Natural Language Processing for Mimicking Clinical Trial Recruitment in Critical Care: A Semi-Automated Simulation Based on the LeoPARDS Trial
Abstract
Clinical trials often fail to recruit an adequate number
of appropriate patients. Identifying eligible trial participants
is resource-intensive when relying on manual review of clinical
notes, particularly in critical care settings where the time window
is short. Automated review of electronic health records (EHR)
may help, but much of the information is in free text rather than a
computable form. We applied natural language processing (NLP)
to free text EHR data using the CogStack platform to simulate
recruitment into the LeoPARDS study, a clinical trial aiming
to reduce organ dysfunction in septic shock. We applied an
algorithm to identify eligible patients using a moving 1-hour time
window, and compared patients identified by our approach with
those actually screened and recruited for the trial, for the time
period that data were available. We manually reviewed records of
a random sample of patients identified by the algorithm but not
screened in the original trial. Our method identified 376 patients,
including 34 patients with EHR data available who were actually
recruited to LeoPARDS in our centre. The sensitivity of CogStack
for identifying patients screened was 90% (95% CI 85%, 93%).
Of the 203 patients identified by both manual screening and
CogStack, the index date matched in 95 (47%) and CogStack
was earlier in 94 (47%). In conclusion, analysis of EHR data
using NLP could effectively replicate recruitment in a critical
care trial, and identify some eligible patients at an earlier stage,
potentially improving trial recruitment if implemented in real time.
URL
https://ieeexplore.ieee.org/document/9027845
DOI
10.1109/JBHI.2020.2977925
LaTeX
@article{Tissot2019JBHI,
author = {H. C. {Tissot} and A. D. {Shah} and D. {Brealey} and S. {Harris} and R. {Agbakoba} and A. {Folarin} and L. {Romao} and L. {Roguski} and R. {Dobson} and F. W. {Asselbergs}},
journal = {IEEE Journal of Biomedical and Health Informatics},
title = {Natural Language Processing for Mimicking Clinical Trial Recruitment in Critical Care: A Semi-Automated Simulation Based on the LeoPARDS Trial},
year = {2020},
volume = {24},
number = {10},
pages = {2950-2959}
}