Patient and Provider Experience with Artificial Intelligence Screening Technology for Diabetic Retinopathy in a Rural Primary Care Setting.

Journal of Maine Medical Center Pub Date : 2023-01-01 Epub Date: 2023-04-20 DOI:10.46804/2641-2225.1144
Brian Nolan, Emma R Daybranch, Kerri Barton, Neil Korsen
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Abstract

Introduction: The development of autonomous artificial intelligence for interpreting diabetic retinopathy (DR) images has allowed for point-of-care testing in the primary care setting. This study describes patient and provider experiences and perceptions of the artificial intelligence DR screening technology called EyeArt by EyeNuk during implementation of the tool at Western Maine Primary Care in Norway, Maine.

Methods: This non-randomized, single-center, prospective observational study surveyed 102 patients and 13 primary care providers on their experience of the new screening intervention.

Results: All surveyed providers agreed that the new screening tool would improve access and annual screening rates. Some providers also identified initial challenges in incorporating the tool into the primary care visit (31%). Patients expressed a favorable view of the service, sharing an openness to being screened more regularly (75%) and a desire to have screenings performed at Western Maine Primary Care going forward (81%).

Discussion: Patients were generally favorable about their experience with the new DR screening technology. Providers indicated challenges due to the limited availability of trained medical assistant photographers during the initial implementation of DR screening, as well as timing issues in coordinating screening with regular office appointments.

Conclusions: This study supports further investigation of this technology in primary care, particularly in areas with challenges to care access. The potential benefits of this innovative tool in caring for people with diabetes includes improving access to retinopathy screenings and supporting wider detection of vision-threatening retinopathy.

农村初级保健环境中糖尿病视网膜病变人工智能筛查技术的患者和提供者体验
引言:用于解释糖尿病视网膜病变(DR)图像的自主人工智能的发展允许在初级保健环境中进行护理点测试。这项研究描述了在缅因州挪威的缅因州西部初级保健中心实施人工智能DR筛查技术EyeArt期间,患者和提供者对该技术的体验和看法。方法:这项非随机、单中心、前瞻性观察性研究调查了102名患者和13名初级保健提供者对新筛查干预的体验。结果:所有接受调查的提供者都认为,新的筛查工具将提高获得率和年度筛查率。一些提供者还发现了将该工具纳入初级保健就诊的最初挑战(31%)。患者对这项服务表示赞同,他们对更定期地接受筛查持开放态度(75%),并希望在缅因州西部初级保健中心进行筛查(81%)。讨论:患者普遍对他们使用新DR筛查技术的经验表示满意。供应商表示,在DR筛查的最初实施过程中,由于训练有素的医疗助理摄影师的可用性有限,以及在协调筛查与定期办公室预约方面的时间问题,因此存在挑战。结论:这项研究支持在初级保健中进一步研究这项技术,特别是在护理机会面临挑战的地区。这种创新工具在照顾糖尿病患者方面的潜在好处包括改善视网膜病变筛查的机会,并支持更广泛地检测威胁视力的视网膜病变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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