Real-World Evidence & Pharmacoepidemiology
Causal inference and observational methods for patient-oriented questions in clinical medicine
Real-world evidence (RWE) research uses data generated outside of randomized controlled trials — electronic health records, claims databases, registries, and wearables — to answer questions about drug effectiveness, safety, and health outcomes in routine clinical practice.
Focus Areas
Pharmacoepidemiology Estimating drug effects in observational data requires careful attention to confounding, selection bias, and exposure misclassification. Methods applied include:
- Propensity score matching and inverse probability of treatment weighting (IPTW)
- Active comparator designs to reduce confounding by indication
- Time-varying exposure and covariate modeling
Health Economics & Outcomes Research (HEOR) Understanding the value of interventions from a patient and health-system perspective:
- Patient-reported outcome measures (PROMs) and their psychometric properties
- Cost-effectiveness frameworks in low- and middle-income country contexts
- Burden-of-disease estimation
Survival Analysis
- Kaplan–Meier estimation and Cox proportional hazards models
- Competing risks and time-to-event endpoints
- Landmark analyses and immortal time bias avoidance
Context
This methodological focus emerged from clinical training in Tunisia and is being deepened through the MPH Epidemiology program at FIU, with particular attention to how RWE methods can extend findings from clinical trials to broader, more diverse populations.