Insights on OMOP vocabularies, healthcare data standards, and observational health research.
Practical guides on OMOP vocabularies, healthcare data standardization, HEOR research methods, and observational health analytics. Written for data engineers, clinical informaticists, and researchers working with OHDSI tools.
A complete guide to the OHDSI data model (OMOP CDM). Learn its structure, tables, ETL workflows, vocabulary mapping, and best practices for real-world evidence.
Dr. Rachel Green
Learn FHIR to OMOP mapping with this developer guide. Covers terminology, ETL code examples, QA, and using OMOPHub to accelerate your data pipeline.
Alex Kumar, MS
Standardize clinical data for ETL, analytics, and AI using a healthcare mapping API. Explore use cases, API design, and best practices with OMOPHub code.
Dr. Jennifer Lee
OHDSI OMOP Common Data Model overview for technical users. Learn core tables, ETL, pitfalls & how OMOPHub simplifies workflows.
Dr. Emily Watson
Unlock the power of OMOP data. Our guide explains the CDM, vocabularies, ETL, best practices, and how OMOPHub APIs accelerate development and research.
David Thompson, PhD
Unlock the power of health care databases. Learn to navigate EHRs, claims data, and the OMOP model to build robust data pipelines for analytics and AI.
David Thompson, PhD
Unlock the power of openEHR and OMOP. This guide shows data engineers how to map clinical data, build robust ETL pipelines, and enable advanced AI analytics.
Michael Rodriguez, PhD
Unlock the power of Gene Ontology (GO) in your clinical data pipelines. This guide explains GO's structure, enrichment analysis, and integration with OMOP.
Dr. Rachel Green