{"title":"医疗保健的工业概念化与自然主义决策范式:想象的工作与完成的工作","authors":"K. Catchpole, Myrtede C. Alfred","doi":"10.1177/1555343418774661","DOIUrl":null,"url":null,"abstract":"Quality and safety concerns in health care over the past 20 years precipitated the need to move beyond the traditional view of health care as an artisanal process toward a sociotechnical systems view of performance. The adoption of industrial approaches placed a greater emphasis on standardization of processes and outcomes, often treating humans as the “weak” part of the system rather than valuing their role in holding together complex, opaque, and unpredictable clinical systems. Although some health care tasks can be modeled linearly, others are much more complex. Efforts to reduce variation in clinical reasoning through evidence-based practices have proven problematic by failing to provide a means for context-specific adaptation or to account for the complex and adaptive nature of clinical work. We argue that the current, highly empirical approach to clinical decision making reflects clinical reasoning “as imagined,” whereas the application of the naturalistic decision-making (NDM) paradigm can help reveal clinical reasoning “as done.” This approach will have benefits for improving the conditions for diagnosis; the design of acute, time-pressured clinical work; the identification of deteriorating patients; the development of clinical decision support systems; and many more clinical tasks. Health care seems ready to accept NDM approaches.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":"12 1","pages":"222 - 226"},"PeriodicalIF":2.2000,"publicationDate":"2018-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343418774661","citationCount":"13","resultStr":"{\"title\":\"Industrial Conceptualization of Health Care Versus the Naturalistic Decision-Making Paradigm: Work as Imagined Versus Work as Done\",\"authors\":\"K. Catchpole, Myrtede C. Alfred\",\"doi\":\"10.1177/1555343418774661\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quality and safety concerns in health care over the past 20 years precipitated the need to move beyond the traditional view of health care as an artisanal process toward a sociotechnical systems view of performance. The adoption of industrial approaches placed a greater emphasis on standardization of processes and outcomes, often treating humans as the “weak” part of the system rather than valuing their role in holding together complex, opaque, and unpredictable clinical systems. Although some health care tasks can be modeled linearly, others are much more complex. Efforts to reduce variation in clinical reasoning through evidence-based practices have proven problematic by failing to provide a means for context-specific adaptation or to account for the complex and adaptive nature of clinical work. We argue that the current, highly empirical approach to clinical decision making reflects clinical reasoning “as imagined,” whereas the application of the naturalistic decision-making (NDM) paradigm can help reveal clinical reasoning “as done.” This approach will have benefits for improving the conditions for diagnosis; the design of acute, time-pressured clinical work; the identification of deteriorating patients; the development of clinical decision support systems; and many more clinical tasks. Health care seems ready to accept NDM approaches.\",\"PeriodicalId\":46342,\"journal\":{\"name\":\"Journal of Cognitive Engineering and Decision Making\",\"volume\":\"12 1\",\"pages\":\"222 - 226\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2018-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/1555343418774661\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cognitive Engineering and Decision Making\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/1555343418774661\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Engineering and Decision Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1555343418774661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Industrial Conceptualization of Health Care Versus the Naturalistic Decision-Making Paradigm: Work as Imagined Versus Work as Done
Quality and safety concerns in health care over the past 20 years precipitated the need to move beyond the traditional view of health care as an artisanal process toward a sociotechnical systems view of performance. The adoption of industrial approaches placed a greater emphasis on standardization of processes and outcomes, often treating humans as the “weak” part of the system rather than valuing their role in holding together complex, opaque, and unpredictable clinical systems. Although some health care tasks can be modeled linearly, others are much more complex. Efforts to reduce variation in clinical reasoning through evidence-based practices have proven problematic by failing to provide a means for context-specific adaptation or to account for the complex and adaptive nature of clinical work. We argue that the current, highly empirical approach to clinical decision making reflects clinical reasoning “as imagined,” whereas the application of the naturalistic decision-making (NDM) paradigm can help reveal clinical reasoning “as done.” This approach will have benefits for improving the conditions for diagnosis; the design of acute, time-pressured clinical work; the identification of deteriorating patients; the development of clinical decision support systems; and many more clinical tasks. Health care seems ready to accept NDM approaches.