By Dr. Paul Terry
As CEO of PHEMI, I get around. I travel a lot, I get to present a lot, I get to meet a lot of people, and I get to hear their thoughts, their plans, and their concerns regarding their businesses and their data. Here’s what we at PHEMI saw as important developments and top five trends for big data in 2015.
1. Big data was still in early adoption in healthcare
For big data, 2015 was still a time for early adoption in healthcare in the US, where big data still isn’t as widely deployed as in other industries. They are looking to deploy it: lots of people are talking about it, there are lots of conferences around it, lots of people think they know what it is, but it’s not widely deployed yet. When that market is ready, though, it will arrive like a tidal wave, and that will be because people see big data in terms of the results it delivers, rather than as a technology. And they will start to realize that big data technology is going to change the face of medicine. And it will; of that I have no doubt.
2. Shift from “science project” to business value
That said, in 2015 we saw early adopters shifting away from initial “science projects” and starting to press for more business value from their big data deployments. What we find in these early adopters is that they are businesses driven by a particular strategic intent, which is to make information the value of their business.
In general, these organizations see information as the future of their company: they know that having an understanding about their people, their customers, and their business, and being able to action that understanding, is key to their future. And they see big data as a fundamentally different technology that is going to change the way they do their business. It’s this strategic intent that has driven them to become early adopters.
3. Outcome-related medicine
In the past, medicine in North America, including the US, has tended to be input-centric. The patient arrives with a condition, the doctor runs a battery of tests, and then the doctor tries to figure out what is wrong. In outcome-related medicine, the focus is on just the activities you need to do to generate the outcome you want. We saw over the past year an increasing demand for outcome-related information—in all industries, but particularly in medicine, and especially in the US.
As medicine becomes more outcome-related, big data becomes more and more important. That’s because big data has essentially a completely adaptive data model, so you can make use of your unstructured data and write programs, even interactive programs, to pull meaningful information out of it. You can basically look at whatever you want, whenever you want.
4. Rise of the CDO
The role of Chief Data Officer (CDO) gained ground as a designation this year. Fortune 1000 companies are increasingly employing CDOs: Harvard now has a job description for CDO, and MIT and Harvard have grouped together to actually promote the designation of CDO as a competitive advantage in business environments.
Notice that this role is not a CTO, and it isn’t a CIO: it’s a CDO. The job of these individuals is to make data a strategic advantage for the company, and the biggest concern they express is around the privacy and access control of data. Typically, these folks have deep domain knowledge: they know their data, and they see the potential advantage from manipulating and interrogating that data. They are keenly aware of big data as a technology: they understand that it is a key part of their future, even if they are still working out how to deploy it.
5. Emergence of secondary use data platforms
2015 saw an increasing press to use data for purposes other than the original purpose for which it was collected. We’re calling solutions that can do this “secondary use data platforms.” For example, the purpose of collecting the data in an Electronic Medical Record (EMR) is to allow a doctor to interact with a patient. But it is becoming more and more obvious how valuable this information can be when used for additional purposes: for example, to plot the disease profile of a population, to monitor how much blood the hospital uses across a population, or to help with operations management, like staffing or equipment ordering. These organizations see that they already have all or much of the data they need, if they could just re-purpose it. Big data platforms are perfect for secondary use, although obviously, privacy and data security considerations must be worked out and governance requirements met. But a great many organizations are beginning to invest in secondary use, even if they are not calling it that.
There were a great many more interesting developments, of course, and we see still more on the horizon. We’ll call out some of them in January, when we take a look at shifts we expect to see in 2016.
About the Author:
As the President and CEO at PHEMI systems, Paul provides the vision and technical leadership at PHEMI. He also currently serves on the Board of Directors for Providence Health Care, advising on its subcommittees for innovation, quality, EMR, and next-generation data strategies in healthcare. Paul also serves on the Board of Directors for Life Sciences BC and Molecular You, and is an advisor to the BC provincial government on next-generation data strategies.