Outcomes Research

How Big Data Analytics Can Improve Cardiovascular Medicine

Cutting-edge big data analytics and artificial intelligence might help alleviate the economic burden due to cardiovascular diseases

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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.
Khurram Nasir, MD, MPH
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. Successful achievement of these goals and objectives will require a multilayered, multidisciplinary effort to ensure continued advancement of big data by investing in big data platforms, harnessing technology to create software applications focusing on optimizing population health management, developing digital solutions to inform clinical and policy decisions, and optimizing public- and patient-engagement strategies.
Khurram Nasir, MD, MPH
Jerold B. Katz Investigator and Professor of Cardiology at Houston Methodist
The development of digital tools such as patient care gaps dashboards, clinical decision support systems (CDSS), 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. Specific performance indicators such as low-density lipoprotein cholesterol levels of less than 70mg/dL amongst CVD patients can be used to monitor progress or target achievement. Furthermore, longitudinal tracking of key performance indicators can identify high-risk and high-cost CVD patients as well as those with multiple comorbidities. The objective of population health initiatives is to provide the right care to the right patient at the right time. Towards this end, several CDSS have been successfully created and implemented. A case in point is Evidence-Based (EB) Guidelines- a CDSS implemented at the Johns Hopkins Health System that allows personalization of guidelines and treatment plans. In many parts of the world, CVD risks are being efficiently managed by integrating CDSS and treatment plans. Ultimately, artificial intelligence including automation, risk prediction and prescriptive analytics can generate reports and updates to effectively close CVD care gaps. According to Nasir, “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. Successful achievement of these goals and objectives will require a multilayered, multidisciplinary effort to ensure continued advancement of big data by investing in big data platforms, harnessing technology to create software applications focusing on optimizing population health management, developing digital solutions to inform clinical and policy decisions, and optimizing public- and patient-engagement strategies.” The technological marvel of digital applications and big data analytics can catapult CVD population management to a new system that can deliver significant cost savings in addition to meaningful solutions toward improved patient outcomes. Big data-driven insights have transformed several industries including financial services, human resources and online retailers. Similar changes are yet to be seen in the realm of healthcare. Further investments by CVD population health stakeholders in digital platforms will help accelerate the progress towards improved healthcare and quality of life.
Khurram Nasir, Zulqarnain Javed, Safi U Khan, Stephen L Jones, Julia Andrieni. Big Data and Digital Solutions: Laying the Foundation for Cardiovascular Population Management. Methodist Debakey Cardiovasc J. 2020 Oct-Dec;16(4):272-282.
Abanti Chattopadhyay, PhD
October 2022
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