Dean Tanner B, Seecheran Rajeev, Badgett Robert G, Zackula Rosey, Symons John
Department of Internal Medicine, Intermountain Health, Salt Lake City, UT 84120, United States.
Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87106, United States.
JAMIA Open. 2024 Oct 7;7(4):ooae100. doi: 10.1093/jamiaopen/ooae100. eCollection 2024 Dec.
This survey aims to understand frontline healthcare professionals' perceptions of artificial intelligence (AI) in healthcare and assess how AI familiarity influences these perceptions.
We conducted a survey from February to March 2023 of physicians and physician assistants registered with the Kansas State Board of Healing Arts. Participants rated their perceptions toward AI-related domains and constructs on a 5-point Likert scale, with higher scores indicating stronger agreement. Two sub-groups were created for analysis to assess the impact of participants' familiarity and experience with AI on the survey results.
From 532 respondents, key concerns were Perceived Communication Barriers (median = 4.0, IQR = 2.8-4.8), Unregulated Standards (median = 4.0, IQR = 3.6-4.8), and Liability Issues (median = 4.0, IQR = 3.5-4.8). Lower levels of agreement were noted for Trust in AI Mechanisms (median = 3.0, IQR = 2.2-3.4), Perceived Risks of AI (median = 3.2, IQR = 2.6-4.0), and Privacy Concerns (median = 3.3, IQR = 2.3-4.0). Positive correlations existed between Intention to use AI and Perceived Benefits ( = 0.825) and Trust in AI Mechanisms ( = 0.777). Perceived risk negatively correlated with Intention to Use AI ( = -0.718). There was no difference in perceptions between AI experienced and AI naïve subgroups.
The findings suggest that perceptions of benefits, trust, risks, communication barriers, regulation, and liability issues influence healthcare professionals' intention to use AI, regardless of their AI familiarity.
The study highlights key factors affecting AI adoption in healthcare from the frontline healthcare professionals' perspective. These insights can guide strategies for successful AI implementation in healthcare.
本次调查旨在了解一线医疗保健专业人员对医疗保健领域人工智能（AI）的看法，并评估对AI的熟悉程度如何影响这些看法。
我们于2023年2月至3月对在堪萨斯州治疗艺术委员会注册的医生和医师助理进行了一项调查。参与者对与AI相关的领域和结构在5点李克特量表上进行评分，分数越高表明同意程度越高。创建了两个亚组进行分析，以评估参与者对AI的熟悉程度和经验对调查结果的影响。
在532名受访者中，主要担忧包括感知到的沟通障碍（中位数 = 4.0，四分位间距 = 2.8 - 4.8）、标准未规范（中位数 = 4.0，四分位间距 = 3.6 - 4.8）和责任问题（中位数 = 4.0，四分位间距 = 3.5 - 4.8）。对AI机制的信任（中位数 = 3.0，四分位间距 = 2.2 - 3.4）、AI的感知风险（中位数 = 3.2，四分位间距 = 2.6 - 4.0）和隐私担忧（中位数 = 3.3，四分位间距 = 2.3 - 4.0）的同意程度较低。使用AI的意愿与感知到的益处（r = 0.825）和对AI机制的信任（r = 0.777）之间存在正相关。感知风险与使用AI的意愿呈负相关（r = -0.718）。有AI经验的亚组和无AI经验的亚组在看法上没有差异。
研究结果表明，无论对AI的熟悉程度如何，对益处、信任、风险、沟通障碍、监管和责任问题的看法都会影响医疗保健专业人员使用AI的意愿。
该研究从一线医疗保健专业人员的角度突出了影响医疗保健领域采用AI的关键因素。这些见解可为医疗保健领域成功实施AI的策略提供指导。
