The burden of infertility is high across Europe. Modest evidence indicates that infertile couples might have an increased risk of cardiovascular disease (CVD), but several questions need clarification to establish a cause-and-effect relationship. This includes understanding: whether both infertile men and women have an increased risk of CVD; how well-known risk factors for CVD (blood-pressure, body-mass index, cholesterol and smoking) relate to infertility; whether there exists common genetic determinants of infertility and CVD; and whether the connection between infertility and CVD in women can be explained by the use of assisted reproductive technologies or pregnancy complications. These questions will be answered by the INFERTILITY project. The working hypothesis of INFERTILITY is that both infertile men and women have an increased risk of CVD, and that this might at least partly reflect a greater burden of CVD risk factors. I will test this by using data from cohort studies and national health registries in Norway and the United Kingdom. I will use genetic markers as instrumental variables to establish the relationship between CVD risk factors and infertility. This is vital to understand whether infertile couples truly have an increased risk of CVD or whether infertility instead reflects a pre-existing propensity for CVD. I will conduct a genome-wide association study of infertility and identify overlapping genetic markers between any findings from this investigation and published studies of CVD. The INFERTILITY project will also clarify whether offspring cardiometabolic health trajectories differ according to parental fertility problems. This will highlight whether any relationship between infertility and CVD also crosses generations. The INFERTILITY project will elucidate whether infertile couples should be followed more closely to mitigate their risk of CVD and whether interventions targeting well-known CVD risk factors could reduce the burden of infertility.

Healthcare based on the best available clinical evidence can lead to better quality of care. Evidence-based guidelines are potentially important instruments, but clinicians often do not adhere to them. A computerised decision support system (CDSS) is a technology that uses patient-specific data to provide relevant medical knowledge at the point-of-care. It is considered to be an important quality improvement intervention and EU member states are recommended to prioritise investment in it. However, the significant investments do not consistently result in value for money due to content and implementation issues.This project aims to improve the impact of CDSS through better content wise development and optimised implementation. Our objectives are to (1) investigate the factors that determine successful CDSS implementation, (2) develop tools to address these factors and (3) validate the utility of these tools through the development of a tailored CDSS intervention. We also (4) develop a protocol for a cluster randomised controlled trial on the effectiveness of the tailored CDSS intervention. We selected the conservative management of knee osteoarthritis as a prototype condition for the pilot. Ultimately, the better implementation of CDSS may lead to better informed decisions and improved care and patient outcomes for a wide range of conditions. This project integrates expertise from multiple scientific domains and builds upon the leading expertise from the consortium in major projects (GRADE, DECIDE, TICD). The planned research and training will lead the fellow to an essential new specialist role for the successful implementation of CDSS and will be the start of an international multidisciplinary career. The project is a response to the Horizon 2020 health priorities on transferring knowledge to clinical practice, individual empowerment for self-management of health, scalable innovation actions, better use of health data, treating chronic diseases, and active ageing.