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Activity Number: 626 - Health Policy and Real World Evidence with Administrative Data and Electronic Health Records
Type: Contributed
Date/Time: Thursday, August 2, 2018 : 8:30 AM to 10:20 AM
Sponsor: Health Policy Statistics Section
Abstract #330546 Presentation
Title: Medication Adherence and Cost Exposure: a Story in Heterogeneity
Author(s): Rahul Ladhania* and Amelia M Haviland and Neeraj Sood and Ateev Mehtotra
Companies: Carnegie Mellon University and Carnegie Mellon University - Heinz College and University of Southern California and Harvard Medical School
Keywords: Medication adherence; Hierarchical clustering; Heterogeneous effects; Chronic condtions; Recursive partitioning

A gap exists in understanding how medication non-adherence differs across subgroups of patients, and the role cost-exposure plays therein. We use 2013 claims data for a sample of patients suffering from four chronic conditions (diabetes, asthma, hypertension, and coronary heart disease), and use agglomerative hierarchical cluster analysis, based on patients' clinical and demographic features, to identify patient clusters. We study the heterogeneous association of cost-exposure - the amount that patients incur out-of-pocket for medications - with adherence across the clusters. We compare this approach with an alternative model-based recursive partitioning method for identifying clusters with distinctive cost and adherence relationships, and evaluate the most relevant partitioning features and their clinical implications. We validate and compare the two approaches by running them on 'test' patients from 2012 claims data. Our study aims to better identify potential reasons for non-adherence across distinct patient groups, and serves as a data-driven way for generating hypotheses to identify patient groups for targeting in experiments aimed at mitigating non-adherence in the future.

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

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