Hoffman Jane, Hattingh Laetitia, Shinners Lucy, Angus Rebecca L, Richards Brent, Hughes Ian, Wenke Rachel
Pharmacy Department, Gold Coast Hospital and Health Service, Southport, Australia.
School of Pharmacy and Medical Sciences, Griffith University, Southport, Australia.
JMIR Form Res. 2024 Dec 30;8:e57204. doi: 10.2196/57204.
Artificial intelligence (AI) has the potential to address growing logistical and economic pressures on the health care system by reducing risk, increasing productivity, and improving patient safety; however, implementing digital health technologies can be disruptive. Workforce perception is a powerful indicator of technology use and acceptance, however, there is little research available on the perceptions of allied health professionals (AHPs) toward AI in health care.
This study aimed to explore AHP perceptions of AI and the opportunities and challenges for its use in health care delivery.
A cross-sectional survey was conducted at a health service in, Queensland, Australia, using the Shinners Artificial Intelligence Perception tool.
A total of 231 (22.1%) participants from 11 AHPs responded to the survey. Participants were mostly younger than 40 years (157/231, 67.9%), female (189/231, 81.8%), working in a clinical role (196/231, 84.8%) with a median of 10 years' experience in their profession. Most participants had not used AI (185/231, 80.1%), had little to no knowledge about AI (201/231, 87%), and reported workforce knowledge and skill as the greatest challenges to incorporating AI in health care (178/231, 77.1%). Age (P=.01), profession (P=.009), and AI knowledge (P=.02) were strong predictors of the perceived professional impact of AI. AHPs generally felt unprepared for the implementation of AI in health care, with concerns about a lack of workforce knowledge on AI and losing valued tasks to AI. Prior use of AI (P=.02) and years of experience as a health care professional (P=.02) were significant predictors of perceived preparedness for AI. Most participants had not received education on AI (190/231, 82.3%) and desired training (170/231, 73.6%) and believed AI would improve health care. Ideas and opportunities suggested for the use of AI within the allied health setting were predominantly nonclinical, administrative, and to support patient assessment tasks, with a view to improving efficiencies and increasing clinical time for direct patient care.
Education and experience with AI are needed in health care to support its implementation across allied health, the second largest workforce in health. Industry and academic partnerships with clinicians should not be limited to AHPs with high AI literacy as clinicians across all knowledge levels can identify many opportunities for AI in health care.
人工智能（AI）有潜力通过降低风险、提高生产力和改善患者安全来应对医疗保健系统日益增长的后勤和经济压力；然而，实施数字健康技术可能会造成干扰。劳动力认知是技术使用和接受程度的有力指标，然而，关于专职医疗人员（AHP）对医疗保健领域人工智能的认知的研究却很少。
本研究旨在探讨AHP对人工智能的认知以及其在医疗保健服务中应用的机遇和挑战。
在澳大利亚昆士兰州的一家医疗服务机构使用Shinners人工智能认知工具进行了一项横断面调查。
来自11个AHP领域的231名（22.1%）参与者对调查做出了回应。参与者大多年龄在40岁以下（157/231，67.9%），女性（189/231，81.8%），担任临床职位（196/231，84.8%），其所在专业的中位工作经验为10年。大多数参与者未使用过人工智能（185/231，80.1%），对人工智能了解很少或几乎不了解（201/231，87%），并报告称劳动力知识和技能是在医疗保健中应用人工智能的最大挑战（178/231，77.1%）。年龄（P = 0.01）、专业（P = 0.009）和人工智能知识（P = 0.02）是人工智能感知专业影响的有力预测因素。AHP普遍认为自己对医疗保健中实施人工智能没有做好准备，担心缺乏关于人工智能的劳动力知识以及一些有价值的任务会被人工智能取代。之前使用过人工智能（P = 0.02）和作为医疗保健专业人员的工作年限（P = 0.02）是感知到的对人工智能准备程度的重要预测因素。大多数参与者未接受过关于人工智能的教育（190/231，82.3%），希望接受培训（170/231，73.6%），并认为人工智能将改善医疗保健。在专职医疗环境中使用人工智能的建议想法和机遇主要是非临床、行政方面的，以及用于支持患者评估任务，目的是提高效率并增加直接护理患者的临床时间。
医疗保健领域需要人工智能方面的教育和经验来支持其在专职医疗领域的实施，专职医疗是医疗领域第二大劳动力群体。行业和学术界与临床医生的合作不应仅限于具有高人工智能素养的AHP，因为所有知识水平的临床医生都能识别出医疗保健中人工智能的许多机遇。
