Pharmacoepidemiology and pharmacoeconomics both focus on the evaluation of pharmaceuticals, but differ in the methods used to answer the varied research questions. Capitalizing on the link between pharmacoeconomics and pharmacoepidemiology allows for economic assessment to be made earlier in a product’s life cycle.

COPERA offers a range of services in epidemiology and pharmacoepidemiology, including: developing tractable questions, systematic literature reviews, clinical expert panels, primary data collection, and analysis of pre-existing data (clinical trial data, population registries, administrative health databases). We also offer epidemiological expertise in following areas:

Descriptive epidemiology: We provide capability in designing studies, and collecting and analysing data to characterize burden of illness, including the incidence, prevalence, morbidity and mortality, and natural history of disease.

Analytic epidemiology: We have extensive experience in designing and conducting pharmacoepidemiology studies – published in the reputable peer-reviewed journals – of disease etiology, risk factor distribution, and estimating unbiased measures of association between determinants and illness.

Characterizing treatment parameters: To support pharmacoeconomic analyses, we can provide descriptions of country-specific treatment pathways and local resource utilization to help frame the potential impacts of new treatments. In addition to pharmacoeconomics, we have extensive experience in measuring treatment efficacy through the design and analysis of randomized and pragmatic trials, and effectiveness, through cohort and case-control studies, administrative datasets, and patient, treatment and disease registries.

Risk management: We have proven capacity in assessing risk, though the detection and measurement of medication errors or adverse drug events, measuring adherence including refill compliance, and through the development of risk-benefit decision-analytic models.

Modern statistics: We can offer statistical expertise and support for the implementation and interpretation of valuable statistical tools including: survival analysis, generalised estimating equations, instrumental variables, propensity scores, and imputation methods to handle missing data.