Home LiteratureArticle Details
PMID: 10413396 Published · ppublish English Journal Article

Accuracy of risk-adjusted mortality rate as a measure of hospital quality of care.

Medical care ·Vol. 37 ·No. 1 ·1999-01-00 ·Pages 83-92

Thomas JW, Hofer TP

Abstract

Reports on hospital quality performance are being produced with increasing frequency by state agencies, commercial data vendors, and health care purchasers. Risk-adjusted mortality rate is the most commonly used measure of quality in these reports. The purpose of this study was to determine whether risk-adjusted mortality rates are valid indicators of hospital quality performance. Based on an analytical model of random measurement error, sensitivity and predictive error of mortality rate indicators of hospital performance were estimated. The following six parameters were shown to determine accuracy: (1) mortality risks of patients who receive good quality care and (2) of those who receive poor quality care, (3) proportion of patients (across all hospitals) who receive poor quality care, (4) proportion of hospitals considered to be "poor quality," (5) patients' relative risk of receiving poor quality care in "good quality" and in "poor quality" hospitals, and (6) number of patients treated per hospital. Using best available values for model parameters, analyses demonstrated that in nearly all situations, even with perfect risk adjustment, identifying poor quality hospitals on the basis of mortality rate performance is highly inaccurate. Of hospitals that delivered poor quality care, fewer than 12% were identified as high mortality rate outliers, and more than 60% of outliers were actually good quality hospitals. Under virtually all realistic assumptions for model parameter values, sensitivity was less than 20% and predictive error was greater than 50%. Reports that measure quality using risk-adjusted mortality rates misinform the public about hospital performance.

MeSH Terms
Bias Confounding Factors, Epidemiologic Health Services Research/methods Hospital Mortality Humans Models, Statistical Quality Indicators, Health Care Reproducibility of Results Risk Adjustment Risk Assessment Sensitivity and Specificity United States
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Thomas J W
Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor 48109, USA. [email protected]
Hofer T P
Article Info
Journal
Medical care
Abbr.
Med Care
ISSN
0025-7079
Published
1999-01-00
Pages
83-92
Language
English
Region
United States
NLM ID
0230027
Subset
IM
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: [email protected]