Identifying medical errors: Developing consensus on classifications and consequences

Cherri Hobgood, Jennifer Eaton, Bryan J. Weiner

Research output: Contribution to journalArticlepeer-review

3 Citations (SciVal)

Abstract

Objective: To develop consensus among clinical experts on the classification and severity of medical errors in the Emergency Department setting. Methods: A 20-member multidisciplinary panel participated in a 3-round modified-Delphi process designed to classify medical errors common to emergency medicine practice. Panelists used a 9-part Likert scale to score 19 case vignettes in 3 categories: (1) degree case represents medication error, (2) degree case represents cognitive error, and (3) outcome severity. Frequency distributions and descriptive statistics were calculated for each item. Results: Nineteen panelists (95%) completed all rounds. Consensus on both class and severity was achieved in 9/19 (47%) cases. Consensus for both error classes was achieved for 11/19 (58%) cases. Of these, a single error class was identified in 8/19 (42%) cases, and 3/19 (16%) cases were identified as both medication and cognitive. No case was identified as a non-error. On average, to achieve consensus, cognitive cases required 1.6 rounds, medication cases required 2.66 rounds, and cases identified as both medication and cognitive required 3 rounds. In 8/19 cases where class consensus in both categories was not achieved, the no-consensus category was always cognitive. In 16/19 (84%) cases, panelists achieved consensus on severity. In only 1 case (5%) did panelists agree on error class and not severity. Conclusions: There is increasing evidence that cognitive errors in medical decision making can be difficult to identify. This study suggests that error classification may challenge expert panel groups as well as individual providers.

Original languageEnglish (US)
Pages (from-to)138-144
Number of pages7
JournalJournal of Patient Safety
Volume1
Issue number3
DOIs
StatePublished - Nov 13 2016

All Science Journal Classification (ASJC) codes

  • Leadership and Management
  • Public Health, Environmental and Occupational Health

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