DS4HEOR brings data science to Health Economics and Outcomes Research — RWD analytics, cost-effectiveness modeling, burden-of-illness studies, and payer evidence generation. HEOR is how clinical value is translated into payer reality; DS4HEOR makes that translation faster and more rigorous.

• Area: Health Economics and Outcomes Research (HEOR)
• Primary users: HEOR scientists, real-world evidence teams
• Business function: Value evidence generation and dissemination
• AI agent type: RWD analytics + economic modeling agent

HEOR work is slow because RWD is messy and economic models are bespoke. DS4HEOR standardizes RWD workflows and accelerates model iteration.

• Primary user: HEOR scientists and RWE analysts
• Secondary users: Market access, medical affairs, clinical
• Human decision owner: Head of HEOR / Real-World Evidence

• RWD cohort building and outcome analytics
• Cost-effectiveness model construction
• Burden-of-illness study automation
• Payer evidence package drafting
• Publication-ready output generation

1. Build a RWD cohort and run an outcomes analysis.
2. Construct a cost-effectiveness model with sensitivity analysis.
3. Draft a burden-of-illness study for a rare disease.

Integrates with claims, EHR, and registry data; reasoning chains and modeling tools produce HEOR-grade outputs reviewed by scientists.

User Interface
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Agent Orchestrator
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Tools / APIs / Databases
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Memory / RAG Layer
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Evaluation & Logging