Shannon Fuller says that knowing what your priorities are is the key piece to efficient development of a governance structure for the data Lake. Fuller is the Director of data Governance at Carolinas Healthcare System, where he piloted an HDInsight Hadoop implementation on Microsoft Azure. Speaking at the DATAVERSITY® Enterprise Data Governance Online 2017 Conference, Fuller shared practical approaches he used to create a System that supports Innovation and insights in health care service delivery.
“Our approach was to look at it from an Analytics perspective and to develop an Analytics Platform” that could be used to serve health care organizations, he said. The trend in health care now is coordination of physician networks for continuum of care – being aware of all providers a patient sees and looking at an entire treatment plan, “instead of how it used to be where you go and see the specialist and then you come back to your primary care.”
Another trend in health care is about moving from “a volume-based model to a value-based model when it comes to compensation for care,” he said. Internal knowledge, patient data, billing data, clinical data, and provider data were already being collected, but, “The challenge was, how do you take into account all these disparate pieces of information that we have and provide that information back to the organization to be able to make decisions?”
“Our guiding principles around how we are going to engage this is, you want your positions and your operational leaders to be able to consume this data and make decisions. That was a driving factor: To take these insights, and put them in plain language, so that they can make operations improvements,” he said. “You have to govern the data, and the Analytics Products that we’re developing also have to be governed, so that you’re getting consistent answers across the organization, and then this should be used to help us build a more data-driven culture.”
He noted that it’s important to ask some questions about what your priorities are and your desired result before focusing on how you get there. “You don’t want to start with the tool. You need to understand what you’re trying to do so you properly evaluate which of these distributions or offerings would be best for you.”
Fuller then discussed the questions they used to develop their Data Governance program:
Fuller said that their initial idea was to bring in all of the data they had, add their Data Quality care measures, and the third-party data that they had from outside agencies, so they could, “Aggregate, cleanse, identify, apply any algorithms, and then provide that in an easily digestible manner back to the organization.”
Their key Data Governance priorities were protecting patient information, encouraging Innovation, protecting intellectual property and having a common, accessible repository. Fuller said that protecting patient data is absolutely critical because, “We’re going to be joining many different data sources together, so there will be a lot of detailed information about our patients being brought together in one place.”
Innovation was important, so they decided to create smaller, stand-alone products that could support rapid development of Analytics Prototypes and Predictive Models, he said, and to minimize risk with third parties, they wanted to build in intellectual property protections.
“Looking at the assets we were going to develop, we made a decision that we were not just creating another Enterprise Data Warehouse. We were going to take the approach that each of the analytic assets that we developed should be a stand-alone asset,” he said. “It’s taking a smaller structured approach to provide information back to the organization. You’re not trying to boil the ocean with any one asset.”
By taking smaller chunks, they could enable quicker availability of new data sources, he said.
