ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018
Computable Eligibility Criteria through Ontology-driven Data Access: A Case Study of Hepatitis C Virus Trials.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical Trial Generalizability Assessment in the Big Data Era: A Review.Clinical and translational science · 2020Pooled it
- Introducing the TOP framework: a novel phenotyping solution for collaborative phenotype algorithm development and application.Journal of biomedical semantics · 2026Article
- Simulating Colorectal Cancer Trials Using Real-World Data.JCO clinical cancer informatics · 2022Article
- EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Deep propensity network using a sparse autoencoder for estimation of treatment effects.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Exploring the feasibility of using real-world data from a large clinical data research network to simulate clinical trials of Alzheimer's disease.NPJ digital medicine · 2021Article
- 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
- Review of Clinical Research Informatics.Yearbook of medical informatics · 2020Review
- A rule-based approach to identify patient eligibility criteria for clinical trials from narrative longitudinal records.JAMIA open · 2019Article
- Assessing the Validity of aAMIA ... Annual Symposium proceedings. AMIA Symposium · 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
10 authors.
Funding
Abstract
The increasing adoption of electronic health record (EHR) systems and proliferation of clinical data offer unprecedented opportunities for cohort identification to accelerate patient recruitment. However, the effort required to translate trial eligibility criteria to the correct cohort identification queries for clinical investigators is substantial, at least in part due to the lack of clear definitions in both the free-text eligibility criteria and the data models used to structure the available data elements in target patient databases. We propose to adopt an ontology-driven data access approach that generates formal representations of the connections between the entities in eligibility criteria and the available data elements to (1) narrow the semantic gap between researchers' cohort identification needs and the underlying database nuances, and (2) render the eligibility criteria computable. We implemented our approach based on an analysis of the eligibility criteria from 77 Hepatitis C trials. We found that 4 major types of data manipulation queries and 4 temporal patterns covered all eligibility criteria that were computable. We built a prototype system that helps researchers write computable eligibility criteria and execute them against clinical data in real-time to find potential trial cohorts.
Indexed as
Identifiers
30815206PMC6371316What 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.