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

Author:

Paydarfar Daniel A.12ORCID,Holodinsky Jessalyn K.3ORCID,Abbas Huda4ORCID,Field Thalia S.5,Zhou Lily W.56ORCID,Kamal Noreen173ORCID

Affiliation:

1. Department of Industrial Engineering (D.A.P., N.K.), Dalhousie University, Halifax, NS, Canada.

2. Department of Statistics, University of Washington, Seattle (D.A.P.).

3. Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine (J.K.H., N.K.), University of Calgary, AB, Canada.

4. Department of Electrical and Computer Engineering (H.A.), University of Calgary, AB, Canada.

5. Department of Medicine (Division of Neurology), University of British Columbia, Vancouver, Canada (T.S.F., L.W.Z.).

6. Stanford Stroke Center, Stanford University, Palo Alto, CA (L.W.Z.).

7. Department of Community Health and Epidemiology (N.K.), Dalhousie University, Halifax, NS, Canada.

Abstract

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Neurology (clinical)

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