Do variations in hospital admission rates bias comparisons of standardized hospital mortality rates? A population-based cohort study.


Journal

Social science & medicine (1982)
ISSN: 1873-5347
Titre abrégé: Soc Sci Med
Pays: England
ID NLM: 8303205

Informations de publication

Date de publication:
08 2019
Historique:
received: 31 10 2018
revised: 25 06 2019
accepted: 08 07 2019
pubmed: 20 7 2019
medline: 25 8 2020
entrez: 20 7 2019
Statut: ppublish

Résumé

Standardized mortality rates are routinely used as measures of hospital performance and quality. Such metrics may, however, be biased if hospital admission thresholds differ and patient severity is not fully measured. To examine whether comparisons of hospital mortality rates suffer from selection bias due to variations in hospital admission rates, using the example of variations by day of the week. 12,900,687 emergency department attendances and 3,418,446 unplanned admissions to all acute non-specialist hospitals of the National Health Service in England between 1 April 2013 and 28 February 2014. Population-based retrospective cohort study. Mortality within 30 days of attendance is modelled as a function of weekend or weekday attendance and hospital-level predictors of admission rates using patient-level risk-adjusted probit and bivariate Heckman selection models. Robustness is supported by the use of different hospital-level predictors. When examining only the admitted population, patients admitted to hospital at weekends have a 0.206 percentage point higher risk of death within 30 days compared to patients admitted during the week. However, patients attending emergency departments at weekends have a 1.390 percentage point lower probability of being admitted to hospital. Once this selection bias is accounted for, the weekend effect in mortality is reduced by two-thirds to a 0.068 percentage point increase in the risk of death. Comparisons of standardized hospital mortality rates following unplanned admissions can be biased by variations in emergency department admission rates, leading to incorrect conclusions about quality. The use of mortality as a performance measure could therefore lead to misleading comparisons if admission rates vary and illness severity is not fully controlled for. Accounting for sample selection bias and dependence between admission and mortality rates is vital if accurate comparisons of hospital performance are to be made.

Sections du résumé

BACKGROUND
Standardized mortality rates are routinely used as measures of hospital performance and quality. Such metrics may, however, be biased if hospital admission thresholds differ and patient severity is not fully measured.
AIM
To examine whether comparisons of hospital mortality rates suffer from selection bias due to variations in hospital admission rates, using the example of variations by day of the week.
DATA
12,900,687 emergency department attendances and 3,418,446 unplanned admissions to all acute non-specialist hospitals of the National Health Service in England between 1 April 2013 and 28 February 2014.
METHODS
Population-based retrospective cohort study. Mortality within 30 days of attendance is modelled as a function of weekend or weekday attendance and hospital-level predictors of admission rates using patient-level risk-adjusted probit and bivariate Heckman selection models. Robustness is supported by the use of different hospital-level predictors.
RESULTS
When examining only the admitted population, patients admitted to hospital at weekends have a 0.206 percentage point higher risk of death within 30 days compared to patients admitted during the week. However, patients attending emergency departments at weekends have a 1.390 percentage point lower probability of being admitted to hospital. Once this selection bias is accounted for, the weekend effect in mortality is reduced by two-thirds to a 0.068 percentage point increase in the risk of death.
CONCLUSIONS
Comparisons of standardized hospital mortality rates following unplanned admissions can be biased by variations in emergency department admission rates, leading to incorrect conclusions about quality. The use of mortality as a performance measure could therefore lead to misleading comparisons if admission rates vary and illness severity is not fully controlled for. Accounting for sample selection bias and dependence between admission and mortality rates is vital if accurate comparisons of hospital performance are to be made.

Identifiants

pubmed: 31323539
pii: S0277-9536(19)30395-8
doi: 10.1016/j.socscimed.2019.112409
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

112409

Subventions

Organisme : Department of Health
ID : 12/128/48
Pays : United Kingdom

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

Rachel Meacock (R)

Health Organisation, Policy and Economics (HOPE), Centre for Primary Care, The University of Manchester, UK. Electronic address: rachel.meacock@manchester.ac.uk.

Laura Anselmi (L)

Health Organisation, Policy and Economics (HOPE), Centre for Primary Care, The University of Manchester, UK.

Søren Rud Kristensen (SR)

Centre for Health Policy Institute of Global Health Innovation, Imperial College London, UK.

Tim Doran (T)

Department of Health Sciences, University of York, UK.

Matt Sutton (M)

Health Organisation, Policy and Economics (HOPE), Centre for Primary Care, The University of Manchester, UK; Melbourne Institute of Applied Economic and Social Research, Faculty of Business and Economics, The University of Melbourne, Australia.

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