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人工智能实施中医生的角色与能力:通过医生访谈进行的定性分析

Roles and Competencies of Doctors in Artificial Intelligence Implementation: Qualitative Analysis Through Physician Interviews.

作者信息

Tanaka Masashi, Matsumura Shinji, Bito Seiji

机构信息

Department of Clinical Epidemiology, Tokyo Medical Center, National Hospital Organization, Tokyo, Japan.

Department of Medical Ethics, Tohoku University Graduate School, Sendai, Japan.

出版信息

JMIR Form Res. 2023 May 18;7:e46020. doi: 10.2196/46020.

DOI:10.2196/46020
PMID:37200074
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10236283/
Abstract

BACKGROUND

Artificial intelligence (AI) is a term used to describe the use of computers and technology to emulate human intelligence mechanisms. Although AI is known to affect health services, the impact of information provided by AI on the patient-physician relationship in actual practice is unclear.

OBJECTIVE

The purpose of this study is to investigate the effect of introducing AI functions into the medical field on the role of the physician or physician-patient relationship, as well as potential concerns in the AI era.

METHODS

We conducted focus group interviews in Tokyo's suburbs with physicians recruited through snowball sampling. The interviews were conducted in accordance with the questions listed in the interview guide. A verbatim transcript recording of all interviews was qualitatively analyzed using content analysis by all authors. Similarly, extracted code was grouped into subcategories, categories, and then core categories. We continued interviewing, analyzing, and discussing until we reached data saturation. In addition, we shared the results with all interviewees and confirmed the content to ensure the credibility of the analysis results.

RESULTS

A total of 9 participants who belonged to various clinical departments in the 3 groups were interviewed. The same interviewers conducted the interview as the moderator each time. The average group interview time for the 3 groups was 102 minutes. Content saturation and theme development were achieved with the 3 groups. We identified three core categories: (1) functions expected to be replaced by AI, (2) functions still expected of human physicians, and (3) concerns about the medical field in the AI era. We also summarized the roles of physicians and patients, as well as the changes in the clinical environment in the age of AI. Some of the current functions of the physician were primarily replaced by AI functions, while others were inherited as the functions of the physician. In addition, "functions extended by AI" obtained by processing massive amounts of data will emerge, and a new role for physicians will be created to deal with them. Accordingly, the importance of physician functions, such as responsibility and commitment based on values, will increase, which will simultaneously increase the expectations of the patients that physicians will perform these functions.

CONCLUSIONS

We presented our findings on how the medical processes of physicians and patients will change as AI technology is fully implemented. Promoting interdisciplinary discussions on how to overcome the challenges is essential, referring to the discussions being conducted in other fields.

摘要

背景

人工智能(AI)是一个用于描述利用计算机和技术来模拟人类智能机制的术语。尽管已知人工智能会影响医疗服务,但在实际临床中,人工智能所提供的信息对医患关系的影响尚不清楚。

目的

本研究旨在探讨将人工智能功能引入医学领域对医生角色或医患关系的影响,以及人工智能时代的潜在问题。

方法

我们在东京郊区通过滚雪球抽样招募医生进行焦点小组访谈。访谈按照访谈指南中列出的问题进行。所有作者使用内容分析法对所有访谈的逐字记录进行定性分析。同样,提取的代码被分组为子类别、类别,然后是核心类别。我们持续进行访谈、分析和讨论,直到达到数据饱和。此外,我们与所有受访者分享结果并确认内容,以确保分析结果的可信度。

结果

共访谈了3组中隶属于不同临床科室的9名参与者。每次访谈均由相同的访谈者担任主持人。3组的平均小组访谈时间为102分钟。3组实现了内容饱和与主题发展。我们确定了三个核心类别:(1)预计会被人工智能取代的功能;(2)仍然期望人类医生具备的功能;(3)对人工智能时代医学领域的担忧。我们还总结了医生和患者的角色,以及人工智能时代临床环境的变化。医生目前的一些功能主要被人工智能功能所取代,而其他功能则作为医生的功能被传承下来。此外,通过处理大量数据获得的“人工智能扩展功能”将会出现,并且将为医生创造一个新的角色来应对这些功能。相应地,基于价值观的责任和承诺等医生功能的重要性将会增加,这同时也会提高患者对医生履行这些功能的期望。

结论

我们展示了关于随着人工智能技术全面应用,医生和患者的医疗过程将如何变化的研究结果。参考其他领域正在进行的讨论,促进关于如何克服这些挑战的跨学科讨论至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b75e/10236283/e2039bac8658/formative_v7i1e46020_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b75e/10236283/e2039bac8658/formative_v7i1e46020_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b75e/10236283/e2039bac8658/formative_v7i1e46020_fig1.jpg

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