Skills Decay in Military Medical Training: A Meta-synthesis of Research Outcomes.
Skills Decay in Military Medical Training: A Meta-synthesis of Research Outcomes.
复制标题
军事医疗训练中的技能衰退：研究成果的综合综合。
DOI：
10.1093/milmed/usx023
复制
发表时间：
2018
影响因子：
1.2
通讯作者：
Kevin Kunkler
中科院分区：
文献类型：
--
作者：
Amber S. Linde;Jona Caridha;Kevin Kunkler
背景
在2012财年，医学模拟和信息科学研究计划发布了两个技能衰退(SD)研究计划公告(PA)，其中包括题为“医疗实践计划的医疗实践广度和疾病频率暴露(MPI-BMP)”和“医疗实践计划程序性技能衰退和维护(MPI-PSD)”的医疗准备计划。海军研究室还发布了一份名为《军事训练与教育医学建模与仿真(MM&S)》的PA。总投资1200万美元。本文提供了在这些努力下进行的技能衰退研究的综合集成。
方法
MSIRRP医学模拟组合收集、审查和分析了来自三个PA的技能衰退研究工作的最终报告。本文对这些研究的结果进行了综合分析。这项研究的重点是确定是否达到了技能衰退考绩制度的预期目标，并向研究界提供了总结经验教训。
讨论
PAS提出的14个研究问题被组织成四个主要目标：(1)技能衰退鉴定，(2)技能衰退工具的创建/有效性和数据提取项目的可行性和可行性，(3)预防或缓解技能衰退的更新培训项目，以及(4)技能衰退教育内容。
结论
使用训练风格的组合，选择已知具有技能衰退预测价值的变量，并开发更好的方法来挖掘可用的数据，进而提供对培训需求的反馈，就有可能开发出准确的技能衰退模型。这些技术不仅能够捕捉学习者在模拟过程中的反应，还能够捕捉模拟结果，以预测医疗专业人员的经验和背景水平。从政府的投资中吸取的经验教训是极其重要的，以确保研究成果影响到战士的生活。
Background
In fiscal year 2012, the Medical Simulation and Information Sciences Research Program released two Skills Decay (SD) research program announcements (PAs) under the Medical Readiness Initiative entitled "Medical Practice Initiative Breadth of Medical Practice & Disease Frequency Exposure (MPI-BMP)" and the "Medical Practice Initiative Procedural Skill Decay and Maintenance (MPI-PSD)." The Office of Naval Research also released a PA entitled "Medical Modeling and Simulation (MM&S) for Military Training and Education." A total investment of $12 M was made. This article provides a meta-synthesis of the Skills Decay research conducted under these efforts.
Methods
The MSIRRP Medical Simulation Portfolio collected, reviewed, and analyzed the final reports of the Skills Decay research efforts from the three PAs. This paper provides a meta-synthesis of the outcomes of those studies. Focus of this study was to determine if the anticipated goals of the Skills Decay PAs were met as well as to provide a summary of lessons learned to the research community.
Discussion
Fourteen research questions posed by the PAs were structured into four main goals: (1) Skills Decay identification, (2) creation/validity of Skills Decay tools and feasibility and viability of data extraction project, (3) refreshment training to prevent or alleviate Skills Decay project, and (4) Skills Decay education content.
Conclusion
Using a combination of training styles, choosing variables known to have Skills Decay predication value, and developing better ways of mining available data that can, in turn, provide feedback to training needs, it is possible for accurate Skills Decay models to be developed. These technologies have the ability not only capture the learner's reaction during the simulation, but to capture the simulation outcomes to predict a medical professional's level of experience and background. Lessons learned from the investments made by the government are extremely important in order to ensure that the outcomes of the research touch the lives of the warfighter.