-making about postacute care in a SNF, whereas there were few if any examples of ambiguity aversion, availability heuristic, confirmation bias, optimism bias, or false consensus effect (Table 2).

Authority Bias/Halo Effect

While most patients deferred to their inpatient teams when it came to decision-making, this effect seemed to differ across VA and non-VA settings. Veterans expressed a higher degree of potential authority bias regarding the VA as an institution, whereas older adults in non-VA settings saw physicians as the authority figure making decisions in their best interests.

Veterans expressed confidence in the VA regarding both whether to go to a SNF and where to go:

“The VA wouldn’t license [an SNF] if they didn’t have a good reputation for care, cleanliness, things of that nature” (Veteran, VA CLC)

“I just knew the VA would have my best interests at heart” (Veteran, VA CLC)

Their caregivers expressed similar confidence:

“I’m not gonna decide [on whether the patient they care for goes to postacute care], like I told you, that’s totally up to the VA. I have trust and faith in them…so wherever they send him, that’s where he’s going” (Caregiver, VA hospital)

In some cases, this perspective was closer to the halo effect: a positive experience with the care provider or the care team led the decision-makers to believe that their recommendations about postacute care would be similarly positive.

“I think we were very trusting in the sense that whatever happened the last time around, he survived it…they took care of him…he got back home, and he started his life again, you know, so why would we question what they’re telling us to do? (Caregiver, VA hospital)

In contrast to Veterans, non-Veteran patients seemed to experience authority bias when it came to the inpatient team.

“Well, I’d like to know more about the PTs [Physical Therapists] there, but I assume since they were recommended, they will be good.” (Patient, University hospital)

This perspective was especially apparent when it came to physicians:

“The level of trust that they [patients] put in their doctor is gonna outweigh what anyone else would say.” (Clinical liaison, SNF)

“[In response to a question about influences on the decision to go to rehab] I don’t…that’s not my decision to make, that’s the doctor’s decision.” (Patient, University hospital)

“They said so…[the doctor] said I needed to go to rehab, so I guess I do because it’s the doctor’s decision.” (Patient, University hospital)

Default/Status quo Bias

In a related way, patients and caregivers with exposure to a SNF seemed to default to the same SNF with which they had previous experience. This bias seems to be primarily related to knowing what to expect.

“He thinks it’s [a particular SNF] the right place for him now…he was there before and he knew, again, it was the right place for him to be” (Caregiver, VA hospital)

“It’s the only one I’ve ever been in…but they have a lot of activities; you have a lot of freedom, staff was good” (Patient, VA hospital)

“I’ve been [to this SNF] before and I kind of know what the program involves…so it was kind of like going home, not, going home is the wrong way to put it…I mean coming here is like something I know, you know, I didn’t need anybody to explain it to me.” (Patient, VA hospital)

“Anybody that’s been to [SNF], that would be their choice to go back to, and I guess I must’ve liked it that first time because I asked to go back again.” (Patient, University hospital)

Anchoring Bias

While anchoring bias was less frequent, it came up in two domains: first, related to costs of care, and second, related to facility characteristics. Costs came up most frequently for Veterans who preferred to move their care to the VA for cost reasons, which appeared in these cases to overshadow other considerations:

“I kept emphasizing that the VA could do all the same things at a lot more reasonable price. The whole purpose of having the VA is for the Veteran, so that…we can get the healthcare that we need at a more reasonable [sic] or a reasonable price.” (Veteran, CLC)

“I think the CLC [VA SNF] is going to take care of her probably the same way any other facility of its type would, unless she were in a private facility, but you know, that costs a lot more money.” (Caregiver, VA hospital)

Patients occasionally had striking responses to particular characteristics of SNFs, regardless of whether this was a central feature or related to their rehabilitation:

“The social worker comes and talks to me about the nursing home where cats are running around, you know, to infect my leg or spin their little cat hairs into my lungs and make my asthma worse…I’m going to have to beg the nurses or the aides or the family or somebody to clean the cat…” (Veteran, VA hospital)

Framing

Framing was the strongest theme among clinician interviews in our sample. Clinicians most frequently described the SNF as a place where patients could recover function (a positive frame), explaining risks (eg, rehospitalization) associated with alternative postacute care options besides the SNF in great detail.

“Aside from explaining the benefits of going and…having that 24-hour care, having the therapies provided to them [the patients], talking about them getting stronger, phrasing it in such a way that patients sometimes are more agreeable, like not calling it a skilled nursing facility, calling it a rehab you know, for them to get physically stronger so they can be the most independent that they can once they do go home, and also explaining … we think that this would be the best plan to prevent them from coming back to the hospital, so those are some of the things that we’ll mention to patients to try and educate them and get them to be agreeable for placement.” (Social worker, University hospital)

Clinicians avoided negative associations with “nursing home” (even though all SNFs are nursing homes) and tended to use more positive frames such as “rehabilitation facility.”

“Use the word rehab….we definitely use the word rehab, to get more therapy, to go home; it’s not a, we really emphasize it’s not a nursing home, it’s not to go to stay forever.” (Physical therapist, safety-net hospital)

Clinicians used a frame of “safety” when discussing the SNF and used a frame of “risk” when discussing alternative postacute care options such as returning home. We did not find examples of clinicians discussing similar risks in going to a SNF even for risks, such as falling, which exist in both settings.

“I’ve talked to them primarily on an avenue of safety because I think people want and they value independence, they value making sure they can get home, but you know, a lot of the times they understand safety is, it can be a concern and outlining that our goal is to make sure that they’re safe and they stay home, and I tend to broach the subject saying that our therapists believe that they might not be safe at home in the moment, but they have potential goals to be safe later on if we continue therapy. I really highlight safety being the major driver of our discussion.” (Physician, VA hospital)

In some cases, framing was so overt that other risk-mitigating options (eg, home healthcare) are not discussed.

“I definitely tend to explain the ideal first. I’m not going to bring up home care when we really think somebody should go to rehab, however, once people say I don’t want to do that, I’m not going, then that’s when I’m like OK, well, let’s talk to the doctors, but we can see about other supports in the home.” (Social worker, VA hospital)

In a large sample of patients and their caregivers, as well as multidisciplinary clinicians at three different hospitals and three SNFs, we found authority bias/halo effect and framing biases were most common and seemed most impactful. Default/status quo bias and anchoring bias were also present in decision-making about a SNF. The combination of authority bias/halo effect and framing biases could synergistically interact to augment the likelihood of patients accepting a SNF for postacute care. Patients who had been to a SNF before seemed more likely to choose the SNF they had experienced previously even if they had no other postacute care experiences, and could be highly influenced by isolated characteristics of that facility (such as the physical environment or cost of care).

It is important to mention that cognitive biases do not necessarily have a negative impact: indeed, as Kahneman and Tversky point out, these are useful heuristics from “fast” thinking that are often effective.²⁴ For example, clinicians may be trying to act in the best interests of the patient when framing the decision in terms of regaining function and averting loss of safety and independence. However, the evidence base regarding the outcomes of an SNF versus other postacute options is not robust, and this decision-making is complex. While this decision was most commonly framed in terms of rehabilitation and returning home, the fact that only about half of patients have returned to the community by 100 days⁴ was not discussed in any interview. In fact, initial evidence suggests replacing the SNF with home healthcare in patients with hip and knee arthroplasty may reduce costs without worsening clinical outcomes.⁶ However, across a broader population, SNFs significantly reduce 30-day readmissions when directly compared with home healthcare, but other clinical outcomes are similar.²⁵ This evidence suggests that the “right” postacute care option for an individual patient is not clear, highlighting a key role biases may play in decision-making. Further, the nebulous concept of “safety” could introduce potential disparities related to social determinants of health.¹² The observed inclination to accept an SNF with which the individual had prior experience may be influenced by the acceptability of this choice because of personal factors or prior research, even if it also represents a bias by limiting the consideration of current alternatives.

Our findings complement those of others in the literature which have also identified profound gaps in discharge decision-making among patients and clinicians,^13-16,26-31 though to our knowledge the role of cognitive biases in these decisions has not been explored. This study also addresses gaps in the cognitive bias literature, including the need for real-world data rather than hypothetical vignettes,¹⁷ and evaluation of treatment and management decisions rather than diagnoses, which have been more commonly studied.²¹

These findings have implications for both individual clinicians and healthcare institutions. In the immediate term, these findings may serve as a call to discharging clinicians to modulate language and “debias” their conversations with patients about care after discharge.^18,22 Shared decision-making requires an informed choice by patients based on their goals and values; framing a decision in a way that puts the clinician’s goals or values (eg, safety) ahead of patient values (eg, independence and autonomy) or limits disclosure (eg, a “rehab” is a nursing home) in the hope of influencing choice may be more consistent with framing bias and less with shared decision-making.¹⁴ Although controversy exists about the best way to “debias” oneself,³² self-awareness of bias is increasingly recognized across healthcare venues as critical to improving care for vulnerable populations.³³ The use of data rather than vignettes may be a useful debiasing strategy, although the limitations of currently available data (eg, capturing nursing home quality) are increasingly recognized.³⁴ From a policy and health system perspective, cognitive biases should be integrated into the development of decision aids to facilitate informed, shared, and high-quality decision-making that incorporates patient values, and perhaps “nudges” from behavioral economics to assist patients in choosing the right postdischarge care for them. Such nudges use principles of framing to influence care without restricting choice.³⁵ As the science informing best practice regarding postacute care improves, identifying the “right” postdischarge care may become easier and recommendations more evidence-based.³⁶

Strengths of the study include a large, diverse sample of patients, caregivers, and clinicians in both the hospital and SNF setting. Also, we used a team-based analysis with an experienced team and a deep knowledge of the data, including triangulation with clinicians to verify results. However, all hospitals and SNFs were located in a single metropolitan area, and responses may vary by region or population density. All three hospitals have housestaff teaching programs, and at the time of the interviews all three community SNFs were “five-star” facilities on the Nursing Home Compare website; results may be different at community hospitals or other SNFs. Hospitalists were the only physician group sampled in the hospital as they provide the majority of inpatient care to older adults; geriatricians, in particular, may have had different perspectives. Since we intended to explore whether cognitive biases were present overall, we did not evaluate whether cognitive biases differed by role or subgroup (by clinician type, patient, or caregiver), but this may be a promising area to explore in future work. Many cognitive biases have been described, and there are likely additional biases we did not identify. To confirm the generalizability of these findings, they should be studied in a larger, more generalizable sample of respondents in future work.

Cognitive biases play an important role in patient decision-making about postacute care, particularly regarding SNF care. As postacute care undergoes a transformation spurred by payment reforms, it is more important than ever to ensure that patients understand their choices at hospital discharge and can make a high-quality decision consistent with their goals.

Pediatric acute pancreatitis is being diagnosed more commonly, affecting approximately one per 10,000 children annually with an estimated inpatient cost burden of $200 million per year.^1,2 Common causes of pediatric acute pancreatitis include systemic illness, biliary disease, trauma, and medications; 13%-34% of cases are idiopathic.¹ Currently, substantial variation exists in the clinical management of this condition.^3,4 Hospitalists should familiarize themselves with the current literature, including the recent practice guideline by the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN).²

(Evidence quality: not graded, recommendation by expert consensus)

Recommendation 1. Diagnosis of acute pancreatitis in pediatric patients requires at least two of the following symptoms: abdominal pain compatible with acute pancreatitis, serum amylase and/or lipase values >3 times the upper limits of normal, and imaging findings consistent with acute pancreatitis.The most common symptoms of acute pancreatitis in children are epigastric or diffuse abdominal pain, vomiting, and irritability. Presentation varies by age, and diagnosis requires a high index of suspicion. Significant elevations in amylase and lipase levels are typically detected early in the disease course. The guideline does not specify a preferred serum biomarker in the diagnosis of pancreatitis but notes that lipase is more sensitive and specific than amylase, rises within 6 hours of symptoms, and stays elevated longer. Amylase levels rise faster but often normalize by 24 hours of symptom onset. Amylase and lipase can originate from extrapancreatic sources and may be elevated during acute illness in the absence of pancreatitis.

Laboratory testing to investigate the etiology of acute pancreatitis should include hepatic enzymes, bilirubin, triglyceride, and calcium levels. Although not typically necessary for diagnosis, imaging may demonstrate pancreatic edema or peripancreatic fluid, confirm disease complications, and identify obstructive causes. Transabdominal ultrasonography is indicated if biliary pancreatitis is suspected. Contrast-enhanced computed tomography should be considered for patients with severe presentation or deteriorating condition. Magnetic resonance cholangiopancreatography is useful in detecting pancreaticobiliary abnormalities.

Recommendation 2. Children with acute pancreatitis should be initially resuscitated with crystalloids, either with lactated Ringer’s or normal saline in the acute setting. These children should be provided 1.5-2 times maintenance intravenous fluids with monitoring of urine output over the next 24-48 hours.

Fluid resuscitation and maintenance are the current mainstays of therapy for pancreatitis. Prompt fluid administration corrects hypovolemia and may prevent potential complications. Early, aggressive fluid replacement in adults reduces the incidence of systemic inflammatory response syndrome and organ failure. Limited pediatric studies support correction of hypovolemia and/or circulatory compromise using 10-20 ml/kg boluses of isotonic crystalloid fluid. Although the literature is sparse regarding the rate of continued fluid replacement, the committee recommends patients receive 1.5-2 times maintenance intravenous fluid (IVF) with normal saline plus 5% dextrose for the first 24-48 hours. The rate of IVF administration should be adjusted based on volume status and urine output. IVF should be discontinued once the patient is able to maintain adequate hydration enterally. Cardiac, renal, and pulmonary complications of pancreatitis often present within the first 48 hours of illness and should prompt close monitoring with assessment of vital signs every four hours. The committee recommends monitoring serum electrolytes and renal function in the first 48 hours but does not offer guidance regarding the frequency of laboratory testing or the value of trending serum biomarkers.

Recommendation 3. Except in the presence of direct contraindications to use the gut, children with mild acute pancreatitis may benefit from early (within 48-72 hours of presentation) oral and enteral nutrition to decrease the length of stay (LOS) and the risk of organ dysfunction.

Adult studies suggest early enteral nutrition decreases complications and reduces LOS. Initiating enteral nutrition within 48 hours in children may have similar benefits. Several small pediatric studies have demonstrated a reduced LOS with early enteral feeds without an increase in complications. In a retrospective single-center study, children who were fed within the first 48 hours and received 1.5-2 times maintenance IVF had shorter LOS, less frequent intensive care admissions, and reduced severity of illness compared with those who were kept nil per os for the first 48 hours.⁵ Nasogastric or nasojejunal feeds may be initiated if a patient is unable to tolerate oral feeding. Parenteral nutrition should be reserved for children in whom enteral nutrition cannot be initiated within five to seven days.

Recommendation 4. Intravenous morphine or other opioids should be used for acute pancreatitis pain not responding to acetaminophen or nonsteroidal antiinflammatory drugs (NSAIDs).

Abdominal pain is the most common presenting symptom of pancreatitis, and pain control is an essential component of supportive care. There are no randomized trials identifying an optimal pain management regimen. The committee recommends the use of opioids for pain not controlled with acetaminophen and NSAIDs. Refractory pain may necessitate consultation with an acute pain specialist.

Recommendation 5. Routine use of prophylactic antibiotics, protease inhibitors, antioxidants, and probiotics is not recommended in acute pancreatitis.

Adult literature does not support routine use of antibiotics in acute pancreatitis, but their use may be beneficial in severe or recalcitrant cases. Pediatric literature neither confirms nor refutes this finding. The guideline does not recommend the use of antibiotics without signs of infection. Limited adult studies have shown protease inhibitors, antioxidants, and probiotics to be beneficial; however, no pediatric data support their use.

This guideline also discusses interventional and surgical procedures. Of note, biliary tract disease may necessitate endoscopic retrograde cholangiopancreatography or cholecystectomy. Such procedures should be considered in conjunction with subspecialty input.²

Methods in Preparing Guideline

The guideline development committee, funded by the NASPGHAN and the National Institutes of Diabetes and Digestive and Kidney Diseases, was composed of members of the NASPGHAN Pancreas Committee and included gastroenterologists from multiple sites.² Topics were selected via group discussion, and Medline searches included both adult and pediatric literature. Preliminary recommendations were presented at the 2016 World Congress of Pediatric Gastroenterology, Hepatology and Nutrition. Following revision, the 24 authors voted on each recommendation using a five-point Likert scale. A recommendation passed if 75% of the participants either agreed or strongly agreed with it. The authors reported no conflicts of interest.

Although the literature review was comprehensive, it lacked prospective pediatric studies and many of the recommendations were derived from adult research. The committee originally intended to grade the quality of evidence; however, the pediatric specific literature was underpowered and retrospective. Therefore, the committee opted to use consensus voting. The authors note that had the group used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system, it would have returned grades of “low” or “very low” quality evidence.² The Hungarian Pancreatic Study Group and the European Pancreatic Club published a consensus guideline on the management of pediatric acute pancreatitis shortly after the NASPGHAN guideline, which offers similar conclusions.^2,6 The strength and generalizability of the NASPGHAN guideline are limited by its overreliance on adult literature, expert consensus, and small, retrospective pediatric studies to guide care.

This guideline highlights the need for pediatric research to guide the management of acute pancreatitis. The etiologies of pancreatitis in children are distinct from adults, where alcohol abuse and biliary disease are significant contributors.¹ Furthermore, age and environmental factors influence the presentation and clinical course.¹ Robust, prospective studies are needed to better understand the treatment outcomes of pediatric pancreatitis. Areas of further research include pediatric pancreatic severity scoring, ideal fluid composition and administration rate, enteral feed timing, optimal pain control, laboratory monitoring frequency, and adjuvant therapies.

Disclosures

Dr. Wall has nothing to disclose.

Pediatric acute pancreatitis is being diagnosed more commonly, affecting approximately one per 10,000 children annually with an estimated inpatient cost burden of $200 million per year.^1,2 Common causes of pediatric acute pancreatitis include systemic illness, biliary disease, trauma, and medications; 13%-34% of cases are idiopathic.¹ Currently, substantial variation exists in the clinical management of this condition.^3,4 Hospitalists should familiarize themselves with the current literature, including the recent practice guideline by the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN).²

(Evidence quality: not graded, recommendation by expert consensus)

Recommendation 1. Diagnosis of acute pancreatitis in pediatric patients requires at least two of the following symptoms: abdominal pain compatible with acute pancreatitis, serum amylase and/or lipase values >3 times the upper limits of normal, and imaging findings consistent with acute pancreatitis.The most common symptoms of acute pancreatitis in children are epigastric or diffuse abdominal pain, vomiting, and irritability. Presentation varies by age, and diagnosis requires a high index of suspicion. Significant elevations in amylase and lipase levels are typically detected early in the disease course. The guideline does not specify a preferred serum biomarker in the diagnosis of pancreatitis but notes that lipase is more sensitive and specific than amylase, rises within 6 hours of symptoms, and stays elevated longer. Amylase levels rise faster but often normalize by 24 hours of symptom onset. Amylase and lipase can originate from extrapancreatic sources and may be elevated during acute illness in the absence of pancreatitis.

Laboratory testing to investigate the etiology of acute pancreatitis should include hepatic enzymes, bilirubin, triglyceride, and calcium levels. Although not typically necessary for diagnosis, imaging may demonstrate pancreatic edema or peripancreatic fluid, confirm disease complications, and identify obstructive causes. Transabdominal ultrasonography is indicated if biliary pancreatitis is suspected. Contrast-enhanced computed tomography should be considered for patients with severe presentation or deteriorating condition. Magnetic resonance cholangiopancreatography is useful in detecting pancreaticobiliary abnormalities.

Recommendation 2. Children with acute pancreatitis should be initially resuscitated with crystalloids, either with lactated Ringer’s or normal saline in the acute setting. These children should be provided 1.5-2 times maintenance intravenous fluids with monitoring of urine output over the next 24-48 hours.

Fluid resuscitation and maintenance are the current mainstays of therapy for pancreatitis. Prompt fluid administration corrects hypovolemia and may prevent potential complications. Early, aggressive fluid replacement in adults reduces the incidence of systemic inflammatory response syndrome and organ failure. Limited pediatric studies support correction of hypovolemia and/or circulatory compromise using 10-20 ml/kg boluses of isotonic crystalloid fluid. Although the literature is sparse regarding the rate of continued fluid replacement, the committee recommends patients receive 1.5-2 times maintenance intravenous fluid (IVF) with normal saline plus 5% dextrose for the first 24-48 hours. The rate of IVF administration should be adjusted based on volume status and urine output. IVF should be discontinued once the patient is able to maintain adequate hydration enterally. Cardiac, renal, and pulmonary complications of pancreatitis often present within the first 48 hours of illness and should prompt close monitoring with assessment of vital signs every four hours. The committee recommends monitoring serum electrolytes and renal function in the first 48 hours but does not offer guidance regarding the frequency of laboratory testing or the value of trending serum biomarkers.

Recommendation 3. Except in the presence of direct contraindications to use the gut, children with mild acute pancreatitis may benefit from early (within 48-72 hours of presentation) oral and enteral nutrition to decrease the length of stay (LOS) and the risk of organ dysfunction.

Adult studies suggest early enteral nutrition decreases complications and reduces LOS. Initiating enteral nutrition within 48 hours in children may have similar benefits. Several small pediatric studies have demonstrated a reduced LOS with early enteral feeds without an increase in complications. In a retrospective single-center study, children who were fed within the first 48 hours and received 1.5-2 times maintenance IVF had shorter LOS, less frequent intensive care admissions, and reduced severity of illness compared with those who were kept nil per os for the first 48 hours.⁵ Nasogastric or nasojejunal feeds may be initiated if a patient is unable to tolerate oral feeding. Parenteral nutrition should be reserved for children in whom enteral nutrition cannot be initiated within five to seven days.

Recommendation 4. Intravenous morphine or other opioids should be used for acute pancreatitis pain not responding to acetaminophen or nonsteroidal antiinflammatory drugs (NSAIDs).

Abdominal pain is the most common presenting symptom of pancreatitis, and pain control is an essential component of supportive care. There are no randomized trials identifying an optimal pain management regimen. The committee recommends the use of opioids for pain not controlled with acetaminophen and NSAIDs. Refractory pain may necessitate consultation with an acute pain specialist.

Recommendation 5. Routine use of prophylactic antibiotics, protease inhibitors, antioxidants, and probiotics is not recommended in acute pancreatitis.

Adult literature does not support routine use of antibiotics in acute pancreatitis, but their use may be beneficial in severe or recalcitrant cases. Pediatric literature neither confirms nor refutes this finding. The guideline does not recommend the use of antibiotics without signs of infection. Limited adult studies have shown protease inhibitors, antioxidants, and probiotics to be beneficial; however, no pediatric data support their use.

This guideline also discusses interventional and surgical procedures. Of note, biliary tract disease may necessitate endoscopic retrograde cholangiopancreatography or cholecystectomy. Such procedures should be considered in conjunction with subspecialty input.²

Methods in Preparing Guideline

The guideline development committee, funded by the NASPGHAN and the National Institutes of Diabetes and Digestive and Kidney Diseases, was composed of members of the NASPGHAN Pancreas Committee and included gastroenterologists from multiple sites.² Topics were selected via group discussion, and Medline searches included both adult and pediatric literature. Preliminary recommendations were presented at the 2016 World Congress of Pediatric Gastroenterology, Hepatology and Nutrition. Following revision, the 24 authors voted on each recommendation using a five-point Likert scale. A recommendation passed if 75% of the participants either agreed or strongly agreed with it. The authors reported no conflicts of interest.

Although the literature review was comprehensive, it lacked prospective pediatric studies and many of the recommendations were derived from adult research. The committee originally intended to grade the quality of evidence; however, the pediatric specific literature was underpowered and retrospective. Therefore, the committee opted to use consensus voting. The authors note that had the group used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system, it would have returned grades of “low” or “very low” quality evidence.² The Hungarian Pancreatic Study Group and the European Pancreatic Club published a consensus guideline on the management of pediatric acute pancreatitis shortly after the NASPGHAN guideline, which offers similar conclusions.^2,6 The strength and generalizability of the NASPGHAN guideline are limited by its overreliance on adult literature, expert consensus, and small, retrospective pediatric studies to guide care.

This guideline highlights the need for pediatric research to guide the management of acute pancreatitis. The etiologies of pancreatitis in children are distinct from adults, where alcohol abuse and biliary disease are significant contributors.¹ Furthermore, age and environmental factors influence the presentation and clinical course.¹ Robust, prospective studies are needed to better understand the treatment outcomes of pediatric pancreatitis. Areas of further research include pediatric pancreatic severity scoring, ideal fluid composition and administration rate, enteral feed timing, optimal pain control, laboratory monitoring frequency, and adjuvant therapies.

Disclosures

Dr. Wall has nothing to disclose.

Pediatric acute pancreatitis is being diagnosed more commonly, affecting approximately one per 10,000 children annually with an estimated inpatient cost burden of $200 million per year.^1,2 Common causes of pediatric acute pancreatitis include systemic illness, biliary disease, trauma, and medications; 13%-34% of cases are idiopathic.¹ Currently, substantial variation exists in the clinical management of this condition.^3,4 Hospitalists should familiarize themselves with the current literature, including the recent practice guideline by the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN).²

(Evidence quality: not graded, recommendation by expert consensus)

Recommendation 1. Diagnosis of acute pancreatitis in pediatric patients requires at least two of the following symptoms: abdominal pain compatible with acute pancreatitis, serum amylase and/or lipase values >3 times the upper limits of normal, and imaging findings consistent with acute pancreatitis.The most common symptoms of acute pancreatitis in children are epigastric or diffuse abdominal pain, vomiting, and irritability. Presentation varies by age, and diagnosis requires a high index of suspicion. Significant elevations in amylase and lipase levels are typically detected early in the disease course. The guideline does not specify a preferred serum biomarker in the diagnosis of pancreatitis but notes that lipase is more sensitive and specific than amylase, rises within 6 hours of symptoms, and stays elevated longer. Amylase levels rise faster but often normalize by 24 hours of symptom onset. Amylase and lipase can originate from extrapancreatic sources and may be elevated during acute illness in the absence of pancreatitis.

Laboratory testing to investigate the etiology of acute pancreatitis should include hepatic enzymes, bilirubin, triglyceride, and calcium levels. Although not typically necessary for diagnosis, imaging may demonstrate pancreatic edema or peripancreatic fluid, confirm disease complications, and identify obstructive causes. Transabdominal ultrasonography is indicated if biliary pancreatitis is suspected. Contrast-enhanced computed tomography should be considered for patients with severe presentation or deteriorating condition. Magnetic resonance cholangiopancreatography is useful in detecting pancreaticobiliary abnormalities.

Recommendation 2. Children with acute pancreatitis should be initially resuscitated with crystalloids, either with lactated Ringer’s or normal saline in the acute setting. These children should be provided 1.5-2 times maintenance intravenous fluids with monitoring of urine output over the next 24-48 hours.

Fluid resuscitation and maintenance are the current mainstays of therapy for pancreatitis. Prompt fluid administration corrects hypovolemia and may prevent potential complications. Early, aggressive fluid replacement in adults reduces the incidence of systemic inflammatory response syndrome and organ failure. Limited pediatric studies support correction of hypovolemia and/or circulatory compromise using 10-20 ml/kg boluses of isotonic crystalloid fluid. Although the literature is sparse regarding the rate of continued fluid replacement, the committee recommends patients receive 1.5-2 times maintenance intravenous fluid (IVF) with normal saline plus 5% dextrose for the first 24-48 hours. The rate of IVF administration should be adjusted based on volume status and urine output. IVF should be discontinued once the patient is able to maintain adequate hydration enterally. Cardiac, renal, and pulmonary complications of pancreatitis often present within the first 48 hours of illness and should prompt close monitoring with assessment of vital signs every four hours. The committee recommends monitoring serum electrolytes and renal function in the first 48 hours but does not offer guidance regarding the frequency of laboratory testing or the value of trending serum biomarkers.

Recommendation 3. Except in the presence of direct contraindications to use the gut, children with mild acute pancreatitis may benefit from early (within 48-72 hours of presentation) oral and enteral nutrition to decrease the length of stay (LOS) and the risk of organ dysfunction.

Adult studies suggest early enteral nutrition decreases complications and reduces LOS. Initiating enteral nutrition within 48 hours in children may have similar benefits. Several small pediatric studies have demonstrated a reduced LOS with early enteral feeds without an increase in complications. In a retrospective single-center study, children who were fed within the first 48 hours and received 1.5-2 times maintenance IVF had shorter LOS, less frequent intensive care admissions, and reduced severity of illness compared with those who were kept nil per os for the first 48 hours.⁵ Nasogastric or nasojejunal feeds may be initiated if a patient is unable to tolerate oral feeding. Parenteral nutrition should be reserved for children in whom enteral nutrition cannot be initiated within five to seven days.

Recommendation 4. Intravenous morphine or other opioids should be used for acute pancreatitis pain not responding to acetaminophen or nonsteroidal antiinflammatory drugs (NSAIDs).

Abdominal pain is the most common presenting symptom of pancreatitis, and pain control is an essential component of supportive care. There are no randomized trials identifying an optimal pain management regimen. The committee recommends the use of opioids for pain not controlled with acetaminophen and NSAIDs. Refractory pain may necessitate consultation with an acute pain specialist.

Recommendation 5. Routine use of prophylactic antibiotics, protease inhibitors, antioxidants, and probiotics is not recommended in acute pancreatitis.

Adult literature does not support routine use of antibiotics in acute pancreatitis, but their use may be beneficial in severe or recalcitrant cases. Pediatric literature neither confirms nor refutes this finding. The guideline does not recommend the use of antibiotics without signs of infection. Limited adult studies have shown protease inhibitors, antioxidants, and probiotics to be beneficial; however, no pediatric data support their use.

This guideline also discusses interventional and surgical procedures. Of note, biliary tract disease may necessitate endoscopic retrograde cholangiopancreatography or cholecystectomy. Such procedures should be considered in conjunction with subspecialty input.²

Methods in Preparing Guideline

The guideline development committee, funded by the NASPGHAN and the National Institutes of Diabetes and Digestive and Kidney Diseases, was composed of members of the NASPGHAN Pancreas Committee and included gastroenterologists from multiple sites.² Topics were selected via group discussion, and Medline searches included both adult and pediatric literature. Preliminary recommendations were presented at the 2016 World Congress of Pediatric Gastroenterology, Hepatology and Nutrition. Following revision, the 24 authors voted on each recommendation using a five-point Likert scale. A recommendation passed if 75% of the participants either agreed or strongly agreed with it. The authors reported no conflicts of interest.

Although the literature review was comprehensive, it lacked prospective pediatric studies and many of the recommendations were derived from adult research. The committee originally intended to grade the quality of evidence; however, the pediatric specific literature was underpowered and retrospective. Therefore, the committee opted to use consensus voting. The authors note that had the group used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system, it would have returned grades of “low” or “very low” quality evidence.² The Hungarian Pancreatic Study Group and the European Pancreatic Club published a consensus guideline on the management of pediatric acute pancreatitis shortly after the NASPGHAN guideline, which offers similar conclusions.^2,6 The strength and generalizability of the NASPGHAN guideline are limited by its overreliance on adult literature, expert consensus, and small, retrospective pediatric studies to guide care.

This guideline highlights the need for pediatric research to guide the management of acute pancreatitis. The etiologies of pancreatitis in children are distinct from adults, where alcohol abuse and biliary disease are significant contributors.¹ Furthermore, age and environmental factors influence the presentation and clinical course.¹ Robust, prospective studies are needed to better understand the treatment outcomes of pediatric pancreatitis. Areas of further research include pediatric pancreatic severity scoring, ideal fluid composition and administration rate, enteral feed timing, optimal pain control, laboratory monitoring frequency, and adjuvant therapies.

Disclosures

Dr. Wall has nothing to disclose.

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

A 40-year-old woman with a history of opioid use disorder (OUD) on buprenorphine-naloxone treatment is admitted to medicine following incision and drainage of a large forearm abscess with surrounding cellulitis. The patient reports severe pain following the procedure, which is not relieved by ibuprofen. The admitting hospitalist orders a pain regimen for the patient, which includes oral and intravenous hydromorphone and discontinues the patient’s buprenorphine-naloxone so that the short-acting opioids can take effect.

Medications to treat OUD include methadone, buprenorphine, and extended-release naltrexone. Buprenorphine is a Schedule III medication under the United States Food and Drug Administration that reduces opioid cravings, subsequently decreasing drug use¹ and opioid-related overdose deaths.² It has a favorable safety profile and can be prescribed for OUD in an office-based, outpatient setting since the Drug Addiction Treatment Act of 2000 (DATA 2000). Due to extensive first-pass metabolism, buprenorphine for OUD is typically administered sublingually, either alone or in a fixed combination with naloxone.

Buprenorphine is a partial opioid agonist with a long half-life and high affinity for the mu opioid receptor. Given these properties, prior recommendations assumed that buprenorphine blocked the effectiveness of additional opioid agonists.^3,4 In 2004, guidelines by the Department of Health and Human Service Center for Substance Abuse Treatment recommended discontinuing buprenorphine in patients taking opioid pain medications.⁵ These suggestions were based on limited case reports describing difficulty controlling pain in patients with OUD with a high opioid tolerance who were receiving buprenorphine.⁶

Providers may hold buprenorphine when treating acute pain out of concern it could precipitate withdrawal by displacing full opioid agonists from the mu receptor. Providers may also believe that the naloxone component in the most commonly prescribed formulation, buprenorphine-naloxone, blocks the effects of opioid analgesics. Evolving understanding of buprenorphine pharmacology and the absence of high-quality evidence has resulted in providers holding buprenorphine in the setting of acute pain.

Finally, providers without dedicated training may feel they lack the necessary qualifications to prescribe buprenorphine in the inpatient setting. DATA 2000 requires mandatory X waiver training for physicians, nurse practitioners, and physician assistants to prescribe outpatient buprenorphine for OUD treatment outside of specialized opioid treatment programs.

Despite buprenorphine’s high affinity at the mu receptor, additional receptors remain available for full opioid agonists to bind and activate,⁶ providing effective pain relief even in patients using buprenorphine. In contrast to the 2004 Department of Health and Human Service guidelines, subsequent clinical studies have demonstrated that concurrent use of opioid analgesics is effective for patients maintained on buprenorphine, similar to patients on other forms of OUD treatment such as methadone.^7,8

Precipitated withdrawal only occurs when buprenorphine is newly introduced to patients with already circulating opioids. Patients receiving buprenorphine-naloxone can also be exposed to opioids without precipitated withdrawal from the naloxone component, as naloxone is not absorbed via sublingual or buccal administration, but only present in the formulation to dissuade intravenous administration of the medication.

Even in the perioperative period, there is insufficient evidence to support the discontinuation of buprenorphine.⁹ Studies in this patient population have found that patients receiving buprenorphine may require higher doses of short-acting opioids to achieve adequate analgesia, but they experience similar pain control, lengths of stay, and functional outcomes to controls.¹⁰ Despite variable perioperative management of buprenorphine,¹¹ protocols at major medical centers now recommend continuing or dose adjusting buprenorphine in the perioperative period rather than discontinuing.^12-14

Patients physically dependent on opioid agonists, including buprenorphine, must be maintained on a daily equivalent opioid dose to avoid experiencing withdrawal. This maintenance requirement must be met before any analgesic effect for acute pain is obtained with additional opioids. Temporarily discontinuing buprenorphine introduces unnecessary complexity to a hospitalization, places the patient at risk of exacerbation of pain, opioid withdrawal, and predisposes the patient to return to use and overdose if not resumed before hospital discharge.⁵

Finally, clinicians do not require additional training or an X waiver to administer buprenorphine to hospitalized patients. These requirements are limited to providers managing buprenorphine in the outpatient setting or those prescribing buprenorphine to patients to take postdischarge. Hospitalists frequently prescribe opioid medications in the inpatient setting with similar or greater safety risk profiles to buprenorphine.

Providers may consider holding buprenorphine if a patient with OUD has not been taking buprenorphine before hospitalization and has severe acute pain needs. This history can be confirmed with the patient and the state’s online prescription drug monitoring program. If further clarification is needed, this can be accomplished with a pharmacist and urine testing or by verifying with the patient’s opioid treatment program, as some programs provide directly administered buprenorphine.

In cases where a patient may have stopped buprenorphine before admission but wants to restart it in the hospital, it is essential to ascertain when the patient last used an opioid. The buprenorphine reinduction should be timed to a sufficient number of hours since last opioid use and/or to when the patient shows signs of active withdrawal. The re-induction can take place before, during, or after an acute pain episode, depending on the individual circumstances.

Patient preference is extremely important in the management of both pain and OUD. After shared decision-making, some patients may ultimately opt to hold buprenorphine in certain situations or switch to an alternative treatment, such as methadone, during their hospitalization. Such adjustments should be made in conjunction with the patient, primary care provider, and pain or addiction medicine specialty consultation.

For patients on buprenorphine admitted to the hospital with anticipated or unanticipated acute pain needs, hospitalists should continue buprenorphine. Continuation of buprenorphine meets a patient’s baseline opioid requirement while still allowing the use of additional short-acting opioid agonists as needed for pain.¹⁵

As with all pain, multimodal pain management should be provided with adjunctive medications such as acetaminophen, nonsteroidal anti-inflammatory drugs, neuropathic agents, topical analgesics, and regional anesthesia.⁸

Acute pain can be addressed by taking advantage of buprenorphine’s analgesic effects and adding additional short-acting opioids if needed.¹⁵ Several options are available, including:

1. Continuing daily buprenorphine and prescribing short-acting opioid agonists, preferably those with high intrinsic activity at the mu receptor (such as morphine, fentanyl, or hydromorphone). Full opioid agonist doses to achieve analgesia for patients on buprenorphine will be higher than in opioid naïve patients due to tolerance.¹⁶

2 .Dividing the total daily buprenorphine dose into three or four times per day dosing, since buprenorphine provides an analgesic effect lasting six to eight hours. Short-acting opioid agonists can still be prescribed on an as-needed basis for additional pain needs.

3. Temporarily increasing the total daily buprenorphine dose and dividing into three or four times per day dosing, as above. Short-acting opioid agonists can still be prescribed on an as-needed basis for additional pain needs.

It is essential to make a clear plan with the patient for initiation and discontinuation of short-acting opioid agonists or buprenorphine changes. Patients on buprenorphine should be managed collaboratively with the primary care provider or addiction specialist to coordinate prescribing and follow-up after discharge.

• Continue outpatient buprenorphine treatment for patients admitted with acute pain.
• Use adjunctive nonopioid pain medications and nonpharmacologic modalities to address acute pain.
• Adjust buprenorphine to address acute pain by dividing the total daily amount into three or four times a day dosing, and/or up-titrate the buprenorphine dose (federal prescribing regulations recommend a maximum of 24 mg daily, but state regulations may vary).
• Add short-acting opioid agonists on an as-needed basis in conjunction with a defined plan to discontinue short-acting opioid agonists to avoid a return to use.
• Make plans collaboratively with the patient and outpatient provider, and communicate medication changes and plan at discharge.

Concerning our case, the hospitalist can continue the patient’s buprenorphine-naloxone, even with her acute pain needs. The patient has a baseline opioid requirement, fulfilled by continuing buprenorphine. Additional short-acting opioid agonists, such as hydromorphone, will provide analgesia for the patient, though the clinician should be aware that higher doses might be required. The practice of holding buprenorphine during episodes of acute pain is not supported by current evidence and may predispose to inadequate analgesia, opioid withdrawal, and risk of return to use and death.²

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

Disclosures

The authors report no conflicts of interest.

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

A 40-year-old woman with a history of opioid use disorder (OUD) on buprenorphine-naloxone treatment is admitted to medicine following incision and drainage of a large forearm abscess with surrounding cellulitis. The patient reports severe pain following the procedure, which is not relieved by ibuprofen. The admitting hospitalist orders a pain regimen for the patient, which includes oral and intravenous hydromorphone and discontinues the patient’s buprenorphine-naloxone so that the short-acting opioids can take effect.

Medications to treat OUD include methadone, buprenorphine, and extended-release naltrexone. Buprenorphine is a Schedule III medication under the United States Food and Drug Administration that reduces opioid cravings, subsequently decreasing drug use¹ and opioid-related overdose deaths.² It has a favorable safety profile and can be prescribed for OUD in an office-based, outpatient setting since the Drug Addiction Treatment Act of 2000 (DATA 2000). Due to extensive first-pass metabolism, buprenorphine for OUD is typically administered sublingually, either alone or in a fixed combination with naloxone.

Buprenorphine is a partial opioid agonist with a long half-life and high affinity for the mu opioid receptor. Given these properties, prior recommendations assumed that buprenorphine blocked the effectiveness of additional opioid agonists.^3,4 In 2004, guidelines by the Department of Health and Human Service Center for Substance Abuse Treatment recommended discontinuing buprenorphine in patients taking opioid pain medications.⁵ These suggestions were based on limited case reports describing difficulty controlling pain in patients with OUD with a high opioid tolerance who were receiving buprenorphine.⁶

Providers may hold buprenorphine when treating acute pain out of concern it could precipitate withdrawal by displacing full opioid agonists from the mu receptor. Providers may also believe that the naloxone component in the most commonly prescribed formulation, buprenorphine-naloxone, blocks the effects of opioid analgesics. Evolving understanding of buprenorphine pharmacology and the absence of high-quality evidence has resulted in providers holding buprenorphine in the setting of acute pain.

Finally, providers without dedicated training may feel they lack the necessary qualifications to prescribe buprenorphine in the inpatient setting. DATA 2000 requires mandatory X waiver training for physicians, nurse practitioners, and physician assistants to prescribe outpatient buprenorphine for OUD treatment outside of specialized opioid treatment programs.

Despite buprenorphine’s high affinity at the mu receptor, additional receptors remain available for full opioid agonists to bind and activate,⁶ providing effective pain relief even in patients using buprenorphine. In contrast to the 2004 Department of Health and Human Service guidelines, subsequent clinical studies have demonstrated that concurrent use of opioid analgesics is effective for patients maintained on buprenorphine, similar to patients on other forms of OUD treatment such as methadone.^7,8

Precipitated withdrawal only occurs when buprenorphine is newly introduced to patients with already circulating opioids. Patients receiving buprenorphine-naloxone can also be exposed to opioids without precipitated withdrawal from the naloxone component, as naloxone is not absorbed via sublingual or buccal administration, but only present in the formulation to dissuade intravenous administration of the medication.

Even in the perioperative period, there is insufficient evidence to support the discontinuation of buprenorphine.⁹ Studies in this patient population have found that patients receiving buprenorphine may require higher doses of short-acting opioids to achieve adequate analgesia, but they experience similar pain control, lengths of stay, and functional outcomes to controls.¹⁰ Despite variable perioperative management of buprenorphine,¹¹ protocols at major medical centers now recommend continuing or dose adjusting buprenorphine in the perioperative period rather than discontinuing.^12-14

Patients physically dependent on opioid agonists, including buprenorphine, must be maintained on a daily equivalent opioid dose to avoid experiencing withdrawal. This maintenance requirement must be met before any analgesic effect for acute pain is obtained with additional opioids. Temporarily discontinuing buprenorphine introduces unnecessary complexity to a hospitalization, places the patient at risk of exacerbation of pain, opioid withdrawal, and predisposes the patient to return to use and overdose if not resumed before hospital discharge.⁵

Finally, clinicians do not require additional training or an X waiver to administer buprenorphine to hospitalized patients. These requirements are limited to providers managing buprenorphine in the outpatient setting or those prescribing buprenorphine to patients to take postdischarge. Hospitalists frequently prescribe opioid medications in the inpatient setting with similar or greater safety risk profiles to buprenorphine.

Providers may consider holding buprenorphine if a patient with OUD has not been taking buprenorphine before hospitalization and has severe acute pain needs. This history can be confirmed with the patient and the state’s online prescription drug monitoring program. If further clarification is needed, this can be accomplished with a pharmacist and urine testing or by verifying with the patient’s opioid treatment program, as some programs provide directly administered buprenorphine.

In cases where a patient may have stopped buprenorphine before admission but wants to restart it in the hospital, it is essential to ascertain when the patient last used an opioid. The buprenorphine reinduction should be timed to a sufficient number of hours since last opioid use and/or to when the patient shows signs of active withdrawal. The re-induction can take place before, during, or after an acute pain episode, depending on the individual circumstances.

Patient preference is extremely important in the management of both pain and OUD. After shared decision-making, some patients may ultimately opt to hold buprenorphine in certain situations or switch to an alternative treatment, such as methadone, during their hospitalization. Such adjustments should be made in conjunction with the patient, primary care provider, and pain or addiction medicine specialty consultation.

For patients on buprenorphine admitted to the hospital with anticipated or unanticipated acute pain needs, hospitalists should continue buprenorphine. Continuation of buprenorphine meets a patient’s baseline opioid requirement while still allowing the use of additional short-acting opioid agonists as needed for pain.¹⁵

As with all pain, multimodal pain management should be provided with adjunctive medications such as acetaminophen, nonsteroidal anti-inflammatory drugs, neuropathic agents, topical analgesics, and regional anesthesia.⁸

Acute pain can be addressed by taking advantage of buprenorphine’s analgesic effects and adding additional short-acting opioids if needed.¹⁵ Several options are available, including:

1. Continuing daily buprenorphine and prescribing short-acting opioid agonists, preferably those with high intrinsic activity at the mu receptor (such as morphine, fentanyl, or hydromorphone). Full opioid agonist doses to achieve analgesia for patients on buprenorphine will be higher than in opioid naïve patients due to tolerance.¹⁶

2 .Dividing the total daily buprenorphine dose into three or four times per day dosing, since buprenorphine provides an analgesic effect lasting six to eight hours. Short-acting opioid agonists can still be prescribed on an as-needed basis for additional pain needs.

3. Temporarily increasing the total daily buprenorphine dose and dividing into three or four times per day dosing, as above. Short-acting opioid agonists can still be prescribed on an as-needed basis for additional pain needs.

It is essential to make a clear plan with the patient for initiation and discontinuation of short-acting opioid agonists or buprenorphine changes. Patients on buprenorphine should be managed collaboratively with the primary care provider or addiction specialist to coordinate prescribing and follow-up after discharge.

• Continue outpatient buprenorphine treatment for patients admitted with acute pain.
• Use adjunctive nonopioid pain medications and nonpharmacologic modalities to address acute pain.
• Adjust buprenorphine to address acute pain by dividing the total daily amount into three or four times a day dosing, and/or up-titrate the buprenorphine dose (federal prescribing regulations recommend a maximum of 24 mg daily, but state regulations may vary).
• Add short-acting opioid agonists on an as-needed basis in conjunction with a defined plan to discontinue short-acting opioid agonists to avoid a return to use.
• Make plans collaboratively with the patient and outpatient provider, and communicate medication changes and plan at discharge.

Concerning our case, the hospitalist can continue the patient’s buprenorphine-naloxone, even with her acute pain needs. The patient has a baseline opioid requirement, fulfilled by continuing buprenorphine. Additional short-acting opioid agonists, such as hydromorphone, will provide analgesia for the patient, though the clinician should be aware that higher doses might be required. The practice of holding buprenorphine during episodes of acute pain is not supported by current evidence and may predispose to inadequate analgesia, opioid withdrawal, and risk of return to use and death.²

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

Disclosures

The authors report no conflicts of interest.

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

A 40-year-old woman with a history of opioid use disorder (OUD) on buprenorphine-naloxone treatment is admitted to medicine following incision and drainage of a large forearm abscess with surrounding cellulitis. The patient reports severe pain following the procedure, which is not relieved by ibuprofen. The admitting hospitalist orders a pain regimen for the patient, which includes oral and intravenous hydromorphone and discontinues the patient’s buprenorphine-naloxone so that the short-acting opioids can take effect.

Medications to treat OUD include methadone, buprenorphine, and extended-release naltrexone. Buprenorphine is a Schedule III medication under the United States Food and Drug Administration that reduces opioid cravings, subsequently decreasing drug use¹ and opioid-related overdose deaths.² It has a favorable safety profile and can be prescribed for OUD in an office-based, outpatient setting since the Drug Addiction Treatment Act of 2000 (DATA 2000). Due to extensive first-pass metabolism, buprenorphine for OUD is typically administered sublingually, either alone or in a fixed combination with naloxone.

Buprenorphine is a partial opioid agonist with a long half-life and high affinity for the mu opioid receptor. Given these properties, prior recommendations assumed that buprenorphine blocked the effectiveness of additional opioid agonists.^3,4 In 2004, guidelines by the Department of Health and Human Service Center for Substance Abuse Treatment recommended discontinuing buprenorphine in patients taking opioid pain medications.⁵ These suggestions were based on limited case reports describing difficulty controlling pain in patients with OUD with a high opioid tolerance who were receiving buprenorphine.⁶

Providers may hold buprenorphine when treating acute pain out of concern it could precipitate withdrawal by displacing full opioid agonists from the mu receptor. Providers may also believe that the naloxone component in the most commonly prescribed formulation, buprenorphine-naloxone, blocks the effects of opioid analgesics. Evolving understanding of buprenorphine pharmacology and the absence of high-quality evidence has resulted in providers holding buprenorphine in the setting of acute pain.

Finally, providers without dedicated training may feel they lack the necessary qualifications to prescribe buprenorphine in the inpatient setting. DATA 2000 requires mandatory X waiver training for physicians, nurse practitioners, and physician assistants to prescribe outpatient buprenorphine for OUD treatment outside of specialized opioid treatment programs.

Despite buprenorphine’s high affinity at the mu receptor, additional receptors remain available for full opioid agonists to bind and activate,⁶ providing effective pain relief even in patients using buprenorphine. In contrast to the 2004 Department of Health and Human Service guidelines, subsequent clinical studies have demonstrated that concurrent use of opioid analgesics is effective for patients maintained on buprenorphine, similar to patients on other forms of OUD treatment such as methadone.^7,8

Precipitated withdrawal only occurs when buprenorphine is newly introduced to patients with already circulating opioids. Patients receiving buprenorphine-naloxone can also be exposed to opioids without precipitated withdrawal from the naloxone component, as naloxone is not absorbed via sublingual or buccal administration, but only present in the formulation to dissuade intravenous administration of the medication.

Even in the perioperative period, there is insufficient evidence to support the discontinuation of buprenorphine.⁹ Studies in this patient population have found that patients receiving buprenorphine may require higher doses of short-acting opioids to achieve adequate analgesia, but they experience similar pain control, lengths of stay, and functional outcomes to controls.¹⁰ Despite variable perioperative management of buprenorphine,¹¹ protocols at major medical centers now recommend continuing or dose adjusting buprenorphine in the perioperative period rather than discontinuing.^12-14

Patients physically dependent on opioid agonists, including buprenorphine, must be maintained on a daily equivalent opioid dose to avoid experiencing withdrawal. This maintenance requirement must be met before any analgesic effect for acute pain is obtained with additional opioids. Temporarily discontinuing buprenorphine introduces unnecessary complexity to a hospitalization, places the patient at risk of exacerbation of pain, opioid withdrawal, and predisposes the patient to return to use and overdose if not resumed before hospital discharge.⁵

Finally, clinicians do not require additional training or an X waiver to administer buprenorphine to hospitalized patients. These requirements are limited to providers managing buprenorphine in the outpatient setting or those prescribing buprenorphine to patients to take postdischarge. Hospitalists frequently prescribe opioid medications in the inpatient setting with similar or greater safety risk profiles to buprenorphine.

Providers may consider holding buprenorphine if a patient with OUD has not been taking buprenorphine before hospitalization and has severe acute pain needs. This history can be confirmed with the patient and the state’s online prescription drug monitoring program. If further clarification is needed, this can be accomplished with a pharmacist and urine testing or by verifying with the patient’s opioid treatment program, as some programs provide directly administered buprenorphine.

In cases where a patient may have stopped buprenorphine before admission but wants to restart it in the hospital, it is essential to ascertain when the patient last used an opioid. The buprenorphine reinduction should be timed to a sufficient number of hours since last opioid use and/or to when the patient shows signs of active withdrawal. The re-induction can take place before, during, or after an acute pain episode, depending on the individual circumstances.

Patient preference is extremely important in the management of both pain and OUD. After shared decision-making, some patients may ultimately opt to hold buprenorphine in certain situations or switch to an alternative treatment, such as methadone, during their hospitalization. Such adjustments should be made in conjunction with the patient, primary care provider, and pain or addiction medicine specialty consultation.

For patients on buprenorphine admitted to the hospital with anticipated or unanticipated acute pain needs, hospitalists should continue buprenorphine. Continuation of buprenorphine meets a patient’s baseline opioid requirement while still allowing the use of additional short-acting opioid agonists as needed for pain.¹⁵

As with all pain, multimodal pain management should be provided with adjunctive medications such as acetaminophen, nonsteroidal anti-inflammatory drugs, neuropathic agents, topical analgesics, and regional anesthesia.⁸

Acute pain can be addressed by taking advantage of buprenorphine’s analgesic effects and adding additional short-acting opioids if needed.¹⁵ Several options are available, including:

1. Continuing daily buprenorphine and prescribing short-acting opioid agonists, preferably those with high intrinsic activity at the mu receptor (such as morphine, fentanyl, or hydromorphone). Full opioid agonist doses to achieve analgesia for patients on buprenorphine will be higher than in opioid naïve patients due to tolerance.¹⁶

2 .Dividing the total daily buprenorphine dose into three or four times per day dosing, since buprenorphine provides an analgesic effect lasting six to eight hours. Short-acting opioid agonists can still be prescribed on an as-needed basis for additional pain needs.

3. Temporarily increasing the total daily buprenorphine dose and dividing into three or four times per day dosing, as above. Short-acting opioid agonists can still be prescribed on an as-needed basis for additional pain needs.

It is essential to make a clear plan with the patient for initiation and discontinuation of short-acting opioid agonists or buprenorphine changes. Patients on buprenorphine should be managed collaboratively with the primary care provider or addiction specialist to coordinate prescribing and follow-up after discharge.

• Continue outpatient buprenorphine treatment for patients admitted with acute pain.
• Use adjunctive nonopioid pain medications and nonpharmacologic modalities to address acute pain.
• Adjust buprenorphine to address acute pain by dividing the total daily amount into three or four times a day dosing, and/or up-titrate the buprenorphine dose (federal prescribing regulations recommend a maximum of 24 mg daily, but state regulations may vary).
• Add short-acting opioid agonists on an as-needed basis in conjunction with a defined plan to discontinue short-acting opioid agonists to avoid a return to use.
• Make plans collaboratively with the patient and outpatient provider, and communicate medication changes and plan at discharge.

Concerning our case, the hospitalist can continue the patient’s buprenorphine-naloxone, even with her acute pain needs. The patient has a baseline opioid requirement, fulfilled by continuing buprenorphine. Additional short-acting opioid agonists, such as hydromorphone, will provide analgesia for the patient, though the clinician should be aware that higher doses might be required. The practice of holding buprenorphine during episodes of acute pain is not supported by current evidence and may predispose to inadequate analgesia, opioid withdrawal, and risk of return to use and death.²

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

Disclosures

The authors report no conflicts of interest.

Elevated serum troponin clearly does not equal myocardial infarction (MI). This was the strong message in the 2018 publication of the Fourth Universal Definition of Myocardial Infarction¹ (4UDMI), the first update to the international consensus document since 2012.

Most clinicians have learned how to accurately diagnose the classic Type 1 MI (T1MI) due to atherosclerotic plaque rupture; however, elevated troponin in the absence of T1MI is increasingly common due to more frequent and less discriminate troponin testing.² Patients with elevated troponin in the absence of T1MI have traditionally created confusion and variability in diagnosis, management, and documentation. Interpretation and management of elevated troponin in the absence of T1MI has become difficult.

In this clinical practice update, we aim to review the updated definition of Type 2 MI (T2MI) and nonischemic myocardial injury (NIMI), since these are the two predominant diagnoses among patients with elevated troponin in the absence of T1MI. We also provide a clinical framework for clinicians to think through elevated serum cardiac troponin levels and identify opportunities for quality improvement around this critical issue.

The presence of an elevated serum troponin level is a critical component in determining the presence of cardiac myocyte injury and possible infarction. Myocardial injury is defined as the presence of serum troponin above the 99th percentile of the upper reference limit (URL), the absolute value of which varies by assay and which applies to traditional and highly sensitive subtypes. Myocardial injury can be confusing to assess, as it can be acute or chronic.

When troponin levels are elevated but stable, this is indicative of chronic (usually nonischemic) myocardial injury, as seen, for example, in patients who have end-stage renal disease. The presence of acute injury requires a change in the troponin value—specifically a rise and/or fall in troponin levels with serial measurements. What constitutes a significant “rise and/or fall” is a matter of some debate and is not precisely defined in the 4UDMI. The percent change in the troponin value over time (relative delta) is listed as part of the criteria for acute injury when the change is greater than or equal to 20%;¹ however, clinicians should be aware that absolute delta in troponin (the change in ng/dL) has better performance characteristics³ in diagnosing acute myocardial injury. Regardless of whether clinicians use relative or absolute changes in the serum troponin level, clinical evaluation of patients with acute injury is critical to establishing whether the injury is ischemic (MI) or nonischemic (NIMI). The presence of at least one of the following is necessary to meet the current criteria for myocardial ischemia according to the fourth universal definition: new ischemic symptoms (eg, chest pain, dyspnea, etc.), new ischemic changes in the patient’s electrocardiogram (eg, new ST segment depression in leads II, III, and aVF), or cardiac imaging changes consistent with ischemic injury (eg, new wall motion abnormality in the inferior wall on echocardiography).

Following diagnosis of MI based on elevated troponin and new symptoms or signs, the cause of MI should then be determined. Type 1 MI remains defined as MI caused by atherosclerotic plaque disruption in a patient with coronary artery disease (CAD). Type 2 MI is not caused by plaque disruption but is due to a mismatch between oxygen supply and demand unrelated to acute atherothrombosis. T2MI is an ischemic myocardial injury traceable to some other illness that leads to inadequate myocyte oxygenation. Causes of T2MI are numerous, can overlap with nonischemic injury, and can include severe anemia, septic shock, rapid atrial fibrillation, and coronary dissection. While CAD may be present in patients with T2MI, it is not a requirement, and an increased demand for, or reduced supply of, myocyte oxygen alone can be sufficient to cause MI.

In the absence of clinical signs or symptoms of cardiac ischemia, clinicians should categorize patients as having a nonischemic myocardial injury. There is significant overlap between causes of T2MI and NIMI, for example, sepsis could cause either T2MI or NIMI. What distinguishes these two entities is whether the signs and symptoms for myocardial ischemia as outlined above are present. If these signs or symptoms are present, the diagnosis is T2MI. If no clinical signs or symptoms of ischemia are present, the diagnosis is NIMI. The assessment of the clinician, using all available clinical information, is pivotal. The characteristics of the three major types of myocardial injury are depicted in the Figure.

Proper distinction between infarction or injury without infarction is central to proper evaluation, treatment, and eventual documentation in patients with elevated troponin levels. In the case of T2MI and NIMI, identifying what underlying illness is causing the troponin elevation is essential for acute management.

Evaluation

Troponin elevation is associated with an elevated risk for major adverse cardiovascular events, regardless of etiology.⁴ While patients with suspected T1MI are most often evaluated by coronary angiography, this may not be necessary for patients with T2MI or NIMI. Developing an evaluation strategy for patients with T2MI or NIMI requires understanding the underlying etiology of myocardial injury. In patients with septic shock for example, there are many potential mechanisms for cardiac myocyte injury, many of which are nonischemic (eg, cytokine-mediated).⁵ Prompt evaluation and treatment of septic shock, therefore, often leads to resolution of cardiac dysfunction, and ischemic evaluation may not be necessary.⁶ In many cases of T2MI or NIMI, waiting for an acute underlying illness to resolve is necessary before deciding whether ischemic evaluation is appropriate. It is important that this decision is deferred but not forgotten though as patients with T2MI or NIMI may benefit from further cardiac evaluation. There are no society recommendations and minimal evidence to guide this evaluation, but clinical trials testing different evaluation strategies are underway.⁷ Until an optimal evidence-based evaluation strategy becomes clear, clinicians should focus on two key principles: first, determine and treat the underlying etiology; second, identify patients with traditional risk factors for CAD and consider further evaluation with either coronary angiography or cardiac imaging. Referral to a cardiologist for assistance with the latter issue, especially for challenging or equivocal cases, is encouraged.

Treatment

While T1MI therapies have a strong evidence base with high rates of appropriate treatment, there are relatively few evidence-based therapies for T2MI and NIMI. The benefits of traditional T1MI therapies should be considered in terms of each therapy’s risk-benefit profile. Among patients with T2MI or NIMI in whom atherosclerotic plaque rupture is unlikely, or in whom bleeding risk is high, antithrombotic agents such as unfractionated heparin and dual antiplatelet therapy represent low value and potentially harmful therapies.⁸ Conversely, patients with multiple risk factors for CAD may benefit from low-risk guideline directed medical therapies such as HMGCoA reductase inhibitors (ie, “statins”). Recent data suggest that lipid-lowering therapies may even be beneficial for preventing T2MI.⁹

Given the lack of evidence for therapies to treat patients with T2MI or NIMI, clinical judgment remains central to creating an optimal management plan. Clinicians should consider consultation with a cardiologist any time there is ambiguity in whether the diagnosis is T1MI or T2MI. For example, postoperative patients represent a particularly challenging clinical scenario due to the difficulty of assessing ischemic signs and symptoms in the operating room. In this setting, early evaluation by a cardiologist has been shown to improve outcomes.¹⁰

Documentation

Documentation of non-ST elevation MI (NSTEMI) for every case of elevated troponin, rather than using the more specific T1MI, T2MI, or NIMI terminology, can have adverse consequences for health systems. From a coding perspective, the terms STEMI and NSTEMI mean T1MI, and the ICD-10 codes used to identify T1MI patients for value-focused programs frequently include patients with T2MI and NIMI due to imprecise documentation.¹¹ When T2MI and NIMI are imprecisely documented as NSTEMI, health systems and clinicians are held to the T1MI care standards. This can negatively skew the performance of a health system or individual clinician because T2MI and NIMI patients have worse outcomes than T1MI patients.⁴ Inaccurate categorization of patients can lead to inaccurate quality and registry reporting, which may hinder the ability of health systems to monitor and implement quality improvement programs for MI patients. The distinction between T1MI and T2MI in documentation is all the more important now that a new ICD-10 code exists for T2MI (I21.A1), which allows clinicians to more precisely identify these patients, both clinically and administratively, as distinct from T1MI patients.¹² While there is no similarly specific ICD-10 code for NIMI, using the appropriate terminology in documentation should prompt coding personnel to use a code for “other abnormal findings of blood chemistry,” reflecting cardiac biomarker elevation (R79.89), rather than using one of the T1MI codes. Clinicians may not be able to determine the etiology of troponin elevation in the initial phase of a hospitalization, but a definitive diagnosis should be documented in the discharge summary.

From the patient perspective, documentation using STEMI and NSTEMI can mislead clinicians, given that this terminology does not specify the underlying cause (ie, plaque rupture or oxygen supply-demand mismatch), potentially leading to delayed initiation of appropriate therapy. Incorrect documentation, using STEMI/NSTEMI language or incorrectly labeling T2MI and NIMI, may lead patients to believe they have had a heart attack when they had myocardial injury instead. This may lead to unnecessary anxiety and change their interactions with the health system. These patients may be started on unnecessary therapies, have inaccurate preoperative evaluations, and be labeled with a preexisting condition for the rest of their lives.

Opportunities for Quality Improvement

Systems-based quality improvement can help to ensure that patients with NIMI and T2MI are labeled appropriately and receive the proper treatment. Clinical education is the cornerstone of such efforts. Hospital medicine practitioners looking for support in understanding this issue might first partner with cardiology colleagues who may already have training materials available. Billing and coding personnel stand to benefit from greater orientation to this topic considering the complexities and errors in the coding of MI. In an attempt to help nonclinical coding personnel, leaders in the American College of Cardiology have advocated for use of the term “non-MI troponin elevation” (nMITE)¹³ to describe NIMI patients. Finally, we see an important role for EHR-embedded decision support tools to facilitate appropriate documentation and management of patients with elevated troponin. A potential care pathway, for example, could be created in partnership between hospital medicine and cardiology providers to identify which patients would benefit from cardiologist consultation.

Understanding the definitions of T1MI, T2MI, and NIMI will help clinicians to better identify the appropriate clinical care and consultation strategy for patients with elevated cardiac troponin. There are relatively few published quality improvement initiatives to help guide clinicians through these nuanced distinctions, but there is great potential in such approaches to help clinicians provide the highest value care possible.

Disclosures

No authors have any conflict of interest, financial or otherwise, to declare regarding this study.

Funding

Dr. Levy receives funding from National Institutes of Health (NIH) T32 Training Grant 5T32-HL007822.

Elevated serum troponin clearly does not equal myocardial infarction (MI). This was the strong message in the 2018 publication of the Fourth Universal Definition of Myocardial Infarction¹ (4UDMI), the first update to the international consensus document since 2012.

Most clinicians have learned how to accurately diagnose the classic Type 1 MI (T1MI) due to atherosclerotic plaque rupture; however, elevated troponin in the absence of T1MI is increasingly common due to more frequent and less discriminate troponin testing.² Patients with elevated troponin in the absence of T1MI have traditionally created confusion and variability in diagnosis, management, and documentation. Interpretation and management of elevated troponin in the absence of T1MI has become difficult.

In this clinical practice update, we aim to review the updated definition of Type 2 MI (T2MI) and nonischemic myocardial injury (NIMI), since these are the two predominant diagnoses among patients with elevated troponin in the absence of T1MI. We also provide a clinical framework for clinicians to think through elevated serum cardiac troponin levels and identify opportunities for quality improvement around this critical issue.

The presence of an elevated serum troponin level is a critical component in determining the presence of cardiac myocyte injury and possible infarction. Myocardial injury is defined as the presence of serum troponin above the 99th percentile of the upper reference limit (URL), the absolute value of which varies by assay and which applies to traditional and highly sensitive subtypes. Myocardial injury can be confusing to assess, as it can be acute or chronic.

When troponin levels are elevated but stable, this is indicative of chronic (usually nonischemic) myocardial injury, as seen, for example, in patients who have end-stage renal disease. The presence of acute injury requires a change in the troponin value—specifically a rise and/or fall in troponin levels with serial measurements. What constitutes a significant “rise and/or fall” is a matter of some debate and is not precisely defined in the 4UDMI. The percent change in the troponin value over time (relative delta) is listed as part of the criteria for acute injury when the change is greater than or equal to 20%;¹ however, clinicians should be aware that absolute delta in troponin (the change in ng/dL) has better performance characteristics³ in diagnosing acute myocardial injury. Regardless of whether clinicians use relative or absolute changes in the serum troponin level, clinical evaluation of patients with acute injury is critical to establishing whether the injury is ischemic (MI) or nonischemic (NIMI). The presence of at least one of the following is necessary to meet the current criteria for myocardial ischemia according to the fourth universal definition: new ischemic symptoms (eg, chest pain, dyspnea, etc.), new ischemic changes in the patient’s electrocardiogram (eg, new ST segment depression in leads II, III, and aVF), or cardiac imaging changes consistent with ischemic injury (eg, new wall motion abnormality in the inferior wall on echocardiography).

Following diagnosis of MI based on elevated troponin and new symptoms or signs, the cause of MI should then be determined. Type 1 MI remains defined as MI caused by atherosclerotic plaque disruption in a patient with coronary artery disease (CAD). Type 2 MI is not caused by plaque disruption but is due to a mismatch between oxygen supply and demand unrelated to acute atherothrombosis. T2MI is an ischemic myocardial injury traceable to some other illness that leads to inadequate myocyte oxygenation. Causes of T2MI are numerous, can overlap with nonischemic injury, and can include severe anemia, septic shock, rapid atrial fibrillation, and coronary dissection. While CAD may be present in patients with T2MI, it is not a requirement, and an increased demand for, or reduced supply of, myocyte oxygen alone can be sufficient to cause MI.

In the absence of clinical signs or symptoms of cardiac ischemia, clinicians should categorize patients as having a nonischemic myocardial injury. There is significant overlap between causes of T2MI and NIMI, for example, sepsis could cause either T2MI or NIMI. What distinguishes these two entities is whether the signs and symptoms for myocardial ischemia as outlined above are present. If these signs or symptoms are present, the diagnosis is T2MI. If no clinical signs or symptoms of ischemia are present, the diagnosis is NIMI. The assessment of the clinician, using all available clinical information, is pivotal. The characteristics of the three major types of myocardial injury are depicted in the Figure.

Proper distinction between infarction or injury without infarction is central to proper evaluation, treatment, and eventual documentation in patients with elevated troponin levels. In the case of T2MI and NIMI, identifying what underlying illness is causing the troponin elevation is essential for acute management.

Evaluation

Troponin elevation is associated with an elevated risk for major adverse cardiovascular events, regardless of etiology.⁴ While patients with suspected T1MI are most often evaluated by coronary angiography, this may not be necessary for patients with T2MI or NIMI. Developing an evaluation strategy for patients with T2MI or NIMI requires understanding the underlying etiology of myocardial injury. In patients with septic shock for example, there are many potential mechanisms for cardiac myocyte injury, many of which are nonischemic (eg, cytokine-mediated).⁵ Prompt evaluation and treatment of septic shock, therefore, often leads to resolution of cardiac dysfunction, and ischemic evaluation may not be necessary.⁶ In many cases of T2MI or NIMI, waiting for an acute underlying illness to resolve is necessary before deciding whether ischemic evaluation is appropriate. It is important that this decision is deferred but not forgotten though as patients with T2MI or NIMI may benefit from further cardiac evaluation. There are no society recommendations and minimal evidence to guide this evaluation, but clinical trials testing different evaluation strategies are underway.⁷ Until an optimal evidence-based evaluation strategy becomes clear, clinicians should focus on two key principles: first, determine and treat the underlying etiology; second, identify patients with traditional risk factors for CAD and consider further evaluation with either coronary angiography or cardiac imaging. Referral to a cardiologist for assistance with the latter issue, especially for challenging or equivocal cases, is encouraged.

Treatment

While T1MI therapies have a strong evidence base with high rates of appropriate treatment, there are relatively few evidence-based therapies for T2MI and NIMI. The benefits of traditional T1MI therapies should be considered in terms of each therapy’s risk-benefit profile. Among patients with T2MI or NIMI in whom atherosclerotic plaque rupture is unlikely, or in whom bleeding risk is high, antithrombotic agents such as unfractionated heparin and dual antiplatelet therapy represent low value and potentially harmful therapies.⁸ Conversely, patients with multiple risk factors for CAD may benefit from low-risk guideline directed medical therapies such as HMGCoA reductase inhibitors (ie, “statins”). Recent data suggest that lipid-lowering therapies may even be beneficial for preventing T2MI.⁹

Given the lack of evidence for therapies to treat patients with T2MI or NIMI, clinical judgment remains central to creating an optimal management plan. Clinicians should consider consultation with a cardiologist any time there is ambiguity in whether the diagnosis is T1MI or T2MI. For example, postoperative patients represent a particularly challenging clinical scenario due to the difficulty of assessing ischemic signs and symptoms in the operating room. In this setting, early evaluation by a cardiologist has been shown to improve outcomes.¹⁰

Documentation

Documentation of non-ST elevation MI (NSTEMI) for every case of elevated troponin, rather than using the more specific T1MI, T2MI, or NIMI terminology, can have adverse consequences for health systems. From a coding perspective, the terms STEMI and NSTEMI mean T1MI, and the ICD-10 codes used to identify T1MI patients for value-focused programs frequently include patients with T2MI and NIMI due to imprecise documentation.¹¹ When T2MI and NIMI are imprecisely documented as NSTEMI, health systems and clinicians are held to the T1MI care standards. This can negatively skew the performance of a health system or individual clinician because T2MI and NIMI patients have worse outcomes than T1MI patients.⁴ Inaccurate categorization of patients can lead to inaccurate quality and registry reporting, which may hinder the ability of health systems to monitor and implement quality improvement programs for MI patients. The distinction between T1MI and T2MI in documentation is all the more important now that a new ICD-10 code exists for T2MI (I21.A1), which allows clinicians to more precisely identify these patients, both clinically and administratively, as distinct from T1MI patients.¹² While there is no similarly specific ICD-10 code for NIMI, using the appropriate terminology in documentation should prompt coding personnel to use a code for “other abnormal findings of blood chemistry,” reflecting cardiac biomarker elevation (R79.89), rather than using one of the T1MI codes. Clinicians may not be able to determine the etiology of troponin elevation in the initial phase of a hospitalization, but a definitive diagnosis should be documented in the discharge summary.

From the patient perspective, documentation using STEMI and NSTEMI can mislead clinicians, given that this terminology does not specify the underlying cause (ie, plaque rupture or oxygen supply-demand mismatch), potentially leading to delayed initiation of appropriate therapy. Incorrect documentation, using STEMI/NSTEMI language or incorrectly labeling T2MI and NIMI, may lead patients to believe they have had a heart attack when they had myocardial injury instead. This may lead to unnecessary anxiety and change their interactions with the health system. These patients may be started on unnecessary therapies, have inaccurate preoperative evaluations, and be labeled with a preexisting condition for the rest of their lives.

Opportunities for Quality Improvement

Systems-based quality improvement can help to ensure that patients with NIMI and T2MI are labeled appropriately and receive the proper treatment. Clinical education is the cornerstone of such efforts. Hospital medicine practitioners looking for support in understanding this issue might first partner with cardiology colleagues who may already have training materials available. Billing and coding personnel stand to benefit from greater orientation to this topic considering the complexities and errors in the coding of MI. In an attempt to help nonclinical coding personnel, leaders in the American College of Cardiology have advocated for use of the term “non-MI troponin elevation” (nMITE)¹³ to describe NIMI patients. Finally, we see an important role for EHR-embedded decision support tools to facilitate appropriate documentation and management of patients with elevated troponin. A potential care pathway, for example, could be created in partnership between hospital medicine and cardiology providers to identify which patients would benefit from cardiologist consultation.

Understanding the definitions of T1MI, T2MI, and NIMI will help clinicians to better identify the appropriate clinical care and consultation strategy for patients with elevated cardiac troponin. There are relatively few published quality improvement initiatives to help guide clinicians through these nuanced distinctions, but there is great potential in such approaches to help clinicians provide the highest value care possible.

Disclosures

No authors have any conflict of interest, financial or otherwise, to declare regarding this study.

Funding

Dr. Levy receives funding from National Institutes of Health (NIH) T32 Training Grant 5T32-HL007822.

Elevated serum troponin clearly does not equal myocardial infarction (MI). This was the strong message in the 2018 publication of the Fourth Universal Definition of Myocardial Infarction¹ (4UDMI), the first update to the international consensus document since 2012.

Most clinicians have learned how to accurately diagnose the classic Type 1 MI (T1MI) due to atherosclerotic plaque rupture; however, elevated troponin in the absence of T1MI is increasingly common due to more frequent and less discriminate troponin testing.² Patients with elevated troponin in the absence of T1MI have traditionally created confusion and variability in diagnosis, management, and documentation. Interpretation and management of elevated troponin in the absence of T1MI has become difficult.

In this clinical practice update, we aim to review the updated definition of Type 2 MI (T2MI) and nonischemic myocardial injury (NIMI), since these are the two predominant diagnoses among patients with elevated troponin in the absence of T1MI. We also provide a clinical framework for clinicians to think through elevated serum cardiac troponin levels and identify opportunities for quality improvement around this critical issue.

The presence of an elevated serum troponin level is a critical component in determining the presence of cardiac myocyte injury and possible infarction. Myocardial injury is defined as the presence of serum troponin above the 99th percentile of the upper reference limit (URL), the absolute value of which varies by assay and which applies to traditional and highly sensitive subtypes. Myocardial injury can be confusing to assess, as it can be acute or chronic.

When troponin levels are elevated but stable, this is indicative of chronic (usually nonischemic) myocardial injury, as seen, for example, in patients who have end-stage renal disease. The presence of acute injury requires a change in the troponin value—specifically a rise and/or fall in troponin levels with serial measurements. What constitutes a significant “rise and/or fall” is a matter of some debate and is not precisely defined in the 4UDMI. The percent change in the troponin value over time (relative delta) is listed as part of the criteria for acute injury when the change is greater than or equal to 20%;¹ however, clinicians should be aware that absolute delta in troponin (the change in ng/dL) has better performance characteristics³ in diagnosing acute myocardial injury. Regardless of whether clinicians use relative or absolute changes in the serum troponin level, clinical evaluation of patients with acute injury is critical to establishing whether the injury is ischemic (MI) or nonischemic (NIMI). The presence of at least one of the following is necessary to meet the current criteria for myocardial ischemia according to the fourth universal definition: new ischemic symptoms (eg, chest pain, dyspnea, etc.), new ischemic changes in the patient’s electrocardiogram (eg, new ST segment depression in leads II, III, and aVF), or cardiac imaging changes consistent with ischemic injury (eg, new wall motion abnormality in the inferior wall on echocardiography).

Following diagnosis of MI based on elevated troponin and new symptoms or signs, the cause of MI should then be determined. Type 1 MI remains defined as MI caused by atherosclerotic plaque disruption in a patient with coronary artery disease (CAD). Type 2 MI is not caused by plaque disruption but is due to a mismatch between oxygen supply and demand unrelated to acute atherothrombosis. T2MI is an ischemic myocardial injury traceable to some other illness that leads to inadequate myocyte oxygenation. Causes of T2MI are numerous, can overlap with nonischemic injury, and can include severe anemia, septic shock, rapid atrial fibrillation, and coronary dissection. While CAD may be present in patients with T2MI, it is not a requirement, and an increased demand for, or reduced supply of, myocyte oxygen alone can be sufficient to cause MI.

In the absence of clinical signs or symptoms of cardiac ischemia, clinicians should categorize patients as having a nonischemic myocardial injury. There is significant overlap between causes of T2MI and NIMI, for example, sepsis could cause either T2MI or NIMI. What distinguishes these two entities is whether the signs and symptoms for myocardial ischemia as outlined above are present. If these signs or symptoms are present, the diagnosis is T2MI. If no clinical signs or symptoms of ischemia are present, the diagnosis is NIMI. The assessment of the clinician, using all available clinical information, is pivotal. The characteristics of the three major types of myocardial injury are depicted in the Figure.

Proper distinction between infarction or injury without infarction is central to proper evaluation, treatment, and eventual documentation in patients with elevated troponin levels. In the case of T2MI and NIMI, identifying what underlying illness is causing the troponin elevation is essential for acute management.

Evaluation

Troponin elevation is associated with an elevated risk for major adverse cardiovascular events, regardless of etiology.⁴ While patients with suspected T1MI are most often evaluated by coronary angiography, this may not be necessary for patients with T2MI or NIMI. Developing an evaluation strategy for patients with T2MI or NIMI requires understanding the underlying etiology of myocardial injury. In patients with septic shock for example, there are many potential mechanisms for cardiac myocyte injury, many of which are nonischemic (eg, cytokine-mediated).⁵ Prompt evaluation and treatment of septic shock, therefore, often leads to resolution of cardiac dysfunction, and ischemic evaluation may not be necessary.⁶ In many cases of T2MI or NIMI, waiting for an acute underlying illness to resolve is necessary before deciding whether ischemic evaluation is appropriate. It is important that this decision is deferred but not forgotten though as patients with T2MI or NIMI may benefit from further cardiac evaluation. There are no society recommendations and minimal evidence to guide this evaluation, but clinical trials testing different evaluation strategies are underway.⁷ Until an optimal evidence-based evaluation strategy becomes clear, clinicians should focus on two key principles: first, determine and treat the underlying etiology; second, identify patients with traditional risk factors for CAD and consider further evaluation with either coronary angiography or cardiac imaging. Referral to a cardiologist for assistance with the latter issue, especially for challenging or equivocal cases, is encouraged.

Treatment

While T1MI therapies have a strong evidence base with high rates of appropriate treatment, there are relatively few evidence-based therapies for T2MI and NIMI. The benefits of traditional T1MI therapies should be considered in terms of each therapy’s risk-benefit profile. Among patients with T2MI or NIMI in whom atherosclerotic plaque rupture is unlikely, or in whom bleeding risk is high, antithrombotic agents such as unfractionated heparin and dual antiplatelet therapy represent low value and potentially harmful therapies.⁸ Conversely, patients with multiple risk factors for CAD may benefit from low-risk guideline directed medical therapies such as HMGCoA reductase inhibitors (ie, “statins”). Recent data suggest that lipid-lowering therapies may even be beneficial for preventing T2MI.⁹

Given the lack of evidence for therapies to treat patients with T2MI or NIMI, clinical judgment remains central to creating an optimal management plan. Clinicians should consider consultation with a cardiologist any time there is ambiguity in whether the diagnosis is T1MI or T2MI. For example, postoperative patients represent a particularly challenging clinical scenario due to the difficulty of assessing ischemic signs and symptoms in the operating room. In this setting, early evaluation by a cardiologist has been shown to improve outcomes.¹⁰

Documentation

Documentation of non-ST elevation MI (NSTEMI) for every case of elevated troponin, rather than using the more specific T1MI, T2MI, or NIMI terminology, can have adverse consequences for health systems. From a coding perspective, the terms STEMI and NSTEMI mean T1MI, and the ICD-10 codes used to identify T1MI patients for value-focused programs frequently include patients with T2MI and NIMI due to imprecise documentation.¹¹ When T2MI and NIMI are imprecisely documented as NSTEMI, health systems and clinicians are held to the T1MI care standards. This can negatively skew the performance of a health system or individual clinician because T2MI and NIMI patients have worse outcomes than T1MI patients.⁴ Inaccurate categorization of patients can lead to inaccurate quality and registry reporting, which may hinder the ability of health systems to monitor and implement quality improvement programs for MI patients. The distinction between T1MI and T2MI in documentation is all the more important now that a new ICD-10 code exists for T2MI (I21.A1), which allows clinicians to more precisely identify these patients, both clinically and administratively, as distinct from T1MI patients.¹² While there is no similarly specific ICD-10 code for NIMI, using the appropriate terminology in documentation should prompt coding personnel to use a code for “other abnormal findings of blood chemistry,” reflecting cardiac biomarker elevation (R79.89), rather than using one of the T1MI codes. Clinicians may not be able to determine the etiology of troponin elevation in the initial phase of a hospitalization, but a definitive diagnosis should be documented in the discharge summary.

From the patient perspective, documentation using STEMI and NSTEMI can mislead clinicians, given that this terminology does not specify the underlying cause (ie, plaque rupture or oxygen supply-demand mismatch), potentially leading to delayed initiation of appropriate therapy. Incorrect documentation, using STEMI/NSTEMI language or incorrectly labeling T2MI and NIMI, may lead patients to believe they have had a heart attack when they had myocardial injury instead. This may lead to unnecessary anxiety and change their interactions with the health system. These patients may be started on unnecessary therapies, have inaccurate preoperative evaluations, and be labeled with a preexisting condition for the rest of their lives.

Opportunities for Quality Improvement

Systems-based quality improvement can help to ensure that patients with NIMI and T2MI are labeled appropriately and receive the proper treatment. Clinical education is the cornerstone of such efforts. Hospital medicine practitioners looking for support in understanding this issue might first partner with cardiology colleagues who may already have training materials available. Billing and coding personnel stand to benefit from greater orientation to this topic considering the complexities and errors in the coding of MI. In an attempt to help nonclinical coding personnel, leaders in the American College of Cardiology have advocated for use of the term “non-MI troponin elevation” (nMITE)¹³ to describe NIMI patients. Finally, we see an important role for EHR-embedded decision support tools to facilitate appropriate documentation and management of patients with elevated troponin. A potential care pathway, for example, could be created in partnership between hospital medicine and cardiology providers to identify which patients would benefit from cardiologist consultation.

Understanding the definitions of T1MI, T2MI, and NIMI will help clinicians to better identify the appropriate clinical care and consultation strategy for patients with elevated cardiac troponin. There are relatively few published quality improvement initiatives to help guide clinicians through these nuanced distinctions, but there is great potential in such approaches to help clinicians provide the highest value care possible.

Disclosures

No authors have any conflict of interest, financial or otherwise, to declare regarding this study.

Funding

Dr. Levy receives funding from National Institutes of Health (NIH) T32 Training Grant 5T32-HL007822.

Community-acquired pneumonia (CAP) accounts for more than 1.5 million adult hospitalizations and 100,000 deaths each year in the United States.¹ Antibiotic overuse in the hospital setting is an important contributor to the rise of antibiotic resistance, prompting increased efforts to limit inappropriate antibiotic use in hospitals.² Procalcitonin, a precursor of the hormone calcitonin, is upregulated in bacterial infections and downregulated in viral infections. The US Food and Drug Administration has approved it as a serum biomarker to assist clinicians with decisions about using antibiotics.³

There is no consensus on how to best use procalcitonin in the management of CAP. We provide a practical update that includes a review of recent literature, added secondary analysis, and expert opinion surrounding the use of procalcitonin in the diagnosis and management of CAP in hospitalized adults.

Initial procalcitonin levels do not sufficiently exclude bacterial etiologies of CAP to withhold antibiotic prescription safely. The largest diagnostic accuracy study of procalcitonin in the diagnosis of CAP was a subanalysis of the Etiology of Pneumonia in the Community Study.⁴ A total of 1,735 adults hospitalized with CAP received procalcitonin testing along with systematic pathogen testing. The area under the receiver operating characteristic curve for procalcitonin in discriminating bacterial pathogens from viral pathogens was 0.73 (95% CI, 0.69-0.77). A procalcitonin cut-off of 0.1 ng/mL resulted in 80.9% (95% CI, 75.3%-85.7%) sensitivity and 51.6% (95% CI, 46.6%-56.5%) specificity for identification of any bacterial pathogen.

In a secondary analysis of this study, we calculated multilevel likelihood ratios (LRs) for ranges of procalcitonin values to determine the diagnostic accuracy of procalcitonin in distinguishing bacterial from viral etiologies of CAP (Table). Multilevel LRs offer more useful diagnostic information than dichotomizing at specified cut-points.⁵ A procalcitonin result less than 0.1 ng/mL has a negative LR of 0.4 (95% CI, 0.3-0.5), which is not low enough to rule out bacterial CAP effectively when starting with intermediate or high pretest probability. For a low result (<0.1 ng/mL) to be useful in ruling out bacterial CAP, for example having less than a 10% posttest probability of bacterial CAP, the pretest probability would have to be no greater than 22%. Even then, a 10% posttest probability of bacterial CAP may still be too high for clinicians to withhold initial antibiotics. For procalcitonin values between 0.1 ng/mL and 1.0 ng/mL, the probability of bacterial CAP does not change significantly, with an LR of 1.0 (95% CI, 0.8-1.3). Procalcitonin values up to 5 ng/mL reach a modest positive LR of 2.3 (95% CI, 0.8-4.3). Very high values, such as those >10 ng/mL, yield a positive LR of 5.5 (95% CI, 3.2-9.7), are potentially useful in decisions to initiate antibiotics in situations of very low pretest probability of bacterial CAP. For example, a 9% pretest probability of bacterial CAP is likely below many physicians’ threshold for starting antibiotics. A procalcitonin of 12 ng/mL in this patient would increase the posttest probability to 35%, a value that would prompt many physicians to initiate antibiotics.

Overall, there is insufficient evidence to support the use of procalcitonin as a stand-alone test for ruling out bacterial CAP, limiting its use in withholding antibiotics in patients with suspected bacterial CAP.

While initial procalcitonin measurements may not affect the initial antibiotic treatment decision, procalcitonin levels thereafter can guide the duration of therapy. A meta-analysis of procalcitonin-guided treatment in patients with upper or lower respiratory tract infection (LRTI) showed that procalcitonin guidance reduces antibiotic exposure and antibiotic-related adverse effects and improves survival, albeit a small absolute mortality difference of 1.4 percentage points, primarily observed in the intensive care unit setting.⁶ Most patients included in this meta-analysis were diagnosed with LRTI (91%), and CAP was the predominant subtype of LRTI (43%). The main effect of procalcitonin guidance for patients with CAP was earlier discontinuation of antibiotic treatment. Procalcitonin-guided algorithms in these trials discouraged, or strongly discouraged, antibiotics if procalcitonin was <0.25 ng/mL or <0.1 ng/mL, respectively. In addition, serial procalcitonin measurements were used to guide discontinuation of antibiotics if procalcitonin dropped below 0.25 ng/mL, or by 80% to 90% from the peak value. This approach safely shortened the duration of therapy in patients with CAP.

There are several limitations in the interpretation and generalizability of this meta-analysis. There is large heterogeneity across the included clinical trials in design, procalcitonin protocols, clinical setting, and respiratory infection type, including bronchitis, acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and CAP. Results were consistent only in one moderate- to high-quality randomized trial specifically studying CAP in the inpatient setting.⁷ Additionally, most of these trials were conducted in Europe. Antibiotic prescribing practices may be different in the US, and prescribing practices on both continents may have changed over the years with greater awareness and appreciation of antibiotic stewardship.

The ProACT trial, the largest randomized, US multicenter trial to evaluate a procalcitonin-based algorithm to assist with antibiotic decision making, included over 1,600 emergency department patients at 14 academic medical centers.⁸ Procalcitonin guidance in this trial did not reduce antibiotic exposure compared with usual care for patients with suspected LRTI. However, its applicability to the practice of hospitalists and the inpatient setting is limited. First, only 48% of the study participants required hospitalization. Second, this study included all LRTIs, with CAP comprising just 20% of all final diagnoses. Third, the average number of antibiotic days during hospitalization for CAP was short in both groups (3.9 days in the procalcitonin group and 4.1 days in the usual care group). This relatively short antibiotic duration makes it difficult for any intervention to decrease antibiotic days meaningfully.

In a prepost controlled intervention study for inpatients at a single US tertiary care hospital, procalcitonin guidance in hospitalized patients safely reduced antibiotic use in LRTI, specifically for the discontinuation of antibiotics.⁹ The greatest benefit of procalcitonin guidance in antibiotic discontinuation was found in patients with AECOPD and patients with an admitting diagnosis of CAP, but with mild illness and a low procalcitonin. Although this prepost study suggested a safe reduction of antibiotic use due to implementation of procalcitonin guidance, the lack of randomization and the absence of a contemporaneous control group are important limitations. Given the mixed findings on the effectiveness of procalcitonin guidance for hospitalized CAP patients in the US, further investigation will be needed with large clinical trials in the inpatient setting for CAP.

There is insufficient evidence to support the use of serum procalcitonin to withhold initial antibiotics in patients with a clinical syndrome consistent with bacterial CAP. However, the literature supports the use of procalcitonin for the early discontinuation of antibiotics for cases in which the probability of bacterial CAP is low, and procalcitonin remains below 0.1 ng/mL (Figure).

Serial measurements of procalcitonin every one to two days may also be used when clinical uncertainty remains regarding the need for antibiotics. Very low or significantly decreasing procalcitonin levels in patients with CAP and no identified bacterial pathogen likely indicate the infection was not bacterial or was bacterial, but has now been adequately treated with antibiotics. For cases of proven bacterial etiology or high clinical suspicion of bacterial CAP, there is insufficient evidence to recommend the early discontinuation of antibiotics based on procalcitonin levels short of the recommended five-day course according to current guidelines.¹⁰ Future clinical trials are needed to determine if procalcitonin guidance can safely decrease the duration of antibiotic therapy for confirmed bacterial CAP to less than five days.

There are discrepancies between the apparent test characteristics of procalcitonin and the recommended antibiotic decisions in many procalcitonin algorithms. For example, algorithms discourage antibiotics when procalcitonin values are 0.1-0.24 ng/mL, and encourage (or even strongly encourage) antibiotic use for higher procalcitonin values of 0.25-1.0 ng/mL. However, the LRs for these ranges are identical and are approximately 1.0 (Table), suggesting that decision-making should be similar across the entire procalcitonin range of 0.1 to 1.0. Future clinical trials should study revised algorithms with different cut-points, including the thresholds found in our secondary analysis of multilevel LRs. Until then, we believe there is insufficient evidence to deviate from current antibiotic decision recommendations at the traditional cut-points.

While procalcitonin is an imperfect biomarker for discriminating bacterial and nonbacterial etiologies of CAP, it may still provide helpful information for the hospitalist in antibiotic decision-making in the same way we apply other commonly used clinical variables such as fever, white blood cell count, band count, and the pattern of infiltrate in chest imaging.

Procalcitonin should be interpreted cautiously in certain populations in which it has not been extensively studied (eg, immunocompromised) or in noninfectious conditions that may elevate procalcitonin, such as major physiologic stress (eg, surgery, trauma, burns) and end-stage renal disease.^12-14 Further investigation is needed to determine the efficacy and safety of procalcitonin-guided antibiotic therapy in these populations.

• Based on currently available data, a low procalcitonin value should not be used as a stand-alone test to withhold antibiotics in a patient with CAP.
• Serum procalcitonin measurements may help guide the early discontinuation of antibiotics for patients who the treating clinician judges the risks of bacterial etiology and clinical deterioration to be low.
• Interpret procalcitonin cautiously in immunocompromised patients, undergoing severe physiologic stress, or have underlying end-stage renal disease.
• Serum procalcitonin serves as an adjunct to, rather than a substitute for, clinical judgment.

Disclosures

Dr Choi, Dr Evans, and Dr Glesby have nothing to disclose. Dr Self reports receiving prior research funding from BRAHMS/Thermo-Fisher and BioMerieux for studies on procalcitonin. Dr Self reports personal fees from Inflammatix, grants from Axis Shield, Rapid Pathogen Screening, and BioMerieux, all outside the submitted work. Dr McCarthy reports receiving research funding from Allergan outside the submitted work. Dr Simon reports receiving consulting fees from Roche Diagnostics.

Community-acquired pneumonia (CAP) accounts for more than 1.5 million adult hospitalizations and 100,000 deaths each year in the United States.¹ Antibiotic overuse in the hospital setting is an important contributor to the rise of antibiotic resistance, prompting increased efforts to limit inappropriate antibiotic use in hospitals.² Procalcitonin, a precursor of the hormone calcitonin, is upregulated in bacterial infections and downregulated in viral infections. The US Food and Drug Administration has approved it as a serum biomarker to assist clinicians with decisions about using antibiotics.³

There is no consensus on how to best use procalcitonin in the management of CAP. We provide a practical update that includes a review of recent literature, added secondary analysis, and expert opinion surrounding the use of procalcitonin in the diagnosis and management of CAP in hospitalized adults.

Initial procalcitonin levels do not sufficiently exclude bacterial etiologies of CAP to withhold antibiotic prescription safely. The largest diagnostic accuracy study of procalcitonin in the diagnosis of CAP was a subanalysis of the Etiology of Pneumonia in the Community Study.⁴ A total of 1,735 adults hospitalized with CAP received procalcitonin testing along with systematic pathogen testing. The area under the receiver operating characteristic curve for procalcitonin in discriminating bacterial pathogens from viral pathogens was 0.73 (95% CI, 0.69-0.77). A procalcitonin cut-off of 0.1 ng/mL resulted in 80.9% (95% CI, 75.3%-85.7%) sensitivity and 51.6% (95% CI, 46.6%-56.5%) specificity for identification of any bacterial pathogen.

In a secondary analysis of this study, we calculated multilevel likelihood ratios (LRs) for ranges of procalcitonin values to determine the diagnostic accuracy of procalcitonin in distinguishing bacterial from viral etiologies of CAP (Table). Multilevel LRs offer more useful diagnostic information than dichotomizing at specified cut-points.⁵ A procalcitonin result less than 0.1 ng/mL has a negative LR of 0.4 (95% CI, 0.3-0.5), which is not low enough to rule out bacterial CAP effectively when starting with intermediate or high pretest probability. For a low result (<0.1 ng/mL) to be useful in ruling out bacterial CAP, for example having less than a 10% posttest probability of bacterial CAP, the pretest probability would have to be no greater than 22%. Even then, a 10% posttest probability of bacterial CAP may still be too high for clinicians to withhold initial antibiotics. For procalcitonin values between 0.1 ng/mL and 1.0 ng/mL, the probability of bacterial CAP does not change significantly, with an LR of 1.0 (95% CI, 0.8-1.3). Procalcitonin values up to 5 ng/mL reach a modest positive LR of 2.3 (95% CI, 0.8-4.3). Very high values, such as those >10 ng/mL, yield a positive LR of 5.5 (95% CI, 3.2-9.7), are potentially useful in decisions to initiate antibiotics in situations of very low pretest probability of bacterial CAP. For example, a 9% pretest probability of bacterial CAP is likely below many physicians’ threshold for starting antibiotics. A procalcitonin of 12 ng/mL in this patient would increase the posttest probability to 35%, a value that would prompt many physicians to initiate antibiotics.

Overall, there is insufficient evidence to support the use of procalcitonin as a stand-alone test for ruling out bacterial CAP, limiting its use in withholding antibiotics in patients with suspected bacterial CAP.

While initial procalcitonin measurements may not affect the initial antibiotic treatment decision, procalcitonin levels thereafter can guide the duration of therapy. A meta-analysis of procalcitonin-guided treatment in patients with upper or lower respiratory tract infection (LRTI) showed that procalcitonin guidance reduces antibiotic exposure and antibiotic-related adverse effects and improves survival, albeit a small absolute mortality difference of 1.4 percentage points, primarily observed in the intensive care unit setting.⁶ Most patients included in this meta-analysis were diagnosed with LRTI (91%), and CAP was the predominant subtype of LRTI (43%). The main effect of procalcitonin guidance for patients with CAP was earlier discontinuation of antibiotic treatment. Procalcitonin-guided algorithms in these trials discouraged, or strongly discouraged, antibiotics if procalcitonin was <0.25 ng/mL or <0.1 ng/mL, respectively. In addition, serial procalcitonin measurements were used to guide discontinuation of antibiotics if procalcitonin dropped below 0.25 ng/mL, or by 80% to 90% from the peak value. This approach safely shortened the duration of therapy in patients with CAP.

There are several limitations in the interpretation and generalizability of this meta-analysis. There is large heterogeneity across the included clinical trials in design, procalcitonin protocols, clinical setting, and respiratory infection type, including bronchitis, acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and CAP. Results were consistent only in one moderate- to high-quality randomized trial specifically studying CAP in the inpatient setting.⁷ Additionally, most of these trials were conducted in Europe. Antibiotic prescribing practices may be different in the US, and prescribing practices on both continents may have changed over the years with greater awareness and appreciation of antibiotic stewardship.

The ProACT trial, the largest randomized, US multicenter trial to evaluate a procalcitonin-based algorithm to assist with antibiotic decision making, included over 1,600 emergency department patients at 14 academic medical centers.⁸ Procalcitonin guidance in this trial did not reduce antibiotic exposure compared with usual care for patients with suspected LRTI. However, its applicability to the practice of hospitalists and the inpatient setting is limited. First, only 48% of the study participants required hospitalization. Second, this study included all LRTIs, with CAP comprising just 20% of all final diagnoses. Third, the average number of antibiotic days during hospitalization for CAP was short in both groups (3.9 days in the procalcitonin group and 4.1 days in the usual care group). This relatively short antibiotic duration makes it difficult for any intervention to decrease antibiotic days meaningfully.

In a prepost controlled intervention study for inpatients at a single US tertiary care hospital, procalcitonin guidance in hospitalized patients safely reduced antibiotic use in LRTI, specifically for the discontinuation of antibiotics.⁹ The greatest benefit of procalcitonin guidance in antibiotic discontinuation was found in patients with AECOPD and patients with an admitting diagnosis of CAP, but with mild illness and a low procalcitonin. Although this prepost study suggested a safe reduction of antibiotic use due to implementation of procalcitonin guidance, the lack of randomization and the absence of a contemporaneous control group are important limitations. Given the mixed findings on the effectiveness of procalcitonin guidance for hospitalized CAP patients in the US, further investigation will be needed with large clinical trials in the inpatient setting for CAP.

There is insufficient evidence to support the use of serum procalcitonin to withhold initial antibiotics in patients with a clinical syndrome consistent with bacterial CAP. However, the literature supports the use of procalcitonin for the early discontinuation of antibiotics for cases in which the probability of bacterial CAP is low, and procalcitonin remains below 0.1 ng/mL (Figure).

Serial measurements of procalcitonin every one to two days may also be used when clinical uncertainty remains regarding the need for antibiotics. Very low or significantly decreasing procalcitonin levels in patients with CAP and no identified bacterial pathogen likely indicate the infection was not bacterial or was bacterial, but has now been adequately treated with antibiotics. For cases of proven bacterial etiology or high clinical suspicion of bacterial CAP, there is insufficient evidence to recommend the early discontinuation of antibiotics based on procalcitonin levels short of the recommended five-day course according to current guidelines.¹⁰ Future clinical trials are needed to determine if procalcitonin guidance can safely decrease the duration of antibiotic therapy for confirmed bacterial CAP to less than five days.

There are discrepancies between the apparent test characteristics of procalcitonin and the recommended antibiotic decisions in many procalcitonin algorithms. For example, algorithms discourage antibiotics when procalcitonin values are 0.1-0.24 ng/mL, and encourage (or even strongly encourage) antibiotic use for higher procalcitonin values of 0.25-1.0 ng/mL. However, the LRs for these ranges are identical and are approximately 1.0 (Table), suggesting that decision-making should be similar across the entire procalcitonin range of 0.1 to 1.0. Future clinical trials should study revised algorithms with different cut-points, including the thresholds found in our secondary analysis of multilevel LRs. Until then, we believe there is insufficient evidence to deviate from current antibiotic decision recommendations at the traditional cut-points.

While procalcitonin is an imperfect biomarker for discriminating bacterial and nonbacterial etiologies of CAP, it may still provide helpful information for the hospitalist in antibiotic decision-making in the same way we apply other commonly used clinical variables such as fever, white blood cell count, band count, and the pattern of infiltrate in chest imaging.

Procalcitonin should be interpreted cautiously in certain populations in which it has not been extensively studied (eg, immunocompromised) or in noninfectious conditions that may elevate procalcitonin, such as major physiologic stress (eg, surgery, trauma, burns) and end-stage renal disease.^12-14 Further investigation is needed to determine the efficacy and safety of procalcitonin-guided antibiotic therapy in these populations.

• Based on currently available data, a low procalcitonin value should not be used as a stand-alone test to withhold antibiotics in a patient with CAP.
• Serum procalcitonin measurements may help guide the early discontinuation of antibiotics for patients who the treating clinician judges the risks of bacterial etiology and clinical deterioration to be low.
• Interpret procalcitonin cautiously in immunocompromised patients, undergoing severe physiologic stress, or have underlying end-stage renal disease.
• Serum procalcitonin serves as an adjunct to, rather than a substitute for, clinical judgment.

Disclosures

Dr Choi, Dr Evans, and Dr Glesby have nothing to disclose. Dr Self reports receiving prior research funding from BRAHMS/Thermo-Fisher and BioMerieux for studies on procalcitonin. Dr Self reports personal fees from Inflammatix, grants from Axis Shield, Rapid Pathogen Screening, and BioMerieux, all outside the submitted work. Dr McCarthy reports receiving research funding from Allergan outside the submitted work. Dr Simon reports receiving consulting fees from Roche Diagnostics.

Community-acquired pneumonia (CAP) accounts for more than 1.5 million adult hospitalizations and 100,000 deaths each year in the United States.¹ Antibiotic overuse in the hospital setting is an important contributor to the rise of antibiotic resistance, prompting increased efforts to limit inappropriate antibiotic use in hospitals.² Procalcitonin, a precursor of the hormone calcitonin, is upregulated in bacterial infections and downregulated in viral infections. The US Food and Drug Administration has approved it as a serum biomarker to assist clinicians with decisions about using antibiotics.³

There is no consensus on how to best use procalcitonin in the management of CAP. We provide a practical update that includes a review of recent literature, added secondary analysis, and expert opinion surrounding the use of procalcitonin in the diagnosis and management of CAP in hospitalized adults.

Initial procalcitonin levels do not sufficiently exclude bacterial etiologies of CAP to withhold antibiotic prescription safely. The largest diagnostic accuracy study of procalcitonin in the diagnosis of CAP was a subanalysis of the Etiology of Pneumonia in the Community Study.⁴ A total of 1,735 adults hospitalized with CAP received procalcitonin testing along with systematic pathogen testing. The area under the receiver operating characteristic curve for procalcitonin in discriminating bacterial pathogens from viral pathogens was 0.73 (95% CI, 0.69-0.77). A procalcitonin cut-off of 0.1 ng/mL resulted in 80.9% (95% CI, 75.3%-85.7%) sensitivity and 51.6% (95% CI, 46.6%-56.5%) specificity for identification of any bacterial pathogen.

In a secondary analysis of this study, we calculated multilevel likelihood ratios (LRs) for ranges of procalcitonin values to determine the diagnostic accuracy of procalcitonin in distinguishing bacterial from viral etiologies of CAP (Table). Multilevel LRs offer more useful diagnostic information than dichotomizing at specified cut-points.⁵ A procalcitonin result less than 0.1 ng/mL has a negative LR of 0.4 (95% CI, 0.3-0.5), which is not low enough to rule out bacterial CAP effectively when starting with intermediate or high pretest probability. For a low result (<0.1 ng/mL) to be useful in ruling out bacterial CAP, for example having less than a 10% posttest probability of bacterial CAP, the pretest probability would have to be no greater than 22%. Even then, a 10% posttest probability of bacterial CAP may still be too high for clinicians to withhold initial antibiotics. For procalcitonin values between 0.1 ng/mL and 1.0 ng/mL, the probability of bacterial CAP does not change significantly, with an LR of 1.0 (95% CI, 0.8-1.3). Procalcitonin values up to 5 ng/mL reach a modest positive LR of 2.3 (95% CI, 0.8-4.3). Very high values, such as those >10 ng/mL, yield a positive LR of 5.5 (95% CI, 3.2-9.7), are potentially useful in decisions to initiate antibiotics in situations of very low pretest probability of bacterial CAP. For example, a 9% pretest probability of bacterial CAP is likely below many physicians’ threshold for starting antibiotics. A procalcitonin of 12 ng/mL in this patient would increase the posttest probability to 35%, a value that would prompt many physicians to initiate antibiotics.

Overall, there is insufficient evidence to support the use of procalcitonin as a stand-alone test for ruling out bacterial CAP, limiting its use in withholding antibiotics in patients with suspected bacterial CAP.

While initial procalcitonin measurements may not affect the initial antibiotic treatment decision, procalcitonin levels thereafter can guide the duration of therapy. A meta-analysis of procalcitonin-guided treatment in patients with upper or lower respiratory tract infection (LRTI) showed that procalcitonin guidance reduces antibiotic exposure and antibiotic-related adverse effects and improves survival, albeit a small absolute mortality difference of 1.4 percentage points, primarily observed in the intensive care unit setting.⁶ Most patients included in this meta-analysis were diagnosed with LRTI (91%), and CAP was the predominant subtype of LRTI (43%). The main effect of procalcitonin guidance for patients with CAP was earlier discontinuation of antibiotic treatment. Procalcitonin-guided algorithms in these trials discouraged, or strongly discouraged, antibiotics if procalcitonin was <0.25 ng/mL or <0.1 ng/mL, respectively. In addition, serial procalcitonin measurements were used to guide discontinuation of antibiotics if procalcitonin dropped below 0.25 ng/mL, or by 80% to 90% from the peak value. This approach safely shortened the duration of therapy in patients with CAP.

There are several limitations in the interpretation and generalizability of this meta-analysis. There is large heterogeneity across the included clinical trials in design, procalcitonin protocols, clinical setting, and respiratory infection type, including bronchitis, acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and CAP. Results were consistent only in one moderate- to high-quality randomized trial specifically studying CAP in the inpatient setting.⁷ Additionally, most of these trials were conducted in Europe. Antibiotic prescribing practices may be different in the US, and prescribing practices on both continents may have changed over the years with greater awareness and appreciation of antibiotic stewardship.

The ProACT trial, the largest randomized, US multicenter trial to evaluate a procalcitonin-based algorithm to assist with antibiotic decision making, included over 1,600 emergency department patients at 14 academic medical centers.⁸ Procalcitonin guidance in this trial did not reduce antibiotic exposure compared with usual care for patients with suspected LRTI. However, its applicability to the practice of hospitalists and the inpatient setting is limited. First, only 48% of the study participants required hospitalization. Second, this study included all LRTIs, with CAP comprising just 20% of all final diagnoses. Third, the average number of antibiotic days during hospitalization for CAP was short in both groups (3.9 days in the procalcitonin group and 4.1 days in the usual care group). This relatively short antibiotic duration makes it difficult for any intervention to decrease antibiotic days meaningfully.

In a prepost controlled intervention study for inpatients at a single US tertiary care hospital, procalcitonin guidance in hospitalized patients safely reduced antibiotic use in LRTI, specifically for the discontinuation of antibiotics.⁹ The greatest benefit of procalcitonin guidance in antibiotic discontinuation was found in patients with AECOPD and patients with an admitting diagnosis of CAP, but with mild illness and a low procalcitonin. Although this prepost study suggested a safe reduction of antibiotic use due to implementation of procalcitonin guidance, the lack of randomization and the absence of a contemporaneous control group are important limitations. Given the mixed findings on the effectiveness of procalcitonin guidance for hospitalized CAP patients in the US, further investigation will be needed with large clinical trials in the inpatient setting for CAP.

There is insufficient evidence to support the use of serum procalcitonin to withhold initial antibiotics in patients with a clinical syndrome consistent with bacterial CAP. However, the literature supports the use of procalcitonin for the early discontinuation of antibiotics for cases in which the probability of bacterial CAP is low, and procalcitonin remains below 0.1 ng/mL (Figure).

Serial measurements of procalcitonin every one to two days may also be used when clinical uncertainty remains regarding the need for antibiotics. Very low or significantly decreasing procalcitonin levels in patients with CAP and no identified bacterial pathogen likely indicate the infection was not bacterial or was bacterial, but has now been adequately treated with antibiotics. For cases of proven bacterial etiology or high clinical suspicion of bacterial CAP, there is insufficient evidence to recommend the early discontinuation of antibiotics based on procalcitonin levels short of the recommended five-day course according to current guidelines.¹⁰ Future clinical trials are needed to determine if procalcitonin guidance can safely decrease the duration of antibiotic therapy for confirmed bacterial CAP to less than five days.

There are discrepancies between the apparent test characteristics of procalcitonin and the recommended antibiotic decisions in many procalcitonin algorithms. For example, algorithms discourage antibiotics when procalcitonin values are 0.1-0.24 ng/mL, and encourage (or even strongly encourage) antibiotic use for higher procalcitonin values of 0.25-1.0 ng/mL. However, the LRs for these ranges are identical and are approximately 1.0 (Table), suggesting that decision-making should be similar across the entire procalcitonin range of 0.1 to 1.0. Future clinical trials should study revised algorithms with different cut-points, including the thresholds found in our secondary analysis of multilevel LRs. Until then, we believe there is insufficient evidence to deviate from current antibiotic decision recommendations at the traditional cut-points.

While procalcitonin is an imperfect biomarker for discriminating bacterial and nonbacterial etiologies of CAP, it may still provide helpful information for the hospitalist in antibiotic decision-making in the same way we apply other commonly used clinical variables such as fever, white blood cell count, band count, and the pattern of infiltrate in chest imaging.

Procalcitonin should be interpreted cautiously in certain populations in which it has not been extensively studied (eg, immunocompromised) or in noninfectious conditions that may elevate procalcitonin, such as major physiologic stress (eg, surgery, trauma, burns) and end-stage renal disease.^12-14 Further investigation is needed to determine the efficacy and safety of procalcitonin-guided antibiotic therapy in these populations.

• Based on currently available data, a low procalcitonin value should not be used as a stand-alone test to withhold antibiotics in a patient with CAP.
• Serum procalcitonin measurements may help guide the early discontinuation of antibiotics for patients who the treating clinician judges the risks of bacterial etiology and clinical deterioration to be low.
• Interpret procalcitonin cautiously in immunocompromised patients, undergoing severe physiologic stress, or have underlying end-stage renal disease.
• Serum procalcitonin serves as an adjunct to, rather than a substitute for, clinical judgment.

Disclosures

Dr Choi, Dr Evans, and Dr Glesby have nothing to disclose. Dr Self reports receiving prior research funding from BRAHMS/Thermo-Fisher and BioMerieux for studies on procalcitonin. Dr Self reports personal fees from Inflammatix, grants from Axis Shield, Rapid Pathogen Screening, and BioMerieux, all outside the submitted work. Dr McCarthy reports receiving research funding from Allergan outside the submitted work. Dr Simon reports receiving consulting fees from Roche Diagnostics.

Venous thromboembolism (VTE), comprising deep venous thrombosis and pulmonary embolism (PE),¹ is a serious medical condition that results in preventable morbidity and mortality.^1-5 VTE affects all age groups, all races/ethnicities, and both genders, but there are known factors that increase the risk of developing VTE (eg, advanced age, undergoing surgery, hospitalization, and immobility).^1-3,5-7 Prevention of VTE among hospitalized patients is of paramount importance to avoid preventable death, chronic illness/long-term complications,⁸ longer hospital stays, and increased hospital costs.⁹ Fortunately, there is clear evidence that provision of appropriate prophylaxis can decrease the risk of a VTE event occurring, and broadly accepted best-practice guidelines reflect this evidence.^3,5

Given the inadequacy of current VTE-related quality measures to identify actionable failures in the provision of VTE prophylaxis, our group created a VTE process-of-care measure to assess adherence to the components of VTE prophylaxis: (1) early ambulation, (2) mechanical prophylaxis (sequential compression devices [SCDs]), and (3) chemoprophylaxis administered at the correct dose and frequency for the duration of the patient’s hospital stay.^3,10,11 This quality measure was conceived, created, and iteratively revised to measure whether optimal care is provided to patients throughout their hospitalization and identify actionable areas in which failures of care occur, in order to decrease the risk of a VTE event. Data from our institution provided evidence that while ambulation and SCD component measure adherence is high, chemoprophylaxis adherence required significant improvement.¹⁰ When chemoprophylaxis process measure adherence data were analyzed further, a major failure mode was patient refusal of one or more doses. However, the drivers of patient refusal are not well defined in the literature, and previous studies have called for a greater focus on developing interventions to improve VTE chemoprophylaxis administration.¹²

Previous research has shown that nurses can influence patient compliance with VTE prophylaxis.^13-15 A mixed-methods study by Elder et al. found that nurses in units with high rates of failure to provide optimal chemoprophylaxis offered the medication as optional, leading researchers to conclude that nurses perceived chemoprophylaxis as discretionary.¹³ Another study by Lee et al., conducted a survey of bedside registered nurses and identified nurses’ lack of education on VTE prevention as a significant barrier to providing care.¹⁴ These studies show that multiple levels of influence impact how nurses provide VTE chemoprophylaxis, particularly when they encounter patients who refuse chemoprophylaxis.

To explore the nuance and interplay of multiple influences, we used the Theoretical Domains Framework (TDF), an integrative framework that applies theoretical approaches to interventions aimed at behavior change.^15-18 The framework contains 14 interrelated domains that characterize the behavior being studied, in this case, administration of VTE chemoprophylaxis. Consequently, we designed a nurse-focused, qualitative evaluation with the objective to identify nursing-related barriers to administration of VTE chemoprophylaxis.

Inpatient Unit Selection

The study team accessed data from the hospital’s Enterprise Data Warehouse to review patient refusal rates of VTE chemoprophylaxis for each inpatient unit in the hospital. Patient refusal was utilized as a proxy measure for the behavior of nurses attempting to administer VTE chemoprophylaxis. Of the 14 medical and surgical units in the hospital, two medical and two surgical units were selected to participate in the qualitative evaluation based on having the highest patient refusal rates. One unit (surgical) was also selected to serve as a benchmark because it had the lowest patient refusal rate. Table 1 includes the refusal rates for the five units. Given the low refusal rate for the best performing unit, we suspected that it would be possible to decrease the patient refusal rate for other units with similar patient populations and interprofessional teams at the institution.

Observations

We observed chemoprophylaxis administration on the five units to understand the process for ordering and administering chemoprophylaxis. An observation protocol was utilized to document the date, time, and location of the observation as well as descriptive notes including accounts of particular events.^19,20 Observations occurred in May 2016 and informed the creation of a process map outlining the procedure for ordering and administering VTE chemoprophylaxis. The process map was utilized to create the focus group interview guide and ensure the interview guide included pertinent questions for each step of the process (Appendix A).

Focus Group Interviews

We conducted focus group interviews with day and night shift nurses on the five units to assess nurses’ understanding of VTE chemoprophylaxis and nurses’ perceptions of barriers to administration of VTE chemoprophylaxis. The study team chose to conduct focus group interviews in an effort to maximize participation and to speak with multiple nurses within a shorter period of time. The focus group structure allowed the study team to speak with nurses during their shifts, as one could briefly step out, if required, for patient care and return to rejoin the discussion.

We developed a semistructured interview guide²¹ with questions focused on identifying nurses’ perceptions of guideline-recommended care for VTE chemoprophylaxis, where they learned these guidelines, how nurses discuss chemoprophylaxis with patients, how they handle the conversation with patients who refuse, and if there are times when chemoprophylaxis is not necessary. The interview guide was vetted by a multidisciplinary team consisting of clinical nursing coordinators and nurse managers from medical and surgical units, hospital quality leaders, surgeons and general internists, and qualitative research experts. The interview guide is included as Appendix B.

The unit clinical coordinators and nurse managers identified dates and times for the focus groups that would be minimally disruptive to the unit. For each of the four units with a high patient refusal rate, two focus groups were conducted during the lunch hour and one was conducted at the end of the night shift to ensure that both day and night shift nurses were included in the study. Two focus groups were conducted with the best-practice unit during the lunch hour. For each focus group, the clinical coordinator identified two to eight nurses who could step away from patient care to participate or who had completed their shifts. In total, approximately 67 nurses participated in the focus groups.

The focus groups (n = 14) lasted approximately 40 minutes during May and June 2016. Two members of the study team cofacilitated interviews, which were recorded and transcribed verbatim.

Coding and Data Analysis

To develop the code book, the study team, consisting of three qualitative researchers, independently read one focus group transcript and applied the TDF domains to the nurses’ perceptions of barriers to administration of VTE chemoprophylaxis.^21-24 In addition to coding by domain, the study team also coded nursing perceptions as barriers or facilitators. The study team reviewed the coded transcript and reconciled any differences in coding. This process was repeated for a second transcript, and then all remaining transcripts were assigned to two out of three study team members for coding, with the entire study team meeting to reconcile any differences. If necessary, the team member who did not code a transcript acted as the tie-breaker if there were discrepancies in codes that could not be reconciled.

Once coding was completed, we identified the TDF domains that were most relevant to the administration of VTE chemoprophylaxis.¹⁶ Member checking (testing the analysis, interpretations, and conclusions with members of those groups from whom the data were originally obtained) was performed with the four clinical nursing coordinators and four nurse managers from the participating units to establish face validity of the themes identified from the focus group interviews.²⁵

The study team used MaxQDA, V12 (Berlin, Germany) to support data coding and analysis.²⁶ The Northwestern University institutional review board office deemed this project research on nonhuman-subjects because it focused on the process of providing VTE chemoprophylaxis and not about the patients themselves. The purpose of the study was explained at the beginning of each focus group, and nurses gave verbal consent to have the focus group recorded.

We conducted 14 focus groups with day and night shift nurses from five units (two medical and three surgical) at a single institution. All nurses invited to participate in a focus group agreed to participate. The data were coded and grouped by domain and identified as barriers or facilitators. The findings included below are for the domains most relevant to the provision of VTE prophylaxis. Table 2 provides illustrative verbatim quotes for each domain that was represented in the focus groups.

Knowledge

All interviewees recognized that providing some form of prophylaxis to mitigate the risk of a VTE event is essential. Some nurses stated that seeing a patient ambulating meant they would consider not administering prescribed chemoprophylaxis, while others would try to negotiate with patients by asking the patient to allow one dose of chemoprophylaxis prescribed two to three times daily because it was better than receiving no doses.

Environmental Context and Resources

Multiple barriers to providing optimal care were associated with the environmental context and a lack of resources. There was a lack of accessible, comprehensive, patient-centered education materials on VTE chemoprophylaxis to supplement a nurse’s explanation about the importance of chemoprophylaxis. Furthermore, many nurses cited the perceived patient pain of chemoprophylaxis injections as the main deterrent to patient compliance, especially subcutaneous heparin injections, which occur up to three times in 24 hours and often cause more pain at the site of injection than low-molecular-weight heparin. Nurses felt that transitioning patients from receiving subcutaneous heparin injections to receiving low-molecular-weight heparin could be a main driver to reduce patient refusals.

Skills

Nurses felt inadequately equipped to handle patient refusals. Many said that patient refusal of treatments was never discussed in nursing school. As a result, when patients refused treatments, the nurses did not know how to handle the situation. They felt that they lacked the tools and techniques to persuade the patient to comply.

Beliefs about Capabilities

Nurses did not know their own patient refusal rate or benchmarks of an acceptable refusal rate in contrast to one that is too high. Without this feedback, they were unable to assess their own behavior or performance related to providing VTE chemoprophylaxis.

Nurses play a critical role in providing VTE chemoprophylaxis to patients throughout their hospitalization. This study provided a unique opportunity to perform an in-depth, qualitative analysis of the barriers nurses face in providing patients with VTE chemoprophylaxis as part of their daily work caring for patients. We discovered several nursing-related barriers to the provision of VTE chemoprophylaxis, including lack of knowledge, resources, skill, and misconceptions of their capability to provide VTE chemoprophylaxis. We used a bottom-up approach by incorporating the voices of unit nurses, clinical coordinators, and nurse managers to understand potential barriers. Our findings brought to light the challenge of delivering standardized care in an area of care that is generally agreed upon, yet not fully followed. Some nurses display greater proficiency than others at communicating with patients who do not understand their risk for VTE and need for chemoprophylaxis. Furthermore, there is a pronounced misconception around the delivery of VTE chemoprophylaxis. Nurses have the inaccurate belief that even if ordered, chemoprophylaxis is not required. This misconception was widespread among nurses taking care of both medical and surgical patients. These factors appear to be modifiable targets for quality improvement and highlight the need for a skills-based education during the new hire onboarding process, as well as ongoing reeducation to ensure nursing staff have the skills to appropriately provide best-practice care for VTE chemoprophylaxis. Nurses felt ownership of the results of the qualitative evaluation because they were included in every aspect from the beginning.²⁷ This sense of ownership will support future quality improvement efforts to develop a skills-based intervention to improve the provision of VTE chemoprophylaxis.^18,27

This study has certain limitations. First, it was a qualitative study assessing nursing-related barriers to providing VTE chemoprophylaxis at a single institution, and the results cannot be generalized broadly. However, the techniques and results are transferable to other hospital settings and other clinical care situations. Thus, we believe that other institutions can utilize our methods and that similar lessons can be learned and applied. Furthermore, the validity of our study is bolstered by concordance between the results of this study and those of other studies conducted on the topic of provision of VTE prophylaxis by nurses.^13-15,21 Other studies utilized observations and surveys to determine potential nurse-related barriers to the provision of VTE prophylaxis, such as lack of knowledge and the belief that the need for prophylaxis can be determined based on whether or not the patient is ambulating;^13,14 however, by utilizing focus group interviews, we allowed nurses to speak in their own voices about their experiences with VTE prophylaxis, and we were able to delve deeper and identify additional barriers that emerged from discussions with nurses, such as the lack of skill and misconceptions of capability.^28,29 Second, the study focused solely on nurses. Additional initiatives are underway to assess the roles of resident physicians, attending physicians, and patients in the provision of VTE prophylaxis.

Nursing-related barriers to the provision of VTE chemoprophylaxis include a lack of knowledge, resources, skills, and misconceptions of the consequences of missed elements of VTE prophylaxis. Future initiatives will focus on equipping nurses to have meaningful conversations with patients and engaging patients in their care through development of a multifaceted bundle of interventions. Furthermore, similar methods of qualitative inquiry will be used to identify the role of resident and attending physicians and patients in the provision of VTE chemoprophylaxis.

Acknowledgments

The authors thank Sonali Oberoi, Joanne Prinz, Nancy Tomaska, and Kate Paredes, as well as all the nurses who participated in focus group interviews for this study and the nurse managers and clinical coordinators who helped to schedule the focus group interviews.

Disclosures

The authors declare that they have no competing interests.

Funding

This study was funded by the Surgical Outcomes and Quality Improvement Center at Northwestern University.

Venous thromboembolism (VTE), comprising deep venous thrombosis and pulmonary embolism (PE),¹ is a serious medical condition that results in preventable morbidity and mortality.^1-5 VTE affects all age groups, all races/ethnicities, and both genders, but there are known factors that increase the risk of developing VTE (eg, advanced age, undergoing surgery, hospitalization, and immobility).^1-3,5-7 Prevention of VTE among hospitalized patients is of paramount importance to avoid preventable death, chronic illness/long-term complications,⁸ longer hospital stays, and increased hospital costs.⁹ Fortunately, there is clear evidence that provision of appropriate prophylaxis can decrease the risk of a VTE event occurring, and broadly accepted best-practice guidelines reflect this evidence.^3,5

Given the inadequacy of current VTE-related quality measures to identify actionable failures in the provision of VTE prophylaxis, our group created a VTE process-of-care measure to assess adherence to the components of VTE prophylaxis: (1) early ambulation, (2) mechanical prophylaxis (sequential compression devices [SCDs]), and (3) chemoprophylaxis administered at the correct dose and frequency for the duration of the patient’s hospital stay.^3,10,11 This quality measure was conceived, created, and iteratively revised to measure whether optimal care is provided to patients throughout their hospitalization and identify actionable areas in which failures of care occur, in order to decrease the risk of a VTE event. Data from our institution provided evidence that while ambulation and SCD component measure adherence is high, chemoprophylaxis adherence required significant improvement.¹⁰ When chemoprophylaxis process measure adherence data were analyzed further, a major failure mode was patient refusal of one or more doses. However, the drivers of patient refusal are not well defined in the literature, and previous studies have called for a greater focus on developing interventions to improve VTE chemoprophylaxis administration.¹²

Previous research has shown that nurses can influence patient compliance with VTE prophylaxis.^13-15 A mixed-methods study by Elder et al. found that nurses in units with high rates of failure to provide optimal chemoprophylaxis offered the medication as optional, leading researchers to conclude that nurses perceived chemoprophylaxis as discretionary.¹³ Another study by Lee et al., conducted a survey of bedside registered nurses and identified nurses’ lack of education on VTE prevention as a significant barrier to providing care.¹⁴ These studies show that multiple levels of influence impact how nurses provide VTE chemoprophylaxis, particularly when they encounter patients who refuse chemoprophylaxis.

To explore the nuance and interplay of multiple influences, we used the Theoretical Domains Framework (TDF), an integrative framework that applies theoretical approaches to interventions aimed at behavior change.^15-18 The framework contains 14 interrelated domains that characterize the behavior being studied, in this case, administration of VTE chemoprophylaxis. Consequently, we designed a nurse-focused, qualitative evaluation with the objective to identify nursing-related barriers to administration of VTE chemoprophylaxis.

Inpatient Unit Selection

The study team accessed data from the hospital’s Enterprise Data Warehouse to review patient refusal rates of VTE chemoprophylaxis for each inpatient unit in the hospital. Patient refusal was utilized as a proxy measure for the behavior of nurses attempting to administer VTE chemoprophylaxis. Of the 14 medical and surgical units in the hospital, two medical and two surgical units were selected to participate in the qualitative evaluation based on having the highest patient refusal rates. One unit (surgical) was also selected to serve as a benchmark because it had the lowest patient refusal rate. Table 1 includes the refusal rates for the five units. Given the low refusal rate for the best performing unit, we suspected that it would be possible to decrease the patient refusal rate for other units with similar patient populations and interprofessional teams at the institution.

Observations

We observed chemoprophylaxis administration on the five units to understand the process for ordering and administering chemoprophylaxis. An observation protocol was utilized to document the date, time, and location of the observation as well as descriptive notes including accounts of particular events.^19,20 Observations occurred in May 2016 and informed the creation of a process map outlining the procedure for ordering and administering VTE chemoprophylaxis. The process map was utilized to create the focus group interview guide and ensure the interview guide included pertinent questions for each step of the process (Appendix A).

Focus Group Interviews

We conducted focus group interviews with day and night shift nurses on the five units to assess nurses’ understanding of VTE chemoprophylaxis and nurses’ perceptions of barriers to administration of VTE chemoprophylaxis. The study team chose to conduct focus group interviews in an effort to maximize participation and to speak with multiple nurses within a shorter period of time. The focus group structure allowed the study team to speak with nurses during their shifts, as one could briefly step out, if required, for patient care and return to rejoin the discussion.

We developed a semistructured interview guide²¹ with questions focused on identifying nurses’ perceptions of guideline-recommended care for VTE chemoprophylaxis, where they learned these guidelines, how nurses discuss chemoprophylaxis with patients, how they handle the conversation with patients who refuse, and if there are times when chemoprophylaxis is not necessary. The interview guide was vetted by a multidisciplinary team consisting of clinical nursing coordinators and nurse managers from medical and surgical units, hospital quality leaders, surgeons and general internists, and qualitative research experts. The interview guide is included as Appendix B.

The unit clinical coordinators and nurse managers identified dates and times for the focus groups that would be minimally disruptive to the unit. For each of the four units with a high patient refusal rate, two focus groups were conducted during the lunch hour and one was conducted at the end of the night shift to ensure that both day and night shift nurses were included in the study. Two focus groups were conducted with the best-practice unit during the lunch hour. For each focus group, the clinical coordinator identified two to eight nurses who could step away from patient care to participate or who had completed their shifts. In total, approximately 67 nurses participated in the focus groups.

The focus groups (n = 14) lasted approximately 40 minutes during May and June 2016. Two members of the study team cofacilitated interviews, which were recorded and transcribed verbatim.

Coding and Data Analysis

To develop the code book, the study team, consisting of three qualitative researchers, independently read one focus group transcript and applied the TDF domains to the nurses’ perceptions of barriers to administration of VTE chemoprophylaxis.^21-24 In addition to coding by domain, the study team also coded nursing perceptions as barriers or facilitators. The study team reviewed the coded transcript and reconciled any differences in coding. This process was repeated for a second transcript, and then all remaining transcripts were assigned to two out of three study team members for coding, with the entire study team meeting to reconcile any differences. If necessary, the team member who did not code a transcript acted as the tie-breaker if there were discrepancies in codes that could not be reconciled.

Once coding was completed, we identified the TDF domains that were most relevant to the administration of VTE chemoprophylaxis.¹⁶ Member checking (testing the analysis, interpretations, and conclusions with members of those groups from whom the data were originally obtained) was performed with the four clinical nursing coordinators and four nurse managers from the participating units to establish face validity of the themes identified from the focus group interviews.²⁵

The study team used MaxQDA, V12 (Berlin, Germany) to support data coding and analysis.²⁶ The Northwestern University institutional review board office deemed this project research on nonhuman-subjects because it focused on the process of providing VTE chemoprophylaxis and not about the patients themselves. The purpose of the study was explained at the beginning of each focus group, and nurses gave verbal consent to have the focus group recorded.

We conducted 14 focus groups with day and night shift nurses from five units (two medical and three surgical) at a single institution. All nurses invited to participate in a focus group agreed to participate. The data were coded and grouped by domain and identified as barriers or facilitators. The findings included below are for the domains most relevant to the provision of VTE prophylaxis. Table 2 provides illustrative verbatim quotes for each domain that was represented in the focus groups.

Knowledge

All interviewees recognized that providing some form of prophylaxis to mitigate the risk of a VTE event is essential. Some nurses stated that seeing a patient ambulating meant they would consider not administering prescribed chemoprophylaxis, while others would try to negotiate with patients by asking the patient to allow one dose of chemoprophylaxis prescribed two to three times daily because it was better than receiving no doses.

Environmental Context and Resources

Multiple barriers to providing optimal care were associated with the environmental context and a lack of resources. There was a lack of accessible, comprehensive, patient-centered education materials on VTE chemoprophylaxis to supplement a nurse’s explanation about the importance of chemoprophylaxis. Furthermore, many nurses cited the perceived patient pain of chemoprophylaxis injections as the main deterrent to patient compliance, especially subcutaneous heparin injections, which occur up to three times in 24 hours and often cause more pain at the site of injection than low-molecular-weight heparin. Nurses felt that transitioning patients from receiving subcutaneous heparin injections to receiving low-molecular-weight heparin could be a main driver to reduce patient refusals.

Skills

Nurses felt inadequately equipped to handle patient refusals. Many said that patient refusal of treatments was never discussed in nursing school. As a result, when patients refused treatments, the nurses did not know how to handle the situation. They felt that they lacked the tools and techniques to persuade the patient to comply.

Beliefs about Capabilities

Nurses did not know their own patient refusal rate or benchmarks of an acceptable refusal rate in contrast to one that is too high. Without this feedback, they were unable to assess their own behavior or performance related to providing VTE chemoprophylaxis.

Nurses play a critical role in providing VTE chemoprophylaxis to patients throughout their hospitalization. This study provided a unique opportunity to perform an in-depth, qualitative analysis of the barriers nurses face in providing patients with VTE chemoprophylaxis as part of their daily work caring for patients. We discovered several nursing-related barriers to the provision of VTE chemoprophylaxis, including lack of knowledge, resources, skill, and misconceptions of their capability to provide VTE chemoprophylaxis. We used a bottom-up approach by incorporating the voices of unit nurses, clinical coordinators, and nurse managers to understand potential barriers. Our findings brought to light the challenge of delivering standardized care in an area of care that is generally agreed upon, yet not fully followed. Some nurses display greater proficiency than others at communicating with patients who do not understand their risk for VTE and need for chemoprophylaxis. Furthermore, there is a pronounced misconception around the delivery of VTE chemoprophylaxis. Nurses have the inaccurate belief that even if ordered, chemoprophylaxis is not required. This misconception was widespread among nurses taking care of both medical and surgical patients. These factors appear to be modifiable targets for quality improvement and highlight the need for a skills-based education during the new hire onboarding process, as well as ongoing reeducation to ensure nursing staff have the skills to appropriately provide best-practice care for VTE chemoprophylaxis. Nurses felt ownership of the results of the qualitative evaluation because they were included in every aspect from the beginning.²⁷ This sense of ownership will support future quality improvement efforts to develop a skills-based intervention to improve the provision of VTE chemoprophylaxis.^18,27

This study has certain limitations. First, it was a qualitative study assessing nursing-related barriers to providing VTE chemoprophylaxis at a single institution, and the results cannot be generalized broadly. However, the techniques and results are transferable to other hospital settings and other clinical care situations. Thus, we believe that other institutions can utilize our methods and that similar lessons can be learned and applied. Furthermore, the validity of our study is bolstered by concordance between the results of this study and those of other studies conducted on the topic of provision of VTE prophylaxis by nurses.^13-15,21 Other studies utilized observations and surveys to determine potential nurse-related barriers to the provision of VTE prophylaxis, such as lack of knowledge and the belief that the need for prophylaxis can be determined based on whether or not the patient is ambulating;^13,14 however, by utilizing focus group interviews, we allowed nurses to speak in their own voices about their experiences with VTE prophylaxis, and we were able to delve deeper and identify additional barriers that emerged from discussions with nurses, such as the lack of skill and misconceptions of capability.^28,29 Second, the study focused solely on nurses. Additional initiatives are underway to assess the roles of resident physicians, attending physicians, and patients in the provision of VTE prophylaxis.

Nursing-related barriers to the provision of VTE chemoprophylaxis include a lack of knowledge, resources, skills, and misconceptions of the consequences of missed elements of VTE prophylaxis. Future initiatives will focus on equipping nurses to have meaningful conversations with patients and engaging patients in their care through development of a multifaceted bundle of interventions. Furthermore, similar methods of qualitative inquiry will be used to identify the role of resident and attending physicians and patients in the provision of VTE chemoprophylaxis.

Acknowledgments

The authors thank Sonali Oberoi, Joanne Prinz, Nancy Tomaska, and Kate Paredes, as well as all the nurses who participated in focus group interviews for this study and the nurse managers and clinical coordinators who helped to schedule the focus group interviews.

Disclosures

The authors declare that they have no competing interests.

Funding

This study was funded by the Surgical Outcomes and Quality Improvement Center at Northwestern University.

Venous thromboembolism (VTE), comprising deep venous thrombosis and pulmonary embolism (PE),¹ is a serious medical condition that results in preventable morbidity and mortality.^1-5 VTE affects all age groups, all races/ethnicities, and both genders, but there are known factors that increase the risk of developing VTE (eg, advanced age, undergoing surgery, hospitalization, and immobility).^1-3,5-7 Prevention of VTE among hospitalized patients is of paramount importance to avoid preventable death, chronic illness/long-term complications,⁸ longer hospital stays, and increased hospital costs.⁹ Fortunately, there is clear evidence that provision of appropriate prophylaxis can decrease the risk of a VTE event occurring, and broadly accepted best-practice guidelines reflect this evidence.^3,5

Given the inadequacy of current VTE-related quality measures to identify actionable failures in the provision of VTE prophylaxis, our group created a VTE process-of-care measure to assess adherence to the components of VTE prophylaxis: (1) early ambulation, (2) mechanical prophylaxis (sequential compression devices [SCDs]), and (3) chemoprophylaxis administered at the correct dose and frequency for the duration of the patient’s hospital stay.^3,10,11 This quality measure was conceived, created, and iteratively revised to measure whether optimal care is provided to patients throughout their hospitalization and identify actionable areas in which failures of care occur, in order to decrease the risk of a VTE event. Data from our institution provided evidence that while ambulation and SCD component measure adherence is high, chemoprophylaxis adherence required significant improvement.¹⁰ When chemoprophylaxis process measure adherence data were analyzed further, a major failure mode was patient refusal of one or more doses. However, the drivers of patient refusal are not well defined in the literature, and previous studies have called for a greater focus on developing interventions to improve VTE chemoprophylaxis administration.¹²

Previous research has shown that nurses can influence patient compliance with VTE prophylaxis.^13-15 A mixed-methods study by Elder et al. found that nurses in units with high rates of failure to provide optimal chemoprophylaxis offered the medication as optional, leading researchers to conclude that nurses perceived chemoprophylaxis as discretionary.¹³ Another study by Lee et al., conducted a survey of bedside registered nurses and identified nurses’ lack of education on VTE prevention as a significant barrier to providing care.¹⁴ These studies show that multiple levels of influence impact how nurses provide VTE chemoprophylaxis, particularly when they encounter patients who refuse chemoprophylaxis.

To explore the nuance and interplay of multiple influences, we used the Theoretical Domains Framework (TDF), an integrative framework that applies theoretical approaches to interventions aimed at behavior change.^15-18 The framework contains 14 interrelated domains that characterize the behavior being studied, in this case, administration of VTE chemoprophylaxis. Consequently, we designed a nurse-focused, qualitative evaluation with the objective to identify nursing-related barriers to administration of VTE chemoprophylaxis.

Inpatient Unit Selection

The study team accessed data from the hospital’s Enterprise Data Warehouse to review patient refusal rates of VTE chemoprophylaxis for each inpatient unit in the hospital. Patient refusal was utilized as a proxy measure for the behavior of nurses attempting to administer VTE chemoprophylaxis. Of the 14 medical and surgical units in the hospital, two medical and two surgical units were selected to participate in the qualitative evaluation based on having the highest patient refusal rates. One unit (surgical) was also selected to serve as a benchmark because it had the lowest patient refusal rate. Table 1 includes the refusal rates for the five units. Given the low refusal rate for the best performing unit, we suspected that it would be possible to decrease the patient refusal rate for other units with similar patient populations and interprofessional teams at the institution.

Observations

We observed chemoprophylaxis administration on the five units to understand the process for ordering and administering chemoprophylaxis. An observation protocol was utilized to document the date, time, and location of the observation as well as descriptive notes including accounts of particular events.^19,20 Observations occurred in May 2016 and informed the creation of a process map outlining the procedure for ordering and administering VTE chemoprophylaxis. The process map was utilized to create the focus group interview guide and ensure the interview guide included pertinent questions for each step of the process (Appendix A).

Focus Group Interviews

We conducted focus group interviews with day and night shift nurses on the five units to assess nurses’ understanding of VTE chemoprophylaxis and nurses’ perceptions of barriers to administration of VTE chemoprophylaxis. The study team chose to conduct focus group interviews in an effort to maximize participation and to speak with multiple nurses within a shorter period of time. The focus group structure allowed the study team to speak with nurses during their shifts, as one could briefly step out, if required, for patient care and return to rejoin the discussion.

We developed a semistructured interview guide²¹ with questions focused on identifying nurses’ perceptions of guideline-recommended care for VTE chemoprophylaxis, where they learned these guidelines, how nurses discuss chemoprophylaxis with patients, how they handle the conversation with patients who refuse, and if there are times when chemoprophylaxis is not necessary. The interview guide was vetted by a multidisciplinary team consisting of clinical nursing coordinators and nurse managers from medical and surgical units, hospital quality leaders, surgeons and general internists, and qualitative research experts. The interview guide is included as Appendix B.

The unit clinical coordinators and nurse managers identified dates and times for the focus groups that would be minimally disruptive to the unit. For each of the four units with a high patient refusal rate, two focus groups were conducted during the lunch hour and one was conducted at the end of the night shift to ensure that both day and night shift nurses were included in the study. Two focus groups were conducted with the best-practice unit during the lunch hour. For each focus group, the clinical coordinator identified two to eight nurses who could step away from patient care to participate or who had completed their shifts. In total, approximately 67 nurses participated in the focus groups.

The focus groups (n = 14) lasted approximately 40 minutes during May and June 2016. Two members of the study team cofacilitated interviews, which were recorded and transcribed verbatim.

Coding and Data Analysis

To develop the code book, the study team, consisting of three qualitative researchers, independently read one focus group transcript and applied the TDF domains to the nurses’ perceptions of barriers to administration of VTE chemoprophylaxis.^21-24 In addition to coding by domain, the study team also coded nursing perceptions as barriers or facilitators. The study team reviewed the coded transcript and reconciled any differences in coding. This process was repeated for a second transcript, and then all remaining transcripts were assigned to two out of three study team members for coding, with the entire study team meeting to reconcile any differences. If necessary, the team member who did not code a transcript acted as the tie-breaker if there were discrepancies in codes that could not be reconciled.

Once coding was completed, we identified the TDF domains that were most relevant to the administration of VTE chemoprophylaxis.¹⁶ Member checking (testing the analysis, interpretations, and conclusions with members of those groups from whom the data were originally obtained) was performed with the four clinical nursing coordinators and four nurse managers from the participating units to establish face validity of the themes identified from the focus group interviews.²⁵

The study team used MaxQDA, V12 (Berlin, Germany) to support data coding and analysis.²⁶ The Northwestern University institutional review board office deemed this project research on nonhuman-subjects because it focused on the process of providing VTE chemoprophylaxis and not about the patients themselves. The purpose of the study was explained at the beginning of each focus group, and nurses gave verbal consent to have the focus group recorded.

We conducted 14 focus groups with day and night shift nurses from five units (two medical and three surgical) at a single institution. All nurses invited to participate in a focus group agreed to participate. The data were coded and grouped by domain and identified as barriers or facilitators. The findings included below are for the domains most relevant to the provision of VTE prophylaxis. Table 2 provides illustrative verbatim quotes for each domain that was represented in the focus groups.

Knowledge

All interviewees recognized that providing some form of prophylaxis to mitigate the risk of a VTE event is essential. Some nurses stated that seeing a patient ambulating meant they would consider not administering prescribed chemoprophylaxis, while others would try to negotiate with patients by asking the patient to allow one dose of chemoprophylaxis prescribed two to three times daily because it was better than receiving no doses.

Environmental Context and Resources

Multiple barriers to providing optimal care were associated with the environmental context and a lack of resources. There was a lack of accessible, comprehensive, patient-centered education materials on VTE chemoprophylaxis to supplement a nurse’s explanation about the importance of chemoprophylaxis. Furthermore, many nurses cited the perceived patient pain of chemoprophylaxis injections as the main deterrent to patient compliance, especially subcutaneous heparin injections, which occur up to three times in 24 hours and often cause more pain at the site of injection than low-molecular-weight heparin. Nurses felt that transitioning patients from receiving subcutaneous heparin injections to receiving low-molecular-weight heparin could be a main driver to reduce patient refusals.

Skills

Nurses felt inadequately equipped to handle patient refusals. Many said that patient refusal of treatments was never discussed in nursing school. As a result, when patients refused treatments, the nurses did not know how to handle the situation. They felt that they lacked the tools and techniques to persuade the patient to comply.

Beliefs about Capabilities

Nurses did not know their own patient refusal rate or benchmarks of an acceptable refusal rate in contrast to one that is too high. Without this feedback, they were unable to assess their own behavior or performance related to providing VTE chemoprophylaxis.

Nurses play a critical role in providing VTE chemoprophylaxis to patients throughout their hospitalization. This study provided a unique opportunity to perform an in-depth, qualitative analysis of the barriers nurses face in providing patients with VTE chemoprophylaxis as part of their daily work caring for patients. We discovered several nursing-related barriers to the provision of VTE chemoprophylaxis, including lack of knowledge, resources, skill, and misconceptions of their capability to provide VTE chemoprophylaxis. We used a bottom-up approach by incorporating the voices of unit nurses, clinical coordinators, and nurse managers to understand potential barriers. Our findings brought to light the challenge of delivering standardized care in an area of care that is generally agreed upon, yet not fully followed. Some nurses display greater proficiency than others at communicating with patients who do not understand their risk for VTE and need for chemoprophylaxis. Furthermore, there is a pronounced misconception around the delivery of VTE chemoprophylaxis. Nurses have the inaccurate belief that even if ordered, chemoprophylaxis is not required. This misconception was widespread among nurses taking care of both medical and surgical patients. These factors appear to be modifiable targets for quality improvement and highlight the need for a skills-based education during the new hire onboarding process, as well as ongoing reeducation to ensure nursing staff have the skills to appropriately provide best-practice care for VTE chemoprophylaxis. Nurses felt ownership of the results of the qualitative evaluation because they were included in every aspect from the beginning.²⁷ This sense of ownership will support future quality improvement efforts to develop a skills-based intervention to improve the provision of VTE chemoprophylaxis.^18,27

This study has certain limitations. First, it was a qualitative study assessing nursing-related barriers to providing VTE chemoprophylaxis at a single institution, and the results cannot be generalized broadly. However, the techniques and results are transferable to other hospital settings and other clinical care situations. Thus, we believe that other institutions can utilize our methods and that similar lessons can be learned and applied. Furthermore, the validity of our study is bolstered by concordance between the results of this study and those of other studies conducted on the topic of provision of VTE prophylaxis by nurses.^13-15,21 Other studies utilized observations and surveys to determine potential nurse-related barriers to the provision of VTE prophylaxis, such as lack of knowledge and the belief that the need for prophylaxis can be determined based on whether or not the patient is ambulating;^13,14 however, by utilizing focus group interviews, we allowed nurses to speak in their own voices about their experiences with VTE prophylaxis, and we were able to delve deeper and identify additional barriers that emerged from discussions with nurses, such as the lack of skill and misconceptions of capability.^28,29 Second, the study focused solely on nurses. Additional initiatives are underway to assess the roles of resident physicians, attending physicians, and patients in the provision of VTE prophylaxis.

Nursing-related barriers to the provision of VTE chemoprophylaxis include a lack of knowledge, resources, skills, and misconceptions of the consequences of missed elements of VTE prophylaxis. Future initiatives will focus on equipping nurses to have meaningful conversations with patients and engaging patients in their care through development of a multifaceted bundle of interventions. Furthermore, similar methods of qualitative inquiry will be used to identify the role of resident and attending physicians and patients in the provision of VTE chemoprophylaxis.

Acknowledgments

The authors thank Sonali Oberoi, Joanne Prinz, Nancy Tomaska, and Kate Paredes, as well as all the nurses who participated in focus group interviews for this study and the nurse managers and clinical coordinators who helped to schedule the focus group interviews.

Disclosures

The authors declare that they have no competing interests.

Funding

This study was funded by the Surgical Outcomes and Quality Improvement Center at Northwestern University.

Asthma results in approximately 125,000 hospitalizations for children annually in the United States.^1,2 The National Heart, Lung, and Blood Institute guidelines recommend that children with persistent asthma be treated with a daily controller medication, ie, an inhaled corticosteroid (ICS).³ Hospitalization for an asthma exacerbation provides an opportunity to optimize daily controller medications and improve disease self-management by providing access to medications and teaching appropriate use of complicated inhalation devices.

To reduce readmission⁴ by mitigating low rates of postdischarge filling of ICS prescriptions,^5,6 a strategy of “meds-in-hand” was implemented at discharge. “Meds-in-hand” mitigates medication access as a barrier to adherence by ensuring that patients are discharged from the hospital with all required medications in hand, removing any barriers to filling their initial prescriptions.⁷ The Asthma Improvement Collaborative at Cincinnati Children’s Hospital Medical Center (CCHMC) previously applied quality improvement methodology to implement “meds-in-hand” as a key intervention in a broad strategy that successfully reduced asthma-specific utilization for the 30-day period following an asthma-related hospitalization of publicly insured children from 12% to 7%.^8,9

At the onset of the work described in this manuscript, children hospitalized with an acute exacerbation of persistent asthma were most often treated with an ICS while inpatients in addition to a standard short course of oral systemic corticosteroids. Conceptually, inpatient administration of ICS provided the opportunity to teach effective device usage with each inpatient administration and to reinforce daily use of the ICS as part of the patient’s daily home medication regimen. However, a proportion of patients admitted for an asthma exacerbation were noted to receive more than one ICS inhaler during their admission, most commonly due to a change in dose or type of ICS. When this occurred, the initially dispensed inhaler was discarded despite weeks of potential doses remaining. While some hospitals preferentially dispense ICS devices marketed to institutions with fewer doses per device, our pharmacy primarily dispensed ICS devices identical to retail locations containing at least a one-month supply of medication. In addition to the wasted medication, this practice resulted in additional work by healthcare staff, unnecessary patient charges, and potentially contributed to confusion about the discharge medication regimen.

Our specific aim for this quality improvement study was to reduce the monthly percentage of admissions for an acute asthma exacerbation treated with >1 ICS from 7% to 4% over a six-month period.

Context

CCHMC is a quaternary care pediatric health system with more than 600 inpatient beds and 800-900 inpatient admissions per year for acute asthma exacerbation. The Hospital Medicine service cares for patients with asthma on five clinical teams across two different campuses. Care teams are supervised by an attending physician and may include residents, fellows, or nurse practitioners. Patients hospitalized for an acute asthma exacerbation may receive a consult from the Asthma Center consult team, staffed by faculty from either the Pediatric Pulmonology or Allergy/Immunology divisions. Respiratory therapists (RTs) administer inhaled medications and provide asthma education.

Planning the Intervention

Our improvement team included physicians from Hospital Medicine and Pulmonary Medicine, an Asthma Education Coordinator, a Clinical Pharmacist, a Pediatric Chief Resident, and a clinical research coordinator. Initial interventions targeted a single resident team at the main campus before spreading improvement activities to all resident teams at the main campus and then the satellite campus by February 2017.

Development of our process map (Figure 1) revealed that the decision for ordering inpatient ICS treatment frequently occurred at admission. Subsequently, the care team or consulting team might make a change in the ICS to fine-tune the outpatient medication regimen given that admission for asthma often results from suboptimal chronic symptom control. Baseline analysis of changes in ICS orders revealed that 81% of ICS changes were associated with a step-up in therapy, defined as an increase in the daily dose of the ICS or the addition of a long-acting beta-agonist. The other common ICS adjustment, accounting for 17%, was a change in corticosteroid without a step-up in therapy, (ie, beclomethasone to fluticasone) that typically occurred near the end of the hospitalization to accommodate outpatient insurance formularies, independent of patient factors related to illness severity.

Improvement Activities

We conceived key drivers or domains that would be necessary to address to effect change. Key drivers included a standardized process for delayed initiation of ICS and confirmation of outpatient insurance prescription drug coverage, prescriber education, and real-time failure notification.

PDSA Interventions

PDSA 1 & 2: Standardized Process for Initiation of ICS

Our initial tests of change targeted the timing of when an ICS was ordered during hospitalization for an asthma exacerbation. Providers were instructed to delay ordering an ICS until the patient’s albuterol treatments were spaced to every three hours and to include a standardized communication prompt within the albuterol order. The prompt instructed the RT to contact the provider once the patient’s albuterol treatments were spaced to every three hours and ask for an ICS order, if appropriate. This intervention was abandoned because it did not reliably occur.

The subsequent intervention delayed the start of ICS treatment by using a PRN indication advising that the ICS was to be administered once the patient’s albuterol treatments were spaced to every three hours. However, after an error resulted in the PRN indication being included on a discharge prescription for an ICS, the PRN indication was abandoned. Subsequent work to develop a standardized process for delayed initiation of ICS occurred as part of the workflow to address the confirmation of outpatient formulary coverage as described next.

PDSA 3: Prioritize the Use of the Institution’s Outpatient Pharmacy

Medication changes that occurred because of outpatient insurance formulary denials were a unique challenge; they required a medication change after the discharge treatment plan had been finalized, and a prescription was already submitted to the outpatient pharmacy. In addition, neither our inpatient electronic medical record nor our inpatient hospital pharmacy has access to decision support tools that incorporate outpatient prescription formulary coverage. Alternatively, outpatient pharmacies have a standard workflow that routinely confirms insurance coverage before dispensing medication. The institutional policy was modified to allow for the inpatient administration of patient-supplied medications, pursuant to an inpatient order. Patient-supplied medications include those brought from home or those supplied by the outpatient pharmacy.

Subsequently, we developed a standardized process to confirm outpatient prescription drug coverage by using our hospital-based outpatient pharmacy to dispense ICS for inpatient treatment and asthma education. This new workflow included placing an order for an ICS at admission as a patient-supplied medication with an administration comment to “please administer once available from the outpatient pharmacy” (Figure 1). Then, once the discharge medication plan is finalized, the prescription is submitted to the outpatient pharmacy. Following verification of insurance coverage, the outpatient pharmacy dispenses the ICS, allowing it to be used for patient education and inpatient administration. If the patient is ineligible to have their prescription filled by the outpatient pharmacy for reasons other than formulary coverage, the ICS is dispensed from the hospital inpatient pharmacy as per the previous standard workflow. Inpatient ICS inhalers are then relabeled for home use per the existing practice to support medications-in-hand.

Further workflow improvements occurred following the development of an algorithm to help the outpatient pharmacy contact the correct inpatient team, and augmentation of the medication delivery process included notification of the RT when the ICS was delivered to the inpatient unit.

PDSA 4: Prescriber Education

Prescribers received education regarding PDSA interventions before testing and throughout the improvement cycle. Education sessions included informal coaching by the Asthma Education Coordinator, e-mail reminders containing screenshots of the ordering process, and formal didactic sessions for ordering providers. The Asthma Education Coordinator also provided education to the nursing and respiratory therapy staff regarding the implemented process and workflow changes.

PDSA 5: Real-Time Failure Notification

To supplement education for the complicated process change, the improvement team utilized a decision support tool (Vigilanz Corp., Chicago, IL) linked to EMR data to provide notification of real-time process failures. When a patient with an admission diagnosis of asthma had a prescription for an ICS verified and dispensed by the inpatient pharmacy, an automated message with relevant patient information would be sent to a member of the improvement team. Following a brief chart review, directed feedback could be offered to the ordering provider, allowing the prescription to be redirected to the outpatient pharmacy.

Study of the Improvement

Patients of all ages, with the International Classification of Diseases, Ninth Revision, and Tenth Revision codes for asthma (493.xx or J45.xx) were included in data collection and analysis if they were treated by the Hospital Medicine service, as the first inpatient service or after transfer from the ICU, and prescribed an ICS with or without a long-acting beta-agonist. Data were collected retrospectively and aggregated monthly. The baseline period was from January 2015 through October 2016. The intervention period was from November 2016 through March 2018. The prolonged baseline and study periods were utilized to understand the seasonal nature of asthma exacerbations.

Measures

Our primary outcome measure was defined as the monthly number of patients admitted to Hospital Medicine for an acute asthma exacerbation administered more than one ICS divided by the total number of asthma patients administered at least one dose of an ICS (patient-supplied or dispensed from the inpatient pharmacy). A full list of ICS is included in the appendix Table.

A secondary process measure approximated our adherence to obtaining ICS from the outpatient pharmacy for inpatient use. All medications administered during hospitalization are documented in the medication administration report. However, only medications dispensed from the inpatient pharmacy are associated with a patient charge. Patient-supplied medications, including those dispensed from the hospital outpatient pharmacy, are not associated with an inpatient charge. Therefore, the secondary process measure was defined as the monthly number of asthma patients administered an ICS not associated with an inpatient charge divided by the total number of asthma patients administered an ICS.

A cost outcome measure was developed to track changes in the average cost of an ICS included on inpatient bills during hospitalization for an asthma exacerbation. This outcome measure was defined as the total monthly cost, using the average wholesale price, of the ICS included on the inpatient bill for an asthma exacerbation, divided by the total number of asthma patients administered at least one dose of an ICS (patient supplied or dispensed from the inpatient pharmacy). The costs of patient-supplied medications (including those dispensed from the outpatient pharmacy) are not included on inpatient hospital bills or this secondary outcome measure.

Our a priori intent was to reduce ICS medication waste while maintaining a highly reliable system that included inpatient administration and education with ICS devices and maintain our medications-in-hand practice. A balancing measure was developed to monitor the reliability of inpatient administration of ICS. It was defined as the monthly number of patients who received a discharge prescription for an ICS and were administered an ICS while an inpatient divided by the total number of asthma patients with a discharge prescription for an ICS.

Analysis

Measures were evaluated using statistical process control charts and special cause variation was determined by previously established rules. Our primary, secondary, and balancing measures were all evaluated using a p-chart with variable subgroup size. The cost outcome measure was evaluated using an X-bar S control chart.^11-13

Primary Outcome Measure

During the baseline period, 7.4% of patients admitted to Hospital Medicine for an acute asthma exacerbation were administered more than one ICS, ranging from 0%-20% of patients per month (Figure 2). Following the start of our interventions, we met criteria for special cause allowing adjustment of the centerline.¹³ The mean percentage of patients receiving more than one ICS decreased from 7.4% to 0.7%. Figure 2 includes the n-value displayed each month and represents all patients admitted to the Hospital Medicine service with an asthma exacerbation who were administered at least one ICS.

Secondary Process Measure

During the baseline period, there were only rare occurrences (less than 1%) of a patient-supplied ICS being administered during an asthma admission. Following the start of our intervention period, the frequency of inpatient administration of patient-supplied ICS showed a rapid increase and met rules for special cause with an increase in the mean percent from 0.7% to 50% (Figure 3). The n-value displayed each month represents all patients admitted to the Hospital Medicine service for an asthma exacerbation administered at least one ICS.

Cost Outcome Measure

The average cost of an ICS billed during hospitalization for an acute asthma exacerbation was $236.57 per ICS during the baseline period. After the intervention period, the average inpatient cost for ICS decreased by 62% to $90.25 per ICS (Figure 4).

Balancing Measure

Our team reduced the monthly percent of children hospitalized with an acute asthma exacerbation administered more than one ICS from 7.4% to 0.7% after implementation of a new workflow process for ordering ICS utilizing the hospital-based outpatient pharmacy. The new workflow delayed ordering and administration of the initial inpatient ICS treatment, allowing time to consider a step-up in therapy. The brief delay in initiating ICS is not expected to have clinical consequence given the concomitant treatment with systemic corticosteroids. In addition, the outpatient pharmacy was utilized to verify insurance coverage reliably prior to dispensing ICS, reducing medication waste, and discharge delays due to outpatient medication formulary conflicts.

Our hospital’s previous approach to inpatient asthma care resulted in a highly reliable process to ensure patients were discharged with medications-in-hand as part of a broader system that effectively decreased reutilization. However, the previous process inadvertently resulted in medication waste. This waste included nearly full inhalers being discarded, additional work by the healthcare team (ordering providers, pharmacists, and RTs), and unnecessary patient charges.

While the primary driver of our decision to use the outpatient pharmacy was to adjudicate insurance prescription coverage reliably to prevent waste, this change likely resulted in a financial benefit to patients. The average cost per asthma admission of an inpatient billed for ICS using the average wholesale price, decreased by 62% following our interventions. The decrease in cost was primarily driven by using patient-supplied medications, including prescriptions newly filled by the on-site outpatient pharmacy, whose costs were not captured in this measure. While our secondary measure may underestimate the total expense incurred by families for an ICS, families likely receive their medications at a lower cost from the outpatient pharmacy than if the ICS was provided by an inpatient pharmacy. The average wholesale price is not what families are charged or pay for medications, partly due to differences in overhead costs that result in inpatient pharmacies having significantly higher charges than outpatient pharmacies. In addition, the 6.7% absolute reduction of our primary measure resulted in direct savings by reducing inpatient medication waste. Our process results in 67 fewer wasted ICS devices ($15,960) per 1,000 admissions for asthma exacerbation, extrapolated using the average cost ($238.20, average wholesale price) of each ICS during the baseline period.

Our quality improvement study had several limitations. (1) The interventions occurred at a single center with an established culture that embraces quality improvement, which may limit the generalizability of the work. (2) Our process verified insurance coverage with a hospital-based outpatient pharmacy. Some ICS prescriptions continued to be dispensed from the inpatient pharmacy, limiting our ability to verify insurance coverage. Local factors, including regulatory restrictions and delivery requirements, may limit the generalizability of using an outpatient pharmacy in this manner. (3) We achieved our goal of decreasing medication waste, but our a priori goal was to maintain our commitment to our established practice of interactive patient education with an ICS device as well as medications-in-hand at time of discharge. Our balancing measure showed a decrease in the percent of patients with a discharge prescription for an ICS who also received an inpatient dose of that ICS. This implies a decreased fidelity in our previously established education protocols. We had postulated that this occurred when the patient-supplied medication arrived on the day of discharge, but not close to when the medication was scheduled on the medication administration report, preventing administration. However, this is not a direct measure of patients receiving medications-in-hand or interactive medication education. Both may have occurred without administration of the ICS. (4) Despite a hospital culture that embraces quality improvement, this project required a significant change in the workflow that required considerable education at the time of implementation to integrate the new process reliably. However, once the process was in place, we have been able to sustain our improvement with limited educational investment.

Implementation of a new process for ordering ICS that emphasized delaying treatment until all necessary information was available and using an outpatient pharmacy to confirm insurance formulary coverage reduced the waste associated with more than one ICS being prescribed during a single admission.

Acknowledgments

The authors thank Sally Pope, MPH and Dr. Michael Carlisle, MD for their contribution to the quality improvement project. Thank you to Drs. Karen McDowell, MD and Carolyn Kercsmar, MD for advisement of our quality improvement project.

The authors appreciate the following individuals for their invaluable contributions. Dr. Hoefgen conceptualized and designed the study, was a member of the primary improvement team, carried out initial analysis, drafted the initial manuscript, and reviewed and revised the manuscript. Drs. Jones and Torres Garcia, and Mr. Hare were members of the primary improvement team who contributed to the design of the quality improvement study and interventions, ongoing data interpretation, and critically reviewed the manuscript. Dr. Courter contributed to the conceptualization and designed the study, was a member of the primary improvement team, designed data collection instruments, and critically reviewed and revised the manuscript. Dr. Simmons conceptualized and designed the study, critically reviewed the manuscript for important intellectual content, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Disclaimer

The information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by the BHPR, HRSA, DHHS, or the U.S. Government.

Asthma results in approximately 125,000 hospitalizations for children annually in the United States.^1,2 The National Heart, Lung, and Blood Institute guidelines recommend that children with persistent asthma be treated with a daily controller medication, ie, an inhaled corticosteroid (ICS).³ Hospitalization for an asthma exacerbation provides an opportunity to optimize daily controller medications and improve disease self-management by providing access to medications and teaching appropriate use of complicated inhalation devices.

To reduce readmission⁴ by mitigating low rates of postdischarge filling of ICS prescriptions,^5,6 a strategy of “meds-in-hand” was implemented at discharge. “Meds-in-hand” mitigates medication access as a barrier to adherence by ensuring that patients are discharged from the hospital with all required medications in hand, removing any barriers to filling their initial prescriptions.⁷ The Asthma Improvement Collaborative at Cincinnati Children’s Hospital Medical Center (CCHMC) previously applied quality improvement methodology to implement “meds-in-hand” as a key intervention in a broad strategy that successfully reduced asthma-specific utilization for the 30-day period following an asthma-related hospitalization of publicly insured children from 12% to 7%.^8,9

At the onset of the work described in this manuscript, children hospitalized with an acute exacerbation of persistent asthma were most often treated with an ICS while inpatients in addition to a standard short course of oral systemic corticosteroids. Conceptually, inpatient administration of ICS provided the opportunity to teach effective device usage with each inpatient administration and to reinforce daily use of the ICS as part of the patient’s daily home medication regimen. However, a proportion of patients admitted for an asthma exacerbation were noted to receive more than one ICS inhaler during their admission, most commonly due to a change in dose or type of ICS. When this occurred, the initially dispensed inhaler was discarded despite weeks of potential doses remaining. While some hospitals preferentially dispense ICS devices marketed to institutions with fewer doses per device, our pharmacy primarily dispensed ICS devices identical to retail locations containing at least a one-month supply of medication. In addition to the wasted medication, this practice resulted in additional work by healthcare staff, unnecessary patient charges, and potentially contributed to confusion about the discharge medication regimen.

Our specific aim for this quality improvement study was to reduce the monthly percentage of admissions for an acute asthma exacerbation treated with >1 ICS from 7% to 4% over a six-month period.

Context

CCHMC is a quaternary care pediatric health system with more than 600 inpatient beds and 800-900 inpatient admissions per year for acute asthma exacerbation. The Hospital Medicine service cares for patients with asthma on five clinical teams across two different campuses. Care teams are supervised by an attending physician and may include residents, fellows, or nurse practitioners. Patients hospitalized for an acute asthma exacerbation may receive a consult from the Asthma Center consult team, staffed by faculty from either the Pediatric Pulmonology or Allergy/Immunology divisions. Respiratory therapists (RTs) administer inhaled medications and provide asthma education.

Planning the Intervention

Our improvement team included physicians from Hospital Medicine and Pulmonary Medicine, an Asthma Education Coordinator, a Clinical Pharmacist, a Pediatric Chief Resident, and a clinical research coordinator. Initial interventions targeted a single resident team at the main campus before spreading improvement activities to all resident teams at the main campus and then the satellite campus by February 2017.

Development of our process map (Figure 1) revealed that the decision for ordering inpatient ICS treatment frequently occurred at admission. Subsequently, the care team or consulting team might make a change in the ICS to fine-tune the outpatient medication regimen given that admission for asthma often results from suboptimal chronic symptom control. Baseline analysis of changes in ICS orders revealed that 81% of ICS changes were associated with a step-up in therapy, defined as an increase in the daily dose of the ICS or the addition of a long-acting beta-agonist. The other common ICS adjustment, accounting for 17%, was a change in corticosteroid without a step-up in therapy, (ie, beclomethasone to fluticasone) that typically occurred near the end of the hospitalization to accommodate outpatient insurance formularies, independent of patient factors related to illness severity.

Improvement Activities

We conceived key drivers or domains that would be necessary to address to effect change. Key drivers included a standardized process for delayed initiation of ICS and confirmation of outpatient insurance prescription drug coverage, prescriber education, and real-time failure notification.

PDSA Interventions

PDSA 1 & 2: Standardized Process for Initiation of ICS

Our initial tests of change targeted the timing of when an ICS was ordered during hospitalization for an asthma exacerbation. Providers were instructed to delay ordering an ICS until the patient’s albuterol treatments were spaced to every three hours and to include a standardized communication prompt within the albuterol order. The prompt instructed the RT to contact the provider once the patient’s albuterol treatments were spaced to every three hours and ask for an ICS order, if appropriate. This intervention was abandoned because it did not reliably occur.

The subsequent intervention delayed the start of ICS treatment by using a PRN indication advising that the ICS was to be administered once the patient’s albuterol treatments were spaced to every three hours. However, after an error resulted in the PRN indication being included on a discharge prescription for an ICS, the PRN indication was abandoned. Subsequent work to develop a standardized process for delayed initiation of ICS occurred as part of the workflow to address the confirmation of outpatient formulary coverage as described next.

PDSA 3: Prioritize the Use of the Institution’s Outpatient Pharmacy

Medication changes that occurred because of outpatient insurance formulary denials were a unique challenge; they required a medication change after the discharge treatment plan had been finalized, and a prescription was already submitted to the outpatient pharmacy. In addition, neither our inpatient electronic medical record nor our inpatient hospital pharmacy has access to decision support tools that incorporate outpatient prescription formulary coverage. Alternatively, outpatient pharmacies have a standard workflow that routinely confirms insurance coverage before dispensing medication. The institutional policy was modified to allow for the inpatient administration of patient-supplied medications, pursuant to an inpatient order. Patient-supplied medications include those brought from home or those supplied by the outpatient pharmacy.

Subsequently, we developed a standardized process to confirm outpatient prescription drug coverage by using our hospital-based outpatient pharmacy to dispense ICS for inpatient treatment and asthma education. This new workflow included placing an order for an ICS at admission as a patient-supplied medication with an administration comment to “please administer once available from the outpatient pharmacy” (Figure 1). Then, once the discharge medication plan is finalized, the prescription is submitted to the outpatient pharmacy. Following verification of insurance coverage, the outpatient pharmacy dispenses the ICS, allowing it to be used for patient education and inpatient administration. If the patient is ineligible to have their prescription filled by the outpatient pharmacy for reasons other than formulary coverage, the ICS is dispensed from the hospital inpatient pharmacy as per the previous standard workflow. Inpatient ICS inhalers are then relabeled for home use per the existing practice to support medications-in-hand.

Further workflow improvements occurred following the development of an algorithm to help the outpatient pharmacy contact the correct inpatient team, and augmentation of the medication delivery process included notification of the RT when the ICS was delivered to the inpatient unit.

PDSA 4: Prescriber Education

Prescribers received education regarding PDSA interventions before testing and throughout the improvement cycle. Education sessions included informal coaching by the Asthma Education Coordinator, e-mail reminders containing screenshots of the ordering process, and formal didactic sessions for ordering providers. The Asthma Education Coordinator also provided education to the nursing and respiratory therapy staff regarding the implemented process and workflow changes.

PDSA 5: Real-Time Failure Notification

To supplement education for the complicated process change, the improvement team utilized a decision support tool (Vigilanz Corp., Chicago, IL) linked to EMR data to provide notification of real-time process failures. When a patient with an admission diagnosis of asthma had a prescription for an ICS verified and dispensed by the inpatient pharmacy, an automated message with relevant patient information would be sent to a member of the improvement team. Following a brief chart review, directed feedback could be offered to the ordering provider, allowing the prescription to be redirected to the outpatient pharmacy.

Study of the Improvement

Patients of all ages, with the International Classification of Diseases, Ninth Revision, and Tenth Revision codes for asthma (493.xx or J45.xx) were included in data collection and analysis if they were treated by the Hospital Medicine service, as the first inpatient service or after transfer from the ICU, and prescribed an ICS with or without a long-acting beta-agonist. Data were collected retrospectively and aggregated monthly. The baseline period was from January 2015 through October 2016. The intervention period was from November 2016 through March 2018. The prolonged baseline and study periods were utilized to understand the seasonal nature of asthma exacerbations.

Measures

Our primary outcome measure was defined as the monthly number of patients admitted to Hospital Medicine for an acute asthma exacerbation administered more than one ICS divided by the total number of asthma patients administered at least one dose of an ICS (patient-supplied or dispensed from the inpatient pharmacy). A full list of ICS is included in the appendix Table.

A secondary process measure approximated our adherence to obtaining ICS from the outpatient pharmacy for inpatient use. All medications administered during hospitalization are documented in the medication administration report. However, only medications dispensed from the inpatient pharmacy are associated with a patient charge. Patient-supplied medications, including those dispensed from the hospital outpatient pharmacy, are not associated with an inpatient charge. Therefore, the secondary process measure was defined as the monthly number of asthma patients administered an ICS not associated with an inpatient charge divided by the total number of asthma patients administered an ICS.

A cost outcome measure was developed to track changes in the average cost of an ICS included on inpatient bills during hospitalization for an asthma exacerbation. This outcome measure was defined as the total monthly cost, using the average wholesale price, of the ICS included on the inpatient bill for an asthma exacerbation, divided by the total number of asthma patients administered at least one dose of an ICS (patient supplied or dispensed from the inpatient pharmacy). The costs of patient-supplied medications (including those dispensed from the outpatient pharmacy) are not included on inpatient hospital bills or this secondary outcome measure.

Our a priori intent was to reduce ICS medication waste while maintaining a highly reliable system that included inpatient administration and education with ICS devices and maintain our medications-in-hand practice. A balancing measure was developed to monitor the reliability of inpatient administration of ICS. It was defined as the monthly number of patients who received a discharge prescription for an ICS and were administered an ICS while an inpatient divided by the total number of asthma patients with a discharge prescription for an ICS.

Analysis

Measures were evaluated using statistical process control charts and special cause variation was determined by previously established rules. Our primary, secondary, and balancing measures were all evaluated using a p-chart with variable subgroup size. The cost outcome measure was evaluated using an X-bar S control chart.^11-13

Primary Outcome Measure

During the baseline period, 7.4% of patients admitted to Hospital Medicine for an acute asthma exacerbation were administered more than one ICS, ranging from 0%-20% of patients per month (Figure 2). Following the start of our interventions, we met criteria for special cause allowing adjustment of the centerline.¹³ The mean percentage of patients receiving more than one ICS decreased from 7.4% to 0.7%. Figure 2 includes the n-value displayed each month and represents all patients admitted to the Hospital Medicine service with an asthma exacerbation who were administered at least one ICS.

Secondary Process Measure

During the baseline period, there were only rare occurrences (less than 1%) of a patient-supplied ICS being administered during an asthma admission. Following the start of our intervention period, the frequency of inpatient administration of patient-supplied ICS showed a rapid increase and met rules for special cause with an increase in the mean percent from 0.7% to 50% (Figure 3). The n-value displayed each month represents all patients admitted to the Hospital Medicine service for an asthma exacerbation administered at least one ICS.

Cost Outcome Measure

The average cost of an ICS billed during hospitalization for an acute asthma exacerbation was $236.57 per ICS during the baseline period. After the intervention period, the average inpatient cost for ICS decreased by 62% to $90.25 per ICS (Figure 4).

Balancing Measure

Our team reduced the monthly percent of children hospitalized with an acute asthma exacerbation administered more than one ICS from 7.4% to 0.7% after implementation of a new workflow process for ordering ICS utilizing the hospital-based outpatient pharmacy. The new workflow delayed ordering and administration of the initial inpatient ICS treatment, allowing time to consider a step-up in therapy. The brief delay in initiating ICS is not expected to have clinical consequence given the concomitant treatment with systemic corticosteroids. In addition, the outpatient pharmacy was utilized to verify insurance coverage reliably prior to dispensing ICS, reducing medication waste, and discharge delays due to outpatient medication formulary conflicts.

Our hospital’s previous approach to inpatient asthma care resulted in a highly reliable process to ensure patients were discharged with medications-in-hand as part of a broader system that effectively decreased reutilization. However, the previous process inadvertently resulted in medication waste. This waste included nearly full inhalers being discarded, additional work by the healthcare team (ordering providers, pharmacists, and RTs), and unnecessary patient charges.

While the primary driver of our decision to use the outpatient pharmacy was to adjudicate insurance prescription coverage reliably to prevent waste, this change likely resulted in a financial benefit to patients. The average cost per asthma admission of an inpatient billed for ICS using the average wholesale price, decreased by 62% following our interventions. The decrease in cost was primarily driven by using patient-supplied medications, including prescriptions newly filled by the on-site outpatient pharmacy, whose costs were not captured in this measure. While our secondary measure may underestimate the total expense incurred by families for an ICS, families likely receive their medications at a lower cost from the outpatient pharmacy than if the ICS was provided by an inpatient pharmacy. The average wholesale price is not what families are charged or pay for medications, partly due to differences in overhead costs that result in inpatient pharmacies having significantly higher charges than outpatient pharmacies. In addition, the 6.7% absolute reduction of our primary measure resulted in direct savings by reducing inpatient medication waste. Our process results in 67 fewer wasted ICS devices ($15,960) per 1,000 admissions for asthma exacerbation, extrapolated using the average cost ($238.20, average wholesale price) of each ICS during the baseline period.

Our quality improvement study had several limitations. (1) The interventions occurred at a single center with an established culture that embraces quality improvement, which may limit the generalizability of the work. (2) Our process verified insurance coverage with a hospital-based outpatient pharmacy. Some ICS prescriptions continued to be dispensed from the inpatient pharmacy, limiting our ability to verify insurance coverage. Local factors, including regulatory restrictions and delivery requirements, may limit the generalizability of using an outpatient pharmacy in this manner. (3) We achieved our goal of decreasing medication waste, but our a priori goal was to maintain our commitment to our established practice of interactive patient education with an ICS device as well as medications-in-hand at time of discharge. Our balancing measure showed a decrease in the percent of patients with a discharge prescription for an ICS who also received an inpatient dose of that ICS. This implies a decreased fidelity in our previously established education protocols. We had postulated that this occurred when the patient-supplied medication arrived on the day of discharge, but not close to when the medication was scheduled on the medication administration report, preventing administration. However, this is not a direct measure of patients receiving medications-in-hand or interactive medication education. Both may have occurred without administration of the ICS. (4) Despite a hospital culture that embraces quality improvement, this project required a significant change in the workflow that required considerable education at the time of implementation to integrate the new process reliably. However, once the process was in place, we have been able to sustain our improvement with limited educational investment.

Implementation of a new process for ordering ICS that emphasized delaying treatment until all necessary information was available and using an outpatient pharmacy to confirm insurance formulary coverage reduced the waste associated with more than one ICS being prescribed during a single admission.

Acknowledgments

The authors thank Sally Pope, MPH and Dr. Michael Carlisle, MD for their contribution to the quality improvement project. Thank you to Drs. Karen McDowell, MD and Carolyn Kercsmar, MD for advisement of our quality improvement project.

The authors appreciate the following individuals for their invaluable contributions. Dr. Hoefgen conceptualized and designed the study, was a member of the primary improvement team, carried out initial analysis, drafted the initial manuscript, and reviewed and revised the manuscript. Drs. Jones and Torres Garcia, and Mr. Hare were members of the primary improvement team who contributed to the design of the quality improvement study and interventions, ongoing data interpretation, and critically reviewed the manuscript. Dr. Courter contributed to the conceptualization and designed the study, was a member of the primary improvement team, designed data collection instruments, and critically reviewed and revised the manuscript. Dr. Simmons conceptualized and designed the study, critically reviewed the manuscript for important intellectual content, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Disclaimer

The information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by the BHPR, HRSA, DHHS, or the U.S. Government.

Asthma results in approximately 125,000 hospitalizations for children annually in the United States.^1,2 The National Heart, Lung, and Blood Institute guidelines recommend that children with persistent asthma be treated with a daily controller medication, ie, an inhaled corticosteroid (ICS).³ Hospitalization for an asthma exacerbation provides an opportunity to optimize daily controller medications and improve disease self-management by providing access to medications and teaching appropriate use of complicated inhalation devices.

To reduce readmission⁴ by mitigating low rates of postdischarge filling of ICS prescriptions,^5,6 a strategy of “meds-in-hand” was implemented at discharge. “Meds-in-hand” mitigates medication access as a barrier to adherence by ensuring that patients are discharged from the hospital with all required medications in hand, removing any barriers to filling their initial prescriptions.⁷ The Asthma Improvement Collaborative at Cincinnati Children’s Hospital Medical Center (CCHMC) previously applied quality improvement methodology to implement “meds-in-hand” as a key intervention in a broad strategy that successfully reduced asthma-specific utilization for the 30-day period following an asthma-related hospitalization of publicly insured children from 12% to 7%.^8,9

At the onset of the work described in this manuscript, children hospitalized with an acute exacerbation of persistent asthma were most often treated with an ICS while inpatients in addition to a standard short course of oral systemic corticosteroids. Conceptually, inpatient administration of ICS provided the opportunity to teach effective device usage with each inpatient administration and to reinforce daily use of the ICS as part of the patient’s daily home medication regimen. However, a proportion of patients admitted for an asthma exacerbation were noted to receive more than one ICS inhaler during their admission, most commonly due to a change in dose or type of ICS. When this occurred, the initially dispensed inhaler was discarded despite weeks of potential doses remaining. While some hospitals preferentially dispense ICS devices marketed to institutions with fewer doses per device, our pharmacy primarily dispensed ICS devices identical to retail locations containing at least a one-month supply of medication. In addition to the wasted medication, this practice resulted in additional work by healthcare staff, unnecessary patient charges, and potentially contributed to confusion about the discharge medication regimen.

Our specific aim for this quality improvement study was to reduce the monthly percentage of admissions for an acute asthma exacerbation treated with >1 ICS from 7% to 4% over a six-month period.

Context

CCHMC is a quaternary care pediatric health system with more than 600 inpatient beds and 800-900 inpatient admissions per year for acute asthma exacerbation. The Hospital Medicine service cares for patients with asthma on five clinical teams across two different campuses. Care teams are supervised by an attending physician and may include residents, fellows, or nurse practitioners. Patients hospitalized for an acute asthma exacerbation may receive a consult from the Asthma Center consult team, staffed by faculty from either the Pediatric Pulmonology or Allergy/Immunology divisions. Respiratory therapists (RTs) administer inhaled medications and provide asthma education.

Planning the Intervention

Our improvement team included physicians from Hospital Medicine and Pulmonary Medicine, an Asthma Education Coordinator, a Clinical Pharmacist, a Pediatric Chief Resident, and a clinical research coordinator. Initial interventions targeted a single resident team at the main campus before spreading improvement activities to all resident teams at the main campus and then the satellite campus by February 2017.

Development of our process map (Figure 1) revealed that the decision for ordering inpatient ICS treatment frequently occurred at admission. Subsequently, the care team or consulting team might make a change in the ICS to fine-tune the outpatient medication regimen given that admission for asthma often results from suboptimal chronic symptom control. Baseline analysis of changes in ICS orders revealed that 81% of ICS changes were associated with a step-up in therapy, defined as an increase in the daily dose of the ICS or the addition of a long-acting beta-agonist. The other common ICS adjustment, accounting for 17%, was a change in corticosteroid without a step-up in therapy, (ie, beclomethasone to fluticasone) that typically occurred near the end of the hospitalization to accommodate outpatient insurance formularies, independent of patient factors related to illness severity.

Improvement Activities

We conceived key drivers or domains that would be necessary to address to effect change. Key drivers included a standardized process for delayed initiation of ICS and confirmation of outpatient insurance prescription drug coverage, prescriber education, and real-time failure notification.

PDSA Interventions

PDSA 1 & 2: Standardized Process for Initiation of ICS

Our initial tests of change targeted the timing of when an ICS was ordered during hospitalization for an asthma exacerbation. Providers were instructed to delay ordering an ICS until the patient’s albuterol treatments were spaced to every three hours and to include a standardized communication prompt within the albuterol order. The prompt instructed the RT to contact the provider once the patient’s albuterol treatments were spaced to every three hours and ask for an ICS order, if appropriate. This intervention was abandoned because it did not reliably occur.

The subsequent intervention delayed the start of ICS treatment by using a PRN indication advising that the ICS was to be administered once the patient’s albuterol treatments were spaced to every three hours. However, after an error resulted in the PRN indication being included on a discharge prescription for an ICS, the PRN indication was abandoned. Subsequent work to develop a standardized process for delayed initiation of ICS occurred as part of the workflow to address the confirmation of outpatient formulary coverage as described next.

PDSA 3: Prioritize the Use of the Institution’s Outpatient Pharmacy

Medication changes that occurred because of outpatient insurance formulary denials were a unique challenge; they required a medication change after the discharge treatment plan had been finalized, and a prescription was already submitted to the outpatient pharmacy. In addition, neither our inpatient electronic medical record nor our inpatient hospital pharmacy has access to decision support tools that incorporate outpatient prescription formulary coverage. Alternatively, outpatient pharmacies have a standard workflow that routinely confirms insurance coverage before dispensing medication. The institutional policy was modified to allow for the inpatient administration of patient-supplied medications, pursuant to an inpatient order. Patient-supplied medications include those brought from home or those supplied by the outpatient pharmacy.

Subsequently, we developed a standardized process to confirm outpatient prescription drug coverage by using our hospital-based outpatient pharmacy to dispense ICS for inpatient treatment and asthma education. This new workflow included placing an order for an ICS at admission as a patient-supplied medication with an administration comment to “please administer once available from the outpatient pharmacy” (Figure 1). Then, once the discharge medication plan is finalized, the prescription is submitted to the outpatient pharmacy. Following verification of insurance coverage, the outpatient pharmacy dispenses the ICS, allowing it to be used for patient education and inpatient administration. If the patient is ineligible to have their prescription filled by the outpatient pharmacy for reasons other than formulary coverage, the ICS is dispensed from the hospital inpatient pharmacy as per the previous standard workflow. Inpatient ICS inhalers are then relabeled for home use per the existing practice to support medications-in-hand.

Further workflow improvements occurred following the development of an algorithm to help the outpatient pharmacy contact the correct inpatient team, and augmentation of the medication delivery process included notification of the RT when the ICS was delivered to the inpatient unit.

PDSA 4: Prescriber Education

Prescribers received education regarding PDSA interventions before testing and throughout the improvement cycle. Education sessions included informal coaching by the Asthma Education Coordinator, e-mail reminders containing screenshots of the ordering process, and formal didactic sessions for ordering providers. The Asthma Education Coordinator also provided education to the nursing and respiratory therapy staff regarding the implemented process and workflow changes.

PDSA 5: Real-Time Failure Notification

To supplement education for the complicated process change, the improvement team utilized a decision support tool (Vigilanz Corp., Chicago, IL) linked to EMR data to provide notification of real-time process failures. When a patient with an admission diagnosis of asthma had a prescription for an ICS verified and dispensed by the inpatient pharmacy, an automated message with relevant patient information would be sent to a member of the improvement team. Following a brief chart review, directed feedback could be offered to the ordering provider, allowing the prescription to be redirected to the outpatient pharmacy.

Study of the Improvement

Patients of all ages, with the International Classification of Diseases, Ninth Revision, and Tenth Revision codes for asthma (493.xx or J45.xx) were included in data collection and analysis if they were treated by the Hospital Medicine service, as the first inpatient service or after transfer from the ICU, and prescribed an ICS with or without a long-acting beta-agonist. Data were collected retrospectively and aggregated monthly. The baseline period was from January 2015 through October 2016. The intervention period was from November 2016 through March 2018. The prolonged baseline and study periods were utilized to understand the seasonal nature of asthma exacerbations.

Measures

Our primary outcome measure was defined as the monthly number of patients admitted to Hospital Medicine for an acute asthma exacerbation administered more than one ICS divided by the total number of asthma patients administered at least one dose of an ICS (patient-supplied or dispensed from the inpatient pharmacy). A full list of ICS is included in the appendix Table.

A secondary process measure approximated our adherence to obtaining ICS from the outpatient pharmacy for inpatient use. All medications administered during hospitalization are documented in the medication administration report. However, only medications dispensed from the inpatient pharmacy are associated with a patient charge. Patient-supplied medications, including those dispensed from the hospital outpatient pharmacy, are not associated with an inpatient charge. Therefore, the secondary process measure was defined as the monthly number of asthma patients administered an ICS not associated with an inpatient charge divided by the total number of asthma patients administered an ICS.

A cost outcome measure was developed to track changes in the average cost of an ICS included on inpatient bills during hospitalization for an asthma exacerbation. This outcome measure was defined as the total monthly cost, using the average wholesale price, of the ICS included on the inpatient bill for an asthma exacerbation, divided by the total number of asthma patients administered at least one dose of an ICS (patient supplied or dispensed from the inpatient pharmacy). The costs of patient-supplied medications (including those dispensed from the outpatient pharmacy) are not included on inpatient hospital bills or this secondary outcome measure.

Our a priori intent was to reduce ICS medication waste while maintaining a highly reliable system that included inpatient administration and education with ICS devices and maintain our medications-in-hand practice. A balancing measure was developed to monitor the reliability of inpatient administration of ICS. It was defined as the monthly number of patients who received a discharge prescription for an ICS and were administered an ICS while an inpatient divided by the total number of asthma patients with a discharge prescription for an ICS.

Analysis

Measures were evaluated using statistical process control charts and special cause variation was determined by previously established rules. Our primary, secondary, and balancing measures were all evaluated using a p-chart with variable subgroup size. The cost outcome measure was evaluated using an X-bar S control chart.^11-13

Primary Outcome Measure

During the baseline period, 7.4% of patients admitted to Hospital Medicine for an acute asthma exacerbation were administered more than one ICS, ranging from 0%-20% of patients per month (Figure 2). Following the start of our interventions, we met criteria for special cause allowing adjustment of the centerline.¹³ The mean percentage of patients receiving more than one ICS decreased from 7.4% to 0.7%. Figure 2 includes the n-value displayed each month and represents all patients admitted to the Hospital Medicine service with an asthma exacerbation who were administered at least one ICS.

Secondary Process Measure

During the baseline period, there were only rare occurrences (less than 1%) of a patient-supplied ICS being administered during an asthma admission. Following the start of our intervention period, the frequency of inpatient administration of patient-supplied ICS showed a rapid increase and met rules for special cause with an increase in the mean percent from 0.7% to 50% (Figure 3). The n-value displayed each month represents all patients admitted to the Hospital Medicine service for an asthma exacerbation administered at least one ICS.

Cost Outcome Measure

The average cost of an ICS billed during hospitalization for an acute asthma exacerbation was $236.57 per ICS during the baseline period. After the intervention period, the average inpatient cost for ICS decreased by 62% to $90.25 per ICS (Figure 4).

Balancing Measure

Our team reduced the monthly percent of children hospitalized with an acute asthma exacerbation administered more than one ICS from 7.4% to 0.7% after implementation of a new workflow process for ordering ICS utilizing the hospital-based outpatient pharmacy. The new workflow delayed ordering and administration of the initial inpatient ICS treatment, allowing time to consider a step-up in therapy. The brief delay in initiating ICS is not expected to have clinical consequence given the concomitant treatment with systemic corticosteroids. In addition, the outpatient pharmacy was utilized to verify insurance coverage reliably prior to dispensing ICS, reducing medication waste, and discharge delays due to outpatient medication formulary conflicts.

Our hospital’s previous approach to inpatient asthma care resulted in a highly reliable process to ensure patients were discharged with medications-in-hand as part of a broader system that effectively decreased reutilization. However, the previous process inadvertently resulted in medication waste. This waste included nearly full inhalers being discarded, additional work by the healthcare team (ordering providers, pharmacists, and RTs), and unnecessary patient charges.

While the primary driver of our decision to use the outpatient pharmacy was to adjudicate insurance prescription coverage reliably to prevent waste, this change likely resulted in a financial benefit to patients. The average cost per asthma admission of an inpatient billed for ICS using the average wholesale price, decreased by 62% following our interventions. The decrease in cost was primarily driven by using patient-supplied medications, including prescriptions newly filled by the on-site outpatient pharmacy, whose costs were not captured in this measure. While our secondary measure may underestimate the total expense incurred by families for an ICS, families likely receive their medications at a lower cost from the outpatient pharmacy than if the ICS was provided by an inpatient pharmacy. The average wholesale price is not what families are charged or pay for medications, partly due to differences in overhead costs that result in inpatient pharmacies having significantly higher charges than outpatient pharmacies. In addition, the 6.7% absolute reduction of our primary measure resulted in direct savings by reducing inpatient medication waste. Our process results in 67 fewer wasted ICS devices ($15,960) per 1,000 admissions for asthma exacerbation, extrapolated using the average cost ($238.20, average wholesale price) of each ICS during the baseline period.

Our quality improvement study had several limitations. (1) The interventions occurred at a single center with an established culture that embraces quality improvement, which may limit the generalizability of the work. (2) Our process verified insurance coverage with a hospital-based outpatient pharmacy. Some ICS prescriptions continued to be dispensed from the inpatient pharmacy, limiting our ability to verify insurance coverage. Local factors, including regulatory restrictions and delivery requirements, may limit the generalizability of using an outpatient pharmacy in this manner. (3) We achieved our goal of decreasing medication waste, but our a priori goal was to maintain our commitment to our established practice of interactive patient education with an ICS device as well as medications-in-hand at time of discharge. Our balancing measure showed a decrease in the percent of patients with a discharge prescription for an ICS who also received an inpatient dose of that ICS. This implies a decreased fidelity in our previously established education protocols. We had postulated that this occurred when the patient-supplied medication arrived on the day of discharge, but not close to when the medication was scheduled on the medication administration report, preventing administration. However, this is not a direct measure of patients receiving medications-in-hand or interactive medication education. Both may have occurred without administration of the ICS. (4) Despite a hospital culture that embraces quality improvement, this project required a significant change in the workflow that required considerable education at the time of implementation to integrate the new process reliably. However, once the process was in place, we have been able to sustain our improvement with limited educational investment.

Implementation of a new process for ordering ICS that emphasized delaying treatment until all necessary information was available and using an outpatient pharmacy to confirm insurance formulary coverage reduced the waste associated with more than one ICS being prescribed during a single admission.

Acknowledgments

The authors thank Sally Pope, MPH and Dr. Michael Carlisle, MD for their contribution to the quality improvement project. Thank you to Drs. Karen McDowell, MD and Carolyn Kercsmar, MD for advisement of our quality improvement project.

The authors appreciate the following individuals for their invaluable contributions. Dr. Hoefgen conceptualized and designed the study, was a member of the primary improvement team, carried out initial analysis, drafted the initial manuscript, and reviewed and revised the manuscript. Drs. Jones and Torres Garcia, and Mr. Hare were members of the primary improvement team who contributed to the design of the quality improvement study and interventions, ongoing data interpretation, and critically reviewed the manuscript. Dr. Courter contributed to the conceptualization and designed the study, was a member of the primary improvement team, designed data collection instruments, and critically reviewed and revised the manuscript. Dr. Simmons conceptualized and designed the study, critically reviewed the manuscript for important intellectual content, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Disclaimer

The information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by the BHPR, HRSA, DHHS, or the U.S. Government.

Hip fractures in the elderly are associated with significant morbidity and mortality.¹ These are typically fragility fractures since they are caused by mechanical forces that would ordinarily not result in a serious injury, such as a fall from or below standing level. The incidence of hip fractures in the United States is expected to increase as the population ages; estimates project 512,000 hip fractures with an associated cost of $16 billion annually by the year 2040.² Timely surgery is recommended for hip fracture patients as delayed surgery beyond 24 to 48 hours of presentation is associated with increased morbidity and mortality.^3-6 Time to surgery (TTS) has been shown to be the major potentially modifiable risk factor in the management of a hip fracture.⁷

Factors that have been noted to influence TTS include the American Society of Anesthesiologists’ (ASA) score, the day of the week of hospital admission, and preoperative testing.^8,9 Preoperative cardiology consultation and subsequent cardiac testing, in particular, can increase the TTS and length of stay (LOS) without changing perioperative management.^9,10 In our review of literature, we could not identify any studies specifically looking at the impact of preoperative specialty consults on short-term mortality or comparison of care provided by hospitalists alone versus additionally involving subspecialists such as cardiologists. To our knowledge, there are no studies that have categorized recommendations from a preoperative specialty consult as minor, moderate, or major.

Our study evaluated whether preoperative specialty consults meaningfully change management and influence outcomes for hip fracture patients. At our institution, all hip fracture patients are admitted to the hospitalist service and comanaged with the orthopedic team. The hospitalist physician performs the preoperative evaluation as part of the admission history and physical exam. Preoperative specialty consult(s), if needed, are requested only by the hospitalist team. A consultant such as a cardiologist provides input; however, final management decisions are coordinated by the hospitalist physician.

Study Design

We performed a retrospective cohort study of patients aged 50 years and older who underwent surgery for an isolated fragility fracture of the hip at Hartford Hospital, a level one trauma and tertiary care medical center, within the 24-month period from April 2015 to March 2017. Fragility hip fracture is defined as one occurring from a fall of a height of standing or less. A consult referred to a specialty or subspecialty consultation, other than hospital medicine, obtained prior to surgery. Patients with additional skeletal trauma and periprosthetic fractures were excluded. A total of 491 unique patients met the inclusion criteria, and data were obtained from chart review and an orthopedic surgery registry. The Hartford Hospital Institutional Review Board approved this study.

Our primary predictor was the presence or absence of a preoperative specialty consultation requested by the hospitalist. We also analyzed the following: covariates of demographics (age, sex, race), the ASA score, and severity of comorbidities using the Charlson comorbidity index (CCI) with a Quan modification;¹¹ “R program package, International Classification of Disease (ICD)”¹² was used to calculate the CCI using ICD-9 and ICD-10 diagnostic codes.

The primary outcome measures were TTS (measured in hours), LOS (measured in days), complications, and preoperative specialty consult resulting in a change in perioperative management. TTS was defined as the time elapsed from the presentation at the emergency department (ED) to surgery start. For transfer or direct admission patients, the time of admission was used in place of time of presentation. The measured complications included postoperative venous thromboembolic events, surgical site infection, myocardial infarction, stroke, and sepsis. Secondary outcome measures included 30-day mortality, readmission rate, and rate of return to OR. There were no elective or planned readmissions postoperatively on review of our institution’s orthopedic surgery registry.

Our team performed an extensive chart review including reviewing the admission note, consulting physician notes, and relevant test results. Our senior investigator (MK) then rated each preoperative specialty consult on appropriateness, the relative strength of the consultant’s recommendation, and resulting change in perioperative management. Cardiology consultations were deemed reasonable if a patient’s cardiac risk was considered elevated by the admitting physician or an active cardiac condition was present (suggestion of or clear evidence for acute coronary syndrome, acute congestive heart failure, uncontrolled arrhythmia, or symptomatic valvular disease). The determination of “elevated cardiac risk” was made, if admit note contained verbiage expressing concern for further evaluation for cardiac issues or words such as “high risk” or “elevated risk”. A specific guideline-based score such as the revised cardiac risk index was not consistently available in this retrospective chart review. A noncardiology consult was deemed reasonable only if it would have been warranted for the specific clinical situation­—for example, a neurology consult for an acute stroke or a pulmonary consult for acute respiratory failure. Consult recommendations or outcomes were rated as minor, moderate, or major (see Table 1 for detailed criteria). Some consults may generate more than one recommendation, in these cases, we determined that a major recommendation supersedes a moderate or minor recommendation and only one was counted in the final analysis. Next we determined if a consult recommendation led to a change in perioperative or therapeutic management, defined as a medication or dosage change, need to delay surgery to stabilize an unstable medical condition, invasive procedures (such as thoracentesis or cardiac catheterization) or change in postoperative monitoring. As a way of clarification, a consult may have a minor recommendation such as an EKG but if no other recommendations were given and there was no change in therapeutic management such as a medication change, this would be considered as a “no change”.

Statistical Analysis

The main analyses compared the two patient subgroups (with or without preoperative specialty consults) around outcome measures. Primary outcome measures were TTS, LOS, complications, and consult resulting in a change in perioperative management. Secondary outcome measures were 30-day readmit, return to OR, and mortality. A preliminary analysis was conducted to explore distributions for TTS and LOS. As expected, none met the assumptions of normality and were thus analyzed with Wilcoxon ranked-sum tests. The other outcomes were dichotomous and analyzed with chi-square tests of proportion or Fisher’s exact test when the expected cell frequencies were too low. Dichotomized variables for TTS (within 24 hours and 48 hours) and LOS (within five days, the median LOS for this cohort) were calculated and subsequently analyzed with additional chi-square tests of proportion or Fisher’s exact test¹³. To explore the effect of preoperative specialty consults independent of potential confounders, logistic regression analyses predicting each of the dichotomous outcomes were conducted with age and CCI used as predictors in addition to the main variable of whether or not there was a preoperative specialty consult. Since the CCI and ASA scores were highly intercorrelated, only the former was chosen for the multivariate analyses based on the consistent algorithm used to calculate CCI.

Additional analyses with the subgroup of patients with a preoperative specialty consult explored whether the consult was reasonable, the relative strength of resulting recommendation and whether it resulted in a change in management. The statistical approach used was the same as for the other dichotomous outcomes. All analyses used 0.05 as the level of statistical significance; SPSSv21 (IBM, Armonk, New York) was the statistical software used.

The sample size for this retrospective analysis was determined by the available number of patients meeting the inclusion criteria. An a priori power calculation was done to determine if the expected volume would be sufficient for the multivariate analysis; the presence of a complication was selected for calculation. Based on an expected volume of approximately 500 and an estimate of a 10% serious complication rate, it was determined that the sample could support the analysis of up to five predictor variables, sufficient for the main variable and four potential confounders; this was considered adequate.¹⁴ Propensity scoring was considered but did not offer any advantages to logistic regression because we only had two observed covariates: CCI and age.

A total of 491 unique patients met our inclusion criteria, 177 patients had a preoperative specialty consult. Of these 177 patients, 24 patients had more than one consult; hence, the total number of consults was 201. Most of the consults were cardiology (159). Others were Infectious disease (11), Pulmonology (10), Neurology (7), and Miscellaneous (14, which included Nephrology, Gastroenterology, Hematology, and Oncology).

No significant differences were found between the consult and no-consult groups with respect to gender, race, body mass index, type of anesthesia, and day of the week of surgery. We did note that patients with a consult were older and had a significantly higher CCI and ASA score (Table 2).

Patients with preoperative specialty consults were older and had more comorbidities than patients without consults. Our findings suggest that consults contribute to delays to surgery and may lead to higher LOS and higher risk of 30-day readmission after controlling for age and comorbidities in a multivariate analysis. This observation is significant considering that consults were requested more frequently on patients with a higher comorbidity burden and included patients who did not get additional preoperative testing, suggesting that a delay from waiting for a consult alone may be deleterious. This was a unique observation in our study; prior studies examining this subject have attributed delays to additional testing and not consults alone. Even though most consult requests appear to be reasonable according to our criteria, the majority of recommendations were minor (72.9%), and 62.7% of consults resulted in no change in perioperative management. Major changes in perioperative management were noted in only 4.5% of patients.

Our finding that a majority of patients in the consult group had no significant change in perioperative management raises an important area of potential improvement in the care of hip fracture patients. We believe that narrowing indications for preoperative specialty consults may result in shorter TTS and LOS for this group of frail elderly patients without sacrificing the quality of care. Since all patients in our study were comanaged by hospitalists and patients without additional consults had similar or better outcomes, we believe that hospitalist physicians are well positioned to provide standardized comanagement to this patient group without additional consultation unless absolutely necessary.

The primary limitation of our study was that this was a retrospective case analysis. The designation of minor, moderate, or major recommendation was done after the consults were already completed, and it may not be possible to predict that a consult results in no change without it being actually performed. Additionally, our classification of recommendations is somewhat arbitrary and subjective; for example, some readers might argue that a medication change counts as a moderate recommendation. We rated a medication change to be minor as we believe that an experienced hospitalist may likely make such management decisions on their own, and if this is the only recommendation from a consult, it is not additional information critical to patient care. There may also be an “unmeasured complexity” noted by the admitting physician, which was not necessarily accounted for by multivariate analysis of age and CCI but one that led to higher mortality and readmissions. However, we feel that this “unmeasured complexity” is likely inconsequential as the vast majority of consults did not result in any change in management. We did adjust for covariates as noted, but some confounding by indication is likely to remain. Additionally, categorization of consult recommendations and consequent changes by one physician could be considered subjective. We did control for this by having another physician review the entire dataset and rate it independently for interrater reliability with excellent correlation and kappa, although these may be inflated to some degree because our chart review did not account for variability among chart extractors.

A prospective evaluation of a clinical protocol that delineates reasonable indications for a preoperative consult would be helpful to validate our findings. In our study, we noted moderate or major recommendations from a cardiologist only in cases where an active cardiac condition was suspected by the hospitalist requesting the consult; hence, limiting preoperative cardiology consults to active cardiac conditions may be a reasonable approach to evaluate in a prospective study.

In conclusion, a majority of preoperative specialty consults do not appear to meaningfully influence management and may indirectly increase morbidity by delaying surgery and extending hospital stays. Our data suggest that unless the patient is clinically unstable and likely to require active management by a consultant prior to hip fracture repair, consults may offer limited benefit. Appropriately standardized perioperative management of this patient group by hospitalist physicians appears to manage most hip fracture patients as effectively with faster TTS and shorter hospital LOS.

Acknowledgments

The authors would like to thank John Corradi, PhD (Research Department at Hartford Hospital) for his input in calculating the Charlson comorbidity index.^12,13

Hip fractures in the elderly are associated with significant morbidity and mortality.¹ These are typically fragility fractures since they are caused by mechanical forces that would ordinarily not result in a serious injury, such as a fall from or below standing level. The incidence of hip fractures in the United States is expected to increase as the population ages; estimates project 512,000 hip fractures with an associated cost of $16 billion annually by the year 2040.² Timely surgery is recommended for hip fracture patients as delayed surgery beyond 24 to 48 hours of presentation is associated with increased morbidity and mortality.^3-6 Time to surgery (TTS) has been shown to be the major potentially modifiable risk factor in the management of a hip fracture.⁷

Factors that have been noted to influence TTS include the American Society of Anesthesiologists’ (ASA) score, the day of the week of hospital admission, and preoperative testing.^8,9 Preoperative cardiology consultation and subsequent cardiac testing, in particular, can increase the TTS and length of stay (LOS) without changing perioperative management.^9,10 In our review of literature, we could not identify any studies specifically looking at the impact of preoperative specialty consults on short-term mortality or comparison of care provided by hospitalists alone versus additionally involving subspecialists such as cardiologists. To our knowledge, there are no studies that have categorized recommendations from a preoperative specialty consult as minor, moderate, or major.

Our study evaluated whether preoperative specialty consults meaningfully change management and influence outcomes for hip fracture patients. At our institution, all hip fracture patients are admitted to the hospitalist service and comanaged with the orthopedic team. The hospitalist physician performs the preoperative evaluation as part of the admission history and physical exam. Preoperative specialty consult(s), if needed, are requested only by the hospitalist team. A consultant such as a cardiologist provides input; however, final management decisions are coordinated by the hospitalist physician.

Study Design

We performed a retrospective cohort study of patients aged 50 years and older who underwent surgery for an isolated fragility fracture of the hip at Hartford Hospital, a level one trauma and tertiary care medical center, within the 24-month period from April 2015 to March 2017. Fragility hip fracture is defined as one occurring from a fall of a height of standing or less. A consult referred to a specialty or subspecialty consultation, other than hospital medicine, obtained prior to surgery. Patients with additional skeletal trauma and periprosthetic fractures were excluded. A total of 491 unique patients met the inclusion criteria, and data were obtained from chart review and an orthopedic surgery registry. The Hartford Hospital Institutional Review Board approved this study.

Our primary predictor was the presence or absence of a preoperative specialty consultation requested by the hospitalist. We also analyzed the following: covariates of demographics (age, sex, race), the ASA score, and severity of comorbidities using the Charlson comorbidity index (CCI) with a Quan modification;¹¹ “R program package, International Classification of Disease (ICD)”¹² was used to calculate the CCI using ICD-9 and ICD-10 diagnostic codes.

The primary outcome measures were TTS (measured in hours), LOS (measured in days), complications, and preoperative specialty consult resulting in a change in perioperative management. TTS was defined as the time elapsed from the presentation at the emergency department (ED) to surgery start. For transfer or direct admission patients, the time of admission was used in place of time of presentation. The measured complications included postoperative venous thromboembolic events, surgical site infection, myocardial infarction, stroke, and sepsis. Secondary outcome measures included 30-day mortality, readmission rate, and rate of return to OR. There were no elective or planned readmissions postoperatively on review of our institution’s orthopedic surgery registry.

Our team performed an extensive chart review including reviewing the admission note, consulting physician notes, and relevant test results. Our senior investigator (MK) then rated each preoperative specialty consult on appropriateness, the relative strength of the consultant’s recommendation, and resulting change in perioperative management. Cardiology consultations were deemed reasonable if a patient’s cardiac risk was considered elevated by the admitting physician or an active cardiac condition was present (suggestion of or clear evidence for acute coronary syndrome, acute congestive heart failure, uncontrolled arrhythmia, or symptomatic valvular disease). The determination of “elevated cardiac risk” was made, if admit note contained verbiage expressing concern for further evaluation for cardiac issues or words such as “high risk” or “elevated risk”. A specific guideline-based score such as the revised cardiac risk index was not consistently available in this retrospective chart review. A noncardiology consult was deemed reasonable only if it would have been warranted for the specific clinical situation­—for example, a neurology consult for an acute stroke or a pulmonary consult for acute respiratory failure. Consult recommendations or outcomes were rated as minor, moderate, or major (see Table 1 for detailed criteria). Some consults may generate more than one recommendation, in these cases, we determined that a major recommendation supersedes a moderate or minor recommendation and only one was counted in the final analysis. Next we determined if a consult recommendation led to a change in perioperative or therapeutic management, defined as a medication or dosage change, need to delay surgery to stabilize an unstable medical condition, invasive procedures (such as thoracentesis or cardiac catheterization) or change in postoperative monitoring. As a way of clarification, a consult may have a minor recommendation such as an EKG but if no other recommendations were given and there was no change in therapeutic management such as a medication change, this would be considered as a “no change”.

Statistical Analysis

The main analyses compared the two patient subgroups (with or without preoperative specialty consults) around outcome measures. Primary outcome measures were TTS, LOS, complications, and consult resulting in a change in perioperative management. Secondary outcome measures were 30-day readmit, return to OR, and mortality. A preliminary analysis was conducted to explore distributions for TTS and LOS. As expected, none met the assumptions of normality and were thus analyzed with Wilcoxon ranked-sum tests. The other outcomes were dichotomous and analyzed with chi-square tests of proportion or Fisher’s exact test when the expected cell frequencies were too low. Dichotomized variables for TTS (within 24 hours and 48 hours) and LOS (within five days, the median LOS for this cohort) were calculated and subsequently analyzed with additional chi-square tests of proportion or Fisher’s exact test¹³. To explore the effect of preoperative specialty consults independent of potential confounders, logistic regression analyses predicting each of the dichotomous outcomes were conducted with age and CCI used as predictors in addition to the main variable of whether or not there was a preoperative specialty consult. Since the CCI and ASA scores were highly intercorrelated, only the former was chosen for the multivariate analyses based on the consistent algorithm used to calculate CCI.

Additional analyses with the subgroup of patients with a preoperative specialty consult explored whether the consult was reasonable, the relative strength of resulting recommendation and whether it resulted in a change in management. The statistical approach used was the same as for the other dichotomous outcomes. All analyses used 0.05 as the level of statistical significance; SPSSv21 (IBM, Armonk, New York) was the statistical software used.

The sample size for this retrospective analysis was determined by the available number of patients meeting the inclusion criteria. An a priori power calculation was done to determine if the expected volume would be sufficient for the multivariate analysis; the presence of a complication was selected for calculation. Based on an expected volume of approximately 500 and an estimate of a 10% serious complication rate, it was determined that the sample could support the analysis of up to five predictor variables, sufficient for the main variable and four potential confounders; this was considered adequate.¹⁴ Propensity scoring was considered but did not offer any advantages to logistic regression because we only had two observed covariates: CCI and age.

A total of 491 unique patients met our inclusion criteria, 177 patients had a preoperative specialty consult. Of these 177 patients, 24 patients had more than one consult; hence, the total number of consults was 201. Most of the consults were cardiology (159). Others were Infectious disease (11), Pulmonology (10), Neurology (7), and Miscellaneous (14, which included Nephrology, Gastroenterology, Hematology, and Oncology).

No significant differences were found between the consult and no-consult groups with respect to gender, race, body mass index, type of anesthesia, and day of the week of surgery. We did note that patients with a consult were older and had a significantly higher CCI and ASA score (Table 2).

Patients with preoperative specialty consults were older and had more comorbidities than patients without consults. Our findings suggest that consults contribute to delays to surgery and may lead to higher LOS and higher risk of 30-day readmission after controlling for age and comorbidities in a multivariate analysis. This observation is significant considering that consults were requested more frequently on patients with a higher comorbidity burden and included patients who did not get additional preoperative testing, suggesting that a delay from waiting for a consult alone may be deleterious. This was a unique observation in our study; prior studies examining this subject have attributed delays to additional testing and not consults alone. Even though most consult requests appear to be reasonable according to our criteria, the majority of recommendations were minor (72.9%), and 62.7% of consults resulted in no change in perioperative management. Major changes in perioperative management were noted in only 4.5% of patients.

Our finding that a majority of patients in the consult group had no significant change in perioperative management raises an important area of potential improvement in the care of hip fracture patients. We believe that narrowing indications for preoperative specialty consults may result in shorter TTS and LOS for this group of frail elderly patients without sacrificing the quality of care. Since all patients in our study were comanaged by hospitalists and patients without additional consults had similar or better outcomes, we believe that hospitalist physicians are well positioned to provide standardized comanagement to this patient group without additional consultation unless absolutely necessary.

The primary limitation of our study was that this was a retrospective case analysis. The designation of minor, moderate, or major recommendation was done after the consults were already completed, and it may not be possible to predict that a consult results in no change without it being actually performed. Additionally, our classification of recommendations is somewhat arbitrary and subjective; for example, some readers might argue that a medication change counts as a moderate recommendation. We rated a medication change to be minor as we believe that an experienced hospitalist may likely make such management decisions on their own, and if this is the only recommendation from a consult, it is not additional information critical to patient care. There may also be an “unmeasured complexity” noted by the admitting physician, which was not necessarily accounted for by multivariate analysis of age and CCI but one that led to higher mortality and readmissions. However, we feel that this “unmeasured complexity” is likely inconsequential as the vast majority of consults did not result in any change in management. We did adjust for covariates as noted, but some confounding by indication is likely to remain. Additionally, categorization of consult recommendations and consequent changes by one physician could be considered subjective. We did control for this by having another physician review the entire dataset and rate it independently for interrater reliability with excellent correlation and kappa, although these may be inflated to some degree because our chart review did not account for variability among chart extractors.

A prospective evaluation of a clinical protocol that delineates reasonable indications for a preoperative consult would be helpful to validate our findings. In our study, we noted moderate or major recommendations from a cardiologist only in cases where an active cardiac condition was suspected by the hospitalist requesting the consult; hence, limiting preoperative cardiology consults to active cardiac conditions may be a reasonable approach to evaluate in a prospective study.

In conclusion, a majority of preoperative specialty consults do not appear to meaningfully influence management and may indirectly increase morbidity by delaying surgery and extending hospital stays. Our data suggest that unless the patient is clinically unstable and likely to require active management by a consultant prior to hip fracture repair, consults may offer limited benefit. Appropriately standardized perioperative management of this patient group by hospitalist physicians appears to manage most hip fracture patients as effectively with faster TTS and shorter hospital LOS.

Acknowledgments

The authors would like to thank John Corradi, PhD (Research Department at Hartford Hospital) for his input in calculating the Charlson comorbidity index.^12,13

Hip fractures in the elderly are associated with significant morbidity and mortality.¹ These are typically fragility fractures since they are caused by mechanical forces that would ordinarily not result in a serious injury, such as a fall from or below standing level. The incidence of hip fractures in the United States is expected to increase as the population ages; estimates project 512,000 hip fractures with an associated cost of $16 billion annually by the year 2040.² Timely surgery is recommended for hip fracture patients as delayed surgery beyond 24 to 48 hours of presentation is associated with increased morbidity and mortality.^3-6 Time to surgery (TTS) has been shown to be the major potentially modifiable risk factor in the management of a hip fracture.⁷

Factors that have been noted to influence TTS include the American Society of Anesthesiologists’ (ASA) score, the day of the week of hospital admission, and preoperative testing.^8,9 Preoperative cardiology consultation and subsequent cardiac testing, in particular, can increase the TTS and length of stay (LOS) without changing perioperative management.^9,10 In our review of literature, we could not identify any studies specifically looking at the impact of preoperative specialty consults on short-term mortality or comparison of care provided by hospitalists alone versus additionally involving subspecialists such as cardiologists. To our knowledge, there are no studies that have categorized recommendations from a preoperative specialty consult as minor, moderate, or major.

Our study evaluated whether preoperative specialty consults meaningfully change management and influence outcomes for hip fracture patients. At our institution, all hip fracture patients are admitted to the hospitalist service and comanaged with the orthopedic team. The hospitalist physician performs the preoperative evaluation as part of the admission history and physical exam. Preoperative specialty consult(s), if needed, are requested only by the hospitalist team. A consultant such as a cardiologist provides input; however, final management decisions are coordinated by the hospitalist physician.

Study Design

We performed a retrospective cohort study of patients aged 50 years and older who underwent surgery for an isolated fragility fracture of the hip at Hartford Hospital, a level one trauma and tertiary care medical center, within the 24-month period from April 2015 to March 2017. Fragility hip fracture is defined as one occurring from a fall of a height of standing or less. A consult referred to a specialty or subspecialty consultation, other than hospital medicine, obtained prior to surgery. Patients with additional skeletal trauma and periprosthetic fractures were excluded. A total of 491 unique patients met the inclusion criteria, and data were obtained from chart review and an orthopedic surgery registry. The Hartford Hospital Institutional Review Board approved this study.

Our primary predictor was the presence or absence of a preoperative specialty consultation requested by the hospitalist. We also analyzed the following: covariates of demographics (age, sex, race), the ASA score, and severity of comorbidities using the Charlson comorbidity index (CCI) with a Quan modification;¹¹ “R program package, International Classification of Disease (ICD)”¹² was used to calculate the CCI using ICD-9 and ICD-10 diagnostic codes.

The primary outcome measures were TTS (measured in hours), LOS (measured in days), complications, and preoperative specialty consult resulting in a change in perioperative management. TTS was defined as the time elapsed from the presentation at the emergency department (ED) to surgery start. For transfer or direct admission patients, the time of admission was used in place of time of presentation. The measured complications included postoperative venous thromboembolic events, surgical site infection, myocardial infarction, stroke, and sepsis. Secondary outcome measures included 30-day mortality, readmission rate, and rate of return to OR. There were no elective or planned readmissions postoperatively on review of our institution’s orthopedic surgery registry.

Our team performed an extensive chart review including reviewing the admission note, consulting physician notes, and relevant test results. Our senior investigator (MK) then rated each preoperative specialty consult on appropriateness, the relative strength of the consultant’s recommendation, and resulting change in perioperative management. Cardiology consultations were deemed reasonable if a patient’s cardiac risk was considered elevated by the admitting physician or an active cardiac condition was present (suggestion of or clear evidence for acute coronary syndrome, acute congestive heart failure, uncontrolled arrhythmia, or symptomatic valvular disease). The determination of “elevated cardiac risk” was made, if admit note contained verbiage expressing concern for further evaluation for cardiac issues or words such as “high risk” or “elevated risk”. A specific guideline-based score such as the revised cardiac risk index was not consistently available in this retrospective chart review. A noncardiology consult was deemed reasonable only if it would have been warranted for the specific clinical situation­—for example, a neurology consult for an acute stroke or a pulmonary consult for acute respiratory failure. Consult recommendations or outcomes were rated as minor, moderate, or major (see Table 1 for detailed criteria). Some consults may generate more than one recommendation, in these cases, we determined that a major recommendation supersedes a moderate or minor recommendation and only one was counted in the final analysis. Next we determined if a consult recommendation led to a change in perioperative or therapeutic management, defined as a medication or dosage change, need to delay surgery to stabilize an unstable medical condition, invasive procedures (such as thoracentesis or cardiac catheterization) or change in postoperative monitoring. As a way of clarification, a consult may have a minor recommendation such as an EKG but if no other recommendations were given and there was no change in therapeutic management such as a medication change, this would be considered as a “no change”.

Statistical Analysis

The main analyses compared the two patient subgroups (with or without preoperative specialty consults) around outcome measures. Primary outcome measures were TTS, LOS, complications, and consult resulting in a change in perioperative management. Secondary outcome measures were 30-day readmit, return to OR, and mortality. A preliminary analysis was conducted to explore distributions for TTS and LOS. As expected, none met the assumptions of normality and were thus analyzed with Wilcoxon ranked-sum tests. The other outcomes were dichotomous and analyzed with chi-square tests of proportion or Fisher’s exact test when the expected cell frequencies were too low. Dichotomized variables for TTS (within 24 hours and 48 hours) and LOS (within five days, the median LOS for this cohort) were calculated and subsequently analyzed with additional chi-square tests of proportion or Fisher’s exact test¹³. To explore the effect of preoperative specialty consults independent of potential confounders, logistic regression analyses predicting each of the dichotomous outcomes were conducted with age and CCI used as predictors in addition to the main variable of whether or not there was a preoperative specialty consult. Since the CCI and ASA scores were highly intercorrelated, only the former was chosen for the multivariate analyses based on the consistent algorithm used to calculate CCI.

Additional analyses with the subgroup of patients with a preoperative specialty consult explored whether the consult was reasonable, the relative strength of resulting recommendation and whether it resulted in a change in management. The statistical approach used was the same as for the other dichotomous outcomes. All analyses used 0.05 as the level of statistical significance; SPSSv21 (IBM, Armonk, New York) was the statistical software used.

The sample size for this retrospective analysis was determined by the available number of patients meeting the inclusion criteria. An a priori power calculation was done to determine if the expected volume would be sufficient for the multivariate analysis; the presence of a complication was selected for calculation. Based on an expected volume of approximately 500 and an estimate of a 10% serious complication rate, it was determined that the sample could support the analysis of up to five predictor variables, sufficient for the main variable and four potential confounders; this was considered adequate.¹⁴ Propensity scoring was considered but did not offer any advantages to logistic regression because we only had two observed covariates: CCI and age.

A total of 491 unique patients met our inclusion criteria, 177 patients had a preoperative specialty consult. Of these 177 patients, 24 patients had more than one consult; hence, the total number of consults was 201. Most of the consults were cardiology (159). Others were Infectious disease (11), Pulmonology (10), Neurology (7), and Miscellaneous (14, which included Nephrology, Gastroenterology, Hematology, and Oncology).

No significant differences were found between the consult and no-consult groups with respect to gender, race, body mass index, type of anesthesia, and day of the week of surgery. We did note that patients with a consult were older and had a significantly higher CCI and ASA score (Table 2).

Patients with preoperative specialty consults were older and had more comorbidities than patients without consults. Our findings suggest that consults contribute to delays to surgery and may lead to higher LOS and higher risk of 30-day readmission after controlling for age and comorbidities in a multivariate analysis. This observation is significant considering that consults were requested more frequently on patients with a higher comorbidity burden and included patients who did not get additional preoperative testing, suggesting that a delay from waiting for a consult alone may be deleterious. This was a unique observation in our study; prior studies examining this subject have attributed delays to additional testing and not consults alone. Even though most consult requests appear to be reasonable according to our criteria, the majority of recommendations were minor (72.9%), and 62.7% of consults resulted in no change in perioperative management. Major changes in perioperative management were noted in only 4.5% of patients.

Our finding that a majority of patients in the consult group had no significant change in perioperative management raises an important area of potential improvement in the care of hip fracture patients. We believe that narrowing indications for preoperative specialty consults may result in shorter TTS and LOS for this group of frail elderly patients without sacrificing the quality of care. Since all patients in our study were comanaged by hospitalists and patients without additional consults had similar or better outcomes, we believe that hospitalist physicians are well positioned to provide standardized comanagement to this patient group without additional consultation unless absolutely necessary.

The primary limitation of our study was that this was a retrospective case analysis. The designation of minor, moderate, or major recommendation was done after the consults were already completed, and it may not be possible to predict that a consult results in no change without it being actually performed. Additionally, our classification of recommendations is somewhat arbitrary and subjective; for example, some readers might argue that a medication change counts as a moderate recommendation. We rated a medication change to be minor as we believe that an experienced hospitalist may likely make such management decisions on their own, and if this is the only recommendation from a consult, it is not additional information critical to patient care. There may also be an “unmeasured complexity” noted by the admitting physician, which was not necessarily accounted for by multivariate analysis of age and CCI but one that led to higher mortality and readmissions. However, we feel that this “unmeasured complexity” is likely inconsequential as the vast majority of consults did not result in any change in management. We did adjust for covariates as noted, but some confounding by indication is likely to remain. Additionally, categorization of consult recommendations and consequent changes by one physician could be considered subjective. We did control for this by having another physician review the entire dataset and rate it independently for interrater reliability with excellent correlation and kappa, although these may be inflated to some degree because our chart review did not account for variability among chart extractors.

A prospective evaluation of a clinical protocol that delineates reasonable indications for a preoperative consult would be helpful to validate our findings. In our study, we noted moderate or major recommendations from a cardiologist only in cases where an active cardiac condition was suspected by the hospitalist requesting the consult; hence, limiting preoperative cardiology consults to active cardiac conditions may be a reasonable approach to evaluate in a prospective study.

In conclusion, a majority of preoperative specialty consults do not appear to meaningfully influence management and may indirectly increase morbidity by delaying surgery and extending hospital stays. Our data suggest that unless the patient is clinically unstable and likely to require active management by a consultant prior to hip fracture repair, consults may offer limited benefit. Appropriately standardized perioperative management of this patient group by hospitalist physicians appears to manage most hip fracture patients as effectively with faster TTS and shorter hospital LOS.

Acknowledgments

The authors would like to thank John Corradi, PhD (Research Department at Hartford Hospital) for his input in calculating the Charlson comorbidity index.^12,13

As a newly recognized specialty, pediatric hospital medicine (PHM) continues to expand and diversify.¹ Pediatric hospitalists care for children in hospitals ranging from small, rural community hospitals to large, free-standing quaternary children’s hospitals.^2-4 In addition, more than 10% of graduating pediatric residents are seeking future careers within PHM.⁵

In 2018, Fromme et al. published a study describing clinical workload for pediatric hospitalists within university-based settings.⁶ They characterized the diversity of work models and programmatic sustainability but limited the study to university-based programs. With over half of children receiving care within community hospitals,⁷ workforce patterns for community-based pediatric hospitalists should be characterized to maximize sustainability and minimize attrition across the field.

In this study, we describe programmatic variability in clinical work expectations of 70 community-based PHM programs. We aimed to describe existing work models and expectations of community-based program leaders as they relate to their unique clinical setting.

We conducted a cross-sectional survey of community-based PHM site directors through structured interviews. Community hospital programs were self-defined by the study participants, although typically defined as general hospitals that admit pediatric patients and are not free-standing or children’s hospitals within a general hospital. Survey respondents were asked to answer questions only reflecting expectations at their community hospital.

Survey Design and Content

Building from a tool used by Fromme et al.⁶ we created a 12-question structured interview questionnaire focused on three areas: (1) full-time employment (FTE) metrics including definitions of a 1.0 FTE, “typical” shifts, and weekend responsibilities; (2) work volume including census parameters, service-line coverage expectations, back-up systems, and overnight call responsibilities; and (3) programmatic model including sense of sustainability (eg, minimizing burnout and attrition), support for activities such as administrative or research time, and employer model (Appendix).

We modified the survey through research team consensus. After pilot-testing by research team members at their own sites, the survey was refined for item clarity, structural design, and length. We chose to administer surveys through phone interviews over a traditional distribution due to anticipated variability in work models. The research team discussed how each question should be asked, and responses were clarified to maintain consistency.

Survey Administration

Given the absence of a national registry or database for community-based PHM programs, study participation was solicited through an invitation posted on the American Academy of Pediatrics Section on Hospital Medicine (AAP SOHM) Listserv and the AAP SOHM Community Hospitalist Listserv in May 2018. Invitations were posted twice at two weeks apart. Each research team member completed 6-19 interviews. Responses to survey questions were recorded in REDCap, a secure, web-based data capture instrument.⁸

Participating in the study was considered implied consent, and participants did not receive a monetary incentive, although respondents were offered deidentified survey data for participation. The study was exempted through the University of Chicago Institutional Review Board.

Data Analysis

Employers were dichotomized as community hospital employer (including primary community hospital employment/private organization) or noncommunity hospital employer (including children’s/university hospital employment or school of medicine). Descriptive statistics were reported to compare the demographics of two employer groups. P values were calculated using two-sample t-tests for the continuous variables and chi-square or Fisher-exact tests for the categorical variables. Mann–Whitney U-test was performed for continuous variables without normality. Analyses were performed using the R Statistical Programming Language (R Foundation for Statistical Computing, Vienna, Austria), version 3.4.3.

Participation and Program Characteristics

We interviewed 70 community-based PHM site directors representing programs across 29 states (Table 1) and five geographic regions: Midwest (34.3%), Northeast (11.4%), Southeast (15.7%), Southwest (4.3%), and West (34.3%). Employer models varied across groups, with more noncommunity hospital employers (57%) than community hospital employers (43%). The top three services covered by pediatric hospitalists were pediatric inpatient or observation bed admissions (97%), emergency department consults (89%), and general newborns (67%). PHM programs also provided coverage for other services, including newborn deliveries (43%), Special Care Nursery/Level II Neonatal Intensive Care Unit (41%), step-down unit (20%), and mental health units (13%). About 59% of programs provided education for family medicine residents, 36% were for pediatric residents, and 70% worked with advanced practice providers. The majority of programs (70%) provided in-house coverage overnight.

Clinical Work Expectations and Employer Model

Clinical work expectations varied broadly across programs (Table 2). The median expected hours for a 1.0 FTE was 1,882 hours per year (interquartile range [IQR] 1,805, 2,016), and the median expected weekend coverage/year (defined as covering two days or two nights of the weekend) was 21 (IQR 14, 24). Most programs did not expand staff coverage based on seasonality (73%), and less than 20% of programs operated with a census cap. Median support for nondirect patient care activities was 4% (IQR 0,10) of a program’s total FTE (ie, a 5.0 FTE program would have 0.20 FTE support). Programs with community hospital employers had an 8% higher expectation of 1.0 FTE hours/year (P = .01) and viewed an appropriate pediatric morning census as 20% higher (P = .01; Table 2).

Program Sustainability

To our knowledge, this study is the first to describe clinical work models exclusively for pediatric community hospitalist programs. We found that expectations for clinical FTE hours, weekend coverage, appropriate morning census, support for nondirect patient care activities, and perception of sustainability varied broadly across programs. The only variable affecting some of these differences was employer model, with those employed by a community hospital employer having a higher expectation for hours/year and appropriate morning pediatric census than those employed by noncommunity hospital employers.

With a growing emphasis on physician burnout and career satisfaction,^9-11 understanding the characteristics of community hospital work settings is critical for identifying and building sustainable employment models. Previous studies have identified that the balance of clinical and nonclinical responsibilities and the setting of community versus university-based programs are major contributors to burnout and career satisfaction.^9,11 Interestingly, although community hospital-based programs have limited FTE for nondirect patient care activities, we found that a higher percentage of program site directors perceived their program models as sustainable when compared with university-based programs in prior research (63% versus 50%).⁶ Elucidating why community hospital PHM programs are perceived as more sustainable provides an opportunity for future research. Potential reasons may include fewer academic requirements for promotion or an increased connection to a local community.

We also found that the employer model had a statistically significant impact on expected FTE hours per year but not on perception of sustainability. Programs employed by community hospitals worked 8% more hours per year than those employed by noncommunity hospital employers and accepted a higher morning pediatric census. This variation in hours and census level appropriateness is likely multifactorial, potentially from higher nonclinical expectations for promotion (eg, academic or scholarly production) at school of medicine or children’s hospital employed programs versus limited reimbursement for administrative responsibilities within community hospital employment models.

There are several potential next steps for our findings. As our data are the first attempt (to our knowledge) at describing the current practice and expectations exclusively within community hospital programs, this study can be used as a starting point for the development of workload expectation standards. Increasing transparency nationally for individual community programs potentially promotes discussions around burnout and attrition. Having objective data to compare program models may assist in advocating with local hospital leadership for restructuring that better aligns with national norms.

Our study has several limitations. First, our sampling frame was based upon a self-selection of program directors. This may have led to a biased representation of programs with higher workloads motivated to develop a standard to compare with other programs, which may have potentially led to an overestimation of hours. Second, without a registry or database for community-based pediatric hospitalist programs, we do not know the percentage of community-based programs that our sample represents. Although our results cannot speak for all community PHM programs, we attempted to mitigate nonresponse bias through the breadth of programs represented, which spanned 29 states, five geographic regions, and teaching and nonteaching programs. The interview-based method for data collection allowed the research team to clarify questions and responses across sites, thereby improving the quality and consistency of the data for the represented study sample. Finally, other factors possibly contributed to sustainability that we did not address in this study, such as programs that are dependent on billable encounters as part of their salary support.

As a newly recognized subspecialty, creating a reference for community-based program leaders to determine and discuss individual models and expectations with hospital administrators may help address programmatic sustainability. It may also allow for the analysis of long-term career satisfaction and longevity within community PHM programs based on workload. Future studies should further explore root causes for workload discrepancies between community and university employed programs along with establishing potential standards for PHM program development.

Acknowledgments

We would like to thank the Stanford School of Medicine Quantitative Sciences Unit staff for their assistance in statistical analysis.

Disclosure

The authors have nothing to disclose.

As a newly recognized specialty, pediatric hospital medicine (PHM) continues to expand and diversify.¹ Pediatric hospitalists care for children in hospitals ranging from small, rural community hospitals to large, free-standing quaternary children’s hospitals.^2-4 In addition, more than 10% of graduating pediatric residents are seeking future careers within PHM.⁵

In 2018, Fromme et al. published a study describing clinical workload for pediatric hospitalists within university-based settings.⁶ They characterized the diversity of work models and programmatic sustainability but limited the study to university-based programs. With over half of children receiving care within community hospitals,⁷ workforce patterns for community-based pediatric hospitalists should be characterized to maximize sustainability and minimize attrition across the field.

In this study, we describe programmatic variability in clinical work expectations of 70 community-based PHM programs. We aimed to describe existing work models and expectations of community-based program leaders as they relate to their unique clinical setting.

We conducted a cross-sectional survey of community-based PHM site directors through structured interviews. Community hospital programs were self-defined by the study participants, although typically defined as general hospitals that admit pediatric patients and are not free-standing or children’s hospitals within a general hospital. Survey respondents were asked to answer questions only reflecting expectations at their community hospital.

Survey Design and Content

Building from a tool used by Fromme et al.⁶ we created a 12-question structured interview questionnaire focused on three areas: (1) full-time employment (FTE) metrics including definitions of a 1.0 FTE, “typical” shifts, and weekend responsibilities; (2) work volume including census parameters, service-line coverage expectations, back-up systems, and overnight call responsibilities; and (3) programmatic model including sense of sustainability (eg, minimizing burnout and attrition), support for activities such as administrative or research time, and employer model (Appendix).

We modified the survey through research team consensus. After pilot-testing by research team members at their own sites, the survey was refined for item clarity, structural design, and length. We chose to administer surveys through phone interviews over a traditional distribution due to anticipated variability in work models. The research team discussed how each question should be asked, and responses were clarified to maintain consistency.

Survey Administration

Given the absence of a national registry or database for community-based PHM programs, study participation was solicited through an invitation posted on the American Academy of Pediatrics Section on Hospital Medicine (AAP SOHM) Listserv and the AAP SOHM Community Hospitalist Listserv in May 2018. Invitations were posted twice at two weeks apart. Each research team member completed 6-19 interviews. Responses to survey questions were recorded in REDCap, a secure, web-based data capture instrument.⁸

Participating in the study was considered implied consent, and participants did not receive a monetary incentive, although respondents were offered deidentified survey data for participation. The study was exempted through the University of Chicago Institutional Review Board.

Data Analysis

Employers were dichotomized as community hospital employer (including primary community hospital employment/private organization) or noncommunity hospital employer (including children’s/university hospital employment or school of medicine). Descriptive statistics were reported to compare the demographics of two employer groups. P values were calculated using two-sample t-tests for the continuous variables and chi-square or Fisher-exact tests for the categorical variables. Mann–Whitney U-test was performed for continuous variables without normality. Analyses were performed using the R Statistical Programming Language (R Foundation for Statistical Computing, Vienna, Austria), version 3.4.3.

Participation and Program Characteristics

We interviewed 70 community-based PHM site directors representing programs across 29 states (Table 1) and five geographic regions: Midwest (34.3%), Northeast (11.4%), Southeast (15.7%), Southwest (4.3%), and West (34.3%). Employer models varied across groups, with more noncommunity hospital employers (57%) than community hospital employers (43%). The top three services covered by pediatric hospitalists were pediatric inpatient or observation bed admissions (97%), emergency department consults (89%), and general newborns (67%). PHM programs also provided coverage for other services, including newborn deliveries (43%), Special Care Nursery/Level II Neonatal Intensive Care Unit (41%), step-down unit (20%), and mental health units (13%). About 59% of programs provided education for family medicine residents, 36% were for pediatric residents, and 70% worked with advanced practice providers. The majority of programs (70%) provided in-house coverage overnight.

Clinical Work Expectations and Employer Model

Clinical work expectations varied broadly across programs (Table 2). The median expected hours for a 1.0 FTE was 1,882 hours per year (interquartile range [IQR] 1,805, 2,016), and the median expected weekend coverage/year (defined as covering two days or two nights of the weekend) was 21 (IQR 14, 24). Most programs did not expand staff coverage based on seasonality (73%), and less than 20% of programs operated with a census cap. Median support for nondirect patient care activities was 4% (IQR 0,10) of a program’s total FTE (ie, a 5.0 FTE program would have 0.20 FTE support). Programs with community hospital employers had an 8% higher expectation of 1.0 FTE hours/year (P = .01) and viewed an appropriate pediatric morning census as 20% higher (P = .01; Table 2).

Program Sustainability

To our knowledge, this study is the first to describe clinical work models exclusively for pediatric community hospitalist programs. We found that expectations for clinical FTE hours, weekend coverage, appropriate morning census, support for nondirect patient care activities, and perception of sustainability varied broadly across programs. The only variable affecting some of these differences was employer model, with those employed by a community hospital employer having a higher expectation for hours/year and appropriate morning pediatric census than those employed by noncommunity hospital employers.

With a growing emphasis on physician burnout and career satisfaction,^9-11 understanding the characteristics of community hospital work settings is critical for identifying and building sustainable employment models. Previous studies have identified that the balance of clinical and nonclinical responsibilities and the setting of community versus university-based programs are major contributors to burnout and career satisfaction.^9,11 Interestingly, although community hospital-based programs have limited FTE for nondirect patient care activities, we found that a higher percentage of program site directors perceived their program models as sustainable when compared with university-based programs in prior research (63% versus 50%).⁶ Elucidating why community hospital PHM programs are perceived as more sustainable provides an opportunity for future research. Potential reasons may include fewer academic requirements for promotion or an increased connection to a local community.

We also found that the employer model had a statistically significant impact on expected FTE hours per year but not on perception of sustainability. Programs employed by community hospitals worked 8% more hours per year than those employed by noncommunity hospital employers and accepted a higher morning pediatric census. This variation in hours and census level appropriateness is likely multifactorial, potentially from higher nonclinical expectations for promotion (eg, academic or scholarly production) at school of medicine or children’s hospital employed programs versus limited reimbursement for administrative responsibilities within community hospital employment models.

There are several potential next steps for our findings. As our data are the first attempt (to our knowledge) at describing the current practice and expectations exclusively within community hospital programs, this study can be used as a starting point for the development of workload expectation standards. Increasing transparency nationally for individual community programs potentially promotes discussions around burnout and attrition. Having objective data to compare program models may assist in advocating with local hospital leadership for restructuring that better aligns with national norms.

Our study has several limitations. First, our sampling frame was based upon a self-selection of program directors. This may have led to a biased representation of programs with higher workloads motivated to develop a standard to compare with other programs, which may have potentially led to an overestimation of hours. Second, without a registry or database for community-based pediatric hospitalist programs, we do not know the percentage of community-based programs that our sample represents. Although our results cannot speak for all community PHM programs, we attempted to mitigate nonresponse bias through the breadth of programs represented, which spanned 29 states, five geographic regions, and teaching and nonteaching programs. The interview-based method for data collection allowed the research team to clarify questions and responses across sites, thereby improving the quality and consistency of the data for the represented study sample. Finally, other factors possibly contributed to sustainability that we did not address in this study, such as programs that are dependent on billable encounters as part of their salary support.

As a newly recognized subspecialty, creating a reference for community-based program leaders to determine and discuss individual models and expectations with hospital administrators may help address programmatic sustainability. It may also allow for the analysis of long-term career satisfaction and longevity within community PHM programs based on workload. Future studies should further explore root causes for workload discrepancies between community and university employed programs along with establishing potential standards for PHM program development.

Acknowledgments

We would like to thank the Stanford School of Medicine Quantitative Sciences Unit staff for their assistance in statistical analysis.

Disclosure

The authors have nothing to disclose.

As a newly recognized specialty, pediatric hospital medicine (PHM) continues to expand and diversify.¹ Pediatric hospitalists care for children in hospitals ranging from small, rural community hospitals to large, free-standing quaternary children’s hospitals.^2-4 In addition, more than 10% of graduating pediatric residents are seeking future careers within PHM.⁵

In 2018, Fromme et al. published a study describing clinical workload for pediatric hospitalists within university-based settings.⁶ They characterized the diversity of work models and programmatic sustainability but limited the study to university-based programs. With over half of children receiving care within community hospitals,⁷ workforce patterns for community-based pediatric hospitalists should be characterized to maximize sustainability and minimize attrition across the field.

In this study, we describe programmatic variability in clinical work expectations of 70 community-based PHM programs. We aimed to describe existing work models and expectations of community-based program leaders as they relate to their unique clinical setting.

We conducted a cross-sectional survey of community-based PHM site directors through structured interviews. Community hospital programs were self-defined by the study participants, although typically defined as general hospitals that admit pediatric patients and are not free-standing or children’s hospitals within a general hospital. Survey respondents were asked to answer questions only reflecting expectations at their community hospital.

Survey Design and Content

Building from a tool used by Fromme et al.⁶ we created a 12-question structured interview questionnaire focused on three areas: (1) full-time employment (FTE) metrics including definitions of a 1.0 FTE, “typical” shifts, and weekend responsibilities; (2) work volume including census parameters, service-line coverage expectations, back-up systems, and overnight call responsibilities; and (3) programmatic model including sense of sustainability (eg, minimizing burnout and attrition), support for activities such as administrative or research time, and employer model (Appendix).

We modified the survey through research team consensus. After pilot-testing by research team members at their own sites, the survey was refined for item clarity, structural design, and length. We chose to administer surveys through phone interviews over a traditional distribution due to anticipated variability in work models. The research team discussed how each question should be asked, and responses were clarified to maintain consistency.

Survey Administration

Given the absence of a national registry or database for community-based PHM programs, study participation was solicited through an invitation posted on the American Academy of Pediatrics Section on Hospital Medicine (AAP SOHM) Listserv and the AAP SOHM Community Hospitalist Listserv in May 2018. Invitations were posted twice at two weeks apart. Each research team member completed 6-19 interviews. Responses to survey questions were recorded in REDCap, a secure, web-based data capture instrument.⁸

Participating in the study was considered implied consent, and participants did not receive a monetary incentive, although respondents were offered deidentified survey data for participation. The study was exempted through the University of Chicago Institutional Review Board.

Data Analysis

Employers were dichotomized as community hospital employer (including primary community hospital employment/private organization) or noncommunity hospital employer (including children’s/university hospital employment or school of medicine). Descriptive statistics were reported to compare the demographics of two employer groups. P values were calculated using two-sample t-tests for the continuous variables and chi-square or Fisher-exact tests for the categorical variables. Mann–Whitney U-test was performed for continuous variables without normality. Analyses were performed using the R Statistical Programming Language (R Foundation for Statistical Computing, Vienna, Austria), version 3.4.3.

Participation and Program Characteristics

We interviewed 70 community-based PHM site directors representing programs across 29 states (Table 1) and five geographic regions: Midwest (34.3%), Northeast (11.4%), Southeast (15.7%), Southwest (4.3%), and West (34.3%). Employer models varied across groups, with more noncommunity hospital employers (57%) than community hospital employers (43%). The top three services covered by pediatric hospitalists were pediatric inpatient or observation bed admissions (97%), emergency department consults (89%), and general newborns (67%). PHM programs also provided coverage for other services, including newborn deliveries (43%), Special Care Nursery/Level II Neonatal Intensive Care Unit (41%), step-down unit (20%), and mental health units (13%). About 59% of programs provided education for family medicine residents, 36% were for pediatric residents, and 70% worked with advanced practice providers. The majority of programs (70%) provided in-house coverage overnight.

Clinical Work Expectations and Employer Model

Clinical work expectations varied broadly across programs (Table 2). The median expected hours for a 1.0 FTE was 1,882 hours per year (interquartile range [IQR] 1,805, 2,016), and the median expected weekend coverage/year (defined as covering two days or two nights of the weekend) was 21 (IQR 14, 24). Most programs did not expand staff coverage based on seasonality (73%), and less than 20% of programs operated with a census cap. Median support for nondirect patient care activities was 4% (IQR 0,10) of a program’s total FTE (ie, a 5.0 FTE program would have 0.20 FTE support). Programs with community hospital employers had an 8% higher expectation of 1.0 FTE hours/year (P = .01) and viewed an appropriate pediatric morning census as 20% higher (P = .01; Table 2).

Program Sustainability

To our knowledge, this study is the first to describe clinical work models exclusively for pediatric community hospitalist programs. We found that expectations for clinical FTE hours, weekend coverage, appropriate morning census, support for nondirect patient care activities, and perception of sustainability varied broadly across programs. The only variable affecting some of these differences was employer model, with those employed by a community hospital employer having a higher expectation for hours/year and appropriate morning pediatric census than those employed by noncommunity hospital employers.

With a growing emphasis on physician burnout and career satisfaction,^9-11 understanding the characteristics of community hospital work settings is critical for identifying and building sustainable employment models. Previous studies have identified that the balance of clinical and nonclinical responsibilities and the setting of community versus university-based programs are major contributors to burnout and career satisfaction.^9,11 Interestingly, although community hospital-based programs have limited FTE for nondirect patient care activities, we found that a higher percentage of program site directors perceived their program models as sustainable when compared with university-based programs in prior research (63% versus 50%).⁶ Elucidating why community hospital PHM programs are perceived as more sustainable provides an opportunity for future research. Potential reasons may include fewer academic requirements for promotion or an increased connection to a local community.

We also found that the employer model had a statistically significant impact on expected FTE hours per year but not on perception of sustainability. Programs employed by community hospitals worked 8% more hours per year than those employed by noncommunity hospital employers and accepted a higher morning pediatric census. This variation in hours and census level appropriateness is likely multifactorial, potentially from higher nonclinical expectations for promotion (eg, academic or scholarly production) at school of medicine or children’s hospital employed programs versus limited reimbursement for administrative responsibilities within community hospital employment models.

There are several potential next steps for our findings. As our data are the first attempt (to our knowledge) at describing the current practice and expectations exclusively within community hospital programs, this study can be used as a starting point for the development of workload expectation standards. Increasing transparency nationally for individual community programs potentially promotes discussions around burnout and attrition. Having objective data to compare program models may assist in advocating with local hospital leadership for restructuring that better aligns with national norms.

Our study has several limitations. First, our sampling frame was based upon a self-selection of program directors. This may have led to a biased representation of programs with higher workloads motivated to develop a standard to compare with other programs, which may have potentially led to an overestimation of hours. Second, without a registry or database for community-based pediatric hospitalist programs, we do not know the percentage of community-based programs that our sample represents. Although our results cannot speak for all community PHM programs, we attempted to mitigate nonresponse bias through the breadth of programs represented, which spanned 29 states, five geographic regions, and teaching and nonteaching programs. The interview-based method for data collection allowed the research team to clarify questions and responses across sites, thereby improving the quality and consistency of the data for the represented study sample. Finally, other factors possibly contributed to sustainability that we did not address in this study, such as programs that are dependent on billable encounters as part of their salary support.

As a newly recognized subspecialty, creating a reference for community-based program leaders to determine and discuss individual models and expectations with hospital administrators may help address programmatic sustainability. It may also allow for the analysis of long-term career satisfaction and longevity within community PHM programs based on workload. Future studies should further explore root causes for workload discrepancies between community and university employed programs along with establishing potential standards for PHM program development.

Acknowledgments

We would like to thank the Stanford School of Medicine Quantitative Sciences Unit staff for their assistance in statistical analysis.

Disclosure

The authors have nothing to disclose.

One of the most promising methods for improving medical decision-making is learning from the outcomes of one’s decisions and either maintaining or modifying future decision-making based on those outcomes.^1-3 This process of iterative improvement over time based on feedback is called calibration and is one of the most important drivers of lifelong learning and improvement.¹

Despite the importance of knowing the outcomes of one’s decisions, this seldom occurs in modern medical education.⁴ Learners do not often obtain specific feedback about the decisions they make within a short enough time frame to intentionally reflect upon and modify that decision-making process.^3,5 In addition, almost every patient admitted to a teaching hospital will be cared for by multiple physicians over the course of a hospitalization. These care transitions may be seen as barriers to high-quality care and education, but we suggest a different paradigm: transitions of care present opportunities for trainees to be teammates in each other’s calibration. Peers can provide specific feedback about the diagnostic process and inform one another about patient outcomes. Transitions of care allow for built-in “second opinions,” and trainees can intentionally learn by comparing the clinical reasoning involved at different points in a patient’s course. The diagnostic process is dynamic and complex; it is fundamental that trainees have the opportunity to reflect on the process to identify how and why the diagnostic process evolved throughout a patient’s hospitalization. Most inpatient diagnoses are “working diagnoses” that are likely to change. Thus, identifying the twists and turns in a patient’s diagnostic journey provides invaluable learning for future practice.

Herein, we describe the implementation and impact of a multisite initiative to engage residents in delivering feedback to their peers about medical decisions around transitions of care.

The LOOP Project is a prospective clinical educational study that aimed to engage resident physicians to deliver feedback and updates about their colleagues’ diagnostic decision-making around care transitions. This study was deemed exempt from review by the University of Minnesota Institutional Review Board and either approved or deemed exempt by the corresponding Institutional Review Boards at all participating institutions. The study was conducted by seven programs at six institutions and included Internal Medicine, Pediatrics, and Internal Medicine–Pediatrics (PGY 1-4) residents from February 2017 to June 2017. Residents rotating through participating clinical services during the study period were invited to participate and given further information by site leads via informational presentations, written handouts, and/or emails.

The intervention entailed residents delivering structured feedback to their colleagues regarding their patients’ diagnoses after transitions of care. The predominant setting was the inpatient hospital medicine day-shift team providing feedback to the night-shift team regarding overnight admissions. Feedback about patients (usually chosen by the day-shift team) was delivered through completion of a standard templated form (Figure) usually sent within 24 hours after hospital admission through secure messaging (ie, EPIC In-Basket message utilizing a Smartphrase of the LOOP feedback form). A 24-hour time period was chosen to allow for rapid cycling of feedback focusing on initial diagnostic assessment. Site leads and resident champions promoted the project through presentations, informal discussions, and prizes for high completion rates of forms and surveys (ie, coffee cards and pizza).

Overall, there were 716 current residents in the training programs that participated in this study; one site planned on participating but did not complete any forms. A total of 405 residents were eligible to participate during the study period. Overall, 221 (54.5%) presurveys and 90 postsurveys were completed (22.2%); 54 residents (13.3%) completed both pre- and postsurveys and were included in the analysis. Of the 54 survey respondents, 26 (48.15%) were female.

Survey results (Table) indicated significantly improved self-efficacy in identifying cognitive errors in residents’ own practice, identifying why those errors occurred, and identifying strategies to decrease future diagnostic errors. Participants noted increased frequency of discussions within teams regarding differential diagnoses, diagnostic errors, and why diagnoses changed over time. The feedback process was viewed positively by participants, who were also generally satisfied with the overall quality, frequency, and value of the feedback received. After the intervention, participants reported an increase in the amount of feedback received for night admissions and an overall increase in the perception that nighttime admissions were as “educational” as daytime admissions.

This study suggests that an intervention to operationalize standardized, structured feedback about diagnostic decision-making around transitions of care is a promising approach to improve residents’ understanding of changes in, and evolution of, the diagnostic process, as well as improve the perceived educational value of overnight admissions. In our results, over 40% of the patients admitted by residents had some change in their diagnoses after a transition of care during their early hospitalization. This finding highlights the importance of ensuring that trainees have the opportunity to know the outcomes of their decisions. Indeed, residents should be encouraged to follow-up on their own patients without prompting; however, studies show that this practice is uncommon and interventions beyond admonition are necessary.⁴

The diagnostic change rate observed in this study confirms that diagnosis is an iterative process and that the concept of a working diagnosis is key—a diagnosis made at admission will very likely be modified by time, the natural history of the disease, and new clinical information. When diagnoses are viewed as working diagnoses, trainees may be empowered to better understand the diagnostic process. As learners and teachers adopt this perspective, training programs are more likely to be successful in helping learners calibrate toward expertise.

Previous studies have questioned whether resident physicians view overnight admissions as valuable.⁶ After our intervention, we found an increase in both the amount of feedback received and the proportion of participants who agreed that night and day admissions were equally educational, suggesting that targeted diagnostic reasoning feedback can bolster educational value of nighttime admissions.

This study presents a number of limitations. First, the survey response rate was low, which could potentially lead to biased results. We excluded those respondents who did not respond to both the pre- and postsurveys from the analysis. Second, we did not measure actual change in diagnostic performance. While learners did report learning and saw feedback as valuable, self-identified learning points may not always translate to improved patient care. Additionally, residents chose the patients for whom feedback was provided, and the diagnostic change rate described may be overestimated. We did not track the total number of admissions for which feedback could have been delivered during the study. We did not include a control group, and the intervention may not be responsible for changing learners’ perceptions. However, the included programs were not implementing other new protocols focused on diagnostic reasoning during the study period. In addition, we addressed diagnostic changes early in a hospital course; a comprehensive program should address more feedback loops (eg, discharging team to admitting team).

This work is a pilot study; for future interventions focused on improving calibration to be sustainable, they should be congruent with existing clinical workflows and avoid adding to the stress and/or cognitive load of an already-busy clinical experience. The most optimal strategies for delivering feedback about clinical reasoning remain unclear.

In summary, a program to deliver structured feedback among resident physicians about diagnostic reasoning across care transitions for selected hospitalized patients is viewed positively by trainees, is feasible, and leads to changes in resident perception and self-efficacy. Future studies and interventions should aim to provide feedback more systematically, rather than just for selected patients, and objectively track diagnostic changes over time in hospitalized patients. While truly objective diagnostic information is challenging to obtain, comparing admission and other inpatient diagnoses to discharge diagnoses or diagnoses from primary care follow-up visits may be helpful. In addition, studies should aim to track trainees’ clinical decision-making over time and determine the effectiveness of feedback at improving diagnostic performance through calibration.

Acknowledgments

The authors thank the trainees who participated in this study, as well as the residency leadership at participating institutions. The authors also thank Qi Wang, PhD, for providing statistical analysis.

Disclosures

The authors have nothing to disclose.

Funding

The study was funded by an AAIM Innovation Grant and local support at each participating institution.

One of the most promising methods for improving medical decision-making is learning from the outcomes of one’s decisions and either maintaining or modifying future decision-making based on those outcomes.^1-3 This process of iterative improvement over time based on feedback is called calibration and is one of the most important drivers of lifelong learning and improvement.¹

Despite the importance of knowing the outcomes of one’s decisions, this seldom occurs in modern medical education.⁴ Learners do not often obtain specific feedback about the decisions they make within a short enough time frame to intentionally reflect upon and modify that decision-making process.^3,5 In addition, almost every patient admitted to a teaching hospital will be cared for by multiple physicians over the course of a hospitalization. These care transitions may be seen as barriers to high-quality care and education, but we suggest a different paradigm: transitions of care present opportunities for trainees to be teammates in each other’s calibration. Peers can provide specific feedback about the diagnostic process and inform one another about patient outcomes. Transitions of care allow for built-in “second opinions,” and trainees can intentionally learn by comparing the clinical reasoning involved at different points in a patient’s course. The diagnostic process is dynamic and complex; it is fundamental that trainees have the opportunity to reflect on the process to identify how and why the diagnostic process evolved throughout a patient’s hospitalization. Most inpatient diagnoses are “working diagnoses” that are likely to change. Thus, identifying the twists and turns in a patient’s diagnostic journey provides invaluable learning for future practice.

Herein, we describe the implementation and impact of a multisite initiative to engage residents in delivering feedback to their peers about medical decisions around transitions of care.

The LOOP Project is a prospective clinical educational study that aimed to engage resident physicians to deliver feedback and updates about their colleagues’ diagnostic decision-making around care transitions. This study was deemed exempt from review by the University of Minnesota Institutional Review Board and either approved or deemed exempt by the corresponding Institutional Review Boards at all participating institutions. The study was conducted by seven programs at six institutions and included Internal Medicine, Pediatrics, and Internal Medicine–Pediatrics (PGY 1-4) residents from February 2017 to June 2017. Residents rotating through participating clinical services during the study period were invited to participate and given further information by site leads via informational presentations, written handouts, and/or emails.

The intervention entailed residents delivering structured feedback to their colleagues regarding their patients’ diagnoses after transitions of care. The predominant setting was the inpatient hospital medicine day-shift team providing feedback to the night-shift team regarding overnight admissions. Feedback about patients (usually chosen by the day-shift team) was delivered through completion of a standard templated form (Figure) usually sent within 24 hours after hospital admission through secure messaging (ie, EPIC In-Basket message utilizing a Smartphrase of the LOOP feedback form). A 24-hour time period was chosen to allow for rapid cycling of feedback focusing on initial diagnostic assessment. Site leads and resident champions promoted the project through presentations, informal discussions, and prizes for high completion rates of forms and surveys (ie, coffee cards and pizza).

Overall, there were 716 current residents in the training programs that participated in this study; one site planned on participating but did not complete any forms. A total of 405 residents were eligible to participate during the study period. Overall, 221 (54.5%) presurveys and 90 postsurveys were completed (22.2%); 54 residents (13.3%) completed both pre- and postsurveys and were included in the analysis. Of the 54 survey respondents, 26 (48.15%) were female.

Survey results (Table) indicated significantly improved self-efficacy in identifying cognitive errors in residents’ own practice, identifying why those errors occurred, and identifying strategies to decrease future diagnostic errors. Participants noted increased frequency of discussions within teams regarding differential diagnoses, diagnostic errors, and why diagnoses changed over time. The feedback process was viewed positively by participants, who were also generally satisfied with the overall quality, frequency, and value of the feedback received. After the intervention, participants reported an increase in the amount of feedback received for night admissions and an overall increase in the perception that nighttime admissions were as “educational” as daytime admissions.

This study suggests that an intervention to operationalize standardized, structured feedback about diagnostic decision-making around transitions of care is a promising approach to improve residents’ understanding of changes in, and evolution of, the diagnostic process, as well as improve the perceived educational value of overnight admissions. In our results, over 40% of the patients admitted by residents had some change in their diagnoses after a transition of care during their early hospitalization. This finding highlights the importance of ensuring that trainees have the opportunity to know the outcomes of their decisions. Indeed, residents should be encouraged to follow-up on their own patients without prompting; however, studies show that this practice is uncommon and interventions beyond admonition are necessary.⁴

The diagnostic change rate observed in this study confirms that diagnosis is an iterative process and that the concept of a working diagnosis is key—a diagnosis made at admission will very likely be modified by time, the natural history of the disease, and new clinical information. When diagnoses are viewed as working diagnoses, trainees may be empowered to better understand the diagnostic process. As learners and teachers adopt this perspective, training programs are more likely to be successful in helping learners calibrate toward expertise.

Previous studies have questioned whether resident physicians view overnight admissions as valuable.⁶ After our intervention, we found an increase in both the amount of feedback received and the proportion of participants who agreed that night and day admissions were equally educational, suggesting that targeted diagnostic reasoning feedback can bolster educational value of nighttime admissions.

This study presents a number of limitations. First, the survey response rate was low, which could potentially lead to biased results. We excluded those respondents who did not respond to both the pre- and postsurveys from the analysis. Second, we did not measure actual change in diagnostic performance. While learners did report learning and saw feedback as valuable, self-identified learning points may not always translate to improved patient care. Additionally, residents chose the patients for whom feedback was provided, and the diagnostic change rate described may be overestimated. We did not track the total number of admissions for which feedback could have been delivered during the study. We did not include a control group, and the intervention may not be responsible for changing learners’ perceptions. However, the included programs were not implementing other new protocols focused on diagnostic reasoning during the study period. In addition, we addressed diagnostic changes early in a hospital course; a comprehensive program should address more feedback loops (eg, discharging team to admitting team).

This work is a pilot study; for future interventions focused on improving calibration to be sustainable, they should be congruent with existing clinical workflows and avoid adding to the stress and/or cognitive load of an already-busy clinical experience. The most optimal strategies for delivering feedback about clinical reasoning remain unclear.

In summary, a program to deliver structured feedback among resident physicians about diagnostic reasoning across care transitions for selected hospitalized patients is viewed positively by trainees, is feasible, and leads to changes in resident perception and self-efficacy. Future studies and interventions should aim to provide feedback more systematically, rather than just for selected patients, and objectively track diagnostic changes over time in hospitalized patients. While truly objective diagnostic information is challenging to obtain, comparing admission and other inpatient diagnoses to discharge diagnoses or diagnoses from primary care follow-up visits may be helpful. In addition, studies should aim to track trainees’ clinical decision-making over time and determine the effectiveness of feedback at improving diagnostic performance through calibration.

Acknowledgments

The authors thank the trainees who participated in this study, as well as the residency leadership at participating institutions. The authors also thank Qi Wang, PhD, for providing statistical analysis.

Disclosures

The authors have nothing to disclose.

Funding

The study was funded by an AAIM Innovation Grant and local support at each participating institution.

One of the most promising methods for improving medical decision-making is learning from the outcomes of one’s decisions and either maintaining or modifying future decision-making based on those outcomes.^1-3 This process of iterative improvement over time based on feedback is called calibration and is one of the most important drivers of lifelong learning and improvement.¹

Despite the importance of knowing the outcomes of one’s decisions, this seldom occurs in modern medical education.⁴ Learners do not often obtain specific feedback about the decisions they make within a short enough time frame to intentionally reflect upon and modify that decision-making process.^3,5 In addition, almost every patient admitted to a teaching hospital will be cared for by multiple physicians over the course of a hospitalization. These care transitions may be seen as barriers to high-quality care and education, but we suggest a different paradigm: transitions of care present opportunities for trainees to be teammates in each other’s calibration. Peers can provide specific feedback about the diagnostic process and inform one another about patient outcomes. Transitions of care allow for built-in “second opinions,” and trainees can intentionally learn by comparing the clinical reasoning involved at different points in a patient’s course. The diagnostic process is dynamic and complex; it is fundamental that trainees have the opportunity to reflect on the process to identify how and why the diagnostic process evolved throughout a patient’s hospitalization. Most inpatient diagnoses are “working diagnoses” that are likely to change. Thus, identifying the twists and turns in a patient’s diagnostic journey provides invaluable learning for future practice.

Herein, we describe the implementation and impact of a multisite initiative to engage residents in delivering feedback to their peers about medical decisions around transitions of care.

The LOOP Project is a prospective clinical educational study that aimed to engage resident physicians to deliver feedback and updates about their colleagues’ diagnostic decision-making around care transitions. This study was deemed exempt from review by the University of Minnesota Institutional Review Board and either approved or deemed exempt by the corresponding Institutional Review Boards at all participating institutions. The study was conducted by seven programs at six institutions and included Internal Medicine, Pediatrics, and Internal Medicine–Pediatrics (PGY 1-4) residents from February 2017 to June 2017. Residents rotating through participating clinical services during the study period were invited to participate and given further information by site leads via informational presentations, written handouts, and/or emails.

The intervention entailed residents delivering structured feedback to their colleagues regarding their patients’ diagnoses after transitions of care. The predominant setting was the inpatient hospital medicine day-shift team providing feedback to the night-shift team regarding overnight admissions. Feedback about patients (usually chosen by the day-shift team) was delivered through completion of a standard templated form (Figure) usually sent within 24 hours after hospital admission through secure messaging (ie, EPIC In-Basket message utilizing a Smartphrase of the LOOP feedback form). A 24-hour time period was chosen to allow for rapid cycling of feedback focusing on initial diagnostic assessment. Site leads and resident champions promoted the project through presentations, informal discussions, and prizes for high completion rates of forms and surveys (ie, coffee cards and pizza).

Overall, there were 716 current residents in the training programs that participated in this study; one site planned on participating but did not complete any forms. A total of 405 residents were eligible to participate during the study period. Overall, 221 (54.5%) presurveys and 90 postsurveys were completed (22.2%); 54 residents (13.3%) completed both pre- and postsurveys and were included in the analysis. Of the 54 survey respondents, 26 (48.15%) were female.

Survey results (Table) indicated significantly improved self-efficacy in identifying cognitive errors in residents’ own practice, identifying why those errors occurred, and identifying strategies to decrease future diagnostic errors. Participants noted increased frequency of discussions within teams regarding differential diagnoses, diagnostic errors, and why diagnoses changed over time. The feedback process was viewed positively by participants, who were also generally satisfied with the overall quality, frequency, and value of the feedback received. After the intervention, participants reported an increase in the amount of feedback received for night admissions and an overall increase in the perception that nighttime admissions were as “educational” as daytime admissions.

This study suggests that an intervention to operationalize standardized, structured feedback about diagnostic decision-making around transitions of care is a promising approach to improve residents’ understanding of changes in, and evolution of, the diagnostic process, as well as improve the perceived educational value of overnight admissions. In our results, over 40% of the patients admitted by residents had some change in their diagnoses after a transition of care during their early hospitalization. This finding highlights the importance of ensuring that trainees have the opportunity to know the outcomes of their decisions. Indeed, residents should be encouraged to follow-up on their own patients without prompting; however, studies show that this practice is uncommon and interventions beyond admonition are necessary.⁴

The diagnostic change rate observed in this study confirms that diagnosis is an iterative process and that the concept of a working diagnosis is key—a diagnosis made at admission will very likely be modified by time, the natural history of the disease, and new clinical information. When diagnoses are viewed as working diagnoses, trainees may be empowered to better understand the diagnostic process. As learners and teachers adopt this perspective, training programs are more likely to be successful in helping learners calibrate toward expertise.

Previous studies have questioned whether resident physicians view overnight admissions as valuable.⁶ After our intervention, we found an increase in both the amount of feedback received and the proportion of participants who agreed that night and day admissions were equally educational, suggesting that targeted diagnostic reasoning feedback can bolster educational value of nighttime admissions.

This study presents a number of limitations. First, the survey response rate was low, which could potentially lead to biased results. We excluded those respondents who did not respond to both the pre- and postsurveys from the analysis. Second, we did not measure actual change in diagnostic performance. While learners did report learning and saw feedback as valuable, self-identified learning points may not always translate to improved patient care. Additionally, residents chose the patients for whom feedback was provided, and the diagnostic change rate described may be overestimated. We did not track the total number of admissions for which feedback could have been delivered during the study. We did not include a control group, and the intervention may not be responsible for changing learners’ perceptions. However, the included programs were not implementing other new protocols focused on diagnostic reasoning during the study period. In addition, we addressed diagnostic changes early in a hospital course; a comprehensive program should address more feedback loops (eg, discharging team to admitting team).

This work is a pilot study; for future interventions focused on improving calibration to be sustainable, they should be congruent with existing clinical workflows and avoid adding to the stress and/or cognitive load of an already-busy clinical experience. The most optimal strategies for delivering feedback about clinical reasoning remain unclear.

In summary, a program to deliver structured feedback among resident physicians about diagnostic reasoning across care transitions for selected hospitalized patients is viewed positively by trainees, is feasible, and leads to changes in resident perception and self-efficacy. Future studies and interventions should aim to provide feedback more systematically, rather than just for selected patients, and objectively track diagnostic changes over time in hospitalized patients. While truly objective diagnostic information is challenging to obtain, comparing admission and other inpatient diagnoses to discharge diagnoses or diagnoses from primary care follow-up visits may be helpful. In addition, studies should aim to track trainees’ clinical decision-making over time and determine the effectiveness of feedback at improving diagnostic performance through calibration.

Acknowledgments

The authors thank the trainees who participated in this study, as well as the residency leadership at participating institutions. The authors also thank Qi Wang, PhD, for providing statistical analysis.

Disclosures

The authors have nothing to disclose.

Funding

The study was funded by an AAIM Innovation Grant and local support at each participating institution.