Population impact and cost-effectiveness of artificial intelligence-based diabetic retinopathy screening in people living with diabetes in Australia: a cost effectiveness analysis.

Background: We aimed to evaluate the cost-effectiveness of an artificial intelligence-(AI) based diabetic retinopathy (DR) screening system in the primary care setting for both non-Indigenous and Indigenous people living with diabetes in Australia. Methods: We performed a cost-effectiveness analysis between January 01, 2022 and August 01, 2023. A decision-analytic Markov model was constructed to simulate DR progression in a population of 1,197,818 non-Indigenous and 65,160 Indigenous Australians living with diabetes aged ≥20 years over 40 years. From a healthcare provider's perspective, we compared current practice to three primary care AI-based screening scenarios-(A) substitution of current manual grading, (B) scaling up to patient acceptance level, and (C) achieving universal screening. Study results were presented as incremental cost-effectiveness ratio (ICER), benefit-cost ratio (BCR), and net monetary benefits (NMB). A Willingness-to-pay (WTP) threshold of AU$50,000 per quality-adjusted life year (QALY) and a discount rate of 3.5% were adopted in this study. Findings: With the status quo, the non-Indigenous diabetic population was projected to develop 96,269 blindness cases, resulting in AU$13,039.6 m spending on DR screening and treatment during 2020-2060. In comparison, all three intervention scenarios were effective and cost-saving. In particular, if a universal screening program was to be implemented (Scenario C), it would prevent 38,347 blindness cases, gain 172,090 QALYs and save AU$595.8 m, leading to a BCR of 3.96 and NMB of AU$9,200 m. Similar findings were also reported in the Indigenous population. With the status quo, 3,396 Indigenous individuals would develop blindness, which would cost the health system AU$796.0 m during 2020-2060. All three intervention scenarios were cost-saving for the Indigenous population. Notably, universal AI-based DR screening (Scenario C) would prevent 1,211 blindness cases and gain 9,800 QALYs in the Indigenous population, leading to a saving of AU$19.2 m with a BCR of 1.62 and NMB of AU$509 m. Interpretation: Our findings suggest that implementing AI-based DR screening in primary care is highly effective and cost-saving in both Indigenous and non-Indigenous populations. Funding: This project received grant funding from the Australian Government: the National Critical Research Infrastructure Initiative, Medical Research Future Fund (MRFAI00035) and the NHMRC Investigator Grant (APP1175405). The contents of the published material are solely the responsibility of the Administering Institution, a participating institution or individual authors and do not reflect the views of the NHMRC. This work was supported by the Global STEM Professorship Scheme (P0046113), the Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075). The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian State Government. W.H. is supported by the Melbourne Research Scholarship established by the University of Melbourne. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Inequity in Access: Cataract Surgery Throughput of Chinese Ophthalmologists from the China National Eye Care Capacity and Resource Survey.

Purpose: To investigate the distribution of cataract surgery performed by ophthalmologists in China.Methods: A cross-sectional study was designed to investigate nationwide ophthalmological resources and capacity for cataract surgery in China⁠-The 2014 China National Eye Care Capacity and Resource Survey. Data analyzed in this report included regional distribution, urban-rural comparison, levels and types of medical institutions, and cataract surgery types and volume per surgeon. In China, only ophthalmologists at or above the level of attending are eligible to perform cataract surgery independently, so the ability of cataract surgery for ophthalmologists at or above the level of attending is analyzed in the current study. Descriptive statistics were used.Results: 36,333 ophthalmologists were included in this survey, which is an average of 1.33 ophthalmologists to every 50,000 population. Of the surgeons in this survey, 23,412 (50.22%) were attending or more senior ophthalmologists and were mainly distributed in eastern urban areas. Annual average cataract surgeries per ophthalmologist in China were 259 in 2017, less than 300 cases.Conclusion: The average number of ophthalmologists per population in China has achieved the goal of WHO's Vision 2020; however, these surgeons are concentrated in urban areas. Further, the ability of cataract surgery among ophthalmologists is unbalanced. The annual average cataract surgeries performed by ophthalmologists are insufficient, which is an important factor resulting in the current situation in China that ophthalmic service capacity has not met the requirements for eliminating cataract blindness.