  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 paper 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.
