Malpractice claims data as a quality improvement tool. II. Is targeting effective?
OBJECTIVE
--To evaluate the usefulness of malpractice claims data for identifying (1) physicians who are prone to negligent errors and (2) physician and hospital characteristics associated with particular kinds of errors.


METHODS
--Retrospective review of physician malpractice claim records.


METHODS
--Large New Jersey physician malpractice insurer.


METHODS
--Physicians practicing obstetrics and gynecology, general surgery, anesthesiology, or radiology and covered by the insurance carrier for any portion of 1977 through 1989.


METHODS
--Claims were classified into 11 clinical error categories comprising three broad groups: patient management problems, technical performance problems, and staff coordination problems. Outcomes were expressed as per-physician frequency of claims due to negligence and proportion of claims associated with various types of errors.


RESULTS
--Using 5 years of claims history to predict long-term claims proneness was more accurate than chance alone by 57% in obstetrics and gynecology, 33% in general surgery, 11% in anesthesiology, and 15% in radiology. Cross-validated recursive partitioning showed that among physician characteristics, only specialty was predictive of physician error profiles. For physician claims arising in acute care hospitals, hospital size and location in addition to hospital services discriminated among different error profiles; the cross-validated accuracy of this method was 69% compared with 22% accuracy achieved by random prediction.


CONCLUSIONS
--Use of physicians' malpractice claims histories to target individuals for education or sanctions is problematic because of the only modest predictive power of such claims histories.
RAND Corporation, Santa Monica, CA 90406-2138.
J E
JE
Rolph
R L
RL
Kravitz
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K
McGuigan
D000776:Anesthesiology / Q000706:statistics & numerical data; D006761:Hospitals / Q000145:classification* / Q000706:statistics & numerical data; D007351:Insurance, Liability / Q000706:statistics & numerical data*; D008318:Malpractice / Q000706:statistics & numerical data*; D008511:Medicine / Q000592:standards / Q000706:statistics & numerical data*; D009515:New Jersey; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010818:Practice Patterns, Physicians' / Q000592:standards*; D011871:Radiology / Q000706:statistics & numerical data; D012189:Retrospective Studies; D013038:Specialization; D013043:Specialties, Surgical / Q000592:standards / Q000706:statistics & numerical data