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USEOF EXPERT KNOWLEDGE ELICITATION TO ESTIMATE PARAMETERS IN HEALTH ECONOMIC DECISION MODELS

Published online by Cambridge University Press:  16 February 2015

David Hadorn
Affiliation:
Burden of Disease Epidemiology, Equity and Cost Effectiveness Programme, Department of Public Health, University of Otago, Wellington, PO Box 7343, Wellington, New Zealandtony.blakely@otago.ac.nz
Giorgi Kvizhinadze
Affiliation:
Burden of Disease Epidemiology, Equity and Cost Effectiveness Programme, Department of Public Health, University of Otago, Wellington, PO Box 7343, Wellington, New Zealandtony.blakely@otago.ac.nz
Lucie Collinson
Affiliation:
Burden of Disease Epidemiology, Equity and Cost Effectiveness Programme, Department of Public Health, University of Otago, Wellington, PO Box 7343, Wellington, New Zealandtony.blakely@otago.ac.nz
Tony Blakely
Affiliation:
Burden of Disease Epidemiology, Equity and Cost Effectiveness Programme, Department of Public Health, University of Otago, Wellington, PO Box 7343, Wellington, New Zealandtony.blakely@otago.ac.nz

Abstract

Objectives: The aim of this study was to determine the prevalence and methods of expert knowledge elicitation (EKE) for specifying input parameters in health economic decision models (HEDM).

Methods: We created two samples using the National Health System Economic Evaluations Database: (1) 100 randomly selected HEDM studies to determine prevalence of EKE and (2) sixty studies using a formal EKE process to determine methods used.

Results: Fifty-seven (57 percent) of the random sample included at least one EKE-derived parameter. Of these, six (10 percent) used a formal expert process. Thirty-four studies from our second sample of sixty studies (57 percent) described at least one aspect of the process (e.g., elicitation method) with reasonable clarity. In approximately two-thirds of studies the external experts estimated parameters de novo; the remainder confirmed or modified initial estimates provided by authors, or the method was unclear. The majority of elicitations obtained point estimates only, although a few studies asked experts to estimate ranges of parameter values.

Conclusions: The use of EKE for parameter estimation is common in HEDMs, although there is room for improvement in the methods used.

Type
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Copyright
Copyright © Cambridge University Press 2015 

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