Unknown

Dataset Information

0

Classifying Clinical Trial Eligibility Criteria to Facilitate Phased Cohort Identification Using Clinical Data Repositories.


ABSTRACT: A major challenge in using electronic health record repositories for research is the difficulty matching subject eligibility criteria to query capabilities of the repositories. We propose categories for study criteria corresponding to the effort needed for querying those criteria: "easy" (supporting automated queries), mixed (initial automated querying with manual review), "hard" (fully manual record review), and "impossible" or "point of enrollment" (not typically in health repositories). We obtained a sample of 292 criteria from 20 studies from ClinicalTrials.gov. Six independent reviewers, three each from two academic research institutions, rated criteria according to our four types. We observed high interrater reliability both within and between institutions. The analysis demonstrated typical features of criteria that map with varying levels of difficulty to repositories. We propose using these features to improve enrollment workflow through more standardized study criteria, self-service repository queries, and analyst-mediated retrievals.

SUBMITTER: Wang AY 

PROVIDER: S-EPMC5977684 | BioStudies | 2017-01-01

REPOSITORIES: biostudies

Similar Datasets

1000-01-01 | S-EPMC3034423 | BioStudies
2015-01-01 | S-EPMC4407835 | BioStudies
2017-01-01 | S-EPMC5510799 | BioStudies
2009-01-01 | S-EPMC2649164 | BioStudies
2020-01-01 | S-EPMC7489858 | BioStudies
2020-01-01 | S-EPMC7372873 | BioStudies
2020-01-01 | S-EPMC7069834 | BioStudies
1000-01-01 | S-EPMC3000787 | BioStudies
2012-01-01 | S-EPMC5222546 | BioStudies
2016-01-01 | S-EPMC5535306 | BioStudies