Missing Opportunities in Healthcare Data

Consultant Sid Adelman recently weighed in on the opportunities for healthcare during the Teradata 2011 Third Party Influencers Meeting, noting significant challenges that stand in the way of healthcare’s ability to benefit from trends in big data analytics.

Adelman’s argument is that if the healthcare industry finds new and better ways to capture, manage and make use of the large amounts of data that are being generated by hospitals.

He says that one of the challenges for big data in healthcare is merely making sure that the data that is currently being collected is going toward something useful. In other words, he suggests that healthcare hasn’t arrived at its “golden moment” of big transformation—it’s still a matter of convincing hospitals and doctors of the value of data.

While some might argue strongly that there are plenty of use cases that showcase how the medical profession is certainly riding the front wave of the big trend, Adelman’s argument is that doctors are still writing down a great deal about patient histories, prescriptions, gender and other demographic data—but that this data is stagnant. He says that too often doctors write it down and it sits unused and unanalyzed in a system, taking up storage space but to no great end.

The ultimate problem with this, outside of human health discoveries that might result from the vast collection and analysis of patient records, is that a lack of new clues about how to diagnose leads to a slew of unnecessary tests. He says that these costs, which could be mitigated through new data-driven discoveries in diagnostic medicine. These healthcare costs, which are rising steadily, in part because of too many unnecessary (and sometimes risky) diagnostic tests and procedures, could be eliminated if hospitals find ways to efficiently capture, store, deeply analyze, and then share diagnostic data.

The subject of the missing opportunities for healthcare in the United States in particular was the subject of a several pages in the noted McKinsey “big data” report. Here, the authors suggested that if big data was used to its full benefit (a very hard concept to quantify), more than $300 billion in value would be created every year. Again, it’s hard to discern the differences between value in the human versus financial context—but the authors say that two-thirds of this undiscovered “value” would be in the form of reducing U.S. health care expenditure by 8%. More on this topic of big data and healthcare can be uncovered in the detailed McKinsey report here.

Healthcare analyst Margalit Gur-Arie claims that healthcare has indeed been “fashionably late” to the information age party, but that it is a top area in terms of its ability to benefit from advances in big data analytics.

Gur-Arie, playing devil’s advocate for the march toward sweeping assumptions about the value of big data for healthcare says, that no matter how large those amassed files becomes, and no matter how sophisticated the analytics are, there is no guarantee of accuracy. Furthermore, Gur-Arie contends that “Big data is not available to all and is not created by all in equal amounts, which may lead to undue power for big data holders and misrepresentation of interests for those who do not generate enough big data. Collection and analysis of big data has obvious implications to privacy and human rights. But the biggest danger of all, in my opinion, is the forthcoming relaxations in the rigors of accepted scientific methods, and none seems bigger than the temptation to infer causality from correlation.”