Healthcare Analytics Approaches Its Tipping Point
Skepticism is a two-edged sword. Not enough of it, and an IT manager might find himself duped into investing in software "solutions" that go nowhere. Too much of it, and skepticism can leave an IT department behind as it waits for enough proof to show a particular platform will improve outcomes beyond a reasonable doubt.
Big data analytics is at that tipping point right now in the healthcare industry. Several vendors promise better quality of care and reduced expenditures, but evidence to support those claims is somewhat tentative. Similarly, some critics of the big data movement say healthcare providers need to squeeze all the intelligence they can from small data sets before moving on to larger projects.
In a recent post in The Health Care Blog, for instance, consultants David C. Kibbe, M.D., and Vince Kuraitis argue that instead of succumbing to the allure of big data analytics, providers should focus on using small data better. In other words, concentrate on the clinical data already available in digitized form and use only those health IT tools that are directly applicable to care management.
Big data analytics, on the other hand, attempts to parse mounds of data from many disparate sources to discover patterns that could be useful in problem solving. For example, researchers are employing the big data approach to study genetic and environmental factors in multiple sclerosis to search for personalized treatments.
Some of this research might lead to exciting payoffs down the road, but IT companies are not waiting. As Kibbe and Kuraitis point out, technology firms are touting big data analytics as a must-have for healthcare systems and physician groups that aim to become accountable care organizations or make ACO-like arrangements with payers. As these ACOs and healthcare organizations try to profit under shared-savings or financial risk contracts, these proponents claim, big data can help them crunch the data for quality improvement and cost reductions.
Some providers are already using big data in patient care. According to BusinessWeek, "many [providers] are turning to companies such as Microsoft, SAS, Dell, IBM, and Oracle for their data-mining expertise." And healthcare analytics is a growth business. Frost & Sullivan projects that half of hospitals will be using advanced analytics software by 2016, compared to 10% today.
Are healthcare providers ready for big data analytics, or should they be content with the more limited data analytics capabilities built into their EHR systems and relational databases to point the way to new policies and procedures?
When asked to weigh in on the big data/small data debate during a recent interview with InformationWeek Healthcare, David Blumenthal, former head of the Office of the National Coordinate of health IT, said, "It's not an either/or choice. Big data starts with small data. As we have more information on health and disease and the patterns of care ... that information will provide useful insights into what works, what doesn't. What the natural history of disease is. It will enable us to do studies faster and more efficiently ... But it's going to take a while to figure out how to use the data."
As for the skepticism heard from many big data critics, Blumethal said, "[We] take on faith that science offers opportunities. And most of the time, our faith is vindicated."
With that perspective in mind, InformationWeek Healthcare looked at seven companies and large medical centers that have already jumped into the water.
