Refining Rare Disease Targeting with Real-World Data

A mid-sized pharmaceutical company leveraged NorstellaLinQ to refine rare disease patient targeting with integrated real-world data. By combining EHR physician notes, claims data, and patient journey analysis, the company identified overlooked patient populations, mapped the physicians diagnosing and treating them, and generated actionable insights to improve commercial targeting and early product planning. The company:

Learned how intermediate-risk cancer patients were diagnosed and treated
Learned diagnosis and treatment information for rare disease patients with an uncommon ICD-10 code and biomarker tests

Key Results

Refined Rare Disease Patient Populations for More Precise Targeting

Challenge

The company wanted to identify the prevalence, diagnosis, and treatment journey of an often misdiagnosed sub-population who do not always test positive for a disease biomarker but are still associated with the disease.

Solution

NorstellaLinQ’s EHR unstructured physicians’ notes plus open claims diagnosis-based business rules identified a narrower patient population. This included patients who underwent biomarker testing but didn’t receive a positive result, yet exhibited common comorbidities associated with the disease.

A patient journey analysis identified the most frequent diagnostic sites for accurate diagnosis and treatment. Then, the team mapped physicians performing tests and adhering to treatment guidelines for each condition.

Outcome

Norstella, using NorstellaLinQ, outlined the business rules used for patient population refinement and trends in biomarker testing and treatment for intermediate-risk cancer and the rare disease. A site and NPI map of physicians conducting diagnostic tests, segmented by focus geographies and conditions, helped the client with physician targeting and marketing efforts.

The insights were used by multiple teams to develop target product profiles for pipeline agents across both indications, aiding strategic decision-making.

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Frequently asked questions

Everything You Need to Know

How can real-world data improve rare disease patient targeting?

By combining EHR physician notes, claims data and patient journey analysis, integrated real-world data helps identify overlooked patient populations, refine patient cohorts and uncover actionable insights for more precise commercial targeting.

Why are unstructured EHR notes valuable for rare disease research?

Unstructured physician notes capture clinical details that structured datasets may miss, such as biomarker testing history, comorbidities and diagnostic context. These insights help identify patients who may not meet traditional diagnostic criteria but are still associated with the disease.

How does patient journey analysis support physician targeting?

Patient journey analysis identifies where patients are diagnosed and treated, then maps the physicians conducting diagnostic testing and following treatment guidelines. This enables more targeted physician engagement and marketing strategies.

What challenge did Norstella help solve in this case study?

The pharmaceutical company needed to identify and better understand an often-misdiagnosed rare disease sub-population that did not always test positive for a disease biomarker. Norstella refined the patient population using integrated real-world data and advanced business rules to improve targeting accuracy.

What business outcomes did the project deliver?

Norstella provided refined patient population definitions, biomarker testing and treatment trend analyses, and NPI-level physician mapping that helped improve physician targeting, marketing efforts and target product profile development for pipeline therapies.