Virtual Short Course: Cohort Modeling in R

December 13, 10-1:30 ET

Cohort state transition models (cSTM), often called Markov models, are frequently used to inform policy makers about how to allocate healthcare resources under constrained budgets. In thiscourse we will teach participants how to integrate different components of a cSTM within a single framework using R. We will first give a conceptual overview of cSTMs and the general structure for their implementation in a programming language. This will be followed by a brief review of good coding practices and how to structure your code in an efficient, transparent and reproducible way. We will demonstrate a cSTM in R, followed by hands-on exercises that will help participants implement a cSTM in R. We will also demonstrate how to conduct a cost-effectiveness analysis(CEA)and how to calculate and visually present epidemiological and health economic outcomes using the cSTM. We will shortly cover the implementation of probabilistic sensitivity analysis (PSA)of a cSTM in R.

Speakers: Petros Pechlivar, Eline Krijkamp

Speaker 1 Bio: Petros Pechlivanoglou, PhD, is a Senior Scientist at The Hospital for Sick Children’s Research Institute and an Associate Professor at the University of Toronto’s Institute of Health Policy, Management and Evaluation. He received a MSc in econometrics and a PhD in health econometrics from the University of Groningen the Netherlands. His research interests include: the use of health decision analysis in economic evaluation; bridging evidence synthesis, administrative data and decision analysis; and the application and extension of predictive models in health economics. Dr. Pechlivanoglou’s research interests focus on methods and applications of decision analysis in health economics, bridging evidence synthesis, administrative data and decision analysis, and the application and extension of predictive models in health economics. He has received funding from the Canadian Institute for Health Research, the Canadian Respiratory Research Network, and more recently, the Ontario Early Researcher Award to work on projects around the economics of pre-term birth prevention, the economic evaluation of oncology interventions in children and adolescents ,the use of decision analysis in paediatric clinical trial design, and the economic impact of COPD in adults.

Speaker 2 Bio: Eline has a background in Health Economics and Epidemiology. She recently obtained her PhD degree in decision modeling from the epidemiology department of the Erasmus Medical center. Her thesis was titled ‘’Open-Source Modeling and Resource Prioritization in Healthcare’’.She did this work under supervision of Prof. Myriam Huninkand Dr. Petros Pechlivanoglou and in collaboration with Stijntje Dijkand the DARTH workgroup, of which Eline is part. The DARTH workgroup is a collaboration that aims to expand the knowledge about R for decision analysis. Eline just started a post-doc position at the Erasmus School of Health management and Policy. As part of this new position, she participates in the external assessment group for NICE submission.


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