Literature DB >> 11556927

Risk adjustment using administrative data: impact of a diagnosis-type indicator.

W A Ghali1, H Quan, R Brant.   

Abstract

OBJECTIVES: To determine the frequency with which commonly coded clinical variables are complications, as opposed to baseline comorbidities, and to compare the results of 2 risk-adjusted outcome analyses for coronary artery bypass graft surgery for which we either (a) ignored, or (b) used the available "diagnosis-type indicator."
DESIGN: Analysis of existing administrative data.
SETTING: Twenty-three Canadian hospitals. PATIENTS: A total of 50,357 coronary artery bypass graft surgery cases.
MEASUREMENTS AND MAIN RESULTS: Among 21 clinical variables whose definitions involve the diagnosis-type indicator, 14 were predominantly (> or =97%) baseline risk factors when present. Seven variables were often complication diagnoses: renal disease (when present, 13% coded as complications), recent myocardial infarction (15%), peptic ulcer disease (15%), congestive heart failure (17%), cerebrovascular disease (26%), hemiplegia (34%), and severe liver disease (35%). The results of risk adjustment analyses predicting in-hospital mortality differed when the diagnosis-type indicator was either used or ignored, and as a result, adjusted hospital mortality rates and rankings changed, often dramatically, with rankings increasing for 10 hospitals, decreasing for 9 hospitals, and remaining the same for only 4 hospitals.
CONCLUSIONS: The results of analyses performed using the diagnosis-type indicator in Canadian administrative data differ considerably from analyses that ignore the indicator. The widespread introduction of such an indicator should be considered in other countries, because risk-adjustment analyses performed without a diagnosis-type indicator may yield misleading results.

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Mesh:

Year:  2001        PMID: 11556927      PMCID: PMC1495253          DOI: 10.1046/j.1525-1497.2001.016008519.x

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


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