Cover Story | Use of big data is increasingly becoming an everyday aspect of modern life. Mobile devices and GPS navigation have been instrumental in not only getting from Point A to Point B, but also in helping to account for victims during recent natural and man-made disasters. Grocery stores are able to offer customers savings based on purchase history, but also directly contact consumers about important food or drug recalls. Electronic health records (EHRs) are serving as ways to share patient information among providers and with patients themselves, as well as provide data to researchers and others about patient care. Companies like Google and Amazon have cornered the market on using big data to personalize the online experience and facilitate information sharing and product purchasing.

These are obviously just a few examples and are arguably just the tip of the iceberg. While the jury is still out on the cost-benefits of big data use, it is definitely here to stay. What, then, does this mean for health care?

According to Andrew Freeman, MD, FACC, past chair of the ACC’s Early Career Section, big data has far-reaching implications for health care and we have yet to fully realize the ways it can be used. “There is really no end to what can be reported on, followed or tracked,” he says. “This could have major implications for monitoring guideline adherence, medication use, exercise and food regimens, and other prevention activities.”

Among the opportunities to make the most of big data: the ability to predict disease risk; respond to treatment and long-term prognosis with greater accuracy; monitor response to therapy with greater ease in real time; stream vital sign data; incorporate environmental factors, such as nutrition and pollution, in disease profiles; and more deeply understand family history.

Specifically, ACC Immediate Past President Patrick T. O’Gara, MD, MACC, suggests big data could be used to target treatment for inherited cardiomyopathies, channelopathies, and other mono-genetic cardiovascular diseases, as well as make genotype-phenotype correlations for patients with polygenic disorders such as diabetes, atherosclerosis, hypertension and atrial fibrillation. “Big data can also help with recognizing the role of metabolomics, environmental factors, educational levels, etc., on disease expression,” he says. “The challenge is how to make it mainstream.”

Big data also has a role to play in economically-challenged countries and other resource-poor communities around the globe. For example, Freeman points out that ever-increasing access to mobile devices worldwide offers new opportunities for cardiovascular professionals in these areas to leverage data and technology to help make basic diagnoses; access and interact with clinical practice guidelines; stay on top of the latest research; and provide patients with easy-to-use tools. “With cardiovascular disease as the leading cause of death around the globe, this could literally be life-changing,” he says.

“Big data sources open up many new ways to view the issues from primordial prevention to primary prevention, disease tracking and outcomes,” notes Richard Kovacs, MD, FACC, chair of ACC’s Clinical Quality Committee. “We need to learn how to leverage these new data to prevent disease, identify disease earlier, and recognize patterns of care and trends in outcomes.”

Of course, doing all this is not without its challenges. O’Gara points out that refining payment mechanisms for whole genome sequencing, navigating cumbersome government bureaucracy, ensuring privacy and avoiding abuse of data, and determining how best to educate physicians, health care workers, patients and the public are among the many issues that need to be addressed. “We also need to avoid drowning in the ‘river’ of data,” says Kovacs. “We cannot be distracted by correlations that are not causations. Big data is not always better.”

Another area of concern is that of data quality. “You have to remember that data are only as good as what people put in,” says Freeman. Mistakes, errors, or even judgment calls of database administrators and developers in capturing, cleaning, structuring and normalizing data can have a big impact on analytic outputs. Of even more concern – particularly in health care big data analytics – is the underlying instability of source systems, such as EHRs, themselves. It’s relatively easy given today’s constantly changing health care technology environment to “not know what you don’t know” and to fail to account for issues associated with software upgrades and other source system change until it’s too late.

While big data seems to present almost limitless possibilities for study and analysis, it’s important to note that those involved in harnessing the power of big data need to remain focused and disciplined with time, money and staff resources in order to be successful. “The payoffs with big data can be potentially enormous,” says Kevin Fitzpatrick, ACC’s chief innovation officer, “but it is far harder than it looks.”

According to Fitzpatrick, this is where the ACC, as a pioneer in big data with its NCDR registries, can play an important role in shaping the future. The ACC’s NCDR has become the engine behind the College’s science and education over the last nearly two decades. It is the economic growth engine of the College and a source of unique value for ACC members and the institutions in which they practice. “The NCDR is what allows us to operate as a data-driven organization,” Fitzpatrick says, “and it has become an authoritative voice in cardiovascular medicine and quality care.”

Moving forward, both Fitzpatrick and Kovacs agree that big data is valueless without the analysis and interpretation provided by ACC members. “We are the experts in cardiovascular care, and a trusted party to interpret these new ‘big data’ findings in the light of what we know scientifically,” says Kovacs.

“The wisdom, experience and insight that ACC members bring to the data is the essential and irreplaceable value of the ACC,” stresses Fitzpatrick. “Immense value is created in that moment of transconfiguration, when data is turned into clinical knowledge. It’s up to us, the custodians of this remarkably unique asset, to continually grow and innovate in our role as the essential catalyst and single source of truth in cardiovascular medicine.”

Clinical Topics: Arrhythmias and Clinical EP, Cardiovascular Care Team, Heart Failure and Cardiomyopathies, Prevention, Genetic Arrhythmic Conditions, Atrial Fibrillation/Supraventricular Arrhythmias, Hypertension

Keywords: Cardiology Magazine, ACC Publications, Atherosclerosis, Atrial Fibrillation, Biomedical Technology, Cardiomyopathies, Causality, Channelopathies, Data Collection, Diabetes Mellitus, Drug Recalls, Electronic Health Records, Genetic Association Studies, Guideline Adherence, Hypertension, Information Dissemination, Metabolomics, Patient Care, Primary Prevention, Registries, Research Design, Software

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