美国军方必须为未来的战场建立实时战斗伤亡护理数据生态系统
Mason H Remondelli1, Jay B Baker2, Jonathan D Stallings3
1Department of Surgery, The Uniformed Services University of the Health Sciences, Bethesda, MD 20814, United States.
Military medicine
|August 26, 2025
概括
现代化军事创伤系统的大规模作战 (LSCO) 需要实时,自动数据收集. 这种转变对于优化伤亡护理,改善决策和提高未来冲突的生存能力至关重要.
科学领域:
- 军事医学
- 创伤系统
- 卫生信息学
背景情况:
- 大规模作战行动 (LSCO) 由于高伤亡量和后勤限制,对军事创伤系统构成重大挑战.
- 美国目前的军事创伤系统依赖于手动,延迟的数据记录,
- 过去在降低战场死亡率方面取得的成功凸显了数据驱动医疗性能优化的潜力.
研究的目的:
- 倡导开发一个实时的,自动化的战斗伤亡护理数据生态系统.
- 支持在各级医疗机构加强决策,资源分配,指挥和控制.
- 解决当前手动数据收集方法在高速战斗环境中的局限性.
主要方法:
- 建议未来的系统集成被动数据收集,边缘计算和人工智能 (AI).
- 强调与战术网络和作战规划工具的无整合.
- 区分实时护理和档案记录的数据.
主要成果:
- 目前的现代化努力 (例如BATDOK,OMDS,SIMON) 是有前途的,但仍然依赖于人类投入.
- 拟议的系统旨在进行临床优化和创伤系统学习, 而不会给提供者带来负担.
- 对实时数据基础设施,机器学习和自动传感的投资被确定为关键.
结论:
- 一个实时的,自动化的数据生态系统对于LSCO有效的战斗伤亡护理至关重要.
- 如果不改造现有系统,可能会导致业绩下降和运营效率下降.
- 实时数据对于未来的军事任务成功和最大化生存能力至关重要.
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