Economic evaluation of combined population-based screening for multiple blindness-causing eye diseases in China: a cost-effectiveness analysis

AI-based teleophthalmology has the potential to drive not only delivery enhancements but also notable cost savings and improvements to the health system. However, the implementation of AI in China might pose concerns and challenges. First, one of the crucial factors in successful implementation is the involvement and collaboration of various stakeholders. Although eye doctors are the core of eye health services, the most engaged group comprises optometrists, general practitioners, and nurses. Therefore, training and management of these practitioners are essential for the success of teleophthalmology services. Second, digital literacy and previous experience working with computers could affect the acceptance of technology-based solutions and thus the satisfaction of users or patients in older populations, especially in rural areas. Another key factor in the wide adoption of AI is its economic viability. Currently, in China, the most common purchase plans for using AI services include one-time purchases, capital leasing plans, and non-capital leasing plans with a minimum number of yearly examinations for research. From the provider perspective, a deficit could still exist, notwithstanding the purchase plan, and a fixed charge per patient and reimbursement would be needed for a break-even marginal revenue. Further benefits will inevitably come from piggybacking multidisease eye screening onto outreach screening programmes for non-communicable diseases (eg, diabetes and hypertension), which will enhance the value of data use for the health-care system and might be the most cost-effective strategy. Finally, policy makers and health sector specifications must consider processes for the continuous updating of AI policies, guidelines, regulations, and health systems to adapt flexibly and efficiently to AI innovations and manage monitoring and risk management practices. Despite the great interest in AI-based teleophthalmology, we advocate following Confucian doctrine—that is, to learn extensively, inquire thoroughly, ponder prudently, discriminate clearly, and practise devotedly—to ensure that affordable, high-quality, equitable, people-centred eye care can be delivered.

Our study has several limitations. First, our analysis was not based on prospective data, and we used some parameters from non-Chinese studies or expert advice. In reality, individuals who frequent primary care services are likely to be patients with chronic systemic disease, such as hypertension and diabetes, which might result in a cohort with greater prevalence of diabetes retinopathy or cataract, and this might alter the economic analysis. However, the model was shown to be robust and insensitive to a wide fluctuation of parameters by extensive sensitivity analyses. Second, because the data incorporated were all Chinese based, it is not clear how relevant our economic results are to other countries with different health settings and medical costs. Third, only five leading common blindness-causing diseases were included in this study. Moreover, given the complexity of the model, we considered one of the most common situations in clinical practice, that patients might have cataracts combined with one of the other four diseases, but we assumed that these four diseases would not all present simultaneously in one person. Indeed, other eye diseases could also be screened for under the proposed setting, and such a screening could even be useful for identifying individuals at risk of cardiovascular disease or cognitive impairment. However, these diseases were not considered in this analysis. Screening for more conditions might not show a linear relationship with cost-effectiveness, so the average number of conditions picked up during a single screening and which diseases should be screened for in order to be most cost-effective could be evaluated in future studies. In addition, the effect on cost-effectiveness of sex, age group, cardiovascular risk factors, and economic level and medical resources in different regions should be considered. Fourth, the costs of AI-based telehealth care have not yet been standardised or determined clearly. Furthermore, the increasing amounts of patient data might cause differences in maintenance costs, and an extra work burden might also be generated by false positives and poor-quality images, which are potential issues in the long-term use of AI.

In conclusion, our study shows that combined screening for multiple blindness-causing diseases is likely to be cost-effective in China. We believe that AI coupled with telemedicine and mobile health would produce social and economic benefits in LMICs by expanding the coverage of medical resources and improving the quality, sustainability, and equity of eye health services.