Health economic analyses are essential for health services research, providing decision-makers and payers with evidence about the value of interventions relative to their opportunity cost. However, many health economic approaches are still limited, especially regarding the primary prevention of cardiovascular disease (CVD). In this article, we discuss some limitations to current health economic models and then outline an approach to address these via the incorporation of genomics into the design of health economic models for CVD. We propose that when a randomised clinical trial is not possible or practical, health economic models for primary prevention of CVD can be based on Mendelian randomisation analyses, a technique to assess causality in observational data. We discuss the advantages of this approach, such as integrating well-known disease biology into health economic models and how this may overcome current statistical approaches to assessing the benefits of interventions. We argue that this approach may provide the economic argument for integrating genomics into clinical practice and the efficient targeting of newer therapeutics, transforming our approach to the primary prevention of CVD, thereby moving from reactive to preventive healthcare. We end by discussing some limitations and potential pitfalls of this approach.