ArticleJournal of the American Medical Informatics Association : JAMIA
Development and evaluation of a common data model enabling active drug safety surveillance using disparate healthcare databases.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 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
69 citing papers in PubMed, 107 citations in OpenAlex.
- 'Crossing borders' in data standardisation: application of OMOP CDM in an international clinical trial network in precision cancer medicine.Acta oncologica (Stockholm, Sweden) · 2026Article
- Preparing real-world data through common data model harmonization of cancer patient records in the COMNet platform at the Modena Oncology Center.Frontiers in digital health · 2026Article
- Development of a big data platform for collecting and utilizing clinical information from the Korea Biobank Network.BMC medical informatics and decision making · 2025Article
- Success and Challenges Querying OMOP-transformed EHR Data from Different Healthcare Organizations.ACI open · 2025Article
- AI-Powered Drug Classification and Indication Mapping for Pharmacoepidemiologic Studies: Prompt Development and Validation.JMIR AI · 2025Article
- Extensive benchmarking of a method that estimates external model performance from limited statistical characteristics.NPJ digital medicine · 2025Article
- Perspective review: Will generative AI make common data models obsolete in future analyses of distributed data networks?Therapeutic advances in drug safety · 2025Review
- A Comparison of the Impact of Pharmacological Treatments on Cardioversion, Rate Control, and Mortality in Data-Driven Atrial Fibrillation Phenotypes in Critical Care.Bioengineering (Basel, Switzerland) · 2024Article
- European Health Data & Evidence Network-learnings from building out a standardized international health data network.Journal of the American Medical Informatics Association : JAMIA · 2023Observational
- Advancing Toward a Common Data Model in Ophthalmology: Gap Analysis of General Eye Examination Concepts to Standard Observational Medical Outcomes Partnership (OMOP) Concepts.Ophthalmology science · 2023Article
- Methods Used in the Development of Common Data Models for Health Data: Scoping Review.JMIR medical informatics · 2023Article
- Review
- Generating synthetic data from administrative health records for drug safety and effectiveness studies.International journal of population data science · 2023Article
- A Data-Driven Reference Standard for Adverse Drug Reaction (RS-ADR) Signal Assessment: Development and Validation.Journal of medical Internet research · 2022Article
- Leveraging Machine Learning to Facilitate Individual Case Causality Assessment of Adverse Drug Reactions.Drug safety · 2022Article
- Applying the OMOP Common Data Model to Facilitate Benefit-Risk Assessments of Medicinal Products Using Real-World Data from Singapore and South Korea.Healthcare informatics research · 2022Article
- Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Co-establishing an infrastructure for routine data collection to address disparities in infant mortality: planning and implementation.BMC health services research · 2022Article
- Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS.Clinical epidemiology · 2022Article
- Association between the use of allopurinol and risk of increased thyroid-stimulating hormone level.Scientific reports · 2021Observational
9 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
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveActive drug safety surveillance may be enhanced by analysis of multiple observational healthcare databases, including administrative claims and electronic health records. The objective of this study was to develop and evaluate a common data model (CDM) enabling rapid, comparable, systematic analyses across disparate observational data sources to identify and evaluate the effects of medicines.
designThe CDM uses a person-centric design, with attributes for demographics, drug exposures, and condition occurrence. Drug eras, constructed to represent periods of persistent drug use, are derived from available elements from pharmacy dispensings, prescriptions written, and other medication history. Condition eras aggregate diagnoses that occur within a single episode of care. Drugs and conditions from source data are mapped to biomedical ontologies to standardize terminologies and enable analyses of higher-order effects. MEASUREMENTS: The CDM was applied to two source types: an administrative claims and an electronic medical record database. Descriptive statistics were used to evaluate transformation rules. Two case studies demonstrate the ability of the CDM to enable standard analyses across disparate sources: analyses of persons exposed to rofecoxib and persons with an acute myocardial infarction.
resultsOver 43 million persons, with nearly 1 billion drug exposures and 3.7 billion condition occurrences from both databases were successfully transformed into the CDM. An analysis routine applied to transformed data from each database produced consistent, comparable results.
conclusionA CDM can normalize the structure and content of disparate observational data, enabling standardized analyses that are meaningfully comparable when assessing the effects of medicines.
Indexed as
Identifiers
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.