For Partners

“The goal should be to change the game entirely and use data to drive new capabilities around case management, predictive analytics, and population health management.”

Drew Ivan,
Chief Strategy Officer at Lyniate

As a healthcare partner, you need a reliable data foundation to support your products and services. We help systems integrators and technology partners solve the problem of dirty clinical data to improve downstream use cases such as quality reporting, clinical analytics, care coordination, population health, and risk adjustment. Our DCaaS SM solution ingests, curates, identity resolves, attributes, governs, and transmits clean clinical data. Our solution empowers partners to:

Access precision data
Access precision data
Achieve faster time-to-value with superior flexibility. We focus on the use cases most important to you and aggregate disparate data for a complete picture.
Audit Trail
See an “always on” audit trail
We provide transparency into everything that happens to your data from ingestion to delivery, so you have complete understanding of your data’s journey from incomplete to clean and curated.
Reduce administrative expenses
Reduce administrative expenses
A clean data foundation helps you address the most pressing clinical and business decisions while eliminating expenses from manual data retrieval and delivery activity.

Discover how health insights and quality data can paint a complete patient picture in our latest webinar featuring our partners at CentraForce Health.

Go well beyond standardizing and normalizing data

To date, Verinovum has ingested data from over 3,000 clinical locations and has successfully integrated from more than 35 EHRs. We are flexible in receiving data types across the HL7 2.x (ADT, ORU, VXU, MDM, etc), 3.x (CCD) and forthcoming 4.x (FHIR) continuum. We curate and enrich the data in two rounds, providing a lift in quality to make the data reliable and usable–amplifying the value of your solution for your customers.

Data Curation
Data Curation

DCaaS focuses on data quality in phases

Initial Curation

Build flexible structure maps

Apply standard code maps

Resolve patient identities (eMPI)

Create comprehensive patient record

Advanced Enrichment

Semantic and local code mapping

Fill NPI gaps

Encounter driven inference
(Data lift)

Curate to use case

Subset by roster

Transparent audit & data quality scoring


Data Curation as a Service (DCaaS)