ArticleJournal of biomedical informatics2016
Evaluating common data models for use with a longitudinal community registry.
Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 5 of them syntheses that pooled it.
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
103 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Common data models and data standards for tabular health data: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Pharmacoepidemiologic Research Based on Common Data Models: Systematic Review and Bibliometric Analysis.JMIR medical informatics · 2025Pooled it
- Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- Correlation of Socioeconomic and Environmental Factors With Incidence of Crohn Disease in Children and Adolescents: Systematic Review and Meta-Regression.JMIR public health and surveillance · 2024Pooled it
- OMOP CDM Can Facilitate Data-Driven Studies for Cancer Prediction: A Systematic Review.International journal of molecular sciences · 2022Pooled it
- A comparison of Fast Healthcare Interoperability Resources and Observational Medical Mutcomes Partnership electronic health record data within the All of Us Research Program.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Enabling interoperability across disparate health data sources using Large Language Models.PLOS digital health · 2026Article
- SafeRx: A Canonical Pharmaceutical Knowledge Integration Framework for Multimodal Medication Safety.Bioengineering (Basel, Switzerland) · 2026Article
- Implementation of OMOP and ConcePTION Common Data Models in CPRD GOLD: Risk of Bleeding and Cardiovascular Outcomes From Anticoagulant Use.Clinical pharmacology and therapeutics · 2026Article
- Expanding the OMOP common data model to support extracorporeal life support research.JAMIA open · 2026Article
- Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study.EClinicalMedicine · 2026Article
- Statistical methods to harmonize electronic health record data across healthcare systems: case study and lessons learned.Bioinformatics (Oxford, England) · 2026Article
- Linking Electronic Health Records for Multiple Sclerosis Research: Comparative Study of Deterministic, Probabilistic, and Machine Learning Linkage Methods.JMIR medical informatics · 2026Article
- Academic impact and research data utilisation of the clinical practice research datalink: scientometric analyses.European journal of epidemiology · 2026Article
- Exploring common data model coverage of nursing flowsheet data: a pilot study using SNOMED CT and LOINC mapping.JAMIA open · 2025Article
- Evaluating Methods for Imputing Race and Ethnicity in Electronic Health Record Data.Health services research · 2025Article
- Streamlining electronic medical record data extraction and validation in digital hospitals: A systematic review to identify optimal approaches and methods.Learning health systems · 2025Article
- Breaking data silos: incorporating the DICOM imaging standard into the OMOP CDM to enable multimodal research.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Advancing Global Cancer Symptom Science: Insights and Strategies From the Inaugural Cancer Symptom Science Expert Meeting.Oncology nursing forum · 2025Article
- Advancing Global Cancer Symptom Science: Insights and Strategies from the Inaugural Cancer Symptom Science Expert Meeting.Seminars in oncology nursing · 2025Article
43 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveTo evaluate common data models (CDMs) to determine which is best suited for sharing data from a large, longitudinal, electronic health record (EHR)-based community registry. MATERIALS AND
methodsFour CDMs were chosen from models in use for clinical research data: Sentinel v5.0 (referred to as the Mini-Sentinel CDM in previous versions), PCORnet v3.0 (an extension of the Mini-Sentinel CDM), OMOP v5.0, and CDISC SDTM v1.4. Each model was evaluated against 11 criteria adapted from previous research. The criteria fell into six categories: content coverage, integrity, flexibility, ease of querying, standards compatibility, and ease and extent of implementation.
resultsThe OMOP CDM accommodated the highest percentage of our data elements (76%), fared well on other requirements, and had broader terminology coverage than the other models. Sentinel and PCORnet fell short in content coverage with 37% and 48% matches respectively. Although SDTM accommodated a significant percentage of data elements (55% true matches), 45% of the data elements mapped to SDTM's extension mechanism, known as Supplemental Qualifiers, increasing the number of joins required to query the data.
conclusionThe OMOP CDM best met the criteria for supporting data sharing from longitudinal EHR-based studies. Conclusions may differ for other uses and associated data element sets, but the methodology reported here is easily adaptable to common data model evaluation for other uses.
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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.