Nancy Leveson1, Aubrey Samost2, Sidney Dekker3, Stan Finkelstein4, Jai Raman5. 1. From the Department of Aeronautics and Astronautics and Engineering Systems. 2. Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, Massachusetts. 3. Safety Science Innovation Lab, Griffith University School of Psychology, University of Queensland, Queensland, Australia. 4. Harvard Medical School, Beth Israel Deaconess Hospital, Boston, Massachusetts. 5. Department of Cardiac Surgery, Rush University Medical Center, Chicago, Illinois.
Abstract
OBJECTIVE: This study aimed to demonstrate the use of a systems theory-based accident analysis technique in health care applications as a more powerful alternative to the chain-of-event accident models currently underpinning root cause analysis methods. METHOD: A new accident analysis technique, CAST [Causal Analysis based on Systems Theory], is described and illustrated on a set of adverse cardiovascular surgery events at a large medical center. The lessons that can be learned from the analysis are compared with those that can be derived from the typical root cause analysis techniques used today. RESULTS: The analysis of the 30 cardiovascular surgery adverse events using CAST revealed the reasons behind unsafe individual behavior, which were related to the design of the system involved and not negligence or incompetence on the part of individuals. With the use of the system-theoretic analysis results, recommendations can be generated to change the context in which decisions are made and thus improve decision making and reduce the risk of an accident. CONCLUSIONS: The use of a systems-theoretic accident analysis technique can assist in identifying causal factors at all levels of the system without simply assigning blame to either the frontline clinicians or technicians involved. Identification of these causal factors in accidents will help health care systems learn from mistakes and design system-level changes to prevent them in the future.
OBJECTIVE: This study aimed to demonstrate the use of a systems theory-based accident analysis technique in health care applications as a more powerful alternative to the chain-of-event accident models currently underpinning root cause analysis methods. METHOD: A new accident analysis technique, CAST [Causal Analysis based on Systems Theory], is described and illustrated on a set of adverse cardiovascular surgery events at a large medical center. The lessons that can be learned from the analysis are compared with those that can be derived from the typical root cause analysis techniques used today. RESULTS: The analysis of the 30 cardiovascular surgery adverse events using CAST revealed the reasons behind unsafe individual behavior, which were related to the design of the system involved and not negligence or incompetence on the part of individuals. With the use of the system-theoretic analysis results, recommendations can be generated to change the context in which decisions are made and thus improve decision making and reduce the risk of an accident. CONCLUSIONS: The use of a systems-theoretic accident analysis technique can assist in identifying causal factors at all levels of the system without simply assigning blame to either the frontline clinicians or technicians involved. Identification of these causal factors in accidents will help health care systems learn from mistakes and design system-level changes to prevent them in the future.
Authors: George S Avrunin; Lori A Clarke; Heather M Conboy; Leon J Osterweil; Roger D Dias; Steven J Yule; Julian M Goldman; Marco A Zenati Journal: Softw Eng Healthc Syst SEHS IEEE ACM Int Workshop Date: 2018-05