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医生是否准备好进行精准的抗生素处方?对印度和新加坡人工智能支持的临床决策支持系统接受情况的定性分析。

Are physicians ready for precision antibiotic prescribing? A qualitative analysis of the acceptance of artificial intelligence-enabled clinical decision support systems in India and Singapore.

机构信息

Infectious Diseases Research and Training Office, National Centre for Infectious Diseases, Singapore; Department of Preventive and Population Medicine, Office of Clinical Epidemiology, Analytics, and Knowledge [OCEAN], Tan Tock Seng Hospital, Singapore.

Department of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India.

出版信息

J Glob Antimicrob Resist. 2023 Dec;35:76-85. doi: 10.1016/j.jgar.2023.08.016. Epub 2023 Aug 26.

Abstract

OBJECTIVES

Artificial intelligence (AI)-driven clinical decision support systems (CDSSs) can augment antibiotic decision-making capabilities, but physicians' hesitancy in adopting them may undermine their utility. We conducted a cross-country comparison of physician perceptions on the barriers and facilitators in accepting an AI-enabled CDSS for antibiotic prescribing.

METHODS

We conducted in-depth interviews with physicians from the National Centre for Infectious Diseases (NCID), Singapore, and Christian Medical College Vellore (CMCV), India, between April and December 2022. Our semi-structured in-depth interview guides were anchored on Venkatesh's UTAUT model. We used clinical vignettes to illustrate the application of AI in clinical decision support for antibiotic prescribing and explore medico-legal concerns.

RESULTS

Most NCID physicians felt that an AI-enabled CDSS could facilitate antibiotic prescribing, while most CMCV physicians were sceptical about the tool's utility. The hesitancy in adopting an AI-enabled CDSS stems from concerns about the lack of validated and successful examples, fear of losing autonomy and clinical skills, difficulty of use, and impediment in work efficiency. Physicians from both sites felt that a user-friendly interface, integration with workflow, transparency of output, a guiding medico-legal framework, and training and technical support would improve the uptake of an AI-enabled CDSS.

CONCLUSION

In conclusion, the acceptance of AI-enabled CDSSs depends on the physician's confidence with the tool's recommendations, perceived ease of use, familiarity with AI, the organisation's digital culture and support, and the presence of medico-legal governance of AI. Progressive implementation and continuous feedback are essential to allay scepticism around the utility of AI-enabled CDSSs.

摘要

目的

人工智能 (AI) 驱动的临床决策支持系统 (CDSS) 可以增强抗生素决策能力,但医生对采用这些系统的犹豫可能会削弱其效用。我们对来自新加坡国家传染病中心 (NCID) 和印度基督教医学院维洛尔 (CMCV) 的医生对接受 AI 赋能的抗生素处方 CDSS 的障碍和促进因素的看法进行了跨国比较。

方法

我们在 2022 年 4 月至 12 月期间对来自新加坡国家传染病中心 (NCID) 和印度基督教医学院维洛尔 (CMCV) 的医生进行了深入访谈。我们的半结构化深入访谈指南以 Venkatesh 的 UTAUT 模型为基础。我们使用临床案例来阐述 AI 在抗生素处方临床决策支持中的应用,并探讨医学法律方面的担忧。

结果

大多数 NCID 医生认为 AI 赋能的 CDSS 可以促进抗生素处方,而大多数 CMCV 医生对该工具的实用性持怀疑态度。采用 AI 赋能的 CDSS 的犹豫源于对缺乏经过验证和成功案例的担忧、对失去自主权和临床技能的恐惧、使用难度以及工作效率障碍的担忧。来自这两个地点的医生都认为用户友好的界面、与工作流程的集成、输出的透明度、指导医学法律框架以及培训和技术支持将提高 AI 赋能的 CDSS 的采用率。

结论

总之,AI 赋能的 CDSS 的接受程度取决于医生对工具建议的信心、感知的易用性、对 AI 的熟悉程度、组织的数字文化和支持以及 AI 的医学法律治理的存在。渐进式实施和持续反馈对于缓解对 AI 赋能的 CDSS 效用的怀疑至关重要。

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