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Identifying Malpractice-Prone Physicians

29 Pages Posted: 18 Apr 2007  

John E. Rolph

University of Southern California - Marshall school of Business

John L. Adams

RAND Corporation

Kimberly McGuigan

affiliation not provided to SSRN


We analyze the claims database of a large malpractice insurer covering more than 8,000 physicians and 9,300 claims. Applying empirical Bayes methods in a regression setting, we construct a predictor of each physician's underlying propensity to incur malpractice claims. Our explanatory factors are physician demographics (age, sex, specialty, training) and physician practice pattern characteristics (practice setting, procedures performed, practice intensity, special risk factors, and characteristics of hospital(s) on staff of). We divide physicians into medical and surgical/ancillary specialty categories and fit separate models to each. In the surgical/ancillary specialty group, physician characteristics can effectively distinguish between more and less claims-prone physicians. Physician characteristics have somewhat less predictive power in the medical specialty group. As measured by predictive information, physician characteristics are superior to 10 years of claims history. Insofar as medical malpractice claims can be thought of as extreme indicators of poor-quality care, this finding suggests that easily gathered physician characteristics can be helpful in designing targeted quality of care improvement policies.

Keywords: physician risk factors, malpractice claims

Suggested Citation

Rolph, John E. and Adams, John L. and McGuigan, Kimberly, Identifying Malpractice-Prone Physicians. Journal of Empirical Legal Studies, Vol. 4, No. 1, pp. 125-153, March 2007. Available at SSRN:

John E. Rolph (Contact Author)

University of Southern California - Marshall school of Business ( email )

Marshall School of Business
BRI 401, 3670 Trousdale Parkway
Los Angeles, CA 90089
United States

John L. Adams

RAND Corporation ( email )

P.O. Box 2138
1776 Main Street
Santa Monica, CA 90407-2138
United States

Kimberly McGuigan

affiliation not provided to SSRN

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