- Correlation analysis and explanatory and predictive models: Linear Regression Analysis, logistic regression, polytomous ordered regression, semi-Markovian modelling (care pathway, time spent in a health state at a given time);
- Use of databases of health system (SNDS): Cost Studies, Cost of illness and care pathway, medical consumption, segmentation of patients and caregivers;
- Comparability of patient groups included in the study: the high dimentional propensity score (hdPS) method(*) (conditional probability for an individual to belong to the treated group, knowing covariates of individuals in the control group);
- Quantifying the uncertainty of results: Parametric simulation of health state pathway with Monte Carlo method (calculation of confidence intervals at 95%).
Cost-effectiveness Studies in Real Life (source : SNDS)
To estimate the ex-post cost-effectiveness of your health strategy, from the Health care system or Health insurance perspective: Statistical analysis and modelling of real life data (cost of illness studies, healthcare pathway analysis, prescription treatment use in real life).
(*)Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data [published correction appears in Epidemiology. 2018 Nov;29(6):e63-e64]. Epidemiology. 2009;20(4):512‐522. doi:10.1097/EDE.0b013e3181a663cc
