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    The importance of severity of illness adjustment in predicting adverse outcomes in the Medicare population

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    Authors
    Rosen, Amy K.
    Ash, Arlene S.
    McNiff, Kathleen J.
    Moskowitz, Mark A.
    UMass Chan Affiliations
    Department of Quantitative Health Sciences
    Document Type
    Journal Article
    Publication Date
    1995-05-01
    Keywords
    Aged
    Aged, 80 and over
    Angioplasty, Transluminal, Percutaneous Coronary
    Cholecystectomy
    Coronary Artery Bypass
    Data Interpretation, Statistical
    Demography
    Female
    Humans
    Male
    Models, Statistical
    Postoperative Complications
    Predictive Value of Tests
    Prostatectomy
    Quality of Health Care
    Risk Factors
    *Severity of Illness Index
    Surgical Procedures, Operative
    Biostatistics
    Epidemiology
    Health Services Research
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    Link to Full Text
    http://dx.doi.org/10.1016/0895-4356(94)00165-M
    Abstract
    The importance of using risk-adjusted mortality rates to measure quality of care is well-established. However, mortality rates may be an insensitive measure of quality for surgical patients since death is a relatively rare outcome. This study used Medicare files to identify, through chart abstraction, clinical postoperative complications of four surgical procedures (n = 8126) that could serve as measures of quality. Disease-specific severity of illness models using a moderate number of clinical variables and admission MedisGroups score models computed from approximately 250 clinical variables were compared in predicting postoperative adverse events. Initial differences between the two models disappeared upon cross-validation. Validated R-squareds and C statistics from models using half the data were generally positive, suggesting that these models had real, although modest, predictive power. We have shown that severity of illness on admission plays a role in predicting adverse events of surgery. Risk-adjusted outcomes may potentially be useful in screening for quality shortfalls.
    Source
    J Clin Epidemiol. 1995 May;48(5):631-43. Link to article on publisher's site
    DOI
    10.1016/0895-4356(94)00165-M
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/47501
    PubMed ID
    7730920
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1016/0895-4356(94)00165-M
    Scopus Count
    Collections
    Population and Quantitative Health Sciences Publications

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