Automatic Population of the Case Report Forms for an International Multifactorial Adaptive Platform Trial Amid the COVID-19 Pandemic

Objectives To automatically populate the case report forms (CRFs) for an international, pragmatic, multifactorial, response-adaptive, Bayesian COVID-19 platform trial. Methods The locations of focus included 27 hospitals and 2 large electronic health record (EHR) instances (1 Cerner Millennium and 1 Epic) that are part of the same health system in the United States. This paper describes our efforts to use EHR data to automatically populate four of the trial’s forms: baseline, daily, discharge, and response-adaptive randomization. Results Between April 2020 and May 2022, 417 patients from the UPMC health system were enrolled in the trial. A MySQL-based extract, transform, and load pipeline automatically populated 499 of 526 CRF variables. The populated forms were statistically and manually reviewed and then reported to the trial’s international data coordinating center. Conclusions We accomplished automatic population of CRFs in a large platform trial and made recommendations for improving this process for future trials. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded in part by the UPMC Learning While Doing Program. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was granted by the University of Pittsburgh Human Research Protection Office. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as [ClinicalTrials.gov][1]. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data underlying this article cannot be shared publicly due to institutional policies that protect the privacy of individuals whose data were used in the study. [1]: http://ClinicalTrials.gov