Sudeep Hegde, A. Hettinger, R. Fairbanks, J. Wreathall, Seth Krevat, A. Bisantz
{"title":"Knowledge Elicitation to Understand Resilience: A Method and Findings From a Health Care Case Study","authors":"Sudeep Hegde, A. Hettinger, R. Fairbanks, J. Wreathall, Seth Krevat, A. Bisantz","doi":"10.1177/1555343419877719","DOIUrl":null,"url":null,"abstract":"Resilience engineering (RE) has ushered new approaches to learning about work in complex sociotechnical systems. In terms of improving safety, RE marks a shift from the traditional approach of retrospectively investigating adverse events, toward learning proactively about patterns in everyday work, including how things go well. This study applied the RE framework to the health care domain, by developing and implementing a new knowledge-elicitation protocol to learn about how frontline care providers achieve safe and effective patient care in their everyday work. Eighteen participants, including physicians, nurses, residents, and clinical leaders from a range of specialties, were interviewed using the new protocol. Qualitative analysis of the data revealed multiple themes and patterns which underlie resilient functioning of individuals, teams, and the organization as a whole. Further, a Resilience Mapping Framework (RMF) was developed based on major thematic categories to systematically represent and map various resilient capabilities—monitoring, anticipating, responding, and learning—across different levels of system scale, from the individual to the organizational. This study demonstrates new methods to identify and represent resilience not just during salient and critical “events,” but across the continuum of situations, from the everyday “normal” functioning to the critical.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":"14 1","pages":"75 - 95"},"PeriodicalIF":2.2000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419877719","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Engineering and Decision Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1555343419877719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 10
Abstract
Resilience engineering (RE) has ushered new approaches to learning about work in complex sociotechnical systems. In terms of improving safety, RE marks a shift from the traditional approach of retrospectively investigating adverse events, toward learning proactively about patterns in everyday work, including how things go well. This study applied the RE framework to the health care domain, by developing and implementing a new knowledge-elicitation protocol to learn about how frontline care providers achieve safe and effective patient care in their everyday work. Eighteen participants, including physicians, nurses, residents, and clinical leaders from a range of specialties, were interviewed using the new protocol. Qualitative analysis of the data revealed multiple themes and patterns which underlie resilient functioning of individuals, teams, and the organization as a whole. Further, a Resilience Mapping Framework (RMF) was developed based on major thematic categories to systematically represent and map various resilient capabilities—monitoring, anticipating, responding, and learning—across different levels of system scale, from the individual to the organizational. This study demonstrates new methods to identify and represent resilience not just during salient and critical “events,” but across the continuum of situations, from the everyday “normal” functioning to the critical.