Consulting

How to Work With Blythe Adamson

Through Infectious Economics, I work with organizations navigating complex decisions at the intersection of health data, economics, and AI — as an advisor, expert witness, research collaborator, or strategic consultant. My clients include federal agencies, health AI companies, pharmaceutical and biotech firms, private equity, academic institutions, and financial services organizations.

Service Areas

Health Economic Evaluation & Value Demonstration

Cost-effectiveness models, budget impact analyses, and value stories for drugs, vaccines, diagnostics, and AI-enabled health technologies. Example: ROI analysis for HIV biomedical prevention technologies; CEA modeling for AI health tools translating algorithmic performance into cost per QALY.

Regulatory Strategy & Health Technology Assessment

Evidence packages for FDA, NICE, ICWG, PMDA. Cross-border transportability of evidence. AI validation frameworks. Example: advising on evidence dossier composition aligned across regulatory approval and reimbursement strategy simultaneously.

Health Policy Design & Government Advisory

Direct advisory work with government agencies on policy design, economic analysis, and coverage determination. Example: federalization policy design for CMS; essential health benefits analysis for prescription drugs.

Real-World Data & Evidence Strategy

Leveraging RWD/RWE sources — claims databases, EHRs, registries, AI-curated datasets — to generate evidence for regulatory submissions, payer negotiations, and clinical positioning across therapeutic areas. Deep international expertise: built and validated EHR-derived oncology datasets in Germany, Japan, and the UK, including navigating GDPR compliance, Japan’s APPI, and processing clinical documentation in local languages for cross-country harmonization. Example: representativeness validation of German EHR oncology cohorts (BMC Cancer, 2026); breast cancer real-world data characterization in Japan (ISPOR 2025).

Advanced Methodologies in Econometrics & Causal Inference

Instrumental variables, difference-in-differences, synthetic controls, propensity score methods for health policy and technology evaluation. Example: AI validation and performance evaluation frameworks.

Executive Education & Workshops

Custom-designed sessions for PE investment teams, banking and financial services, and academic spinouts on AI in health, health data economics, and commercialization strategy. Not off-the-shelf courses — bespoke, high-touch advisory. Background includes developing a professional society short course on reproducible real-world data science, teaching a university course on global health technology assessment, and currently lecturing at Columbia University on cost-effectiveness analysis.

Technical Methods

Comparative-effectiveness analysis (CEA) · Budget impact analysis (BIA) · Markov simulation · Quality-adjusted life years (QALYs) · Incremental cost-effectiveness ratios (ICERs) · Probabilistic sensitivity analysis (PSA) · Propensity score methods · Target trial emulation · Digital twins · Instrumental variables · Difference-in-differences · Network meta-analysis · Systematic review · Real-world evidence integration · Transportability analyses · Thematic analysis · AI/ML validation · Framework development

Interested in Working Together?

Let’s discuss how I can help your organization navigate complex health data and economic decisions.