Senior military leaders and medical practitioners continuously seek new ways to improve the performance and organisation of deployed medical evacuation (MEDEVAC) systems to minimise mortality rates of combat casualties. The objective of this paper is to highlight how recent research in the fields of operations research and machine learning can be leveraged to better inform the implementation and modification of current and future MEDEVAC tactics, techniques and procedures for combat operations in a deployed environment. More specifically, this paper discusses state-of-the-art techniques that optimise the management of MEDEVAC assets prior to and during combat operations. These recent research efforts emphasise that military healthcare administrators should contribute to and extend the evolving portfolio of research that seeks to design and develop decision support systems leveraging artificial intelligence and operations research to improve MEDEVAC system performance.
- accident & emergency medicine
- trauma management
- health services administration & management
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Contributors PRJ planned the study, wrote the initial article draft and submitted the work. MJR conducted additional research and revised the article. BJL also conducted research and provided intellectual improvements to the article. In summary, PRJ, MJR and BJL each contributed substantially to the article in terms of conception, intellectual contribution, research, writing and revising.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
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Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
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