, Volume 16, Issue 8, pp 519-524

Risk adjustment using administrative data

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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 (≥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.

Presented at the 22nd Annual Meeting of the Society of General Internal Medicine, San Francisco, Calif, April 29–May 1, 1999.
This project and WAG were supported by a Population Health Investigator Grant from the Alberta Heritage Foundation for Medical Research in Edmonton, Alberta. WAG is also supported by a Government of Canada Research Chair.