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Developing Representative Complex Casualty Cases for Modeling Healthcare System Throughput
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Introduction:
The congressionally directed NDMS Pilot Project evaluates civilian medical system readiness to manage 1,000 repatriated casualties daily over 100 days from a conventional near-peer conflict. This component simulated patient throughput in NDMS-enrolled healthcare facilities within the National Capital Region (NCR) to assess capacity and identify constraints. Researchers developed projected combat casualty cases to accurately predict healthcare resource needs, treatment phases, and patient throughput under high-volume conditions.
Methods:
Emergency Medicine physicians conducted a literature search and analysis incorporating recent US military experience and peer-reviewed medical literature to project likely injury patterns. Researchers analyzed 1,817 de identified trauma cases from GWU Hospital (2018-2022) and 989,989 cases from the National Trauma Data Bank (2016-2021) to capture similar injury profiles. A prospectively developed Combat Casualty Case Data Tool tracked demographics, ICD-10 codes, medical specialty requirements, bed types, and timelines for sequential treatment phases. Formatted in Excel, the tool enables simulation operators to adjust casualty types and prevalence, examining impacts on resource availability and patient flow. Each case includes an “Arrival Severity Designation” for triage priority, while patient journey maps outline “Optimal Patient Journey Time” and resource needs.
Results:
This approach produced 204 casualty cases, representing a distribution of anticipated injury types and resource demands. This case collection promotes realistic modeling to assess NDMS capacity, with structured data supporting precise tracking through patient care phases from airfield arrival and case distribution, care throughput, recovery, and indicated rehabilitation until NDMS discharge.
Conclusion:
The detailed casualty cases are essential for understanding and planning the NDMS surge capacity that respects clinical standards. By capturing phase-by-phase patient care needs that are matched to healthcare facility capabilities, this model supports accurate healthcare resource assessment and guides future NDMS projects on patient throughput and resource allocation. Future versions could incorporate more detailed rehabilitation and residential care needs for more accurate end-to-end healthcare throughput projections.
Cambridge University Press (CUP)
Title: Developing Representative Complex Casualty Cases for Modeling Healthcare System Throughput
Description:
Introduction:
The congressionally directed NDMS Pilot Project evaluates civilian medical system readiness to manage 1,000 repatriated casualties daily over 100 days from a conventional near-peer conflict.
This component simulated patient throughput in NDMS-enrolled healthcare facilities within the National Capital Region (NCR) to assess capacity and identify constraints.
Researchers developed projected combat casualty cases to accurately predict healthcare resource needs, treatment phases, and patient throughput under high-volume conditions.
Methods:
Emergency Medicine physicians conducted a literature search and analysis incorporating recent US military experience and peer-reviewed medical literature to project likely injury patterns.
Researchers analyzed 1,817 de identified trauma cases from GWU Hospital (2018-2022) and 989,989 cases from the National Trauma Data Bank (2016-2021) to capture similar injury profiles.
A prospectively developed Combat Casualty Case Data Tool tracked demographics, ICD-10 codes, medical specialty requirements, bed types, and timelines for sequential treatment phases.
Formatted in Excel, the tool enables simulation operators to adjust casualty types and prevalence, examining impacts on resource availability and patient flow.
Each case includes an “Arrival Severity Designation” for triage priority, while patient journey maps outline “Optimal Patient Journey Time” and resource needs.
Results:
This approach produced 204 casualty cases, representing a distribution of anticipated injury types and resource demands.
This case collection promotes realistic modeling to assess NDMS capacity, with structured data supporting precise tracking through patient care phases from airfield arrival and case distribution, care throughput, recovery, and indicated rehabilitation until NDMS discharge.
Conclusion:
The detailed casualty cases are essential for understanding and planning the NDMS surge capacity that respects clinical standards.
By capturing phase-by-phase patient care needs that are matched to healthcare facility capabilities, this model supports accurate healthcare resource assessment and guides future NDMS projects on patient throughput and resource allocation.
Future versions could incorporate more detailed rehabilitation and residential care needs for more accurate end-to-end healthcare throughput projections.
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