使用患者级模拟框架评估临床算法对长期健康差异的影响
Sara Khor1, Anirban Basu2, Veena Shankaran3
1Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, University of Washington, Seattle, WA, USA; Spring Health, New York, NY, USA.
概括
从结肠癌治疗算法中省略种族可能会伤害黑人患者并加剧健康差异. 使用包含种族的算法可以改善整体健康状况,减少癌症护理中的不平等.
科学领域:
- 在瘤学瘤学.
- 健康差距 研究 研究 研究 研究
- 医疗信息学 医疗信息学
背景情况:
- 结肠癌的辅助化疗决定显著影响患者的治疗结果.
- 在癌症治疗和治疗结果方面,种族差异仍然存在,需要仔细设计算法.
- 种族在临床决策算法中的作用是健康公平研究的关键领域.
研究的目的:
- 评估从结肠癌辅助化疗决策算法中省略种族的长期影响.
- 通过模拟框架评估对健康结果,成本和种族差异的影响.
- 为了解决癌症复发确定中的测量错误和种族偏见.
主要方法:
- 使用电子健康记录开发了一种患者级别的状态过渡模型.
- 模拟预测了4839名II/III期结肠癌成年人的30年质量调整寿命 (QALY) 和成本.
- 我们比较了三个场景:现行实践,带有种族的算法和没有种族的算法,以及概率灵敏度分析 (PSA).
主要成果:
- 与当前实践相比,包括种族在内的算法提高了0.048的平均QALY,并减少了0.20的QALY的种族差异.
- 省略种族导致接受治疗的黑人患者减少了13%,他们的QALY减少了0.07,差距扩大了0.13QALY.
- 在PSA代的94%,当种族从算法中被遗漏时,健康差异增加了.
结论:
- 结肠癌决策算法可以提高人口健康,减少差距.
- 从算法中省略种族可能会使某些群体处于不利地位,并限制差距减少.
- 在实施之前,患者级模拟对于评估算法对健康差异的影响是有价值的.
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