Linked Oncology Data is Becoming a Biopharma Priority

Key Points:

• Linked oncology real-world data is already in use, but confidence in how data is linked still lags.
• Respondents reported linking to two or more data types. Yet, only 32% said they use all four major oncology data types covered in the survey: electronic health records, open claims, closed claims and genomics.
• The biggest challenges are around data quality, not data volume, with participants citing patient-matching accuracy, missing or incomplete data capture, and inconsistent coding definitions across sources.
• The market is moving quickly toward a more integrated future. More than 60% of respondents expect linked oncology data to become standard practice within two years, and 72% of non-users said a ready-to-use, pre-linked oncology dataset would be very or extremely valuable.

  ---

Real-world data (RWD) has become a strategic asset across the life sciences product lifecycle, especially in oncology, where longitudinal and multimodal data are increasingly important for understanding patient journeys, treatment decisions and outcomes. The State of Linked Oncology Real-World Data, a 2026 report from Ontada and McKesson Compile, reveals an industry in transition.

Based on a survey of 100 senior-level life sciences professionals across health economics and outcomes research (HEOR), market access, commercial, real-world evidence and data analytics, the findings show that organizations have largely moved beyond relying on single-source data, but still face significant challenges in linking multiple data sources, such as electronic health records (EHR), claims and genomics data, accurately, efficiently and with reliability.

The report points to a clear shift in how life sciences organizations are thinking about oncology RWD. “The conversation is moving from data volume to data confidence,” said Amy Sheide, chief data officer, Ontada. “As precision medicine advances, it becomes increasingly important to understand the patient journey in a meaningful way and to trust that the data can support clinical and commercial decisions.”

The report notes that precision therapies now represent a growing share of oncology drug development, with roughly half of approvals guided by biomarker testing. In that environment, the value of data depends not just on scale, but on whether it can support informed decisions across evidence generation, market access and commercialization.

Why a More Complete Patient Journey Matters

Forty-seven percent of survey respondents most often cited patient journey and treatment patterns as a top use case for linked oncology real-world data, tied with comparative effectiveness and real-world evidence studies. That tracks with the broader reality of cancer care: no single source can fully capture the complexity of treatment over time across providers, sites of care and lines of therapy.

EHR data was the most widely used data type in the survey, and use of claims and genomics data was also high. Even so, only 32% of respondents said they use all four major oncology data types covered in the survey. In practice, that suggests that many teams are still working with an incomplete view of the patient journey, even as they recognize how foundational a more complete view has become.

Confidence Matters as Much as Access

One of the clearest findings in the report is that the challenge is no longer access to data alone. It is the work required to connect data from different sources and trust it. Sixty-five percent of respondents said their teams access EHR and claims data separately and stitch them together internally.

At the same time, the top challenges with linking data were all quality-related:

• patient-matching accuracy (44%)
• missing or incomplete data capture (38%)
• differences in coding and definitions across sources (36%)

Those findings reinforce a practical tension in oncology RWD analytics today. If teams spend too much time preparing the data as well as validating whether it is reliable, they have less time to focus on the questions that drive evidence generation, launch planning and in-market decision-making.

What Teams Want Next

The future state described by respondents is not simply more comprehensive data. It is data that arrives faster, with clearer methodology and less internal burden. When asked what would make linked oncology data more useful, respondents most often cited:

• Faster refresh cycles and near real-time availability (30%)
• Data quality, accuracy, assurance and transparency (22%)
• More seamless EHR and claims integration for a unified patient journey (21%)

What This May Signal for Oncology Evidence Generation

Taken together, the findings suggest that the next phase of oncology RWD adoption may be shaped less by how many datasets organizations can access and more by how well those datasets are linked, validated and delivered for real use. For life sciences teams working across clinical and commercial decisions, that shift could help turn more data into more actionable insight.

“The opportunity ahead isn’t simply to gather more data,” Sheide said. “It’s to strengthen confidence in the data teams rely on and ensure it can support meaningful clinical and commercial decisions.”