HEALTH ECONOMICS MODELING

To provide our partners statistical analysis and inovative modeling methods for assessment of health products, technologies and strategies

- Static methods: Decision Trees (RStudio, Excel®);

- Dynamic methods: Markovian modeling (homogeneous, non-homogeneous), Semi-Markovian modeling, Markov microsimulation model, MCMC, bayesian modeling (RStudio, R, Winbugs, OpenBugs, Python, Excel®), DICE modeling;

- Interactive Modeling : Cost-Effectiveness Model (CEM), Cost-Utility Model (CUM), Budget Impact Model (BIM);

- Quantifying uncertainty of results: deterministic sensitivity analysis (DSA) and probabilistic (PSA) - Simulation of second-order Monte Carlo and Bootstrap techniques.

Writing of CEESP (HAS) files (Guidelines: Choices in methods for economic evaluation – HAS, 6 April 2020)

 

- Early meeting with HAS / DEAI

- Adapted or de novo medico-economic models for French settings

- Writing of the technical report (cost-effectiveness or cost-utility analysis, budget impact analysis)

- Writing of the CEESP file

- CEESP auditions 

 

 

Cost-effectiveness Modeling

To estimate an uncertain ex-ante cost-effectiveness of your health technology or innovative treatment (prospective assessment, CEA): Performing the cost-effectiveness acceptability curve (CEAC), the efficiency frontier and positioning the compared strategies with respect to this border.
To perform Markovian and Semi-Markovian cost-effectiveness models can yield the efficiency frontier, the Net Monetary Benefit, the Net Health Benefit [HAS CEESP Efficiency Notice]

   

Interactive Budget Impact Analysis (IBIA)

Assessing the affordability of your innovative product, from the Health insurance perspective.

 

 

 

 
     

 

 

FaLang translation system by Faboba
top arrow