ArticleInternational journal of medical informatics2016
A data-driven concept schema for defining clinical research data needs.
Article in International journal of medical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024Review
- Schema Playground: a tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data.BMC bioinformatics · 2023Article
- Schema Playground: A tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data.bioRxiv : the preprint server for biology · 2022Article
- Structured Data Capture for Oncology.JCO clinical cancer informatics · 2021Article
- Contemporary use of real-world data for clinical trial conduct in the United States: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Amplifying Domain Expertise in Clinical Data Pipelines.JMIR medical informatics · 2020Article
- Discovering Clinical Information Models Online to Promote Interoperability of Electronic Health Records: A Feasibility Study of OpenEHR.Journal of medical Internet research · 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
objectivesThe Patient, Intervention, Control/Comparison, and Outcome (PICO) framework is an effective technique for framing a clinical question. We aim to develop the counterpart of PICO to structure clinical research data needs.
methodsWe use a data-driven approach to abstracting key concepts representing clinical research data needs by adapting and extending an expert-derived framework originally developed for defining cancer research data needs. We annotated clinical trial eligibility criteria, EHR data request logs, and data queries to electronic health records (EHR), to extract and harmonize concept classes representing clinical research data needs. We evaluated the class coverage, class preservation from the original framework, schema generalizability, schema understandability, and schema structural correctness through a semi-structured interview with eight multidisciplinary domain experts. We iteratively refined the schema based on the evaluations.
resultsOur data-driven schema preserved 68% of the 63 classes from the original framework and covered 88% (73/82) of the classes proposed by evaluators. Class coverage for participants of different backgrounds ranged from 60% to 100% with a median value of 95% agreement among the individual evaluators. The schema was found understandable and structurally sound.
conclusionsOur proposed schema may serve as the counterpart to PICO for improving the research data needs communication between researchers and informaticians.
Indexed as
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What 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.