HealthVerity

Real-world data marketplace and identity resolution platform linking de-identified patient records for evidence and commercial use.

HealthVerity, founded in 2014 and headquartered in Philadelphia, Pennsylvania, operates a data marketplace and identity-resolution technology for licensing and linking de-identified real-world healthcare data — claims, pharmacy, lab, and EHR sources — used by pharmaceutical commercial, outcomes research, and safety teams. The company has raised funding through a Series D round. Its site documents HIPAA compliance practices, including expert-determination de-identification for linked datasets. As with any data platform, coverage in your specific indication should be validated before contracting. In May 2026 HealthVerity completed its acquisition of Symphony Health, adding Symphony's commercial analytics and prescription data assets to the combined company.

Headquarters
Philadelphia, United States
Founded
2014
Compliance
HIPAA
Deployment options
cloud
Website
https://healthverity.com
LinkedIn
https://www.linkedin.com/company/healthverity

Categories

AI Use Cases

  • Patient Identification & Segmentation

Vendor Scorecard

64% — Partial coverage. Coverage score — how completely Atlas documents HealthVerity across 7 buyer-evaluation areas. Reflects available Atlas data, not solution quality.

Compliance & Validation — Documented

HIPAA

Deployment & Hosting — Documented

cloud

Pricing Transparency — Not documented by Atlas

Ask the vendor: What is your pricing model, and what drives total cost of ownership?

Implementation & Onboarding — Not documented by Atlas

Ask the vendor: What is a realistic implementation timeline, and what onboarding support is included?

Organization & Role Fit — Documented

Mid-Size Biotech, Large Pharma, Top 20 Pharma, Commercial, Data Management, Data Engineer / Architect

Solution Scope — Documented

Real-World Evidence

Company Viability — Partially documented

Series D, Founded 2014

Always ask the vendor

Not captured in Atlas data — confirm directly. Excluded from the score above.

Data Rights & IP

Who owns model outputs? Is our proprietary data used to train models others can access, and where does our data reside?

Model Credibility & Explainability

Can you share validation studies or benchmarks, explain how the model reaches its conclusions, and describe how bias and drift are monitored?

Questions to Ask This Vendor

  • What patient counts exist in our indication across the linked data sources?
  • How is expert determination documented for the specific datasets we would license?
  • What are the refresh frequencies for claims, pharmacy, and EHR feeds?
  • How does identity resolution accuracy get measured and reported?