Detecting adverse events for patient safety research: a review of current methodologies

  • Authors:

  • Harvey J. Murff;Vimla L. Patel;George Hripcsak;David W. Bates

  • Affiliations:

  • Department of Veterans Affairs, Tennessee Valley Healthcare System, GRECC, 1310 24th Avenue South, Nashville, TN and Division of General Internal Medicine, Department of Medicine, Vanderbilt Unive ...;Laboratory for Decision Making and Cognition, Departments of Biomedical Informatics and Psychiatry, Columbia University, New York;Department of Biomedical Informatics, Columbia University, New York;Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital and Center for Applied Medical Informatics Systems, Partners Healthcare System, and Harvard University

  • Venue:
  • Journal of Biomedical Informatics - Patient safety
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

Promoting patient safety is a national priority. To evaluate interventions for reducing medical errors and adverse event, effective methods for detecting such events are required. This paper reviews the current methodologies for detection of adverse events and discusses their relative advantages and limitations. It also presents a cognitive framework for error monitoring and detection. While manual chart review has been considered the "gold-standard" for identifying adverse events in many patient safety studies, this methodology is expensive and imperfect. Investigators have developed or are currently evaluating, several electronic methods that can detect adverse events using coded data, free-text clinical narratives, or a combination of techniques. Advances in these systems will greatly facilitate our ability to monitor adverse events and promote patient safety research. But these systems will perform optimally only if we improve our understanding of the fundamental nature of errors and the ways in which the human mind can naturally, but erroneously, contribute to the problems that we observe.