Detection of errors by attending physicians on a general medicine service

J Gen Intern Med. 2003 Aug;18(8):595-600. doi: 10.1046/j.1525-1497.2003.20919.x.


Background: Attending physicians are well positioned to identify medical errors and understand their consequences. The spectrum of errors that can be detected by attending physicians in the course of their usual practice is currently unknown.

Objectives: To determine the frequency, types, and consequences of errors that can be detected by attending hospitalist physicians in the care of their patients, and to compare the types of errors first discovered by attending hospitalists to those discovered by other providers.

Design: Prospective identification of errors by attending physicians.

Setting: Two hundred-bed, academic hospital.

Patients: Five hundred twenty-eight patients admitted to the general medicine service from October 2000 to April 2001.

Measurements: Errors, both near misses and adverse events, were identified during the course of routine, clinical care by 2 attending hospitalists. Errors first detected by other health care workers were also recorded.

Main results: Of the 528 patients admitted to the hospitalist service, 10.4% experienced at least 1 error: 6.2% a near miss and 4.2% an adverse event. Although differences did not achieve statistical significance, most of the errors first detected by house staff, nurses, and laboratory technicians were adverse events; most of the errors first detected by the attending hospitalists, pharmacists, and consultants were near misses. Drug errors were the most common type of error overall.

Conclusions: Attending physicians engaged in routine clinical care can detect a range of errors, and differences may exist in the types of errors detected by various health care providers.

Publication types

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

MeSH terms

  • Academic Medical Centers
  • Adolescent
  • Aged
  • Female
  • Hospitals, General
  • Humans
  • Male
  • Medical Errors / standards*
  • Medical Errors / statistics & numerical data
  • Medical Staff, Hospital*
  • Middle Aged
  • Prospective Studies
  • Risk Management / standards*
  • United States