Andrew Dunn, MD

In recent years, much attention has been paid to concerns regarding length of stay (LOS) and safety of hospital discharges.13 Yet studies conducted in a variety of populations suggest that long stays do not wholly reflect acute medical necessity, but may also be driven by nonmedical factors.46 In a study of frail elderly patients, nonmedical factors accounted for over half of patients' hospital stay days.5 Nonmedical factors may include the availability of community and outpatient resources, inadequate patient social support, disagreement with family and/or patient decision‐making, and post‐hospital placement and care needs.7

Homebound patients are at particular risk for long stays because they are typically frail, elderly, and medically complex.8 The United States homebound population numbers at least 2 million and is expected to increase to at least 3 million by the year 2020.9 This group is medically underserved, often only receiving care for medical emergencies, and represents a costly group of health care beneficiaries.10 Although homebound primary care (HBPC) programs are structured to provide coordinated medical and supportive care in the home, the clinical complexity of patients often requires hospitalization during times of acute illness.11

Navigating the discharge process for homebound patients can prove time‐consuming for inpatient physicians whose clinical obligations encompass ensuring safe care transitions between hospital and home.12 The lack of literature on the discharge needs of the homebound population provides little guidance for physicians and health systems seeking to safely transition homebound patients from the hospital to the home in a timely and efficient manner. We performed a pilot study of an urban homebound population cared for by a single academic homebound program to identify and describe nonmedical factors associated with prolonged hospitalization.

METHODS

This retrospective descriptive study included homebound patients cared for by The Mount Sinai Visiting Doctors Program (MSVD), a primary care program affiliated with The Mount Sinai Hospital. MSVD is the largest academic homebound primary care program in the United States. The structure and patient population of MSVD patients have been described previously.13 Briefly, the program employs 8 physicians, 2 nurse practitioners, and support personnel including 2 registered nurses, 4 social workers, and 4 clerical staff members to serve over 1000 homebound patients annually. To be enrolled in the program, patients must meet the Medicare definition of homebound (ie, they must be able to leave home only with great difficulty and for infrequent or short absences). Patients are referred from a variety of sources including emergency rooms, inpatient units, and local nursing and social service agencies. Physicians visit patients on average once every 2 months, but can make more frequent home visits when a clinical need arises. Thirty‐six percent of patients in the program are hospitalized at least once per year while they are under the MSVD's care.14 Patients in the MSVD are referred by their primary care physician to outpatient social work as needed for finite interventions, though not for ongoing case management; approximately one‐third of all MSVD patients have been seen by an MSVD social worker over a 1‐year period.14

All patients enrolled in MSVD discharged from The Mount Sinai Hospital in New York from January 1, 2007, to December 31, 2007, were evaluated for inclusion in this study. The MSVD clinical database was cross‐referenced with The Mount Sinai Hospital data system to maximize reliability of recorded admission and discharge dates. Discrepancies in dates were investigated and corrected by the authors. As the study focused on admissions rather than individual patients, repeat hospitalizations and factors contributing to long stays were included and considered separately. In the event of repeat hospitalizations, factors contributing to LOS were also assessed separately.

Using the University HealthSystems Consortium (UHC) Database, the selected discharges were analyzed for LOS data. The UHC Database contains data from The Mount Sinai Hospital and 106 other academic medical centers and 233 other affiliated hospitals, representing approximately 90% of the United States' nonprofit academic medical centers. UHC members submit clinical, financial, and administrative information for the purpose of facilitating comparative data analysis among institutions.15 The model assigns an expected LOS for each patient based on a 4‐step risk adjustment methodology that adjusts for variations in patient characteristics. The regression models consider a range of independent variables including patient age, sex, race, socioeconomic status, admission source, and comorbid conditions. The expected LOS value is used to produce an LOS ratio, which is the ratio of a patient's observed LOS to expected LOS. We compared LOS ratios for all patient discharges during the study period and determined the mean LOS ratio for the group. Long‐stay patients were defined using the UHC definition of an LOS ratio greater than 2 standard deviations above the mean. These patients were selected for analysis to examine factors contributing to their long stays.

The primary author conducted a chart review for the long‐stay patients. The date of medical readiness for discharge was defined as the date when no acute hospital care needs or pending procedures (eg, intravenous medication, transfusion, invasive and noninvasive testing, surgery) were documented by the attending physician, house officer, nurse practitioner, or physician assistant in the chart. Patients with a discharge immediately following determination of medical readiness were characterized as having a medical stay (eg, patient admitted for pneumonia and discharged home after 3 days once fever, leukocytosis, and symptoms improved with a prescription for remaining antibiotic course). Patients who were classified as medically ready for discharge yet remained additional days in the hospital were categorized as having a nonmedical component to their hospitalization and comprised the nonmedical stay group (eg, patient admitted for pneumonia with improved vital signs and symptoms after 3 days, but discharged home after 10 days awaiting approval of increased home health aide hours). The primary author reviewed cases (<5%) with coauthors when categorization of patient data was unclear from physician documentation in the patient's chart. Similar methodology and terminology have been used in previous studies examining the contribution of nonmedical factors to LOS.5, 7

While literature in other fields, such as social work, often characterize similar factors as social or social care factors, we use the term nonmedical to draw the distinction between factors that acutely reflect a patient's state of health and necessitate days spent in the hospital (eg, surgery, infection), in contrast to factors that are not direct contributors to the patient's current medical status (eg, post‐hospital placement). Factors contributing to nonmedical days were determined based on previous studies and categorized as follows: nursing facility bed availability, nursing facility rejection of the patient, complications with insurance coverage, lack of patient/family agreement with discharge plan, home care service delays, and other. The category other was included to identify and explore any unexpected or unique reasons for prolongation of hospitalization in this population. When multiple nonmedical factors were identified for a given hospitalization, all contributing factors were recorded.

Demographic, clinical, and discharge characteristics were extracted from the MSVD clinical database to qualitatively describe and compare the long‐stay hospitalizations to the remainder of the sample.

RESULTS

There were a total of 479 discharges of 267 unique MSVD patients from The Mount Sinai Hospital occurring from January 1, 2007, to December 31, 2007. During this 12‐month period, the average observed LOS for all admissions was 7.84 days, with a mean UHC LOS ratio of 1.23 (SD = 3.43). Seventeen admissions were identified as long‐stays, representing 3.5% of discharges. The 17 admissions represent 17 unique patients.

As shown in Table 1, the long‐stay group (n = 17) was slightly younger, more likely to be male, and had less dementia than the nonlong‐stay group (n = 462). There was a marked difference in the location of patient discharge; long‐stay patients were more than twice as likely to be discharged to a facility and less likely to be discharged home. There were no in‐hospital deaths in the long‐stay patient group during the time period studied.

Of the 17 long‐stay patients, 8 (47%) remained in the hospital past the date they were determined to be medically ready for discharge and were defined as having a nonmedical component for the extension of their hospitalizations. The number of nonmedical days ranged from 6 to 34 days (mean, 17 days). Out of 428 total long‐stay patient days, 136 were nonmedical. This represented 31.8% of all long‐stay patient days, and 53% of the nonmedical group's total hospital days. The mean LOS ratio for the nonmedical cases was 6.04 (Table 2).

Nine patients were defined as medical stay cases (ie, no nonmedical component contributing to the long hospitalization). The mean observed LOS was 19.2 days, and the mean LOS ratio for this group was 5.07 (Table 2). There were no significant differences between primary diagnosis‐related groups (DRGs) seen in the medical and nonmedical stay groups.

The most common reason for a nonmedical stay was nursing facility placement delays (Table 3), specifically related to lack of bed availability and facility rejection of the patient leading to prolonged time waiting for long‐term placement (n = 6). Other nonmedical factors contributing to LOS were lack of patient and/or family agreement with discharge plans (eg, disagreement among family members regarding caregiving responsibilities, goals of care, or patient refusal to be discharged on a particular day) (n = 4); complications with insurance coverage for facility placement or for home care (n = 3); and home care service delays, such as patient need for increased home care hours after discharge (n = 2). Of note, 5 of the 8 nonmedical stay cases had multiple factors contributing to patients' long stays. All delays were assigned to one of the a priori defined categories. There were no other or unexpected reasons identified.

Of the nonmedical cases, all but 1 patient had been seen by an MSVD social worker prior to hospital admission, though the social work referral may have been years prior to or unrelated to the current admission.

DISCUSSION

Almost half of long‐stay patients identified in this homebound population remained hospitalized in an urban academic medical center due to at least one, and often multiple, nonmedical factors. Nonmedical factors identified in this group are similar to those described in previous studies, particularly family and patient decision‐making and post‐hospital placement and care needs.5, 7 Although this pilot study was limited to a single‐site population, it is to our knowledge the first study to describe these factors in a homebound population, and may be able to guide future research and discussion on this topic.

This study used a risk‐adjusted LOS measure to determine long stay cases. Using the UHC Database allowed for a more accurate understanding of the contribution of nonmedical factors to LOS by accounting for hospitalizations that were numerically lengthy but medically appropriate for their respective DRG. The use of the LOS ratio also allows for standardized application of these data across academic health centers. In our sample, 50% of the patients classified as LOS outliers by the UHC Database (cases with LOS in the top percentile for their respective DRG) had nonmedical stays. Conventional strategies often dismiss outliers in analyses of patient LOS data. However, in doing so there is a missed opportunity to identify underlying reasons for their disproportionately long hospitalizations that may also be impacting the broader set of patients with similar nonmedical factors affecting LOS.

The 8 nonmedical stay patients spent a combined 136 days longer in the hospital than medically necessary due to a variety of nonmedical factors, and represented over half of the nonmedical stay group's total hospital days. Using a conservative estimate for cost per hospital day of $1770,16 the nonmedical days cost the hospital almost a quarter of a million dollars ($240,720). Because this figure only accounts for long‐stay patients, the actual costs attributable to nonmedical days for the homebound population in general may be higher.

The longest patient stays, whether attributable to medical or nonmedical factors, were more likely to result in discharge to a facility than the rest of the sample hospitalizations. Facility placement was the most common nonmedical factor contributing to long stays in this sample. In contrast, home carerelated factors contributed the least to nonmedical days. This finding highlights the need for hospital‐based physicians and other inpatient staff members to be aware that despite patient enrollment in an HBPC, the possibility for homebound patients to be discharged to a nursing facility remains significant. A decreasing number of skilled nursing beds across the United States may magnify this factor in long‐stay cases.17 Increased awareness of this possibility among inpatient staff can allow the team to address facility placement considerations early in the hospital stay, potentially decreasing nonmedical days.18

Seven of the 8 nonmedical stay patients had been referred to and seen by MSVD social workers before hospitalization, a high percentage relative to the general MSVD population, of which fewer than half are seen by a social worker during their enrollment in MSVD. This finding may suggest that this group of patients already exhibited difficult social circumstances before their hospital admission, yet the current referral‐based social work model at MSVD did not mitigate their high LOS. This finding further suggests that patient enrollment in an HBPC does not mitigate the risk of high LOS and prolonged nonmedical stays, and that involvement of inpatient practitioners remains a critical part of advanced discharge planning.

This pilot study found that 32% of all long‐stay hospital days were due to nonmedical factors, suggesting that these factors play a greater role in the homebound population than for general medical patients. A recent study at an academic medical center examined 3574 patient‐days on a general medicine service, and noted that 11% of all days were felt to be medically unnecessary by the treating hospitalists.19 Hospitalists are well situated to participate in and lead improvement efforts given their expertise in managing complex dispositions and advancing collaborative strategies for care of patients with high overall acuity.20 These efforts will be needed to target those patients at highest risk for prolonged LOS with the greatest social care needs. Because this study did not pilot strategies to reduce LOS, we cannot offer evidence‐based suggestions for an enhanced multidisciplinary approach or other avenues for improvement. However, we believe that the study findings provide the basis for future research to test strategies to reduce excess LOS by focusing on nonmedical factors and a multidisciplinary approach. This will become especially relevant as health care systems bear increasing financial responsibility for inefficient and/or unnecessary hospitalizations and readmissions.

The involvement of social work before hospitalization for most of the homebound population with prolonged hospitalization suggests a need for greater team‐based efforts across venues. Though hospital interdisciplinary rounds aim to increase collaboration and reduce LOS, costs, and readmissions, these rounds do not typically include outpatient care providers.21 Improved communication and collaboration between social work with both inpatient and outpatient care teams to address nonmedical issues contributing to long stays are likely to improve care and transitions, though rigorous studies examining specific communication models across venues are lacking. This study found that delay in nursing facility placement was the most common reason for prolonged hospitalization for long‐stay cases. This finding emphasizes the need for communication between inpatient and outpatient staff to convey prior conversations or preparations for placement, identify patients who need post‐discharge facility placement early in hospitalization, and prompt timely discussions with patients and families.

The finding that prolonged hospitalization for the homebound population was due to nonmedical factors for almost one‐half of patients with long hospital stays has important implications for policymakers and other key stakeholders. For example, accountable care organizations are being developed to align members of the health care sector to provide higher quality care in a more efficient manner. These study data suggest that this alignment should include hospitals, nursing homes, and home health care agencies to ensure that discharge delays are minimized and unnecessary societal costs are avoided. Future research will need to confirm and build upon these findings of nonmedical reasons for excessive LOS to further inform the process of implementation of health care reform measures. Recent plans to cut Medicaid funding to nursing homes may further limit bed availability, increasing the risk of prolonged LOS and related costs to the health care system. This potential concern highlights the importance of care coordination and communication between inpatient and outpatient care providers to proactively address nursing home placement needs before hospitalization occurs, and/or to identify alternative safe discharge plans if a previously homebound patient is hospitalized.

There are several limitations to this descriptive study. Admissions included in this analysis were only captured for those admitted to The Mount Sinai Hospital. While MSVD providers report that more than 90% of hospitalizations for MSVD patients occur at The Mount Sinai Hospital, patients may also be admitted to one of many New York City metropolitan area hospitals closer to the patient's residence. It is possible that additional factors contributing to high LOS might be revealed if these admissions were included in the analysis. The urban homebound population served by MSVD may have more access to supplementary home care services (e.g. home attendants, meal services) than populations in more rural and less service‐intensive areas. Thus, it may be difficult to generalize these findings to programs serving less urban constituencies or with more restrictive policies regarding home care services. Additionally, as New York registers one of the highest nursing facility occupancy rates (in 2008, 92.2% versus the national average of 82.9%), patients in other markets may face a shorter wait time for a bed, decreasing the number of nonmedical days attributable to nursing home bed supply.17 The small total number of long‐stay patients also prevented statistical analysis comparing those patients with the rest of the sample. This pilot study may inform the design of future studies that may be able to include multiple HBPC programs or study homebound patients over a longer period to increase sample size.

Identifying the significant contribution of nonmedical days to patient stay is an important initial step to avoiding costly and medically unnecessary days for the patient and the hospital. As has been demonstrated in other interdisciplinary efforts, increased collaboration among physicians, social workers, discharge planners, and other disciplines may help address current gaps in patient care with regard to LOS.20, 21 Future studies should determine which homebound patients are at highest risk for prolonged hospitalization due to nonmedical factors to help design focused strategies and interventions for this vulnerable population.

In recent years, much attention has been paid to concerns regarding length of stay (LOS) and safety of hospital discharges.13 Yet studies conducted in a variety of populations suggest that long stays do not wholly reflect acute medical necessity, but may also be driven by nonmedical factors.46 In a study of frail elderly patients, nonmedical factors accounted for over half of patients' hospital stay days.5 Nonmedical factors may include the availability of community and outpatient resources, inadequate patient social support, disagreement with family and/or patient decision‐making, and post‐hospital placement and care needs.7

Homebound patients are at particular risk for long stays because they are typically frail, elderly, and medically complex.8 The United States homebound population numbers at least 2 million and is expected to increase to at least 3 million by the year 2020.9 This group is medically underserved, often only receiving care for medical emergencies, and represents a costly group of health care beneficiaries.10 Although homebound primary care (HBPC) programs are structured to provide coordinated medical and supportive care in the home, the clinical complexity of patients often requires hospitalization during times of acute illness.11

Navigating the discharge process for homebound patients can prove time‐consuming for inpatient physicians whose clinical obligations encompass ensuring safe care transitions between hospital and home.12 The lack of literature on the discharge needs of the homebound population provides little guidance for physicians and health systems seeking to safely transition homebound patients from the hospital to the home in a timely and efficient manner. We performed a pilot study of an urban homebound population cared for by a single academic homebound program to identify and describe nonmedical factors associated with prolonged hospitalization.

METHODS

This retrospective descriptive study included homebound patients cared for by The Mount Sinai Visiting Doctors Program (MSVD), a primary care program affiliated with The Mount Sinai Hospital. MSVD is the largest academic homebound primary care program in the United States. The structure and patient population of MSVD patients have been described previously.13 Briefly, the program employs 8 physicians, 2 nurse practitioners, and support personnel including 2 registered nurses, 4 social workers, and 4 clerical staff members to serve over 1000 homebound patients annually. To be enrolled in the program, patients must meet the Medicare definition of homebound (ie, they must be able to leave home only with great difficulty and for infrequent or short absences). Patients are referred from a variety of sources including emergency rooms, inpatient units, and local nursing and social service agencies. Physicians visit patients on average once every 2 months, but can make more frequent home visits when a clinical need arises. Thirty‐six percent of patients in the program are hospitalized at least once per year while they are under the MSVD's care.14 Patients in the MSVD are referred by their primary care physician to outpatient social work as needed for finite interventions, though not for ongoing case management; approximately one‐third of all MSVD patients have been seen by an MSVD social worker over a 1‐year period.14

All patients enrolled in MSVD discharged from The Mount Sinai Hospital in New York from January 1, 2007, to December 31, 2007, were evaluated for inclusion in this study. The MSVD clinical database was cross‐referenced with The Mount Sinai Hospital data system to maximize reliability of recorded admission and discharge dates. Discrepancies in dates were investigated and corrected by the authors. As the study focused on admissions rather than individual patients, repeat hospitalizations and factors contributing to long stays were included and considered separately. In the event of repeat hospitalizations, factors contributing to LOS were also assessed separately.

Using the University HealthSystems Consortium (UHC) Database, the selected discharges were analyzed for LOS data. The UHC Database contains data from The Mount Sinai Hospital and 106 other academic medical centers and 233 other affiliated hospitals, representing approximately 90% of the United States' nonprofit academic medical centers. UHC members submit clinical, financial, and administrative information for the purpose of facilitating comparative data analysis among institutions.15 The model assigns an expected LOS for each patient based on a 4‐step risk adjustment methodology that adjusts for variations in patient characteristics. The regression models consider a range of independent variables including patient age, sex, race, socioeconomic status, admission source, and comorbid conditions. The expected LOS value is used to produce an LOS ratio, which is the ratio of a patient's observed LOS to expected LOS. We compared LOS ratios for all patient discharges during the study period and determined the mean LOS ratio for the group. Long‐stay patients were defined using the UHC definition of an LOS ratio greater than 2 standard deviations above the mean. These patients were selected for analysis to examine factors contributing to their long stays.

The primary author conducted a chart review for the long‐stay patients. The date of medical readiness for discharge was defined as the date when no acute hospital care needs or pending procedures (eg, intravenous medication, transfusion, invasive and noninvasive testing, surgery) were documented by the attending physician, house officer, nurse practitioner, or physician assistant in the chart. Patients with a discharge immediately following determination of medical readiness were characterized as having a medical stay (eg, patient admitted for pneumonia and discharged home after 3 days once fever, leukocytosis, and symptoms improved with a prescription for remaining antibiotic course). Patients who were classified as medically ready for discharge yet remained additional days in the hospital were categorized as having a nonmedical component to their hospitalization and comprised the nonmedical stay group (eg, patient admitted for pneumonia with improved vital signs and symptoms after 3 days, but discharged home after 10 days awaiting approval of increased home health aide hours). The primary author reviewed cases (<5%) with coauthors when categorization of patient data was unclear from physician documentation in the patient's chart. Similar methodology and terminology have been used in previous studies examining the contribution of nonmedical factors to LOS.5, 7

While literature in other fields, such as social work, often characterize similar factors as social or social care factors, we use the term nonmedical to draw the distinction between factors that acutely reflect a patient's state of health and necessitate days spent in the hospital (eg, surgery, infection), in contrast to factors that are not direct contributors to the patient's current medical status (eg, post‐hospital placement). Factors contributing to nonmedical days were determined based on previous studies and categorized as follows: nursing facility bed availability, nursing facility rejection of the patient, complications with insurance coverage, lack of patient/family agreement with discharge plan, home care service delays, and other. The category other was included to identify and explore any unexpected or unique reasons for prolongation of hospitalization in this population. When multiple nonmedical factors were identified for a given hospitalization, all contributing factors were recorded.

Demographic, clinical, and discharge characteristics were extracted from the MSVD clinical database to qualitatively describe and compare the long‐stay hospitalizations to the remainder of the sample.

RESULTS

There were a total of 479 discharges of 267 unique MSVD patients from The Mount Sinai Hospital occurring from January 1, 2007, to December 31, 2007. During this 12‐month period, the average observed LOS for all admissions was 7.84 days, with a mean UHC LOS ratio of 1.23 (SD = 3.43). Seventeen admissions were identified as long‐stays, representing 3.5% of discharges. The 17 admissions represent 17 unique patients.

As shown in Table 1, the long‐stay group (n = 17) was slightly younger, more likely to be male, and had less dementia than the nonlong‐stay group (n = 462). There was a marked difference in the location of patient discharge; long‐stay patients were more than twice as likely to be discharged to a facility and less likely to be discharged home. There were no in‐hospital deaths in the long‐stay patient group during the time period studied.

Of the 17 long‐stay patients, 8 (47%) remained in the hospital past the date they were determined to be medically ready for discharge and were defined as having a nonmedical component for the extension of their hospitalizations. The number of nonmedical days ranged from 6 to 34 days (mean, 17 days). Out of 428 total long‐stay patient days, 136 were nonmedical. This represented 31.8% of all long‐stay patient days, and 53% of the nonmedical group's total hospital days. The mean LOS ratio for the nonmedical cases was 6.04 (Table 2).

Nine patients were defined as medical stay cases (ie, no nonmedical component contributing to the long hospitalization). The mean observed LOS was 19.2 days, and the mean LOS ratio for this group was 5.07 (Table 2). There were no significant differences between primary diagnosis‐related groups (DRGs) seen in the medical and nonmedical stay groups.

The most common reason for a nonmedical stay was nursing facility placement delays (Table 3), specifically related to lack of bed availability and facility rejection of the patient leading to prolonged time waiting for long‐term placement (n = 6). Other nonmedical factors contributing to LOS were lack of patient and/or family agreement with discharge plans (eg, disagreement among family members regarding caregiving responsibilities, goals of care, or patient refusal to be discharged on a particular day) (n = 4); complications with insurance coverage for facility placement or for home care (n = 3); and home care service delays, such as patient need for increased home care hours after discharge (n = 2). Of note, 5 of the 8 nonmedical stay cases had multiple factors contributing to patients' long stays. All delays were assigned to one of the a priori defined categories. There were no other or unexpected reasons identified.

Of the nonmedical cases, all but 1 patient had been seen by an MSVD social worker prior to hospital admission, though the social work referral may have been years prior to or unrelated to the current admission.

DISCUSSION

Almost half of long‐stay patients identified in this homebound population remained hospitalized in an urban academic medical center due to at least one, and often multiple, nonmedical factors. Nonmedical factors identified in this group are similar to those described in previous studies, particularly family and patient decision‐making and post‐hospital placement and care needs.5, 7 Although this pilot study was limited to a single‐site population, it is to our knowledge the first study to describe these factors in a homebound population, and may be able to guide future research and discussion on this topic.

This study used a risk‐adjusted LOS measure to determine long stay cases. Using the UHC Database allowed for a more accurate understanding of the contribution of nonmedical factors to LOS by accounting for hospitalizations that were numerically lengthy but medically appropriate for their respective DRG. The use of the LOS ratio also allows for standardized application of these data across academic health centers. In our sample, 50% of the patients classified as LOS outliers by the UHC Database (cases with LOS in the top percentile for their respective DRG) had nonmedical stays. Conventional strategies often dismiss outliers in analyses of patient LOS data. However, in doing so there is a missed opportunity to identify underlying reasons for their disproportionately long hospitalizations that may also be impacting the broader set of patients with similar nonmedical factors affecting LOS.

The 8 nonmedical stay patients spent a combined 136 days longer in the hospital than medically necessary due to a variety of nonmedical factors, and represented over half of the nonmedical stay group's total hospital days. Using a conservative estimate for cost per hospital day of $1770,16 the nonmedical days cost the hospital almost a quarter of a million dollars ($240,720). Because this figure only accounts for long‐stay patients, the actual costs attributable to nonmedical days for the homebound population in general may be higher.

The longest patient stays, whether attributable to medical or nonmedical factors, were more likely to result in discharge to a facility than the rest of the sample hospitalizations. Facility placement was the most common nonmedical factor contributing to long stays in this sample. In contrast, home carerelated factors contributed the least to nonmedical days. This finding highlights the need for hospital‐based physicians and other inpatient staff members to be aware that despite patient enrollment in an HBPC, the possibility for homebound patients to be discharged to a nursing facility remains significant. A decreasing number of skilled nursing beds across the United States may magnify this factor in long‐stay cases.17 Increased awareness of this possibility among inpatient staff can allow the team to address facility placement considerations early in the hospital stay, potentially decreasing nonmedical days.18

Seven of the 8 nonmedical stay patients had been referred to and seen by MSVD social workers before hospitalization, a high percentage relative to the general MSVD population, of which fewer than half are seen by a social worker during their enrollment in MSVD. This finding may suggest that this group of patients already exhibited difficult social circumstances before their hospital admission, yet the current referral‐based social work model at MSVD did not mitigate their high LOS. This finding further suggests that patient enrollment in an HBPC does not mitigate the risk of high LOS and prolonged nonmedical stays, and that involvement of inpatient practitioners remains a critical part of advanced discharge planning.

This pilot study found that 32% of all long‐stay hospital days were due to nonmedical factors, suggesting that these factors play a greater role in the homebound population than for general medical patients. A recent study at an academic medical center examined 3574 patient‐days on a general medicine service, and noted that 11% of all days were felt to be medically unnecessary by the treating hospitalists.19 Hospitalists are well situated to participate in and lead improvement efforts given their expertise in managing complex dispositions and advancing collaborative strategies for care of patients with high overall acuity.20 These efforts will be needed to target those patients at highest risk for prolonged LOS with the greatest social care needs. Because this study did not pilot strategies to reduce LOS, we cannot offer evidence‐based suggestions for an enhanced multidisciplinary approach or other avenues for improvement. However, we believe that the study findings provide the basis for future research to test strategies to reduce excess LOS by focusing on nonmedical factors and a multidisciplinary approach. This will become especially relevant as health care systems bear increasing financial responsibility for inefficient and/or unnecessary hospitalizations and readmissions.

The involvement of social work before hospitalization for most of the homebound population with prolonged hospitalization suggests a need for greater team‐based efforts across venues. Though hospital interdisciplinary rounds aim to increase collaboration and reduce LOS, costs, and readmissions, these rounds do not typically include outpatient care providers.21 Improved communication and collaboration between social work with both inpatient and outpatient care teams to address nonmedical issues contributing to long stays are likely to improve care and transitions, though rigorous studies examining specific communication models across venues are lacking. This study found that delay in nursing facility placement was the most common reason for prolonged hospitalization for long‐stay cases. This finding emphasizes the need for communication between inpatient and outpatient staff to convey prior conversations or preparations for placement, identify patients who need post‐discharge facility placement early in hospitalization, and prompt timely discussions with patients and families.

The finding that prolonged hospitalization for the homebound population was due to nonmedical factors for almost one‐half of patients with long hospital stays has important implications for policymakers and other key stakeholders. For example, accountable care organizations are being developed to align members of the health care sector to provide higher quality care in a more efficient manner. These study data suggest that this alignment should include hospitals, nursing homes, and home health care agencies to ensure that discharge delays are minimized and unnecessary societal costs are avoided. Future research will need to confirm and build upon these findings of nonmedical reasons for excessive LOS to further inform the process of implementation of health care reform measures. Recent plans to cut Medicaid funding to nursing homes may further limit bed availability, increasing the risk of prolonged LOS and related costs to the health care system. This potential concern highlights the importance of care coordination and communication between inpatient and outpatient care providers to proactively address nursing home placement needs before hospitalization occurs, and/or to identify alternative safe discharge plans if a previously homebound patient is hospitalized.

There are several limitations to this descriptive study. Admissions included in this analysis were only captured for those admitted to The Mount Sinai Hospital. While MSVD providers report that more than 90% of hospitalizations for MSVD patients occur at The Mount Sinai Hospital, patients may also be admitted to one of many New York City metropolitan area hospitals closer to the patient's residence. It is possible that additional factors contributing to high LOS might be revealed if these admissions were included in the analysis. The urban homebound population served by MSVD may have more access to supplementary home care services (e.g. home attendants, meal services) than populations in more rural and less service‐intensive areas. Thus, it may be difficult to generalize these findings to programs serving less urban constituencies or with more restrictive policies regarding home care services. Additionally, as New York registers one of the highest nursing facility occupancy rates (in 2008, 92.2% versus the national average of 82.9%), patients in other markets may face a shorter wait time for a bed, decreasing the number of nonmedical days attributable to nursing home bed supply.17 The small total number of long‐stay patients also prevented statistical analysis comparing those patients with the rest of the sample. This pilot study may inform the design of future studies that may be able to include multiple HBPC programs or study homebound patients over a longer period to increase sample size.

Identifying the significant contribution of nonmedical days to patient stay is an important initial step to avoiding costly and medically unnecessary days for the patient and the hospital. As has been demonstrated in other interdisciplinary efforts, increased collaboration among physicians, social workers, discharge planners, and other disciplines may help address current gaps in patient care with regard to LOS.20, 21 Future studies should determine which homebound patients are at highest risk for prolonged hospitalization due to nonmedical factors to help design focused strategies and interventions for this vulnerable population.

In recent years, much attention has been paid to concerns regarding length of stay (LOS) and safety of hospital discharges.13 Yet studies conducted in a variety of populations suggest that long stays do not wholly reflect acute medical necessity, but may also be driven by nonmedical factors.46 In a study of frail elderly patients, nonmedical factors accounted for over half of patients' hospital stay days.5 Nonmedical factors may include the availability of community and outpatient resources, inadequate patient social support, disagreement with family and/or patient decision‐making, and post‐hospital placement and care needs.7

Homebound patients are at particular risk for long stays because they are typically frail, elderly, and medically complex.8 The United States homebound population numbers at least 2 million and is expected to increase to at least 3 million by the year 2020.9 This group is medically underserved, often only receiving care for medical emergencies, and represents a costly group of health care beneficiaries.10 Although homebound primary care (HBPC) programs are structured to provide coordinated medical and supportive care in the home, the clinical complexity of patients often requires hospitalization during times of acute illness.11

Navigating the discharge process for homebound patients can prove time‐consuming for inpatient physicians whose clinical obligations encompass ensuring safe care transitions between hospital and home.12 The lack of literature on the discharge needs of the homebound population provides little guidance for physicians and health systems seeking to safely transition homebound patients from the hospital to the home in a timely and efficient manner. We performed a pilot study of an urban homebound population cared for by a single academic homebound program to identify and describe nonmedical factors associated with prolonged hospitalization.

METHODS

This retrospective descriptive study included homebound patients cared for by The Mount Sinai Visiting Doctors Program (MSVD), a primary care program affiliated with The Mount Sinai Hospital. MSVD is the largest academic homebound primary care program in the United States. The structure and patient population of MSVD patients have been described previously.13 Briefly, the program employs 8 physicians, 2 nurse practitioners, and support personnel including 2 registered nurses, 4 social workers, and 4 clerical staff members to serve over 1000 homebound patients annually. To be enrolled in the program, patients must meet the Medicare definition of homebound (ie, they must be able to leave home only with great difficulty and for infrequent or short absences). Patients are referred from a variety of sources including emergency rooms, inpatient units, and local nursing and social service agencies. Physicians visit patients on average once every 2 months, but can make more frequent home visits when a clinical need arises. Thirty‐six percent of patients in the program are hospitalized at least once per year while they are under the MSVD's care.14 Patients in the MSVD are referred by their primary care physician to outpatient social work as needed for finite interventions, though not for ongoing case management; approximately one‐third of all MSVD patients have been seen by an MSVD social worker over a 1‐year period.14

All patients enrolled in MSVD discharged from The Mount Sinai Hospital in New York from January 1, 2007, to December 31, 2007, were evaluated for inclusion in this study. The MSVD clinical database was cross‐referenced with The Mount Sinai Hospital data system to maximize reliability of recorded admission and discharge dates. Discrepancies in dates were investigated and corrected by the authors. As the study focused on admissions rather than individual patients, repeat hospitalizations and factors contributing to long stays were included and considered separately. In the event of repeat hospitalizations, factors contributing to LOS were also assessed separately.

Using the University HealthSystems Consortium (UHC) Database, the selected discharges were analyzed for LOS data. The UHC Database contains data from The Mount Sinai Hospital and 106 other academic medical centers and 233 other affiliated hospitals, representing approximately 90% of the United States' nonprofit academic medical centers. UHC members submit clinical, financial, and administrative information for the purpose of facilitating comparative data analysis among institutions.15 The model assigns an expected LOS for each patient based on a 4‐step risk adjustment methodology that adjusts for variations in patient characteristics. The regression models consider a range of independent variables including patient age, sex, race, socioeconomic status, admission source, and comorbid conditions. The expected LOS value is used to produce an LOS ratio, which is the ratio of a patient's observed LOS to expected LOS. We compared LOS ratios for all patient discharges during the study period and determined the mean LOS ratio for the group. Long‐stay patients were defined using the UHC definition of an LOS ratio greater than 2 standard deviations above the mean. These patients were selected for analysis to examine factors contributing to their long stays.

The primary author conducted a chart review for the long‐stay patients. The date of medical readiness for discharge was defined as the date when no acute hospital care needs or pending procedures (eg, intravenous medication, transfusion, invasive and noninvasive testing, surgery) were documented by the attending physician, house officer, nurse practitioner, or physician assistant in the chart. Patients with a discharge immediately following determination of medical readiness were characterized as having a medical stay (eg, patient admitted for pneumonia and discharged home after 3 days once fever, leukocytosis, and symptoms improved with a prescription for remaining antibiotic course). Patients who were classified as medically ready for discharge yet remained additional days in the hospital were categorized as having a nonmedical component to their hospitalization and comprised the nonmedical stay group (eg, patient admitted for pneumonia with improved vital signs and symptoms after 3 days, but discharged home after 10 days awaiting approval of increased home health aide hours). The primary author reviewed cases (<5%) with coauthors when categorization of patient data was unclear from physician documentation in the patient's chart. Similar methodology and terminology have been used in previous studies examining the contribution of nonmedical factors to LOS.5, 7

While literature in other fields, such as social work, often characterize similar factors as social or social care factors, we use the term nonmedical to draw the distinction between factors that acutely reflect a patient's state of health and necessitate days spent in the hospital (eg, surgery, infection), in contrast to factors that are not direct contributors to the patient's current medical status (eg, post‐hospital placement). Factors contributing to nonmedical days were determined based on previous studies and categorized as follows: nursing facility bed availability, nursing facility rejection of the patient, complications with insurance coverage, lack of patient/family agreement with discharge plan, home care service delays, and other. The category other was included to identify and explore any unexpected or unique reasons for prolongation of hospitalization in this population. When multiple nonmedical factors were identified for a given hospitalization, all contributing factors were recorded.

Demographic, clinical, and discharge characteristics were extracted from the MSVD clinical database to qualitatively describe and compare the long‐stay hospitalizations to the remainder of the sample.

RESULTS

There were a total of 479 discharges of 267 unique MSVD patients from The Mount Sinai Hospital occurring from January 1, 2007, to December 31, 2007. During this 12‐month period, the average observed LOS for all admissions was 7.84 days, with a mean UHC LOS ratio of 1.23 (SD = 3.43). Seventeen admissions were identified as long‐stays, representing 3.5% of discharges. The 17 admissions represent 17 unique patients.

As shown in Table 1, the long‐stay group (n = 17) was slightly younger, more likely to be male, and had less dementia than the nonlong‐stay group (n = 462). There was a marked difference in the location of patient discharge; long‐stay patients were more than twice as likely to be discharged to a facility and less likely to be discharged home. There were no in‐hospital deaths in the long‐stay patient group during the time period studied.

Of the 17 long‐stay patients, 8 (47%) remained in the hospital past the date they were determined to be medically ready for discharge and were defined as having a nonmedical component for the extension of their hospitalizations. The number of nonmedical days ranged from 6 to 34 days (mean, 17 days). Out of 428 total long‐stay patient days, 136 were nonmedical. This represented 31.8% of all long‐stay patient days, and 53% of the nonmedical group's total hospital days. The mean LOS ratio for the nonmedical cases was 6.04 (Table 2).

Nine patients were defined as medical stay cases (ie, no nonmedical component contributing to the long hospitalization). The mean observed LOS was 19.2 days, and the mean LOS ratio for this group was 5.07 (Table 2). There were no significant differences between primary diagnosis‐related groups (DRGs) seen in the medical and nonmedical stay groups.

The most common reason for a nonmedical stay was nursing facility placement delays (Table 3), specifically related to lack of bed availability and facility rejection of the patient leading to prolonged time waiting for long‐term placement (n = 6). Other nonmedical factors contributing to LOS were lack of patient and/or family agreement with discharge plans (eg, disagreement among family members regarding caregiving responsibilities, goals of care, or patient refusal to be discharged on a particular day) (n = 4); complications with insurance coverage for facility placement or for home care (n = 3); and home care service delays, such as patient need for increased home care hours after discharge (n = 2). Of note, 5 of the 8 nonmedical stay cases had multiple factors contributing to patients' long stays. All delays were assigned to one of the a priori defined categories. There were no other or unexpected reasons identified.

Of the nonmedical cases, all but 1 patient had been seen by an MSVD social worker prior to hospital admission, though the social work referral may have been years prior to or unrelated to the current admission.

DISCUSSION

Almost half of long‐stay patients identified in this homebound population remained hospitalized in an urban academic medical center due to at least one, and often multiple, nonmedical factors. Nonmedical factors identified in this group are similar to those described in previous studies, particularly family and patient decision‐making and post‐hospital placement and care needs.5, 7 Although this pilot study was limited to a single‐site population, it is to our knowledge the first study to describe these factors in a homebound population, and may be able to guide future research and discussion on this topic.

This study used a risk‐adjusted LOS measure to determine long stay cases. Using the UHC Database allowed for a more accurate understanding of the contribution of nonmedical factors to LOS by accounting for hospitalizations that were numerically lengthy but medically appropriate for their respective DRG. The use of the LOS ratio also allows for standardized application of these data across academic health centers. In our sample, 50% of the patients classified as LOS outliers by the UHC Database (cases with LOS in the top percentile for their respective DRG) had nonmedical stays. Conventional strategies often dismiss outliers in analyses of patient LOS data. However, in doing so there is a missed opportunity to identify underlying reasons for their disproportionately long hospitalizations that may also be impacting the broader set of patients with similar nonmedical factors affecting LOS.

The 8 nonmedical stay patients spent a combined 136 days longer in the hospital than medically necessary due to a variety of nonmedical factors, and represented over half of the nonmedical stay group's total hospital days. Using a conservative estimate for cost per hospital day of $1770,16 the nonmedical days cost the hospital almost a quarter of a million dollars ($240,720). Because this figure only accounts for long‐stay patients, the actual costs attributable to nonmedical days for the homebound population in general may be higher.

The longest patient stays, whether attributable to medical or nonmedical factors, were more likely to result in discharge to a facility than the rest of the sample hospitalizations. Facility placement was the most common nonmedical factor contributing to long stays in this sample. In contrast, home carerelated factors contributed the least to nonmedical days. This finding highlights the need for hospital‐based physicians and other inpatient staff members to be aware that despite patient enrollment in an HBPC, the possibility for homebound patients to be discharged to a nursing facility remains significant. A decreasing number of skilled nursing beds across the United States may magnify this factor in long‐stay cases.17 Increased awareness of this possibility among inpatient staff can allow the team to address facility placement considerations early in the hospital stay, potentially decreasing nonmedical days.18

Seven of the 8 nonmedical stay patients had been referred to and seen by MSVD social workers before hospitalization, a high percentage relative to the general MSVD population, of which fewer than half are seen by a social worker during their enrollment in MSVD. This finding may suggest that this group of patients already exhibited difficult social circumstances before their hospital admission, yet the current referral‐based social work model at MSVD did not mitigate their high LOS. This finding further suggests that patient enrollment in an HBPC does not mitigate the risk of high LOS and prolonged nonmedical stays, and that involvement of inpatient practitioners remains a critical part of advanced discharge planning.

This pilot study found that 32% of all long‐stay hospital days were due to nonmedical factors, suggesting that these factors play a greater role in the homebound population than for general medical patients. A recent study at an academic medical center examined 3574 patient‐days on a general medicine service, and noted that 11% of all days were felt to be medically unnecessary by the treating hospitalists.19 Hospitalists are well situated to participate in and lead improvement efforts given their expertise in managing complex dispositions and advancing collaborative strategies for care of patients with high overall acuity.20 These efforts will be needed to target those patients at highest risk for prolonged LOS with the greatest social care needs. Because this study did not pilot strategies to reduce LOS, we cannot offer evidence‐based suggestions for an enhanced multidisciplinary approach or other avenues for improvement. However, we believe that the study findings provide the basis for future research to test strategies to reduce excess LOS by focusing on nonmedical factors and a multidisciplinary approach. This will become especially relevant as health care systems bear increasing financial responsibility for inefficient and/or unnecessary hospitalizations and readmissions.

The involvement of social work before hospitalization for most of the homebound population with prolonged hospitalization suggests a need for greater team‐based efforts across venues. Though hospital interdisciplinary rounds aim to increase collaboration and reduce LOS, costs, and readmissions, these rounds do not typically include outpatient care providers.21 Improved communication and collaboration between social work with both inpatient and outpatient care teams to address nonmedical issues contributing to long stays are likely to improve care and transitions, though rigorous studies examining specific communication models across venues are lacking. This study found that delay in nursing facility placement was the most common reason for prolonged hospitalization for long‐stay cases. This finding emphasizes the need for communication between inpatient and outpatient staff to convey prior conversations or preparations for placement, identify patients who need post‐discharge facility placement early in hospitalization, and prompt timely discussions with patients and families.

The finding that prolonged hospitalization for the homebound population was due to nonmedical factors for almost one‐half of patients with long hospital stays has important implications for policymakers and other key stakeholders. For example, accountable care organizations are being developed to align members of the health care sector to provide higher quality care in a more efficient manner. These study data suggest that this alignment should include hospitals, nursing homes, and home health care agencies to ensure that discharge delays are minimized and unnecessary societal costs are avoided. Future research will need to confirm and build upon these findings of nonmedical reasons for excessive LOS to further inform the process of implementation of health care reform measures. Recent plans to cut Medicaid funding to nursing homes may further limit bed availability, increasing the risk of prolonged LOS and related costs to the health care system. This potential concern highlights the importance of care coordination and communication between inpatient and outpatient care providers to proactively address nursing home placement needs before hospitalization occurs, and/or to identify alternative safe discharge plans if a previously homebound patient is hospitalized.

There are several limitations to this descriptive study. Admissions included in this analysis were only captured for those admitted to The Mount Sinai Hospital. While MSVD providers report that more than 90% of hospitalizations for MSVD patients occur at The Mount Sinai Hospital, patients may also be admitted to one of many New York City metropolitan area hospitals closer to the patient's residence. It is possible that additional factors contributing to high LOS might be revealed if these admissions were included in the analysis. The urban homebound population served by MSVD may have more access to supplementary home care services (e.g. home attendants, meal services) than populations in more rural and less service‐intensive areas. Thus, it may be difficult to generalize these findings to programs serving less urban constituencies or with more restrictive policies regarding home care services. Additionally, as New York registers one of the highest nursing facility occupancy rates (in 2008, 92.2% versus the national average of 82.9%), patients in other markets may face a shorter wait time for a bed, decreasing the number of nonmedical days attributable to nursing home bed supply.17 The small total number of long‐stay patients also prevented statistical analysis comparing those patients with the rest of the sample. This pilot study may inform the design of future studies that may be able to include multiple HBPC programs or study homebound patients over a longer period to increase sample size.

Identifying the significant contribution of nonmedical days to patient stay is an important initial step to avoiding costly and medically unnecessary days for the patient and the hospital. As has been demonstrated in other interdisciplinary efforts, increased collaboration among physicians, social workers, discharge planners, and other disciplines may help address current gaps in patient care with regard to LOS.20, 21 Future studies should determine which homebound patients are at highest risk for prolonged hospitalization due to nonmedical factors to help design focused strategies and interventions for this vulnerable population.

Emergency Department (ED) overcrowding has become an important problem in North American hospitals.13 A national survey identified the prolonged length of stay of admitted patients in the ED as the most frequent reason for overcrowding.4 This complex problem occurs when hospital inpatient census increases and prevents admitted patients from being assigned and transported to hospital beds in a timely manner.5 The practice of holding admitted patients in the ED, known as boarding, is typically defined as the length of stay (LOS) in ED beginning 2 hours after the time of admission to the time of transfer to the wards.

In a study of daily mean ED LOS, Rathlev et al.6 concluded that a 5% increase in hospital occupancy resulted in 14 hours of holding time for all patients in the ED, and an observational study found that when hospital occupancy exceeds a threshold of 90%, the ED LOS for admitted patients correspondingly increased.7 Thus, efforts to decrease overcrowding will need to address both ED and hospital throughput and LOS. Most importantly, overcrowding has important consequences on physician and patient satisfaction and the quality of patient care.811

Between 1995 and 2005, ED visits rose 20% from 96.5 million to 115.3 million visits annually, while the number of hospital EDs decreased from 4176 to 3795, making an overall 7% increase in ED utilization rate.12 Similarly, there was a 12% increase in the total inpatient admissions for all registered hospitals in the United States from 31 million in 1995 to 35.3 million in 2005.13 However, despite this increase in demand of ED utilization and inpatient admissions, there had been a steady decline in the supply of hospital beds, from 874,000 in 1995, to 805,000 in 2006.13 These factors have exacerbated the problem of ED overcrowding and boarding.

Not only does boarding entail additional consumption of space, resources, equipment, and manpower, it also potentially compromises patient safety. Typically, hospitalists and inpatient medical teams are engaged in providing care to patients in the wards, while ED physicians and nurses are busy taking care of newly‐arrived ED patients. Non‐ED physicians may have the false impression that their boarded patients, while in the ED, are receiving continuous care and so may decide to delay seeing these patients, which can jeopardize the quality and timeliness of care. Studies have shown that ED overcrowding may potentially lead to poor patient care and outcomes and increased risk for medical errors.1416 ED overcrowding potentially causes multiple effects, including prolonging patient pain and suffering, long patient waiting time, patient dissatisfaction, ambulance diversions, decreased physician productivity, and increased frustration among medical staff.15 In a report by the Joint Commission Accreditation of Healthcare Organizations,17 ED overcrowding was cited as a significant contributing factor in sentinel event cases of patient death or permanent injury due to delays in treatment. Boarding critically ill patients who are physiologically vulnerable and unstable can allow them to be subjected to treatment delays at a pivotal point when time‐sensitive interventions are necessary, ie, sepsis or cardiogenic shockthe golden hour in trauma.16 Medical errors are usually not caused by individual errors but by complex hospital systems; and ED overcrowding is a prime example of a system problem that creates a high‐risk environment for medical errors and threatens patient safety.18

Our hospital commonly has 5 to 15 boarders and often has 20 to 30 boarders at any time. Approximately 90% of these patients are admitted to the Medical Service. In response to this challenge, our institution has designated a full‐time hospitalist to manage boarded patients. The primary goal of this new role is to ensure patient safety and the delivery of high‐quality care while admitted patients are in the ED (Table 1).

The objectives of the study were to determine: (1) the impact on quality of care by assessing laboratory results acted upon and medication follow‐up by the ED hospitalist, and (2) the impact on throughput by assessing the number of ED discharges and telemetry downgrades.

Methods

Results

During the study period, there were 4363 patients admitted to the Medicine Service and 3555 patients who qualified as boarders (mean of 29 boarders per 24 hours). The mean boarding time of admitted patients was 440 minutes. A total of 634 patients (17.8% of all boarded patients) were evaluated by the ED hospitalist. The mean daily number of patients seen by the ED hospitalist was 8.0.

The key elements of the delivery of care by the ED hospitalist are summarized in Table 2.

The care of boarded patients included follow‐up of laboratory tests for 74.5% (95% CI, 71‐78%) and medication orders for 79.8% (95% CI, 77‐83%) of patients. A total of 46 patients were discharged by the ED hospitalist (0.6 discharges/day) and telemetry was discontinued for 61 patients (0.8 downgrades/day). The discharge rate was 7.3% (95% CI, 5‐10%) and telemetry downgrade rate was 9.6% (95% CI, 8‐12%) of those patients assessed by the ED hospitalist. Expressed as a percentage of the total ED boarders (n = 3555), the combined discharge rate and the admissions avoided rate was 1.5%.

Table 3 shows the discharge diagnoses made from the ED. Chest pain was the most common diagnosis, followed by syncope, pneumonia, and chronic obstructive pulmonary disease (COPD).

Discussion

Our hospital has successfully implemented an innovative strategy utilizing a hospitalist to help provide seamless care to medical patients located in the ED. Other solutions at our hospital had previously been implemented, but had not adequately addressed the problem, including: (1) protocols to monitor length of stay patterns and deviations, (2) discharge planning activities, (3) organized computerized bed tracking, (4) improvement in the timeliness of ancillary services, (5) daily bed briefing among nurse managers, and (6) 24‐hour presence of a MAR to facilitate triage in the ED.

The current study demonstrates the potential for substantial impact on patient care. The substantial number of the assessed boarder patients for whom laboratory tests (74.5%) and medications (79.8%) were ordered by the ED hospitalists suggests that the quality and timeliness of care was enhanced by this initiative. In addition, the considerable number of patients discharged from the ED and downgraded from telemetry (1.5% and 1.8% of all boarder patients, respectively) suggests that an ED hospitalist may have a meaningful impact on bed utilization and thus decrease ED overcrowding. In 2007, there were 11,488 who qualified as boarders; our data suggest that an ED hospitalist would result in approximately 172 boarders not being admitted annually.

Though the ED LOS was higher during the study period compared to 2007, it was lower than the 2 months immediately preceding implementation of the ED hospitalist role. The ED LOS was 732 and 658 minutes for January and February 2008, respectively, which was markedly increased from 2007 (288 minutes), and prompted development of the ED hospitalist role. The ED LOS during the study period subsequently decreased to 440 minutes. Though the wide fluctuations in ED LOS and the short time period with high ED LOS prior to implementation preclude concluding that the ED hospitalist role decreased ED LOS, the data suggest that an ED hospitalist may be able to improve ED throughput.

The majority of the discharges made by the ED hospitalist are patients who had been admitted for chest pain, had improved, and had negative cardiac enzymes and stress tests. Patients with syncope who were discharged were likely patients without any comorbidities. The COPD and pneumonia admissions were likely patients who improved after aggressive treatment in the ED.

The impact of ED overcrowding on the quality of patient care and outcomes may be substantial. Hwang et al.19 found a direct correlation between ED census and time to pain assessment and administration of analgesic medication. A study at an academic medical center found that higher ED volume was associated with less likelihood of antibiotics being administered within 4 hours for patients with community‐acquired pneumonia.20 A comprehensive review of the literature identified 41 studies examining the effects of ED overcrowding on clinical outcomes and the investigators noted that ED overcrowding was associated with increased in‐hospital mortality.8

Causes of poor outcomes during periods of overcrowding may be the high volume of acute patients preventing adequate time and attention for each ED patient, as well as confusion during the transition from ED to ward physicians. For example, a patient may receive their initial dose of antibiotics from the ED physician, but subsequent doses may be overlooked in the transition of care from the ED physician to the inpatient team. In addition, having admitted patients located in the ED for extended periods of time may lead to these patients not being seen as frequently as patients admitted to the inpatient wards. Another potential consequence of prolonged ED stay for admitted patients is delay in inpatient management. Tests done in the ED may prompt further studies that may not be ordered promptly while patients remain in the ED, which subsequently increases LOS. Other potential issues may be an increase in confusion among geriatric patients in a noisy and crowded ED; decreased access to specialized nursing care that may be available on a hospital ward; decreased access to physical therapy and occupational therapy services; and decreased comfort and satisfaction as patients wait in overcrowded EDs for prolonged periods.

Several other potential innovative solutions to ED overcrowding have been proposed, studied, and tested. These measures generally are focused on improving the three interdependent components of ED workflow: INPUT THROUGHPUT OUTPUT.21, 22 However, process redesign and intervention on these 3 interdependent ED workflow components may be difficult to achieve, especially when hospital resources are limited and when inpatient hospital capacity is already maximized. In some institutions, efforts have been reported to successfully streamline the transfer of admitted ED patients to inpatient beds, through transfer‐to‐ward policy interventions (eg, physician coordinators for patient flow and bed management or transfers made within a defined period of time).2326 However, in a study by Quinn et al.,27 implementation of a rapid admission policy resulted in a decrease of only 10.1 minutes in the ED LOS. Several studies have demonstrated the benefits of an acute medical admissions unit in alleviating ED overcrowding.28, 29 Other unconventional solutions by some hospitals include sending admitted patients to the unit's hallways or placing discharged patients in the hallway while waiting for transportation so that the ED bed will be readily available.30

The ED hospitalist is well‐situated to have an impact on several key hospital outcomes. As the ED hospitalist role was shown to affect processes that relate to ED throughput, it is possible that the role will improve ED overcrowding and decrease ED LOS. Specifically, identifying patients who can be discharged and for whom telemetry is no longer indicated decreases unnecessary bed utilization and allows these beds to be available for other ED patients. This initiative also may promote patient satisfaction by assuring patients that their medical and concerns are being fully addressed while they are in the ED. Increased emphasis on hospital reporting will make patient satisfaction a priority for many hospitals, and the ED hospitalist will be in a unique position to meet and greet patients admitted to the Medicine Service and to reassure them that the medical team is present and addressing their concerns. The hospitalist's ability to facilitate diagnostic testing and treatment while patients remain in the ED may also help decrease the total LOS in the hospital. In addition, the ED hospitalist is also in position to recognize social factors at the earliest stage of admission so that they can be immediately addressed. Future studies will need to be done to determine if this model of transitional care impacts these important factors.

Our study has several important limitations. Most notably, the lack of a comparison interval for which a hospitalist was not assigned to this role prevents us from drawing any definitive conclusions on the benefits of the ED hospitalist model. Also, we collected only summary data and do not have demographic data on the patients managed by the ED hospitalist or information on the ED course of patients who were discharged or had telemetry downgraded. This prevents determination of whether discharged patients did not require admission initially or whose condition evolved over a prolonged ED stay. In addition, other key outcomes, such as patient satisfaction and satisfaction of the ED physicians and nursing staff have not yet been formally measured. Future studies will be needed to determine if an ED hospital model can improve important process and clinical outcomes.

The greatest challenge of this initiative was introducing and familiarizing this role to the key stakeholders, including the ED physicians and nursing staff, house staff, and private practice physicians. Though we did not perform structured surveys on satisfaction, through informal discussions we noted that the role was welcomed with enthusiasm by the ED physicians. Notably, several ED physicians expressed appreciation that they were able to focus their care on new ED patients rather than on the boarded ED patients. Through feedback, we noted soon after implementation that ED faculty and nurses needed further clarification about the potential overlapping roles of the ED hospitalist and ED physicians and ward physicians. These concerns were addressed by educational sessions and announcements, including presentations at ED faculty and staff meetings. The hospitalist assigned to the role each month received individualized orientation prior to assuming the role, and an ED Hospitalist Manual was distributed. Possibly due to these focused sessions, the hospitalists assigned to the role became quickly acclimated.

Conclusions

We have found that designating a hospitalist to directly address the care of ED boarders can enhance the quality and timeliness of care and decrease bed and telemetry utilization with the potential to impact ED and hospital LOS. Given the success of the pilot model, the role was expanded at our institution to 10 hours per day, 7 days per week. Hospitals struggling to address the needs of their admitted patients in the ED should consider incorporating an ED hospitalist to enhance clinical care and address issues relating to throughput. A follow‐up study is needed to more precisely describe the impact of the ED hospitalist model.

Emergency Department (ED) overcrowding has become an important problem in North American hospitals.13 A national survey identified the prolonged length of stay of admitted patients in the ED as the most frequent reason for overcrowding.4 This complex problem occurs when hospital inpatient census increases and prevents admitted patients from being assigned and transported to hospital beds in a timely manner.5 The practice of holding admitted patients in the ED, known as boarding, is typically defined as the length of stay (LOS) in ED beginning 2 hours after the time of admission to the time of transfer to the wards.

In a study of daily mean ED LOS, Rathlev et al.6 concluded that a 5% increase in hospital occupancy resulted in 14 hours of holding time for all patients in the ED, and an observational study found that when hospital occupancy exceeds a threshold of 90%, the ED LOS for admitted patients correspondingly increased.7 Thus, efforts to decrease overcrowding will need to address both ED and hospital throughput and LOS. Most importantly, overcrowding has important consequences on physician and patient satisfaction and the quality of patient care.811

Between 1995 and 2005, ED visits rose 20% from 96.5 million to 115.3 million visits annually, while the number of hospital EDs decreased from 4176 to 3795, making an overall 7% increase in ED utilization rate.12 Similarly, there was a 12% increase in the total inpatient admissions for all registered hospitals in the United States from 31 million in 1995 to 35.3 million in 2005.13 However, despite this increase in demand of ED utilization and inpatient admissions, there had been a steady decline in the supply of hospital beds, from 874,000 in 1995, to 805,000 in 2006.13 These factors have exacerbated the problem of ED overcrowding and boarding.

Not only does boarding entail additional consumption of space, resources, equipment, and manpower, it also potentially compromises patient safety. Typically, hospitalists and inpatient medical teams are engaged in providing care to patients in the wards, while ED physicians and nurses are busy taking care of newly‐arrived ED patients. Non‐ED physicians may have the false impression that their boarded patients, while in the ED, are receiving continuous care and so may decide to delay seeing these patients, which can jeopardize the quality and timeliness of care. Studies have shown that ED overcrowding may potentially lead to poor patient care and outcomes and increased risk for medical errors.1416 ED overcrowding potentially causes multiple effects, including prolonging patient pain and suffering, long patient waiting time, patient dissatisfaction, ambulance diversions, decreased physician productivity, and increased frustration among medical staff.15 In a report by the Joint Commission Accreditation of Healthcare Organizations,17 ED overcrowding was cited as a significant contributing factor in sentinel event cases of patient death or permanent injury due to delays in treatment. Boarding critically ill patients who are physiologically vulnerable and unstable can allow them to be subjected to treatment delays at a pivotal point when time‐sensitive interventions are necessary, ie, sepsis or cardiogenic shockthe golden hour in trauma.16 Medical errors are usually not caused by individual errors but by complex hospital systems; and ED overcrowding is a prime example of a system problem that creates a high‐risk environment for medical errors and threatens patient safety.18

Our hospital commonly has 5 to 15 boarders and often has 20 to 30 boarders at any time. Approximately 90% of these patients are admitted to the Medical Service. In response to this challenge, our institution has designated a full‐time hospitalist to manage boarded patients. The primary goal of this new role is to ensure patient safety and the delivery of high‐quality care while admitted patients are in the ED (Table 1).

The objectives of the study were to determine: (1) the impact on quality of care by assessing laboratory results acted upon and medication follow‐up by the ED hospitalist, and (2) the impact on throughput by assessing the number of ED discharges and telemetry downgrades.

Methods

Results

During the study period, there were 4363 patients admitted to the Medicine Service and 3555 patients who qualified as boarders (mean of 29 boarders per 24 hours). The mean boarding time of admitted patients was 440 minutes. A total of 634 patients (17.8% of all boarded patients) were evaluated by the ED hospitalist. The mean daily number of patients seen by the ED hospitalist was 8.0.

The key elements of the delivery of care by the ED hospitalist are summarized in Table 2.

The care of boarded patients included follow‐up of laboratory tests for 74.5% (95% CI, 71‐78%) and medication orders for 79.8% (95% CI, 77‐83%) of patients. A total of 46 patients were discharged by the ED hospitalist (0.6 discharges/day) and telemetry was discontinued for 61 patients (0.8 downgrades/day). The discharge rate was 7.3% (95% CI, 5‐10%) and telemetry downgrade rate was 9.6% (95% CI, 8‐12%) of those patients assessed by the ED hospitalist. Expressed as a percentage of the total ED boarders (n = 3555), the combined discharge rate and the admissions avoided rate was 1.5%.

Table 3 shows the discharge diagnoses made from the ED. Chest pain was the most common diagnosis, followed by syncope, pneumonia, and chronic obstructive pulmonary disease (COPD).

Discussion

Our hospital has successfully implemented an innovative strategy utilizing a hospitalist to help provide seamless care to medical patients located in the ED. Other solutions at our hospital had previously been implemented, but had not adequately addressed the problem, including: (1) protocols to monitor length of stay patterns and deviations, (2) discharge planning activities, (3) organized computerized bed tracking, (4) improvement in the timeliness of ancillary services, (5) daily bed briefing among nurse managers, and (6) 24‐hour presence of a MAR to facilitate triage in the ED.

The current study demonstrates the potential for substantial impact on patient care. The substantial number of the assessed boarder patients for whom laboratory tests (74.5%) and medications (79.8%) were ordered by the ED hospitalists suggests that the quality and timeliness of care was enhanced by this initiative. In addition, the considerable number of patients discharged from the ED and downgraded from telemetry (1.5% and 1.8% of all boarder patients, respectively) suggests that an ED hospitalist may have a meaningful impact on bed utilization and thus decrease ED overcrowding. In 2007, there were 11,488 who qualified as boarders; our data suggest that an ED hospitalist would result in approximately 172 boarders not being admitted annually.

Though the ED LOS was higher during the study period compared to 2007, it was lower than the 2 months immediately preceding implementation of the ED hospitalist role. The ED LOS was 732 and 658 minutes for January and February 2008, respectively, which was markedly increased from 2007 (288 minutes), and prompted development of the ED hospitalist role. The ED LOS during the study period subsequently decreased to 440 minutes. Though the wide fluctuations in ED LOS and the short time period with high ED LOS prior to implementation preclude concluding that the ED hospitalist role decreased ED LOS, the data suggest that an ED hospitalist may be able to improve ED throughput.

The majority of the discharges made by the ED hospitalist are patients who had been admitted for chest pain, had improved, and had negative cardiac enzymes and stress tests. Patients with syncope who were discharged were likely patients without any comorbidities. The COPD and pneumonia admissions were likely patients who improved after aggressive treatment in the ED.

The impact of ED overcrowding on the quality of patient care and outcomes may be substantial. Hwang et al.19 found a direct correlation between ED census and time to pain assessment and administration of analgesic medication. A study at an academic medical center found that higher ED volume was associated with less likelihood of antibiotics being administered within 4 hours for patients with community‐acquired pneumonia.20 A comprehensive review of the literature identified 41 studies examining the effects of ED overcrowding on clinical outcomes and the investigators noted that ED overcrowding was associated with increased in‐hospital mortality.8

Causes of poor outcomes during periods of overcrowding may be the high volume of acute patients preventing adequate time and attention for each ED patient, as well as confusion during the transition from ED to ward physicians. For example, a patient may receive their initial dose of antibiotics from the ED physician, but subsequent doses may be overlooked in the transition of care from the ED physician to the inpatient team. In addition, having admitted patients located in the ED for extended periods of time may lead to these patients not being seen as frequently as patients admitted to the inpatient wards. Another potential consequence of prolonged ED stay for admitted patients is delay in inpatient management. Tests done in the ED may prompt further studies that may not be ordered promptly while patients remain in the ED, which subsequently increases LOS. Other potential issues may be an increase in confusion among geriatric patients in a noisy and crowded ED; decreased access to specialized nursing care that may be available on a hospital ward; decreased access to physical therapy and occupational therapy services; and decreased comfort and satisfaction as patients wait in overcrowded EDs for prolonged periods.

Several other potential innovative solutions to ED overcrowding have been proposed, studied, and tested. These measures generally are focused on improving the three interdependent components of ED workflow: INPUT THROUGHPUT OUTPUT.21, 22 However, process redesign and intervention on these 3 interdependent ED workflow components may be difficult to achieve, especially when hospital resources are limited and when inpatient hospital capacity is already maximized. In some institutions, efforts have been reported to successfully streamline the transfer of admitted ED patients to inpatient beds, through transfer‐to‐ward policy interventions (eg, physician coordinators for patient flow and bed management or transfers made within a defined period of time).2326 However, in a study by Quinn et al.,27 implementation of a rapid admission policy resulted in a decrease of only 10.1 minutes in the ED LOS. Several studies have demonstrated the benefits of an acute medical admissions unit in alleviating ED overcrowding.28, 29 Other unconventional solutions by some hospitals include sending admitted patients to the unit's hallways or placing discharged patients in the hallway while waiting for transportation so that the ED bed will be readily available.30

The ED hospitalist is well‐situated to have an impact on several key hospital outcomes. As the ED hospitalist role was shown to affect processes that relate to ED throughput, it is possible that the role will improve ED overcrowding and decrease ED LOS. Specifically, identifying patients who can be discharged and for whom telemetry is no longer indicated decreases unnecessary bed utilization and allows these beds to be available for other ED patients. This initiative also may promote patient satisfaction by assuring patients that their medical and concerns are being fully addressed while they are in the ED. Increased emphasis on hospital reporting will make patient satisfaction a priority for many hospitals, and the ED hospitalist will be in a unique position to meet and greet patients admitted to the Medicine Service and to reassure them that the medical team is present and addressing their concerns. The hospitalist's ability to facilitate diagnostic testing and treatment while patients remain in the ED may also help decrease the total LOS in the hospital. In addition, the ED hospitalist is also in position to recognize social factors at the earliest stage of admission so that they can be immediately addressed. Future studies will need to be done to determine if this model of transitional care impacts these important factors.

Our study has several important limitations. Most notably, the lack of a comparison interval for which a hospitalist was not assigned to this role prevents us from drawing any definitive conclusions on the benefits of the ED hospitalist model. Also, we collected only summary data and do not have demographic data on the patients managed by the ED hospitalist or information on the ED course of patients who were discharged or had telemetry downgraded. This prevents determination of whether discharged patients did not require admission initially or whose condition evolved over a prolonged ED stay. In addition, other key outcomes, such as patient satisfaction and satisfaction of the ED physicians and nursing staff have not yet been formally measured. Future studies will be needed to determine if an ED hospital model can improve important process and clinical outcomes.

The greatest challenge of this initiative was introducing and familiarizing this role to the key stakeholders, including the ED physicians and nursing staff, house staff, and private practice physicians. Though we did not perform structured surveys on satisfaction, through informal discussions we noted that the role was welcomed with enthusiasm by the ED physicians. Notably, several ED physicians expressed appreciation that they were able to focus their care on new ED patients rather than on the boarded ED patients. Through feedback, we noted soon after implementation that ED faculty and nurses needed further clarification about the potential overlapping roles of the ED hospitalist and ED physicians and ward physicians. These concerns were addressed by educational sessions and announcements, including presentations at ED faculty and staff meetings. The hospitalist assigned to the role each month received individualized orientation prior to assuming the role, and an ED Hospitalist Manual was distributed. Possibly due to these focused sessions, the hospitalists assigned to the role became quickly acclimated.

Conclusions

We have found that designating a hospitalist to directly address the care of ED boarders can enhance the quality and timeliness of care and decrease bed and telemetry utilization with the potential to impact ED and hospital LOS. Given the success of the pilot model, the role was expanded at our institution to 10 hours per day, 7 days per week. Hospitals struggling to address the needs of their admitted patients in the ED should consider incorporating an ED hospitalist to enhance clinical care and address issues relating to throughput. A follow‐up study is needed to more precisely describe the impact of the ED hospitalist model.

Emergency Department (ED) overcrowding has become an important problem in North American hospitals.13 A national survey identified the prolonged length of stay of admitted patients in the ED as the most frequent reason for overcrowding.4 This complex problem occurs when hospital inpatient census increases and prevents admitted patients from being assigned and transported to hospital beds in a timely manner.5 The practice of holding admitted patients in the ED, known as boarding, is typically defined as the length of stay (LOS) in ED beginning 2 hours after the time of admission to the time of transfer to the wards.

In a study of daily mean ED LOS, Rathlev et al.6 concluded that a 5% increase in hospital occupancy resulted in 14 hours of holding time for all patients in the ED, and an observational study found that when hospital occupancy exceeds a threshold of 90%, the ED LOS for admitted patients correspondingly increased.7 Thus, efforts to decrease overcrowding will need to address both ED and hospital throughput and LOS. Most importantly, overcrowding has important consequences on physician and patient satisfaction and the quality of patient care.811

Between 1995 and 2005, ED visits rose 20% from 96.5 million to 115.3 million visits annually, while the number of hospital EDs decreased from 4176 to 3795, making an overall 7% increase in ED utilization rate.12 Similarly, there was a 12% increase in the total inpatient admissions for all registered hospitals in the United States from 31 million in 1995 to 35.3 million in 2005.13 However, despite this increase in demand of ED utilization and inpatient admissions, there had been a steady decline in the supply of hospital beds, from 874,000 in 1995, to 805,000 in 2006.13 These factors have exacerbated the problem of ED overcrowding and boarding.

Not only does boarding entail additional consumption of space, resources, equipment, and manpower, it also potentially compromises patient safety. Typically, hospitalists and inpatient medical teams are engaged in providing care to patients in the wards, while ED physicians and nurses are busy taking care of newly‐arrived ED patients. Non‐ED physicians may have the false impression that their boarded patients, while in the ED, are receiving continuous care and so may decide to delay seeing these patients, which can jeopardize the quality and timeliness of care. Studies have shown that ED overcrowding may potentially lead to poor patient care and outcomes and increased risk for medical errors.1416 ED overcrowding potentially causes multiple effects, including prolonging patient pain and suffering, long patient waiting time, patient dissatisfaction, ambulance diversions, decreased physician productivity, and increased frustration among medical staff.15 In a report by the Joint Commission Accreditation of Healthcare Organizations,17 ED overcrowding was cited as a significant contributing factor in sentinel event cases of patient death or permanent injury due to delays in treatment. Boarding critically ill patients who are physiologically vulnerable and unstable can allow them to be subjected to treatment delays at a pivotal point when time‐sensitive interventions are necessary, ie, sepsis or cardiogenic shockthe golden hour in trauma.16 Medical errors are usually not caused by individual errors but by complex hospital systems; and ED overcrowding is a prime example of a system problem that creates a high‐risk environment for medical errors and threatens patient safety.18

Our hospital commonly has 5 to 15 boarders and often has 20 to 30 boarders at any time. Approximately 90% of these patients are admitted to the Medical Service. In response to this challenge, our institution has designated a full‐time hospitalist to manage boarded patients. The primary goal of this new role is to ensure patient safety and the delivery of high‐quality care while admitted patients are in the ED (Table 1).

The objectives of the study were to determine: (1) the impact on quality of care by assessing laboratory results acted upon and medication follow‐up by the ED hospitalist, and (2) the impact on throughput by assessing the number of ED discharges and telemetry downgrades.

Methods

Results

During the study period, there were 4363 patients admitted to the Medicine Service and 3555 patients who qualified as boarders (mean of 29 boarders per 24 hours). The mean boarding time of admitted patients was 440 minutes. A total of 634 patients (17.8% of all boarded patients) were evaluated by the ED hospitalist. The mean daily number of patients seen by the ED hospitalist was 8.0.

The key elements of the delivery of care by the ED hospitalist are summarized in Table 2.

The care of boarded patients included follow‐up of laboratory tests for 74.5% (95% CI, 71‐78%) and medication orders for 79.8% (95% CI, 77‐83%) of patients. A total of 46 patients were discharged by the ED hospitalist (0.6 discharges/day) and telemetry was discontinued for 61 patients (0.8 downgrades/day). The discharge rate was 7.3% (95% CI, 5‐10%) and telemetry downgrade rate was 9.6% (95% CI, 8‐12%) of those patients assessed by the ED hospitalist. Expressed as a percentage of the total ED boarders (n = 3555), the combined discharge rate and the admissions avoided rate was 1.5%.

Table 3 shows the discharge diagnoses made from the ED. Chest pain was the most common diagnosis, followed by syncope, pneumonia, and chronic obstructive pulmonary disease (COPD).

Discussion

Our hospital has successfully implemented an innovative strategy utilizing a hospitalist to help provide seamless care to medical patients located in the ED. Other solutions at our hospital had previously been implemented, but had not adequately addressed the problem, including: (1) protocols to monitor length of stay patterns and deviations, (2) discharge planning activities, (3) organized computerized bed tracking, (4) improvement in the timeliness of ancillary services, (5) daily bed briefing among nurse managers, and (6) 24‐hour presence of a MAR to facilitate triage in the ED.

The current study demonstrates the potential for substantial impact on patient care. The substantial number of the assessed boarder patients for whom laboratory tests (74.5%) and medications (79.8%) were ordered by the ED hospitalists suggests that the quality and timeliness of care was enhanced by this initiative. In addition, the considerable number of patients discharged from the ED and downgraded from telemetry (1.5% and 1.8% of all boarder patients, respectively) suggests that an ED hospitalist may have a meaningful impact on bed utilization and thus decrease ED overcrowding. In 2007, there were 11,488 who qualified as boarders; our data suggest that an ED hospitalist would result in approximately 172 boarders not being admitted annually.

Though the ED LOS was higher during the study period compared to 2007, it was lower than the 2 months immediately preceding implementation of the ED hospitalist role. The ED LOS was 732 and 658 minutes for January and February 2008, respectively, which was markedly increased from 2007 (288 minutes), and prompted development of the ED hospitalist role. The ED LOS during the study period subsequently decreased to 440 minutes. Though the wide fluctuations in ED LOS and the short time period with high ED LOS prior to implementation preclude concluding that the ED hospitalist role decreased ED LOS, the data suggest that an ED hospitalist may be able to improve ED throughput.

The majority of the discharges made by the ED hospitalist are patients who had been admitted for chest pain, had improved, and had negative cardiac enzymes and stress tests. Patients with syncope who were discharged were likely patients without any comorbidities. The COPD and pneumonia admissions were likely patients who improved after aggressive treatment in the ED.

The impact of ED overcrowding on the quality of patient care and outcomes may be substantial. Hwang et al.19 found a direct correlation between ED census and time to pain assessment and administration of analgesic medication. A study at an academic medical center found that higher ED volume was associated with less likelihood of antibiotics being administered within 4 hours for patients with community‐acquired pneumonia.20 A comprehensive review of the literature identified 41 studies examining the effects of ED overcrowding on clinical outcomes and the investigators noted that ED overcrowding was associated with increased in‐hospital mortality.8

Causes of poor outcomes during periods of overcrowding may be the high volume of acute patients preventing adequate time and attention for each ED patient, as well as confusion during the transition from ED to ward physicians. For example, a patient may receive their initial dose of antibiotics from the ED physician, but subsequent doses may be overlooked in the transition of care from the ED physician to the inpatient team. In addition, having admitted patients located in the ED for extended periods of time may lead to these patients not being seen as frequently as patients admitted to the inpatient wards. Another potential consequence of prolonged ED stay for admitted patients is delay in inpatient management. Tests done in the ED may prompt further studies that may not be ordered promptly while patients remain in the ED, which subsequently increases LOS. Other potential issues may be an increase in confusion among geriatric patients in a noisy and crowded ED; decreased access to specialized nursing care that may be available on a hospital ward; decreased access to physical therapy and occupational therapy services; and decreased comfort and satisfaction as patients wait in overcrowded EDs for prolonged periods.

Several other potential innovative solutions to ED overcrowding have been proposed, studied, and tested. These measures generally are focused on improving the three interdependent components of ED workflow: INPUT THROUGHPUT OUTPUT.21, 22 However, process redesign and intervention on these 3 interdependent ED workflow components may be difficult to achieve, especially when hospital resources are limited and when inpatient hospital capacity is already maximized. In some institutions, efforts have been reported to successfully streamline the transfer of admitted ED patients to inpatient beds, through transfer‐to‐ward policy interventions (eg, physician coordinators for patient flow and bed management or transfers made within a defined period of time).2326 However, in a study by Quinn et al.,27 implementation of a rapid admission policy resulted in a decrease of only 10.1 minutes in the ED LOS. Several studies have demonstrated the benefits of an acute medical admissions unit in alleviating ED overcrowding.28, 29 Other unconventional solutions by some hospitals include sending admitted patients to the unit's hallways or placing discharged patients in the hallway while waiting for transportation so that the ED bed will be readily available.30

The ED hospitalist is well‐situated to have an impact on several key hospital outcomes. As the ED hospitalist role was shown to affect processes that relate to ED throughput, it is possible that the role will improve ED overcrowding and decrease ED LOS. Specifically, identifying patients who can be discharged and for whom telemetry is no longer indicated decreases unnecessary bed utilization and allows these beds to be available for other ED patients. This initiative also may promote patient satisfaction by assuring patients that their medical and concerns are being fully addressed while they are in the ED. Increased emphasis on hospital reporting will make patient satisfaction a priority for many hospitals, and the ED hospitalist will be in a unique position to meet and greet patients admitted to the Medicine Service and to reassure them that the medical team is present and addressing their concerns. The hospitalist's ability to facilitate diagnostic testing and treatment while patients remain in the ED may also help decrease the total LOS in the hospital. In addition, the ED hospitalist is also in position to recognize social factors at the earliest stage of admission so that they can be immediately addressed. Future studies will need to be done to determine if this model of transitional care impacts these important factors.

Our study has several important limitations. Most notably, the lack of a comparison interval for which a hospitalist was not assigned to this role prevents us from drawing any definitive conclusions on the benefits of the ED hospitalist model. Also, we collected only summary data and do not have demographic data on the patients managed by the ED hospitalist or information on the ED course of patients who were discharged or had telemetry downgraded. This prevents determination of whether discharged patients did not require admission initially or whose condition evolved over a prolonged ED stay. In addition, other key outcomes, such as patient satisfaction and satisfaction of the ED physicians and nursing staff have not yet been formally measured. Future studies will be needed to determine if an ED hospital model can improve important process and clinical outcomes.

The greatest challenge of this initiative was introducing and familiarizing this role to the key stakeholders, including the ED physicians and nursing staff, house staff, and private practice physicians. Though we did not perform structured surveys on satisfaction, through informal discussions we noted that the role was welcomed with enthusiasm by the ED physicians. Notably, several ED physicians expressed appreciation that they were able to focus their care on new ED patients rather than on the boarded ED patients. Through feedback, we noted soon after implementation that ED faculty and nurses needed further clarification about the potential overlapping roles of the ED hospitalist and ED physicians and ward physicians. These concerns were addressed by educational sessions and announcements, including presentations at ED faculty and staff meetings. The hospitalist assigned to the role each month received individualized orientation prior to assuming the role, and an ED Hospitalist Manual was distributed. Possibly due to these focused sessions, the hospitalists assigned to the role became quickly acclimated.

Conclusions

We have found that designating a hospitalist to directly address the care of ED boarders can enhance the quality and timeliness of care and decrease bed and telemetry utilization with the potential to impact ED and hospital LOS. Given the success of the pilot model, the role was expanded at our institution to 10 hours per day, 7 days per week. Hospitals struggling to address the needs of their admitted patients in the ED should consider incorporating an ED hospitalist to enhance clinical care and address issues relating to throughput. A follow‐up study is needed to more precisely describe the impact of the ED hospitalist model.