Free and Low-Cost RWE Data: From Clinical to Commercial Operations

Written By Chaney O

Executive Summary

Real-World Evidence (RWE) is increasingly essential for securing FDA approvals, accelerating reimbursement, and understanding U.S. market penetration. While access to proprietary claims databases is costly, numerous free, publicly available government and regulatory datasets offer high-value insights, supplemented by strategic access to low-cost, patient-level data.

This guide details the top free and low-cost RWE sources in the U.S., categorized by their primary use case (Safety, Regulatory/Clinical, or Epidemiology).

U.S. Free RWE Data Sources

These sources, managed primarily by the FDA, CMS and HHS, are critical for use cases such as competitive analysis, safety monitoring, establishing disease prevalence and cost benefit analysis.

  • FAERS (FDA)

    • Use Case Focus: Safety/PV

    • Key Value & Data Type: Drug Adverse Events: Reports on drug side effects, medication errors, and quality problems. Essential for post-market safety and competitive risk profile monitoring.

  • MAUDE (FDA)

    • Use Case Focus: Safety/PV

    • Key Value & Data Type: Medical Device Adverse Events: Mandatory and voluntary reports of device-related injuries, malfunctions, and deaths. Critical for medtech post-market surveillance.

  • ClinicalTrials.gov (NIH)

    • Use Case Focus: Regulatory/Clinical

    • Key Value & Data Type: Trial Design & Results: Database of public and private clinical studies. Use for competitor trial design, recruitment metrics, and published results.

  • NHANES (CDC)

    • Use Case Focus: Epidemiology

    • Key Value & Data Type: Population Health & Nutrition: Surveys on health and nutritional status of U.S. adults and children. Excellent for establishing prevalence, baseline health indicators, and comorbidities.

  • SEER Program (NCI)

    • Use Case Focus: Epidemiology

    • Key Value & Data Type: Cancer Incidence & Survival: Comprehensive data on incidence, prevalence, and survival rates for cancer across the U.S. Indispensable for oncology companies.

  • CMS Data Navigator (CMS/HHS)

    • Use Case Focus: Market/Claims

    • Key Value & Data Type: Medicare/Medicaid Summaries: Public-use files and research summaries providing de-identified aggregated claims data (e.g., physician payment, cost of care). Useful for market access and economic modeling.

  • Drugs@FDA (FDA)

    • Use Case Focus: Regulatory

    • Key Value & Data Type: Approval History & Labeling: Comprehensive list of approved drugs and therapeutic biological products, including full prescribing information (labels).

Accessing Patient-Level CMS Data

While the data sources above are free, the true RWE gold standard—patient-level claims data—is accessed via the paid CMS Virtual Research Data Center (VRDC).

  • Cost vs. Value: VRDC access is significantly cheaper than commercial claims databases and provides access to the claims history for virtually 100% of Medicare and Medicaid-enrolled populations.

  • Mechanism: This is a secure, cloud-based platform where researchers analyze the de-identified patient data.

  • Patient-Level Claims Linkage: Allows sponsors to link clinical trial cohorts or other clinical data to longitudinal claims data, generating safety, utilization, and cost-effectiveness evidence—key inputs for U.S. reimbursement discussions and real-world product positioning.

  • Access Guidance: International companies should plan to partner with a U.S. research institution or CRO that holds an existing Data Use Agreement (DUA) or can serve as the designated applicant and custodian for the data, as the process is smoother if the Principal Investigator (PI) is U.S.-based.

Key Caveats and Limitations

  • Time Lag: Publicly reported data often has a significant time lag (6–24 months) between event occurrence and public release. This data is not real-time.

  • Access to Patient Data: Accessing de-identified, patient-level claims data (VRDC) is paid and requires an approved research proposal and security compliance. Free public datasets are only aggregated summaries.

  • Age subset limits and gaps: Medicare VRDC data primarily covers ages 65+. Medicaid VRDC data covers a broader population but exhibits data quality and completeness issues including longitudinal gaps.

  • Data quality: The quality of the data is often highly variable and depends on the originating agency or reporting body.

  • Underreporting: Post-market surveillance systems (FAERS, MAUDE) are prone to significant underreporting and biases. They are excellent for signal detection but poor for estimating true incidence rates.

Resources

Chaney O
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