Citation

Ahmed S, Lieberthal RD, Hechtman DM, Rayson LA, Amirault DR, Haas S. AMIA Annu. Symp. Proc. 2022; 2022: 102-111.

Copyright

(Copyright © 2022, American Medical Informatics Association)

DOI

unavailable

PMID

35854752

PMCID

PMC9285155

Abstract

Air ambulances can provide more rapid access to medical care than ground ambulances for rural, underserved, and hard to reach populations. However, the existing allocation of ambulance bases across metropolitan and rural areas is driven primarily by individual operator decisions rather than a health outcomes-based approach. This paper describes a framework for optimizing air ambulance services delivery based on healthcare demand and locational constraints to other modes of transportation. In particular, the paper highlights the need for combining data and how data can be used to identify locations where air ambulance services could be located based on impact. We utilize an information systems approach, applying linear programing models to identify the optimal base locations at the state and regional level. Two data driven use cases for the state of Virginia and New England demonstrate the application of our approach and underscore the importance of data interoperability in health transportation planning.

Language: en

Keywords

Humans; Information Systems; Rural Population; *Air Ambulances; *Emergency Medical Services; Ambulances