Analysis of surgical errors in closed malpractice claims at 4 liability insurers

Surgery. 2006 Jul;140(1):25-33. doi: 10.1016/j.surg.2006.01.008.


Background: The relative importance of the different factors that cause surgical error is unknown. Malpractice claim file analysis may help to identify leading causes of surgical error and identify opportunities for prevention.

Methods: We retrospectively reviewed 444 closed malpractice claims, from 4 malpractice liability insurers, in which patients alleged a surgical error. Surgeon-reviewers examined the litigation file and medical record to determine whether an injury attributable to surgical error had occurred and, if so, what factors contributed. Detailed descriptive information concerning etiology and outcome was recorded.

Results: Reviewers identified surgical errors that resulted in patient injury in 258 of the 444 (58%) claims. Sixty-five percent of these cases involved significant or major injury; 23% involved death. In most cases (75%), errors occurred in intraoperative care; 25% in preoperative care; 35% in postoperative care. Thirty-one percent of the cases had errors occurring during multiple phases of care; in 62%, more than 1 clinician played a contributory role. Systems factors contributed to error in 82% of cases. The leading system factors were inexperience/lack of technical competence (41%) and communication breakdown (24%). Cases with technical errors (54%) were more likely than those without technical errors to involve errors in multiple phases of care (36% vs 24%, P = .03), multiple personnel (83% vs 63%, P < .001), lack of technical competence/knowledge (51% vs 29%, P < .001) and patient-related factors (54% vs 33%, P = .001).

Conclusions: Systems factors play a critical role in most surgical errors, including technical errors. Closed claims analysis can help to identify priority areas for intervening to reduce errors.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Female
  • Humans
  • Infant
  • Insurance Claim Review*
  • Insurance, Liability* / statistics & numerical data
  • Male
  • Malpractice* / statistics & numerical data
  • Medical Errors* / prevention & control
  • Medical Errors* / statistics & numerical data
  • Middle Aged
  • Retrospective Studies
  • Training Support
  • United States