医疗决策和日常生活中的算法：有什么区别？

IF 2.2 Q2 MEDICINE, GENERAL & INTERNAL

Diagnosis Pub Date : 2024-02-23 eCollection Date: 2024-08-01 DOI:10.1515/dx-2024-0010

David Chartash, Michael A Bruno

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引用次数: 0

摘要

算法是现代生活中无处不在的一部分。尽管从早期将计算机应用于医学的努力开始，算法就已成为医学的一部分，但临床医生对使用决策支持和算法来解决认知偏差问题的抵触情绪一直很有限。这种抵制不仅限于使用算法临床决策支持，还包括证据和随机推理以及电子病历强制功能的影响。医生在临床决策中对算法支持的抵制与他们在生活其他方面对算法支持的普遍接受形成了鲜明对比。

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Algorithms in medical decision-making and in everyday life: what's the difference?

Algorithms are a ubiquitous part of modern life. Despite being a component of medicine since early efforts to deploy computers in medicine, clinicians' resistance to using decision support and use algorithms to address cognitive biases has been limited. This resistance is not just limited to the use of algorithmic clinical decision support, but also evidence and stochastic reasoning and the implications of the forcing function of the electronic medical record. Physician resistance to algorithmic support in clinical decision making is in stark contrast to their general acceptance of algorithmic support in other aspects of life.

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来源期刊

Diagnosis MEDICINE, GENERAL & INTERNAL-

CiteScore

7.20

自引率

5.70%

发文量

期刊介绍： Diagnosis focuses on how diagnosis can be advanced, how it is taught, and how and why it can fail, leading to diagnostic errors. The journal welcomes both fundamental and applied works, improvement initiatives, opinions, and debates to encourage new thinking on improving this critical aspect of healthcare quality.　 Topics: -Factors that promote diagnostic quality and safety -Clinical reasoning -Diagnostic errors in medicine -The factors that contribute to diagnostic error: human factors, cognitive issues, and system-related breakdowns -Improving the value of diagnosis – eliminating waste and unnecessary testing -How culture and removing blame promote awareness of diagnostic errors -Training and education related to clinical reasoning and diagnostic skills -Advances in laboratory testing and imaging that improve diagnostic capability -Local, national and international initiatives to reduce diagnostic error