Department of Ophthalmology, Rajavithi Hospital, College of Medicine, Rangsit University.
Department of Biochemistry, Chulalongkorn University, Bangkok, Thailand.
Curr Opin Ophthalmol. 2023 Sep 1;34(5):449-458. doi: 10.1097/ICU.0000000000000987. Epub 2023 Jul 17.
Health economic evaluation (HEE) is essential for assessing value of health interventions, including artificial intelligence. Recent approaches, current challenges, and future directions of HEE of artificial intelligence in ophthalmology are reviewed.
Majority of recent HEEs of artificial intelligence in ophthalmology were for diabetic retinopathy screening. Two models, one conducted in the rural USA (5-year period) and another in China (35-year period), found artificial intelligence to be more cost-effective than without screening for diabetic retinopathy. Two additional models, which compared artificial intelligence with human screeners in Brazil and Thailand for the lifetime of patients, found artificial intelligence to be more expensive from a healthcare system perspective. In the Thailand analysis, however, artificial intelligence was less expensive when opportunity loss from blindness was included. An artificial intelligence model for screening retinopathy of prematurity was cost-effective in the USA. A model for screening age-related macular degeneration in Japan and another for primary angle close in China did not find artificial intelligence to be cost-effective, compared with no screening. The costs of artificial intelligence varied widely in these models.
Like other medical fields, there is limited evidence in assessing the value of artificial intelligence in ophthalmology and more appropriate HEE models are needed.
健康经济评估(HEE)对于评估健康干预措施的价值至关重要,包括人工智能。本文综述了眼科人工智能 HEE 的最新方法、当前挑战和未来方向。
最近眼科人工智能 HEE 的大部分研究都针对糖尿病视网膜病变筛查。有两个模型,一个在美国农村(5 年期间)进行,另一个在中国(35 年期间)进行,发现人工智能筛查比不筛查糖尿病视网膜病变更具成本效益。另外两个模型在巴西和泰国比较了人工智能和人工筛查者对患者终身的影响,发现从医疗保健系统的角度来看,人工智能更昂贵。然而,在泰国的分析中,包括失明机会损失后,人工智能的成本更低。美国的早产儿视网膜病变筛查人工智能模型具有成本效益。日本的年龄相关性黄斑变性筛查模型和中国的原发性闭角型青光眼筛查模型都没有发现人工智能比不筛查更具成本效益。这些模型中人工智能的成本差异很大。
与其他医学领域一样,在评估眼科人工智能的价值方面,证据有限,需要更合适的 HEE 模型。