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Activity Number: 227
Type: Invited
Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
Sponsor: Health Policy Statistics Section
Abstract #314518 View Presentation
Title: Modeling Strategies for Patient-Centered Comparative Effectiveness Research
Author(s): Douglas P. Landsittel* and Sally Morton and Joyce Chang and Elan Cohen and Andrew Topp
Companies: University of Pittsburgh and University of Pittsburgh and University of Pittsburgh and University of Pittsburgh and University of Pittsburgh
Keywords: observational ; causal inference ; propensity scores ; instrumental variables ; CER

Comparative effectiveness research (CER) seeks to evaluate which treatment works best when, and for whom, under which circumstances. CER often relies on observational data; associated limitations, such as treatment self-selection or other forms of bias, may necessitate use of methods such as propensity scores and instrumental variables. While there is substantial literature on these methods, there are also many variations and a lack of clear guidance on when to use which method. For instance, there are still no clear answers to the most fundamental questions, such as "Which method should I trust more if instrumental variables and propensity scores lead to different results?" This presentation summarizes preliminary results from a study funded by the Patient-Centered Outcomes Research Institute that aims to 1) conduct a systematic review, 2) conduct simulations to address gaps, and 3) develop a decision tool for recommending optimal methods for a given data set. The presentation will present findings of the systematic review and present a preliminary version of the Decision Tool for Observational Data Analysis Methods for Comparative Effectiveness Research, or DecODe CER.

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

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