Practice indicators of suboptimal care and avoidable adverse events: a content analysis of a national qualifying examination

Acad Med. 2013 Oct;88(10):1493-8. doi: 10.1097/ACM.0b013e3182a356af.

Abstract

Purpose: To (1) compile an initial list of physician-related practice indicators (PRINDs) that contribute to causing or preventing suboptimal care (SOCR) and adverse events (AEs) and (2) determine the extent to which one national exam assessed these PRINDs.

Method: In 2009-2010, the authors searched the literature and surveyed 17 physician experts to compile a list of PRINDs of SOCR and avoidable AEs. They then conducted a content analysis of the 2008 and 2009 Medical Council of Canada (MCC) Qualifying Examinations (QEs).

Results: The authors identified 92 unique PRINDs, of which 59 were behaviors or decisions expected of all physicians and suitable for assessment on a general medical examination. Of these, 36 (61%) were tested on the 2008 and 2009 MCC QEs. The mean number of PRINDs tested per exam was highest for Part I Knowledge (32.2), followed by Part I clinical decision making (CDM) (18.4) and Part II clinical performance (objective structured clinical examination [OSCE]) (9.8). The percentage of questions or cases per exam testing a PRIND (e.g., 14/36 [39%] for CDM and 5.26/12 [44%] for OSCE) differed from the percentage of the total test score attributed to PRINDs (e.g., 10.8/36 [30%] for CDM and 68.5/1,522.3 [5%] for OSCE).

Conclusions: PRINDs represent candidates' abilities to avoid SOCR and AEs and constitute an important aspect of medical practice to be assessed on licensing or certifying examinations to best protect the public. The different scoring methods used to measure such knowledge and skills warrant further consideration.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Canada
  • Clinical Competence*
  • Decision Making
  • Education, Medical*
  • Educational Measurement / methods*
  • Humans
  • Medical Errors / prevention & control*
  • Patient Safety*
  • Practice Patterns, Physicians' / statistics & numerical data*
  • Predictive Value of Tests
  • Quality Assurance, Health Care*
  • Risk Factors