Abstract
This study aimed to reform supply chain management in the field of neuroendovascular treatment. In endovascular treatment, expensive equipment such as microcatheters, coils, and stents are used once for each patient. Moreover, the surgeon learning curve is steep. As learning opportunities are rare in general facilities, treatment is often performed with the support of supervising surgeons from other hospitals. From a medicoeconomic perspective, the unnecessary inventory of treatment equipment and disposal costs due to sterilization are ultimately added to product costs. Additionally, devices are stored in small quantities at many hospitals and scattered across multiple vendor warehouses. Therefore, is difficult to quickly and accurately deliver equipment to hospitals for surgery. This study aimed to construct a system that uses artificial intelligence (AI) and telemedicine technologies to support treatment planning during neuroendovascular treatment, reduce physician workload, and improve medicoeconomics. Many treatment databases of two facilities will be used for AI analysis of device selection and surgical guidance. This information will be used to create a treatment planning support program (“AI system”) that will enable even inexperienced doctors to select appropriate devices. The telemedicine platform uses the Join mobile communication app, which has already been introduced to over 1,000 facilities in Japan and overseas. Using the app’s telemedicine system, it is now possible for senior supervising surgeons to provide remote guidance to inexperienced surgeons, thereby reducing the labor burden on doctors and providing highly medically and economically effective treatments.
