An evidence-based toolkit for the development of effective and sustainable root cause analysis system safety solutions.
Root cause analysis (RCA) after adverse events in healthcare is a standard practice at many institutions. However, healthcare has failed to see a dramatic improvement in patient safety over the last decade. In order to improve the RCA process, this study used systems safety science, which is based partly on human factors engineering principles and has been applied with success in other high-risk industries like aviation. A multi-institutional dataset of 334 RCA cases and 782 solutions was analyzed using qualitative methods. A team of safety science experts developed a model of 13 RCA solutions categories through an iterative process, using semi-structured interview data from 44 frontline staff members from 7 different hospital-based unit types. These categories were placed in a model and toolkit to help guide RCA teams in developing sustainable and effective solutions to prevent future adverse events. This study was limited by its retrospective review of cases and use of interviews rather than clinical observations. In conclusion, systems safety principles were used to develop guidelines for RCA teams to promote systems-level sustainable and effective solutions for adverse events.
Assistant Professor, Emergency Medicine at Georgetown University School of Medicine and Director of Informatics Research, National Center for Human Factors in Healthcare.
A Zachary
AZ
Hettinger
Rollin J
RJ
Fairbanks
Sudeep
S
Hegde
Alexandra S
AS
Rackoff
John
J
Wreathall
Vicki L
VL
Lewis
Ann M
AM
Bisantz
Robert L
RL
Wears
D016208:Databases, Factual; D006801:Humans; D007407:Interviews as Topic; D019300:Medical Errors / Q000517:prevention & control*; D061214:Patient Safety / Q000592:standards*; D036301:Qualitative Research; D012189:Retrospective Studies; D060891:Root Cause Analysis / Q000379:methods* / Q000592:standards; D017751:Safety Management / Q000379:methods* / Q000458:organization & administration / Q000592:standards