Decision Modelling For Health Economic Evaluation

概率逻辑 钥匙(锁) 经济评价 信息的价值 决策分析 经济模型 价值(数学) 风险分析(工程) 心理干预 管理科学 计算机科学 业务 运筹学 卫生经济学 证据推理法 决策支持系统 精算学 经济分析 决策模型 工程类 经济 医学 人工智能 机器学习 数理经济学 宏观经济学 微观经济学 精神科 计算机安全
作者
Andrew Briggs,Karl Claxton,Mark Sculpher
标识
DOI:10.1093/oso/9780198526629.001.0001
摘要

Abstract 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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