2021
DOI: 10.1186/s12889-021-11097-w
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Health care cost and benefits of artificial intelligence-assisted population-based glaucoma screening for the elderly in remote areas of China: a cost-offset analysis

Abstract: Background Population-based screening was essential for glaucoma management. Although various studies have investigated the cost-effectiveness of glaucoma screening, policymakers facing with uncontrollably growing total health expenses were deeply concerned about the potential financial consequences of glaucoma screening. This present study was aimed to explore the impact of glaucoma screening with artificial intelligence (AI) automated diagnosis from a budgetary standpoint in Changjiang county… Show more

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Cited by 18 publications
(17 citation statements)
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“…The health examination center screening model provides an opportunity to detect these asymptomatic individuals and prevent severe visual impairment by intense follow-up and prophylactic management when necessary. AS-OCT is quick and non-invasive, and combined with a semi-quantitative assessment as described here, can be readily performed by non-specialists after modest training, or by artificial intelligence software in the near future [ 12 , 13 ].…”
Section: Discussionmentioning
confidence: 99%
“…The health examination center screening model provides an opportunity to detect these asymptomatic individuals and prevent severe visual impairment by intense follow-up and prophylactic management when necessary. AS-OCT is quick and non-invasive, and combined with a semi-quantitative assessment as described here, can be readily performed by non-specialists after modest training, or by artificial intelligence software in the near future [ 12 , 13 ].…”
Section: Discussionmentioning
confidence: 99%
“…In an analysis of AI-glaucoma screening in rural China, the authors found an excess cost of such implementation that could not be offset by the reduction in disease progression. 37 Potential reasons why an AI model for glaucoma diagnosis might not show accurate results in clinical practice include: Lack of diversity in training data: AI models rely on large datasets to learn how to accurately classify images. If the training dataset is biased or lacks diversity, the AI model may not perform as well on new data.…”
Section: Clinical Settings Implementationmentioning
confidence: 99%
“…Xiao et al [34] conducted a cost-offset analysis on screening for primary angle closure (PAC) using artificial intelligence in a Chinese population compared to no screening [34]. In a Markov model-simulated screening for 15 years, the screening was able to reduce the number of PAC, PAC glaucoma, and blindness by 8.8, 16.7, and 33.3%, respectively.…”
Section: Recent Economic Evaluations Of Artificial Intelligence In Op...mentioning
confidence: 99%