The pharmaceutical industry is hitting a wall. Data aggregators, once considered reliable partners, are now liabilities facing significant challenges, including cyber threats, data restrictions, and opaque sourcing. With legal and cyber events significantly reducing available data, aggregators have begun losing credibility and market share. In contrast, marketplace models are rapidly emerging as more transparent, sustainable solutions for obtaining Verified real-world data (RWD).
Recent events underscore aggregator vulnerabilities:
A marketplace model, demonstrated by HealthVerity Marketplace, counters these challenges:
HealthVerity Marketplace supports a Verified data ecosystem built on three foundational pillars:
The SEPRA trial (NCT03596450) utilized HealthVerity Marketplace Identity Manager through the HVID to effectively link clinical trial participants with real-world data.2,3 Our privacy-preserving record linkage technology securely converted SEPRA participants’ personally identifiable information into unique, persistent tokens. These tokens were matched against HealthVerity's extensive real-world data resources to identify participants who had available closed medical or pharmacy claims data in the year prior to their randomization between July 2017 and October 2020.3
The researchers compared the group in the trial to their broader health data from HealthVerity to:
The results showed that out of 1,278 participants, 1,107 (87%) were tokenized with an HVID and 633 (49.5%) had claims data available during the licensed data time period.3 Further, the baseline characteristics observed in the overall trial population were similar to those found in the HealthVerity claims data (Figure 1). This suggests that the trial population closely mirrors real-world patients thereby increasing external validity of the clinical trial.
Figure 1. Baseline characteristics of the SEPRA trial population (N=1,278) compared with participants matched to HealthVerity claims data (N=633). The chart illustrates age, gender, region, and treatment category distribution across both datasets, showing strong demographic alignment. Baseline characteristics observed in the overall trial population were similar to those found in the HealthVerity claims data. Figure created using data from clinical trial NCT03596450 and the ISPOR 2023 poster presented by Novo Nordisk Inc (Poster ID: SA16).
HealthVerity Identity Manager, which utilizes the HVID, has demonstrated superior accuracy in patient matching compared to legacy tokenization techniques, achieving approximately 0.2% false positive and 3-5% false negative rates. Traditional deterministic methods report significantly higher error rates, between 1-3% false positives and 9–42% false negatives (Figure 2).4,5 This capability enables comprehensive insights into patient outcomes and adherence patterns, critical for effective real-world evidence generation.
Figure 2. HealthVerity identity management technology achieves a considerable improvement over legacy de-identification methodologies with a lower false positive and false negative rate while maintaining high accuracy.
Pharmaceutical companies and consulting groups are increasingly recommending marketplace models. By shifting from traditional aggregators to HealthVerity Marketplace, pharma can achieve:
And discovery is just as important as access. HealthVerity taXonomy and taXOnomy help pharma teams identify precise patient cohorts across open and closed claims, lab, and EHR sources without relying on outdated or inconsistent field logic. These solutions make it easy to define medically relevant populations at scale, then link that data across sources in a verified, privacy-preserving way. It’s how life sciences leaders are transforming static datasets into flexible, high-trust tools for market analysis, brand strategy, and real-world evidence.
The shift towards transparent, marketplace-driven data ecosystems represents a fundamental evolution in how pharma obtains and utilizes real-world data. HealthVerity Marketplace is uniquely positioned to support this transformation, providing data integrity, transparency, and actionable insights that aggregators simply can no longer reliably deliver. Contact our sales team to learn more or schedule a demo for Marketplace or for taXonomy below.
¹ Kranz, A. M., Dworsky, M., Ryan, J., Heins, S. E., & Bhandarkar, M. (2023). State All Payer Claims Databases: Identifying Challenges and Opportunities for Conducting Patient-Centered Outcomes Research and Multi-State Studies. RAND Corporation.
https://aspe.hhs.gov/sites/default/files/documents/a2add9e2d2e196f240357fee73cf3990/APCD-PCOR-Report-2023.pdf
² Brantley, J. (2022). Overcoming Data Fragmentation is Key to Avoiding Future Health Care Crises. Medical Economics.
https://www.medicaleconomics.com/view/overcoming-data-fragmentation-is-key-to-avoiding-future-health-care-crises
³ Chung, S. C., Toh, S., & Wang, S. V. (2023). Leveraging national insurance claims data for insights on rare diseases: a public health approach. BMJ Public Health, 2(1), e000346.
https://bmjpublichealth.bmj.com/content/2/1/e000346