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MAXIMIZING EFFICIENCY IN RISK ADJUSTMENT UNDER CONDITIONS OF UNCERTAINTY AND RESOURCE CONSTRAINTS

Terris, Darcey Dickinson
http://rave.ohiolink.edu/etdc/view?acc_num=case1174432210

Abstract Details

2007, Doctor of Philosophy, Case Western Reserve University, Epidemiology and Biostatistics.
In this dissertation, the issues surrounding limitations in data quality and resources are explored within the field of health services research and the use of risk adjustment for evaluation of health care quality. The first chapter describes a model of the multiple sources of bias in health state information. The focus is on sources of bias that arise from health systems and influence the validity of data stored in secondary databases. The conclusion drawn is that perfect accuracy in health state information is an unobtainable goal. The second chapter describes the development of the cost-conscious approach and comparison of the new method with the two traditional methods of risk adjustment. The traditional methods are inclusive risk adjustment, using fully specified models, and exclusive risk adjustment, where statistically insignificant factors are eliminated. A simulated dataset was created to know, with certainty, the quality status of a cohort of hypothetical hospitals. Random and systematic error was then introduced into the dataset and the three risk adjustment methods were used to identify the hospitals’ quality ranking. The performance of the methods was assessed by a new metric, “managerial efficiency”, defined as the ratio of a model’s ability to correctly identify quality status, divided by the costs associated with the data required. Based on this measure, the cost-conscious modeling approach was shown to out-perform the inclusive and exclusive approaches. Specifically, the cost-conscious method was found to have an equivalent ability to correctly identify hospitals’ relative quality status, but did so at a cost savings of up to 60%, regardless of data quality. The final chapter reviews risk adjustment methodology published in two journals of health services research. The review is linked to a discussion of the statistical properties and managerial efficiency of the two prevalent approaches to risk adjustment and the proposed cost-conscious approach. The potential impact of a cost-conscious strategy to risk adjustment is demonstrated by the fact that 20% of the published reports utilized over 200 risk adjustment factors and when additional risk adjustment factors were added to previously developed models, only small improvements in prediction or discrimination were typically observed.
Duncan Neuhauser (Advisor)
316 p.
Risk Adjustment; Quality of Health Care; Health Services Research; Secondary Database Analysis; Cost / Benefit Analysis

Recommended Citations

Citations

  • Terris, D. D. (2007). MAXIMIZING EFFICIENCY IN RISK ADJUSTMENT UNDER CONDITIONS OF UNCERTAINTY AND RESOURCE CONSTRAINTS [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1174432210

    APA Style (7th edition)

  • Terris, Darcey. MAXIMIZING EFFICIENCY IN RISK ADJUSTMENT UNDER CONDITIONS OF UNCERTAINTY AND RESOURCE CONSTRAINTS. 2007. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1174432210.

    MLA Style (8th edition)

  • Terris, Darcey. "MAXIMIZING EFFICIENCY IN RISK ADJUSTMENT UNDER CONDITIONS OF UNCERTAINTY AND RESOURCE CONSTRAINTS." Doctoral dissertation, Case Western Reserve University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=case1174432210

    Chicago Manual of Style (17th edition)

case1174432210
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© 2007, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.