Use of expert knowledge elicitation to estimate parameters in health economic decision models

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.