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Optimized density and locations of stroke centers for improved cost effectiveness of mechanical thrombectomy in patients with acute ischemic stroke
- Publication Year :
- 2024
-
Abstract
- Background: Despite the proven cost effectiveness of mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) due to large vessel occlusion, treatment within 6 hours from symptom onset remains inaccessible for many patients. We aimed to find the optimal number and location of treatment facilities with respect to the cost effectiveness of MT in patients with AIS, first by the most cost effective implementation of comprehensive stroke centers (CSCs), and second by the most cost effective addition of complementary thrombectomy capable stroke centers (TSCs). Methods: This study was based on nationwide observational data comprising 18 793 patients with suspected AIS potentially eligible for treatment with MT. The most cost effective solutions were attained by solving the p median facility location-allocation problem with the objective function of maximizing the incremental net monetary benefit (INMB) of MT compared with no MT in patients with AIS. Deterministic sensitivity analysis (DSA) was used as the basis of the results analysis. Results: The implementation strategy with seven CSCs produced the highest annual INMB per patient of all possible solutions in the base case scenario. The most cost effective implementation strategy of the extended scenario comprised seven CSCs and four TSCs. DSA revealed sensitivity to variability in MT rate and the maximum willingness to pay per quality adjusted life year gained. Conclusion: The combination of optimization modeling and cost effectiveness analysis provides a powerful tool for configuring the extent and locations of CSCs (and TSCs). The most cost effective implementation of CSCs in Sweden entails 24/7 MT services at all seven university hospitals.
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1399553031
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.1136.jnis-2023-020299