Cardiovascular diseases (CVDs) are a leading cause of death globally, causing 38% of all premature deaths. Providing care for the patients who survive is considered a priority for healthcare managers. In the Netherlands, 1.7 million people currently are diagnosed with cardiovascular diseases. After experiencing and surviving a CVD event, patients require support to get their lives back on track. However, over the next years, the number of patients is expected to increase to 2.6 million people, creating a burden on the healthcare system. Moreover, the costs of healthcare have been increasing over the last few years, decreasing the accessible and affordable for the patients to receive care. Intervention is needed to keep the quality of life of patients high. However, most interventions focus on the prevention of CVDs, with no attention to patients that already diagnosed with cardiovascular diseases. This research presents a model for the support of patients with cardiovascular diseases within the Netherlands. It is done in conjunction with Harteraad, a non-profit Dutch patient organisation that represents the interests of the 1.7 million patients. The model aims to explore the effect of interventions on the lives of patients while keeping the investment cost-efficient. To successfully answer the research question, four steps were taken. First, a literature study was conducted to find potential candidate interventions that Harteraad can implement. The results from the literature study suggest that the priority lies in interventions on physical activity, mental health and medication adherence. In the second step, a causal loop diagram (CLD) was built that maps the interventions to outcomes. For this research, the main outcome variable is the social returns on investment (SROI). SROI measures value creation on a social, environmental and economic level. Secondary outcomes include deaths, hospitalisations, and quality of life. All three of which are used to calculate the SROI. The CLD shows that the interventions affect the outcomes by improving patient behaviour. Whether that is in more exercise, seeking mental support or medical adherence. In the third step, a System Dynamics model was developed to simulate the economic effect of different interventions. Population data were retrieved from the Hartstichting, whereas data sources on input values were found in academic literature. The latter being a source of uncertainty, as healthcare systems across countries cannot be directly compared. So in the fourth step, uncertainties were incorporated into the SD model and tested systematically. The results for the simulation show that the SROI is positive for six interventions. As such, the recommendation is to invest in either of those interventions. More specifically, for physical activity, the efficient interventions are “Active-at-Home”, “Video Gaming”, and “Group-Based Training”. For mental health, the efficient interventions are “Care Coordination”, “Cognitive Behavioural Therapy”, and “Telemedicine”. Lastly, for “CombiConsult”, the recommendation is to offer additional mental support as well to create social return. Although the model is able to give insights into potential interventions, more research is required. The model is only a simplified representation of the real world. Data was either lacking or outdated, creating nuance in the model results. As such, the model cannot be used to give the optimal solution. These nuances thus need to be addressed in future research. Despite the limitations of the model, the research provides societal and scientific contributions. The research shows that system dynamics modelling is a suitable method to model the support of patients. Moreover, the model is able to determine if interventions are cost-efficient while increasing social benefits to the patient. This research furthermore adds a contribution by performing a systematic uncertainty analysis and so on, offering aid in robust decision-making. Lastly, the model is suitable to be used in different countries under different healthcare systems. As such, this research contributes to the research on patient support.