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Research

Characteristics of short general internal medicine hospital stays: a multicentre cross-sectional study

Amol A. Verma, Yishan Guo, Janice L. Kwan, Lauren Lapointe-Shaw, Shail Rawal, Terence Tang, Adina Weinerman and Fahad Razak
January 28, 2019 7 (1) E47-E54; DOI: https://doi.org/10.9778/cmajo.20180181
Amol A. Verma
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Yishan Guo
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Janice L. Kwan
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Lauren Lapointe-Shaw
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Shail Rawal
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Terence Tang
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Adina Weinerman
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Fahad Razak
Li Ka Shing Knowledge Institute (Verma, Guo, Razak), St. Michael’s Hospital; Department of Medicine (Verma, Kwan, Lapointe-Shaw, Rawal, Tang, Weinerman, Razak) and Institute of Health Policy, Management and Evaluation (Razak), University of Toronto; Department of Medicine (Kwan), Mount Sinai Hospital; Division of General Internal Medicine (Rawal), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Sunnybrook Health Sciences Centre (Weinerman), Toronto, Ont.; Harvard Center for Population and Development Studies (Razak), Cambridge, Mass.
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Article Figures & Tables

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    Table 1:

    Patient characteristics associated with duration of stay after admission to general internal medicine

    CharacteristicDuration of stay; no. (%) of patients*p value‡
    < 24 h
    n = 4245
    24–72 h
    n = 13 442
    > 72 h†
    n = 38 368
    Age, yr, median (IQR)63 (45–78)67 (50–81)74 (59–84)< 0.001
    Female sex2155 (50.8)6722 (50.0)19 026 (49.6)0.3
    Charlson Comorbidity Index score< 0.001
     01846 (43.5)4666 (34.7)8809 (23.0)
     1962 (22.7)3061 (22.8)7737 (20.2)
     2557 (13.1)2210 (16.4)6785 (17.7)
     ≥ 3880 (20.7)3505 (26.1)15 037 (39.2)
    Transported via ambulance1531 (36.1)5700 (42.4)21 533 (56.1)< 0.001
    Admitted to general internal medicine at a study site in prior 30 d*372 (8.8)1283 (9.5)5315 (13.8)< 0.001
    Laboratory-based Acute Physiology Score, mean ± SD13.0 ± 12.416.3 ± 13.921.4 ± 17.1< 0.001
    Admitted on weekend929 (21.9)3516 (26.2)10 152 (26.4)< 0.001
    Time of admission< 0.001
     Day (0800–1659:59)398 (9.4)2832 (21.1)8398 (21.9)
     Evening (1700–2400)1795 (42.3)5156 (38.4)14 828 (38.6)
     Night (0000:01–0759:59)2052 (48.3)5454 (40.6)15 142 (39.5)
    • Note: IQR = interquartile range, SD = standard deviation.

    • ↵* Except where noted otherwise.

    • ↵† Patients who left hospital against medical advice, died or were transferred to another acute inpatient, rehabilitation or palliative care facility were categorized as having a stay of more than 72 hours.

    • ↵‡ χ2 analysis for categorical variables, Kruskall–Wallis test for continuous variables.

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    Table 2:

    Univariate and multivariable regression models of patient, physician and situational characteristics associated with a short stay after admission to general internal medicine

    CharacteristicModel A: < 24 hModel B: ≤ 72 h
    Univariate OR* (95% CI)Multivariable adjusted OR* (95% CI)Univariate OR* (95% CI)Multivariable adjusted OR* (95% CI)
    Patients
    Age0.98 (0.98–0.98)0.99 (0.99–0.99)0.98 (0.98–0.98)0.99 (0.99–0.99)
    Female sex1.06 (0.98–1.14)0.96 (0.90–1.02)1.05 (1.01–1.10)0.97 (0.94–1.01)
    Charlson Comorbidity Index score
     03.10 (2.79–3.44)1.97 (1.79–2.16)2.77 (2.62–2.94)1.75 (1.66–1.84)
     11.98 (1.76–2.22)1.63 (1.47–1.79)1.91 (1.79–2.03)1.54 (1.46–1.62)
     21.33 (1.16–1.52)1.20 (1.08–1.34)1.46 (1.36–1.56)1.29 (1.21–1.36)
    Not transported via ambulance2.03 (1.88–2.20)1.44 (1.34–1.54)1.92 (1.84–2.00)1.47 (1.41–1.53)
    Admitted to general internal medicine at a study site in prior 30 d*0.54 (0.44–0.65)0.84 (0.75–0.94)0.53 (0.48–0.59)0.77 (0.73–0.82)
    Laboratory-based Acute Physiology Score0.96 (0.96–0.97)0.97 (0.97–0.98)0.97 (0.97–0.97)0.98 (0.98–0.98)
    Physicians
    Female sex0.83 (0.77–0.91)0.80 (0.74–0.86)0.84 (0.80–0.88)0.82 (0.79–0.86)
    Years since graduation1.00 (1.00–1.01)1.00 (1.00–1.00)1.00 (1.00–1.00)1.00 (1.00–1.00)
    Situational
    Admitted weekday1.34 (1.23–1.47)1.26 (1.17–1.36)1.09 (1.03–1.14)1.05 (1.01–1.10)
    Admitted evening2.53 (2.22–2.88)2.61 (2.33–2.92)1.20 (1.13–1.28)1.24 (1.17–1.30)
    Admitted night2.93 (2.57–3.33)2.73 (2.44–3.06)1.31 (1.23–1.39)1.29 (1.22–1.37)
    Admissions to general internal medicine in prior 12 h1.05 (1.04–1.06)1.01 (1.00–1.02)1.02 (1.02–1.03)1.00 (1.00–1.01)
    Admitted to short-stay unit2.26 (2.03–2.52)1.56 (1.39–1.75)3.06 (2.83–3.31)2.35 (2.17–2.54)
    Fiscal year of admission1.09 (1.04–1.14)1.09 (1.05–1.14)1.05 (1.03–1.08)1.05 (1.03–1.08)
    • Note: CI = confidence interval, OR = odds ratio.

    • ↵* Derived from logistic regression models with the use of generalized estimating equations to account for clustering of admissions within physicians. The multivariable model included all covariates listed in the table. For variables with more than 2 categories, the reference categories were Charlson Comorbidity Index score 3 (high comorbidity) and admission in the day (v. evening and night).

    • View popup
    Table 3:

    Discharge diagnoses that were more common among short and long hospital stays

    DiagnosisDuration of stay; no. (%) of admissions*Absolute difference
    < 24 h> 72 h
    More common among short stays
    Nonspecific chest pain167 (3.9)194 (0.5)3.4
    Syncope124 (2.9)399 (1.0)1.9
    Essential hypertension90 (2.1)158 (0.4)1.7
    Intestinal infection163 (3.8)822 (2.1)1.7
    Dizziness or vertigo92 (2.2)201 (0.5)1.6
    More common among long stays
    Congestive heart failure101 (2.4)2251 (5.9)3.5
    Sepsis7 (0.2)1016 (2.6)2.5
    Delirium, dementia, cognitive disorder62 (0.2)1444 (3.8)2.3
    Stroke27 (0.6)996 (2.6)2.0
    Urinary tract infection123 (2.9)1823 (4.8)1.9
    • ↵* Calculated among patients discharged alive in less than 24 hours and among those who died in hospital or whose hospital stay exceeded 72 hours. Diagnoses were ranked by the difference in prevalence between short and long stays, and the diagnoses with largest absolute differences between short and long stays are reported.

    • View popup
    Table 4:

    Resource use among patients admitted to general internal medicine by duration of stay

    ResourceDuration of stay; no. (%) of admissions*
    < 24 h24–72 h> 72 h
    Length of time in emergency department, h, mean ± SD14.8 ± 6.615.7 ± 9.016.4 ± 9.9
    Intravenously administered medication†2788 (65.7)10 722 (79.8)33 022 (86.1)
    Radiography†2803 (66.0)10 013 (74.5)33 260 (86.7)
    Computed tomography†1561 (36.8)5254 (39.1)21 772 (56.7)
    Ultrasonography†418 (9.8)2363 (17.6)12 110 (31.6)
    Magnetic resonance imaging†144 (3.4)842 (6.3)4983 (13.0)
    Red blood cell transfusion†86 (2.0)593 (4.4)4522 (11.8)
    Endoscopy†92 (2.2)1053 (7.8)4037 (10.5)
    Bronchoscopy†1 (0.0)39 (0.3)965 (2.5)
    Intensive care unit admission18 (0.4)101 (0.8)2509 (6.5)
    No advanced interventions‡779 (18.4)1146 (8.5)1347 (3.5)
    • Note: SD = standard deviation.

    • ↵* Except where noted otherwise.

    • ↵† Number of admissions in which at least 1 of this test or treatment was used.

    • ↵‡ Number of admissions in which none of the following tests or treatments were used: intravenous medication, computed tomography, ultrasonography, magnetic resonance imaging, endoscopy, bronchoscopy or intensive care unit admission.

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Characteristics of short general internal medicine hospital stays: a multicentre cross-sectional study
Amol A. Verma, Yishan Guo, Janice L. Kwan, Lauren Lapointe-Shaw, Shail Rawal, Terence Tang, Adina Weinerman, Fahad Razak
Jan 2019, 7 (1) E47-E54; DOI: 10.9778/cmajo.20180181

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Characteristics of short general internal medicine hospital stays: a multicentre cross-sectional study
Amol A. Verma, Yishan Guo, Janice L. Kwan, Lauren Lapointe-Shaw, Shail Rawal, Terence Tang, Adina Weinerman, Fahad Razak
Jan 2019, 7 (1) E47-E54; DOI: 10.9778/cmajo.20180181
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