Bayesian methods in health economics / by Gianluca Baio.

Format:

Book

Author/Creator:

Baio, Gianluca.

Contributor:

EBSCOhost.

William Pepper Medical Library Fund.

Series:

Chapman & Hall/CRC biostatistics series ; 53.

Chapman & Hall/CRC biostatistics series ; 53

Language:

English

Subjects (All):

Medical economics--Statistics.

Medical economics.

Bayesian statistical decision theory.

Economics, Medical--statistics & numerical data.

Bayes Theorem.

Medical Subjects:

Economics, Medical--statistics & numerical data.

Bayes Theorem.

Genre:

Statistics.

Physical Description:

1 online resource (xviii, 225 pages) : illustrations.

Place of Publication:

Boca Raton, Fla. ; London : Chapman & Hall/CRC, 2013.

System Details:

text file

Summary:

Health economics is a relatively new discipline, characterised by the integration of different expertise and perspectives. Clearly, the clinical aspect is fundamental and the clinical background plays a basic role in the definition of any health economic evaluation. However, in its modern incarnation, health economics is effectively identified by the integration of economic models and increasingly advanced statistical techniques, particularly under the Bayesian approach.

Bayesian Methods in Health Economics focuses on the theory and practice of Bayesian analysis and its application to decision-making in health economics evaluations. The arguments are shown formally, although the level of the mathematical sophistication is kept fairly general. Designed as a manual for an advanced course in statistical methods for health economics, it develops case studies and examples using a combination of R and WinBUGS/JAGS for the main Bayesian analysis, usually based on Markov Chain Monte Carlo. Advanced topics such as probabilistic sensitivity analysis are also discussed to provide a practical understanding of their subtleties.

The book is linked to code with which to replicate the examples and case studies, and an associated R package (BCEA) can be used in real applications to produce systematic health economics evaluations of Bayesian models. Book jacket.

Contents:

1 Introduction to health economic evaluation 1

1.1 Introduction 1

1.2 Health economic evaluation 2

1.2.1 Clinical trials versus decision-analytical models 5

1.3 Cost components 6

1.3.1 Perspective and what costs include 6

1.3.2 Sources and types of cost data 7

1.4 Outcomes 9

1.4.1 Condition specific outcomes 10

1.4.2 Generic outcomes 10

1.4.3 Valuing outcomes 13

1.5 Discounting 17

1.6 Types of economic evaluations 18

1.6.1 Cost-minimisation analysis 18

1.6.2 Cost-benefit analysis 19

1.6.3 Cost-effectiveness analysis 22

1.6.4 Cost-utility analysis 22

1.7 Comparing health interventions 25

1.7.1 The cost-effectiveness plane 27

2 Introduction to Bayesian inference 29

2.1 Introduction 29

2.2 Subjective probability and Bayes theorem 31

2.2.1 Probability as a measure of uncertainty against a standard 31

2.2.2 Fundamental rules of probability 33

2.2.3 Coherence 34

2.2.4 Bayes theorem 36

2.3 Bayesian (parametric) modelling 38

2.3.1 Exchangeability and predictive inference 40

2.3.2 Inference on the posterior distribution 43

2.4 Choosing prior distributions and Bayesian computation 48

2.4.1 Vague priors 48

2.4.2 Conjugate priors 53

2.4.3 Monte Carlo estimation 58

2.4.4 Nonconjugate priors 61

2.4.5 Markov Chain Monte Carlo methods 62

2.4.6 MCMC convergence 65

2.4.7 MCMC autocorrelation 68

3 Statistical cost-effectiveness analysis 75

3.1 Introduction 75

3.2 Decision theory and expected utility 76

3.2.1 Problem 76

3.2.2 Decision criterion: Maximisation of the expected utility 78

3.3 Decision-making in health economics 80

3.3.1 Statistical framework 81

3.3.2 Decision process 83

3.3.3 Choosing a utility function: The net benefit 84

3.3.4 Uncertainty in the decision process 89

3.4 Probabilistic sensitivity analysis to parameter uncertainty 91

3.5 Reporting the results of probabilistic sensitivity analysis 92

3.5.1 Cost-effectiveness acceptability curves 93

3.5.2 The value of information 97

3.5.3 The value of partial information 100

3.6 Probabilistic sensitivity analysis to structural uncertainty 102

3.7 Advanced issues in cost-effectiveness analysis 107

3.7.1 Including a risk aversion parameter in the net benefit 107

3.7.2 Expected value of information for mixed strategies 110

4 Bayesian analysis in practice 115

4.1 Introduction 115

4.2 Software configuration 116

4.3 An example of analysis in JAGS/BUGS 117

4.3.1 Model specification 117

4.3.2 Pre-processing in R 118

4.3.3 Launching JAGS from R 120

4.3.4 Checking convergence and post-processing in R 122

4.4 Logical nodes 126

4.5 For loops and node transformations 129

4.5.1 Blocking to improve convergence 132

4.6 Predictive distributions 134

4.6.1 Predictive distributions as missing values 137

4.7 Modelling the cost-effectiveness of a new chemotherapy drug in R/JAGS 140

4.7.1 Programming the analysis of the EVPPI 145

4.7.2 Programming probabilistic sensitivity analysis to structural uncertainty 148

5 Health economic evaluation in practice 153

5.1 Introduction 153

5.2 Cost-effectiveness analysis alongside clinical trials 154

5.2.1 Example: RCT of acupuncture for chronic headache in primary care 155

5.2.2 Model description 155

5.2.3 JAGS implementation 157

5.2.4 Cost-effectiveness analysis 159

5.2.5 Alternative specifications of the model 161

5.3 Evidence synthesis and hierarchical models 168

5.3.1 Example: Neuraminidase inhibitors to reduce influenza in healthy adults 172

5.3.2 Model description 173

5.3.3 JAGS implementation 176

5.3.4 Cost-effectiveness analysis 179

5.4 Markov models 180

5.4.1 Example: Markov, model for the treatment of asthma 185

5.4.2 Model description 188

5.4.3 JAGS implementation 189

5.4.4 Cost-effectiveness analysis 191

5.4.5 Adding memory to Markov models 195

5.4.6 Indirect estimation of the transition probabilities 197.

Notes:

Description based on print version record.

Includes bibliographical references (pages 209-221) and index.

Electronic reproduction. Ipswich, MA Available via World Wide Web.

Local Notes:

Acquired for the Penn Libraries with assistance from the William Pepper Medical Library Fund.

ISBN:

1439895562

9781439895566

Publisher Number:

99953112505

Access Restriction:

Restricted for use by site license.