We believe healthcare data science should be open, reproducible, and accessible. Our research and open-source contributions advance the entire field.
The Observational Health Data Sciences and Informatics (OHDSI) community is an international collaborative dedicated to generating reliable evidence from observational health data. With over 400 collaborators across 80+ countries, OHDSI maintains the OMOP Common Data Model (CDM) — the gold standard for transforming disparate healthcare data into a unified, analyzable format.
Acumenus Data Sciences is a premier OHDSI partner, contributing both technical infrastructure and clinical expertise to the community. We actively participate in network studies, develop open-source tools that extend the OHDSI ecosystem, and help healthcare organizations adopt the OMOP CDM for research and operations.
Our commitment to OHDSI reflects our core belief: standardized data, open methods, and transparent analysis are the foundation of trustworthy healthcare evidence. Every platform we build speaks OMOP, and every engagement we deliver strengthens the network.
Production-hardened OHDSI Broadsea distribution with Python-based configurator for rapid ecosystem deployment.
Production-ready ETL for transforming Synthea synthetic patient data into the OMOP CDM for testing and validation.
Active participation in OHDSI network studies with standardized analytics packages and reproducible results.
Helping academic medical centers and health systems adopt OHDSI tools through hands-on implementation support.
Contributing to data quality assessment workflows, vocabulary mapping validation, and CDM conformance testing.
All of our core platforms and research tools are released as open-source software. We believe transparency accelerates progress across the healthcare data community.
Rett syndrome is a rare neurodevelopmental disorder affecting approximately 1 in 10,000 females, caused by mutations in the MECP2 gene. Patients experience regression of acquired skills, loss of purposeful hand use, breathing irregularities, and seizures. Research is hampered by small, geographically dispersed patient populations and fragmented clinical data.
Acumenus partnered with the International Rett Syndrome Foundation to develop data infrastructure for natural history studies. By mapping the IRSF patient registry data to the OMOP Common Data Model, we enabled the foundation's research team to apply standardized analytics, define patient cohorts using ATLAS, and participate in OHDSI network studies alongside major academic medical centers.
This work demonstrates a replicable model for rare disease foundations: standardize your patient registry data to OMOP, leverage the open-source OHDSI toolchain, and unlock the same research capabilities available to the world's largest health systems — regardless of your organization's size.
"Working with Acumenus transformed our ability to conduct meaningful research. By standardizing our patient registry data to the OMOP Common Data Model, we gained access to a world-class analytics toolchain that we never could have built on our own. For the first time, our small foundation can participate in the same types of observational studies that major academic medical centers conduct."
IRSF Research Team
International Rett Syndrome Foundation
Registry Standardized
CDM Deployed
Generating actionable evidence from routine clinical data requires rigorous methodology, standardized data, and transparent analysis. We bring all three to every engagement.
The foundation of reliable real-world evidence is high-quality, standardized data. We transform clinical, claims, and registry data into the OMOP Common Data Model, enabling reproducible analysis across institutions and data sources.
Rigorous observational study design using OHDSI best practices. We build cohort definitions in ATLAS, implement analytics using HADES R packages, and execute studies with full reproducibility and transparency.
Research that stays in a database doesn't improve patient care. We help translate findings into clinical action through publication support, stakeholder communication, and integration into decision support systems.
Whether you're a rare disease foundation seeking to standardize your registry, a health system joining the OHDSI network, or a research team looking for technical collaborators, we'd love to hear from you.