患有复杂慢性疾病的儿童的模式:潜伏类分析
Eyal Cohen1,2, Maria Osipovich3, Hallie Benjamin4
1Edwin S.H. Leong Centre for Healthy Children, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Pediatrics
|February 17, 2026
概括
患有复杂慢性疾病 (CCC) 的儿童可以根据他们的健康需求和技术依赖性分为三个不同的组. 这些分类预测了未来的医疗保健利用率和成本,有助于为儿科护理分配资源.
科学领域:
- 儿科健康服务研究 儿童健康服务研究
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 复杂慢性疾病 (CCCs) 影响着大量的儿科患者.
- 了解CCC中的异质性对于预测医疗保健需求至关重要.
- 以前的分类可能没有完全捕捉到护理利用的细微差别.
研究的目的:
- 识别有CCC儿童的不同实证类别.
- 评估这些已识别的类别是否预测未来的医疗保健使用和支出.
- 为患有CCC的儿科患者群体提供有针对性的医疗保健资源分配信息.
主要方法:
- 对1-18岁的CCC儿童的医疗补助索赔数据 (2017-2019) 的潜在类别分析.
- 包括人口因素,临床特征和2017年医疗保健利用情况.
- 负二项式和后勤回归模型来评估2018-2019年医疗保健支出和使用情况.
主要成果:
- 在185,672名患有CCC的儿童中,出现了三类解决方案.
- 第1类 (9.1%):高神经障碍,高技术依赖,高多病症.
- 2类 (14.8%):高神经障碍,低技术依赖.
- 3类 (76.0%):低神经障碍,低技术依赖.
- 与3级相比,1级和2级的医疗保健支出显著增加 (RR分别为6.9和2.5).
- 住院和门诊专家服务在第1类中带来了成本;门诊药物,专家和心理健康在第2类中.
结论:
- 患有CCC的儿童可以有意义地分为不同的类别.
- 这些类可以使用易于获得的数据来识别.
- 已识别的类别显示了未来医疗保健使用和相关成本的差异性模式.
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