Jankovic, Dina orcid.org/0000-0002-9311-1409, Payne, Katherine, Kanaan, Mona orcid.org/0000-0001-7956-7576 et al. (1 more author) (2022) Eliciting uncertainty for complex parameters in model-based economic evaluations: quantifying a temporal change in the treatment effect. International Journal of Health Technology Assessment in Health Care. e21. ISSN 0266-4623
Abstract
Background. In model-based economic evaluations, the effectiveness parameter is often informed by studies with a limited duration of follow-up, requiring extrapolation of the treatment effect over a longer time horizon. Extrapolation from short-term data alone may not adequately capture uncertainty in that extrapolation. This study aimed to use structured expert elicitation to quantify uncertainty associated with extrapolation of the treatment effect observed in a clinical trial. Methods. A structured expert elicitation exercise was conducted for an applied study of a podiatry intervention designed to reduce the rate of falls and fractures in the elderly. A bespoke web application was used to elicit experts’ beliefs about two outcomes (rate of falls and odds of fracture) as probability distributions (priors), for two treatment options (intervention and treatment as usual) at multiple time points. These priors were used to derive the temporal change in the treatment effect of the intervention, to extrapolate outcomes observed in a trial. The results were compared with extrapolation without experts’ priors. Results. The study recruited thirty-eight experts (geriatricians, general practitioners, physiotherapists, nurses, and academics) from England and Wales. The majority of experts (32/38) believed that the treatment effect would depreciate over time and expressed greater uncertainty than that extrapolated from a trial-based outcome alone. The between-expert variation in predicted outcomes was relatively small. Conclusions. This study suggests that uncertainty in extrapolation can be informed using structured expert elicitation methods. Using structured elicitation to attach values to complex parameters requires key assumptions and simplifications to be considered.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s), 2022. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Centre for Health Economics (York) The University of York > Faculty of Sciences (York) > Health Sciences (York) |
Depositing User: | Pure (York) |
Date Deposited: | 05 Jun 2023 16:30 |
Last Modified: | 03 Dec 2024 11:03 |
Published Version: | https://doi.org/10.1017/S0266462322000022 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1017/S0266462322000022 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199953 |
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Description: eliciting-uncertainty-for-complex-parameters-in-model-based-economic-evaluations-quantifying-a-temporal-change-in-the-treatment-effect
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