The impact of artificial intelligence-supported store-and-forward teledermatology on equity and conditions for its widespeard introduction in Hungary

Abstract

Store-and-forward (SAF) teledermatology, also known as asynchronous teledermatology, allows the provision of dermatological care in cases where access to personal care is limited by time or space, which is particularly prevalent in socially or spatially disadvantaged communities with a low population density. The cost-effectiveness of teledermatology has been demonstrated in the literature in many care settings, however the use of artificial intelligence (AI) can further increase the effectiveness of care, by reducing the costs associated with care and using the remaining resources for service provision for additional patients. The present study is based on the analysis of a dataset with more than 8,000 entries, and it shows that the provision of care in low population territories has a significant impact on the principle of health equity, as 73.26% of the cases originate from territories with less than 5,000 inhabitants. Furthermore, AI-supported teledermatology is able to provide remote symptomatic care in nearly 75% of cases, therefore it can also be used for screening of patients requiring face-to-face care. The remaining resources can be used for the analysis of additional cases, covering up to the entire Hungarian population, and furtherly increasing the fulfilment of the health equity principle. Equity is a matter for policy makers, and the widespread use of AI-supported SAF teledermatology, even more, its nationwide expansion depends on the policy decision makers’ views. Nonetheless, based on the current research, the nationwide expansion is proposed.