基于可信任的专业活动信任-监督水平预测里程碑水平的模型的开发和验证
概括
这项研究开发了一种模型,用于预测儿科住院计划中使用可信任的专业活动 (EPA) 预测住院里程碑水平. 该模型准确地预测了里程碑进展,有助于居民评估.
科学领域:
- 医学教育 医学教育
- 研究生医学培训评估评估
背景情况:
- 住院计划越来越需要使用医学研究生教育认证委员会 (ACGME) 的里程碑和专业定义的可信任专业活动 (EPA) 的评估.
- 准确的评估对于居民发展和计划评估至关重要.
研究的目的:
- 开发和验证个别居民里程碑水平的预测模型.
- 利用环保署的委托监督级别作为ACGME里程碑成就的预测指标.
主要方法:
- 一项前性队列研究,涉及48个美国儿科住院计划超过3个学年 (2021-2024).
- 多层次结构方程模型是使用两年一度的EPA委托监督和ACGME里程碑数据从4,328名居民.
- 开发了两个模型:一个使用17个EPA,另一个使用12个EPA.
主要成果:
- 这些模型表现出极好的内部适应性 (相对适应性指数>0.98).
- 对未来周期的里程碑水平的外部预测显示出强烈的相关性 (系数从0.68到0.72).
- 17-EPA和12-EPA模型都表现出类似的预测能力.
结论:
- 一个强大的模型存在,可以从EPA委托监督数据中预测居民里程碑水平.
- 这种预测能力支持在居住计划评估中有意义地整合EPA和里程碑.
- 这些发现促进了更有效和数据驱动的居民评估策略.
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