Authors
Jim Chilcott, Paul Tappenden, Andrew Rawdin, Maxine Johnson, Eva Kaltenthaler, Suzy Paisley, Diana Papaioannou, & Andrea Shippam
Abstract
Health policy decisions must be relevant, evidence-based and transparent. Decision-analytic modelling supports this process but its role is reliant on its credibility.
Errors in mathematical decision models or simulation exercises are unavoidable but little attention has been paid to processes in model development.
Numerous error avoidance/identification strategies could be adopted but it is difficult to evaluate the merits of strategies for improving the credibility of models without first developing an understanding of error types and causes.
Sample
From the interviews, over 70% of comments related to the problem definition, structuring process and the use of evidence.
Only 17% of comments related to actual errors in the implementation of models, even though implementation errors are very common and may have a high impact in Health Technology Assessment (HTA) models.
Publication
2010, Health Technology Assessment, Volume 14, Number 25, May
Full article
Avoiding and identifying errors in health technology assessment models
