Helicopter EMS Actuarial Model

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.

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Publication Details

Journal
PubMed
Published
2026-06-09
DOI
https://doi.org/10.5281/zenodo.20601704
Citations
2
Primary Topic
Trauma and Emergency Care Studies
Type
article
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article

Helicopter EMS Actuarial Model

Robert D. Lieberthal, Sabin Ahmed, David Hechtman
2 citations
PubMed
Trauma and Emergency Care Studies
article

Helicopter EMS Actuarial Model

Robert D. Lieberthal, Sabin Ahmed, David Hechtman
article en
2 citations

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.

PubMedVol. 2022
Thomas Jefferson University (US), Mary Ann Liebert (United States) (US), Ariadne Diagnostics (United States) (US), Mitre (United States) (US), New York University (US)
Trauma and Emergency Care Studies
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Helicopter EMS Actuarial Model — Robert D. Lieberthal, Sabin Ahmed, et al. · PubMed (2026) | TGRS Research Map | TGRS