Estimating Heterogeneous Treatment Effects With Real-World Health Data: A Scoping Review of Machine Learning Methods

ML methods for HTE estimation are increasingly applied to RWD. Tree-based models are most common, and interest in customized conditional average treatment effect approaches is growing. Better evaluation standards and more transparent reporting are needed for these methods to become reliable tools for health economics research.