AI Article Synopsis
- The study aimed to automate the filling of case report forms (CRFs) for a COVID-19 trial across multiple locations in the U.S.
- It utilized data from 27 hospitals and electronic health records to efficiently populate trial forms, successfully processing 499 out of 526 variables for 417 enrolled patients.
- The researchers concluded that the automated system was effective and suggested improvements for future clinical trials.
Article 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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Source |
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141839 | PMC |
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