Corrie E McDaniel, DO

Regionalization of pediatric acute care is increasing across the United States, with rates of interfacility transfer for general medical conditions in children similar to those of high-risk conditions in adults.¹ The inability for children to receive definitive care (ie, care provided to conclusively manage a patient’s condition without requiring an interfacility transfer) within their local community has implications on public health as well as family function and financial burden.^1,2 Previous studies demonstrated that 30% to 80% of interfacility transfers are potentially unnecessary,^3-6 as indicated by a high proportion of short lengths of stay after transfer. While rapidity of discharge is an important factor in identifying potentially unnecessary transfers, many of these studies included diagnoses requiring specialized imaging or surgical interventions, which may not be available in referring institutions.

To highlight conditions that referring hospitals may prioritize for pediatric capacity building, we aimed to identify the most common medical diagnoses among pediatric transfer patients that did not require advanced evaluation or intervention and that had high rates of discharge within 1 day of interfacility transfer.

METHODS

We conducted a retrospective, cross-sectional, descriptive study using the Pediatric Health Information System (PHIS) database, which contains administrative data from 48 geographically diverse US children’s hospitals.

We included children <18 years old who were transferred to a participating PHIS hospital in 2019, including emergency department (ED), observation, and inpatient encounters. We identified patients through the source-of-admission code labeled as “transfer.” Diagnoses were identified through the International Classification of Diseases, Tenth Revision (ICD-10) codes using the Pediatric Clinical Classification System.⁷We excluded the following categories: mental or behavioral health diagnoses, maternal or labor diagnoses, primary newborn birth diagnoses, and transfers directly to an intensive care unit (ICU).

For each diagnosis, we determined the number of transfers and frequency of rapid discharge, defined as either discharge from the ED without admission or admission and discharge within 1 day from a general inpatient unit. As discharge times are not reliably available in PHIS, all patients discharged on the day of transfer or the following calendar day were identified as rapid discharge. Medical complexity was determined through applying the Pediatric Medical Complexity Algorithm (PMCA).⁸

To identify diagnoses seen with sufficient frequency to represent potentially useful areas for referring hospitals to target, we limited our analysis to diagnoses that had a minimum of 576 transfers per year, equivalent to at least 1 transfer for that diagnosis per month per PHIS hospital. We then categorized the frequency of interventions after transfer, including (1) no interventions received; (2) basic interventions only, defined as receiving any intravenous fluids, antimicrobials, antipyretics or analgesics, and/or basic imaging (ie, radiography and computed tomography [CT]); or (3) advanced interventions, including transfer to an ICU after initial presentation/management in the ED or inpatient ward, advanced imaging (eg, ultrasound, magnetic resonance [MR] imaging, MR angiography or venography, CT angiography), or any surgical intervention. A full categorization of basic and advanced interventions is available in Appendix Table 1.

For descriptive statistics, we calculated means for normally distributed variables, medians for continuous variables with nonnormal distributions, and percentages for binary variables. Comparisons were made using t-tests and chi-square tests.

This study was approved by the Seattle Children’s Institutional Review Board.

RESULTS

We identified 286,905 transfers into participating PHIS hospitals in 2019. Of these, 89,519 (31.2%) were excluded (Appendix Table 2), leaving 197,386 (68.6%) transfers. Patients discharged within 1 day were more likely to have public or unknown insurance (65.1% vs 61.5%, P < 0.01), to have no co-occurring chronic conditions (60.2% vs 28.5%, P < 0.01), and to reside within the Northeast (35.0% vs 11.0%, P < 0.01) (Appendix Table 3).

The most common medical diagnoses among these transfers included acute bronchiolitis (4.3% of all interfacility transfers, n = 8,425), chemotherapy (4.0%, n = 7,819), and asthma (3.3%, n = 6,430) (Appendix Table 4); 45.9% of bronchiolitis, 15.0% of chemotherapy, and 67.4% of asthma transfers were rapidly discharged.

The Table shows the medical conditions among transfers that most frequently experienced rapid discharge (primary surgical diagnoses are presented in Appendix Table 5).

Within this cohort, patients transferred for cough were most likely to be rapidly discharged, with 98.5% (n = 611) discharged within 1 day of transfer. Among these, 66.5% (n = 412) received no interventions and 33.4% (n = 207) received only basic interventions. Only 1.3% (n = 8) required any advanced intervention. Similarly, 96.0% (n = 603) of patients with the diagnosis of chest pain were rapidly discharged, with 45.1% (n = 272) requiring no interventions, 48.3% (n = 291) receiving basic interventions, and 17.7% (n = 107) requiring advanced intervention. Patients with the diagnosis of febrile seizures, croup, and allergic reactions were rapidly discharged 91.8% (n = 584), 87.3% (n = 1,893) and 87.2% (n = 1,350) of the time, respectively, and more than 70% patients with these diagnoses underwent no intervention after transfer. In addition, while 92.0% (n = 3,392) of patients with abdominal pain diagnoses were discharged rapidly, 55.5% (n = 1,883) received advanced imaging (Appendix Table 6). Similarly, while 92.0% (n = 2,229) of patients with open wounds to the head, neck, and trunk were discharged rapidly, 17.3% (n = 419) of patients with these diagnoses required a surgical intervention after transfer (Appendix Table 6).

DISCUSSION

We have identified medical conditions that not only had high rates of rapid discharge after transfer, but also received minimal intervention from the accepting institution. Although bronchiolitis and chemotherapy were the most common conditions for which patients were transferred, the range of severity varied widely, with more than 50% of bronchiolitis and 85% of chemotherapy transfers requiring hospitalization for longer than 1 day. Diagnoses such as chemotherapy, although common among transferred patients, likely represent conditions that may not be appropriate to care for in pediatric-limited settings, as they require subspecialized pediatric care. General conditions, however, such as cough, chest pain, allergic reactions, and febrile seizures may represent diagnoses for which it would be appropriate for general hospitals to develop infrastructure to provide definitive pediatric care given how infrequently specialized pediatric resources are needed in caring for these conditions.

Identifying conditions as potential targets to reduce the number of interfacility transfers requires balancing a hospital’s capacity (or lack thereof) for pediatric admissions, perceived risk of decompensation, referring provider discomfort, and parental preference.^9-11 Although several studies have identified conditions associated with frequent transfer and rapid discharge,^3-5 prior studies’ conclusions that 40% or more of interhospital transfers may be avoidable are potential over-estimates, representing conditions that may not be appropriate to care for in pediatric-limited settings given their need for advanced interventions. Our findings demonstrate that defining a cohort of conditions based on frequency of transfer, even when accounting for minimal intervention post transfer, may not adequately capture avoidable transfers. For example, abdominal pain was one of the conditions for which patients were most frequently transferred, with 92% of patients discharged rapidly. However, the most common surgical transfer was acute appendicitis with peritonitis. Many of these transfers may have been identified initially as “abdominal pain” at the referring institution, highlighting the role of diagnostic uncertainty in identifying preventable transfers. In addition, more than 56% of patients transferred for abdominal pain required advanced interventions, further illustrating the potential risk and uncertainty for referring hospitals that do not have the capacity for advanced imaging or surgical intervention.

The rapid upscale of telehealth may provide a unique opportunity to support the provision of pediatric care within local communities.^12,13 As many general hospitals do not have ultrasound technicians trained for children available 24 hours per day, several conditions that fell into the advanced intervention category, like abdominal pain, were driven by the receipt of an ultrasound at the accepting hospital. Targeted work to expand ultrasound capabilities at referring hospitals may enable changing the categorization of an ultrasound to a basic intervention rather than an advanced intervention. Paired with telehealth, this might broaden the scope of potential diagnoses that could be triaged to stay within referring institutions.

Building infrastructure to prevent interfacility transfers may improve healthcare access for children in rural areas proportionately more than children in urban areas. Children in rural communities experience significantly higher rates of interfacility transfers than children in urban areas.¹⁴ This increases financial burden and causes additional distress and inconvenience for families.¹⁵ With constraints in staffing capacity, equipment, and finances, identifying a subset of medical conditions is a critical initial step to inform the design of targeted interventions to support pediatric healthcare delivery in local communities and avoid costly transfers, although it is not the wholesale solution. Additional utilization of tools such as informed shared decision-making resources and implementation of pediatric-specific protocols likely represent additional necessary steps.

Our study has several limitations. Because we used administrative data, there is a risk of misclassifying diagnoses. We attempted to mitigate this by using a standard ICD-10-based, pediatric-specific grouper. ICD-10 coding is also based upon discharge diagnoses, which inherently has retrospective bias that cannot capture the diagnostic uncertainty when making an initial decision for transfer. In addition, without a comparator group of patients who were not transferred, it remains unknown to what extent balancing factors informed the decision to transfer or whether these diagnoses represent conditions that the referring hospital encounters only a few times a year, or alternatively, that the percentage transferred represents a small fraction of the referring institution’s population with a given diagnosis.

CONCLUSION

Our exploration of pediatric interfacility transfers that experienced rapid discharge with minimal intervention provides a building block to support the provision of definitive pediatric care in non-pediatric hospitals and represents a step towards addressing limited access to care in general hospitals.

Regionalization of pediatric acute care is increasing across the United States, with rates of interfacility transfer for general medical conditions in children similar to those of high-risk conditions in adults.¹ The inability for children to receive definitive care (ie, care provided to conclusively manage a patient’s condition without requiring an interfacility transfer) within their local community has implications on public health as well as family function and financial burden.^1,2 Previous studies demonstrated that 30% to 80% of interfacility transfers are potentially unnecessary,^3-6 as indicated by a high proportion of short lengths of stay after transfer. While rapidity of discharge is an important factor in identifying potentially unnecessary transfers, many of these studies included diagnoses requiring specialized imaging or surgical interventions, which may not be available in referring institutions.

To highlight conditions that referring hospitals may prioritize for pediatric capacity building, we aimed to identify the most common medical diagnoses among pediatric transfer patients that did not require advanced evaluation or intervention and that had high rates of discharge within 1 day of interfacility transfer.

METHODS

We conducted a retrospective, cross-sectional, descriptive study using the Pediatric Health Information System (PHIS) database, which contains administrative data from 48 geographically diverse US children’s hospitals.

We included children <18 years old who were transferred to a participating PHIS hospital in 2019, including emergency department (ED), observation, and inpatient encounters. We identified patients through the source-of-admission code labeled as “transfer.” Diagnoses were identified through the International Classification of Diseases, Tenth Revision (ICD-10) codes using the Pediatric Clinical Classification System.⁷We excluded the following categories: mental or behavioral health diagnoses, maternal or labor diagnoses, primary newborn birth diagnoses, and transfers directly to an intensive care unit (ICU).

For each diagnosis, we determined the number of transfers and frequency of rapid discharge, defined as either discharge from the ED without admission or admission and discharge within 1 day from a general inpatient unit. As discharge times are not reliably available in PHIS, all patients discharged on the day of transfer or the following calendar day were identified as rapid discharge. Medical complexity was determined through applying the Pediatric Medical Complexity Algorithm (PMCA).⁸

To identify diagnoses seen with sufficient frequency to represent potentially useful areas for referring hospitals to target, we limited our analysis to diagnoses that had a minimum of 576 transfers per year, equivalent to at least 1 transfer for that diagnosis per month per PHIS hospital. We then categorized the frequency of interventions after transfer, including (1) no interventions received; (2) basic interventions only, defined as receiving any intravenous fluids, antimicrobials, antipyretics or analgesics, and/or basic imaging (ie, radiography and computed tomography [CT]); or (3) advanced interventions, including transfer to an ICU after initial presentation/management in the ED or inpatient ward, advanced imaging (eg, ultrasound, magnetic resonance [MR] imaging, MR angiography or venography, CT angiography), or any surgical intervention. A full categorization of basic and advanced interventions is available in Appendix Table 1.

For descriptive statistics, we calculated means for normally distributed variables, medians for continuous variables with nonnormal distributions, and percentages for binary variables. Comparisons were made using t-tests and chi-square tests.

This study was approved by the Seattle Children’s Institutional Review Board.

RESULTS

We identified 286,905 transfers into participating PHIS hospitals in 2019. Of these, 89,519 (31.2%) were excluded (Appendix Table 2), leaving 197,386 (68.6%) transfers. Patients discharged within 1 day were more likely to have public or unknown insurance (65.1% vs 61.5%, P < 0.01), to have no co-occurring chronic conditions (60.2% vs 28.5%, P < 0.01), and to reside within the Northeast (35.0% vs 11.0%, P < 0.01) (Appendix Table 3).

The most common medical diagnoses among these transfers included acute bronchiolitis (4.3% of all interfacility transfers, n = 8,425), chemotherapy (4.0%, n = 7,819), and asthma (3.3%, n = 6,430) (Appendix Table 4); 45.9% of bronchiolitis, 15.0% of chemotherapy, and 67.4% of asthma transfers were rapidly discharged.

The Table shows the medical conditions among transfers that most frequently experienced rapid discharge (primary surgical diagnoses are presented in Appendix Table 5).

Within this cohort, patients transferred for cough were most likely to be rapidly discharged, with 98.5% (n = 611) discharged within 1 day of transfer. Among these, 66.5% (n = 412) received no interventions and 33.4% (n = 207) received only basic interventions. Only 1.3% (n = 8) required any advanced intervention. Similarly, 96.0% (n = 603) of patients with the diagnosis of chest pain were rapidly discharged, with 45.1% (n = 272) requiring no interventions, 48.3% (n = 291) receiving basic interventions, and 17.7% (n = 107) requiring advanced intervention. Patients with the diagnosis of febrile seizures, croup, and allergic reactions were rapidly discharged 91.8% (n = 584), 87.3% (n = 1,893) and 87.2% (n = 1,350) of the time, respectively, and more than 70% patients with these diagnoses underwent no intervention after transfer. In addition, while 92.0% (n = 3,392) of patients with abdominal pain diagnoses were discharged rapidly, 55.5% (n = 1,883) received advanced imaging (Appendix Table 6). Similarly, while 92.0% (n = 2,229) of patients with open wounds to the head, neck, and trunk were discharged rapidly, 17.3% (n = 419) of patients with these diagnoses required a surgical intervention after transfer (Appendix Table 6).

DISCUSSION

We have identified medical conditions that not only had high rates of rapid discharge after transfer, but also received minimal intervention from the accepting institution. Although bronchiolitis and chemotherapy were the most common conditions for which patients were transferred, the range of severity varied widely, with more than 50% of bronchiolitis and 85% of chemotherapy transfers requiring hospitalization for longer than 1 day. Diagnoses such as chemotherapy, although common among transferred patients, likely represent conditions that may not be appropriate to care for in pediatric-limited settings, as they require subspecialized pediatric care. General conditions, however, such as cough, chest pain, allergic reactions, and febrile seizures may represent diagnoses for which it would be appropriate for general hospitals to develop infrastructure to provide definitive pediatric care given how infrequently specialized pediatric resources are needed in caring for these conditions.

Identifying conditions as potential targets to reduce the number of interfacility transfers requires balancing a hospital’s capacity (or lack thereof) for pediatric admissions, perceived risk of decompensation, referring provider discomfort, and parental preference.^9-11 Although several studies have identified conditions associated with frequent transfer and rapid discharge,^3-5 prior studies’ conclusions that 40% or more of interhospital transfers may be avoidable are potential over-estimates, representing conditions that may not be appropriate to care for in pediatric-limited settings given their need for advanced interventions. Our findings demonstrate that defining a cohort of conditions based on frequency of transfer, even when accounting for minimal intervention post transfer, may not adequately capture avoidable transfers. For example, abdominal pain was one of the conditions for which patients were most frequently transferred, with 92% of patients discharged rapidly. However, the most common surgical transfer was acute appendicitis with peritonitis. Many of these transfers may have been identified initially as “abdominal pain” at the referring institution, highlighting the role of diagnostic uncertainty in identifying preventable transfers. In addition, more than 56% of patients transferred for abdominal pain required advanced interventions, further illustrating the potential risk and uncertainty for referring hospitals that do not have the capacity for advanced imaging or surgical intervention.

The rapid upscale of telehealth may provide a unique opportunity to support the provision of pediatric care within local communities.^12,13 As many general hospitals do not have ultrasound technicians trained for children available 24 hours per day, several conditions that fell into the advanced intervention category, like abdominal pain, were driven by the receipt of an ultrasound at the accepting hospital. Targeted work to expand ultrasound capabilities at referring hospitals may enable changing the categorization of an ultrasound to a basic intervention rather than an advanced intervention. Paired with telehealth, this might broaden the scope of potential diagnoses that could be triaged to stay within referring institutions.

Building infrastructure to prevent interfacility transfers may improve healthcare access for children in rural areas proportionately more than children in urban areas. Children in rural communities experience significantly higher rates of interfacility transfers than children in urban areas.¹⁴ This increases financial burden and causes additional distress and inconvenience for families.¹⁵ With constraints in staffing capacity, equipment, and finances, identifying a subset of medical conditions is a critical initial step to inform the design of targeted interventions to support pediatric healthcare delivery in local communities and avoid costly transfers, although it is not the wholesale solution. Additional utilization of tools such as informed shared decision-making resources and implementation of pediatric-specific protocols likely represent additional necessary steps.

Our study has several limitations. Because we used administrative data, there is a risk of misclassifying diagnoses. We attempted to mitigate this by using a standard ICD-10-based, pediatric-specific grouper. ICD-10 coding is also based upon discharge diagnoses, which inherently has retrospective bias that cannot capture the diagnostic uncertainty when making an initial decision for transfer. In addition, without a comparator group of patients who were not transferred, it remains unknown to what extent balancing factors informed the decision to transfer or whether these diagnoses represent conditions that the referring hospital encounters only a few times a year, or alternatively, that the percentage transferred represents a small fraction of the referring institution’s population with a given diagnosis.

CONCLUSION

Our exploration of pediatric interfacility transfers that experienced rapid discharge with minimal intervention provides a building block to support the provision of definitive pediatric care in non-pediatric hospitals and represents a step towards addressing limited access to care in general hospitals.

Regionalization of pediatric acute care is increasing across the United States, with rates of interfacility transfer for general medical conditions in children similar to those of high-risk conditions in adults.¹ The inability for children to receive definitive care (ie, care provided to conclusively manage a patient’s condition without requiring an interfacility transfer) within their local community has implications on public health as well as family function and financial burden.^1,2 Previous studies demonstrated that 30% to 80% of interfacility transfers are potentially unnecessary,^3-6 as indicated by a high proportion of short lengths of stay after transfer. While rapidity of discharge is an important factor in identifying potentially unnecessary transfers, many of these studies included diagnoses requiring specialized imaging or surgical interventions, which may not be available in referring institutions.

To highlight conditions that referring hospitals may prioritize for pediatric capacity building, we aimed to identify the most common medical diagnoses among pediatric transfer patients that did not require advanced evaluation or intervention and that had high rates of discharge within 1 day of interfacility transfer.

METHODS

We conducted a retrospective, cross-sectional, descriptive study using the Pediatric Health Information System (PHIS) database, which contains administrative data from 48 geographically diverse US children’s hospitals.

We included children <18 years old who were transferred to a participating PHIS hospital in 2019, including emergency department (ED), observation, and inpatient encounters. We identified patients through the source-of-admission code labeled as “transfer.” Diagnoses were identified through the International Classification of Diseases, Tenth Revision (ICD-10) codes using the Pediatric Clinical Classification System.⁷We excluded the following categories: mental or behavioral health diagnoses, maternal or labor diagnoses, primary newborn birth diagnoses, and transfers directly to an intensive care unit (ICU).

For each diagnosis, we determined the number of transfers and frequency of rapid discharge, defined as either discharge from the ED without admission or admission and discharge within 1 day from a general inpatient unit. As discharge times are not reliably available in PHIS, all patients discharged on the day of transfer or the following calendar day were identified as rapid discharge. Medical complexity was determined through applying the Pediatric Medical Complexity Algorithm (PMCA).⁸

To identify diagnoses seen with sufficient frequency to represent potentially useful areas for referring hospitals to target, we limited our analysis to diagnoses that had a minimum of 576 transfers per year, equivalent to at least 1 transfer for that diagnosis per month per PHIS hospital. We then categorized the frequency of interventions after transfer, including (1) no interventions received; (2) basic interventions only, defined as receiving any intravenous fluids, antimicrobials, antipyretics or analgesics, and/or basic imaging (ie, radiography and computed tomography [CT]); or (3) advanced interventions, including transfer to an ICU after initial presentation/management in the ED or inpatient ward, advanced imaging (eg, ultrasound, magnetic resonance [MR] imaging, MR angiography or venography, CT angiography), or any surgical intervention. A full categorization of basic and advanced interventions is available in Appendix Table 1.

For descriptive statistics, we calculated means for normally distributed variables, medians for continuous variables with nonnormal distributions, and percentages for binary variables. Comparisons were made using t-tests and chi-square tests.

This study was approved by the Seattle Children’s Institutional Review Board.

RESULTS

We identified 286,905 transfers into participating PHIS hospitals in 2019. Of these, 89,519 (31.2%) were excluded (Appendix Table 2), leaving 197,386 (68.6%) transfers. Patients discharged within 1 day were more likely to have public or unknown insurance (65.1% vs 61.5%, P < 0.01), to have no co-occurring chronic conditions (60.2% vs 28.5%, P < 0.01), and to reside within the Northeast (35.0% vs 11.0%, P < 0.01) (Appendix Table 3).

The most common medical diagnoses among these transfers included acute bronchiolitis (4.3% of all interfacility transfers, n = 8,425), chemotherapy (4.0%, n = 7,819), and asthma (3.3%, n = 6,430) (Appendix Table 4); 45.9% of bronchiolitis, 15.0% of chemotherapy, and 67.4% of asthma transfers were rapidly discharged.

The Table shows the medical conditions among transfers that most frequently experienced rapid discharge (primary surgical diagnoses are presented in Appendix Table 5).

Within this cohort, patients transferred for cough were most likely to be rapidly discharged, with 98.5% (n = 611) discharged within 1 day of transfer. Among these, 66.5% (n = 412) received no interventions and 33.4% (n = 207) received only basic interventions. Only 1.3% (n = 8) required any advanced intervention. Similarly, 96.0% (n = 603) of patients with the diagnosis of chest pain were rapidly discharged, with 45.1% (n = 272) requiring no interventions, 48.3% (n = 291) receiving basic interventions, and 17.7% (n = 107) requiring advanced intervention. Patients with the diagnosis of febrile seizures, croup, and allergic reactions were rapidly discharged 91.8% (n = 584), 87.3% (n = 1,893) and 87.2% (n = 1,350) of the time, respectively, and more than 70% patients with these diagnoses underwent no intervention after transfer. In addition, while 92.0% (n = 3,392) of patients with abdominal pain diagnoses were discharged rapidly, 55.5% (n = 1,883) received advanced imaging (Appendix Table 6). Similarly, while 92.0% (n = 2,229) of patients with open wounds to the head, neck, and trunk were discharged rapidly, 17.3% (n = 419) of patients with these diagnoses required a surgical intervention after transfer (Appendix Table 6).

DISCUSSION

We have identified medical conditions that not only had high rates of rapid discharge after transfer, but also received minimal intervention from the accepting institution. Although bronchiolitis and chemotherapy were the most common conditions for which patients were transferred, the range of severity varied widely, with more than 50% of bronchiolitis and 85% of chemotherapy transfers requiring hospitalization for longer than 1 day. Diagnoses such as chemotherapy, although common among transferred patients, likely represent conditions that may not be appropriate to care for in pediatric-limited settings, as they require subspecialized pediatric care. General conditions, however, such as cough, chest pain, allergic reactions, and febrile seizures may represent diagnoses for which it would be appropriate for general hospitals to develop infrastructure to provide definitive pediatric care given how infrequently specialized pediatric resources are needed in caring for these conditions.

Identifying conditions as potential targets to reduce the number of interfacility transfers requires balancing a hospital’s capacity (or lack thereof) for pediatric admissions, perceived risk of decompensation, referring provider discomfort, and parental preference.^9-11 Although several studies have identified conditions associated with frequent transfer and rapid discharge,^3-5 prior studies’ conclusions that 40% or more of interhospital transfers may be avoidable are potential over-estimates, representing conditions that may not be appropriate to care for in pediatric-limited settings given their need for advanced interventions. Our findings demonstrate that defining a cohort of conditions based on frequency of transfer, even when accounting for minimal intervention post transfer, may not adequately capture avoidable transfers. For example, abdominal pain was one of the conditions for which patients were most frequently transferred, with 92% of patients discharged rapidly. However, the most common surgical transfer was acute appendicitis with peritonitis. Many of these transfers may have been identified initially as “abdominal pain” at the referring institution, highlighting the role of diagnostic uncertainty in identifying preventable transfers. In addition, more than 56% of patients transferred for abdominal pain required advanced interventions, further illustrating the potential risk and uncertainty for referring hospitals that do not have the capacity for advanced imaging or surgical intervention.

The rapid upscale of telehealth may provide a unique opportunity to support the provision of pediatric care within local communities.^12,13 As many general hospitals do not have ultrasound technicians trained for children available 24 hours per day, several conditions that fell into the advanced intervention category, like abdominal pain, were driven by the receipt of an ultrasound at the accepting hospital. Targeted work to expand ultrasound capabilities at referring hospitals may enable changing the categorization of an ultrasound to a basic intervention rather than an advanced intervention. Paired with telehealth, this might broaden the scope of potential diagnoses that could be triaged to stay within referring institutions.

Building infrastructure to prevent interfacility transfers may improve healthcare access for children in rural areas proportionately more than children in urban areas. Children in rural communities experience significantly higher rates of interfacility transfers than children in urban areas.¹⁴ This increases financial burden and causes additional distress and inconvenience for families.¹⁵ With constraints in staffing capacity, equipment, and finances, identifying a subset of medical conditions is a critical initial step to inform the design of targeted interventions to support pediatric healthcare delivery in local communities and avoid costly transfers, although it is not the wholesale solution. Additional utilization of tools such as informed shared decision-making resources and implementation of pediatric-specific protocols likely represent additional necessary steps.

Our study has several limitations. Because we used administrative data, there is a risk of misclassifying diagnoses. We attempted to mitigate this by using a standard ICD-10-based, pediatric-specific grouper. ICD-10 coding is also based upon discharge diagnoses, which inherently has retrospective bias that cannot capture the diagnostic uncertainty when making an initial decision for transfer. In addition, without a comparator group of patients who were not transferred, it remains unknown to what extent balancing factors informed the decision to transfer or whether these diagnoses represent conditions that the referring hospital encounters only a few times a year, or alternatively, that the percentage transferred represents a small fraction of the referring institution’s population with a given diagnosis.

CONCLUSION

Our exploration of pediatric interfacility transfers that experienced rapid discharge with minimal intervention provides a building block to support the provision of definitive pediatric care in non-pediatric hospitals and represents a step towards addressing limited access to care in general hospitals.

Despite the widespread availability of evidence-based guidelines,¹ there is inappropriate variation in the care and outcomes for children with asthma in both the emergency department (ED) and the inpatient setting.^2-6 Operational versions of evidence-based guidelines known as “pathways” have been shown to improve adoption of evidence-based guidelines, quality of care, and health outcomes for children with asthma.^7-14 However, little is known about how to successfully implement pathways outside of free-standing children’s hospitals.^15-19

The majority of children with asthma in the United States are cared for in community hospitals, which provide services for both adults and children.²⁰ However, prior studies of pediatric asthma pathways have largely excluded community hospitals. These studies primarily focused on determining clinical effectiveness, rather than detailing the implementation process. These approaches have left critical gaps that hinder our ability to implement pathways and improve care in community hospitals, which have unique barriers and less resources.^21,22 Therefore, understanding the process of pathway implementation in community hospitals is critical to improving care for children.²² Our objective was to identify the key determinants of successful pediatric asthma pathway implementation using a national sample of community hospitals. This knowledge can guide hospital leaders and healthcare providers in efforts to improve pediatric care and outcomes in these settings.

METHODS

Study Setting, Design, and Population

In Fall 2017, the Value in Inpatient Pediatrics (VIP) network launched PIPA, Pathways to Improving Pediatric Asthma care.²³ The VIP network, a part of the American Academy of Pediatrics (AAP), aims to improve the value of care delivered to any pediatric patient in a hospital bed, from rural to free-standing children’s hospitals.²⁴ PIPA used a learning collaborative model²⁵ and recruited local project leaders (physicians, nurses, respiratory therapists (RT), and pharmacists) from 89 hospitals around the country. PIPA provided these hospital teams with asthma pathways and several resources for implementation support, including educational meetings, quality improvement (QI) training, audit and feedback, and facilitation. Facilitation is a process of interactive problem-solving and support that occurs in the context of a supportive interpersonal relationship and a recognized need for improvement.²⁶ A facilitator, or a “coach”, is an external expert who provides project mentorship and assists the process of making meaningful changes to improve patient care.²⁶ Facilitation was provided by external consultants with QI expertise.

For this qualitative study, facilitators conducted semi-structured interviews with a convenience sample of project leaders from community hospitals participating in PIPA, with some interviews including multiple project leaders (eg, nursing, inpatient, and Emergency Department [ED] leaders). Verbal consent was obtained from all participants. No incentives were provided. This study was approved by the AAP institutional review board.

 

Data Collection

We used the constructs described in the Consolidated Framework for Implementation Research (CFIR)²⁷ and adapted those salient to pediatric asthma pathways to develop an interview guide that was used with all participants (Appendix 1). The CFIR offers an overarching typology to understand what works where and why across five major domains that influence implementation: intervention characteristics, inner setting (hospital), outer setting (economic, political, and social context of the hospital), characteristics of the individuals involved, and the process of implementation. Data were collected across these domains to inform our analysis of the key determinants of pediatric asthma pathway implementation in community hospitals.

Interviews were conducted by phone from December 2017 to April 2018 (first four months of pathway implementation). Interviews lasted 30-60 minutes and were recorded and transcribed verbatim. Transcripts were edited for accuracy using the audio recordings. As data collection occurred concurrently with analysis, the interview guide was iteratively revised to reflect new insights and patterns that emerged from our analysis. All sites were anonymized in the data analysis. New interviews were coded until thematic saturation was reached.

Analysis

We conducted an inductive thematic analysis using the CFIR as our conceptual framework.^28,29 Four investigators (CM, MJ, ES, and SK) performed the initial open coding of the data. Investigators met twice during the open coding process to develop and then finalize a codebook of standard definitions for codes. This codebook facilitated coding consistency through the remainder of the analytic process. Two investigators (CM and MJ) then independently read and coded all data to ensure intercoder reliability. During this process, CM and MJ met every two weeks to compare coding consistency, resolve discrepancies, and discuss preliminary findings. When the coding was complete, all investigators met to explore and develop themes that encompassed related common codes.

The CFIR was used at two stages of the study: (1) developing the interview guide and (2) cross-checking for any potentially important codes that were missing/needed to be explored further. Thus, the investigators maintained an inductive approach grounded in the data. To assure study rigor, we employed investigator triangulation (use of multiple investigators and participants from multiple clinical roles) and reflexivity (ongoing critique and critical reflection of the individual biases of the investigators).³⁰ Coding was performed using Dedoose (version 7.0.23; Los Angeles, California).

RESULTS

A total of 34 community hospitals completed the PIPA project, of which the project leaders of 25 hospitals connected with the facilitators and were approached to participate; 18 (72%) hospitals’ project leaders participated in the study. We analyzed 18 interviews conducted between facilitators and project leaders, which included a total of 32 project leaders (one to five leaders per interview). The hospitals represented were diverse in geographic location and size (range 4-50 pediatric beds per hospital), and the majority of sites (78%) supported the trainees (Table 1).

We identified four overarching themes that described the key determinants of pathway implementation in community hospitals. These themes are presented in order of their frequency of occurrence in the data. They included (1) building an implementation infrastructure, (2) engaging and motivating providers, (3) addressing organizational and resource limitations, and (4) devising implementation solutions with facilitators. Descriptions and exemplary quotations for each theme are provided in Table 2 and Appendix Figure 1.

 

Building an Implementation Infrastructure

Participants described the importance of building an implementation infrastructure as a critical first step. Establishing an infrastructure required multiple efforts, including forming a team of local champions, delivering didactic education and skills training, and modifying clinical workflows. The multidisciplinary “team of champions” facilitated the division of practical tasks (eg, data entry, Institutional Review Board [IRB] application) and planned educational interventions and setting specific goals, without overloading any given individual. Building an implementation infrastructure “on-the-ground” required thoughtful consideration of local context and engagement of frontline hospital staff commonly involved in the care of children with asthma.

“So, I’m going to sit down with the primary nursing staff and the other four physicians in the group to go over the expectations…We’re not going to have the actual EMR [changes] and we’re not going to have the nursing documentation field built right away but [we want to] make sure that people are documenting the respiratory score in their generic nursing note so that the information is easily accessible.” (Physician leader, Hospital G)

Participants also described the need to deliver education on the evidence supporting changes in practice and skills training specific to pediatric asthma care:

“Once we realized that we were going to be doing this pathway, we started training our nurses on the inpatient side on [pediatric respiratory scoring].” (Nursing leader, Hospital P)

In addition, pathway implementation required modification of clinical workflows via changes to hospital policies or guidelines, electronic medical records (EMR), and/or the physical environment (eg, placing supplies in proximity to care delivery):

“I think it can help if we could get an order set or a nursing protocol where asthmatics over a certain severity can just get steroids in triage.” (Physician leader, Hospital A)

Engaging and Motivating Providers

Another crucial step in pathway implementation was engaging and motivating providers. This included overcoming inertia to practice change, facilitating multidisciplinary collaboration, and handling conflicts regarding practice changes. Participants discussed the excitement of participating in a national collaborative as especially motivating to help drive engagement and overcome barriers to change, particularly the ability to compare local hospital performance to national peers.

“I think everyone is a little competitive. So I think that when we see how we compare to other institutions—both our group and the ER—I think it also adds a little oomph…I think for our nurses too; we’re able to say, ‘[look how we compare to] most of the other hospitals.’ I think that helps.” (Physician leader, Hospital B)

Multidisciplinary collaboration across a wide variety of frontline pediatric and nonpediatric providers was key to understanding current workflows and identifying needed modifications for pathway implementation:

“I do think clearly our biggest obstacles are the fact that we have adult ED providers. We have the opportunity on the inpatient side [with nursing and respiratory therapy], who really do awesome with pediatric changes, to take our wins where we can and make the changes with the ED. In the ED we have an RN educator. She’s very on board with doing the respiratory scoring and getting this whole thing started.” (Physician leader, Hospital L)

 

Intentional communication and leadership skills also played key roles in engaging hesitant providers and handling conflict:

“Just sitting and talking with our respiratory therapist about the ability to provide this type of service or support and seeing what their reservations have been, at least it’s open to conversation so that we could provide these types of therapies in the future and we’re able to see like what people’s concerns are. I think just basically increasing familiarity with not only these processes, but different types of therapy will hopefully in the future help us provide better care to our patients.” (Physician leader, Hospital Q)

Addressing Organizational and Resource Limitations

Participants recognized organizational and resource limitations, some of which may be unique to community hospitals that prioritize resources for adult care. The limitations described included EMR staff support, healthcare provider staffing/capacity, navigating IRBs, and addressing administrative processes. Competing demands for information technology staff support and lack of prioritization of pediatric-specific initiatives often hindered efforts to modify the EMR.

“Resource wise, we are hoping to implement an order set in our Epic EMR, [but] finding the availability from the Epic team may be a challenge.” (Physician Leader, Hospital A)

Participants also reported that limited staff capacity (eg, nursing, RT) hindered pathway implementation efforts. This limited capacity hindered workflow changes and limited the time available for education and training on pathways:

“[Respiratory scoring for asthma is] an added responsibility for the [nursing] staff and we don’t have patient technicians. So they’re doing everything from changing the sheets to bringing water to all of the medical patients. So, that I think may be a barrier.” (Physician leader, Hospital B)

Across sites, navigating the IRB posed various challenges. Some sites were required to obtain approval from regional IRBs, which did not have resources to devote to pediatric projects. Other sites did not have IRBs at all, but instead required separate approvals for the project from hospital leadership or other entities:

“On the IRB, I contacted the manager of the IRB and she’s said, ‘No, it’s not an IRB project,’ but she sent it to another director for review, and it took forever to be able to get a data agreement with [the local university hospital] so that we can pull the data. I just couldn’t believe it took months to get done.” (Physician Leader, Hospital K)

Finally, administrative barriers such as addressing formulary changes in the context of adult-focused settings were challenging. For example, at one hospital, metered dose inhalers (MDIs) were not used for adult patients, and the hospital administration was resistant to incorporate their use into practice for pediatric patients due to the cost of such changes.

“The [general hospital] didn’t have MDI’s anymore because of cost reasons, and when we started the pediatric work, we really made it a point to get the MDI’s for pediatric patients back in the formulary.” (Physician leader, Hospital A)

Devising Implementation Solutions with Practice Facilitators

 

Participants often devised pathway implementation solutions with facilitators in-the-moment during meetings. This problem-solving included figuring out work-arounds, proactive coaching by external facilitators, and just-in-time solution building. Furthermore, in meetings that included more than one project leader, leaders would often work with each other to devise solutions. Meetings provided forums that stimulated identification of implementation barriers, brainstorming, and subsequently solution building.

Physician leader: I’m wondering if we could, as an interim solution, try out an algorithm on paper, I don’t know if that’s allowed, until we get Epic approval. Do you know?

Nurse Leader: You mean having an algorithm posted in triage? Yeah, I don’t see why not. (Hospital A)

Next, problem solving was often driven by the facilitator’s experience and knowledge, drawn from their interactions with other collaborative sites or their own prior experiences with asthma, QI, or pathway implementation. The facilitators brought an outside perspective, not bound by that particular hospital’s local culture or structural intricacies. This proactive coaching spurred the identification of creative, yet practical solutions:

Project Leader: We’re still trying to get all our templates [for the EMR]…because [currently they are] all adult templates.

Facilitator: If you’re making templates right now, could you also add the three asterisks? Like smoking or exposure to second hand tobacco smoke or marijuana…then have the three asterisks there and then “Referral made?***”. That would force people to document in a certain place in the template as well.Project Leader: That’s definitely something we could add right now. (Hospital O)

Check-in meetings with facilitators offered an opportunity to trouble shoot, brainstorm work-arounds, devise in-the-moment site-specific solutions to enable successful pathway implementation, and provide ongoing support throughout implementation.

DISCUSSION

Pathways can improve the quality of care for children with asthma.³¹ However, there is little evidence-based guidance on how to implement pathways and improve pediatric care in community hospitals,^17-20 where the majority of children are cared for nationally. This is the first study to our knowledge that details the key determinants of pediatric asthma pathway implementation in community hospital settings. We identified four key determinants of implementation that can help guide others in similar settings. These include building an implementation infrastructure, engaging and motivating multidisciplinary providers, addressing organizational and resource limitations, and using external facilitators to devise implementation solutions.

Existing frameworks such as the CFIR outline the potential determinants of implementation success but do not provide population- or setting-specific guidance.²⁷ There have been prior studies detailing pathway implementation for pediatric populations, but these studies did not focus on community hospitals.^32,33 Our findings align with these prior studies, which highlight the importance of identifying implementation champions, engaging and motivating multidisciplinary providers, establishing a QI infrastructure, and addressing organizational and resource limitations, such as EMR integration.^32,33 However, our study provides unique insights into issues that are important to successful pathway implementation in community hospitals, including engagement of adult-focused healthcare providers, reprioritization of resources toward the care of children, and the potentially critical role of external facilitators.

Our findings indicate that community hospitals seeking to improve care for children may particularly benefit from using external facilitators and/or partnering with external organizations. We found that external facilitators played a significant and proactive role in community hospitals’ efforts to improve care for children. Facilitators helped devise work-arounds and engaged in just-in-time solution building with local project leaders. For instance, facilitators helped develop strategies for training healthcare providers in performing new clinical tasks, building reminders of pathway recommendations into clinical workflows, and overcoming resource barriers. Thus, community hospitals may uniquely benefit from participation in national learning collaboratives, which often provide avenues for external facilitation.^25,34,35 National networks, such as the VIP network, lead national learning collaboratives that provide external facilitation as well as other resources (eg, educational materials, data analysis support) to community hospitals seeking to improve pediatric care.²⁴ Previous work by McDaniel et al. identified that intentional partnerships between children’s and community hospitals can also potentially provide access to resources for education and training in pediatric care and support in navigating organizational and resource challenges.²²

Our results characterize the key determinants of pediatric asthma pathway implementation using a national sample of community hospitals that were diverse in geography, size, and structure. This imparts greater transferability of our findings. We also used strategies to promote the rigor of our findings, including triangulation and reflexivity. However, our study has several limitations. First, we analyzed only the meetings that occurred during the early months of pathway implementation. As such, we did not capture any key determinants that may have arisen later in implementation. However, process analyses of implementation indicate that the majority of implementation efforts occurred within these first three to four months.³⁶ Second, we did not elicit input from hospital administration or leadership. The lack of administrative/leadership input probably affected the CFIR themes we found, as no themes from the outer setting were elicited. However, the goal of our study was to characterize the experiences of those leading implementation efforts, and focusing on these leaders allows our work to better guide those doing similar work in the future. Third, we used CFIR to guide the development of our interview guide and as a reference during analysis, which may have skewed our findings to preferentially reflect CFIR constructs. However, our overall analysis was grounded in the primary data and we employed reflexivity during all stages of our analysis. In addition, having the facilitators conduct the qualitative interviews may have biased our findings toward the perspectives of the facilitators; however, the facilitators represented quite diverse clinical and QI backgrounds. Finally, our findings do not necessarily correlate with improvements in clinical outcomes. As such, they are not meant to serve as explicit recommendations for improving patient outcomes, but rather as a characterization of the context, processes, and experiences of implementing pathways in the community setting to inform others doing this important work.

 

CONCLUSIONS

We identified the key determinants of pediatric asthma pathway implementation in community hospitals, which may help inform QI efforts in these settings. We also identified organizational and resource limitations that are probably unique to these adult-focused hospitals. Participating in national learning collaboratives and/or working with facilitators may support pathway implementation and improved quality of care for children with asthma in community hospitals.

Future work should seek to correlate these and other determinants of pathway implementation with health outcomes for hospitalized children, as well as integrate broader and more diverse samples of community hospitals.

Despite the widespread availability of evidence-based guidelines,¹ there is inappropriate variation in the care and outcomes for children with asthma in both the emergency department (ED) and the inpatient setting.^2-6 Operational versions of evidence-based guidelines known as “pathways” have been shown to improve adoption of evidence-based guidelines, quality of care, and health outcomes for children with asthma.^7-14 However, little is known about how to successfully implement pathways outside of free-standing children’s hospitals.^15-19

The majority of children with asthma in the United States are cared for in community hospitals, which provide services for both adults and children.²⁰ However, prior studies of pediatric asthma pathways have largely excluded community hospitals. These studies primarily focused on determining clinical effectiveness, rather than detailing the implementation process. These approaches have left critical gaps that hinder our ability to implement pathways and improve care in community hospitals, which have unique barriers and less resources.^21,22 Therefore, understanding the process of pathway implementation in community hospitals is critical to improving care for children.²² Our objective was to identify the key determinants of successful pediatric asthma pathway implementation using a national sample of community hospitals. This knowledge can guide hospital leaders and healthcare providers in efforts to improve pediatric care and outcomes in these settings.

METHODS

Study Setting, Design, and Population

In Fall 2017, the Value in Inpatient Pediatrics (VIP) network launched PIPA, Pathways to Improving Pediatric Asthma care.²³ The VIP network, a part of the American Academy of Pediatrics (AAP), aims to improve the value of care delivered to any pediatric patient in a hospital bed, from rural to free-standing children’s hospitals.²⁴ PIPA used a learning collaborative model²⁵ and recruited local project leaders (physicians, nurses, respiratory therapists (RT), and pharmacists) from 89 hospitals around the country. PIPA provided these hospital teams with asthma pathways and several resources for implementation support, including educational meetings, quality improvement (QI) training, audit and feedback, and facilitation. Facilitation is a process of interactive problem-solving and support that occurs in the context of a supportive interpersonal relationship and a recognized need for improvement.²⁶ A facilitator, or a “coach”, is an external expert who provides project mentorship and assists the process of making meaningful changes to improve patient care.²⁶ Facilitation was provided by external consultants with QI expertise.

For this qualitative study, facilitators conducted semi-structured interviews with a convenience sample of project leaders from community hospitals participating in PIPA, with some interviews including multiple project leaders (eg, nursing, inpatient, and Emergency Department [ED] leaders). Verbal consent was obtained from all participants. No incentives were provided. This study was approved by the AAP institutional review board.

 

Data Collection

We used the constructs described in the Consolidated Framework for Implementation Research (CFIR)²⁷ and adapted those salient to pediatric asthma pathways to develop an interview guide that was used with all participants (Appendix 1). The CFIR offers an overarching typology to understand what works where and why across five major domains that influence implementation: intervention characteristics, inner setting (hospital), outer setting (economic, political, and social context of the hospital), characteristics of the individuals involved, and the process of implementation. Data were collected across these domains to inform our analysis of the key determinants of pediatric asthma pathway implementation in community hospitals.

Interviews were conducted by phone from December 2017 to April 2018 (first four months of pathway implementation). Interviews lasted 30-60 minutes and were recorded and transcribed verbatim. Transcripts were edited for accuracy using the audio recordings. As data collection occurred concurrently with analysis, the interview guide was iteratively revised to reflect new insights and patterns that emerged from our analysis. All sites were anonymized in the data analysis. New interviews were coded until thematic saturation was reached.

Analysis

We conducted an inductive thematic analysis using the CFIR as our conceptual framework.^28,29 Four investigators (CM, MJ, ES, and SK) performed the initial open coding of the data. Investigators met twice during the open coding process to develop and then finalize a codebook of standard definitions for codes. This codebook facilitated coding consistency through the remainder of the analytic process. Two investigators (CM and MJ) then independently read and coded all data to ensure intercoder reliability. During this process, CM and MJ met every two weeks to compare coding consistency, resolve discrepancies, and discuss preliminary findings. When the coding was complete, all investigators met to explore and develop themes that encompassed related common codes.

The CFIR was used at two stages of the study: (1) developing the interview guide and (2) cross-checking for any potentially important codes that were missing/needed to be explored further. Thus, the investigators maintained an inductive approach grounded in the data. To assure study rigor, we employed investigator triangulation (use of multiple investigators and participants from multiple clinical roles) and reflexivity (ongoing critique and critical reflection of the individual biases of the investigators).³⁰ Coding was performed using Dedoose (version 7.0.23; Los Angeles, California).

RESULTS

A total of 34 community hospitals completed the PIPA project, of which the project leaders of 25 hospitals connected with the facilitators and were approached to participate; 18 (72%) hospitals’ project leaders participated in the study. We analyzed 18 interviews conducted between facilitators and project leaders, which included a total of 32 project leaders (one to five leaders per interview). The hospitals represented were diverse in geographic location and size (range 4-50 pediatric beds per hospital), and the majority of sites (78%) supported the trainees (Table 1).

We identified four overarching themes that described the key determinants of pathway implementation in community hospitals. These themes are presented in order of their frequency of occurrence in the data. They included (1) building an implementation infrastructure, (2) engaging and motivating providers, (3) addressing organizational and resource limitations, and (4) devising implementation solutions with facilitators. Descriptions and exemplary quotations for each theme are provided in Table 2 and Appendix Figure 1.

 

Building an Implementation Infrastructure

Participants described the importance of building an implementation infrastructure as a critical first step. Establishing an infrastructure required multiple efforts, including forming a team of local champions, delivering didactic education and skills training, and modifying clinical workflows. The multidisciplinary “team of champions” facilitated the division of practical tasks (eg, data entry, Institutional Review Board [IRB] application) and planned educational interventions and setting specific goals, without overloading any given individual. Building an implementation infrastructure “on-the-ground” required thoughtful consideration of local context and engagement of frontline hospital staff commonly involved in the care of children with asthma.

“So, I’m going to sit down with the primary nursing staff and the other four physicians in the group to go over the expectations…We’re not going to have the actual EMR [changes] and we’re not going to have the nursing documentation field built right away but [we want to] make sure that people are documenting the respiratory score in their generic nursing note so that the information is easily accessible.” (Physician leader, Hospital G)

Participants also described the need to deliver education on the evidence supporting changes in practice and skills training specific to pediatric asthma care:

“Once we realized that we were going to be doing this pathway, we started training our nurses on the inpatient side on [pediatric respiratory scoring].” (Nursing leader, Hospital P)

In addition, pathway implementation required modification of clinical workflows via changes to hospital policies or guidelines, electronic medical records (EMR), and/or the physical environment (eg, placing supplies in proximity to care delivery):

“I think it can help if we could get an order set or a nursing protocol where asthmatics over a certain severity can just get steroids in triage.” (Physician leader, Hospital A)

Engaging and Motivating Providers

Another crucial step in pathway implementation was engaging and motivating providers. This included overcoming inertia to practice change, facilitating multidisciplinary collaboration, and handling conflicts regarding practice changes. Participants discussed the excitement of participating in a national collaborative as especially motivating to help drive engagement and overcome barriers to change, particularly the ability to compare local hospital performance to national peers.

“I think everyone is a little competitive. So I think that when we see how we compare to other institutions—both our group and the ER—I think it also adds a little oomph…I think for our nurses too; we’re able to say, ‘[look how we compare to] most of the other hospitals.’ I think that helps.” (Physician leader, Hospital B)

Multidisciplinary collaboration across a wide variety of frontline pediatric and nonpediatric providers was key to understanding current workflows and identifying needed modifications for pathway implementation:

“I do think clearly our biggest obstacles are the fact that we have adult ED providers. We have the opportunity on the inpatient side [with nursing and respiratory therapy], who really do awesome with pediatric changes, to take our wins where we can and make the changes with the ED. In the ED we have an RN educator. She’s very on board with doing the respiratory scoring and getting this whole thing started.” (Physician leader, Hospital L)

 

Intentional communication and leadership skills also played key roles in engaging hesitant providers and handling conflict:

“Just sitting and talking with our respiratory therapist about the ability to provide this type of service or support and seeing what their reservations have been, at least it’s open to conversation so that we could provide these types of therapies in the future and we’re able to see like what people’s concerns are. I think just basically increasing familiarity with not only these processes, but different types of therapy will hopefully in the future help us provide better care to our patients.” (Physician leader, Hospital Q)

Addressing Organizational and Resource Limitations

Participants recognized organizational and resource limitations, some of which may be unique to community hospitals that prioritize resources for adult care. The limitations described included EMR staff support, healthcare provider staffing/capacity, navigating IRBs, and addressing administrative processes. Competing demands for information technology staff support and lack of prioritization of pediatric-specific initiatives often hindered efforts to modify the EMR.

“Resource wise, we are hoping to implement an order set in our Epic EMR, [but] finding the availability from the Epic team may be a challenge.” (Physician Leader, Hospital A)

Participants also reported that limited staff capacity (eg, nursing, RT) hindered pathway implementation efforts. This limited capacity hindered workflow changes and limited the time available for education and training on pathways:

“[Respiratory scoring for asthma is] an added responsibility for the [nursing] staff and we don’t have patient technicians. So they’re doing everything from changing the sheets to bringing water to all of the medical patients. So, that I think may be a barrier.” (Physician leader, Hospital B)

Across sites, navigating the IRB posed various challenges. Some sites were required to obtain approval from regional IRBs, which did not have resources to devote to pediatric projects. Other sites did not have IRBs at all, but instead required separate approvals for the project from hospital leadership or other entities:

“On the IRB, I contacted the manager of the IRB and she’s said, ‘No, it’s not an IRB project,’ but she sent it to another director for review, and it took forever to be able to get a data agreement with [the local university hospital] so that we can pull the data. I just couldn’t believe it took months to get done.” (Physician Leader, Hospital K)

Finally, administrative barriers such as addressing formulary changes in the context of adult-focused settings were challenging. For example, at one hospital, metered dose inhalers (MDIs) were not used for adult patients, and the hospital administration was resistant to incorporate their use into practice for pediatric patients due to the cost of such changes.

“The [general hospital] didn’t have MDI’s anymore because of cost reasons, and when we started the pediatric work, we really made it a point to get the MDI’s for pediatric patients back in the formulary.” (Physician leader, Hospital A)

Devising Implementation Solutions with Practice Facilitators

 

Participants often devised pathway implementation solutions with facilitators in-the-moment during meetings. This problem-solving included figuring out work-arounds, proactive coaching by external facilitators, and just-in-time solution building. Furthermore, in meetings that included more than one project leader, leaders would often work with each other to devise solutions. Meetings provided forums that stimulated identification of implementation barriers, brainstorming, and subsequently solution building.

Physician leader: I’m wondering if we could, as an interim solution, try out an algorithm on paper, I don’t know if that’s allowed, until we get Epic approval. Do you know?

Nurse Leader: You mean having an algorithm posted in triage? Yeah, I don’t see why not. (Hospital A)

Next, problem solving was often driven by the facilitator’s experience and knowledge, drawn from their interactions with other collaborative sites or their own prior experiences with asthma, QI, or pathway implementation. The facilitators brought an outside perspective, not bound by that particular hospital’s local culture or structural intricacies. This proactive coaching spurred the identification of creative, yet practical solutions:

Project Leader: We’re still trying to get all our templates [for the EMR]…because [currently they are] all adult templates.

Facilitator: If you’re making templates right now, could you also add the three asterisks? Like smoking or exposure to second hand tobacco smoke or marijuana…then have the three asterisks there and then “Referral made?***”. That would force people to document in a certain place in the template as well.Project Leader: That’s definitely something we could add right now. (Hospital O)

Check-in meetings with facilitators offered an opportunity to trouble shoot, brainstorm work-arounds, devise in-the-moment site-specific solutions to enable successful pathway implementation, and provide ongoing support throughout implementation.

DISCUSSION

Pathways can improve the quality of care for children with asthma.³¹ However, there is little evidence-based guidance on how to implement pathways and improve pediatric care in community hospitals,^17-20 where the majority of children are cared for nationally. This is the first study to our knowledge that details the key determinants of pediatric asthma pathway implementation in community hospital settings. We identified four key determinants of implementation that can help guide others in similar settings. These include building an implementation infrastructure, engaging and motivating multidisciplinary providers, addressing organizational and resource limitations, and using external facilitators to devise implementation solutions.

Existing frameworks such as the CFIR outline the potential determinants of implementation success but do not provide population- or setting-specific guidance.²⁷ There have been prior studies detailing pathway implementation for pediatric populations, but these studies did not focus on community hospitals.^32,33 Our findings align with these prior studies, which highlight the importance of identifying implementation champions, engaging and motivating multidisciplinary providers, establishing a QI infrastructure, and addressing organizational and resource limitations, such as EMR integration.^32,33 However, our study provides unique insights into issues that are important to successful pathway implementation in community hospitals, including engagement of adult-focused healthcare providers, reprioritization of resources toward the care of children, and the potentially critical role of external facilitators.

Our findings indicate that community hospitals seeking to improve care for children may particularly benefit from using external facilitators and/or partnering with external organizations. We found that external facilitators played a significant and proactive role in community hospitals’ efforts to improve care for children. Facilitators helped devise work-arounds and engaged in just-in-time solution building with local project leaders. For instance, facilitators helped develop strategies for training healthcare providers in performing new clinical tasks, building reminders of pathway recommendations into clinical workflows, and overcoming resource barriers. Thus, community hospitals may uniquely benefit from participation in national learning collaboratives, which often provide avenues for external facilitation.^25,34,35 National networks, such as the VIP network, lead national learning collaboratives that provide external facilitation as well as other resources (eg, educational materials, data analysis support) to community hospitals seeking to improve pediatric care.²⁴ Previous work by McDaniel et al. identified that intentional partnerships between children’s and community hospitals can also potentially provide access to resources for education and training in pediatric care and support in navigating organizational and resource challenges.²²

Our results characterize the key determinants of pediatric asthma pathway implementation using a national sample of community hospitals that were diverse in geography, size, and structure. This imparts greater transferability of our findings. We also used strategies to promote the rigor of our findings, including triangulation and reflexivity. However, our study has several limitations. First, we analyzed only the meetings that occurred during the early months of pathway implementation. As such, we did not capture any key determinants that may have arisen later in implementation. However, process analyses of implementation indicate that the majority of implementation efforts occurred within these first three to four months.³⁶ Second, we did not elicit input from hospital administration or leadership. The lack of administrative/leadership input probably affected the CFIR themes we found, as no themes from the outer setting were elicited. However, the goal of our study was to characterize the experiences of those leading implementation efforts, and focusing on these leaders allows our work to better guide those doing similar work in the future. Third, we used CFIR to guide the development of our interview guide and as a reference during analysis, which may have skewed our findings to preferentially reflect CFIR constructs. However, our overall analysis was grounded in the primary data and we employed reflexivity during all stages of our analysis. In addition, having the facilitators conduct the qualitative interviews may have biased our findings toward the perspectives of the facilitators; however, the facilitators represented quite diverse clinical and QI backgrounds. Finally, our findings do not necessarily correlate with improvements in clinical outcomes. As such, they are not meant to serve as explicit recommendations for improving patient outcomes, but rather as a characterization of the context, processes, and experiences of implementing pathways in the community setting to inform others doing this important work.

 

CONCLUSIONS

We identified the key determinants of pediatric asthma pathway implementation in community hospitals, which may help inform QI efforts in these settings. We also identified organizational and resource limitations that are probably unique to these adult-focused hospitals. Participating in national learning collaboratives and/or working with facilitators may support pathway implementation and improved quality of care for children with asthma in community hospitals.

Future work should seek to correlate these and other determinants of pathway implementation with health outcomes for hospitalized children, as well as integrate broader and more diverse samples of community hospitals.

Despite the widespread availability of evidence-based guidelines,¹ there is inappropriate variation in the care and outcomes for children with asthma in both the emergency department (ED) and the inpatient setting.^2-6 Operational versions of evidence-based guidelines known as “pathways” have been shown to improve adoption of evidence-based guidelines, quality of care, and health outcomes for children with asthma.^7-14 However, little is known about how to successfully implement pathways outside of free-standing children’s hospitals.^15-19

The majority of children with asthma in the United States are cared for in community hospitals, which provide services for both adults and children.²⁰ However, prior studies of pediatric asthma pathways have largely excluded community hospitals. These studies primarily focused on determining clinical effectiveness, rather than detailing the implementation process. These approaches have left critical gaps that hinder our ability to implement pathways and improve care in community hospitals, which have unique barriers and less resources.^21,22 Therefore, understanding the process of pathway implementation in community hospitals is critical to improving care for children.²² Our objective was to identify the key determinants of successful pediatric asthma pathway implementation using a national sample of community hospitals. This knowledge can guide hospital leaders and healthcare providers in efforts to improve pediatric care and outcomes in these settings.

METHODS

Study Setting, Design, and Population

In Fall 2017, the Value in Inpatient Pediatrics (VIP) network launched PIPA, Pathways to Improving Pediatric Asthma care.²³ The VIP network, a part of the American Academy of Pediatrics (AAP), aims to improve the value of care delivered to any pediatric patient in a hospital bed, from rural to free-standing children’s hospitals.²⁴ PIPA used a learning collaborative model²⁵ and recruited local project leaders (physicians, nurses, respiratory therapists (RT), and pharmacists) from 89 hospitals around the country. PIPA provided these hospital teams with asthma pathways and several resources for implementation support, including educational meetings, quality improvement (QI) training, audit and feedback, and facilitation. Facilitation is a process of interactive problem-solving and support that occurs in the context of a supportive interpersonal relationship and a recognized need for improvement.²⁶ A facilitator, or a “coach”, is an external expert who provides project mentorship and assists the process of making meaningful changes to improve patient care.²⁶ Facilitation was provided by external consultants with QI expertise.

For this qualitative study, facilitators conducted semi-structured interviews with a convenience sample of project leaders from community hospitals participating in PIPA, with some interviews including multiple project leaders (eg, nursing, inpatient, and Emergency Department [ED] leaders). Verbal consent was obtained from all participants. No incentives were provided. This study was approved by the AAP institutional review board.

 

Data Collection

We used the constructs described in the Consolidated Framework for Implementation Research (CFIR)²⁷ and adapted those salient to pediatric asthma pathways to develop an interview guide that was used with all participants (Appendix 1). The CFIR offers an overarching typology to understand what works where and why across five major domains that influence implementation: intervention characteristics, inner setting (hospital), outer setting (economic, political, and social context of the hospital), characteristics of the individuals involved, and the process of implementation. Data were collected across these domains to inform our analysis of the key determinants of pediatric asthma pathway implementation in community hospitals.

Interviews were conducted by phone from December 2017 to April 2018 (first four months of pathway implementation). Interviews lasted 30-60 minutes and were recorded and transcribed verbatim. Transcripts were edited for accuracy using the audio recordings. As data collection occurred concurrently with analysis, the interview guide was iteratively revised to reflect new insights and patterns that emerged from our analysis. All sites were anonymized in the data analysis. New interviews were coded until thematic saturation was reached.

Analysis

We conducted an inductive thematic analysis using the CFIR as our conceptual framework.^28,29 Four investigators (CM, MJ, ES, and SK) performed the initial open coding of the data. Investigators met twice during the open coding process to develop and then finalize a codebook of standard definitions for codes. This codebook facilitated coding consistency through the remainder of the analytic process. Two investigators (CM and MJ) then independently read and coded all data to ensure intercoder reliability. During this process, CM and MJ met every two weeks to compare coding consistency, resolve discrepancies, and discuss preliminary findings. When the coding was complete, all investigators met to explore and develop themes that encompassed related common codes.

The CFIR was used at two stages of the study: (1) developing the interview guide and (2) cross-checking for any potentially important codes that were missing/needed to be explored further. Thus, the investigators maintained an inductive approach grounded in the data. To assure study rigor, we employed investigator triangulation (use of multiple investigators and participants from multiple clinical roles) and reflexivity (ongoing critique and critical reflection of the individual biases of the investigators).³⁰ Coding was performed using Dedoose (version 7.0.23; Los Angeles, California).

RESULTS

A total of 34 community hospitals completed the PIPA project, of which the project leaders of 25 hospitals connected with the facilitators and were approached to participate; 18 (72%) hospitals’ project leaders participated in the study. We analyzed 18 interviews conducted between facilitators and project leaders, which included a total of 32 project leaders (one to five leaders per interview). The hospitals represented were diverse in geographic location and size (range 4-50 pediatric beds per hospital), and the majority of sites (78%) supported the trainees (Table 1).

We identified four overarching themes that described the key determinants of pathway implementation in community hospitals. These themes are presented in order of their frequency of occurrence in the data. They included (1) building an implementation infrastructure, (2) engaging and motivating providers, (3) addressing organizational and resource limitations, and (4) devising implementation solutions with facilitators. Descriptions and exemplary quotations for each theme are provided in Table 2 and Appendix Figure 1.

 

Building an Implementation Infrastructure

Participants described the importance of building an implementation infrastructure as a critical first step. Establishing an infrastructure required multiple efforts, including forming a team of local champions, delivering didactic education and skills training, and modifying clinical workflows. The multidisciplinary “team of champions” facilitated the division of practical tasks (eg, data entry, Institutional Review Board [IRB] application) and planned educational interventions and setting specific goals, without overloading any given individual. Building an implementation infrastructure “on-the-ground” required thoughtful consideration of local context and engagement of frontline hospital staff commonly involved in the care of children with asthma.

“So, I’m going to sit down with the primary nursing staff and the other four physicians in the group to go over the expectations…We’re not going to have the actual EMR [changes] and we’re not going to have the nursing documentation field built right away but [we want to] make sure that people are documenting the respiratory score in their generic nursing note so that the information is easily accessible.” (Physician leader, Hospital G)

Participants also described the need to deliver education on the evidence supporting changes in practice and skills training specific to pediatric asthma care:

“Once we realized that we were going to be doing this pathway, we started training our nurses on the inpatient side on [pediatric respiratory scoring].” (Nursing leader, Hospital P)

In addition, pathway implementation required modification of clinical workflows via changes to hospital policies or guidelines, electronic medical records (EMR), and/or the physical environment (eg, placing supplies in proximity to care delivery):

“I think it can help if we could get an order set or a nursing protocol where asthmatics over a certain severity can just get steroids in triage.” (Physician leader, Hospital A)

Engaging and Motivating Providers

Another crucial step in pathway implementation was engaging and motivating providers. This included overcoming inertia to practice change, facilitating multidisciplinary collaboration, and handling conflicts regarding practice changes. Participants discussed the excitement of participating in a national collaborative as especially motivating to help drive engagement and overcome barriers to change, particularly the ability to compare local hospital performance to national peers.

“I think everyone is a little competitive. So I think that when we see how we compare to other institutions—both our group and the ER—I think it also adds a little oomph…I think for our nurses too; we’re able to say, ‘[look how we compare to] most of the other hospitals.’ I think that helps.” (Physician leader, Hospital B)

Multidisciplinary collaboration across a wide variety of frontline pediatric and nonpediatric providers was key to understanding current workflows and identifying needed modifications for pathway implementation:

“I do think clearly our biggest obstacles are the fact that we have adult ED providers. We have the opportunity on the inpatient side [with nursing and respiratory therapy], who really do awesome with pediatric changes, to take our wins where we can and make the changes with the ED. In the ED we have an RN educator. She’s very on board with doing the respiratory scoring and getting this whole thing started.” (Physician leader, Hospital L)

 

Intentional communication and leadership skills also played key roles in engaging hesitant providers and handling conflict:

“Just sitting and talking with our respiratory therapist about the ability to provide this type of service or support and seeing what their reservations have been, at least it’s open to conversation so that we could provide these types of therapies in the future and we’re able to see like what people’s concerns are. I think just basically increasing familiarity with not only these processes, but different types of therapy will hopefully in the future help us provide better care to our patients.” (Physician leader, Hospital Q)

Addressing Organizational and Resource Limitations

Participants recognized organizational and resource limitations, some of which may be unique to community hospitals that prioritize resources for adult care. The limitations described included EMR staff support, healthcare provider staffing/capacity, navigating IRBs, and addressing administrative processes. Competing demands for information technology staff support and lack of prioritization of pediatric-specific initiatives often hindered efforts to modify the EMR.

“Resource wise, we are hoping to implement an order set in our Epic EMR, [but] finding the availability from the Epic team may be a challenge.” (Physician Leader, Hospital A)

Participants also reported that limited staff capacity (eg, nursing, RT) hindered pathway implementation efforts. This limited capacity hindered workflow changes and limited the time available for education and training on pathways:

“[Respiratory scoring for asthma is] an added responsibility for the [nursing] staff and we don’t have patient technicians. So they’re doing everything from changing the sheets to bringing water to all of the medical patients. So, that I think may be a barrier.” (Physician leader, Hospital B)

Across sites, navigating the IRB posed various challenges. Some sites were required to obtain approval from regional IRBs, which did not have resources to devote to pediatric projects. Other sites did not have IRBs at all, but instead required separate approvals for the project from hospital leadership or other entities:

“On the IRB, I contacted the manager of the IRB and she’s said, ‘No, it’s not an IRB project,’ but she sent it to another director for review, and it took forever to be able to get a data agreement with [the local university hospital] so that we can pull the data. I just couldn’t believe it took months to get done.” (Physician Leader, Hospital K)

Finally, administrative barriers such as addressing formulary changes in the context of adult-focused settings were challenging. For example, at one hospital, metered dose inhalers (MDIs) were not used for adult patients, and the hospital administration was resistant to incorporate their use into practice for pediatric patients due to the cost of such changes.

“The [general hospital] didn’t have MDI’s anymore because of cost reasons, and when we started the pediatric work, we really made it a point to get the MDI’s for pediatric patients back in the formulary.” (Physician leader, Hospital A)

Devising Implementation Solutions with Practice Facilitators

 

Participants often devised pathway implementation solutions with facilitators in-the-moment during meetings. This problem-solving included figuring out work-arounds, proactive coaching by external facilitators, and just-in-time solution building. Furthermore, in meetings that included more than one project leader, leaders would often work with each other to devise solutions. Meetings provided forums that stimulated identification of implementation barriers, brainstorming, and subsequently solution building.

Physician leader: I’m wondering if we could, as an interim solution, try out an algorithm on paper, I don’t know if that’s allowed, until we get Epic approval. Do you know?

Nurse Leader: You mean having an algorithm posted in triage? Yeah, I don’t see why not. (Hospital A)

Next, problem solving was often driven by the facilitator’s experience and knowledge, drawn from their interactions with other collaborative sites or their own prior experiences with asthma, QI, or pathway implementation. The facilitators brought an outside perspective, not bound by that particular hospital’s local culture or structural intricacies. This proactive coaching spurred the identification of creative, yet practical solutions:

Project Leader: We’re still trying to get all our templates [for the EMR]…because [currently they are] all adult templates.

Facilitator: If you’re making templates right now, could you also add the three asterisks? Like smoking or exposure to second hand tobacco smoke or marijuana…then have the three asterisks there and then “Referral made?***”. That would force people to document in a certain place in the template as well.Project Leader: That’s definitely something we could add right now. (Hospital O)

Check-in meetings with facilitators offered an opportunity to trouble shoot, brainstorm work-arounds, devise in-the-moment site-specific solutions to enable successful pathway implementation, and provide ongoing support throughout implementation.

DISCUSSION

Pathways can improve the quality of care for children with asthma.³¹ However, there is little evidence-based guidance on how to implement pathways and improve pediatric care in community hospitals,^17-20 where the majority of children are cared for nationally. This is the first study to our knowledge that details the key determinants of pediatric asthma pathway implementation in community hospital settings. We identified four key determinants of implementation that can help guide others in similar settings. These include building an implementation infrastructure, engaging and motivating multidisciplinary providers, addressing organizational and resource limitations, and using external facilitators to devise implementation solutions.

Existing frameworks such as the CFIR outline the potential determinants of implementation success but do not provide population- or setting-specific guidance.²⁷ There have been prior studies detailing pathway implementation for pediatric populations, but these studies did not focus on community hospitals.^32,33 Our findings align with these prior studies, which highlight the importance of identifying implementation champions, engaging and motivating multidisciplinary providers, establishing a QI infrastructure, and addressing organizational and resource limitations, such as EMR integration.^32,33 However, our study provides unique insights into issues that are important to successful pathway implementation in community hospitals, including engagement of adult-focused healthcare providers, reprioritization of resources toward the care of children, and the potentially critical role of external facilitators.

Our findings indicate that community hospitals seeking to improve care for children may particularly benefit from using external facilitators and/or partnering with external organizations. We found that external facilitators played a significant and proactive role in community hospitals’ efforts to improve care for children. Facilitators helped devise work-arounds and engaged in just-in-time solution building with local project leaders. For instance, facilitators helped develop strategies for training healthcare providers in performing new clinical tasks, building reminders of pathway recommendations into clinical workflows, and overcoming resource barriers. Thus, community hospitals may uniquely benefit from participation in national learning collaboratives, which often provide avenues for external facilitation.^25,34,35 National networks, such as the VIP network, lead national learning collaboratives that provide external facilitation as well as other resources (eg, educational materials, data analysis support) to community hospitals seeking to improve pediatric care.²⁴ Previous work by McDaniel et al. identified that intentional partnerships between children’s and community hospitals can also potentially provide access to resources for education and training in pediatric care and support in navigating organizational and resource challenges.²²

Our results characterize the key determinants of pediatric asthma pathway implementation using a national sample of community hospitals that were diverse in geography, size, and structure. This imparts greater transferability of our findings. We also used strategies to promote the rigor of our findings, including triangulation and reflexivity. However, our study has several limitations. First, we analyzed only the meetings that occurred during the early months of pathway implementation. As such, we did not capture any key determinants that may have arisen later in implementation. However, process analyses of implementation indicate that the majority of implementation efforts occurred within these first three to four months.³⁶ Second, we did not elicit input from hospital administration or leadership. The lack of administrative/leadership input probably affected the CFIR themes we found, as no themes from the outer setting were elicited. However, the goal of our study was to characterize the experiences of those leading implementation efforts, and focusing on these leaders allows our work to better guide those doing similar work in the future. Third, we used CFIR to guide the development of our interview guide and as a reference during analysis, which may have skewed our findings to preferentially reflect CFIR constructs. However, our overall analysis was grounded in the primary data and we employed reflexivity during all stages of our analysis. In addition, having the facilitators conduct the qualitative interviews may have biased our findings toward the perspectives of the facilitators; however, the facilitators represented quite diverse clinical and QI backgrounds. Finally, our findings do not necessarily correlate with improvements in clinical outcomes. As such, they are not meant to serve as explicit recommendations for improving patient outcomes, but rather as a characterization of the context, processes, and experiences of implementing pathways in the community setting to inform others doing this important work.

 

CONCLUSIONS

We identified the key determinants of pediatric asthma pathway implementation in community hospitals, which may help inform QI efforts in these settings. We also identified organizational and resource limitations that are probably unique to these adult-focused hospitals. Participating in national learning collaboratives and/or working with facilitators may support pathway implementation and improved quality of care for children with asthma in community hospitals.

Future work should seek to correlate these and other determinants of pathway implementation with health outcomes for hospitalized children, as well as integrate broader and more diverse samples of community hospitals.

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.

METHODS

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.

RESULTS

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

Twenty-six (37%) site directors described their program as unsustainable. When programmatic characteristics and clinical work expectations were analyzed by perception of sustainability, we observed no difference between programs that were perceived as unsustainable in the number of 1.0 FTE hours/year (P = .16), weekends/year (P = .65), in-house call (P = .36), or the presence of a back-up system (P = .61).

 

DISCUSSION

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.

 

CONCLUSION

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.

METHODS

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.

RESULTS

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

Twenty-six (37%) site directors described their program as unsustainable. When programmatic characteristics and clinical work expectations were analyzed by perception of sustainability, we observed no difference between programs that were perceived as unsustainable in the number of 1.0 FTE hours/year (P = .16), weekends/year (P = .65), in-house call (P = .36), or the presence of a back-up system (P = .61).

 

DISCUSSION

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.

 

CONCLUSION

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.

METHODS

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.

RESULTS

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

Twenty-six (37%) site directors described their program as unsustainable. When programmatic characteristics and clinical work expectations were analyzed by perception of sustainability, we observed no difference between programs that were perceived as unsustainable in the number of 1.0 FTE hours/year (P = .16), weekends/year (P = .65), in-house call (P = .36), or the presence of a back-up system (P = .61).

 

DISCUSSION

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.

 

CONCLUSION

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.