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

Overview

Journal AMIA Jt Summits Transl Sci Proc

Specialty Biology

Date 2024 Jun 3

PMID 38827056

Authors

Andrew J King

Lisa Higgins

Carly Au

Salim Malakouti

Edvin Music

Kyle Kalchthaler

Gilles Clermont

William Garrard

David T Huang

Bryan J McVerry

Christopher W Seymour

Kelsey Linstrum

Amanda McNamara

Cameron Green

India Loar

Tracey Roberts

Oscar Marroquin

Derek C Angus

Christopher M Horvat

Affiliations

Soon will be listed here.

Abstract

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.

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