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Analysis of Eligibility Criteria Complexity in Clinical Trials

Formal, computer-interpretable representations of eligibility criteria would allow computers to better support key clinical research and care use cases such as eligibility determination. To inform the development of such formal representations for eligibility criteria, we conducted this study to cha...

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Detalles Bibliográficos
Autores principales: Ross, Jessica, Tu, Samson, Carini, Simona, Sim, Ida
Formato: Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041539/
https://www.ncbi.nlm.nih.gov/pubmed/21347148
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author Ross, Jessica
Tu, Samson
Carini, Simona
Sim, Ida
author_facet Ross, Jessica
Tu, Samson
Carini, Simona
Sim, Ida
author_sort Ross, Jessica
collection PubMed
description Formal, computer-interpretable representations of eligibility criteria would allow computers to better support key clinical research and care use cases such as eligibility determination. To inform the development of such formal representations for eligibility criteria, we conducted this study to characterize and quantify the complexity present in 1000 eligibility criteria randomly selected from studies in ClinicalTrials.gov. We classified the criteria by their complexity, semantic patterns, clinical content, and data sources. Our analyses revealed significant semantic and clinical content variability. We found that 93% of criteria were comprehensible, with 85% of these criteria having significant semantic complexity, including 40% relying on temporal data. We also identified several domains of clinical content. Using the findings of the study as requirements for computer-interpretable representations of eligibility, we discuss the challenges for creating such representations for use in clinical research and practice.
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spelling pubmed-30415392011-02-23 Analysis of Eligibility Criteria Complexity in Clinical Trials Ross, Jessica Tu, Samson Carini, Simona Sim, Ida Summit on Translat Bioinforma Articles Formal, computer-interpretable representations of eligibility criteria would allow computers to better support key clinical research and care use cases such as eligibility determination. To inform the development of such formal representations for eligibility criteria, we conducted this study to characterize and quantify the complexity present in 1000 eligibility criteria randomly selected from studies in ClinicalTrials.gov. We classified the criteria by their complexity, semantic patterns, clinical content, and data sources. Our analyses revealed significant semantic and clinical content variability. We found that 93% of criteria were comprehensible, with 85% of these criteria having significant semantic complexity, including 40% relying on temporal data. We also identified several domains of clinical content. Using the findings of the study as requirements for computer-interpretable representations of eligibility, we discuss the challenges for creating such representations for use in clinical research and practice. American Medical Informatics Association 2010-03-01 /pmc/articles/PMC3041539/ /pubmed/21347148 Text en ©2010 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Ross, Jessica
Tu, Samson
Carini, Simona
Sim, Ida
Analysis of Eligibility Criteria Complexity in Clinical Trials
title Analysis of Eligibility Criteria Complexity in Clinical Trials
title_full Analysis of Eligibility Criteria Complexity in Clinical Trials
title_fullStr Analysis of Eligibility Criteria Complexity in Clinical Trials
title_full_unstemmed Analysis of Eligibility Criteria Complexity in Clinical Trials
title_short Analysis of Eligibility Criteria Complexity in Clinical Trials
title_sort analysis of eligibility criteria complexity in clinical trials
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041539/
https://www.ncbi.nlm.nih.gov/pubmed/21347148
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