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Activity Number: 247 - Causal Inference and Statistical Learning of Intervention and Policy Effects
Type: Contributed
Date/Time: Wednesday, August 11, 2021 : 10:00 AM to 11:50 AM
Sponsor: Health Policy Statistics Section
Abstract #318291
Title: Enhancing Patient-Level Clinical Trial Data with Medical Expenditure Panel Survey Data: Quick Start Guide to the Enhanced Data Sets
Author(s): Jennifer Unangst* and Steven B. Cohen and Feng Yu
Companies: RTI International and RTI and RTI International
Keywords: data integration; clinical trials; survey data; Project Data Sphere

The Project Data Sphere® (PDS) online platform provides the cancer research community with broad access to de-identified patient-level clinical trial data. These data are rich in measures that characterize the clinical trials under study, but to address the confidentiality provisions inherent to the trials, data providers are required to mask or remove certain demographic data, limiting researchers’ ability to study the influence of health-related and socioeconomic factors, access to and use of health care services, and predisposition of health behaviors on treatment effects and patient outcomes. To overcome these analytic constraints, our team created a series of enhanced datasets, whereby content from the nationally representative Medical Expenditure Survey (MEPS) has been appended to patient-level data from select clinical trials. Comparator arm patients from the clinical trials were deterministically matched with similar cancer survivors from MEPS based on age, sex, race, and quality of life. In this paper, we describe the enhanced datasets, the types of analyses they support, and the free resources available for data users.

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

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