Big data is a term with uncertain roots, and variable usage, but one which paints a picture of extremely large amounts of information, complex and disparate, that is difficult to analyze using traditional tools. Other challenges with big data include collection and storage, sorting and searching, sharing and individual privacy â€“ just because you have massive amounts of information doesnâ€™t mean you can use it effectively.
In an arena such as health care, where privacy concerns are paramount, and data collection is both disperse and diverse, it is not surprising that the challenges of using big data have â€“ until recently â€“ appeared to outweigh the benefits. However, as other industries have found, being able to successfully â€˜mineâ€™ data sources and extrapolate well-developed customer profiles enables individualized communication and customized products and services. This saves costs and increases the effectiveness of every interaction â€“ adding value for both the service provider and the customer.
Complex challenges face our nationâ€™s health care system, one that is disintegrated, uncoordinated and expensive. Defining (and adding) value and reducing cost are goals for all segments of the industry. Mayo Clinic is at the forefront of health care delivery and individualized medicine research, seeking solutions in part through analysis of big data. Our teams seek to evaluate and implement care delivery models that maximize effectiveness while minimizing cost. This includes both custom treatment plans for individual patients based on genetic and other information, and holistic, system-level changes to the way we provide care across populations.
At the end of the day, why do we care about big data? Because our patients are the center of what we do and we strive to provide the best value and overall care experience for each patient, every day. Using big data can help us achieve that goal.