See more of the patient, understand more of the market and make better-informed decisions throughout the product lifecycle.
Commercial data indicates the behavior. Clinical and medical signals reveal what’s behind it. Connect the two and you can uncover the patients, providers, patterns and market dynamics that otherwise remain hidden.
HealthVerity + Symphony Health unites those signals, including exclusive datasets, so that you can know what others can’t – from the decisions that shape development to those that drive commercial growth.
Commercial Intelligence
Connect pharmacy and payer data with medical, clinical and specialty signals to reveal more of the patients, providers, accounts, access dynamics and competitive dynamics shaping performance.
Clinical / RWE
Connect longitudinal claims, clinical, lab and other real-world signals to understand patient journeys, treatment patterns, outcomes and healthcare utilization in greater context.
Real-world evidence helps life sciences teams make more confident decisions by reflecting how patients experience care in the real world. HealthVerity Marketplace™ is built on data with scale, representativeness, longitudinal depth, stability and interoperability. With Symphony Health now part of the ecosystem, it includes best-in-class open pharmacy data, IC-grade medical benefit and products built for commercial teams across every therapeutic area. The result is more rigorous research, sharper subgroup analysis and clearer insight into patient journeys over time.
Understand diagnoses, procedures, encounters, utilization, payer activity and care settings.
Track prescription activity, treatment patterns, therapy progression and medication access.
Add clinical context from patient records, care encounters, diagnoses and provider documentation.
Support diagnostic confirmation, disease severity assessment, biomarker analysis and trigger-based research.
Add behavioral, demographic, lifestyle and social context that may influence access and outcomes.
Understand social determinants that can shape care access, adherence and health outcomes.
Add outcome signals that help complete longitudinal patient journeys.
Support therapeutic-area and fit-for-purpose research needs.
Identify, engage, and incentivize the highest-value healthcare providers and accounts.
Research-ready visibility into diagnoses, procedures and healthcare utilization.
Across recent HealthVerity analyses, we explored what becomes visible when additional clinical, medical and longitudinal signals are connected to the data already informing commercial and research decisions.
In a multiple myeloma analysis, incorporating medical-benefit activity alongside pharmacy claims changed the observed competitive ranking for an individual prescriber. A therapy initially ranked #2 moved to #1 when physician-administered treatments were included, revealing a different picture of competitive performance.
When additional patient and treatment activity was incorporated into an HCP analysis, up to 56% of Decile 6-7 HCPs were re-ranked. The expanded view changed the observed importance of certain providers, demonstrating how incremental data can influence targeting, segmentation and field resource allocation.
In a primary biliary cholangitis (PBC) analysis, clinical laboratory data identified elevated liver-enzyme signals a median of 481 days before the observed diagnosis. Connecting laboratory results with diagnosis history provided visibility into earlier clinical activity that diagnosis codes alone would not reveal.
In a study feasibility analysis, an initial population of 171,073 patients was refined to 49,252 after applying full protocol eligibility criteria. Even after this refinement, the identified population was 16.4 times the recruitment target, supporting a realistic assessment of study feasibility before recruitment begins.
In a rare disease analysis, expanding patient identification beyond prescription activity to include diagnosis signals made up to 45% more of the diagnosed population observable. This revealed patients whose disease was documented but whose treatment activity alone would not have identified them.
In a longitudinal data analysis, connecting additional patient records extended the observable history of 35.9 million patients by at least one year. This expanded the ability to examine events preceding and following important clinical milestones, supporting richer analyses of treatment patterns and patient journeys.
Because no other single source covers lab, pharmacy, medical claims and EHR at this scale - simultaneously. Starting here means you're never leaving coverage on the table before you've even begun.
Rare and specialty populations are hard to find in single-source data. The combined ecosystem surfaces patients and providers that traditional datasets miss entirely. What used to require three vendors and months of linkage work is now one starting point.
The data is already formatted, linked, and privacy-safe - delivered under a single contract. No stitching across vendors, no separate data use agreements, no months of normalization. Most teams are seeing insights in weeks, not quarters.
Yes, and it was built with that in mind. AI amplifies insight only when the underlying data is complete, trusted, and linkable. The combined ecosystem gives you the depth, representativeness, and longitudinal coverage that RWE-grade research and complex commercial models require now and as those models evolve.
Your current relationship stays intact, but your access just got significantly broader. Think of it as your existing investment unlocking a much larger ecosystem.