Why Claims Data Alone Leave Gaps in Understanding the Patient Journey
In today’s precision medicine landscape, pharmaceutical companies and access teams face a critical challenge: understanding not just whether therapies work, but how they are accessed, adopted, and experienced by real-world patients. This requires going beyond traditional data sources, particularly claims data, which—while useful—often fails to capture the nuanced clinical and diagnostic steps that define the ... Read More


In today’s precision medicine landscape, pharmaceutical companies and access teams face a critical challenge: understanding not just whether therapies work, but how they are accessed, adopted, and experienced by real-world patients. This requires going beyond traditional data sources, particularly claims data, which—while useful—often fails to capture the nuanced clinical and diagnostic steps that define the patient journey. To truly understand and improve therapy adoption, stakeholders need a more complete, context-rich view of real-world care pathways.
The Limits of Traditional Data Sources in Market Access
In precision medicine today, market access isn’t just about generating real-world evidence; it also requires understanding how therapies are adopted across the complex care pathways patients experience in actual clinical practice. From diagnosis to testing to treatment, each step can introduce friction. Yet many commercial and analytics teams still rely almost entirely on claims data to better understand access and adoption patterns.
These datasets are foundational, but they’re not the whole story. They often fail to capture diagnostic details, treatment timing, and clinical decision-making that contribute to whether a therapy reaches the right patient at the right time.
What Claims Data Misses
Claims data provides a standardized and scalable view of healthcare utilization. It tracks procedures, medication fills, and billing activity across millions of patients. It’s especially useful for analyzing payer mix, treatment adherence, and high-level healthcare costs. But because claims data is built around billing, it often lacks the context needed to fully understand what happened during the patient journey. It may show that a molecular test was billed, but not what the result was, whether it was actionable, or how it influenced treatment. Timing can also be difficult to interpret, as billing events may not align precisely with when clinical decisions were made. Claims data may also miss non-billable services, leading to gaps in the complete picture of a patient’s care journey. For access teams trying to understand therapy adoption or treatment delays, this lack of context can leave critical questions unanswered.
Why Diagnostic Context Matters
Without these important pieces, market access teams face challenges that go beyond traditional data analysis. They struggle to quantify the real-world impact of diagnostic testing on therapy initiation and treatment outcomes. Questions such as, “Were patients delayed in starting treatment because test results were not available on time”” or “At what point in the care pathway are patients dropping off?” remain difficult to answer. Moreover, understanding variations in physician behavior, how providers across different institutions or regions interpret diagnostic tests and make treatment decisions, requires data that extends beyond what claims data can offer.
The Consequences of an Incomplete View
The consequence is a fragmented view of the patient journey. When decision makers rely solely on claims data, they may overlook important signals related to diagnostics timing, test outcomes, or how patients are moving, or not moving, through care. This incomplete picture can lead to market access strategies that do not fully account for barriers in real-world treatment adoption, resulting in missed opportunities to optimize therapy access and patient outcomes.
Augmenting Traditional Data with Structured Molecular Insights
To bridge these gaps, there is a growing need for solutions that can access and standardize the missing layers of information. This is where new models can start to fill in the gaps.
Federated data models present a promising approach. In these systems, data remains securely within each participating institution’s control while enabling pre-approved queries across multiple sources. These models can capture structured data from laboratory systems, imaging platforms, and pathology reporting systems, offering insights into the timing of tests, the outcomes of molecular and diagnostic assays, and the subsequent care sequence. Although federated platforms do not capture every nuance, such as the narrative behind a clinician’s decision, they do provide a clearer, data-driven view of what actually occurs across care pathways. By integrating these structured diagnostic elements with claims data, market access teams can obtain a more complete picture of the patient journey. This comprehensive view enables them to identify where patients experience delays or drop-offs, understand regional variations in provider behavior, and ultimately adjust strategies to ensure that the right therapies reach the right patients more efficiently.
The Path Toward a More Comprehensive Market Access Strategy
Claims data will always be a foundational part of real-world evidence generation. However, to meet the evolving demands of market access, it is important to augment these data sources with structured diagnostic insights. As the industry moves toward models that preserve institutional control while unlocking deeper, more granular data, the opportunity to connect the full care journey, from diagnosis to treatment, is possible.
As the stakes rise for delivering timely, equitable access to life-changing therapies, market access strategies must evolve beyond one-dimensional data sources. By combining the breadth of claims data with the depth of diagnostic insights enabled through federated models, pharmaceutical companies can finally illuminate the blind spots in the patient journey. This integrated approach isn’t just a data upgrade—it’s a strategic imperative for ensuring that innovations in precision medicine reach the patients who need them, when they need them most.
About Noah Nasser
Noah Nasser is the CEO of datma, a leading provider of federated Real-World Data platforms and related analytical tools. With more than twenty-five years of experience in biotechnology, Noah brings a broad background in developing and commercializing novel technology to advance human health, including serving as the CEO of Serimmune and Chief Commercial Officer roles at Human Longevity and Counsyl. Noah led Counsyl’s commercial team through its acquisition in 2018 by Myriad Genetics. He previously held senior leadership positions at AltheaDx and Verinata Health, a leader in non-invasive prenatal testing (NIPT), where he led his team through the company’s 2013 acquisition by Illumina.