Literature DB >> 8876505

Judging hospitals by severity-adjusted mortality rates: the influence of the severity-adjustment method.

L I Iezzoni1, A S Ash, M Shwartz, J Daley, J S Hughes, Y D Mackiernan.   

Abstract

OBJECTIVES: This research examined whether judgments about a hospital's risk-adjusted mortality performance are affected by the severity-adjustment method.
METHODS: Data came from 100 acute care hospitals nationwide and 11880 adults admitted in 1991 for acute myocardial infarction. Ten severity measures were used in separate multivariable logistic models predicting in-hospital death. Observed-to-expected death rates and z scores were calculated with each severity measure for each hospital.
RESULTS: Unadjusted mortality rates for the 100 hospitals ranged from 4.8% to 26.4%. For 32 hospitals, observed mortality rates differed significantly from expected rates for 1 or more, but not for all 10, severity measures. Agreement between pairs of severity measures on whether hospitals were flagged as statistical mortality outliers ranged from fair to good. Severity measures based on medical records frequently disagreed with measures based on discharge abstracts.
CONCLUSIONS: Although the 10 severity measures agreed about relative hospital performance more often than would be expected by chance, assessments of individual hospital mortality rates varied by different severity-adjustment methods.

Entities:  

Mesh:

Year:  1996        PMID: 8876505      PMCID: PMC1380647          DOI: 10.2105/ajph.86.10.1379

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  45 in total

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2.  Biased estimates of expected acute myocardial infarction mortality using MedisGroups admission severity groups.

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10.  The relationship between adjusted hospital mortality and the results of peer review.

Authors:  A J Hartz; M S Gottlieb; E M Kuhn; A A Rimm
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10.  Measuring quality for public reporting of health provider quality: making it meaningful to patients.

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Journal:  Am J Public Health       Date:  2009-12-17       Impact factor: 9.308

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