预先定义的基于规则的多因素风险分层与农村初级保健实践中改善的结果有关
Laith Abu Lekham1, Ellen Hey, Jose Canario
1Author Affiliations: Data Department/Quality Division (Mr Abu Lekham), Executive Department/Quality Division (Ms Hey), Executive Department/Medical Division (Dr Canario), Behavioral Health Department/Medical Divison (Ms Felice), Executive Department/Support Service Division (Ms Rivas), Care Management Department/Division (Mr Mantegna).
Family & community health
|May 10, 2024
概括
农村初级保健的新风险分层模型,整合了医疗和非医疗因素,使高风险患者减少了30%. 该模型有效地识别了需要干预的患者,改善了健康结果.
科学领域:
- 初级医疗保健医学 一级医疗保健医学
- 医疗保健服务研究 医疗服务研究
- 农村卫生 农村卫生
背景情况:
- 现有的风险分层模型往往缺乏非医疗因素的整合.
- 特别需要适应农村社区独特挑战的模型.
- 非医疗因素,如交通工具的可用性,对农村环境的健康结果有很大影响.
研究的目的:
- 为农村初级保健机构开发和评估预定义的基于规则的风险分层范式.
- 将医疗和非医疗变量整合到一个全面的风险评估工具中.
- 具体解决服务不足的农村人口的需求.
主要方法:
- 利用了19个因素,包括人口特征,交通可用性和临床变量 (例如血压,BMI).
- 使用2021年医疗访问数据开发了一个基于规则的模型.
- 使用2022年的数据和实施的干预措施验证了模型的性能.
主要成果:
- 实施的风险分层和干预措施导致健康状况恶化的高或中等风险患者减少了30% (34.9%至24.4%).
- 中等复杂型患者的比例从29%降至5.7%.
- 在总风险得分和双重诊断 (0.63),提供者数量 (0.54) 和PHQ9得分 (0.45) 之间发现了强烈的相关性.
结论:
- 开发的风险分层模型有效地识别和管理农村初级保健中高风险患者.
- 整合非医学因素可以提高模型在不同人群中的适用性和有效性.
- 该模型促进了有针对性的干预,从而显著改善了患者健康结果和资源配置.
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