CardioSource WorldNews - Page 38

STRAIGHT TALK Weighing in on Big Data’s Role in Health Care B ig data analytics has emerged as a trend across nearly every industry – from transportation to education and health care – and experts around the country and across the world are seeking ways to leverage insights gleaned from these large data sets to advance their fields. While there are unlimited opportunities for big data analytics to transform health care, there are also many implications to consider and serious complexities to navigate. A recent Special Issue of Circulation: Cardiovascular Quality and Outcomes focuses on big data research methods and their impact on cardiovascular care. The issue includes several studies that used big data analysis and features perspective pieces from several cardiologists on this hot topic. “Be assured, research and clinical care are about to join the digital, mobile, mathematical, personalized revolution. We all need to ensure that the changes produce progress for people and society,” said Harlan M. Krumholz, MD, SM, in the Editor’s Perspective. Krumholz offered insights and recommendations on training, application, replication, dissemination, interoperability, funding and collaboration, all of which must be addressed in order to successfully transition to a big data analytics strategy. This era of digital health care opens doors for applying big data analytics to the emerging area of precision medicine; however, health care lags behind other industries in this space for a variety of reasons. There was consensus among the authors of the perspectives that numerous and significant changes must be made in order to evolve the research paradigm that has driven medicine for decades. Several authors stressed that big data analysis must be held to the same standards as traditional research methods and ensuring reproducibility was a common concern. “The rise of big data analytics in health care settings presents an exciting opportunity to leverage the power of increasingly voluminous health care data in ways that were simply impossible as recently as 10 years ago,” said John S. Rumsfeld, MD, PhD, ACC’s Chief Innovation Officer, and  36 CardioSource WorldNews Peter W. Groeneveld, MD, MS, in a Cardiovascular Perspective. “However, it is critical to recognize that the fundamental pitfalls of observational data analysis cannot be ignored, and in fact, the risks of such pitfalls demand rigorous scientific testing and novel methods for peer review of big data analytic models.” In another Cardiovascular Perspective, Sanjeev P. Bhavnani, MD, and coauthors provide insight into implications of big data science “One of the issues with big data is that if it comes from clinical databases, the accuracy and completeness of coding can be an issue,” commented Kim A. Eagle, MD, editor-in-chief of “Some processes for educating providers about coding have focused on maximizing revenue, not necessarily on creating a proper list of diagnoses according to severity and timeframe. Furthermore, the process of caring for patients in the EMR is further complicated by “Be assured, research and clinical care are about to join the digital, mobile, mathematical, personalized revolution.” —Harlan Krumholz, MD for early career investigators. They stress that retraining and collaboration are key, and clinical and research teams must be restructured. The authors point to several examples of new research models that signal the future, such as PatientsLikeMe, the United Kingdom’s BioBank and Apple’s Research Kit. The ACC has partnered with Patients Like Me in 2015 announced a partnership to explore innovative ways to make real-world patient feedback and experience more central to diabetes research and care. “Similar to the objectives of established data sources such as census and public health data sets, or standardized patient registries such as (those in the NCDR) where data are structured and aggregated to monitor po