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Activity Number: 452
Type: Contributed
Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #313285 View Presentation
Title: Using Patient-Reported Outcome Measures and Electronic Health Record Data for Clinical Trial Recruitment
Author(s): Sandra D. Griffith*+ and Susannah Rose
Companies: Cleveland Clinic and Cleveland Clinic
Keywords: patient-reported outcomes ; electronic health record ; clinical trials ; data quality ; predictive models ; incomplete data
Abstract:

Identification of eligible patients poses a threat to resource efficiency in clinical trial recruitment. Screening using electronic health record (EHR) data can improve efficiency; however, challenges remain, particularly in the presence of complex inclusion and exclusion criteria. Investigators must first extract clinical features from the raw EHR data, complicated by issues of data quality and completeness. When patient-reported outcome measures (PROMs) are collected electronically, they present an opportunity to augment existing EHR data and improve patient identification. We propose a methodology to recruit patients by first building models for predicting trial eligibility. Based on predicted probability of eligibility, we then selectively target patients with upcoming scheduled visits. We propose a series of decisions rules accounting for uncertainty in the estimates and present results from a simulation study comparing their performance. We apply these methods to a clinical trial evaluating palliative care interventions on heart failure patients by augmenting clinical EHR data with two PROMS-the Kansas City Cardiomyopathy Questionnaire (KCCQ) and the EuroQol (EQ-5D).


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