To estimate the infections averted by several new prevention technologies, we needed realistic assumptions about how many people would actually use each product. We derived these uptake estimates from a discrete choice experiment, translating user preferences into credible adoption probabilities. Integrating these uptake predictions into the modeling framework allowed us to generate robust, evidence‑driven projections of population‑level impact.
For a time‑critical HTA submission, we developed a fully validated economic model and conducted a comprehensive reanalysis of the supporting clinical trial data. Despite the compressed timelines, the analytical package met all methodological and documentation standards, withstood external scrutiny, and ultimately contributed to the product’s successful approval.
For a client preparing the value narrative for an ultra‑orphan therapy, we developed a simple but robust epidemiological model to estimate the likely prevalence of an extremely rare disease. By combining this model with a structured literature review, we generated credible prevalence estimates that strengthened the clinical and economic justification for the therapy.
A client urgently needed an experienced economic modeling lead to step into an ongoing project and adapt an existing model for a complex disease area. We quickly absorbed the natural history of the condition, the treatment landscape, relevant cost structures, and all supporting data sources. This rapid onboarding allowed us to update, validate the model and provide technical documentation on schedule, ensuring the client met their critical deadlines without compromising analytical quality.
These outcomes are grounded in a full range of health economics, epidemiology, and data science services — see what we offer.