Abstract
OBJECTIVE: Air medical evacuation for residents of remote islands is expensive yet essential for addressing urgent and critical health conditions. This study aims to identify common referral reasons and quantify the economic impact of such services, with a focus on the potential benefits of implementing preventive medicine and telemedicine to improve medical care accessibility and coverage in these regions. METHODS: We conducted a retrospective analysis of adult patients who traveled from the Matsu Islands to the Taiwan mainland between January 2016 and June 2022 and divided them into two groups: Emergency Air Medical Transport (EAMT) and non-EAMT. We included both direct medical and non-medical costs, and indirect costs measured by productivity loss due to health conditions. A generalized linear model adjusted for age and gender was employed to estimate average costs per patient. RESULTS: Data were available for 423 participants, with 136 in the EAMT group and 287 in the non-medical evacuation group. The average direct costs were significantly higher in the EAMT group ($12,067, 95% confidence interval [CI] 9,592-15,181) compared to the non-EAMT group ($5,540, 95% CI 4,645-6,608). Transportation costs made up the largest portion of these direct costs, particularly for those requiring EAMT services. The most common referral reasons for EAMT were cardiovascular diseases (27.2%), followed by injuries (21.3%) and general conditions (15.4%). Across all referral reasons, the EAMT group consistently incurred higher average costs compared to the non-EAMT group, with fractures resulting in the highest costs ($21,342, 95% CI 13,794-33,019). CONCLUSION: The findings highlight the significant financial burden of medical evacuation services in remote islands, particularly for cardiovascular conditions, injuries, and fractures. These results emphasize the need for targeted preventive measures and improved healthcare access to reduce both economic impact and health risks, providing a basis for further cost-effectiveness analysis of future interventions.