Fisher, D., & Ferguson, J. P., & Patel, E. N., & Ahluwalia, G., & Barbera, J. A., & Santos, J. R. (2024, April), Optimizing the distribution of combat casualties for quality medical care: a prototype decision support tool for patient-healthcare facility matching  Paper presented at ASEE Mid-Atlantic Section Spring Conference, George Washington University, District of Columbia. 10.18260/1-2--45736

\bibitem{asee_peer_45736}
  Fisher, D., \& Ferguson, J. P., \& Patel, E. N., \& Ahluwalia, G., \& Barbera, J. A., \& Santos, J. R. (2024, April), \emph{Optimizing the distribution of combat casualties for quality medical care: a prototype decision support tool for patient-healthcare facility matching}
  Paper presented at ASEE Mid-Atlantic Section Spring Conference, George Washington University, District of Columbia.
  10.18260/1-2--45736

Daniel Fisher, James P Ferguson, Esha Niraj Patel, Gujri Ahluwalia, Joseph Anthony Barbera M.D., and Joost R. Santos.  "Optimizing the distribution of combat casualties for quality medical care: a prototype decision support tool for patient-healthcare facility matching".  ASEE Mid-Atlantic Section Spring Conference, George Washington University, District of Columbia, 2024, April.  ASEE Conferences, 2024.  https://peer.asee.org/45736 Internet.  16 Aug, 2024

\bibitem{asee_peer_45736}
  Daniel Fisher, James P Ferguson, Esha Niraj Patel, Gujri Ahluwalia, Joseph Anthony Barbera M.D., and Joost R. Santos.
  "Optimizing the distribution of combat casualties for quality medical care: a prototype decision support tool for patient-healthcare facility matching".
  \emph{ASEE Mid-Atlantic Section Spring Conference, George Washington University, District of Columbia, 2024, April}.
  ASEE Conferences, 2024.
  https://peer.asee.org/45736 Internet.  16 Aug, 2024

@INPROCEEDINGS{asee_peer_45736
author = "Daniel Fisher, James P Ferguson, Esha Niraj Patel, Gujri Ahluwalia, Joseph Anthony Barbera M.D., and Joost R. Santos"
title = "Optimizing the distribution of combat casualties for quality medical care: a prototype decision support tool for patient-healthcare facility matching"
booktitle = "ASEE Mid-Atlantic Section Spring Conference"
year = "2024"
month = "April"
address = "George Washington University, District of Columbia"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/45736}
number = {10.18260/1-2--45736}
}

TY  - CPAPER
AB  - US military personnel volunteer to risk their lives as an integral element of the United States defense system. Therefore, it is of utmost priority to ensure they have the best available medical care in times of war. During a near-peer conventional conflict (e.g., a war in which the United States does not have air superiority), combat casualties may exceed the military medical system and be returned to the United States for acute and long-term medical treatment in civilian healthcare facilities (HCFs). Currently, no comprehensive, robust guidance exists for rapid and accurate patient distribution to HCFs upon arrival at an airfield in the United States. This study focuses on developing a matching algorithm and decision support tool to aid medical experts in determining where arriving casualties at Joint Base Andrews will be sent to National Disaster Medical System (NDMS) partnering HCFs in the Washington, D.C. metropolitan area. To develop the matching algorithm, subject matter experts who have experience in emergency medicine and organizing civilian mass-casualty responses were interviewed to inform and validate the logic of the matching algorithm. The algorithm uses a patient’s movement record (PMR), a detailed data set characterizing each relevant HCF, the decision-maker’s input, and the patient’s medical needs to assign an “adequate” HCF for that patient. Factors considered are bed type availability, medical specialty availability, scarce specialty availability, travel time, roundtrip travel time, transportation vehicle availability, medical transport crew availability using an assignment matrix to determine the list of “adequate” HCFs (the HCFs that match the patient’s medical needs) while balancing the patient load across the system. Using expert-developed patient casualty cases, the developed algorithm was evaluated for accuracy. Additionally, a graphical user interface (GUI) was created for the prototype decision support tool that the decision-maker would use during casualty assignment. A second round of semi-structured interviews was completed to verify the reliability in matching and the usefulness of the GUI by potential decision-makers. This tool demonstrates a proactive and efficient approach to matching arriving combat casualties with adequate HCFs. Preliminary testing of the model indicates improvement in patient processing time, increased accuracy of facility matching, and anticipated usefulness in real-world applications. Further validation will refine the system to ensure operational success and enhance overall efficiency.

AU  - Daniel Fisher
AU  - James P Ferguson
AU  - Esha Niraj Patel
AU  - Gujri Ahluwalia
AU  - Joseph Anthony Barbera M.D.
AU  - Joost R. Santos
CY  - George Washington University, District of Columbia
DA  - 2024/04/19
PB  - ASEE Conferences
TI  - Optimizing the distribution of combat casualties for quality medical care: a prototype decision support tool for patient-healthcare facility matching
UR  - https://peer.asee.org/45736
DO  - 10.18260/1-2--45736
ER  -