Industrial Conceptualization of Health Care Versus the Naturalistic Decision-Making Paradigm: Work as Imagined Versus Work as Done

IF 2.2 Q3 ENGINEERING, INDUSTRIAL
K. Catchpole, Myrtede C. Alfred
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引用次数: 13

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.
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
过去20年来,医疗保健的质量和安全问题促使人们需要超越传统的医疗保健视为一个手工过程的观点,转向社会技术系统的绩效观。工业方法的采用更加强调过程和结果的标准化,通常将人类视为系统的“薄弱”部分,而不是重视他们在将复杂、不透明和不可预测的临床系统结合在一起方面的作用。尽管一些医疗保健任务可以线性建模,但其他任务则要复杂得多。事实证明,通过循证实践减少临床推理差异的努力存在问题,因为未能提供针对具体情况的适应手段,也未能解释临床工作的复杂性和适应性。我们认为,目前高度实证的临床决策方法反映了临床推理“如想象的那样”,而自然决策(NDM)范式的应用可以帮助揭示临床推理“如常”。这种方法将有利于改善诊断条件;急性、时间紧迫的临床工作的设计;识别病情恶化的患者;临床决策支持系统的开发;以及更多的临床任务。医疗保健似乎已经准备好接受NDM方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.60
自引率
10.00%
发文量
21
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