{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/107502"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/107502","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Application of CAST to hospital adverse events","abstract":"Despite the passage of 15 years since the Institute of Medicine sought to galvanize the nation with its report To Err is Human, the authors' goal to dramatically improve the quality of healthcare delivery in the United States has yet to be accomplished. While the report and subsequent efforts make frequent reference to the challenges of designing and obtaining system safety, few system tools have been applied in the healthcare industry. Instead, methods such as root cause analysis (RCA) are the current accepted industry standards. The Systems Theoretic Accident Model and Processes (STAMP) is a model created by Dr. Nancy Leveson that has been successfully applied in a number of industries worldwide to improve system safety. STAMP has the capability to aid the healthcare industry professionals in reaching their goal of improving the quality of patient care. This thesis applies the Causal Accident Systems Theoretic (CAST) accident analysis tool, created by Dr. Leveson based on STAMP, to a hospital accident. The accident reviewed is a realistic, fictionalized accident described by a case study created by the VA to train healthcare personnel in the VA RCA methodology. This thesis provides an example of the application of CAST and provides a comparison of the method to the outcomes of an RCA performed by the VA independently on the same case. The CAST analysis demonstrated that a broader set of causes was identified by the systems approach compared to that of the RCA. This enhanced ability to identify causality led to the identification of additional system improvements. Continued future efforts should be taken to aid in the adoption of a systems approach such as CAST throughout the healthcare industry to ensure the realization of the quality improvements outlined by the IOB in 1999.","abstract_html":"Despite the passage of 15 years since the Institute of Medicine sought to galvanize the nation with its report To Err is Human, the authors' goal to dramatically improve the quality of healthcare delivery in the United States has yet to be accomplished. While the report and subsequent efforts make frequent reference to the challenges of designing and obtaining system safety, few system tools have been applied in the healthcare industry. Instead, methods such as root cause analysis (RCA) are the current accepted industry standards. The Systems Theoretic Accident Model and Processes (STAMP) is a model created by Dr. Nancy Leveson that has been successfully applied in a number of industries worldwide to improve system safety. STAMP has the capability to aid the healthcare industry professionals in reaching their goal of improving the quality of patient care. This thesis applies the Causal Accident Systems Theoretic (CAST) accident analysis tool, created by Dr. Leveson based on STAMP, to a hospital accident. The accident reviewed is a realistic, fictionalized accident described by a case study created by the VA to train healthcare personnel in the VA RCA methodology. This thesis provides an example of the application of CAST and provides a comparison of the method to the outcomes of an RCA performed by the VA independently on the same case. The CAST analysis demonstrated that a broader set of causes was identified by the systems approach compared to that of the RCA. This enhanced ability to identify causality led to the identification of additional system improvements. Continued future efforts should be taken to aid in the adoption of a systems approach such as CAST throughout the healthcare industry to ensure the realization of the quality improvements outlined by the IOB in 1999.","abstract_has_math":false,"creators":["O'Neil, Meaghan (Meaghan Marie)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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