Discrete Event Simulation for Health Technology Assessment

Author:   J. Jaime Caro (McGill University, Montreal, Quebec, Canada) ,  Jörgen Möller (Lund University, Sweden) ,  Jonathan Karnon (University of Adelaide, Australia) ,  James Stahl (Dartmouth College, Hanover, New Hampshire, USA)
Publisher:   Taylor & Francis Ltd
ISBN:  

9780367737689


Pages:   354
Publication Date:   18 December 2020
Format:   Paperback
Availability:   In Print   Availability explained
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Discrete Event Simulation for Health Technology Assessment


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Author:   J. Jaime Caro (McGill University, Montreal, Quebec, Canada) ,  Jörgen Möller (Lund University, Sweden) ,  Jonathan Karnon (University of Adelaide, Australia) ,  James Stahl (Dartmouth College, Hanover, New Hampshire, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.512kg
ISBN:  

9780367737689


ISBN 10:   036773768
Pages:   354
Publication Date:   18 December 2020
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Introduction. Central Concepts. Implementation. A Simple Example. Analyses. Formulating the Required Equations. Efficiency and Variance Reduction. Validation. Special Topics. Case Study: Breast Cancer Surveillance.

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J. Jaime Caro, MDCM, FRCPC, FACP, is an adjunct professor of medicine as well as epidemiology and biostatistics at McGill University. He also teaches discrete event simulation (DES) at Thomas Jefferson University School of Population Health and is chief scientist at Evidera. He founded the Caro Research Institute, chaired the Modeling Task Force jointly sponsored by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), chaired the Expert Panel guiding the German government on methods for health technology assessment (HTA), and helped the World Bank Institute address the growing problem of supreme courts overriding health care system decisions. Jörgen Möller, MSc Mech Eng, is an associate researcher in the Division of Health Economics, Faculty of Medicine at Lund University and vice president of modeling technology at Evidera. He is an expert in health care and logistics management decision modeling using advanced techniques. His work focuses on translating methods from operations research to pharmacoeconomics, developing guidelines for this type of modeling, and conducting advanced courses in DES and Arena software. Jonathan Karnon, PhD, is a professor in health economics at the University of Adelaide. He wrote one of the few papers that directly compared cohort state transition models and DES techniques for HTA, built a range of DES HTA models for the evaluation of alternative screening strategies, and co-chaired the ISPOR/SMDM modeling good research practices taskforce working group on the use of DES for HTA. James E. Stahl, MDCM, MPH, is an associate professor of medicine in the Geisel School of Medicine at Dartmouth College, Section Chief of General Internal Medicine at Dartmouth-Hitchcock Medical Center, the director of systems engineering for the Point of Care Testing Research Network at the Center for Integration of Medicine and Innovative Technology, senior scientist at the MGH Institute for Technology Assessment, and adjunct professor in mechanical and industrial engineering at Northeastern University. His work focuses on health care delivery, process redesign, the development and evaluation of innovation in health care, and improvement in patient experience. K. Jack Ishak, PhD, is executive director of biostatistics and senior research scientist at Evidera. Dr. Ishak specializes in statistical methods for health economics, pharmaco-epidemiology, and observational research. His current methodological work focuses on study designs for comparative effectiveness research (such as pragmatic and Bayesian adaptive trial designs), methods for adjusting for bias due to crossover in oncology trials, and simulation-based techniques for treatment comparisons (including trial simulation).

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