Quantifying Improved Outcomes, Cost Savings, and Hospital Volume Changes From Optimized Emergency Stroke Transport.

BACKGROUND: A previously published conditional probability model optimizes prehospital emergency transport protocols for patients with suspected large-vessel occlusion by recommending the transport strategy, drip-and-ship or mothership, that results in a higher probability of an excellent outcome. In this study, we create generalized models to quantify the change in annual hospital patient volume, the expected annual increase in the number of patients with an excellent outcome, and the annual cost savings to a single-payer healthcare system resulting from these optimized transport protocols. METHODS: We calculated the expected number of patients with suspected large-vessel occlusion transported by ambulance over a 1-year period in a region of interest, using the annual stroke incidence rate and a large-vessel occlusion screening tool. Assuming transport to the closest hospital is the baseline transport policy across the region (drip-and-ship), we determined the change in annual hospital patient volume from implementing optimized transport protocols. We also calculated the resulting annual increase in the number of patients with an excellent outcome (modified Rankin Score of 0-1 at 90 days) and associated cost savings to a single-payer healthcare system. We then performed a case study applying these generalized models to the stroke system serving the Greater Vancouver and Fraser Valley Area, BC, Canada. RESULTS: In the Greater Vancouver and Fraser Valley Area, there was an annual increase of 36 patients with an excellent outcome, translating to an annual cost savings of CA$2 182 824 to the British Columbia healthcare system. We also studied how these results change depending on our assumptions of treatment times at the regional stroke centers. CONCLUSIONS: Our framework quantifies the impact of optimized emergency stroke transport protocols on hospital volume, outcomes, and cost savings to a single-payer healthcare system. When applied to a specific region of interest, these models can help inform health policies concerning emergency transport of patients with suspected large-vessel occlusion.

Optimizing Emergency Stroke Transport Strategies Using Physiological Models.

BACKGROUND AND PURPOSE: The criteria for choosing between drip and ship and mothership transport strategies in emergency stroke care is widely debated. Although existing data-driven probability models can inform transport decision-making at an epidemiological level, we propose a novel mathematical, physiologically derived framework that provides insight into how patient characteristics underlying infarct core growth influence these decisions. METHODS: We represent the physiology of time-dependent infarct core growth within an ischemic penumbra as an exponential function with consideration to rate-determining collateral blood flow. Monte Carlo methods generate distributions of infarct core volumes, which are translated to distributions of 90-day modified Rankin Scale scores. We apply the model to a stroke network that serves rural Bastrop County and urban Travis County by simulating transport strategies from thousands of potential patient pickup locations. In every pickup location, the simulation yields a distribution of outcomes corresponding to each transport strategy. A 2-sample Kolmogorov-Smirnov test and Student t test determine which transport strategy provides a significantly better probability of a good outcome for a given pickup location in each respective county (P<0.01). RESULTS: In Travis County, drip and ship provides significantly better probabilities of a good outcome in 24.0% of the pickup locations, while 59.8% favor mothership. In Bastrop County, 11.3% of the pickup locations favor drip and ship, while only 7.1% favor mothership. The remaining pickup locations in each county are not statistically significant in either direction. We also reveal how differing rates of infarct core growth, the application of bypass policies, and the use of large vessel occlusion field tests impact these results. CONCLUSIONS: Modeling stroke physiology enables the use of clinically relevant metrics for determining comparative significance between drip and ship and mothership in a given geography. This formalism can help understand and inform emergency medical service transport decision-making, as well as regional bypass policies.