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Selective recruitment designs for improving observational studies using electronic health records

Barrett, JE; Cakiroglu, A; Bunce, C; Shah, A; Denaxas, S; (2020) Selective recruitment designs for improving observational studies using electronic health records. Statistics in Medicine 10.1002/sim.8556. (In press). Green open access

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Abstract

Large‐scale electronic health records (EHRs) present an opportunity to quickly identify suitable individuals in order to directly invite them to participate in an observational study. EHRs can contain data from millions of individuals, raising the question of how to optimally select a cohort of size n from a larger pool of size N . In this article, we propose a simple selective recruitment protocol that selects a cohort in which covariates of interest tend to have a uniform distribution. We show that selectively recruited cohorts potentially offer greater statistical power and more accurate parameter estimates than randomly selected cohorts. Our protocol can be applied to studies with multiple categorical and continuous covariates. We apply our protocol to a numerically simulated prospective observational study using an EHR database of stable acute coronary disease patients from 82 089 individuals in the U.K. Selective recruitment designs require a smaller sample size, leading to more efficient and cost‐effective studies.

Type: Article
Title: Selective recruitment designs for improving observational studies using electronic health records
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sim.8556
Publisher version: https://doi.org/10.1002/sim.8556
Language: English
Additional information: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/
Keywords: electronic health records, observational study, optimal experimental design, selective recruitment
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/10102468
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