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A Bayesian approach to net health benefits: an illustration and application to modeling HIV prevention. Med Decis Making 2004 Nov-Dec;24(6):634-53 PMID: 15534344

Pubmed ID

15534344

Abstract

PURPOSE: To conduct a cost-effectiveness analysis of HIV prevention when costs and effects cannot be measured directly. To quantify the total estimation of uncertainty due to sampling variability as well as inexact knowledge of HIV transmission parameters.

METHODS: The authors focus on estimating the incremental net health benefit (INHB) in a randomized trial of HIV prevention with intervention and control conditions. Using a Bernoulli model of HIV transmission, changes in the participants' risk behaviors are converted into the number of HIV infections averted. A sampling model is used to account for variation in the behavior measurements. Bayes's theorem and Monte Carlo methods are used to attain the stated objectives.

RESULTS: The authors obtained a positive mean INHB of 0.0008, indicating that advocacy training is just slightly favored over the control condition for men, assuming a $50,000 per quality-adjusted life year (QALY) threshold. To be confident of a positive INHB, the decision maker would need to spend more than $100,000 per QALY.

Author List

Johnson-Masotti AP, Laud PW, Hoffmann RG, Hayat MJ, Pinkerton SD

Author

Purushottam W. Laud PhD Professor in the Institute for Health and Equity department at Medical College of Wisconsin




Scopus

2-s2.0-8744303778   2 Citations

MESH terms used to index this publication - Major topics in bold

Bayes Theorem
Cost-Benefit Analysis
Decision Support Techniques
Female
HIV Infections
Humans
Male
Monte Carlo Method
Patient Education as Topic
Quality-Adjusted Life Years
Randomized Controlled Trials as Topic
Risk-Taking
Uncertainty
jenkins-FCD Prod-299 9ef562391eceb2b8f95265c767fbba1ce5a52fd6