Case Study: National Institutes of Health achieves a centralized, AI-driven COVID-19 data lake with Adeptia

Learn the part Adeptia played in making this COVID data accessible to researchers, helping the NIH fight the pandemic

Adeptia partnered with the NIH’s N3C effort to help consolidate and standardize patient-level COVID‑19 data coming from thousands of labs, hospitals and research groups in different formats and common data models. The challenge was to rapidly collect, normalize and quality-check high‑volume, nationally representative clinical, lab and demographic data so researchers and policymakers could answer urgent questions about treatments, risk factors and public‑health strategies.

Adeptia provided an AI‑driven, self‑service data integration pipeline that automated ingestion, data‑quality checks, COVID LOINC encoding and transformation into OMOP 5.3, enabling centralized merging on a secure analytics platform. The result is the largest U.S. row‑level COVID‑19 database, supporting ZIP‑code‑level tracking, machine‑learning research and far faster access for epidemiologists and clinicians to inform testing, treatment, CDS and public‑health decisions.

National Institutes of Health