Document Detail

A framework for addressing structural uncertainty in decision models.
MedLine Citation:
PMID:  21602487     Owner:  NLM     Status:  MEDLINE    
Decision analytic models used for health technology assessment are subject to uncertainties. These uncertainties can be quantified probabilistically, by placing distributions on model parameters and simulating from these to generate estimates of cost-effectiveness. However, many uncertain model choices, often termed structural assumptions, are usually only explored informally by presenting estimates of cost-effectiveness under alternative scenarios. The authors show how 2 recent research proposals represent parts of a framework to formally account for all common structural uncertainties. First, the model is expanded to include parameters that encompass all possible structural choices. Uncertainty can then arise because these parameters are estimated imprecisely from data, for example, a treatment effect of doubtful significance. Uncertainty can also arise if there are no relevant data. If there are relevant data, uncertainty can be addressed by averaging expected costs and effects generated from probabilistic analysis of the models with and without the parameter. The weights used for averaging are related to the predictive ability of each model, assessed against the data. If there are no data, additional parameters can often be informed by eliciting expert beliefs as probability distributions. These ideas are illustrated in decision models for antiplatelet therapies for vascular disease and new biologic drugs for the treatment of active psoriatic arthritis.
Christopher H Jackson; Laura Bojke; Simon G Thompson; Karl Claxton; Linda D Sharples
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-05-20
Journal Detail:
Title:  Medical decision making : an international journal of the Society for Medical Decision Making     Volume:  31     ISSN:  1552-681X     ISO Abbreviation:  Med Decis Making     Publication Date:    2011 Jul-Aug
Date Detail:
Created Date:  2011-07-15     Completed Date:  2011-11-18     Revised Date:  2014-02-20    
Medline Journal Info:
Nlm Unique ID:  8109073     Medline TA:  Med Decis Making     Country:  United States    
Other Details:
Languages:  eng     Pagination:  662-74     Citation Subset:  IM    
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MeSH Terms
Cost-Benefit Analysis
Decision Support Techniques*
Quality-Adjusted Life Years
Grant Support
MC_U105232027//Medical Research Council; MC_U105260792//Medical Research Council; MC_U145079308//Medical Research Council; U.1052.00.001//Medical Research Council; U.1052.00.008//Medical Research Council
Comment In:
Med Decis Making. 2011 Jul-Aug;31(4):521-3   [PMID:  21757646 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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