The Impact of Threat Levels at the Casualty Collection Point on Military Medical Evacuation System Performance

Abstract

One of the primary duties of the Military Health System is to provide effective and efficient medical evacuation (MEDEVAC) to injured battle fixC;eld personnel. To accomplish this, military medical planners seek to develop high-quality dispatching policies that dictate how deployed MEDEVAC assets are utilized throughout combat operations. This thesis seeks to determine dispatching policies that improve the performance of the MEDEVAC system. A discounted, infixC;nite-horizon continuous-time Markov decision process (MDP) model is developed to examine the MEDEVAC dispatching problem. The model incorporates problem features that are not considered under the current dispatching policy (e.g., myopic policy), which tasks the closest-available MEDEVAC unit to service an incoming request. More specificxC;ally, the MDP model explicitly accounts for admission control, precedence level of calls, different asset types (e.g., Army versus Air Force helicopters), and threat level at casualty collection points. An approximate dynamic programming (ADP) algorithm is developed within an approximate policy iteration algorithmic framework that leverages kernel regression to approximate the state value function. The ADP algorithm is used to develop high-quality solutions for large scale problems that cannot be solved to optimality due to the curse of dimensionality. We develop a notional scenario based on combat operations in southern Afghanistan to investigate model performance, which is measured in terms of casualty survivability. The results indicate that significant improvement in MEDEVAC system performance can be obtained by utilizing either the MDP or ADP generated policies. These results inform the development and implementation of tactics, techniques and procedures for the military medical planning community.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 25, 2021
Accession Number
AD1133454

Entities

People

  • Nathaniel C. Dennie

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Combat Casualty Care
  • Combat Operations
  • Dynamic Programming
  • Evacuation
  • Health Services
  • Medical Evacuation
  • Medical Personnel
  • Military Medicine
  • Operations Research
  • Systems Engineering
  • Therapy
  • United States
  • United States Government
  • Urban Areas
  • Warfare

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research
  • Trauma or Military Medicine