Pharmaceutical market is of particular interest for us, as this field has given us the major part of the experience we have. Our projects include a wide range of pharmacoeconomic studies, such as CMA, CEA, CBA, CUA, and research-based QALY/DALY calculations. Considering the variety of existing approaches and the limited data, we involve modeling and forecast tools, like a decision tree, Markov model, digital methods, and probability theory algorithms. Generally, we use mathematics-based approach as much as possible for pharmacoeconomic research.
Pharmacoeconomic models come in many variants and hybrids, but there are four primary types we use: decision tree, Markov model, discrete event simulation, and Monte Carlo simulation. We also work with various algorithms of probability theory, mathematical and statistical analysis, and many others, if relevant. The final choice is usually based on many dimensions of the model, such as treatment comparisons, time horizon, data source, perspectives, economic evaluation, parameter estimation, cost calculations, and so on.
Cost-of-Illness Studies and Cost Calculations
We take into account any costs required for different research types and purposes. The aim of a cost-of-illness study and cost calculation is to identify and measure all the costs of a particular disease or treatment. They can be estimated using different approaches and depend on direct (hospital care, physician services, nursing home care, drugs and other medical needs) or indirect expenses (losses as a result of disease). First, we use top-down (examined in an aggregate form for specific diseases) or bottom-up (costs of discrete units of service performed) approaches, and then human capital, willingness-to-pay (WTP), friction costs and others.