Unlocking the Full Potential of Real-World Data: Claims and EHR Data Integration in Life Sciences

In the Life Sciences industry, real-world data (RWD) plays a critical role in driving insights for commercial strategies, health economics and outcomes research (HEOR), and drug development. Claims data, which has long been used as a valuable source of healthcare information, offers a broad view of patient interactions within the healthcare ecosystem. However, while claims data is essential for understanding healthcare utilization, reimbursement, and patient journeys, it often lacks the clinical depth necessary for more detailed research and clinical applications. This is where the integration of electronic health record (EHR) data comes into play, providing a more complete picture of patient health and outcomes.

Although claims are primarily a payment mechanism, advanced data science techniques can transform claims into a powerful resource for commercial, research, and clinical use cases. By analyzing claims data, Life Sciences professionals can gain insights into patient comorbidities, site of care, treatment patterns, and overall healthcare utilization. However, it's important to recognize that claims data alone may not answer every question—since it is focused on what is required for reimbursement, critical clinical details like symptoms, lab results, and diagnostic evaluations are often missing.

EHR data, on the other hand, typically contains more detailed clinical information, including patient details, lab tests and results, medications, and physician notes. Similar to claims data, EHR data in its raw form presents challenges and may also have gaps. For instance, if a patient receives care at multiple sites that don’t share medical records, key health information may be absent, limiting the completeness of the data.

A Brief Overview of Claims Data

Claims data represents information submitted by healthcare providers to insurers or clearinghouses for reimbursement. It can be categorized into two types: open and closed claims data.

• Open claims data, which comes from multiple sources, offers an unbiased view of patient interactions across the healthcare system, regardless of the insurer or provider, making it possible to track longitudinal patient journeys across different payers through the healthcare landscape with no limitations on time frame. Open claims may not, however, capture all healthcare interactions an individual may have. 
• Closed claims data provides a complete view of healthcare interactions within a single-payer network, as long as the patient remains enrolled with that payer, offering detailed information on treatments, diagnoses, and costs. Closed claims may take several weeks or months to be finalized, which can limit their usefulness for real-time decision-making.

Claims data typically includes demographic information (e.g., birth date, gender), site of care locations, diagnostic codes (ICD-10), procedure codes (CPT, HCPCS), prescription details (NDC codes), and reimbursement amounts. Because of its scale and detail, claims data is commonly used for HEOR studies, where its longitudinal nature allows for in-depth analyses of treatment patterns, healthcare costs, disease incidence, and more.

‍A Brief Overview of EHR Data

Electronic health records are digital files maintained by healthcare providers that capture both structured and unstructured patient data. Structured data in EHRs includes patient demographics, vital signs, medications, lab test results, and radiology images. Unstructured data includes clinical narratives like physician notes, discharge summaries, and other detailed observations that provide a comprehensive clinical context.

One of the main advantages of EHR data is its detailed clinical insights beyond billing codes, facilitating a deeper understanding of disease progression, treatment effectiveness, and patient outcomes. However, as rich as EHR data can be, it is often fragmented across different healthcare providers, leading to potential gaps when a patient’s records are spread across unconnected systems.

The Power of Integrating Claims and EHR Data

When claims data and EHR data are combined, professionals gain a much richer and more complete understanding of real-world patient experiences. Integration of these datasets enables more robust patient cohort identification, the creation of comprehensive patient journeys, and deeper studies of treatment effectiveness and patient outcomes.

By joining claims data with EHR data, companies can:

• Build more accurate and granular patient profiles.
• Enhance clinical research with both utilization and outcome data.
• Generate comprehensive evidence for regulatory submissions, HEOR studies, and market access strategies.

Integrating these data sources empowers teams to make more informed decisions, supporting everything from drug development to commercial strategies, ultimately improving patient care and outcomes.

As companies continue to explore the power of RWD, the integration of claims and EHR data offers the potential to unlock new insights, overcome existing data gaps, and provide a holistic view of the healthcare ecosystem. Let's keep the conversation going on LinkedIn or drop Kythera a line!