Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information
结局与协变量信息不完整时 HIV 照护留存的贝叶斯反事实预测AI 解读 ↓
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结局与协变量信息不完整时 HIV 照护留存的贝叶斯反事实预测
- 研究问题
- 如何根据电子健康记录评估不同复诊安排下的 HIV 照护留存率，并在混杂、死亡竞争事件、删失和协变量缺失下支持安排决策。
- 方法与思路
- 作者用假想复诊安排下的潜在返回时间定义因果目标，以灵活贝叶斯模型刻画返回时间分布，并形成后验点估计与不确定性估计。
- 材料陈述的贡献
- 摘要称，方法将反事实留存预测与复诊安排优化结合，并应用于肯尼亚西部 AMPATH 诊所联盟的电子健康记录。
- 阅读关注点
- 应核对反事实目标的时间范围、混杂调整与缺失机制条件，以及死亡和删失如何分别进入留存定义、似然及决策目标。
- 阅读边界
- 这是 arXiv 预印本，不能据此认定已同行评审或期刊接收；摘要未给出完整识别条件、缺失处理细节或安排优化的实际收益。
原文摘要
Like many chronic diseases, human immunodeficiency virus (HIV) is managed over time at regular clinic visits. At each visit, patient features are assessed, treatments are prescribed, and a subsequent visit is scheduled. There is a need for data-driven methods for both predicting retention and recommending scheduling decisions that optimize retention. Prediction models can be useful for estimating retention rates across a range of scheduling options. However, training such models with electronic health records (EHR) involves several complexities. First, formal causal inference methods are needed to adjust for observed confounding when estimating retention rates under counterfactual scheduling decisions. Second, competing events such as death preclude retention, while censoring events render retention missing. Third, inconsistent monitoring of features such as viral load and CD4 count lead to covariate missingness. This paper presents an all-in-one approach for both predicting HIV retention and optimizing scheduling while accounting for these complexities. We formulate and identify causal retention estimands in terms of potential return-time under a hypothetical scheduling decision. Flexible Bayesian approaches are used to model the observed return-time distribution while accounting for competing and censoring events and form posterior point and uncertainty estimates for these estimands. We address the urgent need for data-driven decision support in HIV care by applying our method to EHR from the Academic Model Providing Access to Healthcare (AMPATH) - a consortium of clinics that treat HIV in Western Kenya.