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Activity Number: 656 - Using Unique Associations to Address Health Policy Questions
Type: Contributed
Date/Time: Thursday, August 1, 2019 : 10:30 AM to 12:20 PM
Sponsor: Health Policy Statistics Section
Abstract #304307 Presentation
Title: A Unified Counterfactual Framework for Estimating Health Disparity
Author(s): Chen-Pin Wang*
Companies: University of Texas Health Science Center San Antonio
Keywords: causal inference; disparity; balancing scores; rank-and-replace; Peters-Belson

This paper considered an integration of three Institute of Medicine concordant health disparity measures derived from the counterfactual framework: balancing scores weighting, rank-and-replace, and Peters-Belson methods. We began by comparing the three disparity estimates regarding (1) their underlying assumptions about the relationship between actionable and nonactionable factors; (2) their corresponding estimates when the predictivity and/or the distribution of actionable factors differ(s) between groups conditioned on both the default and constrained relationship between actionable and nonactionable factors; and (3) their implications for identifying intervention strategies to reduce health disparity. We then identified scenarios where a unification of these health disparity estimates can be formulated. We demonstrated the proposed unification method with simulated data and an application example that assessed racial/ethnic disparity in chronic liver diseases attributed to behavioral/clinical factors in a cohort study funded by the Cancer Prevention and Research Institute of Texas.

Authors who are presenting talks have a * after their name.

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