Malpractice risk at the physician level: Claim-prone physicians

J Forensic Leg Med. 2018 Aug:58:152-154. doi: 10.1016/j.jflm.2018.06.004. Epub 2018 Jun 27.

Abstract

Professional liability and patient safety are worldwide concerns and efforts to identify claimed physicians' characteristics cross borders. Interventions with "at risk populations" would help to better address the underlying problems that lead to many claims. We analyzed physicians' characteristics of every paid claim between 2005 and 2014 in Catalonia region (Spain). We identified 808 physicians involved in 725 paid claims. A total of 12.38% physicians had at least two paid claims over the study period. Physicians' risk of future paid claims was increased if they had more than one previous paid claim (hazard ratio, 1.87; 95% confidence interval [CI], 1.67-2,1). More than half the claims were accounted for by physicians in four specialty groups: obstetrics and gynecology (20.4%), traumatology and orthopedic Surgery (17.5%), plastic surgery (10%) and general surgery (9.7%). The risk of recurrence was higher among surgery-related specialties than among non-surgery-related specialties. Specialty is a particularly strong determinant of claim incidence, so the risk issue may not be so individually determined, but conditioned by the kind of medicine or procedures we practice. Nevertheless, physicians' risk of future paid-claims increases after the second claim. Management systems should take advantage of this information, in order to prevent patient safety events and malpractice claims. Our results support both specialty-based interventions in high-risk specialties, such us Plastic Surgery, as well as interventions at a physician level in those physicians with more than one paid claim.

Keywords: Claims; Malpractice; Medical errors; Patient safety; Professional liability; Quality improvement.

MeSH terms

  • Humans
  • Liability, Legal
  • Malpractice / statistics & numerical data*
  • Physicians / statistics & numerical data*
  • Spain
  • Specialization / statistics & numerical data