In this talk I will draw on my experiences working as a professional statistician at the Public Health Agency of Canada to identify many inter-related disciplines and their role as possible stepping stones in bridging the gap. Considerable progress has been made in developing guidelines for the formal evidence-based decision-making process. Though mathematical models have a long history of addressing questions related to public health interventions and policy, their results are still considered ‘expert opinion’ and not included in the formal GRADE process. Efforts to address this are under consideration. I will include a short review of the decision-making process and formal guidelines that are currently in place and have been used in developing policy decisions at the Public Health Agency of Canada. Areas related to developing a GRADE equivalent for mathematical models, such as model validation and inter-disciplinary communication (model reporting), are less well developed though very important in trying to avoid misadventures in public health policy. Applying GRADE to all parameter estimates used in the model would be a good first step. I will provide examples of a few policy decision processes and some suggestions for improving model validation, model reporting and communication for further discussion in the panel session this afternoon.