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Our portfolio gives you access to relevant data insights from across the pharmaceutical markets.
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Real World Evidence
Real-World Medical Data: Real Insights. Better Decisions.
With real-world data, we deliver insights from everyday clinical practice. Our data captures what traditional clinical trials often miss: how patients actually use their medications in daily life. We empower your research and development with new, deeply grounded knowledge — so you can better evaluate and manage the use and performance of medicinal products and therapies.
“Our real-world data gives you entirely new perspectives on how medicines and therapies perform in everyday clinical practice, beyond the confines of clinical trials. We analyze prescribing and treatment decisions under real-life conditions — for example, the prescription itself and the behavior of the treating physician. This is complemented by information on patient comedication and comorbidities, treatment and dosing patterns, and much more.”
More Than Data: Analytics for Better Decisions.
Insight Health’s many years of data expertise, combined with the broad reach of our parent company CompuGroup Medical, provide you with truly relevant insights. This enables you to identify levers for cost savings, develop new revenue models, and benefit from many additional advantages:
- We staff your project with experts: physicians, epidemiologists, medical assistants, data scientists, and data engineers
- We implement your studies and analyses in the shortest possible time
- We support you with personal, end-to-end project guidance
- Our real-world data enable high-reach analyses of patient care and retrospective data with a long-term time horizon
- You gain access to data from real-world healthcare delivery even before you formulate your research hypothesis
Get a hands-on view of patient data analytics and read our case study on real-world medical data in small patient populations now.
Services
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Diagnose- und Verordnungsgeschehen
FAQ
What exactly do Real-World Medical Data solutions encompass in a pharmaceutical context, and which data sources are used?
In a pharmaceutical context, Real-World Data (RWMD) includes all health data generated outside of traditional, controlled clinical trials – in everyday clinical practice. These data show how medications, therapies, and care pathways are actually used in routine care.
The data sources feeding into our Real-World Insights include:
Longitudinal claims data
- 77% coverage
- High longitudinal depth
- Across all medical specialties
Physician panel data
- Diagnoses / consultations / prescriptions
- Procedure codes (OPS) and billing codes
- Laboratory values
Patient-reported outcomes (PRO)
- Timing of medication intake
- Concomitant medication
- Option to conduct direct patient surveys
Hospital data
- Patient populations
- Insight into primary and secondary diagnoses in combination with therapy and active-ingredient-level medication
- Length of stay, departments, and ward transfers
Primary market research
- Quantitative studies or qualitative interviews with physicians, pharmacists, and patients
Our Real-World Medical Data solutions analyze these different sources in a data protection–compliant and methodologically robust way to answer questions around effectiveness, safety, quality of care, treatment pathways, patient segments, and real-world cost-effectiveness. They complement traditional clinical trials and enable evidence-based decision-making for pharmaceutical companies, healthcare providers, payers, and regulators.
Why is Real-World Evidence so important for pharmaceutical companies and payers?
Real-World Evidence (RWE) shows how medicines perform in real-life clinical practice – across all comorbidities, age groups, and treatment patterns that are often only partially reflected in clinical trials.
For pharmaceutical companies
- RWE demonstrates effectiveness and safety under routine conditions and provides insights into how therapies interact within the broader treatment landscape.
- RWE supports regulatory approval, indication extensions, and post-authorization studies.
- RWE strengthens market access and reimbursement, for example in the context of health technology assessment, AMNOG procedures, and price negotiations.
- RWE generates insights for product positioning and lifecycle management (patient segments, adherence, treatment sequences).
For payers/health insurance funds
- RWE enables evaluation of care quality, effectiveness, and cost-effectiveness in real-world practice.
- RWE identifies under-, over-, and misutilization of care and supports evidence-based management of healthcare delivery.
RWE thus complements clinical trials and becomes a central foundation for evidence-based, patient-centered, and economically sound decision-making in healthcare.
How do Real-World Medical Data solutions ensure that data is valid, representative, and suitable for extrapolation to the overall market?
Validity and representativeness are ensured at all times by applying standardized methods for quality assurance and extrapolation.
1. Data validity
- Data clearing: Plausibility and consistency checks identify and correct aberrant data sets.
- Clear study designs: Precise definitions of cohorts, methodology, observation periods, and endpoints ensure reproducible results.
2. Representativeness for healthcare provision in Germany
- Claims data: Broad statutory health insurance (GKV) data with high market coverage, stratified by age, gender, region, and specialty.
- Physician panel / hospital: Structured selection based on specialty, region, and patient profile.
- Patient-reported outcomes / primary market research: Targeted recruitment of relevant patient populations.
- Benchmarking against external metrics: Comparison of key parameters, such as prescription volumes, with other in-house data sources.
3. Extrapolation to the overall market
- Defined target population: Clear identification of the total population based on in-house data sources.
- Weighting and projection: Use of established, month-specific and product-code–specific (PZN) projection methods to reliably extrapolate from samples and panel data to the overall market.
- Transparency: Full documentation of methods and clear communication of potential limitations so that final results can be used with confidence.