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PMID: 19297447 Published · epublish English Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Evidence of methodological bias in hospital standardised mortality ratios: retrospective database study of English hospitals.

BMJ (Clinical research ed.) ·Vol. 338 ·2009-03-18 ·Pages b780

Mohammed MA, Deeks JJ, Girling A, Rudge G, Carmalt M, Stevens AJ, Lilford RJ

Abstract

To assess the validity of case mix adjustment methods used to derive standardised mortality ratios for hospitals, by examining the consistency of relations between risk factors and mortality across hospitals. Retrospective analysis of routinely collected hospital data comparing observed deaths with deaths predicted by the Dr Foster Unit case mix method. Four acute National Health Service hospitals in the West Midlands (England) with case mix adjusted standardised mortality ratios ranging from 88 to 140. 96 948 (April 2005 to March 2006), 126 695 (April 2006 to March 2007), and 62 639 (April to October 2007) admissions to the four hospitals. Presence of large interaction effects between case mix variable and hospital in a logistic regression model indicating non-constant risk relations, and plausible mechanisms that could give rise to these effects. Large significant (P<or=0.0001) interaction effects were seen with several case mix adjustment variables. For two of these variables-the Charlson (comorbidity) index and emergency admission-interaction effects could be explained credibly by differences in clinical coding and admission practices across hospitals. The Dr Foster Unit hospital standardised mortality ratio is derived from an internationally adopted/adapted method, which uses at least two variables (the Charlson comorbidity index and emergency admission) that are unsafe for case mix adjustment because their inclusion may actually increase the very bias that case mix adjustment is intended to reduce. Claims that variations in hospital standardised mortality ratios from Dr Foster Unit reflect differences in quality of care are less than credible.

MeSH Terms
Bias Emergencies/epidemiology England/epidemiology Hospital Mortality Length of Stay/statistics & numerical data Patient Admission/statistics & numerical data Regression Analysis Retrospective Studies Risk Adjustment/statistics & numerical data Risk Factors
Authors & Affiliations
7 authors, click to expand affiliations / ORCID
Mohammed Mohammed A
Unit of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham B15 2TT. [email protected]
Deeks Jonathan J
Girling Alan
Rudge Gavin
Carmalt Martin
Stevens Andrew J
Lilford Richard J
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Article Info
Journal
BMJ (Clinical research ed.)
Abbr.
BMJ
ISSN
1756-1833
Published
2009-03-18
Epub
2009-00-18
Pages
b780
Language
English
Region
England
NLM ID
8900488
PMCID
PMC2659855
Subset
IM
Grants
Medical Research Council · G0800808 · United Kingdom
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