Decision Modelling for Health Economic Evaluation
In financially constrained health systems across the world, increasing emphasis is being placed on the ability to demonstrate that health care interventions are not only effective, but also cost-effective. This book deals with decision modelling techniques that can be used to estimate the value for money of various interventions including medical devices, surgical procedures, diagnostic technologies, and pharmaceuticals. Particular emphasis is placed on the importance of the appropriate representation of uncertainty in the evaluative process and the implication this uncertainty has for decision making and the need for future research. This highly practical guide takes the reader through the key principles and approaches of modelling techniques. It begins with the basics of constructing different forms of the model, the population of the model with input parameter estimates, analysis of the results, and progression to the holistic view of models as a valuable tool for informing future research exercises. Case studies and exercises are supported with online templates and solutions. This book will help analysts understand the contribution of decision-analytic modelling to the evaluation of health care programmes. ABOUT THE SERIES: Economic evaluation of health interventions is a growing specialist field, and this series of practical handbooks will tackle, in-depth, topics superficially addressed in more general health economics books. Each volume will include illustrative material, case histories and worked examples to encourage the reader to apply the methods discussed, with supporting material provided online. This series is aimed at health economists in academia, the pharmaceutical industry and the health sector, those on advanced health economics courses, and health researchers in associated fields.
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2 Key aspects of decision modelling for economic evaluation
3 Further developments in decision analytic models for economic evaluation
4 Making decision models probabilistic
5 Analysing and presenting simulation output from probabilistic models
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acceptability curves additional allocation alternative approach baseline Bayesian benefits beta distribution binomial Briggs calculate CEACs cell Chapter Cholesky decomposition Claxton clinical trial cohort models column consider correlation cost-effectiveness analysis cost-effectiveness plane cost-effectiveness threshold covariance cycle decision analysis decision models decision problem decision tree decision uncertainty Dirichlet distribution disease economic evaluation ENBS endpoint estimate event evidence EVPPI EVSI example exercise expected costs expected net-benefit expected value framework function further research gamma distribution given GORD H2RA hazard Health Economics heterogeneity ICER incremental net-benefit interventions macro Markov model matrix mean Medical Decision methods myocardial infarction normal distribution options outcomes patient-level simulation perfect information perindopril possible predicted posterior probabilistic model prosthesis QALY relative risk sample information Sculpher standard error statistical strategy structure survival analysis Table therapy time-dependent transition probabilities value of information value of sample value-of-information analysis variability Weibull worksheet zanamivir