Document Detail


The relationship between the C-statistic of a risk-adjustment model and the accuracy of hospital report cards: a Monte Carlo Study.
MedLine Citation:
PMID:  23295579     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards.
OBJECTIVES: To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards.
RESEARCH DESIGN: Monte Carlo simulations were used to examine this issue. We examined the influence of 3 factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada.
RESULTS: The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact.
CONCLUSIONS: The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card.
Authors:
Peter C Austin; Mathew J Reeves
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Medical care     Volume:  51     ISSN:  1537-1948     ISO Abbreviation:  Med Care     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-02-13     Completed Date:  2013-04-08     Revised Date:  2013-07-31    
Medline Journal Info:
Nlm Unique ID:  0230027     Medline TA:  Med Care     Country:  United States    
Other Details:
Languages:  eng     Pagination:  275-84     Citation Subset:  IM    
Affiliation:
Institute for Clinical Evaluative Sciences Institute of Health Management, Policy and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. peter.austin@ices.on.ca
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MeSH Terms
Descriptor/Qualifier:
Benchmarking*
Hospitals*
Humans
Logistic Models
Monte Carlo Method
Myocardial Infarction / mortality,  therapy
Ontario
Reproducibility of Results
Risk Adjustment / statistics & numerical data*
Grant Support
ID/Acronym/Agency:
MOP 86508//Canadian Institutes of Health Research
Comments/Corrections
Comment In:
Med Care. 2013 Jul;51(7):633   [PMID:  23685404 ]
Med Care. 2013 Jul;51(7):633-5   [PMID:  23685405 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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