Background: Rehabilitation is an essential medical service for patients who have suffered acute stroke. Although the effectiveness of 7-days-per-week rehabilitation schedule has been studied in comparison with 5- or 6-days-per-week rehabilitation schedule, its cost-effectiveness has not been analyzed. In this research, to help formulate more cost-effective medical treatments for acute stroke patients, we analyzed the cost-effectiveness of 7-days-per-week rehabilitation for acute stroke from public health payer’s perspective, and public healthcare and long-term care payerʼs perspective in Japan. Methods: Cost-effectiveness of 7-days-per-week rehabilitation for acute stroke patients was analyzed based on the result from a previous study using a Japanese database examining the efficacy of 7-days-per-week rehabilitation. Cost utility analysis was conducted by comparing 7-days-per-week rehabilitation with 5- or 6-days-per-week rehabilitation, with its main outcome incremental cost-effectiveness ratio (ICER) calculated by dividing estimated incremental medical and long-term care costs by incremental quality-adjusted life years (QALY). The costs were estimated using the Japanese fee table and from published sources. The time horizon was 5 years, and Markov modeling was used for the analysis. Results: The ICER was $6339/QALY from public health payer’s perspective, lower than 5,000,000 Yen/QALY (approximately US$37,913), which was the willingness-to-pay used for the cost-effectiveness evaluation in Japan. The 7-day-per-week rehabilitation was dominant from public healthcare and long-term care payerʼs perspective. The result of sensitivity analysis confirmed the results. Conclusion: The results indicated that 7-days-per-week rehabilitation for acute stroke rehabilitation was likely to be cost-effective.
CITATION STYLE
Morii, Y., Abiko, K., Osanai, T., Takami, J., Tanikawa, T., Fujiwara, K., … Ogasawara, K. (2023). Cost-effectiveness of seven-days-per-week rehabilitation schedule for acute stroke patients. Cost Effectiveness and Resource Allocation, 21(1). https://doi.org/10.1186/s12962-023-00421-3
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