INDIRECT AND MIXED TREATMENT COMPARISONS, NETWORK META-ANALYSIS

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

Definition : The comparative effectiveness research of an innovative treatment is defined as the estimation of its incremental clinical value, in comparison to the best of comparators (reference strategy) or to all existing treatments (#bayesian multi-treatment meta-analysis #mixed treatment comparison MTC #network meta-analysis NMA #R software # Winbugs).

Our services: 

- Writing of the study protocol

- Data collection (literature review)

- Computer programming (R, Winbugs)

- Statistical analysis and interpretation of NMA results

- Writing of the study report

- Presentation of the results and discussion-conclusion

- Scientific Publication: writing, submission, discussion with journal editor and reviewers

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 

Validation of medico-economic models (Guidelines: Choices in methods for economic evaluation – HAS, 6 April 2020)

- Franck MAUNOURY, PhD, HDR, can help you validate your medico-economic models (Verification of calculation formulas and functional testing by a statistician health economist not involved in your model development): Usually required by HAS (cf. HAS-CEESP opinions)

REAL LIFE DATA ANALYSIS (SNDS)

To provide our partners statistical analysis and inovative modelling methods for assessment of health products, technologies and strategies in real life.

- 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