Correspondence to Dr Jinhyun Kim; [email protected]
STRENGTHS AND LIMITATIONS OF THIS STUDY
This cohort study was conducted among a large number of medical inpatients who were admitted through the emergency department (ED) to assess the impact of acute medical unit hospitalist care compared with non-hospitalist care.
The study was retrospective in nature and was conducted at a single institution.
However, all medical inpatients admitted from the ED to general medical wards between 1 June 2016 and 31 May 2017 were included, lending a certain degree of credibility to the results.
Introduction
The hospitalist care model in South Korea was introduced to improve the quality of inpatient care and to address the issue of a reduced number of available medical residents—owing to the Resident Act, which limited their work hours to 80/week.1 As of July 2019, approximately 140 physicians in South Korea work as hospitalists and are in charge of approximately 2200 beds in 22 tertiary hospitals and 10 general hospitals.1
A hospitalist—a medical doctor in charge of inpatient care during hospital stays—is defined as a ‘dedicated specialist that directly takes comprehensive responsibility for the managed care of inpatients during admission’.2 3 The two principles that guide the hospitalist’s role are comprehensiveness and continuity.3 4 In the USA, hospitalists were effective in improving patient satisfaction and in reducing patients’ length of hospital stays, readmission rates and medical costs.5 A hospitalist care model in Korea was introduced to enhance the safety and efficiency of inpatient care and to eliminate gaps in medical staffing that resulted from improvements in the residents’ training environment.2
In contrast to the hospitalist care model in the USA, the acute medical care model developed in the UK was concerned with immediate and early specialist management of adult patients with a wide range of medical conditions requiring urgent or emergency care.6 Patients that could be stabilised, treated and discharged were efficiently dealt with in the acute medical unit (AMU). When a patient appeared to need a longer hospital stay, they were offered a rapid and appropriate transfer from the AMU to the specialty ward. The key to this hand-off was close cooperation and mutual respect between the providers of complementary specialties.7
A census of the Royal College of Physicians reported rapid growth in the implementation of the acute medical care model in the UK; there was a 63% increase in the number of consultants in acute medicine between 2002 and 2007. Previous studies, evaluating the efficacy of AMUs, have reported reductions in mortality and lengths of hospital stays.8–10
The Seoul National University Bundang Hospital adopted both the hospitalist care model and the AMU model. Our institution established the first hospital medicine centre in Korea and opened a hospitalist-run AMU in August 2015. The AMU started with a 20-bed ward, where patients with acute medical needs, who were admitted through the emergency department (ED), received appropriate and timely medical care. They were discharged within 72 hours after the end of treatment in the AMU, or transferred to another special ward for additional care, as required.4 In 2017, the hospitalist team of our hospital reported the effects of the implementation of the AMU. The AMU reduced the ED length of stay (ED-LOS) by 40%, and remarkably shortened the length of hospital stay, from 10 days to 9.1 days.11 However, no study has thoroughly evaluated the effects of the implementation of AMU on patient outcomes, including in-hospital mortality, the intensive care unit (ICU) admission rate or the readmission rate. Therefore, this study aimed to evaluate the effects of the establishment of an AMU operated according to the Korean hospitalist care model on patient outcomes and to provide supporting data that may help inform the design of the most efficient Korean hospitalist care model.
Methods
AMU setting
The AMU had 28 beds; however, it initially started with 20 beds. Medical patients waiting in the ED were randomly admitted to either the AMU or the medical ward, as soon as a bed was available. Patients in the AMU were rapidly evaluated and cared for by four internists, who served as hospitalists, from the following four specialist fields: infectious diseases, pulmonology and critical care, nephrology and endocrinology. They had an average of 10.0 years of clinical experience (range 8–13 years). Two AMU hospitalists were responsible for the patients admitted to the AMU during the daytime for 7 days/week. The hospitalists rotated on a weekly to biweekly basis and did not participate in resident teaching during AMU shifts.
Furthermore, non-hospitalist inpatient care was administered by subspecialists and residents in a specialty medical ward, where residents (usually first-year and second-year residents) were mainly in charge of inpatient care, under the supervision of an attending physician with an average clinical experience of 19.5 years (range: 8–36 years). The AMU hospitalist care at our institution mainly focused on acute and general care. In contrast, non-hospitalist care in the specialty medical ward was focused on long-term and specialised care. The AMU models of Korea and the UK are compared in online supplemental file 1.12
Study design
This was a retrospective cohort study that employed a secondary analysis of data extracted from clinical records and hospital administrative information from the Electronic Medical Record system of our institution.
Study participants
All medical inpatients admitted from the ED between 1 June 2016 and 31 May 2017 were included and allocated to the hospitalist or case group (admitted to AMU and cared for by hospitalists) and control or non-hospitalist group (admitted to the medical ward and cared for by non-hospitalists). We excluded patients who were admitted to the ICU and surgical ward via the ED. A flow diagram of the study population selection is presented in online supplemental file 2.
Variables
We measured the following outcome variables: in-hospital mortality (IHM), ICU admission, LOS, ED-LOS and unscheduled readmissions (within 10 days and 30 days). ‘IHM’ was defined as the ratio of inpatient deaths to the total number of inpatients. ‘ICU admission’ was defined as entry into the ICU. When a patient was admitted more than once during a single hospital stay, only the features of the first admission were analysed. The ‘LOS’ was defined as the duration of a single episode of hospitalisation and was calculated by subtracting the date of admission from the date of discharge. The ‘ED-LOS’ was defined as the time spent waiting in the ED before admission to the AMU or a medical ward. ‘Readmissions’ were identified as an unscheduled admission via the ED, owing to any cause within 10 or 30 days after discharge.
We recorded the following clinical variables of the participants: age, sex, prior hospitalisation, cardiopulmonary resuscitation (CPR) incidence, cause of ICU admission, referral to a specialty, consultations, surgical intervention (cases performed during the hospitalisation, not before), major diagnosis (based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Australian Modification (ICD-10)), the Korean Triage and Acuity Scale (KTAS), the Age-adjusted Charlson Comorbidity Index (ACCI), and the Acute Physiology and Chronic Health Evaluation (APACHE) II score.
Measurement of severity of illness
The KTAS consists of five stages: resuscitation, emergency, urgent, less urgent and non-urgent. This was Korea’s first unified emergency patient triage system at the national level. It was developed according to the domestic situation in Korea and was based on the Canadian Triage and Acuity Scale.13 The KTAS, which is currently applied in emergency medical centres in Korea, is a national standardised classification tool for evaluating illness severity. It is the only tool commonly available for assessing patients from the prehospital phase to the hospital phase. Previous validity testing demonstrated that the higher the severity level of the illness, the higher the ICU and general hospital admission rates, the LOS, the number of clinic consultations, the CT scan rate, the emergency intervention rate and the ED medical expenses. Thus, the KTAS was confirmed as a valid tool that reflected the severity trend, and it is currently used in national and regional emergency medical centres.13 Accordingly, in this study, we used the KTAS to compare the severity of conditions among patients.
Measurement of the degree of comorbidity
The comorbidity score was calculated with the Charlson Comorbidity Index (CCI). The CCI score is the sum of 1, 2, 3 and 6 weighted values for 17 disease groups, ranging from 0 to 29; higher scores indicate higher severity.14 Additionally, because age was determined to be a significant factor of survival, it was subsequently incorporated into the Charlson comorbidity score to create a single index that accounted for both age and comorbidity; that is, the ACCI.15 The ACCI was calculated with additional points added for age (1 point was added for each decade over 40 years of age, ranging from 0 to 4). In addition, the clinical comorbidities were translated into ICD codes, which were used as a risk-adjustment tool based on administrative data.16 Therefore, in this study, we used ICD-coded data and age to calculate the ACCI score.
Comparison of disease severity among ICU admissions
The APACHE II scoring system has been widely recognised as an ICU prognostic scoring model.17–19 The APACHE II score uses the worst values of 12 physiological variables, including blood pressure, heart rate, body temperature, oxygenation, Glasgow Coma Score during the first 24 hours after ICU admission, an evaluation of the patient’s chronic health issues, age and the type of ICU admission.20 The APACHE II score was shown to be an accurate measurement of the severity of a patient’s disease and was strongly correlated with outcomes among patients in critical conditions.17 This score (range: 0–71) was closely correlated with the risk of hospital death.18 Consequently, we used the APACHE II score to compare the disease severity among ICU admissions.
Statistical analysis
Categorical variables were reported as percentages, and continuous variables are reported as the mean±SD. Groups were compared with Pearson’s Χ2 test or the t-test, as appropriate. ACCI, the LOS and the ED-LOS were expressed as the median and IQR. For these variables, groups were compared with the Mann-Whitney U test, owing to their skewed data distributions. We performed subgroup analyses according to the severity of the patient’s condition (based on the KTAS score), the degree of comorbidity (based on the ACCI) and the major disease category (based on the ICD-10).
We identified disease codes for the 10 most frequent diseases in the cohort. The remaining diseases were aggregated into a single category designated as others. We then included these disease codes as dummy variables in the regression models to determine the extent to which they affected the outcome. The main analyses focused on the five outcome measures for the case and control groups. The logistic regression model (with IHM, ICU admission and all-cause unscheduled readmissions as binary outcomes) and linear regression model (with LOS and ED-LOS as continuous variables) were used to adjust for the following factors: age, sex, prior hospitalisation, KTAS score, ACCI score, surgical intervention and major disease. Using the estimates from the regression models, we presented differences between the hospitalist and the non-hospitalist groups in the IHM rate, ICU admission rate, all-cause unscheduled readmission rate, LOS and ED-LOS.
Patient and public involvement
This study was conducted retrospectively as a non-interventional research endeavour. As a result, no patients were directly involved in the design of the study, the formulation of research objectives and questions, or the execution of the study. Furthermore, patients did not participate in the interpretation of the results or the preparation of the manuscript. It is not within our current plans to distribute the findings to the participants of the study.
Results
Baseline characteristics
Among the 6391 patients with data available for analysis, 2426 received hospitalist care and 3965 received non-hospitalist care. The clinical baseline features and outcomes of all patients are shown in table 1. There were no differences in sex (p=0.120), the number of prior hospitalisation (p=0.480) or the CPR incidence (p=0.244) between the hospitalist and non-hospitalist groups. Compared with the hospitalist group, the non-hospitalist group was older (63.24±16.20 vs 67.38±16.52 years, p<0.001) and had a higher proportion of individuals over 80 years old (15% vs 25%, p<0.001), a higher proportion of individuals who underwent surgical interventions (11.6% vs 14.1%, p=0.004) and a higher frequency of consultations (3.50±6.18 vs 3.99±7.02, p=0.004). Based on the KTAS, the hospitalist group had a higher proportion of patients who required urgent care (KTAS=3, 70.0%) compared with the non-hospitalist group (63.3%). Moreover, the distributions of patients with KTAS=2 (13.4% vs 23.7%, hospitalist vs non-hospitalist group, respectively) and KTAS=4 (15.1% vs 10.2%, hospitalist vs non-hospitalist group, respectively) were significantly different between the two groups (p<0.001 for both). The most common underlying disease in the hospitalist and non-hospitalist groups was malignant neoplasm (34.8% and 22.4%, respectively). The distribution of major diseases was significantly different between groups (p<0.001), whereas the ACCI scores were not significantly different between the groups (median (IQR): 4 (2–5) vs 4 (2–5), p=0.055).
Table 1Baseline characteristics of patients cared for by hospitalists and non-hospitalists (N=6391)
| Baseline characteristics | Hospitalist (n=2426) | Non-hospitalist (n=3965) | P value |
| Sex | |||
| 1387 (57.2) | 2188 (55.2) | 0.120 | |
| 1039 (42.8) | 1777 (44.8) | ||
| Age (years) | 63.24±16.20 | 67.38±16.52 | <0.001 |
| 488 (20.1) | 610 (15.4) | <0.001 | |
| 401 (16.5) | 499 (12.6) | ||
| 542 (22.3) | 733 (18.5) | ||
| 632 (26.1) | 1131 (28.5) | ||
| 363 (15.0) | 992 (25.0) | ||
| Prior hospitalisation | 2101 (86.6) | 3373 (85.1) | 0.090 |
| Number of prior hospital admissions | 3.16±4.07 | 3.24±4.20 | 0.480 |
| Korean Triage and Acuity Scale | |||
| 12 (0.5) | 69 (1.7) | <0.001 | |
| 324 (13.4) | 941 (23.7) | ||
| 1699 (70.0) | 2511 (63.3) | ||
| 367 (15.1) | 403 (10.2) | ||
| 24 (1.0) | 41 (1.0) | ||
| Major disease | |||
| 845 (34.8) | 890 (22.4) | <0.001 | |
| 48 (2.0) | 552 (13.9) | ||
| 266 (11.0) | 875 (22.1) | ||
| 441 (18.2) | 424 (10.7) | ||
| 202 (8.3) | 375 (9.5) | ||
| 162 (6.7) | 167 (4.2) | ||
| 86 (3.5) | 204 (5.1) | ||
| 95 (3.9) | 158 (4.0) | ||
| 130 (5.4) | 47 (1.2) | ||
| 58 (2.4) | 89 (2.2) | ||
| 93 (3.8) | 184 (4.6) | ||
| Age-adjusted Charlson Comorbidity Index | 3.82±2.63 | 3.77±2.19 | |
| Median (IQR) | 4 (2–5) | 4 (2–5) | 0.055 |
| 729 (30.0) | 1018 (25.7) | 0.001 | |
| 436 (18.0) | 733 (18.5) | ||
| 502 (20.7) | 943 (23.8) | ||
| 759 (31.3) | 1271 (32.1) | ||
| Surgical intervention | 282 (11.6) | 560 (14.1) | 0.004 |
| CPR incidence | 15 (0.6) | 35 (0.9) | 0.244 |
| Consultation | 1830 (75.4) | 2946 (74.3) | 0.312 |
| The number of consultations | 3.50±6.18 | 3.99±7.02 | 0.004 |
| Referral to a specialty | 1613 (66.5) | 450 (11.3) | <0.001 |
| Type of specialty referral (n=2063) | |||
| 658 (40.8) | 114 (25.3) | <0.001 | |
| 360 (22.3) | 20 (4.4) | ||
| 174 (10.8) | 53 (11.8) | ||
| 96 (6.0) | 11 (2.4) | ||
| 96 (6.0) | 8 (1.8) | ||
| 80 (5.0) | 9 (2.0) | ||
| 149 (9.2) | 235 (52.2) | ||
| Outcomes | |||
| 117 (4.8) | 361 (9.1) | <0.001 | |
| 95 (3.9) | 343 (8.7) | <0.001 | |
| Cause of ICU admission (n=438) | |||
| 55 (57.9) | 223 (65.0) | 0.077 | |
| 23 (24.2) | 78 (22.7) | ||
| 7 (7.4) | 17 (5.0) | ||
| 7 (7.4) | 12 (3.5) | ||
| 0 (0.0) | 8 (2.3) | ||
| 3 (3.2) | 2 (0.6) | ||
| 0 (0.0) | 3 (0.9) | ||
| APACHE II score at ICU admission (n=438) | 25.20±10.62 | 21.26±12.03 | 0.004 |
| Length of hospital stay (days) | 10.56±11.68 | 11.40±12.36 | |
| 7 (4–12) | 8 (5–13) | 0.007 | |
| ED-LOS (hours) | 11.24±8.49 | 13.74±10.11 | |
| 8.4 (6.1–12.7) | 10.2 (6.7–19.0) | <0.001 | |
| Readmission within 10 days | 117 (4.8) | 177 (4.5) | 0.507 |
| Readmission within 30 days | 277 (11.4) | 416 (10.5) | 0.248 |
Data are presented as the mean±SD, number (%) or median (IQR), as indicated.
‘Surgical intervention’ implies the patient underwent surgery during the hospital stay, not before.
APACHE, Acute Physiology and Chronic Health Evaluation; CPR, cardiopulmonary resuscitation; ED-LOS, emergency department length of stay; GI, gastrointestinal; ICU, intensive care unit.
Compared with the non-hospitalist group, the hospitalist group had lower rates of IHM (4.8% vs 9.1%, p<0.001) and ICU admissions (3.9% vs 8.7%, p<0.001). Among the patients admitted to the ICU, the hospitalist group displayed greater disease severity than the non-hospitalist group (APACHE II scores: 25.20±10.62 vs 21.26±12.03, p=0.004). The hospitalist group had shorter LOS (median (IQR): 7 (4–12) vs 8 (5–13) days, p=0.007) and shorter ED-LOS (median (IQR): 8.4 (6.1–12.7) vs 10.2 (6.7–19) hours, p<0.001) than the non-hospitalist group. However, there were no significant differences between the two groups in the readmission rates within 10 or 30 days (p=0.507 and p=0.248, respectively).
Subgroup analysis, according to KTAS, comorbidity severity and major disease
We performed subgroup analyses of patients stratified by KTAS and ACCI scores to determine differences between the two groups (table 2 and online supplemental file 3, respectively). Among the more urgent cases, the hospitalist group showed lower rates of IHM (4.8% vs 9.8%, p<0.001) and ICU admission (4.0% vs 9.1%, p<0.001) compared with the non-hospitalist group.
Table 2Analysis of variables for urgent and non-urgent cases treated by a hospitalist or non-hospitalist (N=6391)
| Variable | KTAS 1–3: more urgent (N=5556) | KTAS 4–5: less urgent (N=835) | ||||
| HG (n=2035) | NHG (n=3521) | P value | HG (n=391) | NHG (n=444) | P value | |
| ACCI | 3.87±2.63 | 3.83±2.17 | 3.56±2.66 | 3.23±2.28 | ||
| Median (IQR) | 4 (2–5) | 4 (3–5) | 0.037 | 3 (2–5) | 3 (2–5) | 0.236 |
| CPR incidence | 12 (0.6) | 35 (1.0) | 0.113 | 3 (0.8) | 0 (0.0) | 0.064 |
| IHM | 98 (4.8) | 345 (9.8) | <0.001 | 19 (4.9) | 16 (3.6) | 0.366 |
| ICU admission | 81 (4.0) | 319 (9.1) | <0.001 | 14 (3.6) | 24 (5.4) | 0.207 |
| Cause of ICU admission (n=438) | ||||||
| Close monitoring after procedure or surgical intervention | 44 (54.3) | 202 (63.3) | 0.040 | 11 (78.6) | 21 (87.5) | 0.580 |
| Respiratory failure or insufficiency | 21 (25.9) | 77 (24.1) | 2 (14.3) | 1 (4.2) | ||
| Septic shock | 6 (7.4) | 16 (5.0) | 1 (7.1) | 1 (4.2) | ||
| Cardiovascular failure or insufficiency | 7 (8.6) | 11 (3.4) | 0 (0.0) | 1 (4.2) | ||
| Metabolic/renal failure | 0 (0.0) | 8 (2.5) | 0 (0.0) | 0 (0.0) | ||
| GI bleeding | 3 (3.7) | 2 (0.6) | 0 (0.0) | 0 (0.0) | ||
| Neurogenic dysfunction | 0 (0.0) | 3 (0.9) | 0 (0.0) | 0 (0.0) | ||
| APACHE II score of ICU admission (n=438) | 25.15±10.62 | 21.65±12.11 | 0.018 | 25.50±11.00 | 16.17±9.78 | 0.010 |
| LOS (days) | 10.63±12.06 | 11.47±12.48 | 10.22±9.42 | 10.80±11.41 | ||
| Median (IQR) | 7 (4–12) | 8 (5–13) | 0.014 | 7 (5–12) | 7 (5–12) | 0.433 |
| ED-LOS (hours) | 11.38±8.56 | 13.87±10.16 | 10.54±8.09 | 12.71±9.59 | ||
| Median (IQR) | 8.4 (6.2–13.1) | 10.3 (6.8–19.1) | <0.001 | 7.8 (5.9–11.0) | 8.9 (6.2–18.3) | <0.001 |
| Readmission within 10 days | 106 (5.2) | 162 (4.6) | 0.308 | 11 (2.8) | 15 (3.4) | 0.639 |
| Readmission within 30 days | 240 (11.8) | 381 (10.8) | 0.268 | 37 (9.5) | 35 (7.9) | 0.417 |
Data are presented as mean±SD, number (%) or median (IQR), as indicated.
ACCI, Age-adjusted Charlson Comorbidity Index; APACHE, Acute Physiology and Chronic Health Evaluation; CPR, cardiopulmonary resuscitation; ED-LOS, emergency department length of stay; GI, gastrointestinal; HG, hospitalist group; ICU, intensive care unit; IHM, in-hospital mortality; KTAS, Korean Triage and Acuity Scale; LOS, length of hospital stay; NHG, non-hospitalist group.
Among the more urgent cases, patients in the hospitalist group had shorter LOS (median (IQR): 7 (4–12) vs 8 (5–13) days, p=0.014) and shorter ED-LOS (median (IQR): 8.4 (6.2–13.1) vs 10.3 (6.8–19.1) hours, p<0.001) compared with patients in the non-hospitalist group. Among the less urgent cases, the hospitalist group had shorter ED-LOS (median (IQR): 7.8 (5.9–11.0) vs 8.9 (6.2–18.3) hours, p<0.001) than the non-hospitalist group. However, other variables were not significantly different between the groups.
In the moderate-to-high comorbidity groups (ACCI=3, 4 and 5 points), IHM was significantly lower in the hospitalist group than in the non-hospitalist group (p=0.009, p<0.001 and p=0.002, respectively). In the low-to-moderate comorbidity groups (ACCI=2, 3 and 4 points), ICU admission was significantly lower in the hospitalist group than in the non-hospitalist group (p<0.001, p<0.001 and p<0.001, respectively). In all ACCI groups, the ED-LOS was considerably shorter in the hospitalist group than in the non-hospitalist group.
We performed another analysis of subgroups stratified by the major disease to determine whether the two groups showed differences in IHM (online supplemental file 4). Among patients with malignant neoplasms, infectious diseases and diseases involving the respiratory system, digestive system, musculoskeletal system and connective tissue, IHM was significantly lower in the hospitalist group than in the non-hospitalist group (p<0.001, p=0.008, p=0.006, p=0.010 and p=0.043, respectively).
Regression analysis of associations between clinical factors and major outcomes
We performed logistic regression analysis to adjust clinical variables potentially associated with the four major outcomes: IHM, ICU admission, readmission within 10 days and readmission within 30 days (table 3). Logistic regression analysis revealed significantly lower rates of IHM (OR: 0.43; 95% CI: 0.34 to 0.54; p<0.001) and ICU admission (OR: 0.72; 95% CI: 0.55 to 0.93; p=0.013) in the hospitalist group compared with the non-hospitalist group. However, there was no significant difference in the readmission rates within 10 or 30 days between the two groups (10-day rates: p=0.974, 30-day rates: p=0.965).
Table 3Logistic regression analysis of factors potentially associated with IHM, readmissions and ICU admission (N=6391)
| Variables | IHM | Readmission (10 days) | Readmission (30 days) | ICU admission | ||||
| OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | |
| HG (ref=NHG) | 0.43 (0.34, 0.54) | <0.001 | 0.99 (0.77, 1.28) | 0.974 | 0.99 (0.84, 1.18) | 0.965 | 0.72 (0.55, 0.93) | 0.013 |
| Female (ref=male) | 0.78 (0.64, 0.96) | 0.017 | 0.94 (0.73, 1.19) | 0.571 | 0.89 (0.76, 1.05) | 0.168 | 0.73 (0.58, 0.91) | 0.005 |
| Age | 1.02 (1.01, 1.03) | <0.001 | 0.99 (0.99, 1.00) | 0.127 | 0.99 (0.99, 1.00) | 0.038 | 1.00 (0.99, 1.01) | 0.558 |
| Prior hospitalisation | 1.06 (1.04, 1.08) | <0.001 | 1.05 (1.03, 1.07) | <0.001 | 1.05 (1.03, 1.07) | <0.001 | 0.98 (0.95, 1.01) | 0.200 |
| KTAS (ref=more urgent group)* | 0.57 (0.40, 0.83) | 0.003 | 0.64 (0.42, 0.97) | 0.036 | 0.78 (0.60, 1.01) | 0.061 | 0.74 (0.51, 1.07) | 0.113 |
| ACCI | 1.09 (1.04, 1.14) | <0.001 | 1.07 (1.02, 1.13) | 0.007 | 1.08 (1.04, 1.12) | <0.001 | 1.08 (1.03, 1.14) | 0.003 |
| Diseases (ref=malignant neoplasms) | ||||||||
| Circulatory system | 0.17 (0.10, 0.26) | <0.001 | 0.56 (0.40, 0.94) | 0.028 | 0.56 (0.40, 0.79) | 0.001 | 12.54 (8.75, 17.97) | <0.001 |
| Respiratory system | 0.44 (0.34, 0.58) | <0.001 | 0.67 (0.46, 0.99) | 0.039 | 0.67 (0.52, 0.87) | 0.002 | 1.55 (1.08, 2.24) | 0.019 |
| Digestive system | 0.18 (0.12, 0.28) | <0.001 | 0.66 (0.44, 0.99) | 0.044 | 0.58 (0.44, 0.77) | <0.001 | 0.77 (0.46, 1.30) | 0.324 |
| Genitourinary system | 0.10 (0.05, 0.18) | <0.001 | 0.43 (0.25, 0.76) | 0.003 | 0.53 (0.37, 0.74) | <0.001 | 0.80 (0.47, 1.37) | 0.417 |
| Symptoms, signs, and abnormal clinical and laboratory findings | 0.18 (0.09, 0.38) | <0.001 | 0.85 (0.48, 1.51) | 0.588 | 0.64 (0.42, 0.97) | 0.035 | 0.65 (0.30, 1.39) | 0.264 |
| Certain infectious and parasitic diseases | 0.38 (0.22, 0.65) | <0.001 | 0.70 (0.37, 1.34) | 0.283 | 0.50 (0.31, 0.82) | 0.005 | 1.15 (0.62, 2.17) | 0.650 |
| Endocrine, nutritional and metabolic diseases | 0.03 (0.00, 0.19) | <0.001 | 0.75 (0.40, 1.44) | 0.390 | 0.79 (0.52, 1.21) | 0.284 | 0.79 (0.33, 1.88) | 0.594 |
| Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism | 0.39 (0.18, 0.85) | 0.018 | 0.48 (0.19, 1.19) | 0.111 | 0.76 (0.46, 1.25) | 0.278 | 1.36 (0.56, 3.28) | 0.496 |
| Diseases of the musculoskeletal system and connective tissue | 0.33 (0.14, 0.77) | 0.010 | 0.38 (0.12, 1.21) | 0.102 | 0.24 (0.10, 0.59) | 0.002 | 3.67 (1.98, 6.80) | <0.001 |
| Others | 0.30 (0.17, 0.54) | <0.001 | 0.74 (0.40, 1.38) | 0.344 | 0.61 (0.39, 0.95) | 0.030 | 2.33 (1.36, 3.99) | 0.002 |
| Surgical intervention | 8.47 (6.64, 10.82) | <0.001 | ||||||
*The less urgent group with KTAS=4–5 was compared with the more urgent group with KTAS=1–3.
ACCI, Age-adjusted Charlson Comorbidity Index; HG, hospitalist group; ICU, intensive care unit; IHM, in-hospital mortality; KTAS, Korean Triage and Acuity Scale; NHG, non-hospitalist group; ref, reference group.
We also performed linear regression analysis to adjust clinical factors associated with LOS and the ED-LOS (table 4). Both the LOS (coefficient: −0.984, SE: 0.318; p=0.002) and ED-LOS (coefficient: −3.021, SE: 0.256; p<0.001) were significantly shorter in the hospitalist group than in the non-hospitalist group.
Table 4Linear regression analysis for LOS and ED waiting time (N=6391)
| Variables | LOS | ED-LOS | ||||
| Coefficient | SE | P value | Coefficient | SE | P value | |
| (Constant) | 10.773 | 0.699 | <0.001 | 13.281 | 0.563 | <0.001 |
| HG (ref=NHG) | −0.984 | 0.318 | 0.002 | −3.021 | 0.256 | <0.001 |
| Female (ref=male) | −0.378 | 0.299 | 0.207 | −0.043 | 0.241 | 0.857 |
| Age | −0.049 | 0.011 | <0.001 | 0.006 | 0.009 | 0.535 |
| ACCI | 1.097 | 0.083 | <0.001 | 0.317 | 0.066 | <0.001 |
| KTAS* (ref=more urgent group) | −0.639 | 0.443 | 0.149 | −1.161 | 0.356 | 0.001 |
| Prior hospitalisation | 0.109 | 0.036 | 0.002 | 0.090 | 0.029 | 0.002 |
| Diseases (ref=malignant neoplasms) | ||||||
| Diseases of the circulatory system | −2.936 | 0.594 | <0.001 | −3.471 | 0.478 | <0.001 |
| Diseases of the respiratory system | 1.545 | 0.492 | 0.002 | −2.535 | 0.396 | <0.001 |
| Diseases of the digestive system | −2.570 | 0.520 | <0.001 | 0.090 | 0.419 | 0.830 |
| Diseases of the genitourinary system | −1.366 | 0.588 | 0.020 | −0.807 | 0.473 | 0.088 |
| Symptoms, signs, and abnormal clinical and laboratory findings | −2.688 | 0.730 | <0.001 | −1.865 | 0.588 | 0.002 |
| Certain infectious and parasitic diseases | 0.773 | 0.771 | 0.316 | −0.547 | 0.620 | 0.378 |
| Endocrine, nutritional and metabolic diseases | −1.821 | 0.802 | 0.023 | −1.201 | 0.646 | 0.063 |
| Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism | 0.096 | 0.939 | 0.919 | −1.931 | 0.756 | 0.011 |
| Diseases of the musculoskeletal system and connective tissue | 8.088 | 1.024 | <0.001 | 0.486 | 0.824 | 0.555 |
| Others | 2.888 | 0.780 | <0.001 | 0.403 | 0.628 | 0.522 |
| Adjusted R2=0.072, F=31.808 (p<0.001) | Adjusted R2=0.043, F=18.884 (p<0.001) | |||||
*The less urgent group with KTAS=4–5 was compared with the more urgent group with KTAS=1–3.
ACCI, Age-adjusted Charlson Comorbidity Index; ED, emergency department; ED-LOS, ED length of stay; HG, hospitalist group; KTAS, Korean Triage and Acuity Scale; LOS, length of hospital stay; NHG, non-hospitalist group; ref, reference group.
Discussion
Study summary
This study is the first to report the patient outcomes of a Korean AMU hospitalist model with additional adjustments for patient-related clinical factors. We found lower IHM and ICU admission rates and shorter LOS and ED-LOS with AMU hospitalist care compared with non-hospitalist care. The same trend was observed in the subgroup and regression analyses. However, there was no significant difference in the readmission rates between patients cared for by hospitalists and those cared for by non-hospitalists.
The strength of our AMU care is the direct, real-time communication among variously trained team members, which facilitates appropriate and rapid decision-making regarding treatments for patients with acute conditions.11 The AMU at our institution was different from typical emergency short-stay units operated by emergency physicians, mainly because the AMU follows the following essential principles: intensive care, active care, multidisciplinary teamwork, and rapid diagnostics and therapy.12
Impact on IHM
Previous studies that investigated the impact of AMU or hospitalist care have reported that IHM was reduced with hospitalist care.7 8 10 21–28 Contrary to those studies, another report found no significant difference in mortality between patients treated by a hospitalist and those treated by a non-hospitalist.29–34 Moreover, a recent Korean study found no difference in IHM between the hospitalist and non-hospitalist care groups in the integrated medical model.34 Although the previously published reports present contradictory results, our findings provide evidence that a hospitalist-run AMU is an effective model with the potential to extensively reduce IHM among patients with acute medical needs compared with those receiving non-hospitalist care. This study also demonstrated that the existing British acute medical model was effectively transformed into a Korean AMU model.
Impact on ICU admission rates
Few studies have reported ICU admission rates in AMU care. One study of a surgical co-management model, which mainly focused on patients who required surgery, found a marked reduction in the ICU admission rate in the hospitalist group35 compared with the non-hospitalist group. Other studies have reported no significant difference in the ICU admission rates between the two types of care.36–38 However, in our study, the ICU admission rate decreased remarkably with AMU hospitalist care. This finding implies that hospitalists in the AMU effectively treated patients with acute medical needs and greatly contributed to stabilising their conditions without requiring ICU admission. This result showed that the new, effective AMU hospitalist care in Korea could reduce ICU admission through efficient, high-quality treatment for patients who require acute medical care.
Impact on LOS
Most studies on acute medicine have reported that hospitalist care could reduce LOS compared with non-hospitalist care.7–10 21–23 30 31 33 34 39–47 In contrast, others have found that hospitalist care resulted in longer LOS or did not significantly affect LOS.32 48 49 Bearing in mind these paradoxical reports, at our institute, AMU hospitalist care reduced the total LOS compared with non-hospitalist care. Recently, another study reported that hospitalist care within the integrated medical model of Korea showed a reduction in LOS, particularly in patients with multiple comorbidities.34 They reported several reasons for a shorter LOS; one was that the hospitalists were better trained than residents, and consequently, they could manage diseases from more perspectives, which increased the likelihood of resolving the condition.34 This finding implies that Korean hospitalist care might extensively shorten LOS, regardless of the type of care model applied.
Impact on ED-LOS
Some studies showed that AMU hospitalist care considerably shortened the ED-LOS compared with non-hospitalist care.7–9 23 Consistent with previous studies, in our institution, AMU care also reduced the ED-LOS. This result might be explained by an increase in the bed turnover rate and alleviation of delays caused by waiting inpatients.
Impact on readmission rates
In our study, AMU hospitalist care was not associated with a significant difference in unscheduled readmissions. Previous studies showed that hospitalist care led to markedly lower readmission rates compared with non-hospitalist care.10 21 22 29 39 48 50 Others found no significant difference in the readmission rate.30 32–34 40–44 Those results suggested that the readmission rate might depend on the type of hospitalist care model applied, disease-related factors and the hospitalist’s roles. Shu et al reported that when a hospitalist provided post-discharge transitional care by telephone to discharged patients, the readmission rate was significantly reduced.50 Some studies have found that an AMU extensively reduces the readmission rate,51 but most studies on the effects of acute medicine found no effect of hospitalist care on the rate of unscheduled readmissions.42 43 At our institution, AMU hospitalist care was focused on the acute treatment of inpatients admitted through the ED; therefore, we did not expect a significant impact on the post-discharge readmission rate.
Limitations
Our study had some limitations. First, it followed a retrospective design, making it difficult to reduce confounding and to distinguish whether the effects on outcomes were due to the AMU setting or the care provided by the hospitalists. Furthermore, although patient allocation into the two groups was based on bed availability, the baseline characteristics between the study groups differed, which might have led to a selection bias. Second, it was a single-centre study, thereby restricting the generalisability of our findings. Third, we did not collect the DNR (Do-Not-Resuscitate) status for each patient in this study. Thus, we could not control it when evaluating IHM.
Finally, we did not perform an economic evaluation, including the medical costs. Future studies are necessary to determine whether the introduction of the AMU will improve patient outcomes in the long term, increase patient or staff satisfaction, and improve the cost-effectiveness of patient care.
Conclusion
To recapitulate, our study found lower IHM and ICU admission rates and shorter LOS and ED-LOS with AMU hospitalist care, indicating that adequate, rapid management by hospitalists in the early phase of an acute illness and their efficient operation of the AMU can contribute to improved patient outcomes.
We would like to thank Editage (www.editage.co.kr) for English language editing.
Data availability statement
Data are available upon reasonable request. Data are available from the corresponding author upon reasonable request.
Ethics statements
Patient consent for publication
Not required.
Ethics approval
Ethical approval was confirmed by the Institutional Review Board of Seoul National University Bundang Hospital (IRB no. B-1711/435-107). Our institution’s ethics committee waived the need for informed consent owing to the retrospective nature of the study and as it uses anonymised data that were previously collected for routine clinical care.
Contributors Conceptualisation—HJK, JK, JHO and N-HK. Methodology—HJK, JK, JHO and N-HK. Software—HJK. Validation—HJK, JK, JHO and N-HK. Formal analysis—HJK. Investigation—HJK, JK, JHO and N-HK. Data curation—HJK. Writing (original draft)—HJK. Writing (review and editing)—HJK, JK, JHO and N-HK. All authors have read and approved the final draft of the manuscript. JK is guarantor.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
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Abstract
Objective
To assess a newly introduced, hospitalist-run, acute medical unit (AMU) care model at a tertiary care hospital in the Republic of Korea.
Design
Retrospective cohort study.
Setting
Tertiary care hospital in the Republic of Korea.
Participants
We evaluated 6391 medical inpatients admitted through the emergency department (ED) from 1 June 2016 to 31 May 2017.
Interventions
The study compared multiple outcomes among medical inpatients from the ED between the non-hospitalist group and the AMU hospitalist group.
Outcome measures
In-hospital mortality (IHM), intensive care unit (ICU) admission rate, hospital length of stay (LOS), ED-LOS and unscheduled readmission rates were defined as patient outcomes and compared between the two groups.
Results
Compared with the non-hospitalist group, the AMU hospitalist group had lower IHM (OR: 0.43, p<0.001), a lower ICU admission rate (OR: 0.72, p=0.013), a shorter LOS (coefficient: −0.984, SE: 0.318; p=0.002) and a shorter ED-LOS (coefficient: −3.021, SE: 0.256; p<0.001). There were no significant differences in the 10-day or 30-day readmission rates (p=0.974, p=0.965, respectively).
Conclusions
The AMU hospitalist care model was associated with reductions in IHM, ICU admission rate, LOS and ED-LOS. These findings suggest that the AMU hospitalist care model has the potential to be adopted into other healthcare systems to improve care for patients with acute medical needs.
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Details
; Kim, Jinhyun 2 ; Ohn, Jung Hun 3 ; Kim, Nak-Hyun 3
1 College of Nursing, Seoul National University, Seoul, Korea (the Republic of); Department of Nursing, Seoul National University Bundang Hospital, Seongnam-si, Korea (the Republic of)
2 College of Nursing, Seoul National University, Seoul, Korea (the Republic of)
3 Internal Medicine, Seoul National University College of Medicine, Seoul, Korea (the Republic of); Hospital Medicine Center, Seoul National University Bundang Hospital, Seongnam-si, Korea (the Republic of)