Abstract

Background: Mobile stroke units (MSUs) are ambulances with brain scanning capability and specialised staff. In Australia, the first MSU was launched in Melbourne, November 2017. The Melbourne MSU has two paramedics, a radiographer, a stroke neurologist and a stroke nurse specialist (5 days per week/ 8am-6pm). The MSU is co-dispatched with a standard ambulance to a patient with suspected stroke within metropolitan Melbourne (20km radius). In cases where the standard ambulance assessed the patient first and stroke is eliminated, the MSU is contacted to ‘stand-down’. The cost-effectiveness of this type of ‘pre-hospital’ service remains unclear. Methods: The potential cost-effectiveness of the Melbourne MSU was estimated for 2018 following the pilot period (Nov-Dec 2017). A simulation model was developed for 2018 with a) program costs: operational/finance reports, self-report program leads/senior operational staff; b) clinical processes: MSU medical records/historical data; and c) health effects of treatment taken from the literature for reperfusion therapies to patients with ischaemic stroke (i.e. benefits: additional patients treated/faster treatment). Primary outcome: incremental cost per disability adjusted life year (DALY) avoided. The comparison was to standard pre-hospital and emergency department historical ‘usual’ care. Probabilistic, multivariable uncertainty analyses with Monte Carlo (10,000) simulations and sensitivity analyses were conducted. Results: In 2018, the Melbourne MSU was dispatched for 1244 suspected strokes (200 operational days). Overall, 46.9 DALYs were potentially avoided (95% uncertainty interval 33.02, 82.15 DALYs). The net cost of operating the MSU was ~$US 980,000, and the incremental cost/DALY avoided was $US 20,681 compared to standard care (95% uncertainty interval $US 14,167, $US 32,214). Conclusion: The Melbourne MSU is a cost-effective model for stroke care based on a standard willingness-to-pay cost-effectiveness threshold (<$US 50,000 per DALY avoided). Future adaptations to the operational model may improve the cost-effectiveness of this service.

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