Open AccessRoot Cause Analysis: Learning from Adverse Safety Events
Author(s) -
Olga R. Brook,
Jonathan B. Kruskal,
Ronald L. Eisenberg,
David B. Larson
Publication year - 2015
Publication title -
radiographics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.866
H-Index - 172
eISSN - 1527-1323
pISSN - 0271-5333
DOI - 10.1148/rg.2015150067
Subject(s) - root cause analysis , medicine , root cause , causation , adverse effect , patient safety , process (computing) , root (linguistics) , causality (physics) , intensive care medicine , medical emergency , health care , operations management , computer science , linguistics , philosophy , physics , forensic engineering , quantum mechanics , political science , law , engineering , economics , economic growth , operating system
Serious adverse events continue to occur in clinical practice, despite our best preventive efforts. It is essential that radiologists, both as individuals and as a part of organizations, learn from such events and make appropriate changes to decrease the likelihood that such events will recur. Root cause analysis (RCA) is a process to (a) identify factors that underlie variation in performance or that predispose an event toward undesired outcomes and (b) allow for development of effective strategies to decrease the likelihood of similar adverse events occurring in the future. An RCA process should be performed within the environment of a culture of safety, focusing on underlying system contributors and, in a confidential manner, taking into account the emotional effects on the staff involved. The Joint Commission now requires that a credible RCA be performed within 45 days for all sentinel or major adverse events, emphasizing the need for all radiologists to understand the processes with which an effective RCA can be performed. Several RCA-related tools that have been found to be useful in the radiology setting include the "five whys" approach to determine causation; cause-and-effect, or Ishikawa, diagrams; causal tree mapping; affinity diagrams; and Pareto charts.