Analytic Approaches for Causal Inference with Complex Multi-Component Interventions

Authors

Glen P. Mays, University of KentuckyFollow
Arnold J. Stromberg, University of KentuckyFollow
Jing Li, University of KentuckyFollow
Mark V. Williams, University of KentuckyFollow

Abstract

Estimating the causal effects of complex, multi-component health interventions is a task with many challenges in measurement and methodology. This presentation profiles the methods being used as part of the PCORI-funded Project Achieve, a national study to estimate the comparative effectiveness of heterogeneous care transition programs designed to help hospitalized patients and their caregivers navigate care delivery systems effectively and return back to the community with optimal health and wellbeing.

Document Type

Presentation

Publication Date

10-8-2015

Notes/Citation Information

A presentation at the First Annual Meeting of the Patient Centered Outcomes Research Institute in Arlington, VA.

Repository Citation

Mays, Glen P.; Stromberg, Arnold J.; Li, Jing; and Williams, Mark V., "Analytic Approaches for Causal Inference with Complex Multi-Component Interventions" (2015). Health Management and Policy Presentations. 115.
https://uknowledge.uky.edu/hsm_present/115