ISSUE: This panel addresses the crucial topic of trusting the results of economic analyses based on decision analytical models and the resulting requirements for validation and transparency, areas where our field is currently very deficient. Based on their differing perspectives and experiences, the panelists will characterize the situation, pose the challenges and outline requirements for improvement and pragmatic solutions to the problem of inadequate validation. OVERVIEW: Health economic models have been used to extend the efficacy and safety information obtained from clinical trials to the broader populations, horizons and outcomes of interest to health technology assessors. Despite the extensive use of these decision-analytic models and repeated calls for their transparency and validation, our field continues to depend on poorly validated models, often constructed under time and other constraints duress. These highly artificial models are often complexly formulated and, thus, difficult to validate; but even if they can be assessed, their ability to predict the outcomes of interest in a reasonably accurate and unbiased way is usually unknown because it has not been tested. In part this situation is a result of the lack of sufficient data to both populate the model and validate it, but with the growing availability of automated datasets this reason is diminishing. Nevertheless, the short timelines and pressures to keep models simple and transparent impair accuracy and its usefulness.