Transportation for Patients with Stroke in Need of Mechanical Thrombectomy: A Simulation-Based Study in Hyogo Prefecture, Japan.

Objective: This study aimed to simulate patient transportation to a mechanical thrombectomy (MT)-capable hospital within 60 minutes, taking into account patient volume (demand side of healthcare) and hospital capacity to accept patients (supply side of healthcare).

Methods: Simulations were conducted in Hyogo Prefecture, Japan. The estimates of the annual number of patients with stroke eligible for MT in 2020 were based on the incidence of stroke by age group and the percentage of patients with stroke indicated for MT in existing publications. Patients were then randomly placed on a 1 km² mesh map. The patients were randomly generated 100 times using R software (version 4.1.2; R Foundation for Statistical Computing, Vienna, Austria). Hospitals were selected based on 2 criteria: (1) actual provision patterns (39 hospitals) and (2) consolidated patterns (12 hospitals). Simulations were performed using ArcGIS Pro (version 10.8; Esri, Redlands, CA, USA) and Network Analyst extension (Esri) in 3 cases: (1) number of patients estimated from the population in 2020 transported to hospitals that provided MT, (2) number of patients estimated based on the 2020 population transported to selected hospitals in the case of consolidation, and (3) number of patients estimated based on 2040's projected population and transportation to the selected hospitals.

Results: In Case 1, the estimated annual number of patients undergoing MT in 2020 was 976. The average number of patients undergoing MT and transported was 961, indicating that 98% (961/976) of the total generated patients could be transported within 60 min. In Case 2, the average number of patients undergoing MT and transported was 940, indicating that 96.3% (940/976) of the total patients could be transported within 60 min. In Case 3, the average number of patients undergoing MT and transported was 1184, showing that 95.1% (1184/1244) of the total generated patients could be transported within 60 min. A few patients in rural areas and remote islands required longer transport times.

Conclusion: The simulations showed that patient estimates from the incidence of cerebral infarction by age group and the percentage of patients with stroke indicated for MT were similar to the actual values. The simulation was closed to reality when both the supply and demand sides of healthcare were considered. Thus, this simulation study informs future healthcare policy by demonstrating the geographic distribution of human and capital resources and potential cost reduction through consolidation, taking into account demographic changes.