Real-World Data from EHRs and Claims: Strengths, Limitations, and Regulatory Impact

Real-World Data from EHRs and Claims: Strengths, Limitations, and Regulatory Impact

Real-world data (RWD) from Electronic Health Records (EHRs) and claims offers significant value for pharmaceutical research and regulatory submissions. However, understanding its inherent strengths and limitations is crucial for effective utilization. As the FDA and EMA increasingly accept real-world evidence (RWE) in regulatory filings, BD teams and investors need a clear-eyed view of what these data sources can—and cannot—deliver for drug development and commercialization strategies.

Key Takeaways

• RWD from EHRs and claims is increasingly vital for pharmaceutical research and regulatory submissions, with the FDA issuing formal guidance on assessing these data sources to support drug and biological product decisions.
• Strengths include comprehensive patient information, longitudinal tracking, diverse data types, and the ability to capture treatment patterns across large, real-world populations—enabling strong evidence generation beyond clinical trial settings.
• Key limitations involve missing data, data entry errors, interoperability challenges, patient adherence gaps, and systemic biases inherent in how EHR and claims data are collected and coded.
• Understanding these strengths and limitations is critical for regulatory compliance, strategic BD planning, and accurate assessment of RWE-based assets in licensing and partnership evaluations.

The Evolving Landscape of Real-World Data in Pharma

The pharmaceutical industry's reliance on real-world data has shifted from supplementary to strategic. In December 2021, the FDA issued a finalized guidance document—Real-World Data: Assessing Electronic Health Records and Medical Claims Data to Support Regulatory Decision-Making for Drug and Biological Products—establishing a framework for sponsors aiming to use RWD sources to support regulatory decisions and labeling. This guidance, published in the Federal Register, signals the agency's formal acceptance that EHR and claims data can serve as primary or supportive evidence in submissions when data quality and fitness-for-use standards are met.

Real-world data examples span electronic health records containing clinical notes, lab results, and diagnostic codes, paired with administrative claims capturing pharmacy dispensing, procedure codes, and billing information. Together, these sources offer a more complete picture of patient journeys than either could alone. The European Medicines Agency has similarly advanced its own RWE framework, creating parallel expectations for multinational submissions. For pharma BD teams evaluating assets with RWE components, this regulatory maturity means real-world evidence examples are no longer theoretical—they are appearing in label expansions, post-market commitments, and increasingly in pre-approval discussions.

What Are the Strengths of EHR and Claims Data?

EHR data enhances patient care and safety by providing clinicians with comprehensive, accessible patient information at the point of care. The nine main benefits of EHRs include optimized efficiencies and productivity, enhanced coordination among healthcare providers, stronger data security and privacy controls, reduced paperwork and administrative costs, easier access to patient information, and enhanced clinical decision-making. These operational advantages translate directly into research value: EHRs capture granular clinical detail—vital signs, lab values, imaging results, physician assessments—that claims data alone cannot provide.

Claims data, meanwhile, excels at mapping treatment patterns, healthcare utilization, and longitudinal patient trajectories across providers and settings. Because claims are generated for payment purposes, they offer structured, standardized coding that enables large-scale analyses of drug exposure, switching behavior, and outcomes. The synergy is clear: EHR data fills in clinical nuance, while claims data provides the population-level denominators and longitudinal coverage that EHRs—often siloed within single health systems—cannot match. For investors and analysts assessing RWE-based evidence generation platforms, this combined approach represents the current gold standard in real-world evidence data infrastructure.

What Are the Challenges to Using Electronic Health Records?

Despite their promise, EHR and claims data carry well-documented limitations that BD teams and regulatory strategists must factor into decision-making. According to research published in Pharmacoepidemiology and Drug Safety, sources of bias and error in EHR data include: missing data (EHRs only capture encounters within a given health system, creating gaps when patients seek care elsewhere), data entry errors (multiple input methods contribute to inconsistency), patient adherence and compliance gaps (prescription records in the EHR do not confirm medication was taken), and changes over time (system updates, coding modifications, and practice pattern shifts can alter data structure and meaning).

Seven additional challenges outlined in the clinical quality improvement literature compound these issues: clinician workflow constraints that make appropriate data entry difficult, alert fatigue from system-generated notifications, interoperability failures between EHR platforms, poor visual display design that obscures critical information, inconsistent availability of relevant data fields, system automation and defaults that may introduce systematic errors, and inadequate workflow support tools. For claims data specifically, a key limitation is that dispensed prescriptions may not generate insurance claims—particularly for cash-paying patients or those with high-deductible plans—creating underreporting bias that can skew exposure-outcome analyses.

Implications for Pharma Business Development and Regulatory Teams

For BD teams evaluating partnerships, licensing targets, or acquisitions involving RWE capabilities, the quality and provenance of underlying data assets matter as much as the analytical methods applied to them. A platform built on fragmented EHR data from a single health system without claims linkage carries fundamentally different risk than one integrating multi-source, longitudinally linked datasets. Regulatory acceptance hinges on data standards for drug and biological product submissions containing real-world data—the FDA's guidance explicitly requires sponsors to demonstrate data fitness for use, including assessment of data quality, completeness, and relevance to the regulatory question.

Regulatory affairs teams must now build RWE strategies into submission planning earlier in the development cycle. The FDA's finalized guidance means that post-market commitments, label expansion applications, and even certain efficacy supplements can be supported by EHR and claims-derived evidence—provided the data meet the agency's standards for reliability and relevance. For investors, the practical takeaway is that RWE maturity is becoming a competitive differentiator: companies with validated, regulatory-grade real-world evidence data infrastructure are better positioned to accelerate timelines, reduce development costs, and generate the evidence packages that regulators increasingly expect.

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