USING CLAIMS DATA FOR EVIDENCE GENERATION IN MANAGED ENTRY AGREEMENTS.

Area of Science:

• Health economics
• Health services research
• Pharmaceutical policy

Background:

• Managed entry agreements (MEA) are crucial for incorporating novel health technologies into healthcare systems.
• Statutory health insurance (SHI) funds in Germany utilize various MEA to manage risks associated with new technologies.
• Assessing the value of new technologies in routine care requires robust data, with claims data being a potential source.

Purpose of the Study:

• To evaluate the suitability of routinely collected claims data for different types of MEA within German SHI.
• To develop a value-based typology for classifying MEA based on their data requirements.
• To systematically assess the fitness of claims data for establishing evidence of a novel technology's value in real-world settings.

Main Methods:

• A nonsystematic literature review identified MEA data needs.
• A value-based typology was created, focusing on health outcomes, utilization, and costs.
• Claims data suitability was assessed against criteria including availability, completeness, timeliness, confidentiality, reliability, and validity.

Main Results:

• Claims data are most suitable for MEA addressing uncertainties in utilization and costs of novel technologies.
• The role of claims data is limited in MEA focused on safety and clinical effectiveness due to a lack of detailed clinical information.
• The validity of claims data requires cautious interpretation as they are primarily collected for billing purposes.

Conclusions:

• The appropriateness of claims data for MEA is contingent on the specific uncertainties and outcome measures defined in the agreement.
• A framework is proposed to aid manufacturers and payers in selecting appropriate MEA types and contract conditions.
• Further research is needed to validate these findings and explore broader implications of using claims data in MEA.