[edit]
Electronic Medical Records Assisted Digital Clinical Trial Design
Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2836-2844, 2024.
Abstract
Randomized controlled trials (RCTs) are gold standards for assessing intervention efficacy. Yet, generalizing evidence from classical RCTs can be challenging and sometimes problematic due to their limited external validity under stringent eligibility criteria and inadequate statistical power resulting from limited sample sizes under budgetary constraints. "Digital clinical trial," which utilizes digital technology and electronic medical records (EMRs) to expand eligibility criteria and enhance data collection efficiency, offers a promising concept for solving the above-mentioned conundrums encountered in classical RCTs. In this paper, we propose two novel digital clinical trial design strategies assisted by EMRs collected from diverse patient populations. On the one hand, leveraging digital technologies, our design strategies adaptively modify both the eligibility criteria and treatment assignment mechanism to enhance data collection efficiency. As a result, evidence gathered from our design can possess greater statistical power. On the other hand, since EMRs capture diverse patient populations and provide large sample sizes, our design not only broadens the trial’s eligibility criteria but also enhances its statistical power, enabling us to collect more generalizable evidence with boosted statistical power for evaluating intervention efficacy than classical RCTs. We demonstrate the validity and merit of the proposed designs with detailed theoretical investigation, simulation studies, and a synthetic case study.