Glenn Rosenbluth, MD

CHANGING CIRCUMSTANCES OF CARE

CORE VALUES DURING COVID-19

CONCLUSION

Disclosures

Disclaimer

CHANGING CIRCUMSTANCES OF CARE

CORE VALUES DURING COVID-19

CONCLUSION

Disclosures

Disclaimer

CHANGING CIRCUMSTANCES OF CARE

CORE VALUES DURING COVID-19

CONCLUSION

Disclosures

Disclaimer

Duty‐hour restrictions were implemented by the Accreditation Council for Graduate Medical Education (ACGME) in 2003 in response to data showing that sleep deprivation was correlated with serious medical errors.[1] In 2011, the ACGME required more explicit restrictions in the number of hours worked and the maximal shift length.[2] These requirements have necessitated a transition from a traditional q4 call model for interns to one in which shifts are limited to a maximum of 16 hours.

Studies of interns working these shorter shifts have had varied results, and comprehensive reviews have failed to demonstrate consistent improvements.[3, 4, 5] Studies of shift‐length limitation initially suggested improvements in patient safety (decreased length of stay,[6, 7] cost of hospitalization,[6] medication errors,[7] serious medical errors,[8] and intensive care unit [ICU] admissions[9]) and resident quality of life.[10] However, other recent studies have reported an increased number of self‐reported medical errors[11] and either did not detect change[12] or reported perceived decreases[13] in quality of care and continuity of care.

We previously reported decreased length of stay and decreased cost of hospitalization in pediatric inpatients cared for in a day/night‐shiftbased care model.[6] An hypothesized reason for those care improvements is the restructured care model led to increased active clinical management during both day and night hours. Here we report the findings of a retrospective analysis to investigate this hypothesis.

PATIENTS AND METHODS

Intervention

During the preintervention period, patients were cared for by interns who took call every sixth night (duty periods up to 30 hours), with cross‐coverage of patients on multiple teams. Cross‐coverage was defined as coverage of patients cared for during nonconsecutive shifts and for whom residents did not participate in attending rounds. Noncall shifts were typically 10 to 11 hours. They were supervised by senior residents who took call every fourth or fifth night and who provided similar cross‐coverage.

During the postintervention period, interns worked day and night shifts of 13 hours (1 hour overlap time between shifts for handoffs), with increased night staffing to eliminate intern‐level cross‐coverage of multiple teams and maintain interns as the primary providers. Interns covered the same team for 5 to 7 consecutive days on either the day or night shifts. Interns remained on the same teams when they switched from day shifts to night shifts to preserve continuity. There were some 24‐hour shifts for senior residents on weekends. Senior residents maintained supervisory responsibility for all patients (both hospitalist teams and a subspecialty team). They also worked 7 consecutive nights.

There were changes in the staffing ratios associated with the change to day and night teams (Table 1, Figure 1). In the preintervention period, general pediatrics patients were covered by a single hospitalist and cohorted on a single team (team A), which also covered several groups of subspecialty patients with subspecialty attendings. The team consisted of 2 interns and 1 senior resident, who shared extended (30‐hour) call in a cycle with 2 other inpatient teams. In the postintervention period, general pediatrics patients were split between 2 teams (teams D and E) and mixed with subspecialty patients. Hospitalist continued to be the attendings, and these hospitalists also covered specialty patients with subspecialists in consulting roles. The teams consisted of 3 interns on the day shift, and 1 on the night shift. There was 1 senior resident per team on day shift, and a single senior resident covering all teams at night.

Table 1.Team Composition Before and After Intervention

	Preintervention			Postintervention
a Refers to only to general pediatrics patient coverage Teams A, D, and E. NOTE: Abbreviations: GI, gastrointestinal. *Refers to only to general pediatrics patient coverageteams A, D, and E.
General Pediatrics	Team A	Team B	Team C	Team D	Team E	Team F
Patient Distribution	General Pediatrics	GI/Liver	Renal	General Pediatrics	General Pediatrics	Liver
	Pulmonary	Neurology	Rheumatology	Mixed Specialty	Mixed Specialty	Renal
		Adolescent	Endocrine
Team membersa	2 interns (q6 call)			4 interns (3 on day shift/1 on night shift)
	1 senior resident (q5 call)			1 senior resident
Night‐shift coveragea	1 intern and 1 senior resident together covered all 3 teams.			1 night intern per team (teams D/E) working 7 consecutive night shifts
				1 supervising night resident covering all 3 teams
Intern cross‐coverage of other teams	Nights/clinic afternoons			None
Length of night shift	30 hours			13 hours

Figure 1

There was no change in the paper‐order system, the electronic health record, timing of the morning blood draw, use of new facilities for patient care, or protocol for emergency department admission. Concomitant with the restructuring, most subspecialty patients were consolidated onto the hospitalist service, necessitating creation of a second hospitalist team. However, patients admitted with the diagnoses identified above would have been on the hospitalist service before and after the restructuring.

RESULTS

We analyzed data for 48 admissions preintervention and 50 postintervention. With the exception of insurance type, there was no difference in baseline demographics, diagnoses, or severity of illness between the groups (Table 2). Within the order classes above, we identified 212 orders preintervention and 231 orders postintervention.

After the intervention, there was a statistically significant increase in the average number of orders written within the first 12 hours (pre: 0.58 orders vs post: 1.12, P = 0.009) and 24 hours (pre: 1.52 vs post: 2.38, P = 0.004) following admission (Table 3), not including the admission order set. The fraction of orders written at night was not significantly different (27% at night preintervention, 33% postintervention, P = 0.149). The fraction of admissions on the day shift compared to the night shift did not change (P = 0.72). There was no difference in the ratio of de‐escalation to escalation orders written during the night (Table 2).

DISCUSSION

In this study, we demonstrate increased patient care management early in the hospitalization, measured in this study by the mean number of orders written per patient in the first 12 and 24 hours after admission, after transition from a call schedule with extended (>16 hours) shifts to one with shorter shifts compliant with current ACGME duty‐hour restrictions and an explicit focus on greater continuity of care. We did not detect a change in the proportion of total orders written on the night shift compared to the day shift. Earlier active medical management, such as weaning nebulized albuterol or supplemental oxygen, can speed the time to discharge.[14]

Our failure to detect a significant change in the proportion or type of orders written at night may have been due to our small sample size. Anecdotally, after the intervention, medical students reported to us that they noticed a difference between our service, in which we expect night teams to advance care, and other services at our institution, in which nights are a time to focus on putting out fires. This was not something that had been reported to us prior. It is likely reflective of the overall approach to patient care taken by residents working a night shift as part of a longitudinal care team.

This study builds on previous findings that demonstrated lower costs and shorter length of stay after implementing a schedule based on day and night teams.[7] The reasons for such improvements are likely multifactorial. In our model, which was purposefully designed to create night‐team continuity and minimize cross‐coverage, it is likely that residents also felt a greater sense of responsibility for and familiarity with the patients[15] and therefore felt more comfortable advancing care. Not only were interns likely better rested, the patient‐to‐provider ratio was also lower than in the preintervention model. Increases in staffing are often necessary to eliminate cross‐coverage while maintaining safe, 24‐hour care. These findings suggest that increases in cost from additional staffing may be at least partially offset by more active patient management early in the hospitalization, which has the potential to lead to shorter hospital stays.

There are several limitations to our research. We studied a small sample, including a subset of general pediatrics diagnoses that are amenable to active management, limiting generalizability. We did not calculate a physician‐to‐patient ratio because this was not possible with the retrospective data we collected. Staffing ratios likely improved, and we consider that part of the overall improvements in staffing that may have contributed to the observed changes in ordering patterns. Although intern‐level cross‐coverage was eliminated, the senior resident continued to cover multiple teams overnight. This senior covered the same 3 teams for 7 consecutive nights. The addition of a hospitalist team, with subspecialists being placed in consultant roles, may have contributed to the increase in active management, though our study population did not include subspecialty patients. There was a difference in insurance status between the 2 groups. This was unlikely to affect resident physician practices as insurance information is not routinely discussed in the course of patient care. In the context of the ongoing debate about duty‐hour restrictions, it will be important for future studies to elucidate whether sleep or other variables are the primary contributors to this finding. Our data are derived solely from 1 inpatient service at a single academic medical center; however, we do feel there are lessons that may be applied to other settings.

CONCLUSION

A coverage system with improved nighttime resident coverage was associated with a greater number of orders written early in the hospitalization, suggesting more active management of clinical problems to advance care.

Duty‐hour restrictions were implemented by the Accreditation Council for Graduate Medical Education (ACGME) in 2003 in response to data showing that sleep deprivation was correlated with serious medical errors.[1] In 2011, the ACGME required more explicit restrictions in the number of hours worked and the maximal shift length.[2] These requirements have necessitated a transition from a traditional q4 call model for interns to one in which shifts are limited to a maximum of 16 hours.

Studies of interns working these shorter shifts have had varied results, and comprehensive reviews have failed to demonstrate consistent improvements.[3, 4, 5] Studies of shift‐length limitation initially suggested improvements in patient safety (decreased length of stay,[6, 7] cost of hospitalization,[6] medication errors,[7] serious medical errors,[8] and intensive care unit [ICU] admissions[9]) and resident quality of life.[10] However, other recent studies have reported an increased number of self‐reported medical errors[11] and either did not detect change[12] or reported perceived decreases[13] in quality of care and continuity of care.

We previously reported decreased length of stay and decreased cost of hospitalization in pediatric inpatients cared for in a day/night‐shiftbased care model.[6] An hypothesized reason for those care improvements is the restructured care model led to increased active clinical management during both day and night hours. Here we report the findings of a retrospective analysis to investigate this hypothesis.

PATIENTS AND METHODS

Intervention

During the preintervention period, patients were cared for by interns who took call every sixth night (duty periods up to 30 hours), with cross‐coverage of patients on multiple teams. Cross‐coverage was defined as coverage of patients cared for during nonconsecutive shifts and for whom residents did not participate in attending rounds. Noncall shifts were typically 10 to 11 hours. They were supervised by senior residents who took call every fourth or fifth night and who provided similar cross‐coverage.

During the postintervention period, interns worked day and night shifts of 13 hours (1 hour overlap time between shifts for handoffs), with increased night staffing to eliminate intern‐level cross‐coverage of multiple teams and maintain interns as the primary providers. Interns covered the same team for 5 to 7 consecutive days on either the day or night shifts. Interns remained on the same teams when they switched from day shifts to night shifts to preserve continuity. There were some 24‐hour shifts for senior residents on weekends. Senior residents maintained supervisory responsibility for all patients (both hospitalist teams and a subspecialty team). They also worked 7 consecutive nights.

There were changes in the staffing ratios associated with the change to day and night teams (Table 1, Figure 1). In the preintervention period, general pediatrics patients were covered by a single hospitalist and cohorted on a single team (team A), which also covered several groups of subspecialty patients with subspecialty attendings. The team consisted of 2 interns and 1 senior resident, who shared extended (30‐hour) call in a cycle with 2 other inpatient teams. In the postintervention period, general pediatrics patients were split between 2 teams (teams D and E) and mixed with subspecialty patients. Hospitalist continued to be the attendings, and these hospitalists also covered specialty patients with subspecialists in consulting roles. The teams consisted of 3 interns on the day shift, and 1 on the night shift. There was 1 senior resident per team on day shift, and a single senior resident covering all teams at night.

Table 1.Team Composition Before and After Intervention

	Preintervention			Postintervention
a Refers to only to general pediatrics patient coverage Teams A, D, and E. NOTE: Abbreviations: GI, gastrointestinal. *Refers to only to general pediatrics patient coverageteams A, D, and E.
General Pediatrics	Team A	Team B	Team C	Team D	Team E	Team F
Patient Distribution	General Pediatrics	GI/Liver	Renal	General Pediatrics	General Pediatrics	Liver
	Pulmonary	Neurology	Rheumatology	Mixed Specialty	Mixed Specialty	Renal
		Adolescent	Endocrine
Team membersa	2 interns (q6 call)			4 interns (3 on day shift/1 on night shift)
	1 senior resident (q5 call)			1 senior resident
Night‐shift coveragea	1 intern and 1 senior resident together covered all 3 teams.			1 night intern per team (teams D/E) working 7 consecutive night shifts
				1 supervising night resident covering all 3 teams
Intern cross‐coverage of other teams	Nights/clinic afternoons			None
Length of night shift	30 hours			13 hours

Figure 1

There was no change in the paper‐order system, the electronic health record, timing of the morning blood draw, use of new facilities for patient care, or protocol for emergency department admission. Concomitant with the restructuring, most subspecialty patients were consolidated onto the hospitalist service, necessitating creation of a second hospitalist team. However, patients admitted with the diagnoses identified above would have been on the hospitalist service before and after the restructuring.

RESULTS

We analyzed data for 48 admissions preintervention and 50 postintervention. With the exception of insurance type, there was no difference in baseline demographics, diagnoses, or severity of illness between the groups (Table 2). Within the order classes above, we identified 212 orders preintervention and 231 orders postintervention.

After the intervention, there was a statistically significant increase in the average number of orders written within the first 12 hours (pre: 0.58 orders vs post: 1.12, P = 0.009) and 24 hours (pre: 1.52 vs post: 2.38, P = 0.004) following admission (Table 3), not including the admission order set. The fraction of orders written at night was not significantly different (27% at night preintervention, 33% postintervention, P = 0.149). The fraction of admissions on the day shift compared to the night shift did not change (P = 0.72). There was no difference in the ratio of de‐escalation to escalation orders written during the night (Table 2).

DISCUSSION

In this study, we demonstrate increased patient care management early in the hospitalization, measured in this study by the mean number of orders written per patient in the first 12 and 24 hours after admission, after transition from a call schedule with extended (>16 hours) shifts to one with shorter shifts compliant with current ACGME duty‐hour restrictions and an explicit focus on greater continuity of care. We did not detect a change in the proportion of total orders written on the night shift compared to the day shift. Earlier active medical management, such as weaning nebulized albuterol or supplemental oxygen, can speed the time to discharge.[14]

Our failure to detect a significant change in the proportion or type of orders written at night may have been due to our small sample size. Anecdotally, after the intervention, medical students reported to us that they noticed a difference between our service, in which we expect night teams to advance care, and other services at our institution, in which nights are a time to focus on putting out fires. This was not something that had been reported to us prior. It is likely reflective of the overall approach to patient care taken by residents working a night shift as part of a longitudinal care team.

This study builds on previous findings that demonstrated lower costs and shorter length of stay after implementing a schedule based on day and night teams.[7] The reasons for such improvements are likely multifactorial. In our model, which was purposefully designed to create night‐team continuity and minimize cross‐coverage, it is likely that residents also felt a greater sense of responsibility for and familiarity with the patients[15] and therefore felt more comfortable advancing care. Not only were interns likely better rested, the patient‐to‐provider ratio was also lower than in the preintervention model. Increases in staffing are often necessary to eliminate cross‐coverage while maintaining safe, 24‐hour care. These findings suggest that increases in cost from additional staffing may be at least partially offset by more active patient management early in the hospitalization, which has the potential to lead to shorter hospital stays.

There are several limitations to our research. We studied a small sample, including a subset of general pediatrics diagnoses that are amenable to active management, limiting generalizability. We did not calculate a physician‐to‐patient ratio because this was not possible with the retrospective data we collected. Staffing ratios likely improved, and we consider that part of the overall improvements in staffing that may have contributed to the observed changes in ordering patterns. Although intern‐level cross‐coverage was eliminated, the senior resident continued to cover multiple teams overnight. This senior covered the same 3 teams for 7 consecutive nights. The addition of a hospitalist team, with subspecialists being placed in consultant roles, may have contributed to the increase in active management, though our study population did not include subspecialty patients. There was a difference in insurance status between the 2 groups. This was unlikely to affect resident physician practices as insurance information is not routinely discussed in the course of patient care. In the context of the ongoing debate about duty‐hour restrictions, it will be important for future studies to elucidate whether sleep or other variables are the primary contributors to this finding. Our data are derived solely from 1 inpatient service at a single academic medical center; however, we do feel there are lessons that may be applied to other settings.

CONCLUSION

A coverage system with improved nighttime resident coverage was associated with a greater number of orders written early in the hospitalization, suggesting more active management of clinical problems to advance care.

Duty‐hour restrictions were implemented by the Accreditation Council for Graduate Medical Education (ACGME) in 2003 in response to data showing that sleep deprivation was correlated with serious medical errors.[1] In 2011, the ACGME required more explicit restrictions in the number of hours worked and the maximal shift length.[2] These requirements have necessitated a transition from a traditional q4 call model for interns to one in which shifts are limited to a maximum of 16 hours.

Studies of interns working these shorter shifts have had varied results, and comprehensive reviews have failed to demonstrate consistent improvements.[3, 4, 5] Studies of shift‐length limitation initially suggested improvements in patient safety (decreased length of stay,[6, 7] cost of hospitalization,[6] medication errors,[7] serious medical errors,[8] and intensive care unit [ICU] admissions[9]) and resident quality of life.[10] However, other recent studies have reported an increased number of self‐reported medical errors[11] and either did not detect change[12] or reported perceived decreases[13] in quality of care and continuity of care.

We previously reported decreased length of stay and decreased cost of hospitalization in pediatric inpatients cared for in a day/night‐shiftbased care model.[6] An hypothesized reason for those care improvements is the restructured care model led to increased active clinical management during both day and night hours. Here we report the findings of a retrospective analysis to investigate this hypothesis.

PATIENTS AND METHODS

Intervention

During the preintervention period, patients were cared for by interns who took call every sixth night (duty periods up to 30 hours), with cross‐coverage of patients on multiple teams. Cross‐coverage was defined as coverage of patients cared for during nonconsecutive shifts and for whom residents did not participate in attending rounds. Noncall shifts were typically 10 to 11 hours. They were supervised by senior residents who took call every fourth or fifth night and who provided similar cross‐coverage.

During the postintervention period, interns worked day and night shifts of 13 hours (1 hour overlap time between shifts for handoffs), with increased night staffing to eliminate intern‐level cross‐coverage of multiple teams and maintain interns as the primary providers. Interns covered the same team for 5 to 7 consecutive days on either the day or night shifts. Interns remained on the same teams when they switched from day shifts to night shifts to preserve continuity. There were some 24‐hour shifts for senior residents on weekends. Senior residents maintained supervisory responsibility for all patients (both hospitalist teams and a subspecialty team). They also worked 7 consecutive nights.

There were changes in the staffing ratios associated with the change to day and night teams (Table 1, Figure 1). In the preintervention period, general pediatrics patients were covered by a single hospitalist and cohorted on a single team (team A), which also covered several groups of subspecialty patients with subspecialty attendings. The team consisted of 2 interns and 1 senior resident, who shared extended (30‐hour) call in a cycle with 2 other inpatient teams. In the postintervention period, general pediatrics patients were split between 2 teams (teams D and E) and mixed with subspecialty patients. Hospitalist continued to be the attendings, and these hospitalists also covered specialty patients with subspecialists in consulting roles. The teams consisted of 3 interns on the day shift, and 1 on the night shift. There was 1 senior resident per team on day shift, and a single senior resident covering all teams at night.

Table 1.Team Composition Before and After Intervention

	Preintervention			Postintervention
a Refers to only to general pediatrics patient coverage Teams A, D, and E. NOTE: Abbreviations: GI, gastrointestinal. *Refers to only to general pediatrics patient coverageteams A, D, and E.
General Pediatrics	Team A	Team B	Team C	Team D	Team E	Team F
Patient Distribution	General Pediatrics	GI/Liver	Renal	General Pediatrics	General Pediatrics	Liver
	Pulmonary	Neurology	Rheumatology	Mixed Specialty	Mixed Specialty	Renal
		Adolescent	Endocrine
Team membersa	2 interns (q6 call)			4 interns (3 on day shift/1 on night shift)
	1 senior resident (q5 call)			1 senior resident
Night‐shift coveragea	1 intern and 1 senior resident together covered all 3 teams.			1 night intern per team (teams D/E) working 7 consecutive night shifts
				1 supervising night resident covering all 3 teams
Intern cross‐coverage of other teams	Nights/clinic afternoons			None
Length of night shift	30 hours			13 hours

Figure 1

There was no change in the paper‐order system, the electronic health record, timing of the morning blood draw, use of new facilities for patient care, or protocol for emergency department admission. Concomitant with the restructuring, most subspecialty patients were consolidated onto the hospitalist service, necessitating creation of a second hospitalist team. However, patients admitted with the diagnoses identified above would have been on the hospitalist service before and after the restructuring.

RESULTS

We analyzed data for 48 admissions preintervention and 50 postintervention. With the exception of insurance type, there was no difference in baseline demographics, diagnoses, or severity of illness between the groups (Table 2). Within the order classes above, we identified 212 orders preintervention and 231 orders postintervention.

After the intervention, there was a statistically significant increase in the average number of orders written within the first 12 hours (pre: 0.58 orders vs post: 1.12, P = 0.009) and 24 hours (pre: 1.52 vs post: 2.38, P = 0.004) following admission (Table 3), not including the admission order set. The fraction of orders written at night was not significantly different (27% at night preintervention, 33% postintervention, P = 0.149). The fraction of admissions on the day shift compared to the night shift did not change (P = 0.72). There was no difference in the ratio of de‐escalation to escalation orders written during the night (Table 2).

DISCUSSION

In this study, we demonstrate increased patient care management early in the hospitalization, measured in this study by the mean number of orders written per patient in the first 12 and 24 hours after admission, after transition from a call schedule with extended (>16 hours) shifts to one with shorter shifts compliant with current ACGME duty‐hour restrictions and an explicit focus on greater continuity of care. We did not detect a change in the proportion of total orders written on the night shift compared to the day shift. Earlier active medical management, such as weaning nebulized albuterol or supplemental oxygen, can speed the time to discharge.[14]

Our failure to detect a significant change in the proportion or type of orders written at night may have been due to our small sample size. Anecdotally, after the intervention, medical students reported to us that they noticed a difference between our service, in which we expect night teams to advance care, and other services at our institution, in which nights are a time to focus on putting out fires. This was not something that had been reported to us prior. It is likely reflective of the overall approach to patient care taken by residents working a night shift as part of a longitudinal care team.

This study builds on previous findings that demonstrated lower costs and shorter length of stay after implementing a schedule based on day and night teams.[7] The reasons for such improvements are likely multifactorial. In our model, which was purposefully designed to create night‐team continuity and minimize cross‐coverage, it is likely that residents also felt a greater sense of responsibility for and familiarity with the patients[15] and therefore felt more comfortable advancing care. Not only were interns likely better rested, the patient‐to‐provider ratio was also lower than in the preintervention model. Increases in staffing are often necessary to eliminate cross‐coverage while maintaining safe, 24‐hour care. These findings suggest that increases in cost from additional staffing may be at least partially offset by more active patient management early in the hospitalization, which has the potential to lead to shorter hospital stays.

There are several limitations to our research. We studied a small sample, including a subset of general pediatrics diagnoses that are amenable to active management, limiting generalizability. We did not calculate a physician‐to‐patient ratio because this was not possible with the retrospective data we collected. Staffing ratios likely improved, and we consider that part of the overall improvements in staffing that may have contributed to the observed changes in ordering patterns. Although intern‐level cross‐coverage was eliminated, the senior resident continued to cover multiple teams overnight. This senior covered the same 3 teams for 7 consecutive nights. The addition of a hospitalist team, with subspecialists being placed in consultant roles, may have contributed to the increase in active management, though our study population did not include subspecialty patients. There was a difference in insurance status between the 2 groups. This was unlikely to affect resident physician practices as insurance information is not routinely discussed in the course of patient care. In the context of the ongoing debate about duty‐hour restrictions, it will be important for future studies to elucidate whether sleep or other variables are the primary contributors to this finding. Our data are derived solely from 1 inpatient service at a single academic medical center; however, we do feel there are lessons that may be applied to other settings.

CONCLUSION

A coverage system with improved nighttime resident coverage was associated with a greater number of orders written early in the hospitalization, suggesting more active management of clinical problems to advance care.

Handoffs among hospital providers are highly error prone and can result in serious morbidity and mortality. Best practices for verbal handoffs have been described[1, 2, 3, 4] and include conducting verbal handoffs face to face, providing opportunities for questions, having the receiver perform a readback, as well as specific content recommendations including action items. Far less research has focused on best practices for printed handoff documents,[5, 6] despite the routine use of written handoff tools as a reference by on‐call physicians.[7, 8] Erroneous or outdated information on the written handoff can mislead on‐call providers, potentially leading to serious medical errors.

In their most basic form, printed handoff documents list patients for whom a provider is responsible. Typically, they also contain demographic information, reason for hospital admission, and a task list for each patient. They may also contain more detailed information on patient history, hospital course, and/or care plan, and may vary among specialties.[9] They come in various forms, ranging from index cards with handwritten notes, to word‐processor or spreadsheet documents, to printed documents that are autopopulated from the electronic health record (EHR).[2] Importantly, printed handoff documents supplement the verbal handoff by allowing receivers to follow along as patients are presented. The concurrent use of written and verbal handoffs may improve retention of clinical information as compared with either alone.[10, 11]

The Joint Commission requires an institutional approach to patient handoffs.[12] The requirements state that handoff communication solutions should take a standardized form, but they do not provide details regarding what data elements should be included in printed or verbal handoffs. Accreditation Council for Graduate Medical Education Common Program Requirements likewise require that residents must become competent in patient handoffs[13] but do not provide specific details or measurement tools. Absent widely accepted guidelines, decisions regarding which elements to include in printed handoff documents are currently made at an individual or institutional level.

The I‐PASS study is a federally funded multi‐institutional project that demonstrated a decrease in medical errors and preventable adverse events after implementation of a standardized resident handoff bundle.[14, 15] The I‐PASS Study Group developed a bundle of handoff interventions, beginning with a handoff and teamwork training program (based in part on TeamSTEPPS [Team Strategies and Tools to Enhance Performance and Patient Safety]),[16] a novel verbal mnemonic, I‐PASS (Illness Severity, Patient Summary, Action List, Situation Awareness and Contingency Planning, and Synthesis by Receiver),[17] and changes to the verbal handoff process, in addition to several other elements.

We hypothesized that developing a standardized printed handoff template would reinforce the handoff training and enhance the value of the verbal handoff process changes. Given the paucity of data on best printed handoff practices, however, we first conducted a needs assessment to identify which data elements were currently contained in printed handoffs across sites, and to allow an expert panel to make recommendations for best practices.

METHODS

I‐PASS Study sites included 9 pediatric residency programs at academic medical centers from across North America. Programs were identified through professional networks and invited to participate. The nonintensive care unit hospitalist services at these medical centers are primarily staffed by residents and medical students with attending supervision. At 1 site, nurse practitioners also participate in care. Additional details about study sites can be found in the study descriptions previously published.[14, 15] All sites received local institutional review board approval.

We began by inviting members of the I‐PASS Education Executive Committee (EEC)[14] to build a collective, comprehensive list of possible data elements for printed handoff documents. This committee included pediatric residency program directors, pediatric hospitalists, education researchers, health services researchers, and patient safety experts. We obtained sample handoff documents from pediatric hospitalist services at each of 9 institutions in the United States and Canada (with protected health information redacted). We reviewed these sample handoff documents to characterize their format and to determine what discrete data elements appeared in each site's printed handoff document. Presence or absence of each data element across sites was tabulated. We also queried sites to determine the feasibility of including elements that were not presently included.

Subsequently, I‐PASS site investigators led structured group interviews at participating sites to gather additional information about handoff practices at each site. These structured group interviews included diverse representation from residents, faculty, and residency program leadership, as well as hospitalists and medical students, to ensure the comprehensive acquisition of information regarding site‐specific characteristics. Each group provided answers to a standardized set of open‐ended questions that addressed current practices, handoff education, simulation use, team structure, and the nature of current written handoff tools, if applicable, at each site. One member of the structured group interview served as a scribe and created a document that summarized the content of the structured group interview meeting and answers to the standardized questions.

RESULTS

Nine programs (100%) provided data on the structure and contents of their printed handoff documents. We found wide variation in structure across the 9 sites. Three sites used a word‐processorbased document that required manual entry of all data elements. The other 6 institutions had a direct link with the EHR to enable autopopulation of between 10 and 20 elements on the printed handoff document.

The content of written handoff documents, as well as the sources of data included in them (present or future), likewise varied substantially across sites (Table 1). Only 4 data elements (name, age, weight, and a list of medications) were universally included at all 9 sites. Among the 6 institutions that linked the printed handoff to the EHR, there was also substantial variation in which elements were autoimported. Only 7 elements were universally autoimported at these 6 sites: patient name, medical record number, room number, weight, date of birth, age, and date of admission. Two elements from the original brainstorming were not presently included in any sites' documents (emergency contact and primary language).

Nine institutions (100%) conducted structured group interviews, ranging in size from 4 to 27 individuals with a median of 5 participants. The documents containing information from each site were provided to the authors. The authors then tabulated categorical information, reviewed narrative comments to understand current institutional practices, and conducted simple content analysis to identify areas of concordance or discordance, particularly with respect to data elements and EHR usage. Based on the results of the printed handoff document review and structured group interviews, with additional perspectives provided by the I‐PASS EEC, the expert panel came to consensus on a list of 23 elements that should be included in printed handoff documents, including 15 essential data elements and 8 additional recommended elements (Table 2).

Evidence ratings[19] of these elements are included. Several elements are classified as I‐B (effective, nonrandomized studies) based on either studies of individual elements, or greater than 1 study of bundled elements that could reasonably be extrapolated. These include Illness severity,[20, 21] patient summary,[21, 22] action items[21, 22] (to do lists), situation awareness and contingency plan,[21, 22] and medications[22, 23, 24] with attention to importing from the EHR. Medications entered as free text were classified as IIa‐C because of risk and potential significance of errors; in particular there was concern that transcription errors, errors of omission, or errors of commission could potentially lead to patient harms. The remaining essential elements are classified as I‐C (effective, expert consensus). Of note, date of birth was specifically included as a patient identifier, distinct from age, which was felt to be useful as a descriptor (often within a one‐liner or as part of the patient summary).

The 8 recommended elements were elements for which there was not unanimous agreement on inclusion, but the majority of the panel felt they should be included. These elements were classified as IIa‐C, with 1 exception. Code status generated significant controversy among the group. After extensive discussion among the group and consideration of safety, supervision, educational, and pediatric‐specific considerations, all members of the group agreed on the categorization as a recommended element; it is classified as IIb‐C.

All members of the group agreed that data elements should be directly imported from the EHR whenever possible. Finally, members agreed that the elements that make up the I‐PASS mnemonic (illness severity, patient summary, action items, situation awareness/contingency planning) should be listed in that order whenever possible. A sample I‐PASS‐compliant printed handoff document is shown Figure 1.

Figure 1

DISCUSSION

We identified substantial variability in the structure and content of printed handoff documents used by 9 pediatric hospitalist teaching services, reflective of a lack of standardization. We found that institutional printed handoff documents shared some demographic elements (eg, name, room, medical record number) but also varied in clinical content (eg, vital signs, lab tests, code status). Our expert panel developed a list of 15 essential and 8 recommended data elements for printed handoff documents. Although this is a large number of fields, the majority of the essential fields were already included by most sites, and many are basic demographic identifiers. Illness severity is the 1 essential field that was not routinely included; however, including this type of overview is consistently recommended[2, 4] and supported by evidence,[20, 21] and contributes to building a shared mental model.[16] We recommend the categories of stable/watcher/unstable.[17]

Several prior single‐center studies have found that introducing a printed handoff document can lead to improvements in workflow, communication, and patient safety. In an early study, Petersen et al.[25] showed an association between use of a computerized sign‐out program and reduced odds of preventable adverse events during periods of cross‐coverage. Wayne et al.[26] reported fewer perceived inaccuracies in handoff documents as well as improved clarity at the time of transfer, supporting the role for standardization. Van Eaton et al.[27] demonstrated rapid uptake and desirability of a computerized handoff document, which combined autoimportation of information from an EHR with resident‐entered patient details, reflecting the importance of both data sources. In addition, they demonstrated improvements in both the rounding and sign‐out processes.[28]

Two studies specifically reported the increased use of specific fields after implementation. Payne et al. implemented a Web‐based handoff tool and documented significant increases in the number of handoffs containing problem lists, medication lists, and code status, accompanied by perceived improvements in quality of handoffs and fewer near‐miss events.[24] Starmer et al. found that introduction of a resident handoff bundle that included a printed handoff tool led to reduction in medical errors and adverse events.[22] The study group using the tool populated 11 data elements more often after implementation, and introduction of this printed handoff tool in particular was associated with reductions in written handoff miscommunications. Neither of these studies included subanalysis to indicate which data elements may have been most important.

In contrast to previous single‐institution studies, our recommendations for a printed handoff template come from evaluations of tools and discussions with front line providers across 9 institutions. We had substantial overlap with data elements recommended by Van Eaton et al.[27] However, there were several areas in which we did not have overlap with published templates including weight, ins/outs, primary language, emergency contact information, or primary care provider. Other published handoff tools have been highly specialized (eg, for cardiac intensive care) or included many fewer data elements than our group felt were essential. These differences may reflect the unique aspects of caring for pediatric patients (eg, need for weights) and the absence of defined protocols for many pediatric conditions. In addition, the level of detail needed for contingency planning may vary between teaching and nonteaching services.

Resident physicians may provide valuable information in the development of standardized handoff documents. Clark et al.,[29] at Virginia Mason University, utilized resident‐driven continuous quality improvement processes including real‐time feedback to implement an electronic template. They found that engagement of both senior leaders and front‐line users was an important component of their success in uptake. Our study utilized residents as essential members of structured group interviews to ensure that front‐line users' needs were represented as recommendations for a printed handoff tool template were developed.

As previously described,[17] our study group had identified several key data elements that should be included in verbal handoffs: illness severity, a patient summary, a discrete action list, situation awareness/contingency planning, and a synthesis by receiver. With consideration of the multivoting results as well as known best practices,[1, 4, 12] the expert panel for this study agreed that each of these elements should also be highlighted in the printed template to ensure consistency between the printed document and the verbal handoff, and to have each reinforce the other. On the printed handoff tool, the final S in the I‐PASS mnemonic (synthesis by receiver) cannot be prepopulated, but considering the importance of this step,[16, 30, 31, 32] it should be printed as synthesis by receiver to serve as a text‐reminder to both givers and receivers.

The panel also felt, however, that the printed handoff document should provide additional background information not routinely included in a verbal handoff. It should serve as a reference tool both at the time of verbal handoff and throughout the day and night, and therefore should include more comprehensive information than is necessary or appropriate to convey during the verbal handoff. We identified 10 data elements that are essential in a printed handoff document in addition to the I‐PASS elements (Table 2).

Patient demographic data elements, as well as team assignments and attending physician, were uniformly supported for inclusion. The medication list was viewed as essential; however, the panel also recognized the potential for medical errors due to inaccuracies in the medication list. In particular, there was concern that including all fields of a medication order (drug, dose, route, frequency) would result in handoffs containing a high proportion of inaccurate information, particularly for complex patients whose medication regimens may vary over the course of hospitalization. Therefore, the panel agreed that if medication lists were entered manually, then only the medication name should be included as they did not wish to perpetuate inaccurate or potentially harmful information. If medication lists were autoimported from an EHR, then they should include drug name, dose, route, and frequency if possible.

In the I‐PASS study,[15] all institutions implemented printed handoff documents that included fields for the essential data elements. After implementation, there was a significant increase in completion of all essential fields. Although there is limited evidence to support any individual data element, increased usage of these elements was associated with the overall study finding of decreased rates of medical errors and preventable adverse events.

EHRs have the potential to help standardize printed handoff documents[5, 6, 33, 34, 35]; all participants in our study agreed that printed handoff documents should ideally be linked with the EHR and should autoimport data wherever appropriate. Manually populated (eg, word processor‐ or spreadsheet‐based) handoff tools have important limitations, particularly related to the potential for typographical errors as well as accidental omission of data fields, and lead to unnecessary duplication of work (eg, re‐entering data already included in a progress note) that can waste providers' time. It was also acknowledged that word processor‐ or spreadsheet‐based documents may have flexibility that is lacking in EHR‐based handoff documents. For example, formatting can more easily be adjusted to increase the number of patients per printed page. As technology advances, printed documents may be phased out in favor of EHR‐based on‐screen reports, which by their nature would be more accurate due to real‐time autoupdates.

In making recommendations about essential versus recommended items for inclusion in the printed handoff template, the only data element that generated controversy among our experts was code status. Some felt that it should be included as an essential element, whereas others did not. We believe that this was unique to our practice in pediatric hospital ward settings, as codes in most pediatric ward settings are rare. Among the concerns expressed with including code status for all patients were that residents might assume patients were full‐code without verifying. The potential inaccuracy created by this might have severe implications. Alternatively, residents might feel obligated to have code discussions with all patients regardless of severity of illness, which may be inappropriate in a pediatric population. Several educators expressed concerns about trainees having unsupervised code‐status conversations with families of pediatric patients. Conversely, although codes are rare in pediatric ward settings, concerns were raised that not including code status could be problematic during these rare but critically important events. Other fields, such as weight, might have less relevance for an adult population in which emergency drug doses are standardized.

CONCLUSIONS

In this article we describe the results of a needs assessment that informed expert consensus‐based recommendations for data elements to include in a printed handoff document. We recommend that pediatric programs include the elements identified as part of a standardized written handoff tool. Although many of these elements are also applicable to other specialties, future work should be conducted to adapt the printed handoff document elements described here for use in other specialties and settings. Future studies should work to validate the importance of these elements, studying the manner in which their inclusion affects the quality of written handoffs, and ultimately patient safety.

Handoffs among hospital providers are highly error prone and can result in serious morbidity and mortality. Best practices for verbal handoffs have been described[1, 2, 3, 4] and include conducting verbal handoffs face to face, providing opportunities for questions, having the receiver perform a readback, as well as specific content recommendations including action items. Far less research has focused on best practices for printed handoff documents,[5, 6] despite the routine use of written handoff tools as a reference by on‐call physicians.[7, 8] Erroneous or outdated information on the written handoff can mislead on‐call providers, potentially leading to serious medical errors.

In their most basic form, printed handoff documents list patients for whom a provider is responsible. Typically, they also contain demographic information, reason for hospital admission, and a task list for each patient. They may also contain more detailed information on patient history, hospital course, and/or care plan, and may vary among specialties.[9] They come in various forms, ranging from index cards with handwritten notes, to word‐processor or spreadsheet documents, to printed documents that are autopopulated from the electronic health record (EHR).[2] Importantly, printed handoff documents supplement the verbal handoff by allowing receivers to follow along as patients are presented. The concurrent use of written and verbal handoffs may improve retention of clinical information as compared with either alone.[10, 11]

The Joint Commission requires an institutional approach to patient handoffs.[12] The requirements state that handoff communication solutions should take a standardized form, but they do not provide details regarding what data elements should be included in printed or verbal handoffs. Accreditation Council for Graduate Medical Education Common Program Requirements likewise require that residents must become competent in patient handoffs[13] but do not provide specific details or measurement tools. Absent widely accepted guidelines, decisions regarding which elements to include in printed handoff documents are currently made at an individual or institutional level.

The I‐PASS study is a federally funded multi‐institutional project that demonstrated a decrease in medical errors and preventable adverse events after implementation of a standardized resident handoff bundle.[14, 15] The I‐PASS Study Group developed a bundle of handoff interventions, beginning with a handoff and teamwork training program (based in part on TeamSTEPPS [Team Strategies and Tools to Enhance Performance and Patient Safety]),[16] a novel verbal mnemonic, I‐PASS (Illness Severity, Patient Summary, Action List, Situation Awareness and Contingency Planning, and Synthesis by Receiver),[17] and changes to the verbal handoff process, in addition to several other elements.

We hypothesized that developing a standardized printed handoff template would reinforce the handoff training and enhance the value of the verbal handoff process changes. Given the paucity of data on best printed handoff practices, however, we first conducted a needs assessment to identify which data elements were currently contained in printed handoffs across sites, and to allow an expert panel to make recommendations for best practices.

METHODS

I‐PASS Study sites included 9 pediatric residency programs at academic medical centers from across North America. Programs were identified through professional networks and invited to participate. The nonintensive care unit hospitalist services at these medical centers are primarily staffed by residents and medical students with attending supervision. At 1 site, nurse practitioners also participate in care. Additional details about study sites can be found in the study descriptions previously published.[14, 15] All sites received local institutional review board approval.

We began by inviting members of the I‐PASS Education Executive Committee (EEC)[14] to build a collective, comprehensive list of possible data elements for printed handoff documents. This committee included pediatric residency program directors, pediatric hospitalists, education researchers, health services researchers, and patient safety experts. We obtained sample handoff documents from pediatric hospitalist services at each of 9 institutions in the United States and Canada (with protected health information redacted). We reviewed these sample handoff documents to characterize their format and to determine what discrete data elements appeared in each site's printed handoff document. Presence or absence of each data element across sites was tabulated. We also queried sites to determine the feasibility of including elements that were not presently included.

Subsequently, I‐PASS site investigators led structured group interviews at participating sites to gather additional information about handoff practices at each site. These structured group interviews included diverse representation from residents, faculty, and residency program leadership, as well as hospitalists and medical students, to ensure the comprehensive acquisition of information regarding site‐specific characteristics. Each group provided answers to a standardized set of open‐ended questions that addressed current practices, handoff education, simulation use, team structure, and the nature of current written handoff tools, if applicable, at each site. One member of the structured group interview served as a scribe and created a document that summarized the content of the structured group interview meeting and answers to the standardized questions.

RESULTS

Nine programs (100%) provided data on the structure and contents of their printed handoff documents. We found wide variation in structure across the 9 sites. Three sites used a word‐processorbased document that required manual entry of all data elements. The other 6 institutions had a direct link with the EHR to enable autopopulation of between 10 and 20 elements on the printed handoff document.

The content of written handoff documents, as well as the sources of data included in them (present or future), likewise varied substantially across sites (Table 1). Only 4 data elements (name, age, weight, and a list of medications) were universally included at all 9 sites. Among the 6 institutions that linked the printed handoff to the EHR, there was also substantial variation in which elements were autoimported. Only 7 elements were universally autoimported at these 6 sites: patient name, medical record number, room number, weight, date of birth, age, and date of admission. Two elements from the original brainstorming were not presently included in any sites' documents (emergency contact and primary language).

Nine institutions (100%) conducted structured group interviews, ranging in size from 4 to 27 individuals with a median of 5 participants. The documents containing information from each site were provided to the authors. The authors then tabulated categorical information, reviewed narrative comments to understand current institutional practices, and conducted simple content analysis to identify areas of concordance or discordance, particularly with respect to data elements and EHR usage. Based on the results of the printed handoff document review and structured group interviews, with additional perspectives provided by the I‐PASS EEC, the expert panel came to consensus on a list of 23 elements that should be included in printed handoff documents, including 15 essential data elements and 8 additional recommended elements (Table 2).

Evidence ratings[19] of these elements are included. Several elements are classified as I‐B (effective, nonrandomized studies) based on either studies of individual elements, or greater than 1 study of bundled elements that could reasonably be extrapolated. These include Illness severity,[20, 21] patient summary,[21, 22] action items[21, 22] (to do lists), situation awareness and contingency plan,[21, 22] and medications[22, 23, 24] with attention to importing from the EHR. Medications entered as free text were classified as IIa‐C because of risk and potential significance of errors; in particular there was concern that transcription errors, errors of omission, or errors of commission could potentially lead to patient harms. The remaining essential elements are classified as I‐C (effective, expert consensus). Of note, date of birth was specifically included as a patient identifier, distinct from age, which was felt to be useful as a descriptor (often within a one‐liner or as part of the patient summary).

The 8 recommended elements were elements for which there was not unanimous agreement on inclusion, but the majority of the panel felt they should be included. These elements were classified as IIa‐C, with 1 exception. Code status generated significant controversy among the group. After extensive discussion among the group and consideration of safety, supervision, educational, and pediatric‐specific considerations, all members of the group agreed on the categorization as a recommended element; it is classified as IIb‐C.

All members of the group agreed that data elements should be directly imported from the EHR whenever possible. Finally, members agreed that the elements that make up the I‐PASS mnemonic (illness severity, patient summary, action items, situation awareness/contingency planning) should be listed in that order whenever possible. A sample I‐PASS‐compliant printed handoff document is shown Figure 1.

Figure 1

DISCUSSION

We identified substantial variability in the structure and content of printed handoff documents used by 9 pediatric hospitalist teaching services, reflective of a lack of standardization. We found that institutional printed handoff documents shared some demographic elements (eg, name, room, medical record number) but also varied in clinical content (eg, vital signs, lab tests, code status). Our expert panel developed a list of 15 essential and 8 recommended data elements for printed handoff documents. Although this is a large number of fields, the majority of the essential fields were already included by most sites, and many are basic demographic identifiers. Illness severity is the 1 essential field that was not routinely included; however, including this type of overview is consistently recommended[2, 4] and supported by evidence,[20, 21] and contributes to building a shared mental model.[16] We recommend the categories of stable/watcher/unstable.[17]

Several prior single‐center studies have found that introducing a printed handoff document can lead to improvements in workflow, communication, and patient safety. In an early study, Petersen et al.[25] showed an association between use of a computerized sign‐out program and reduced odds of preventable adverse events during periods of cross‐coverage. Wayne et al.[26] reported fewer perceived inaccuracies in handoff documents as well as improved clarity at the time of transfer, supporting the role for standardization. Van Eaton et al.[27] demonstrated rapid uptake and desirability of a computerized handoff document, which combined autoimportation of information from an EHR with resident‐entered patient details, reflecting the importance of both data sources. In addition, they demonstrated improvements in both the rounding and sign‐out processes.[28]

Two studies specifically reported the increased use of specific fields after implementation. Payne et al. implemented a Web‐based handoff tool and documented significant increases in the number of handoffs containing problem lists, medication lists, and code status, accompanied by perceived improvements in quality of handoffs and fewer near‐miss events.[24] Starmer et al. found that introduction of a resident handoff bundle that included a printed handoff tool led to reduction in medical errors and adverse events.[22] The study group using the tool populated 11 data elements more often after implementation, and introduction of this printed handoff tool in particular was associated with reductions in written handoff miscommunications. Neither of these studies included subanalysis to indicate which data elements may have been most important.

In contrast to previous single‐institution studies, our recommendations for a printed handoff template come from evaluations of tools and discussions with front line providers across 9 institutions. We had substantial overlap with data elements recommended by Van Eaton et al.[27] However, there were several areas in which we did not have overlap with published templates including weight, ins/outs, primary language, emergency contact information, or primary care provider. Other published handoff tools have been highly specialized (eg, for cardiac intensive care) or included many fewer data elements than our group felt were essential. These differences may reflect the unique aspects of caring for pediatric patients (eg, need for weights) and the absence of defined protocols for many pediatric conditions. In addition, the level of detail needed for contingency planning may vary between teaching and nonteaching services.

Resident physicians may provide valuable information in the development of standardized handoff documents. Clark et al.,[29] at Virginia Mason University, utilized resident‐driven continuous quality improvement processes including real‐time feedback to implement an electronic template. They found that engagement of both senior leaders and front‐line users was an important component of their success in uptake. Our study utilized residents as essential members of structured group interviews to ensure that front‐line users' needs were represented as recommendations for a printed handoff tool template were developed.

As previously described,[17] our study group had identified several key data elements that should be included in verbal handoffs: illness severity, a patient summary, a discrete action list, situation awareness/contingency planning, and a synthesis by receiver. With consideration of the multivoting results as well as known best practices,[1, 4, 12] the expert panel for this study agreed that each of these elements should also be highlighted in the printed template to ensure consistency between the printed document and the verbal handoff, and to have each reinforce the other. On the printed handoff tool, the final S in the I‐PASS mnemonic (synthesis by receiver) cannot be prepopulated, but considering the importance of this step,[16, 30, 31, 32] it should be printed as synthesis by receiver to serve as a text‐reminder to both givers and receivers.

The panel also felt, however, that the printed handoff document should provide additional background information not routinely included in a verbal handoff. It should serve as a reference tool both at the time of verbal handoff and throughout the day and night, and therefore should include more comprehensive information than is necessary or appropriate to convey during the verbal handoff. We identified 10 data elements that are essential in a printed handoff document in addition to the I‐PASS elements (Table 2).

Patient demographic data elements, as well as team assignments and attending physician, were uniformly supported for inclusion. The medication list was viewed as essential; however, the panel also recognized the potential for medical errors due to inaccuracies in the medication list. In particular, there was concern that including all fields of a medication order (drug, dose, route, frequency) would result in handoffs containing a high proportion of inaccurate information, particularly for complex patients whose medication regimens may vary over the course of hospitalization. Therefore, the panel agreed that if medication lists were entered manually, then only the medication name should be included as they did not wish to perpetuate inaccurate or potentially harmful information. If medication lists were autoimported from an EHR, then they should include drug name, dose, route, and frequency if possible.

In the I‐PASS study,[15] all institutions implemented printed handoff documents that included fields for the essential data elements. After implementation, there was a significant increase in completion of all essential fields. Although there is limited evidence to support any individual data element, increased usage of these elements was associated with the overall study finding of decreased rates of medical errors and preventable adverse events.

EHRs have the potential to help standardize printed handoff documents[5, 6, 33, 34, 35]; all participants in our study agreed that printed handoff documents should ideally be linked with the EHR and should autoimport data wherever appropriate. Manually populated (eg, word processor‐ or spreadsheet‐based) handoff tools have important limitations, particularly related to the potential for typographical errors as well as accidental omission of data fields, and lead to unnecessary duplication of work (eg, re‐entering data already included in a progress note) that can waste providers' time. It was also acknowledged that word processor‐ or spreadsheet‐based documents may have flexibility that is lacking in EHR‐based handoff documents. For example, formatting can more easily be adjusted to increase the number of patients per printed page. As technology advances, printed documents may be phased out in favor of EHR‐based on‐screen reports, which by their nature would be more accurate due to real‐time autoupdates.

In making recommendations about essential versus recommended items for inclusion in the printed handoff template, the only data element that generated controversy among our experts was code status. Some felt that it should be included as an essential element, whereas others did not. We believe that this was unique to our practice in pediatric hospital ward settings, as codes in most pediatric ward settings are rare. Among the concerns expressed with including code status for all patients were that residents might assume patients were full‐code without verifying. The potential inaccuracy created by this might have severe implications. Alternatively, residents might feel obligated to have code discussions with all patients regardless of severity of illness, which may be inappropriate in a pediatric population. Several educators expressed concerns about trainees having unsupervised code‐status conversations with families of pediatric patients. Conversely, although codes are rare in pediatric ward settings, concerns were raised that not including code status could be problematic during these rare but critically important events. Other fields, such as weight, might have less relevance for an adult population in which emergency drug doses are standardized.

CONCLUSIONS

In this article we describe the results of a needs assessment that informed expert consensus‐based recommendations for data elements to include in a printed handoff document. We recommend that pediatric programs include the elements identified as part of a standardized written handoff tool. Although many of these elements are also applicable to other specialties, future work should be conducted to adapt the printed handoff document elements described here for use in other specialties and settings. Future studies should work to validate the importance of these elements, studying the manner in which their inclusion affects the quality of written handoffs, and ultimately patient safety.

Handoffs among hospital providers are highly error prone and can result in serious morbidity and mortality. Best practices for verbal handoffs have been described[1, 2, 3, 4] and include conducting verbal handoffs face to face, providing opportunities for questions, having the receiver perform a readback, as well as specific content recommendations including action items. Far less research has focused on best practices for printed handoff documents,[5, 6] despite the routine use of written handoff tools as a reference by on‐call physicians.[7, 8] Erroneous or outdated information on the written handoff can mislead on‐call providers, potentially leading to serious medical errors.

In their most basic form, printed handoff documents list patients for whom a provider is responsible. Typically, they also contain demographic information, reason for hospital admission, and a task list for each patient. They may also contain more detailed information on patient history, hospital course, and/or care plan, and may vary among specialties.[9] They come in various forms, ranging from index cards with handwritten notes, to word‐processor or spreadsheet documents, to printed documents that are autopopulated from the electronic health record (EHR).[2] Importantly, printed handoff documents supplement the verbal handoff by allowing receivers to follow along as patients are presented. The concurrent use of written and verbal handoffs may improve retention of clinical information as compared with either alone.[10, 11]

The Joint Commission requires an institutional approach to patient handoffs.[12] The requirements state that handoff communication solutions should take a standardized form, but they do not provide details regarding what data elements should be included in printed or verbal handoffs. Accreditation Council for Graduate Medical Education Common Program Requirements likewise require that residents must become competent in patient handoffs[13] but do not provide specific details or measurement tools. Absent widely accepted guidelines, decisions regarding which elements to include in printed handoff documents are currently made at an individual or institutional level.

The I‐PASS study is a federally funded multi‐institutional project that demonstrated a decrease in medical errors and preventable adverse events after implementation of a standardized resident handoff bundle.[14, 15] The I‐PASS Study Group developed a bundle of handoff interventions, beginning with a handoff and teamwork training program (based in part on TeamSTEPPS [Team Strategies and Tools to Enhance Performance and Patient Safety]),[16] a novel verbal mnemonic, I‐PASS (Illness Severity, Patient Summary, Action List, Situation Awareness and Contingency Planning, and Synthesis by Receiver),[17] and changes to the verbal handoff process, in addition to several other elements.

We hypothesized that developing a standardized printed handoff template would reinforce the handoff training and enhance the value of the verbal handoff process changes. Given the paucity of data on best printed handoff practices, however, we first conducted a needs assessment to identify which data elements were currently contained in printed handoffs across sites, and to allow an expert panel to make recommendations for best practices.

METHODS

I‐PASS Study sites included 9 pediatric residency programs at academic medical centers from across North America. Programs were identified through professional networks and invited to participate. The nonintensive care unit hospitalist services at these medical centers are primarily staffed by residents and medical students with attending supervision. At 1 site, nurse practitioners also participate in care. Additional details about study sites can be found in the study descriptions previously published.[14, 15] All sites received local institutional review board approval.

We began by inviting members of the I‐PASS Education Executive Committee (EEC)[14] to build a collective, comprehensive list of possible data elements for printed handoff documents. This committee included pediatric residency program directors, pediatric hospitalists, education researchers, health services researchers, and patient safety experts. We obtained sample handoff documents from pediatric hospitalist services at each of 9 institutions in the United States and Canada (with protected health information redacted). We reviewed these sample handoff documents to characterize their format and to determine what discrete data elements appeared in each site's printed handoff document. Presence or absence of each data element across sites was tabulated. We also queried sites to determine the feasibility of including elements that were not presently included.

Subsequently, I‐PASS site investigators led structured group interviews at participating sites to gather additional information about handoff practices at each site. These structured group interviews included diverse representation from residents, faculty, and residency program leadership, as well as hospitalists and medical students, to ensure the comprehensive acquisition of information regarding site‐specific characteristics. Each group provided answers to a standardized set of open‐ended questions that addressed current practices, handoff education, simulation use, team structure, and the nature of current written handoff tools, if applicable, at each site. One member of the structured group interview served as a scribe and created a document that summarized the content of the structured group interview meeting and answers to the standardized questions.

RESULTS

Nine programs (100%) provided data on the structure and contents of their printed handoff documents. We found wide variation in structure across the 9 sites. Three sites used a word‐processorbased document that required manual entry of all data elements. The other 6 institutions had a direct link with the EHR to enable autopopulation of between 10 and 20 elements on the printed handoff document.

The content of written handoff documents, as well as the sources of data included in them (present or future), likewise varied substantially across sites (Table 1). Only 4 data elements (name, age, weight, and a list of medications) were universally included at all 9 sites. Among the 6 institutions that linked the printed handoff to the EHR, there was also substantial variation in which elements were autoimported. Only 7 elements were universally autoimported at these 6 sites: patient name, medical record number, room number, weight, date of birth, age, and date of admission. Two elements from the original brainstorming were not presently included in any sites' documents (emergency contact and primary language).

Nine institutions (100%) conducted structured group interviews, ranging in size from 4 to 27 individuals with a median of 5 participants. The documents containing information from each site were provided to the authors. The authors then tabulated categorical information, reviewed narrative comments to understand current institutional practices, and conducted simple content analysis to identify areas of concordance or discordance, particularly with respect to data elements and EHR usage. Based on the results of the printed handoff document review and structured group interviews, with additional perspectives provided by the I‐PASS EEC, the expert panel came to consensus on a list of 23 elements that should be included in printed handoff documents, including 15 essential data elements and 8 additional recommended elements (Table 2).

Evidence ratings[19] of these elements are included. Several elements are classified as I‐B (effective, nonrandomized studies) based on either studies of individual elements, or greater than 1 study of bundled elements that could reasonably be extrapolated. These include Illness severity,[20, 21] patient summary,[21, 22] action items[21, 22] (to do lists), situation awareness and contingency plan,[21, 22] and medications[22, 23, 24] with attention to importing from the EHR. Medications entered as free text were classified as IIa‐C because of risk and potential significance of errors; in particular there was concern that transcription errors, errors of omission, or errors of commission could potentially lead to patient harms. The remaining essential elements are classified as I‐C (effective, expert consensus). Of note, date of birth was specifically included as a patient identifier, distinct from age, which was felt to be useful as a descriptor (often within a one‐liner or as part of the patient summary).

The 8 recommended elements were elements for which there was not unanimous agreement on inclusion, but the majority of the panel felt they should be included. These elements were classified as IIa‐C, with 1 exception. Code status generated significant controversy among the group. After extensive discussion among the group and consideration of safety, supervision, educational, and pediatric‐specific considerations, all members of the group agreed on the categorization as a recommended element; it is classified as IIb‐C.

All members of the group agreed that data elements should be directly imported from the EHR whenever possible. Finally, members agreed that the elements that make up the I‐PASS mnemonic (illness severity, patient summary, action items, situation awareness/contingency planning) should be listed in that order whenever possible. A sample I‐PASS‐compliant printed handoff document is shown Figure 1.

Figure 1

DISCUSSION

We identified substantial variability in the structure and content of printed handoff documents used by 9 pediatric hospitalist teaching services, reflective of a lack of standardization. We found that institutional printed handoff documents shared some demographic elements (eg, name, room, medical record number) but also varied in clinical content (eg, vital signs, lab tests, code status). Our expert panel developed a list of 15 essential and 8 recommended data elements for printed handoff documents. Although this is a large number of fields, the majority of the essential fields were already included by most sites, and many are basic demographic identifiers. Illness severity is the 1 essential field that was not routinely included; however, including this type of overview is consistently recommended[2, 4] and supported by evidence,[20, 21] and contributes to building a shared mental model.[16] We recommend the categories of stable/watcher/unstable.[17]

Several prior single‐center studies have found that introducing a printed handoff document can lead to improvements in workflow, communication, and patient safety. In an early study, Petersen et al.[25] showed an association between use of a computerized sign‐out program and reduced odds of preventable adverse events during periods of cross‐coverage. Wayne et al.[26] reported fewer perceived inaccuracies in handoff documents as well as improved clarity at the time of transfer, supporting the role for standardization. Van Eaton et al.[27] demonstrated rapid uptake and desirability of a computerized handoff document, which combined autoimportation of information from an EHR with resident‐entered patient details, reflecting the importance of both data sources. In addition, they demonstrated improvements in both the rounding and sign‐out processes.[28]

Two studies specifically reported the increased use of specific fields after implementation. Payne et al. implemented a Web‐based handoff tool and documented significant increases in the number of handoffs containing problem lists, medication lists, and code status, accompanied by perceived improvements in quality of handoffs and fewer near‐miss events.[24] Starmer et al. found that introduction of a resident handoff bundle that included a printed handoff tool led to reduction in medical errors and adverse events.[22] The study group using the tool populated 11 data elements more often after implementation, and introduction of this printed handoff tool in particular was associated with reductions in written handoff miscommunications. Neither of these studies included subanalysis to indicate which data elements may have been most important.

In contrast to previous single‐institution studies, our recommendations for a printed handoff template come from evaluations of tools and discussions with front line providers across 9 institutions. We had substantial overlap with data elements recommended by Van Eaton et al.[27] However, there were several areas in which we did not have overlap with published templates including weight, ins/outs, primary language, emergency contact information, or primary care provider. Other published handoff tools have been highly specialized (eg, for cardiac intensive care) or included many fewer data elements than our group felt were essential. These differences may reflect the unique aspects of caring for pediatric patients (eg, need for weights) and the absence of defined protocols for many pediatric conditions. In addition, the level of detail needed for contingency planning may vary between teaching and nonteaching services.

Resident physicians may provide valuable information in the development of standardized handoff documents. Clark et al.,[29] at Virginia Mason University, utilized resident‐driven continuous quality improvement processes including real‐time feedback to implement an electronic template. They found that engagement of both senior leaders and front‐line users was an important component of their success in uptake. Our study utilized residents as essential members of structured group interviews to ensure that front‐line users' needs were represented as recommendations for a printed handoff tool template were developed.

As previously described,[17] our study group had identified several key data elements that should be included in verbal handoffs: illness severity, a patient summary, a discrete action list, situation awareness/contingency planning, and a synthesis by receiver. With consideration of the multivoting results as well as known best practices,[1, 4, 12] the expert panel for this study agreed that each of these elements should also be highlighted in the printed template to ensure consistency between the printed document and the verbal handoff, and to have each reinforce the other. On the printed handoff tool, the final S in the I‐PASS mnemonic (synthesis by receiver) cannot be prepopulated, but considering the importance of this step,[16, 30, 31, 32] it should be printed as synthesis by receiver to serve as a text‐reminder to both givers and receivers.

The panel also felt, however, that the printed handoff document should provide additional background information not routinely included in a verbal handoff. It should serve as a reference tool both at the time of verbal handoff and throughout the day and night, and therefore should include more comprehensive information than is necessary or appropriate to convey during the verbal handoff. We identified 10 data elements that are essential in a printed handoff document in addition to the I‐PASS elements (Table 2).

Patient demographic data elements, as well as team assignments and attending physician, were uniformly supported for inclusion. The medication list was viewed as essential; however, the panel also recognized the potential for medical errors due to inaccuracies in the medication list. In particular, there was concern that including all fields of a medication order (drug, dose, route, frequency) would result in handoffs containing a high proportion of inaccurate information, particularly for complex patients whose medication regimens may vary over the course of hospitalization. Therefore, the panel agreed that if medication lists were entered manually, then only the medication name should be included as they did not wish to perpetuate inaccurate or potentially harmful information. If medication lists were autoimported from an EHR, then they should include drug name, dose, route, and frequency if possible.

In the I‐PASS study,[15] all institutions implemented printed handoff documents that included fields for the essential data elements. After implementation, there was a significant increase in completion of all essential fields. Although there is limited evidence to support any individual data element, increased usage of these elements was associated with the overall study finding of decreased rates of medical errors and preventable adverse events.

EHRs have the potential to help standardize printed handoff documents[5, 6, 33, 34, 35]; all participants in our study agreed that printed handoff documents should ideally be linked with the EHR and should autoimport data wherever appropriate. Manually populated (eg, word processor‐ or spreadsheet‐based) handoff tools have important limitations, particularly related to the potential for typographical errors as well as accidental omission of data fields, and lead to unnecessary duplication of work (eg, re‐entering data already included in a progress note) that can waste providers' time. It was also acknowledged that word processor‐ or spreadsheet‐based documents may have flexibility that is lacking in EHR‐based handoff documents. For example, formatting can more easily be adjusted to increase the number of patients per printed page. As technology advances, printed documents may be phased out in favor of EHR‐based on‐screen reports, which by their nature would be more accurate due to real‐time autoupdates.

In making recommendations about essential versus recommended items for inclusion in the printed handoff template, the only data element that generated controversy among our experts was code status. Some felt that it should be included as an essential element, whereas others did not. We believe that this was unique to our practice in pediatric hospital ward settings, as codes in most pediatric ward settings are rare. Among the concerns expressed with including code status for all patients were that residents might assume patients were full‐code without verifying. The potential inaccuracy created by this might have severe implications. Alternatively, residents might feel obligated to have code discussions with all patients regardless of severity of illness, which may be inappropriate in a pediatric population. Several educators expressed concerns about trainees having unsupervised code‐status conversations with families of pediatric patients. Conversely, although codes are rare in pediatric ward settings, concerns were raised that not including code status could be problematic during these rare but critically important events. Other fields, such as weight, might have less relevance for an adult population in which emergency drug doses are standardized.

CONCLUSIONS

In this article we describe the results of a needs assessment that informed expert consensus‐based recommendations for data elements to include in a printed handoff document. We recommend that pediatric programs include the elements identified as part of a standardized written handoff tool. Although many of these elements are also applicable to other specialties, future work should be conducted to adapt the printed handoff document elements described here for use in other specialties and settings. Future studies should work to validate the importance of these elements, studying the manner in which their inclusion affects the quality of written handoffs, and ultimately patient safety.