Methods to elicit experts’ beliefs over uncertain quantities: application to a cost effectiveness transition model of negative pressure wound therapy for severe pressure ulceration
Article first published online: 11 JUL 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 19, pages 2363–2380, 30 August 2011
How to Cite
Soares, M. O., Bojke, L., Dumville, J., Iglesias, C., Cullum, N. and Claxton, K. (2011), Methods to elicit experts’ beliefs over uncertain quantities: application to a cost effectiveness transition model of negative pressure wound therapy for severe pressure ulceration. Statist. Med., 30: 2363–2380. doi: 10.1002/sim.4288
- Issue published online: 20 JUL 2011
- Article first published online: 11 JUL 2011
- Manuscript Accepted: 11 APR 2011
- Manuscript Revised: 24 FEB 2011
- Manuscript Received: 19 OCT 2010
- decision analytic models;
- negative pressure wound therapy
We can use decision models to estimate cost effectiveness, quantify uncertainty regarding the adoption decision and provide estimates of the value of further research. In many cases, the existence of only limited data with which to populate a decision model can mean that a cost-effectiveness analysis either does not proceed or may misrepresent the degree of uncertainty associated with model inputs. An example is the case of negative pressure wound therapy (NPWT) used to treat severe pressure ulceration, for which the evidence base is limited and sparse. There is, however, substantial practical experience of using this treatment and its comparators. We can capture this knowledge quantitatively to inform a cost-effectiveness model by eliciting beliefs from experts.
This paper describes the design and conduct of an elicitation exercise to generate estimates of multiple uncertain model inputs and validate analytical assumptions for a decision model on the use of NPWT. In designing the exercise, the primary focus was the use of elicitation to inform decision models (multistate models), where representations of uncertain beliefs need to be probabilistically coherent. This paper demonstrates that it is feasible to collect formally elicited evidence to inform decision models. Copyright © 2011 John Wiley & Sons, Ltd.