Abstract / Summary
Introduction Artificial intelligence-based imaging can support acute stroke treatment decisions, yet cost-effectiveness evidence spanning intravenous thrombolysis and mechanical thrombectomy pathways is limited. We evaluated cost-effectiveness of Brainomix 360 Stroke across National Health Service hospitals in England. Patients and Methods We developed a decision-analytic model from the National Health Service and personal social services perspective, combining a decision tree for acute stroke pathways with a long-term Markov model based on the modified Rankin Scale. The cohort comprised all acute ischaemic stroke admissions in England in one year (year = 2023, n=81,565 patients). Brainomix 360 Stroke was modelled as increasing the probability that eligible patients receive reperfusion therapy, based on a five-year real-world evaluation across 26 hospitals. Costs and quality-adjusted life years were discounted at 3.5% per year, with incremental net monetary benefit calculated at £20,000 per quality-adjusted life year. Results Brainomix 360 Stroke increased the number of patients receiving intravenous thrombolysis 8% and mechanical thrombectomy by 44%. The intervention was dominant, generating almost £4 million in cost savings and over 1,700 additional quality-adjusted life years, yielding an incremental net monetary benefit of over £38 million. Per AIS patient, this equates to £49 in cost savings and 0.021 additional quality-adjusted life years. Probabilistic sensitivity analysis indicated a 98.9% probability of cost-effectiveness at £20,000 per quality-adjusted life year. Results were robust across sensitivity and scenario analyses, though most sensitive to cohort age, long-term cost assumptions and treatment eligibility parameters. Conclusion Implementing artificial intelligence-assisted stroke imaging is highly likely to be cost-effective, driven by improved access to reperfusion therapies and better long-term functional outcomes.