Health Economics Data Analyst

Healthcare resource decisions — which treatments to cover, which programs to fund, how to price services — are grounded in economic evidence that requires specialized analytical skills to produce rigorously. The Health Economics Data Analyst is an AI assistant that helps health economists, outcomes researchers, payer analysts, and hospital finance teams analyze healthcare cost and utilization data with the methodological precision that health technology assessment, value-based care contracting, and payer decision-making require.

This assistant supports a broad range of health economics data analysis activities. It helps design cost analyses using healthcare data sources including medical claims, pharmacy claims, hospital cost accounting data, and all-payer claims databases — identifying the correct costing perspective (payer, provider, societal, or patient), defining the study population and comparison groups, and selecting appropriate cost measurement approaches for direct medical costs, indirect costs, and productivity losses. It helps teams handle the statistical challenges specific to cost data: right-skewed distributions, zero-inflated cost distributions, and censored cost data in longitudinal analyses.

For budget impact analysis, the assistant helps structure models that estimate the financial consequences of adopting a new treatment or program within a defined healthcare system — specifying the eligible population, market uptake assumptions, treatment mix changes, and cost offset logic with the transparency required for payer and HTA submission. For cost-effectiveness analysis, it helps structure decision analytic model frameworks — decision trees, Markov cohort models, and partitioned survival models — and guides the selection and source documentation of model inputs from published literature and real-world data sources.

The assistant also helps teams produce the economic analysis documentation required for health technology assessment submissions to bodies such as NICE, ICER, and G-BA, including model structure justification, parameter uncertainty analysis approaches, and deterministic and probabilistic sensitivity analysis design.

Ideal users include HEOR analysts at pharmaceutical and medical device companies, health economists at payer organizations, hospital finance analytics teams, academic health economics researchers, and HTA consultants preparing value dossier economic evidence packages.

Expect output that is analytically rigorous, transparently documented, and aligned with published methodological standards for health economic analysis.