HCI for ophthalmology: Tele-ophthalmology-enabled and AI-ready referral between community optometry and hospital-based eye clinics for retinal disease

眼科人机交互：在社区验光和医院眼科诊所之间进行视网膜疾病的远程眼科支持和人工智能转诊

• 批准号: 2412706
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2412706
• 关键词: HCI; ophthalmology; Tele; enabled; AI

Brief description of the context of the research including potential impact Hospital eye clinics receive a very large number of referrals for patients who had an eye check-up at a high street optometrist. Of those a significant proportion relate to problems with the retina. The best way to detect problems of the retina is by doing a quick, non-invasive scan called Optical Coherence Tomography (OCT). Increasingly, high street opticians are equipped with this technology, but there is a shortage of trained staff for interpreting these scans. The result can be a 'deluge' of referrals that overwhelm hospital eye clinics and delay access to care for patients that do require treatment. Recently, revolutionising technology based on Artificial Intelligence and tele-ophthalmology has been developed that can read OCT scans in an automated way and/or by a specialist and offer advice on whether a referral to hospital clinics is needed and how urgently. This research project aims to investigate the facilitators and barriers to implementing the AI and tele-ophthalmology platform at scale. The project will involve a number of high street optometry practices with OCT that refer patients to hospital based clinics, as well as two hospital based clinics. This project should enable the smooth adoption of novel interventions for triaging referrals between primary and secondary ophthalmology at scale. Aims and Objectives The specific objectives are to: review relevant literature on AI in healthcare, ophthalmology referral, and related topics; conduct studies to identify factors at different levels that affect the implementation of novel interventions; and propose best practice in the design of technology and workflows to facilitate the integration of novel technologies in routine ophthalmology practice. Novelty of Research Methodology The research methodology will adapt established techniques from HCI and Human Factors to address the specific needs of the work contexts (primary and secondary ophthalmology care), take into account the perceptions, expectations and experiences of patients as well as clinicians, and develop best practices in "explainable AI" interfaces as appropriate to the context. Alignment to EPSRC's strategies and research areas The project particularly addresses the EPSRC Health Technologies strategy of accelerating the translation of EPSRC research to healthcare applications, with a particular focus on AI-enabled healthcare. Any companies or collaborators involved The project is in collaboration with the Moorfields BRC, and will involve Moorfields Eye Hospital and referring primary care ophthalmology practices.

研究背景的简要描述，包括潜在的影响医院眼科诊所收到了大量的转诊病人谁有一个高街验光师眼科检查。其中很大一部分与视网膜问题有关。检测视网膜问题的最佳方法是进行快速、非侵入性的扫描，称为光学相干断层扫描（OCT）。越来越多的高街眼镜商配备了这项技术，但缺乏训练有素的工作人员来解释这些扫描。其结果可能是转诊的“洪水”，淹没了医院的眼科诊所，并推迟了确实需要治疗的患者获得护理的机会。最近，基于人工智能和远程眼科学的革命性技术已经开发出来，可以自动和/或由专家读取OCT扫描，并就是否需要转诊到医院诊所以及有多紧急提供建议。该研究项目旨在调查大规模实施人工智能和远程眼科平台的促进因素和障碍。该项目将涉及与OCT合作的一些商业街验光实践，这些实践将患者转介到医院诊所以及两家医院诊所。该项目应能够顺利采用新的干预措施，在初级和二级眼科之间进行大规模的分诊转诊。目的和目标具体目标是：回顾医疗保健、眼科转诊和相关主题中人工智能的相关文献;进行研究，以确定影响新干预措施实施的不同层面的因素;并提出技术和工作流程设计的最佳实践，以促进新技术在常规眼科实践中的整合。研究方法的新奇研究方法将采用HCI和人为因素的既定技术，以满足工作环境（初级和二级眼科护理）的特定需求，考虑患者和临床医生的感知，期望和经验，并根据上下文开发“可解释的AI”界面的最佳实践。与EPSRC的战略和研究领域保持一致该项目特别关注EPSRC健康技术战略，即加速将EPSRC研究转化为医疗保健应用，特别关注人工智能医疗保健。任何公司或合作者参与该项目是在与穆尔菲尔德BRC合作，并将涉及穆尔菲尔德眼科医院和转诊初级保健眼科实践。