ArticlePloS one2022
Extract, transform, load framework for the conversion of health databases to OMOP.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- 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
- Article
- Evaluating the statistical utility and information loss in the transformation of a real-world oncology database from CDISC-SDTM to OMOP-CDM.ESMO real world data and digital oncology · 2026Article
- Harmonizing patient health data into the OMOP common data model: a case study using tuberculosis data from Douala General Hospital, Cameroon.Frontiers in digital health · 2026Article
- Evaluating the impact of OMOP-CDM on data quality insight generation in respiratory disease management.Frontiers in big data · 2026Article
- Streamlining electronic medical record data extraction and validation in digital hospitals: A systematic review to identify optimal approaches and methods.Learning health systems · 2025Article
- Gap Analysis of Standard Automated Perimetry Concept Representation in Medical Terminologies.Journal of glaucoma · 2025Article
- Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective Observational Study by Using the Common Data Model.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- Use of Metadata-Driven Approaches for Data Harmonization in the Medical Domain: Scoping Review.JMIR medical informatics · 2024Article
- Recommendations for the collection and annotation of biosamples for analysis of biomarkers in neurofibromatosis and schwannomatosis clinical trials.Clinical trials (London, England) · 2024Review
- The standard problem.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record.The American journal of cardiology · 2023Review
- Observational
- Present and Future of Utilizing Healthcare Data.Healthcare informatics research · 2023Article
- Using A Standardized Nomenclature to Semantically Map Oncology-Related Concepts from Common Data Models to a Pediatric Cancer Data Model.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Factors affecting the changes in antihypertensive medications in patients with hypertension.Frontiers in cardiovascular medicine · 2022Article
- Measuring the impact of anonymization on real-world consolidated health datasets engineered for secondary research use: Experiments in the context of MODELHealth project.Frontiers in digital health · 2022Article
- Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies.Ophthalmology scienceArticle
- Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Common data models standardize the structures and semantics of health datasets, enabling reproducibility and large-scale studies that leverage the data from multiple locations and settings. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) is one of the leading common data models. While there is a strong incentive to convert datasets to OMOP, the conversion is time and resource-intensive, leaving the research community in need of tools for mapping data to OMOP. We propose an extract, transform, load (ETL) framework that is metadata-driven and generic across source datasets. The ETL framework uses a new data manipulation language (DML) that organizes SQL snippets in YAML. Our framework includes a compiler that converts YAML files with mapping logic into an ETL script. Access to the ETL framework is available via a web application, allowing users to upload and edit YAML files via web editor and obtain an ETL SQL script for use in development environments. The structure of the DML maximizes readability, refactoring, and maintainability, while minimizing technical debt and standardizing the writing of ETL operations for mapping to OMOP. Our framework also supports transparency of the mapping process and reuse by different institutions.
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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.