马尔科夫建模用于使用联合健康数据网络的成本效益
Markus Haug1, Marek Oja1, Maarja Pajusalu1
1Institute of Computer Science, University of Tartu, Tartu 51009, Estonia.
概括
新的R包将在OMOP数据网络上对健康经济学研究进行标准化. 发现心力衰竭的远程监测在国际站点上不具有成本效益.
科学领域:
- 卫生经济学 卫生经济学
- 医疗信息学 医疗信息学
- 药物经济学 药物经济学
背景情况:
- 医疗保健中的成本效益分析 (CEA) 缺乏标准化工具,通常依赖于特设方法和有限的特定站点数据.
- 发表的CEA结果可能缺乏普遍性,因为其焦点狭窄,决策标准部分,阻碍了国际比较.
- 观察医学结果伙伴关系 (OMOP) 共同数据模型 (CDM) 为协调健康数据提供了一个框架,但需要用于健康经济建模的工具.
研究的目的:
- 通过使用基于OMOP的数据网络,引入两个R包,旨在标准化和提高卫生经济模型的可重复性,透明度和可转移性.
- 通过为状态定义,数据库交互,马尔科夫模型学习和个人资料合成提供工具,促进健康经济学研究.
- 通过多个站点的国际卫生经济评估来证明这些R套餐的实用性.
主要方法:
- 开发两个R包:一个用于管理状态定义和数据库交互,另一个用于马尔科夫模型学习和个人资料合成.
- 在五个国际 OMOP CDM 数据库 (爱沙尼亚,西班牙,塞尔维亚,美国) 中复制英国心力衰竭成本效益分析.
- 对47163名患者的治疗轨迹的检查,将远程监控与标准护理进行比较.
主要成果:
- 远程监测与标准护理的整体增量成本效益比率 (ICER) 是57,472€/QALY.
- 各个国家的ICER从40372欧元/QALY (塞尔维亚) 到90893欧元/QALY (美国) 之间,都超过了典型的支付意愿门.
- 通过R套餐进行的分析表明,心力衰竭的远程监测在研究群体中没有成本效益.
结论:
- 开发的R包成功地在OMOP CDM数据网络上实现了标准化和可重复的成本效益分析.
- 这项研究强调了心力衰竭远程监测在各种国际医疗保健机构的成本效益不足.
- 这些工具通过促进强大,可转移和透明的模型开发和应用,推动健康经济学领域的发展.
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