ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Classifying Clinical Trial Eligibility Criteria to Facilitate Phased Cohort Identification Using Clinical Data Repositories.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- EC2Seq2Sql: Patient-trial matching with LLM agents.PloS one · 2026Article
- LeafAI: query generator for clinical cohort discovery rivaling a human programmer.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- ELaPro, a LOINC-mapped core dataset for top laboratory procedures of eligibility screening for clinical trials.BMC medical research methodology · 2022Article
- Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials.Applied clinical informatics · 2021Article
- Deep Learning Approach to Parse Eligibility Criteria in Dietary Supplements Clinical Trials Following OMOP Common Data Model.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Hybrid bag of approaches to characterize selection criteria for cohort identification.Journal of the American Medical Informatics Association : JAMIA · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
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.
Indexed as
Identifiers
29854246PMC5977684What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.