Deanne T. Kashiwagi, MD

Handoffs are key events in the care of hospitalized patients whereby vital information is relayed between healthcare providers. Resident duty hour restrictions and the popularity of shift‐based work schedules have increased the frequency of inpatient handoffs.[1, 2] Failures in communication at the time of patient handoff have been implicated as contributing factors to preventable adverse events.[3, 4, 5, 6] With patient safety in mind, accreditation organizations and professional societies have made the standardization of hospital handoff procedures a priority.[7, 8] A variety of strategies have been utilized to standardize handoffs. Examples include the use of mnemonics,[9] electronic resources,[10, 11, 12] preformatted handoff sheets,[13, 14, 15, 16] and optimization of the handoff environment.[17] The primary outcomes for many of these studies center on the provider by measuring their retention of patient facts[18, 19] and completion of tasks[14, 16] after handoff, for example. Few studies examined patient‐centered outcomes such as transfer to a higher level of care,[20] length of stay,[11] mortality,[21] or readmission rate.[22] A study in the pediatric population found that implementation of a handoff bundle was associated with a decrease in medical errors and preventable adverse events.[23]

The Society of Hospital Medicine recommends that patient handoffs consist of both a written and verbal component.[8] Providers in our division work on 3 shifts: day, evening, and night. In 2009, we developed a face‐to‐face morning handoff, during which night‐shift providers hand off patient care to day‐shift providers incorporating an electronically generated service information list.[17] Given that the evening shift ends well before the day shift begins, the evening‐shift providers do not participate in this face‐to‐face handoff of care for patients they admit to day providers.

We wished to compare the clinical outcomes and adverse events of patients admitted by the night‐shift providers to those admitted by the evening‐shift providers. We hypothesized that transfer of care using a face‐to‐face handoff would be associated with fewer adverse events and improved clinical outcomes.

METHODS

The study was deemed exempt by the Mayo Clinic Institutional Review Board.

Setting

The division's shift schedule during the study period is depicted in Figure 1. Day‐shift providers included a physician and nurse practitioner (NP) or physician assistant (PA) on each of 7 teams. Each service had an average daily patient census between 10 and 15 patients with 3 to 4 new admissions every 24 hours, with 1 to 2 of these admissions occurring during the evening and night shifts, on average. The day shift started at 7:45 _am and ended at 7:45 _pm, at which time the day teams transitioned care of their patients to 1 of 2 overnight NP/PAs who provided cross‐cover for all teams through the night. The overnight NP/PAs then transitioned care back to the day teams at 7:45 _am the following morning.

Figure 1

Two evening‐shift providers, both physicians, including a staff hospitalist and a hospital medicine fellowship trainee, admitted patients without any cross‐cover responsibility. Their shifts had the same start time, but staggered end times (2 _pm10 _pm and 2 _pmmidnight). At the end of their shifts, the evening‐shift providers relayed concerns or items for follow‐up to the night cross‐cover NP/PAs; however, this handoff was nonstandardized and provider dependent. The cross‐cover providers could also choose to pass on any relevant information to day‐shift providers if thought to be necessary, but this, again, was not required or standardized. A printed electronic handoff tool (including the patient's problem list, medications, vital signs, laboratory results, and to do list as determined by the admitting provider) as well as all clinical notes generated since admission were made available to day‐shift providers who assumed care at 7:45 _am; however, there was no face‐to‐face handoff between the evening‐ and day‐shift providers.

Two night‐shift physicians, including a moonlighting board‐eligible internal medicine physician and staff hospitalist, also started at staggered times, 6:45 _pm and 10 _pm, but their shifts both ended at 7:45 _am. These physicians also admitted patients without cross‐cover responsibilities. At 7:45 _am, in a face‐to‐face meeting, they transitioned care of patients admitted overnight to day‐shift providers. This handoff occurred at a predesignated place with assigned start times for each team. During the meeting, printed electronic documents, including the aforementioned electronic handoff tool as well as all clinical notes generated since admission, were made available to the oncoming day‐shift providers. The face‐to‐face interaction between night‐ and day‐shift providers lasted approximately 5 minutes and allowed for a brief presentation of the patient, review of the diagnostic testing and treatments performed so far, as well as anticipatory guidance regarding potential issues throughout the remainder of the hospitalization. Although inclusion of the above components was encouraged during the face‐to‐face handoff, the interaction was not scripted and topics discussed were at the providers' discretion.

Patients admitted during the evening and night shifts were assigned to day‐shift services primarily based on the current census of each team, so as to distribute the workload evenly.

RESULTS

Of 805 patients admitted between 6:45 _pm and midnight during the study period, 305 (37.9%) patients were handed off to day‐shift providers without face‐to‐face handoff, and 500 (62.1%) patients were transferred to the care of day‐shift providers with the use of a face‐to‐face handoff.

Baseline characteristics of both groups are depicted in Table 1. Demographic characteristics, including age, gender, and race, were not significantly different between groups. The mean Charlson Comorbidity Index score was not significantly different between the groups without and with a face‐to‐face handoff. In addition, the presence of medical comorbidities including type 2 diabetes mellitus, hypertension, coronary artery disease, hyperlipidemia, heart failure, body mass index (BMI) <18, active cancer, and current cigarette smoking were not significantly different between the 2 groups. There was a trend to a significantly increased proportion of patients with a BMI >30 in the group without face‐to‐face handoff (P=0.05).

Results for the outcomes of this study are depicted in Table 2. The frequency of rapid response team calls, code team calls, transfers to a higher level of care, and death in the hospital in the 12 hours following the first morning handoff of the admission were not significantly different between the 2 groups. Both 30‐day readmission rate and LOS (median and mean) were not significantly different between groups.

There was no significant difference between the 2 groups in the frequency of adverse events resulting in harm for any of the categories (categories EI). Total adverse events between groups were also compared. Adverse events per 100 admissions were not significantly different between the group without face‐to‐face handoff compared to the group with face‐to‐face handoff. The percentage of admissions with an adverse event was also similar between groups.

DISCUSSION

We found no significant difference in the rate of rapid response team calls, code team calls, transfers to a higher level of care, death in hospital, or adverse events when comparing patients transitioned to the care of day‐shift providers with or without a face‐to‐face handoff. We hypothesize that a reason adverse events were no different between the 2 groups may be that providers were more vigilant when they did not receive a face‐to‐face handoff from the previous provider. As a result, providers may have dedicated additional time reviewing the medical record, speaking with the patients, and communicating with other healthcare providers to ensure a safe care transition. Similarly, other studies found no significant reduction in adverse events when using a standardized handoff.[10, 13, 29] This may be because patient handoff is 1 of a multitude of factors that impact the rate of adverse events, and a handoff may play a less vital role in a system where documentation of care for a given patient is readily accessible, uniform, and detailed. A face‐to‐face interaction itself in a patient handoff may be less pertinent if key information can be communicated through other channels, such as an electronic handoff tool, email, or phone.

Another potential explanation for the lack of a significant difference in patient outcomes with and without a face‐to‐face handoff is related to the study design and inherent rate of the events measured. With the exception of 30‐day readmission rate and LOS, the outcomes of the study were recorded only if they occurred in the 12 hours following the first morning handoff of the admission. This was done in an attempt to isolate the effect of the nonface‐to‐face versus face‐to‐face handoff on the first morning of the admission, and to avoid confounding effects by subsequent transitions of care later in the hospitalization. The frequency of hospital admissions in which an adverse event occurred during this relatively short 12‐hour window was approximately 3% for all patients in the study. With 805 total patients in the study, there may have been insufficient statistical power to detect a difference in the rate of outcomes, if a difference did exist, considering the event rate for both groups and the sample size.

There are several additional limitations to our study. First, the GTT was designed to be applied across the entirety of a hospitalization. By screening for adverse events over the span of only 12 hours for each hospitalization, the sensitivity of the tool may have been diminished, with a proportion of adverse events not captured, even when the sequence of events leading to patient harm began during the 12 hours in question. Second, this is a retrospective study, and all adverse events may not be documented in the medical record. Third, although not formally structured and infrequent, some evening‐shift providers did send an email or call the oncoming day‐shift provider to discuss patients admitted. This process, however, was provider dependent, unstructured, uncommon, and erratic, and thus we were not able to capture it from medical record review. Finally, the patients in this study were deemed low acuity upon triage prior to admission. A face‐to‐face handoff may be less important in ensuring patient safety when caring for low‐acuity compared to high‐acuity patients, considering the rapidity at which the critically ill can deteriorate.

Handoffs of patient care in the hospital have certainly increased in recent years. Consequently, communication among providers is undoubtedly important, with patient safety being the primary goal. Our work suggests that a face‐to‐face component of a handoff is not vital to ensure a safe care transition. Because of the increasing frequency of handoffs, providers' ability to do so face‐to‐face will likely be challenged by time and logistical constraints. Future work is needed to delineate the most effective components of the handoff so that we can design information transfer that promotes safe and efficient care, even without a face‐to‐face interaction.

Handoffs are key events in the care of hospitalized patients whereby vital information is relayed between healthcare providers. Resident duty hour restrictions and the popularity of shift‐based work schedules have increased the frequency of inpatient handoffs.[1, 2] Failures in communication at the time of patient handoff have been implicated as contributing factors to preventable adverse events.[3, 4, 5, 6] With patient safety in mind, accreditation organizations and professional societies have made the standardization of hospital handoff procedures a priority.[7, 8] A variety of strategies have been utilized to standardize handoffs. Examples include the use of mnemonics,[9] electronic resources,[10, 11, 12] preformatted handoff sheets,[13, 14, 15, 16] and optimization of the handoff environment.[17] The primary outcomes for many of these studies center on the provider by measuring their retention of patient facts[18, 19] and completion of tasks[14, 16] after handoff, for example. Few studies examined patient‐centered outcomes such as transfer to a higher level of care,[20] length of stay,[11] mortality,[21] or readmission rate.[22] A study in the pediatric population found that implementation of a handoff bundle was associated with a decrease in medical errors and preventable adverse events.[23]

The Society of Hospital Medicine recommends that patient handoffs consist of both a written and verbal component.[8] Providers in our division work on 3 shifts: day, evening, and night. In 2009, we developed a face‐to‐face morning handoff, during which night‐shift providers hand off patient care to day‐shift providers incorporating an electronically generated service information list.[17] Given that the evening shift ends well before the day shift begins, the evening‐shift providers do not participate in this face‐to‐face handoff of care for patients they admit to day providers.

We wished to compare the clinical outcomes and adverse events of patients admitted by the night‐shift providers to those admitted by the evening‐shift providers. We hypothesized that transfer of care using a face‐to‐face handoff would be associated with fewer adverse events and improved clinical outcomes.

METHODS

The study was deemed exempt by the Mayo Clinic Institutional Review Board.

Setting

The division's shift schedule during the study period is depicted in Figure 1. Day‐shift providers included a physician and nurse practitioner (NP) or physician assistant (PA) on each of 7 teams. Each service had an average daily patient census between 10 and 15 patients with 3 to 4 new admissions every 24 hours, with 1 to 2 of these admissions occurring during the evening and night shifts, on average. The day shift started at 7:45 _am and ended at 7:45 _pm, at which time the day teams transitioned care of their patients to 1 of 2 overnight NP/PAs who provided cross‐cover for all teams through the night. The overnight NP/PAs then transitioned care back to the day teams at 7:45 _am the following morning.

Figure 1

Two evening‐shift providers, both physicians, including a staff hospitalist and a hospital medicine fellowship trainee, admitted patients without any cross‐cover responsibility. Their shifts had the same start time, but staggered end times (2 _pm10 _pm and 2 _pmmidnight). At the end of their shifts, the evening‐shift providers relayed concerns or items for follow‐up to the night cross‐cover NP/PAs; however, this handoff was nonstandardized and provider dependent. The cross‐cover providers could also choose to pass on any relevant information to day‐shift providers if thought to be necessary, but this, again, was not required or standardized. A printed electronic handoff tool (including the patient's problem list, medications, vital signs, laboratory results, and to do list as determined by the admitting provider) as well as all clinical notes generated since admission were made available to day‐shift providers who assumed care at 7:45 _am; however, there was no face‐to‐face handoff between the evening‐ and day‐shift providers.

Two night‐shift physicians, including a moonlighting board‐eligible internal medicine physician and staff hospitalist, also started at staggered times, 6:45 _pm and 10 _pm, but their shifts both ended at 7:45 _am. These physicians also admitted patients without cross‐cover responsibilities. At 7:45 _am, in a face‐to‐face meeting, they transitioned care of patients admitted overnight to day‐shift providers. This handoff occurred at a predesignated place with assigned start times for each team. During the meeting, printed electronic documents, including the aforementioned electronic handoff tool as well as all clinical notes generated since admission, were made available to the oncoming day‐shift providers. The face‐to‐face interaction between night‐ and day‐shift providers lasted approximately 5 minutes and allowed for a brief presentation of the patient, review of the diagnostic testing and treatments performed so far, as well as anticipatory guidance regarding potential issues throughout the remainder of the hospitalization. Although inclusion of the above components was encouraged during the face‐to‐face handoff, the interaction was not scripted and topics discussed were at the providers' discretion.

Patients admitted during the evening and night shifts were assigned to day‐shift services primarily based on the current census of each team, so as to distribute the workload evenly.

RESULTS

Of 805 patients admitted between 6:45 _pm and midnight during the study period, 305 (37.9%) patients were handed off to day‐shift providers without face‐to‐face handoff, and 500 (62.1%) patients were transferred to the care of day‐shift providers with the use of a face‐to‐face handoff.

Baseline characteristics of both groups are depicted in Table 1. Demographic characteristics, including age, gender, and race, were not significantly different between groups. The mean Charlson Comorbidity Index score was not significantly different between the groups without and with a face‐to‐face handoff. In addition, the presence of medical comorbidities including type 2 diabetes mellitus, hypertension, coronary artery disease, hyperlipidemia, heart failure, body mass index (BMI) <18, active cancer, and current cigarette smoking were not significantly different between the 2 groups. There was a trend to a significantly increased proportion of patients with a BMI >30 in the group without face‐to‐face handoff (P=0.05).

Results for the outcomes of this study are depicted in Table 2. The frequency of rapid response team calls, code team calls, transfers to a higher level of care, and death in the hospital in the 12 hours following the first morning handoff of the admission were not significantly different between the 2 groups. Both 30‐day readmission rate and LOS (median and mean) were not significantly different between groups.

There was no significant difference between the 2 groups in the frequency of adverse events resulting in harm for any of the categories (categories EI). Total adverse events between groups were also compared. Adverse events per 100 admissions were not significantly different between the group without face‐to‐face handoff compared to the group with face‐to‐face handoff. The percentage of admissions with an adverse event was also similar between groups.

DISCUSSION

We found no significant difference in the rate of rapid response team calls, code team calls, transfers to a higher level of care, death in hospital, or adverse events when comparing patients transitioned to the care of day‐shift providers with or without a face‐to‐face handoff. We hypothesize that a reason adverse events were no different between the 2 groups may be that providers were more vigilant when they did not receive a face‐to‐face handoff from the previous provider. As a result, providers may have dedicated additional time reviewing the medical record, speaking with the patients, and communicating with other healthcare providers to ensure a safe care transition. Similarly, other studies found no significant reduction in adverse events when using a standardized handoff.[10, 13, 29] This may be because patient handoff is 1 of a multitude of factors that impact the rate of adverse events, and a handoff may play a less vital role in a system where documentation of care for a given patient is readily accessible, uniform, and detailed. A face‐to‐face interaction itself in a patient handoff may be less pertinent if key information can be communicated through other channels, such as an electronic handoff tool, email, or phone.

Another potential explanation for the lack of a significant difference in patient outcomes with and without a face‐to‐face handoff is related to the study design and inherent rate of the events measured. With the exception of 30‐day readmission rate and LOS, the outcomes of the study were recorded only if they occurred in the 12 hours following the first morning handoff of the admission. This was done in an attempt to isolate the effect of the nonface‐to‐face versus face‐to‐face handoff on the first morning of the admission, and to avoid confounding effects by subsequent transitions of care later in the hospitalization. The frequency of hospital admissions in which an adverse event occurred during this relatively short 12‐hour window was approximately 3% for all patients in the study. With 805 total patients in the study, there may have been insufficient statistical power to detect a difference in the rate of outcomes, if a difference did exist, considering the event rate for both groups and the sample size.

There are several additional limitations to our study. First, the GTT was designed to be applied across the entirety of a hospitalization. By screening for adverse events over the span of only 12 hours for each hospitalization, the sensitivity of the tool may have been diminished, with a proportion of adverse events not captured, even when the sequence of events leading to patient harm began during the 12 hours in question. Second, this is a retrospective study, and all adverse events may not be documented in the medical record. Third, although not formally structured and infrequent, some evening‐shift providers did send an email or call the oncoming day‐shift provider to discuss patients admitted. This process, however, was provider dependent, unstructured, uncommon, and erratic, and thus we were not able to capture it from medical record review. Finally, the patients in this study were deemed low acuity upon triage prior to admission. A face‐to‐face handoff may be less important in ensuring patient safety when caring for low‐acuity compared to high‐acuity patients, considering the rapidity at which the critically ill can deteriorate.

Handoffs of patient care in the hospital have certainly increased in recent years. Consequently, communication among providers is undoubtedly important, with patient safety being the primary goal. Our work suggests that a face‐to‐face component of a handoff is not vital to ensure a safe care transition. Because of the increasing frequency of handoffs, providers' ability to do so face‐to‐face will likely be challenged by time and logistical constraints. Future work is needed to delineate the most effective components of the handoff so that we can design information transfer that promotes safe and efficient care, even without a face‐to‐face interaction.

Handoffs are key events in the care of hospitalized patients whereby vital information is relayed between healthcare providers. Resident duty hour restrictions and the popularity of shift‐based work schedules have increased the frequency of inpatient handoffs.[1, 2] Failures in communication at the time of patient handoff have been implicated as contributing factors to preventable adverse events.[3, 4, 5, 6] With patient safety in mind, accreditation organizations and professional societies have made the standardization of hospital handoff procedures a priority.[7, 8] A variety of strategies have been utilized to standardize handoffs. Examples include the use of mnemonics,[9] electronic resources,[10, 11, 12] preformatted handoff sheets,[13, 14, 15, 16] and optimization of the handoff environment.[17] The primary outcomes for many of these studies center on the provider by measuring their retention of patient facts[18, 19] and completion of tasks[14, 16] after handoff, for example. Few studies examined patient‐centered outcomes such as transfer to a higher level of care,[20] length of stay,[11] mortality,[21] or readmission rate.[22] A study in the pediatric population found that implementation of a handoff bundle was associated with a decrease in medical errors and preventable adverse events.[23]

The Society of Hospital Medicine recommends that patient handoffs consist of both a written and verbal component.[8] Providers in our division work on 3 shifts: day, evening, and night. In 2009, we developed a face‐to‐face morning handoff, during which night‐shift providers hand off patient care to day‐shift providers incorporating an electronically generated service information list.[17] Given that the evening shift ends well before the day shift begins, the evening‐shift providers do not participate in this face‐to‐face handoff of care for patients they admit to day providers.

We wished to compare the clinical outcomes and adverse events of patients admitted by the night‐shift providers to those admitted by the evening‐shift providers. We hypothesized that transfer of care using a face‐to‐face handoff would be associated with fewer adverse events and improved clinical outcomes.

METHODS

The study was deemed exempt by the Mayo Clinic Institutional Review Board.

Setting

The division's shift schedule during the study period is depicted in Figure 1. Day‐shift providers included a physician and nurse practitioner (NP) or physician assistant (PA) on each of 7 teams. Each service had an average daily patient census between 10 and 15 patients with 3 to 4 new admissions every 24 hours, with 1 to 2 of these admissions occurring during the evening and night shifts, on average. The day shift started at 7:45 _am and ended at 7:45 _pm, at which time the day teams transitioned care of their patients to 1 of 2 overnight NP/PAs who provided cross‐cover for all teams through the night. The overnight NP/PAs then transitioned care back to the day teams at 7:45 _am the following morning.

Figure 1

Two evening‐shift providers, both physicians, including a staff hospitalist and a hospital medicine fellowship trainee, admitted patients without any cross‐cover responsibility. Their shifts had the same start time, but staggered end times (2 _pm10 _pm and 2 _pmmidnight). At the end of their shifts, the evening‐shift providers relayed concerns or items for follow‐up to the night cross‐cover NP/PAs; however, this handoff was nonstandardized and provider dependent. The cross‐cover providers could also choose to pass on any relevant information to day‐shift providers if thought to be necessary, but this, again, was not required or standardized. A printed electronic handoff tool (including the patient's problem list, medications, vital signs, laboratory results, and to do list as determined by the admitting provider) as well as all clinical notes generated since admission were made available to day‐shift providers who assumed care at 7:45 _am; however, there was no face‐to‐face handoff between the evening‐ and day‐shift providers.

Two night‐shift physicians, including a moonlighting board‐eligible internal medicine physician and staff hospitalist, also started at staggered times, 6:45 _pm and 10 _pm, but their shifts both ended at 7:45 _am. These physicians also admitted patients without cross‐cover responsibilities. At 7:45 _am, in a face‐to‐face meeting, they transitioned care of patients admitted overnight to day‐shift providers. This handoff occurred at a predesignated place with assigned start times for each team. During the meeting, printed electronic documents, including the aforementioned electronic handoff tool as well as all clinical notes generated since admission, were made available to the oncoming day‐shift providers. The face‐to‐face interaction between night‐ and day‐shift providers lasted approximately 5 minutes and allowed for a brief presentation of the patient, review of the diagnostic testing and treatments performed so far, as well as anticipatory guidance regarding potential issues throughout the remainder of the hospitalization. Although inclusion of the above components was encouraged during the face‐to‐face handoff, the interaction was not scripted and topics discussed were at the providers' discretion.

Patients admitted during the evening and night shifts were assigned to day‐shift services primarily based on the current census of each team, so as to distribute the workload evenly.

RESULTS

Of 805 patients admitted between 6:45 _pm and midnight during the study period, 305 (37.9%) patients were handed off to day‐shift providers without face‐to‐face handoff, and 500 (62.1%) patients were transferred to the care of day‐shift providers with the use of a face‐to‐face handoff.

Baseline characteristics of both groups are depicted in Table 1. Demographic characteristics, including age, gender, and race, were not significantly different between groups. The mean Charlson Comorbidity Index score was not significantly different between the groups without and with a face‐to‐face handoff. In addition, the presence of medical comorbidities including type 2 diabetes mellitus, hypertension, coronary artery disease, hyperlipidemia, heart failure, body mass index (BMI) <18, active cancer, and current cigarette smoking were not significantly different between the 2 groups. There was a trend to a significantly increased proportion of patients with a BMI >30 in the group without face‐to‐face handoff (P=0.05).

Results for the outcomes of this study are depicted in Table 2. The frequency of rapid response team calls, code team calls, transfers to a higher level of care, and death in the hospital in the 12 hours following the first morning handoff of the admission were not significantly different between the 2 groups. Both 30‐day readmission rate and LOS (median and mean) were not significantly different between groups.

There was no significant difference between the 2 groups in the frequency of adverse events resulting in harm for any of the categories (categories EI). Total adverse events between groups were also compared. Adverse events per 100 admissions were not significantly different between the group without face‐to‐face handoff compared to the group with face‐to‐face handoff. The percentage of admissions with an adverse event was also similar between groups.

DISCUSSION

We found no significant difference in the rate of rapid response team calls, code team calls, transfers to a higher level of care, death in hospital, or adverse events when comparing patients transitioned to the care of day‐shift providers with or without a face‐to‐face handoff. We hypothesize that a reason adverse events were no different between the 2 groups may be that providers were more vigilant when they did not receive a face‐to‐face handoff from the previous provider. As a result, providers may have dedicated additional time reviewing the medical record, speaking with the patients, and communicating with other healthcare providers to ensure a safe care transition. Similarly, other studies found no significant reduction in adverse events when using a standardized handoff.[10, 13, 29] This may be because patient handoff is 1 of a multitude of factors that impact the rate of adverse events, and a handoff may play a less vital role in a system where documentation of care for a given patient is readily accessible, uniform, and detailed. A face‐to‐face interaction itself in a patient handoff may be less pertinent if key information can be communicated through other channels, such as an electronic handoff tool, email, or phone.

Another potential explanation for the lack of a significant difference in patient outcomes with and without a face‐to‐face handoff is related to the study design and inherent rate of the events measured. With the exception of 30‐day readmission rate and LOS, the outcomes of the study were recorded only if they occurred in the 12 hours following the first morning handoff of the admission. This was done in an attempt to isolate the effect of the nonface‐to‐face versus face‐to‐face handoff on the first morning of the admission, and to avoid confounding effects by subsequent transitions of care later in the hospitalization. The frequency of hospital admissions in which an adverse event occurred during this relatively short 12‐hour window was approximately 3% for all patients in the study. With 805 total patients in the study, there may have been insufficient statistical power to detect a difference in the rate of outcomes, if a difference did exist, considering the event rate for both groups and the sample size.

There are several additional limitations to our study. First, the GTT was designed to be applied across the entirety of a hospitalization. By screening for adverse events over the span of only 12 hours for each hospitalization, the sensitivity of the tool may have been diminished, with a proportion of adverse events not captured, even when the sequence of events leading to patient harm began during the 12 hours in question. Second, this is a retrospective study, and all adverse events may not be documented in the medical record. Third, although not formally structured and infrequent, some evening‐shift providers did send an email or call the oncoming day‐shift provider to discuss patients admitted. This process, however, was provider dependent, unstructured, uncommon, and erratic, and thus we were not able to capture it from medical record review. Finally, the patients in this study were deemed low acuity upon triage prior to admission. A face‐to‐face handoff may be less important in ensuring patient safety when caring for low‐acuity compared to high‐acuity patients, considering the rapidity at which the critically ill can deteriorate.

Handoffs of patient care in the hospital have certainly increased in recent years. Consequently, communication among providers is undoubtedly important, with patient safety being the primary goal. Our work suggests that a face‐to‐face component of a handoff is not vital to ensure a safe care transition. Because of the increasing frequency of handoffs, providers' ability to do so face‐to‐face will likely be challenged by time and logistical constraints. Future work is needed to delineate the most effective components of the handoff so that we can design information transfer that promotes safe and efficient care, even without a face‐to‐face interaction.

Many patients are admitted and readmitted to acute care hospitals with alcohol‐related diagnoses, including alcohol withdrawal syndrome (AWS), and experience significant morbidity and mortality. In patients with septic shock or at risk for acute respiratory distress syndrome (ARDS), chronic alcohol abuse is associated with increased ARDS and severity of multiple organ dysfunction.1 Among intensive care unit (ICU) patients, those with alcohol dependence have higher morbidity, including septic shock, and higher hospital mortality.2 Patients who experience AWS as a result of alcohol dependence may experience life‐threatening complications, such as seizures and delirium tremens.3,4 In‐hospital mortality from AWS is historically high,5 but with benzodiazepines used in a symptom‐driven manner to treat the complications of alcohol use, hospital mortality rates are more recently reported at 2.4%.6

As inpatient outcomes1,2,7 and hospital mortality810 are negatively affected by alcohol abuse, the post‐hospital course of these patients is also of interest. Specifically, patients are often admitted and readmitted with alcohol‐related diagnoses or AWS to acute care hospitals, but relatively little quantitative data exist on readmission factors in this population.11 Patients readmitted to detoxification units or alcohol and substance abuse units have been studied, and factors associated with readmission include psychiatric disorder,1217 female gender,14,15 and delay in rehabilitation aftercare.18

These results cannot be generalized to patients with AWS who are admitted and readmitted to acute‐care hospitals. First, patients hospitalized for alcohol withdrawal symptoms are often medically ill with more severe symptoms, and more frequent coexisting medical and psychiatric illnesses, that complicate the withdrawal syndrome. Detoxification units and substance abuse units require patients to be medically stable before admission, because they do not have the ability to provide a high level of supervision and treatment. Second, much of what we know regarding risk factors for readmission to detoxification centers and substance abuse units comes from studies of administrative data of the Veterans Health Administration,12,13 Medicare Provider Analysis and Review file,16 privately owned outpatient substance abuse centers,14 and publicly funded detoxification centers.18 These results may be difficult to generalize to other patient populations. Accordingly, the objective of this study was to identify demographic and clinical factors associated with multiple admissions to a general medicine service for treatment of AWS over a 3‐year period. Characterization of these high‐risk patients and their hospital course may help focus intervention and reduce these revolving door admissions.

METHODS

The Mayo Clinic Institutional Review Board deemed the study exempt.

Patient Selection

The study was conducted at an 1157‐bed academic tertiary referral hospital, located in the Midwest, that has approximately 15,000 inpatient admissions to general medicine services annually and serves as the main referral center for the region. Patients included in this study were adults admitted to general medicine services and treated with symptom‐triggered Clinical Institute Withdrawal AssessmentAlcohol Revised (CIWA‐Ar) protocol19 between January 1, 2006 and December 31, 2008. Patients were identified using the Mayo Clinic Quality Improvement Resource Center database, as done in a previous CIWA‐Ar study.20 Patients were excluded if the primary diagnosis was a nonalcohol‐related diagnosis (Figure 1).

Figure 1

Patients were placed in 1 of 2 groups based on number of admissions during the study period, either a single‐admission group or a multiple‐admissions group. While most readmission studies use a 30‐day mark from discharge, we used 3 years to better capture relapse and recidivism in this patient population. The 2 groups were then compared retrospectively. To insure that a single admission was not arbitrarily created by the December 2008 cutoff, we reviewed the single‐admission group for additional admissions through June of 2009. If a patient did have a subsequent admission, then the patient was moved to the multiple‐admissions group.

RESULTS

The CIWA‐Ar protocol was ordered on 1199 admissions during the study period. Of these, 411 (34.3%) admissions were excluded because AWS was not the primary diagnosis, leaving 788 (65.7%) admissions for 322 patients, which formed the study population. Of the 322 patients, 180 (56%) had a single admission and 142 (44%) had multiple admissions.

Univariate analyses of demographic and clinical variables are shown in Tables 1 and 2, respectively. Patients with multiple admissions were more likely divorced (P = 0.028), have a high school education or less (P = 0.002), have a higher CCI score (P < 0.0001), a higher CIWA‐Ar score (max) (P < 0.0001), a higher ALT level (P = 0.050), more psychiatric comorbidity (P < 0.026), and a positive urine drug screen (P < 0.001). Adverse events were not significantly different between the 2 groups (Table 2).

Multivariate logistic model analysis was performed using the variables age, male gender, divorced marital status, high school education or less, CIWA‐Ar score (max), CCI score, psychiatric comorbidity, and positive urine drug screen. With a stepwise elimination process, the final model showed that multiple admissions were associated with high school education or less (P = 0.0071), higher CCI score (P = 0.0010), higher CIWA‐Ar score (max) (P < 0.0001), a positive urine drug screen (P = 0.0002), and psychiatric comorbidity (P = 0.0303) (Table 3).

DISCUSSION

We provide important information regarding identification of individuals at high risk for multiple admissions to general medicine services for treatment of AWS. This study found that patients with multiple admissions for AWS had more medical comorbidity. They had more cases of diabetes mellitus, cardiovascular disease, and cerebrovascular disease, and their CCI scores were higher. They also had higher CIWA‐Ar (max) scores, as well as higher CIWA‐Ar component scores, indicating a more severe withdrawal.

Further, psychiatric comorbidity was also associated with multiple admissions. Consistent with the high prevalence in alcoholic patients, psychiatric comorbidity was common in both patients with a single admission and multiple admissions. We also found that a positive urine drug screen was associated with multiple admissions. Interestingly, few patients in each group had a diagnosis recorded in the medical record of an additional substance abuse disorder, yet 14% of patients with a single admission and 29% of patients with multiple admissions had a positive urine drug screen for a non‐alcohol substance. Psychiatric comorbidity, including additional substance abuse, is a well‐established risk factor for readmission to detoxification centers.1215, 17,22,23 Also, people with either an alcohol or non‐alcohol drug addiction, are known to be 7 times more likely to have another addiction than the rest of the population.24 This study suggests clinicians may underrecognize additional substance abuse disorders which are common in this patient population.

In contrast to studies of patients readmitted to detoxification units and substance abuse units,14,15,18,22 we found level of education, specifically a high school education or less, to be associated with multiple admissions. In a study of alcoholics, Greenfield and colleagues found that lower education in alcoholics predicts shorter time to relapse.25 A lack of education may result in inadequate healthcare literacy. Poor health behavior choices that follow may lead to relapse and subsequent admissions for AWS. With respect to other demographic variables, patients in our study population were predominantly men, which is not surprising. Gender differences in alcoholism are well established, with alcohol abuse and dependence more prevalent in men.26 We did not find gender associated with multiple admissions.

Our findings have management and treatment implications. First, providers who care for patients with AWS should not simply focus on treating withdrawal signs and symptoms, but also screen for and address other medical issues, which may not be apparent or seem stable at first glance. While a comorbid medical condition may not be the primary reason for hospital admission, comorbid medical conditions are known to be a source of psychological distress27 and have a negative effect on abstinence. Second, all patients should be screened for additional substance abuse. Initial laboratory testing should include a urine drug screen. Third, before discharging the patient, providers should establish primary care follow‐up for continued surveillance of medical issues. There is evidence that primary care services are predictive of better substance abuse treatment outcomes for those with medical problems.28,29

Finally, inpatient psychiatric consultation, upon admission, is essential for several reasons. First, the psychiatric team can help with initial management and treatment of the alcohol withdrawal regardless of stage and severity, obtain a more comprehensive psychiatric history, and assess for the presence of psychiatric comorbidities that may contribute to, aggravate, or complicate the clinical picture. The team can also address other substance abuse issues when detected by drug screen or clinical history. The psychiatric team, along with chemical‐dependency counselors and social workers, can provide valuable input regarding chemical‐dependency resources available on discharge and help instruct the patient in healthy behaviors. Because healthcare illiteracy may be an issue in this patient population, these instructions should be tailored to the patient's educational level. Prior to discharge, the psychiatry team, social workers, or chemical‐dependency counselors can also assist with, or arrange, rehabilitation aftercare for patients. Recent work shows that patients were less likely to be readmitted to crisis detoxification if they entered rehabilitation care within 3 days of discharge.18

Our study has significant limitations. This study was performed with data at a single academic medical center with an ethnically homogeneous patient population, limiting the external validity of its results. Because this is a retrospective study, data analyses are limited by the quality and accuracy of data in the electronic medical record. Also, our follow‐up period may not have been long enough to detect additional admissions, and we did not screen for patient admissions prior to the study period. By limiting data collection to admissions for AWS to general medical services, we may have missed cases of AWS when admitted for other reasons or to subspecialty services, and we may have missed severe cases requiring admission to an intensive care unit. While we believe we were able to capture most admissions, we may underreport this number since we cannot account for those events that may have occurred at other facilities and locations. Lastly, without a control group, this study is limited in its ability to show an association between any variable and readmission.

In our study, 142 patients accounted for 608 admissions during the 3‐year study period, which speaks to the high recidivism rates for patients with AWS. This disease is associated with high morbidity, high medical costs, and high utilization of healthcare. Our study provides insight regarding identification of patients at high risk of multiple admissions with respect to demographic (lower level of education) and clinical characteristics (worse withdrawal severity, more medical and psychiatric comorbidity, and polysubstance abuse). We believe collaboration between social services, chemical‐dependency counselors, psychiatry, and medicine is necessary to effectively treat this population of patients and assist with the crucial transition to the outpatient setting. Future studies should include key social factors, such as health literacy in the readmission risk assessment, as well as primary care follow‐up and rehabilitation aftercare.

Many patients are admitted and readmitted to acute care hospitals with alcohol‐related diagnoses, including alcohol withdrawal syndrome (AWS), and experience significant morbidity and mortality. In patients with septic shock or at risk for acute respiratory distress syndrome (ARDS), chronic alcohol abuse is associated with increased ARDS and severity of multiple organ dysfunction.1 Among intensive care unit (ICU) patients, those with alcohol dependence have higher morbidity, including septic shock, and higher hospital mortality.2 Patients who experience AWS as a result of alcohol dependence may experience life‐threatening complications, such as seizures and delirium tremens.3,4 In‐hospital mortality from AWS is historically high,5 but with benzodiazepines used in a symptom‐driven manner to treat the complications of alcohol use, hospital mortality rates are more recently reported at 2.4%.6

As inpatient outcomes1,2,7 and hospital mortality810 are negatively affected by alcohol abuse, the post‐hospital course of these patients is also of interest. Specifically, patients are often admitted and readmitted with alcohol‐related diagnoses or AWS to acute care hospitals, but relatively little quantitative data exist on readmission factors in this population.11 Patients readmitted to detoxification units or alcohol and substance abuse units have been studied, and factors associated with readmission include psychiatric disorder,1217 female gender,14,15 and delay in rehabilitation aftercare.18

These results cannot be generalized to patients with AWS who are admitted and readmitted to acute‐care hospitals. First, patients hospitalized for alcohol withdrawal symptoms are often medically ill with more severe symptoms, and more frequent coexisting medical and psychiatric illnesses, that complicate the withdrawal syndrome. Detoxification units and substance abuse units require patients to be medically stable before admission, because they do not have the ability to provide a high level of supervision and treatment. Second, much of what we know regarding risk factors for readmission to detoxification centers and substance abuse units comes from studies of administrative data of the Veterans Health Administration,12,13 Medicare Provider Analysis and Review file,16 privately owned outpatient substance abuse centers,14 and publicly funded detoxification centers.18 These results may be difficult to generalize to other patient populations. Accordingly, the objective of this study was to identify demographic and clinical factors associated with multiple admissions to a general medicine service for treatment of AWS over a 3‐year period. Characterization of these high‐risk patients and their hospital course may help focus intervention and reduce these revolving door admissions.

METHODS

The Mayo Clinic Institutional Review Board deemed the study exempt.

Patient Selection

The study was conducted at an 1157‐bed academic tertiary referral hospital, located in the Midwest, that has approximately 15,000 inpatient admissions to general medicine services annually and serves as the main referral center for the region. Patients included in this study were adults admitted to general medicine services and treated with symptom‐triggered Clinical Institute Withdrawal AssessmentAlcohol Revised (CIWA‐Ar) protocol19 between January 1, 2006 and December 31, 2008. Patients were identified using the Mayo Clinic Quality Improvement Resource Center database, as done in a previous CIWA‐Ar study.20 Patients were excluded if the primary diagnosis was a nonalcohol‐related diagnosis (Figure 1).

Figure 1

Patients were placed in 1 of 2 groups based on number of admissions during the study period, either a single‐admission group or a multiple‐admissions group. While most readmission studies use a 30‐day mark from discharge, we used 3 years to better capture relapse and recidivism in this patient population. The 2 groups were then compared retrospectively. To insure that a single admission was not arbitrarily created by the December 2008 cutoff, we reviewed the single‐admission group for additional admissions through June of 2009. If a patient did have a subsequent admission, then the patient was moved to the multiple‐admissions group.

RESULTS

The CIWA‐Ar protocol was ordered on 1199 admissions during the study period. Of these, 411 (34.3%) admissions were excluded because AWS was not the primary diagnosis, leaving 788 (65.7%) admissions for 322 patients, which formed the study population. Of the 322 patients, 180 (56%) had a single admission and 142 (44%) had multiple admissions.

Univariate analyses of demographic and clinical variables are shown in Tables 1 and 2, respectively. Patients with multiple admissions were more likely divorced (P = 0.028), have a high school education or less (P = 0.002), have a higher CCI score (P < 0.0001), a higher CIWA‐Ar score (max) (P < 0.0001), a higher ALT level (P = 0.050), more psychiatric comorbidity (P < 0.026), and a positive urine drug screen (P < 0.001). Adverse events were not significantly different between the 2 groups (Table 2).

Multivariate logistic model analysis was performed using the variables age, male gender, divorced marital status, high school education or less, CIWA‐Ar score (max), CCI score, psychiatric comorbidity, and positive urine drug screen. With a stepwise elimination process, the final model showed that multiple admissions were associated with high school education or less (P = 0.0071), higher CCI score (P = 0.0010), higher CIWA‐Ar score (max) (P < 0.0001), a positive urine drug screen (P = 0.0002), and psychiatric comorbidity (P = 0.0303) (Table 3).

DISCUSSION

We provide important information regarding identification of individuals at high risk for multiple admissions to general medicine services for treatment of AWS. This study found that patients with multiple admissions for AWS had more medical comorbidity. They had more cases of diabetes mellitus, cardiovascular disease, and cerebrovascular disease, and their CCI scores were higher. They also had higher CIWA‐Ar (max) scores, as well as higher CIWA‐Ar component scores, indicating a more severe withdrawal.

Further, psychiatric comorbidity was also associated with multiple admissions. Consistent with the high prevalence in alcoholic patients, psychiatric comorbidity was common in both patients with a single admission and multiple admissions. We also found that a positive urine drug screen was associated with multiple admissions. Interestingly, few patients in each group had a diagnosis recorded in the medical record of an additional substance abuse disorder, yet 14% of patients with a single admission and 29% of patients with multiple admissions had a positive urine drug screen for a non‐alcohol substance. Psychiatric comorbidity, including additional substance abuse, is a well‐established risk factor for readmission to detoxification centers.1215, 17,22,23 Also, people with either an alcohol or non‐alcohol drug addiction, are known to be 7 times more likely to have another addiction than the rest of the population.24 This study suggests clinicians may underrecognize additional substance abuse disorders which are common in this patient population.

In contrast to studies of patients readmitted to detoxification units and substance abuse units,14,15,18,22 we found level of education, specifically a high school education or less, to be associated with multiple admissions. In a study of alcoholics, Greenfield and colleagues found that lower education in alcoholics predicts shorter time to relapse.25 A lack of education may result in inadequate healthcare literacy. Poor health behavior choices that follow may lead to relapse and subsequent admissions for AWS. With respect to other demographic variables, patients in our study population were predominantly men, which is not surprising. Gender differences in alcoholism are well established, with alcohol abuse and dependence more prevalent in men.26 We did not find gender associated with multiple admissions.

Our findings have management and treatment implications. First, providers who care for patients with AWS should not simply focus on treating withdrawal signs and symptoms, but also screen for and address other medical issues, which may not be apparent or seem stable at first glance. While a comorbid medical condition may not be the primary reason for hospital admission, comorbid medical conditions are known to be a source of psychological distress27 and have a negative effect on abstinence. Second, all patients should be screened for additional substance abuse. Initial laboratory testing should include a urine drug screen. Third, before discharging the patient, providers should establish primary care follow‐up for continued surveillance of medical issues. There is evidence that primary care services are predictive of better substance abuse treatment outcomes for those with medical problems.28,29

Finally, inpatient psychiatric consultation, upon admission, is essential for several reasons. First, the psychiatric team can help with initial management and treatment of the alcohol withdrawal regardless of stage and severity, obtain a more comprehensive psychiatric history, and assess for the presence of psychiatric comorbidities that may contribute to, aggravate, or complicate the clinical picture. The team can also address other substance abuse issues when detected by drug screen or clinical history. The psychiatric team, along with chemical‐dependency counselors and social workers, can provide valuable input regarding chemical‐dependency resources available on discharge and help instruct the patient in healthy behaviors. Because healthcare illiteracy may be an issue in this patient population, these instructions should be tailored to the patient's educational level. Prior to discharge, the psychiatry team, social workers, or chemical‐dependency counselors can also assist with, or arrange, rehabilitation aftercare for patients. Recent work shows that patients were less likely to be readmitted to crisis detoxification if they entered rehabilitation care within 3 days of discharge.18

Our study has significant limitations. This study was performed with data at a single academic medical center with an ethnically homogeneous patient population, limiting the external validity of its results. Because this is a retrospective study, data analyses are limited by the quality and accuracy of data in the electronic medical record. Also, our follow‐up period may not have been long enough to detect additional admissions, and we did not screen for patient admissions prior to the study period. By limiting data collection to admissions for AWS to general medical services, we may have missed cases of AWS when admitted for other reasons or to subspecialty services, and we may have missed severe cases requiring admission to an intensive care unit. While we believe we were able to capture most admissions, we may underreport this number since we cannot account for those events that may have occurred at other facilities and locations. Lastly, without a control group, this study is limited in its ability to show an association between any variable and readmission.

In our study, 142 patients accounted for 608 admissions during the 3‐year study period, which speaks to the high recidivism rates for patients with AWS. This disease is associated with high morbidity, high medical costs, and high utilization of healthcare. Our study provides insight regarding identification of patients at high risk of multiple admissions with respect to demographic (lower level of education) and clinical characteristics (worse withdrawal severity, more medical and psychiatric comorbidity, and polysubstance abuse). We believe collaboration between social services, chemical‐dependency counselors, psychiatry, and medicine is necessary to effectively treat this population of patients and assist with the crucial transition to the outpatient setting. Future studies should include key social factors, such as health literacy in the readmission risk assessment, as well as primary care follow‐up and rehabilitation aftercare.

Many patients are admitted and readmitted to acute care hospitals with alcohol‐related diagnoses, including alcohol withdrawal syndrome (AWS), and experience significant morbidity and mortality. In patients with septic shock or at risk for acute respiratory distress syndrome (ARDS), chronic alcohol abuse is associated with increased ARDS and severity of multiple organ dysfunction.1 Among intensive care unit (ICU) patients, those with alcohol dependence have higher morbidity, including septic shock, and higher hospital mortality.2 Patients who experience AWS as a result of alcohol dependence may experience life‐threatening complications, such as seizures and delirium tremens.3,4 In‐hospital mortality from AWS is historically high,5 but with benzodiazepines used in a symptom‐driven manner to treat the complications of alcohol use, hospital mortality rates are more recently reported at 2.4%.6

As inpatient outcomes1,2,7 and hospital mortality810 are negatively affected by alcohol abuse, the post‐hospital course of these patients is also of interest. Specifically, patients are often admitted and readmitted with alcohol‐related diagnoses or AWS to acute care hospitals, but relatively little quantitative data exist on readmission factors in this population.11 Patients readmitted to detoxification units or alcohol and substance abuse units have been studied, and factors associated with readmission include psychiatric disorder,1217 female gender,14,15 and delay in rehabilitation aftercare.18

These results cannot be generalized to patients with AWS who are admitted and readmitted to acute‐care hospitals. First, patients hospitalized for alcohol withdrawal symptoms are often medically ill with more severe symptoms, and more frequent coexisting medical and psychiatric illnesses, that complicate the withdrawal syndrome. Detoxification units and substance abuse units require patients to be medically stable before admission, because they do not have the ability to provide a high level of supervision and treatment. Second, much of what we know regarding risk factors for readmission to detoxification centers and substance abuse units comes from studies of administrative data of the Veterans Health Administration,12,13 Medicare Provider Analysis and Review file,16 privately owned outpatient substance abuse centers,14 and publicly funded detoxification centers.18 These results may be difficult to generalize to other patient populations. Accordingly, the objective of this study was to identify demographic and clinical factors associated with multiple admissions to a general medicine service for treatment of AWS over a 3‐year period. Characterization of these high‐risk patients and their hospital course may help focus intervention and reduce these revolving door admissions.

METHODS

The Mayo Clinic Institutional Review Board deemed the study exempt.

Patient Selection

The study was conducted at an 1157‐bed academic tertiary referral hospital, located in the Midwest, that has approximately 15,000 inpatient admissions to general medicine services annually and serves as the main referral center for the region. Patients included in this study were adults admitted to general medicine services and treated with symptom‐triggered Clinical Institute Withdrawal AssessmentAlcohol Revised (CIWA‐Ar) protocol19 between January 1, 2006 and December 31, 2008. Patients were identified using the Mayo Clinic Quality Improvement Resource Center database, as done in a previous CIWA‐Ar study.20 Patients were excluded if the primary diagnosis was a nonalcohol‐related diagnosis (Figure 1).

Figure 1

Patients were placed in 1 of 2 groups based on number of admissions during the study period, either a single‐admission group or a multiple‐admissions group. While most readmission studies use a 30‐day mark from discharge, we used 3 years to better capture relapse and recidivism in this patient population. The 2 groups were then compared retrospectively. To insure that a single admission was not arbitrarily created by the December 2008 cutoff, we reviewed the single‐admission group for additional admissions through June of 2009. If a patient did have a subsequent admission, then the patient was moved to the multiple‐admissions group.

RESULTS

The CIWA‐Ar protocol was ordered on 1199 admissions during the study period. Of these, 411 (34.3%) admissions were excluded because AWS was not the primary diagnosis, leaving 788 (65.7%) admissions for 322 patients, which formed the study population. Of the 322 patients, 180 (56%) had a single admission and 142 (44%) had multiple admissions.

Univariate analyses of demographic and clinical variables are shown in Tables 1 and 2, respectively. Patients with multiple admissions were more likely divorced (P = 0.028), have a high school education or less (P = 0.002), have a higher CCI score (P < 0.0001), a higher CIWA‐Ar score (max) (P < 0.0001), a higher ALT level (P = 0.050), more psychiatric comorbidity (P < 0.026), and a positive urine drug screen (P < 0.001). Adverse events were not significantly different between the 2 groups (Table 2).

Multivariate logistic model analysis was performed using the variables age, male gender, divorced marital status, high school education or less, CIWA‐Ar score (max), CCI score, psychiatric comorbidity, and positive urine drug screen. With a stepwise elimination process, the final model showed that multiple admissions were associated with high school education or less (P = 0.0071), higher CCI score (P = 0.0010), higher CIWA‐Ar score (max) (P < 0.0001), a positive urine drug screen (P = 0.0002), and psychiatric comorbidity (P = 0.0303) (Table 3).

DISCUSSION

We provide important information regarding identification of individuals at high risk for multiple admissions to general medicine services for treatment of AWS. This study found that patients with multiple admissions for AWS had more medical comorbidity. They had more cases of diabetes mellitus, cardiovascular disease, and cerebrovascular disease, and their CCI scores were higher. They also had higher CIWA‐Ar (max) scores, as well as higher CIWA‐Ar component scores, indicating a more severe withdrawal.

Further, psychiatric comorbidity was also associated with multiple admissions. Consistent with the high prevalence in alcoholic patients, psychiatric comorbidity was common in both patients with a single admission and multiple admissions. We also found that a positive urine drug screen was associated with multiple admissions. Interestingly, few patients in each group had a diagnosis recorded in the medical record of an additional substance abuse disorder, yet 14% of patients with a single admission and 29% of patients with multiple admissions had a positive urine drug screen for a non‐alcohol substance. Psychiatric comorbidity, including additional substance abuse, is a well‐established risk factor for readmission to detoxification centers.1215, 17,22,23 Also, people with either an alcohol or non‐alcohol drug addiction, are known to be 7 times more likely to have another addiction than the rest of the population.24 This study suggests clinicians may underrecognize additional substance abuse disorders which are common in this patient population.

In contrast to studies of patients readmitted to detoxification units and substance abuse units,14,15,18,22 we found level of education, specifically a high school education or less, to be associated with multiple admissions. In a study of alcoholics, Greenfield and colleagues found that lower education in alcoholics predicts shorter time to relapse.25 A lack of education may result in inadequate healthcare literacy. Poor health behavior choices that follow may lead to relapse and subsequent admissions for AWS. With respect to other demographic variables, patients in our study population were predominantly men, which is not surprising. Gender differences in alcoholism are well established, with alcohol abuse and dependence more prevalent in men.26 We did not find gender associated with multiple admissions.

Our findings have management and treatment implications. First, providers who care for patients with AWS should not simply focus on treating withdrawal signs and symptoms, but also screen for and address other medical issues, which may not be apparent or seem stable at first glance. While a comorbid medical condition may not be the primary reason for hospital admission, comorbid medical conditions are known to be a source of psychological distress27 and have a negative effect on abstinence. Second, all patients should be screened for additional substance abuse. Initial laboratory testing should include a urine drug screen. Third, before discharging the patient, providers should establish primary care follow‐up for continued surveillance of medical issues. There is evidence that primary care services are predictive of better substance abuse treatment outcomes for those with medical problems.28,29

Finally, inpatient psychiatric consultation, upon admission, is essential for several reasons. First, the psychiatric team can help with initial management and treatment of the alcohol withdrawal regardless of stage and severity, obtain a more comprehensive psychiatric history, and assess for the presence of psychiatric comorbidities that may contribute to, aggravate, or complicate the clinical picture. The team can also address other substance abuse issues when detected by drug screen or clinical history. The psychiatric team, along with chemical‐dependency counselors and social workers, can provide valuable input regarding chemical‐dependency resources available on discharge and help instruct the patient in healthy behaviors. Because healthcare illiteracy may be an issue in this patient population, these instructions should be tailored to the patient's educational level. Prior to discharge, the psychiatry team, social workers, or chemical‐dependency counselors can also assist with, or arrange, rehabilitation aftercare for patients. Recent work shows that patients were less likely to be readmitted to crisis detoxification if they entered rehabilitation care within 3 days of discharge.18

Our study has significant limitations. This study was performed with data at a single academic medical center with an ethnically homogeneous patient population, limiting the external validity of its results. Because this is a retrospective study, data analyses are limited by the quality and accuracy of data in the electronic medical record. Also, our follow‐up period may not have been long enough to detect additional admissions, and we did not screen for patient admissions prior to the study period. By limiting data collection to admissions for AWS to general medical services, we may have missed cases of AWS when admitted for other reasons or to subspecialty services, and we may have missed severe cases requiring admission to an intensive care unit. While we believe we were able to capture most admissions, we may underreport this number since we cannot account for those events that may have occurred at other facilities and locations. Lastly, without a control group, this study is limited in its ability to show an association between any variable and readmission.

In our study, 142 patients accounted for 608 admissions during the 3‐year study period, which speaks to the high recidivism rates for patients with AWS. This disease is associated with high morbidity, high medical costs, and high utilization of healthcare. Our study provides insight regarding identification of patients at high risk of multiple admissions with respect to demographic (lower level of education) and clinical characteristics (worse withdrawal severity, more medical and psychiatric comorbidity, and polysubstance abuse). We believe collaboration between social services, chemical‐dependency counselors, psychiatry, and medicine is necessary to effectively treat this population of patients and assist with the crucial transition to the outpatient setting. Future studies should include key social factors, such as health literacy in the readmission risk assessment, as well as primary care follow‐up and rehabilitation aftercare.

Transfer of responsibility for patients, or handoff,1 occurs frequently in hospitalist services, requiring excellent and timely communication to ensure patient safety. Communication failure is a major contributor to medical errors.2, 3 Recognizing such findings, a growing body of literature addresses handoff techniques for learners.47

Vidyarthi described the handoff process as traditionally informal, unstructured, and idiosyncratic,4 and many believe efforts to formalize and structure this process are important for patient safety.8 Standardized handoff forms have improved accuracy of information.9 Web‐based sign‐out systems reportedly reduced the number of patients missed on rounds.10

Hospitalists also face challenges with effective communication during service change.11 The Society of Hospital Medicine identified the handoff skill as a core competency for hospitalists, and recommendations based on a systematic review of the literature were published.12 Inpatient medicine programs are increasingly using midlevel providers such as nurse practitioners (NPs) and physician assistants (PAs) along with hospitalists to accommodate workload while maintaining the scholarly enterprise in academic centers.13 To our knowledge there is no literature examining the hospitalist service handoffs involving NP/PAs.

We wished to study the effectiveness and timeliness of the morning handoff from the night coverage providers to the daytime teams consisting of one hospitalist and one NP/PA. Our objectives were to identify deficiencies and to evaluate the effectiveness of a restructured handoff process.

Methods

The Mayo Clinic Institutional Review Board reviewed and approved this study.

Intervention

The improvement team structured a new handoff process to address these deficiencies.

• 1

  Environment: Moved to a smaller room (lower ceiling, less ambient noise).

• 2

  Identification: table cards designating seats for participants (reduced queries regarding what service are you, today?).

• 3

  Start Times: Each service team assigned a consistent start time (labeled on the table card) within a 15‐minute period, and although earlier reportage could occur, any service team present at their designated time has priority for the attention of the night NP/PA, and the opportunity to ask questions.

• 4

  Quiet and Focus: HIM members were reminded to remain quiet in the handoff room, so the service receiving report has the floor and personal conversations must not impede the principals.

• 5

  Visual Cue: Green Good to go sign placed on team table cards when no verbal was required.

• 6

  Written e‐Material: The improvement team required elements of a brief written report in a specified column of our existing electronic service list (ESL). The ESL is a custom designed template importing laboratory, medication, and demographic data automatically but also capable of free text additions (Figure 1). All providers were instructed to update the ESL every 12 hours.

• 7

  Admission and Progress Notes: After manual electronic medical record search, the CAs printed any notes generated in the preceding 12 hours and placed them by the team table card.

Figure 1

The improvement team provided education for the new process at a division meeting and through e‐mail. The recommended report sequence was night NP/PA reporting and day service teams asking questions and seeking clarifications. We discouraged editorial comments and chit‐chat.

A member of the improvement team monitored the new handoff process for 15 days, and 3 months later for 10 days.

Survey

An anonymous survey (Figure 2) concerning staff satisfaction with handoff was conducted immediately before and 15 days after the intervention. In the e‐mail containing the postintervention survey, providers were asked to respond only if they had been on service the preceding 15 days (and thus eligible to participate in handoff). To help insure this, the first question read, Have you been on service during the past 15 days?

Figure 2

Results

Thirty‐six of the 44 providers (82%) answered the preintervention survey, including 18 of 22 hospitalists (82%), 17 of 20 NPs/PAs (85%), and 1 of 2 CAs (50%). During the intervention based on our staffing model, 21 providers had the opportunity to participate in handoff, and 18 (86%) answered the postintervention survey, including 5 of 6 hospitalists (83%), 9 of 14 NPs/PAs (64%), and 2 of 2 CAs (100%). All respondents to the postintervention survey reported being on service during the previous 15 days.

As summarized in Table 1, compared to 60.5% of survey participants (n = 38) who thought morning handoff was performed in a timely fashion preintervention, 100% (n = 15) felt it was performed in a timely fashion postintervention (P = 0.005). The average time spent in morning report before the intervention was 11 minutes, as compared to 5 minutes after the intervention (P < 0.0028). Prior to the intervention, 6.5 minutes of the handoff were viewed to be wasteful, as compared to 0.5 minutes of the handoff in the postintervention survey (P < 0.0001). Attendance and quality of information perceptions did not demonstrate statistically significant change.

During the 15‐day observation period, morning handoff started by 0745 on 14 of 15 (93%) of days and finished by 0800 on 15 of 15 (100%) of days. Table cards, ESL, and progress notes were on the table by 0745 on 15 of 15 (100%) of days following the intervention. Three months after the intervention, the following were observed: morning handoff started by 0745 on 10 of 10 (100%) of days; finished by 0800 on 10 of 10 (100%) of days; and table cards, ESL, and progress notes were on the table by 0745 on 10 of 10 (100%) of days.

Discussion

We describe an intervention that set the expectation for formal, structured written and verbal communication in a focused environment involving outgoing and incoming clinicians, resulting in improved satisfaction. Before the intervention, the improvement team identified by consensus 4 problems: unpredictable start time, inefficiency, environment, and report quality. Formal structuring of our handoff process resulted in statistically significant improvement in handoff timeliness and efficiency in the view of the HIM division members. Process improvement included precise team specific start times within a 12‐minute window to improve reliability and predictability and eliminating nonproductive waiting. Additionally, receiving teams were clearly identified with table cards so that no time was wasted locating the appropriate service for report, and minimizing role‐identification challenges. The good to go sign signaled teams that no events had occurred overnight requiring verbal report. Handoff timeliness persisted 3 months after the intervention, suggesting that the process is easily sustainable.

Postintervention survey comments noted the improved environment: a smaller, quieter room with the door closed. Before the intervention, all day team providers, CAs and night provider met in a large, loud room where multiple conversations were commonplace. Previous study of the handoff process supports creating an environment free of distraction.4

Postintervention survey responses to the open‐ended questions suggested improved provider satisfaction with the quality of the report. We believe this occurred for several reasons. First, having a precise start time for each team within a 12‐minute window led to a more focused report. Second, the ESL provided a column for providers to suggest plans of care for anticipated overnight events to improve preparedness and avoid significant omissions. Third, hospital notes generated overnight were made available which allowed daytime providers to review events before handoff, for a more informed update, or just after verbal report to reinforce the information just received, a technique used in other high‐reliability organizations.16 This measure also provided an at‐a‐glance view of each patient, decreasing the complexity of handoff.17

This study has important limitations. We address the handoff process of 1 hospitalist group at a single academic center. NP/PAs are the clinicians with first‐call responsibility for the night coverage of our patients, and the handoff process between the night NP/PA and daytime provider was studied. The handoff between physicians for patients admitted overnight was not assessed. Another limitation is that the time spent in handoff is reported as a participant estimate. There was no objective measurement of time, and respondents may have been biased. An additional limitation of our study concerns the preintervention and postintervention surveys. Both surveys were anonymous, which makes discerning the absolute impact of the intervention difficult due to the lack of paired responses. Lastly, our institution has an ESL. This option may not be available in other hospital systems.

Several deficiencies in the handoff process were addressed by providing key clinical data verbally and in written format, enhancing the physical environment, and defining each team's handoff start time. Our process improvements are consistent with the handoff recommendations endorsed by the Society of Hospital Medicine.12 Subsequent direct observation, subjective reports, and survey results demonstrated improvement in the handoff process.

Future studies might measure the effectiveness of morning handoff by end‐shift interviews of the daytime clinicians. Similarly, a study of evening handoff could measure the efficiency and effectiveness of report given by day teams to night‐coverage colleagues. Furthermore, if the handoff report skill set can be more rigorously defined and measured, a hospitalist clinical competency for hospitalists and NP/PAs could be developed in this core process‐of‐care.12

Transfer of responsibility for patients, or handoff,1 occurs frequently in hospitalist services, requiring excellent and timely communication to ensure patient safety. Communication failure is a major contributor to medical errors.2, 3 Recognizing such findings, a growing body of literature addresses handoff techniques for learners.47

Vidyarthi described the handoff process as traditionally informal, unstructured, and idiosyncratic,4 and many believe efforts to formalize and structure this process are important for patient safety.8 Standardized handoff forms have improved accuracy of information.9 Web‐based sign‐out systems reportedly reduced the number of patients missed on rounds.10

Hospitalists also face challenges with effective communication during service change.11 The Society of Hospital Medicine identified the handoff skill as a core competency for hospitalists, and recommendations based on a systematic review of the literature were published.12 Inpatient medicine programs are increasingly using midlevel providers such as nurse practitioners (NPs) and physician assistants (PAs) along with hospitalists to accommodate workload while maintaining the scholarly enterprise in academic centers.13 To our knowledge there is no literature examining the hospitalist service handoffs involving NP/PAs.

We wished to study the effectiveness and timeliness of the morning handoff from the night coverage providers to the daytime teams consisting of one hospitalist and one NP/PA. Our objectives were to identify deficiencies and to evaluate the effectiveness of a restructured handoff process.

Methods

The Mayo Clinic Institutional Review Board reviewed and approved this study.

Intervention

The improvement team structured a new handoff process to address these deficiencies.

• 1

  Environment: Moved to a smaller room (lower ceiling, less ambient noise).

• 2

  Identification: table cards designating seats for participants (reduced queries regarding what service are you, today?).

• 3

  Start Times: Each service team assigned a consistent start time (labeled on the table card) within a 15‐minute period, and although earlier reportage could occur, any service team present at their designated time has priority for the attention of the night NP/PA, and the opportunity to ask questions.

• 4

  Quiet and Focus: HIM members were reminded to remain quiet in the handoff room, so the service receiving report has the floor and personal conversations must not impede the principals.

• 5

  Visual Cue: Green Good to go sign placed on team table cards when no verbal was required.

• 6

  Written e‐Material: The improvement team required elements of a brief written report in a specified column of our existing electronic service list (ESL). The ESL is a custom designed template importing laboratory, medication, and demographic data automatically but also capable of free text additions (Figure 1). All providers were instructed to update the ESL every 12 hours.

• 7

  Admission and Progress Notes: After manual electronic medical record search, the CAs printed any notes generated in the preceding 12 hours and placed them by the team table card.

Figure 1

The improvement team provided education for the new process at a division meeting and through e‐mail. The recommended report sequence was night NP/PA reporting and day service teams asking questions and seeking clarifications. We discouraged editorial comments and chit‐chat.

A member of the improvement team monitored the new handoff process for 15 days, and 3 months later for 10 days.

Survey

An anonymous survey (Figure 2) concerning staff satisfaction with handoff was conducted immediately before and 15 days after the intervention. In the e‐mail containing the postintervention survey, providers were asked to respond only if they had been on service the preceding 15 days (and thus eligible to participate in handoff). To help insure this, the first question read, Have you been on service during the past 15 days?

Figure 2

Results

Thirty‐six of the 44 providers (82%) answered the preintervention survey, including 18 of 22 hospitalists (82%), 17 of 20 NPs/PAs (85%), and 1 of 2 CAs (50%). During the intervention based on our staffing model, 21 providers had the opportunity to participate in handoff, and 18 (86%) answered the postintervention survey, including 5 of 6 hospitalists (83%), 9 of 14 NPs/PAs (64%), and 2 of 2 CAs (100%). All respondents to the postintervention survey reported being on service during the previous 15 days.

As summarized in Table 1, compared to 60.5% of survey participants (n = 38) who thought morning handoff was performed in a timely fashion preintervention, 100% (n = 15) felt it was performed in a timely fashion postintervention (P = 0.005). The average time spent in morning report before the intervention was 11 minutes, as compared to 5 minutes after the intervention (P < 0.0028). Prior to the intervention, 6.5 minutes of the handoff were viewed to be wasteful, as compared to 0.5 minutes of the handoff in the postintervention survey (P < 0.0001). Attendance and quality of information perceptions did not demonstrate statistically significant change.

During the 15‐day observation period, morning handoff started by 0745 on 14 of 15 (93%) of days and finished by 0800 on 15 of 15 (100%) of days. Table cards, ESL, and progress notes were on the table by 0745 on 15 of 15 (100%) of days following the intervention. Three months after the intervention, the following were observed: morning handoff started by 0745 on 10 of 10 (100%) of days; finished by 0800 on 10 of 10 (100%) of days; and table cards, ESL, and progress notes were on the table by 0745 on 10 of 10 (100%) of days.

Discussion

We describe an intervention that set the expectation for formal, structured written and verbal communication in a focused environment involving outgoing and incoming clinicians, resulting in improved satisfaction. Before the intervention, the improvement team identified by consensus 4 problems: unpredictable start time, inefficiency, environment, and report quality. Formal structuring of our handoff process resulted in statistically significant improvement in handoff timeliness and efficiency in the view of the HIM division members. Process improvement included precise team specific start times within a 12‐minute window to improve reliability and predictability and eliminating nonproductive waiting. Additionally, receiving teams were clearly identified with table cards so that no time was wasted locating the appropriate service for report, and minimizing role‐identification challenges. The good to go sign signaled teams that no events had occurred overnight requiring verbal report. Handoff timeliness persisted 3 months after the intervention, suggesting that the process is easily sustainable.

Postintervention survey comments noted the improved environment: a smaller, quieter room with the door closed. Before the intervention, all day team providers, CAs and night provider met in a large, loud room where multiple conversations were commonplace. Previous study of the handoff process supports creating an environment free of distraction.4

Postintervention survey responses to the open‐ended questions suggested improved provider satisfaction with the quality of the report. We believe this occurred for several reasons. First, having a precise start time for each team within a 12‐minute window led to a more focused report. Second, the ESL provided a column for providers to suggest plans of care for anticipated overnight events to improve preparedness and avoid significant omissions. Third, hospital notes generated overnight were made available which allowed daytime providers to review events before handoff, for a more informed update, or just after verbal report to reinforce the information just received, a technique used in other high‐reliability organizations.16 This measure also provided an at‐a‐glance view of each patient, decreasing the complexity of handoff.17

This study has important limitations. We address the handoff process of 1 hospitalist group at a single academic center. NP/PAs are the clinicians with first‐call responsibility for the night coverage of our patients, and the handoff process between the night NP/PA and daytime provider was studied. The handoff between physicians for patients admitted overnight was not assessed. Another limitation is that the time spent in handoff is reported as a participant estimate. There was no objective measurement of time, and respondents may have been biased. An additional limitation of our study concerns the preintervention and postintervention surveys. Both surveys were anonymous, which makes discerning the absolute impact of the intervention difficult due to the lack of paired responses. Lastly, our institution has an ESL. This option may not be available in other hospital systems.

Several deficiencies in the handoff process were addressed by providing key clinical data verbally and in written format, enhancing the physical environment, and defining each team's handoff start time. Our process improvements are consistent with the handoff recommendations endorsed by the Society of Hospital Medicine.12 Subsequent direct observation, subjective reports, and survey results demonstrated improvement in the handoff process.

Future studies might measure the effectiveness of morning handoff by end‐shift interviews of the daytime clinicians. Similarly, a study of evening handoff could measure the efficiency and effectiveness of report given by day teams to night‐coverage colleagues. Furthermore, if the handoff report skill set can be more rigorously defined and measured, a hospitalist clinical competency for hospitalists and NP/PAs could be developed in this core process‐of‐care.12

Transfer of responsibility for patients, or handoff,1 occurs frequently in hospitalist services, requiring excellent and timely communication to ensure patient safety. Communication failure is a major contributor to medical errors.2, 3 Recognizing such findings, a growing body of literature addresses handoff techniques for learners.47

Vidyarthi described the handoff process as traditionally informal, unstructured, and idiosyncratic,4 and many believe efforts to formalize and structure this process are important for patient safety.8 Standardized handoff forms have improved accuracy of information.9 Web‐based sign‐out systems reportedly reduced the number of patients missed on rounds.10

Hospitalists also face challenges with effective communication during service change.11 The Society of Hospital Medicine identified the handoff skill as a core competency for hospitalists, and recommendations based on a systematic review of the literature were published.12 Inpatient medicine programs are increasingly using midlevel providers such as nurse practitioners (NPs) and physician assistants (PAs) along with hospitalists to accommodate workload while maintaining the scholarly enterprise in academic centers.13 To our knowledge there is no literature examining the hospitalist service handoffs involving NP/PAs.

We wished to study the effectiveness and timeliness of the morning handoff from the night coverage providers to the daytime teams consisting of one hospitalist and one NP/PA. Our objectives were to identify deficiencies and to evaluate the effectiveness of a restructured handoff process.

Methods

The Mayo Clinic Institutional Review Board reviewed and approved this study.

Intervention

The improvement team structured a new handoff process to address these deficiencies.

• 1

  Environment: Moved to a smaller room (lower ceiling, less ambient noise).

• 2

  Identification: table cards designating seats for participants (reduced queries regarding what service are you, today?).

• 3

  Start Times: Each service team assigned a consistent start time (labeled on the table card) within a 15‐minute period, and although earlier reportage could occur, any service team present at their designated time has priority for the attention of the night NP/PA, and the opportunity to ask questions.

• 4

  Quiet and Focus: HIM members were reminded to remain quiet in the handoff room, so the service receiving report has the floor and personal conversations must not impede the principals.

• 5

  Visual Cue: Green Good to go sign placed on team table cards when no verbal was required.

• 6

  Written e‐Material: The improvement team required elements of a brief written report in a specified column of our existing electronic service list (ESL). The ESL is a custom designed template importing laboratory, medication, and demographic data automatically but also capable of free text additions (Figure 1). All providers were instructed to update the ESL every 12 hours.

• 7

  Admission and Progress Notes: After manual electronic medical record search, the CAs printed any notes generated in the preceding 12 hours and placed them by the team table card.

Figure 1

The improvement team provided education for the new process at a division meeting and through e‐mail. The recommended report sequence was night NP/PA reporting and day service teams asking questions and seeking clarifications. We discouraged editorial comments and chit‐chat.

A member of the improvement team monitored the new handoff process for 15 days, and 3 months later for 10 days.

Survey

An anonymous survey (Figure 2) concerning staff satisfaction with handoff was conducted immediately before and 15 days after the intervention. In the e‐mail containing the postintervention survey, providers were asked to respond only if they had been on service the preceding 15 days (and thus eligible to participate in handoff). To help insure this, the first question read, Have you been on service during the past 15 days?

Figure 2

Results

Thirty‐six of the 44 providers (82%) answered the preintervention survey, including 18 of 22 hospitalists (82%), 17 of 20 NPs/PAs (85%), and 1 of 2 CAs (50%). During the intervention based on our staffing model, 21 providers had the opportunity to participate in handoff, and 18 (86%) answered the postintervention survey, including 5 of 6 hospitalists (83%), 9 of 14 NPs/PAs (64%), and 2 of 2 CAs (100%). All respondents to the postintervention survey reported being on service during the previous 15 days.

As summarized in Table 1, compared to 60.5% of survey participants (n = 38) who thought morning handoff was performed in a timely fashion preintervention, 100% (n = 15) felt it was performed in a timely fashion postintervention (P = 0.005). The average time spent in morning report before the intervention was 11 minutes, as compared to 5 minutes after the intervention (P < 0.0028). Prior to the intervention, 6.5 minutes of the handoff were viewed to be wasteful, as compared to 0.5 minutes of the handoff in the postintervention survey (P < 0.0001). Attendance and quality of information perceptions did not demonstrate statistically significant change.

During the 15‐day observation period, morning handoff started by 0745 on 14 of 15 (93%) of days and finished by 0800 on 15 of 15 (100%) of days. Table cards, ESL, and progress notes were on the table by 0745 on 15 of 15 (100%) of days following the intervention. Three months after the intervention, the following were observed: morning handoff started by 0745 on 10 of 10 (100%) of days; finished by 0800 on 10 of 10 (100%) of days; and table cards, ESL, and progress notes were on the table by 0745 on 10 of 10 (100%) of days.

Discussion

We describe an intervention that set the expectation for formal, structured written and verbal communication in a focused environment involving outgoing and incoming clinicians, resulting in improved satisfaction. Before the intervention, the improvement team identified by consensus 4 problems: unpredictable start time, inefficiency, environment, and report quality. Formal structuring of our handoff process resulted in statistically significant improvement in handoff timeliness and efficiency in the view of the HIM division members. Process improvement included precise team specific start times within a 12‐minute window to improve reliability and predictability and eliminating nonproductive waiting. Additionally, receiving teams were clearly identified with table cards so that no time was wasted locating the appropriate service for report, and minimizing role‐identification challenges. The good to go sign signaled teams that no events had occurred overnight requiring verbal report. Handoff timeliness persisted 3 months after the intervention, suggesting that the process is easily sustainable.

Postintervention survey comments noted the improved environment: a smaller, quieter room with the door closed. Before the intervention, all day team providers, CAs and night provider met in a large, loud room where multiple conversations were commonplace. Previous study of the handoff process supports creating an environment free of distraction.4

Postintervention survey responses to the open‐ended questions suggested improved provider satisfaction with the quality of the report. We believe this occurred for several reasons. First, having a precise start time for each team within a 12‐minute window led to a more focused report. Second, the ESL provided a column for providers to suggest plans of care for anticipated overnight events to improve preparedness and avoid significant omissions. Third, hospital notes generated overnight were made available which allowed daytime providers to review events before handoff, for a more informed update, or just after verbal report to reinforce the information just received, a technique used in other high‐reliability organizations.16 This measure also provided an at‐a‐glance view of each patient, decreasing the complexity of handoff.17

This study has important limitations. We address the handoff process of 1 hospitalist group at a single academic center. NP/PAs are the clinicians with first‐call responsibility for the night coverage of our patients, and the handoff process between the night NP/PA and daytime provider was studied. The handoff between physicians for patients admitted overnight was not assessed. Another limitation is that the time spent in handoff is reported as a participant estimate. There was no objective measurement of time, and respondents may have been biased. An additional limitation of our study concerns the preintervention and postintervention surveys. Both surveys were anonymous, which makes discerning the absolute impact of the intervention difficult due to the lack of paired responses. Lastly, our institution has an ESL. This option may not be available in other hospital systems.

Several deficiencies in the handoff process were addressed by providing key clinical data verbally and in written format, enhancing the physical environment, and defining each team's handoff start time. Our process improvements are consistent with the handoff recommendations endorsed by the Society of Hospital Medicine.12 Subsequent direct observation, subjective reports, and survey results demonstrated improvement in the handoff process.

Future studies might measure the effectiveness of morning handoff by end‐shift interviews of the daytime clinicians. Similarly, a study of evening handoff could measure the efficiency and effectiveness of report given by day teams to night‐coverage colleagues. Furthermore, if the handoff report skill set can be more rigorously defined and measured, a hospitalist clinical competency for hospitalists and NP/PAs could be developed in this core process‐of‐care.12