确定医院持续高成本患者的护理管理:开发和验证预测模型
Ursula W de Ruijter1,2, Z L Rana Kaplan3, Frank Eijkenaar4
1Department of Public Health, Erasmus MC University Medical Center, Rotterdam, The Netherlands. u.deruijter@erasmusmc.nl.
我们开发并验证了两种预测模型,以识别可能持续高昂的医疗保健成本的高需求高成本患者. 这些模型通过预测门诊诊所或住院后的持续高成本来帮助护理管理.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 预测建模预测建模
- 医疗保健管理的管理
背景情况:
- 高需要高成本 (HNHC) 患者对医疗保健系统构成重大负担.
- 改善护理协调对于有效管理HNHC患者至关重要.
- 准确预测持续高昂的医疗保健成本对于有针对性的干预至关重要.
研究的目的:
- 开发和验证持续高成本 (PHC) 状态的预测模型.
- 确定需要主动护理管理的HNHC患者.
- 支持一种混合方法,将临床评估和成本预测结合起来,用于发现病例.
主要方法:
- 使用荷兰国家医疗保险公司索赔数据进行的回顾性队列研究.
- 开发和验证两个模型:一个用于门诊诊所,一个用于住院.
- 后勤多变量回归分析以预测PHC状态 (连续3年最高10%的成本).
- 使用歧视 (C-统计) 和校准评估模型性能.
主要成果:
- 开发和验证了两种模型,预测PHC状态具有良好的歧视性 (C-统计数据0.70-0.75).
- 完整的模型包括27个预测器;较小,可用的版本有10-11个预测器.
- 模型表现出良好的校准,表明对门诊和入院队列的可靠预测.
结论:
- 经过验证的模型准确地预测了持续高成本患者的状态.
- 这些模型可以集成到电子健康记录中.
- 这些模型支持HNHC护理管理的混合案例寻找策略.
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