Literature DB >> 1920697

Malpractice claims data as a quality improvement tool. II. Is targeting effective?

J E Rolph1, R L Kravitz, K McGuigan.   

Abstract

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.
DESIGN: --Retrospective review of physician malpractice claim records.
SETTING: --Large New Jersey physician malpractice insurer. PARTICIPANTS: --Physicians practicing obstetrics and gynecology, general surgery, anesthesiology, or radiology and covered by the insurance carrier for any portion of 1977 through 1989. MAIN OUTCOME MEASURES: --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.
CONCLUSION: --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.

Entities:  

Mesh:

Year:  1991        PMID: 1920697

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  10 in total

1.  Measuring errors and adverse events in health care.

Authors:  Eric J Thomas; Laura A Petersen
Journal:  J Gen Intern Med       Date:  2003-01       Impact factor: 5.128

2.  Predicting risk for medical malpractice claims using quality-of-care characteristics.

Authors:  S C Charles; R D Gibbons; P R Frisch; C E Pyskoty; D Hedeker; N K Singha
Journal:  West J Med       Date:  1992-10

3.  Role of previous claims and specialty on the effectiveness of risk-management education for office-based physicians.

Authors:  P R Frisch; S C Charles; R D Gibbons; D Hedeker
Journal:  West J Med       Date:  1995-10

4.  A brief history of health care quality assessment and improvement in the United States.

Authors:  J M Luce; A B Bindman; P R Lee
Journal:  West J Med       Date:  1994-03

5.  Physician malpractice: does the past predict the future?

Authors:  M I Taragin; K Martin; S Shapiro; R Trout; J L Carson
Journal:  J Gen Intern Med       Date:  1995-10       Impact factor: 5.128

6.  What can patients do to improve health care?

Authors:  Michel Wensing; Richard Grol
Journal:  Health Expect       Date:  1998-06       Impact factor: 3.377

7.  The PRONE score: an algorithm for predicting doctors' risks of formal patient complaints using routinely collected administrative data.

Authors:  Matthew J Spittal; Marie M Bismark; David M Studdert
Journal:  BMJ Qual Saf       Date:  2015-04-08       Impact factor: 7.035

8.  Identification of practitioners at high risk of complaints to health profession regulators.

Authors:  Matthew J Spittal; Marie M Bismark; David M Studdert
Journal:  BMC Health Serv Res       Date:  2019-06-13       Impact factor: 2.655

9.  Learning From Lawsuits: Using Malpractice Claims Data to Develop Care Transitions Planning Tools.

Authors:  Alicia I Arbaje; Nicole E Werner; Eileen M Kasda; Albert W Wu; Charles F S Locke; Hanan Aboumatar; Lori A Paine; Bruce Leff; Richard O Davis; Romsai Boonyasai
Journal:  J Patient Saf       Date:  2020-03       Impact factor: 2.243

10.  Identification of doctors at risk of recurrent complaints: a national study of healthcare complaints in Australia.

Authors:  Marie M Bismark; Matthew J Spittal; Lyle C Gurrin; Michael Ward; David M Studdert
Journal:  BMJ Qual Saf       Date:  2013-04-10       Impact factor: 7.035

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.