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Evaluation of Hospital Outcomes: the Relation Between Length-of-stay, Readmission, and Mortality in a Large International Administrative Database

Overview
Publisher Biomed Central
Specialty Health Services
Date 2018 Feb 16
PMID 29444713
Citations 77
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Abstract

Background: Hospital mortality, readmission and length of stay (LOS) are commonly used measures for quality of care. We aimed to disentangle the correlations between these interrelated measures and propose a new way of combining them to evaluate the quality of hospital care.

Methods: We analyzed administrative data from the Global Comparators Project from 26 hospitals on patients discharged between 2007 and 2012. We correlated standardized and risk-adjusted hospital outcomes on mortality, readmission and long LOS. We constructed a composite measure with 5 levels, based on literature review and expert advice, from survival without readmission and normal LOS (best) to mortality (worst outcome). This composite measure was analyzed using ordinal regression, to obtain a standardized outcome measure to compare hospitals.

Results: Overall, we observed a 3.1% mortality rate, 7.8% readmission rate (in survivors) and 20.8% long LOS rate among 4,327,105 admissions. Mortality and LOS were correlated at the patient and the hospital level. A patient in the upper quartile LOS had higher odds of mortality (odds ratio = 1.45, 95% confidence interval 1.43-1.47) than those in the lowest quartile. Hospitals with a high standardized mortality had higher proportions of long LOS (r = 0.79, p < 0.01). Readmission rates did not correlate with either mortality or long LOS rates. The interquartile range of the standardized ordinal composite outcome was 74-117. The composite outcome had similar or better reliability in ranking hospitals than individual outcomes.

Conclusions: Correlations between different outcome measures are complex and differ between hospital- and patient-level. The proposed composite measure combines three outcomes in an ordinal fashion for a more comprehensive and reliable view of hospital performance than its component indicators.

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References
1.
Jen M, Bottle A, Kirkwood G, Johnston R, Aylin P . The performance of automated case-mix adjustment regression model building methods in a health outcome prediction setting. Health Care Manag Sci. 2011; 14(3):267-78. DOI: 10.1007/s10729-011-9159-6. View

2.
Reynolds K, Butler M, Kimes T, Rosales A, Chan W, Nichols G . Relation of Acute Heart Failure Hospital Length of Stay to Subsequent Readmission and All-Cause Mortality. Am J Cardiol. 2015; 116(3):400-5. DOI: 10.1016/j.amjcard.2015.04.052. View

3.
Bottle A, Middleton S, Kalkman C, Livingston E, Aylin P . Global comparators project: international comparison of hospital outcomes using administrative data. Health Serv Res. 2013; 48(6 Pt 1):2081-100. PMC: 3876394. DOI: 10.1111/1475-6773.12074. View

4.
Fischer C, Steyerberg E, Fonarow G, Ganiats T, Lingsma H . A systematic review and meta-analysis on the association between quality of hospital care and readmission rates in patients with heart failure. Am Heart J. 2015; 170(5):1005-1017.e2. DOI: 10.1016/j.ahj.2015.06.026. View

5.
Kolfschoten N, Kievit J, Gooiker G, van Leersum N, Snijders H, Eddes E . Focusing on desired outcomes of care after colon cancer resections; hospital variations in 'textbook outcome'. Eur J Surg Oncol. 2012; 39(2):156-63. DOI: 10.1016/j.ejso.2012.10.007. View