Is prehospital treatment of acute stroke too expensive? An economic evaluation based on the first trial

Background: Recently, a strategy for treating stroke directly at the emergency site was developed. It was based on the use of an ambulance equipped with a scanner, a point-of-care laboratory, and telemedicine capabilities (Mobile Stroke Unit). Despite demonstrating a marked reduction in the delay to thrombolysis, this strategy is criticized because of potentially unacceptable costs.

Methods: We related the incremental direct costs of prehospital stroke treatment based on data of the first trial on this concept to one year direct cost savings taken from published research results. Key parameters were configuration of emergency medical service personnel, operating distance, and population density. Model parameters were varied to cover 5 different relevant emergency medical service scenarios. Additionally, the effects of operating distance and population density on benefit-cost ratios were analyzed.

Results: Benefits of the concept of prehospital stroke treatment outweighed its costs with a benefit-cost ratio of 1.96 in the baseline experimental setting. The benefit-cost ratio markedly increased with the reduction of the staff and with higher population density. Maximum benefit-cost ratios between 2.16 and 6.85 were identified at optimum operating distances in a range between 43.01 and 64.88 km (26.88 and 40.55 miles). Our model implies that in different scenarios the Mobile Stroke Unit strategy is cost-efficient starting from an operating distance of 15.98 km (9.99 miles) or from a population density of 79 inhabitants per km2 (202 inhabitants per square mile).

Conclusion: This study indicates that based on a one-year benefit-cost analysis that prehospital treatment of acute stroke is highly cost-effective across a wide range of possible scenarios. It is the highest when the staff size of the Mobile Stroke Unit can be reduced, for example, by the use of telemedical support from hospital experts. Although efficiency is positively related to population density, benefit-cost ratios can be greater than 1 even in rural settings.