How Big Data Analytics Can Improve Cardiovascular Medicine

A research team spearheaded by Khurram Nasir, MD, MPH, Jerold B. Katz Investigator and professor of cardiology at Houston Methodist, has provided a detailed analysis of how big data analytics can enhance health care value as it pertains to cardiovascular population health management. Cardiovascular diseases (CVD), which are the leading cause of death in the United States, account for $229 billion each year from 2017 to 2018, according to the Centers for Disease Control and Prevention. This includes the cost of health care services, medications and loss of productivity. Details of the analyses published in the Houston Methodist DeBakey Cardiovascular Journal provide a detailed look into the big picture of the cardiovascular health care system model and how big data analytics and digital application tools can enhance cardiovascular health care value. Payers typically define health care value as the overall population health at the lowest possible cost. The overarching goal is to reduce the cost of care by achieving a state of the population with fewer chronic ailments. CVDs are a huge economic burden to the United States healthcare system affecting payers, providers and patients. Efforts to reduce CVD risk and cost of care have remained counterproductive. 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 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. Big data platforms have the potential to alter the world of cardiovascular medicine by the successful translation of big data into knowledge that can allow clinicians to identify care gaps. It is imperative to identify care gaps (discrepancies between the health care provided to patients and the recommended best practices) since these result in missed or delayed diagnosis and increased downstream cost of care. An example of care gaps is the category of patients with atherosclerotic CVD who are not receiving high-intensity statin therapy. Addressing care gaps via risk stratification, patient outreach, in-person patient visits, patient education and implementation of robust preventative routines can reduce costs for patients as well as payers and providers. Thus, big data platforms can lower disease burden, shed light on evidence-based disease prevention and offer suggestions on how disease management can be modified.