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Real-World Medical Data
in Small Patient Groups
Analyzing patient data for a rare disease (orphan disease) is often a complex undertaking – and differentiating between two nearly identical disease patterns presents a particular challenge.
In this case study, we demonstrate how our Patient Insights Analytics delivers scientifically valid results even with relatively small patient groups by leveraging real-world medical data.
Project Overview:
- Retrospective cohort study
- Algorithms for data aggregation and analysis
- Distinguishing between two indications with similar treatment methods
- Identifying country-specific information on patient characteristics, dosage, and persistence
As a result, the cohort study successfully identified all desired parameters regarding demographics and persistence in the respective patient groups.
The application-related questions were answered using anonymized statutory health insurance (SHI) billing data. The biopharmaceutical company UCB presented its study to a specialist audience at the 97th Annual Congress of the German Society for Neurology. Our case study on this client project explains how Insight Health contributed to the retrospective cohort study by analyzing real-world medical data.
"Together with neurology experts from UCB, we developed parameters and then created our own algorithms to identify the patient group and detect treatment discontinuations in individually dosed patients."
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