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基层医疗电子问诊中人工智能的七个机遇:工作人员和患者观点的定性研究

Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.

作者信息

Moschogianis Susan, Darley Sarah, Coulson Tessa, Peek Niels, Cheraghi-Sohi Sudeh, Brown Benjamin C

机构信息

School of Health Sciences, Division of Population Health, Health Services Research and Primary Care, University of Manchester, Manchester, United Kingdom.

National Health Service Salford Clinical Commissioning Group, Salford, United Kingdom.

出版信息

Ann Fam Med. 2025 May 27;23(3):214-222. doi: 10.1370/afm.240292.


DOI:10.1370/afm.240292
PMID:40425478
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12120151/
Abstract

PURPOSE: Increased workload associated with electronic visits (eVisits) in primary care could potentially be decreased by the use of artificial intelligence (AI); however, it is unknown whether this use of AI would be acceptable to staff and patients. We explored patient and primary care staff views on the use of and opportunities for AI during eVisits. METHODS: We conducted semistructured interviews and focus groups with primary care staff (n = 16) and patients (n = 37) from primary care practices in northwest England and London (n = 14) using the Patchs eVisits system (Patchs Health Limited; ) from May 2020 to September 2021. We analyzed verbatim transcripts using thematic analysis. RESULTS: Misconceptions regarding AI were common, which led to initial reservations on its use during eVisits. Perceived potential AI benefits included decreased staff workload and faster response times for patients. Safety concerns stemmed from the complexity of primary care and fears of depersonalized service. The following 7 opportunities for AI during eVisits were identified: workflow, directing, prioritization, asking questions, writing assistance, providing self-help information, and face-to-face appointment booking. Despite staff concerns regarding patient acceptability, most patients welcomed the use of AI if it were used as an adjunct to (not replacement for) clinical judgment and could support them in getting help more quickly. Retention of clinical oversight and ongoing evaluation was key to staff acceptability. CONCLUSIONS: Patients and staff welcomed the use of AI and identified 7 potential uses during eVisits to decrease staff workload and improve patient safety. Successful implementation will depend on clear communication from practices, demonstrating and monitoring safety, clarifying misconceptions, and reassuring that it will not replace humans.

摘要

目的:在基层医疗中,使用人工智能(AI)可能会减少与电子问诊(eVisits)相关的工作量增加;然而,尚不清楚这种AI的使用是否会被工作人员和患者接受。我们探讨了患者和基层医疗工作人员对在电子问诊期间使用AI及其机会的看法。 方法:2020年5月至2021年9月,我们使用Patchs电子问诊系统(Patchs Health Limited)对来自英格兰西北部和伦敦的基层医疗机构的基层医疗工作人员(n = 16)和患者(n = 37)进行了半结构化访谈和焦点小组讨论(n = 14)。我们使用主题分析法分析逐字记录。 结果:对AI的误解很常见,这导致了对其在电子问诊期间使用的初步保留意见。AI的潜在好处包括减少工作人员工作量和加快患者响应时间。安全担忧源于基层医疗的复杂性以及对非人性化服务的恐惧。确定了电子问诊期间AI的以下7个机会:工作流程、指导、优先级排序、提问、写作辅助、提供自助信息和面对面预约挂号。尽管工作人员担心患者的接受度,但如果AI用作临床判断的辅助手段(而非替代)并能帮助他们更快获得帮助,大多数患者欢迎使用AI。保留临床监督和持续评估是工作人员接受度的关键。 结论:患者和工作人员欢迎使用AI,并确定了电子问诊期间的7种潜在用途,以减少工作人员工作量并提高患者安全性。成功实施将取决于医疗机构的清晰沟通、展示和监测安全性、澄清误解以及确保其不会取代人类。

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Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.

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本文引用的文献

[1]
Exploring the experiences and preferences of South Asian patients' of primary care in England since COVID-19.

Health Expect. 2024-2

[2]
Understanding How the Design and Implementation of Online Consultations Affect Primary Care Quality: Systematic Review of Evidence With Recommendations for Designers, Providers, and Researchers.

J Med Internet Res. 2022-10-24

[3]
Is primary health care ready for artificial intelligence? What do primary health care stakeholders say?

BMC Med Inform Decis Mak. 2022-9-9

[4]
General Practitioners' Attitudes Toward Artificial Intelligence-Enabled Systems: Interview Study.

J Med Internet Res. 2022-1-27

[5]
Patient apprehensions about the use of artificial intelligence in healthcare.

NPJ Digit Med. 2021-9-21

[6]
Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal.

J Med Internet Res. 2021-9-3

[7]
Professionals' responses to the introduction of AI innovations in radiology and their implications for future adoption: a qualitative study.

BMC Health Serv Res. 2021-8-14

[8]
Artificial intelligence projects in healthcare: 10 practical tips for success in a clinical environment.

BMJ Health Care Inform. 2021-7

[9]
How to conduct written online consultations with patients in primary care.

BMJ. 2021-2-24

[10]
Experiences of digital communication with automated patient interviews and asynchronous chat in Swedish primary care: a qualitative study.

BMJ Open. 2020-7-23

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