Date of Award
3-2021
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Operational Sciences
First Advisor
Phillip R. Jenkins, PhD
Abstract
In a deployed environment, evacuation requests of injured personnel are serviced by multiple forms of evacuation including medical evacuation (MEDEVAC) and casualty evacuation (CASEVAC). This thesis focuses on the optimal dispatching policy for MEDEVAC units when triage classification errors and blood transfusion kits are considered. A discounted, infinite-horizon Markov decision process (MDP) model is formulated to analyze the MEDEVAC dispatching problem and determine the optimal policy based on the status of the MEDEVAC units in the system, the priority level of incoming requests, and the locations from which requests originate. A notional, representational scenario based in Azerbaijan is utilized to compare the optimal policy against the currently practiced policy of always dispatching the nearest available MEDEVAC unit. Multiple excursions are analyzed to understand the impact of altering problem parameters, including the misclassification rate, number of aircraft equipped with blood transfusion kits, arrival rate of incoming service requests, aircraft speed, and types of triage classification errors. Results reveal that with the application of the optimal policy found by the MDP model the performance of the MEDEVAC dispatching system improves, wherein performance is measured in terms of casualty survivability. Additionally, the inclusion of blood transfusion kits on board aircraft increase MEDEVAC system performance. This analysis is of interest to the military medical planning community and may inform the development of tactics, techniques, and procedures of future dispatching policies for MEDEVAC systems.
AFIT Designator
AFIT-ENS-MS-21-M-163
DTIC Accession Number
AD1131069
Recommended Citation
Graves, Emily S., "The Impact of Triage Classification Errors on Military Medical Evacuation System Performance" (2021). Theses and Dissertations. 4926.
https://scholar.afit.edu/etd/4926