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EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites

OBJECTIVE: The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from elect...

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Autores principales: Nelson, Sarah J, Drury, Bethany, Hood, Daniel, Harper, Jeremy, Bernard, Tiffany, Weng, Chunhua, Kennedy, Nan, LaSalle, Bernie, Gouripeddi, Ramkiran, Wilkins, Consuelo H, Harris, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922182/
https://www.ncbi.nlm.nih.gov/pubmed/34850917
http://dx.doi.org/10.1093/jamia/ocab265
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author Nelson, Sarah J
Drury, Bethany
Hood, Daniel
Harper, Jeremy
Bernard, Tiffany
Weng, Chunhua
Kennedy, Nan
LaSalle, Bernie
Gouripeddi, Ramkiran
Wilkins, Consuelo H
Harris, Paul
author_facet Nelson, Sarah J
Drury, Bethany
Hood, Daniel
Harper, Jeremy
Bernard, Tiffany
Weng, Chunhua
Kennedy, Nan
LaSalle, Bernie
Gouripeddi, Ramkiran
Wilkins, Consuelo H
Harris, Paul
author_sort Nelson, Sarah J
collection PubMed
description OBJECTIVE: The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method. MATERIALS AND METHODS: In building this service line, the RIC strove to complement, rather than replace, CTSA hubs’ existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection. RESULTS: From 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%. DISCUSSION: Achieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants. CONCLUSION: The RIC’s EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs.
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spelling pubmed-89221822022-03-15 EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites Nelson, Sarah J Drury, Bethany Hood, Daniel Harper, Jeremy Bernard, Tiffany Weng, Chunhua Kennedy, Nan LaSalle, Bernie Gouripeddi, Ramkiran Wilkins, Consuelo H Harris, Paul J Am Med Inform Assoc Research and Applications OBJECTIVE: The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method. MATERIALS AND METHODS: In building this service line, the RIC strove to complement, rather than replace, CTSA hubs’ existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection. RESULTS: From 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%. DISCUSSION: Achieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants. CONCLUSION: The RIC’s EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs. Oxford University Press 2021-11-30 /pmc/articles/PMC8922182/ /pubmed/34850917 http://dx.doi.org/10.1093/jamia/ocab265 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research and Applications
Nelson, Sarah J
Drury, Bethany
Hood, Daniel
Harper, Jeremy
Bernard, Tiffany
Weng, Chunhua
Kennedy, Nan
LaSalle, Bernie
Gouripeddi, Ramkiran
Wilkins, Consuelo H
Harris, Paul
EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites
title EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites
title_full EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites
title_fullStr EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites
title_full_unstemmed EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites
title_short EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites
title_sort ehr-based cohort assessment for multicenter rcts: a fast and flexible model for identifying potential study sites
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922182/
https://www.ncbi.nlm.nih.gov/pubmed/34850917
http://dx.doi.org/10.1093/jamia/ocab265
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