基于医疗保健轨迹的人口分层:一种鼓励在中等水平上进行适应性学习的方法
Anne-Sophie Lambert1, Catherine Legrand2, Béatrice Scholtes3
1Institute of Health and Society (IRSS), Catholic University of Louvain, Brussels, Belgium.
这项研究引入了一种新的医疗保健轨迹方法,用于人口分层. 它确定了五个不同的患者群体,以改善人口健康管理和资源分配.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 人口健康管理 人口健康管理
- 在医疗保健中的数据科学.
背景情况:
- 有效的人口管理需要了解不同的医疗保健需求.
- 目前的方法可能缺乏针对量身定制的干预措施的细节性.
- 医疗保健消费数据为轨迹分析提供了丰富的来源.
研究的目的:
- 开发和验证一种使用医疗保健轨迹进行人口分层的方法.
- 根据他们的医疗保健利用模式来识别不同的患者群体.
- 支持适应性管理人口健康需求.
主要方法:
- 报销医疗保健消费数据的分析 (2017年第一学期).
- 为60-79岁的个人创建医疗保健轨迹 (N=22,832).
- 应用K-mers方法和多项混合模型进行分类.
主要成果:
- 确定了五个不同的人口群体:"低使用者"",高强度护理"",过渡护理和护理"",过渡护理"和"长时间住院".
- 展示系统视角,而不是特定疾病的方法.
- 对人口细分的医疗保健轨迹的验证.
结论:
- 医疗保健轨迹分析为人口分层提供了一个细微的方法.
- 这种方法使地方区域政府机构能够超越"一刀切"的战略.
- 常规收集的数据可以用于持续学习和适应性人口健康管理.
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