Elements for a discussion on the development of a course on microsimulation of health Philippe Finès July 2010

2 Statistics Canada Statistique Canada Context  One of the objectives of the STAR project is to develop a graduate course on microsimulation applied to health  This course would address needs and gaps among epidemiology and medicine clientele be a fine balance between theory (process of modeling) and practice (programming and POHEM) general (health) and particular (a specific disease) data-oriented and policy-oriented  Using the experience we have so far on webinars and consultations in POHEM, we should be able to draw the outline of the course

3 Statistics Canada Statistique Canada Purpose of the discussion  Update on the webinars/consultations on POHEM What went well Interactive aspects (interactive in the technical sense, interactive in the process) How this will help us to build the course  Construction of the course Objectives Format Contents  Next steps

4 Statistics Canada Statistique Canada Update on the webinars / consultations on POHEM  Instructors Bill, Philippe  Trainees Anya, Behnam, Eric, Leslie, Meltem  Format Webinars A “formal” explanation followed by a short period of questions The ppt files are uploaded in the site by Anya Started in February 6 sessions so far; we could have done more:  it is not a problem of contents, but of scheduling (simultaneous availability of the trainees and the instructors) Face-to-face consultations Chains of s

5 Statistics Canada Statistique Canada Update on the webinars / consultations on POHEM  Topics covered: Basics in POHEM programming (all)  How to implement a disease in POHEM  Table building (to come)  Data issues (to come) Utilisation of POHEM-OA (Eric)  Interpretation of parameters  Computation of variance  Scenario building Development of POHEM-Heart disease (Anya)  COPD Calibration, sensitivity analysis (Behnam)  Calibration  Sensitivity analysis  Uncertainty

6 Statistics Canada Statistique Canada Update on the webinars / consultations on POHEM  Conclusions: Despite organizational constraints (simultaneous availability of all, technical aspects of webinars, etc…) we were able to provide interventions in a relatively short time The contents of the interventions was by nature interactive, i.e. they addressed the specific needs of the trainees From this experience, we are able to determine what would be the ideal course

7 Statistics Canada Statistique Canada Interlude: Conceptual model of disease Risk factors Birth Other stages Incidence of Disease Intervention Cure Sequelae; Other diseases Evolution of disease Death Measure of health (HUI: Health utility index) Screening

8 Statistics Canada Statistique Canada Construction of the course  Clientele, level Graduate students who already have a background on clinical trials and on statistics  Objectives  see next slides  Principles  see next slides  Material References: famous simulation models (description and analysis)

9 Statistics Canada Statistique Canada Objectives – general description  Objectives (“At the end of the course, the student should be able to…”) 1.know the essentials of simulation 2.know the concepts involved in simulation in the health context 3.(depending on the student and/or the scope) Develop and run a model Analyse models available in literature

10 Statistics Canada Statistique Canada Objectives – details 1.know the essentials of simulation why simulate? micro/macro simulation discrete/continuous time levels of complexity use of probability in simulation strengths/weaknesses of simulation (comparison with other tools) basics on programming in microsimulation 2.know the concepts involved in simulation in the health context how to model a disease, the interventions, the screening (see slide 7) how to model relative risk, specificity/sensitivity, hazard, … the need to validate the role of data (as parameters, as output, as validation tool) some typical models (diseases) used in literature

11 Statistics Canada Statistique Canada Objectives – details  The 3 rd part depends on the scope of the course and the profiles of the students 3a. (For programming-oriented students)  Run a microsimulation model build the model define hypotheses run scenarios interpret results 3b. (For policy-oriented students)  Analyse/compare results of microsimulation models available in literature identify the models to analyse/compare define hypotheses interpret results make policy-relevant decisions

12 Statistics Canada Statistique Canada Principles used in the course  Simulation is used in lieu of clinical trials or surveys or censuses.. when and why? i.e. microsimulation is to be used in conjunction with other data analysis methods i.e. microsimulation may be used to predict or to explain  Simulation is not “let’s put together data and see what happens” i.e. microsimulation must be run with the same rigor than any other data analysis method  Microsimulation is complex! hard to reproduce individual trends hard to reproduce joint distributions of covariates balance between reproducing past and projecting future problem with variables missing in the model computation of variance sensitivity analysis

13 Statistics Canada Statistique Canada Next steps  Identification of the development team  Outline of the course Timeline for a 1 st draft Writing of the 1 st draft Evaluation of the 1 st draft (dry run, focus group, pilot students) Modification and finalisation of the outline  Administrative aspects