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Clinical researchers’ insights on key data for eligibility screening in clinical studies

Published online by Cambridge University Press:  16 October 2024

Betina Idnay
Affiliation:
Department of Biomedical Informatics, Columbia University, New York, NY, USA
Emily R. Gordon
Affiliation:
Department of Biomedical Informatics, Columbia University, New York, NY, USA Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
Aubrey S. Johnson
Affiliation:
Department of Neurology, Columbia University, New York, NY, USA
Jordan G. Nestor
Affiliation:
Department of Medicine, Columbia University, New York, NY, USA
Karen Marder
Affiliation:
Department of Neurology, Columbia University, New York, NY, USA
Chunhua Weng*
Affiliation:
Department of Biomedical Informatics, Columbia University, New York, NY, USA
*
Corresponding author: C. Weng; Email: cw2384@cumc.columbia.edu
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Abstract

Introduction:

Clinical research is critical for healthcare advancement, but participant recruitment remains challenging. Clinical research professionals (CRPs; e.g., clinical research coordinator, research assistant) perform eligibility prescreening, ensuring adherence to study criteria while upholding scientific and ethical standards. This study investigates the key information CRP prioritizes during eligibility prescreening, providing insights to optimize data standardization, and recruitment approaches.

Methods:

We conducted a freelisting survey targeting 150 CRPs from diverse domains (i.e., neurological disorders, rare diseases, and other diseases) where they listed essential information they look for from medical records, participant/caregiver inquiries, and discussions with principal investigators to determine a potential participant’s research eligibility. We calculated the salience scores of listed items using Anthropac, followed by a two-level analytic procedure to classify and thematically categorize the data.

Results:

The majority of participants were female (81%), identified as White (44%) and as non-Hispanic (64.5%). The first-level analysis universally emphasized age, medication list, and medical history across all domains. The second-level analysis illuminated domain-specific approaches in information retrieval: for instance, history of present illness was notably significant in neurological disorders during participant and principal investigator inquiries, while research participation was distinctly salient in potential participant inquiries within the rare disease domain.

Conclusion:

This study unveils the intricacies of eligibility prescreening, with both universal and domain-specific methods observed. Variations in data use across domains suggest the need for tailored prescreening in clinical research. Incorporating these insights into CRP training and refining prescreening tools, combined with an ethical, participant-focused approach, can advance eligibility prescreening practices.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Association for Clinical and Translational Science
Figure 0

Table 1. Participant characteristics (N = 150)

Figure 1

Table 2. Top 10 synonyms by disease domain: a first-level analysis of salience scores

Figure 2

Figure 1. Shared and divergent information inquiry from data sources across domains.

Figure 3

Table 3. Categories by disease domain: a second-level analysis of salience scores

Figure 4

Table 4. Recommended practices for clinical research eligibility prescreening

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