使用机器学习来识别影响住院患者出院处置的健康社会决定因素
He Ren1, Chun Wang1, David J Weiss2
1School of Psychology, University of Washington, Seattle, WA, USA.
Journal of the American Medical Directors Association
|March 1, 2025
概括
健康的社会决定因素 (SDOH),如社会联系和交通需求,大大预测了熟练护理机构 (SNF) 的退休情况. 解决这些因素可以帮助更多的患者在住院后返回家园.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 社会流行病学 社会流行病学
- 医疗信息学 医疗信息学
背景情况:
- 医院出院规划旨在确保适当的患者处置.
- 熟练护理机构 (SNF) 的安置是一个常见的结果,但家庭出院通常是首选的.
- 健康的社会决定因素 (SDOH) 越来越多地被认为是影响健康结果的关键因素.
研究的目的:
- 确定自我报告的健康社会决定因素 (SDOH),预测住院患者中被送往熟练护理机构 (SNF) 的出院情况.
- 开发和验证基于SDOH的SNF处置的预测模型.
主要方法:
- 对134,807名住院患者的回顾性队列分析.
- 使用堆叠弹性网 (SENET) 和启动引算稳定性选择 (BISS) 进行不完整数据的变量选择.
- 开发和验证了后勤回归模型,使用曲线下的面积 (AUC) 和校准评估性能.
主要成果:
- 8.72%的患者被释放到一个SNF.
- 主要的SDOH预测因素包括酒精消费,牙科护理,就业,财务资源,营养,体力活动,社会联系和交通.
- 纳入SDOH,临床 (查尔森并发症指数) 和人口因素的模型在验证队列中实现了大约0.77的AUC.
结论:
- 多种SDOH特征,特别是社会联系和婚姻状况,显著预测SNF倾向.
- 营养,体力活动和交通等潜在的缓解因素为增加家庭出院率提供了可行的目标.
- 将SDOH数据集成到排放规划中可以优化适当性和效率.
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