The studies, led by Nasir, help us understand from two different perspectives how CVD management can be enhanced. Scrutiny of the contemporary practices in CVD health care management and delivery led Nasir to propose a three-step solution for enhancing CVD health care value. This solution entails creating big data platforms, developing digital tools and translating data science into real-world applications to improve patient outcomes. “Big data” refers to large sets of data that are amenable to analytics with the end goal of identifying trends, patterns and associations. Characterized by the 4Vs (volume, velocity, variety and veracity), big data is collected from various sources such as electronic medical records, administrative data, national registries, patient surveys, geocoding, smartwatches and internet applications. Appropriate storage, analytics and visualization tools allow leveraging these enormous amounts of data into useful and unique conclusions that can be applied toward successful population health initiatives. On the other hand, Nasir and his team dove deeper into why the rates of influenza vaccine uptake were low within the population at high risk of CVD and found several sociodemographic factors. Influenza vaccine rates were particularly low in patients younger than 65 years of age, non-Hispanic black patients, those without health insurance and patients with lesser access to health care resources. Additionally, various psychological factors also played a role. These included perceived vaccine efficacy, vaccine safety, and sentiments towards vaccination. According to Nasir, “The rate of influenza vaccination in U.S. adults with CVD remains much lower than the national target despite known incidence of increased influenza-related complications, cardiovascular events, and deaths in this high-risk population. Vaccine uptake is a complex interplay of sociodemographic factors including age, insurance status, and health care access, as well as behavioral factors such as perception of vaccine efficacy and safety. Multilevel strategies to increase awareness of vaccine effectiveness and its limited side effect profile and efforts to improve accessibility are urgently warranted in this vulnerable and expansive patient population.” Because influenza viruses are constantly mutating, scientists alter the vaccine each year to match the likely prevalent strands. On average, a vaccine’s effectiveness at preventing infection is 40%, which is sufficient to significantly lower the risk of severe illness in most people. As a result of the demonstrated benefits conferred by influenza vaccination and the risks posed by this infection among those with CVD, several international scientific societies including the CDC, the American Heart Association and the European Society of Cardiology strongly recommend annual influenza vaccination in patients with CVD. On a larger scale, the development of digital tools such as patient care gaps dashboards, clinical decision support systems, direct patient engagement applications, and key performance indicator tools can address unmet needs of CVD population health management. Science, informatics, correct analytical approaches, data visualization tools and workflow designs can be leveraged to create novel insights and real-world solutions for CVD patients and those at risk of future CVDs. “Health care is at a critical and exciting juncture, an inflection point, where big data applications and tools have tremendous potential to optimize point of care management, enhance cardiovascular health care quality and performance, and improve outcomes across large populations,” added Nasir. The objective of population health initiatives is to provide the right care to the right patient at the right time. Unfortunately, many heart patients visit their cardiologists more frequently than their primary care providers, and cardiology practices typically do not provide flu vaccinations, though proposed recommendations may change in the future. Until then, it is incumbent upon both the cardiology provider and the primary care provider to communicate the increased risk to their patients and the importance of getting vaccinated. Towards effectively closing CVD case gaps, artificial intelligence including automation, risk prediction and prescriptive analytics can generate useful reports. Thus, digital applications and big data analytics along with guidelines for reducing heart diseases via influenza vaccination can enhance CVD disease management and reduce the CVD economic burden.