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Optimizing Data Governance

April 15, 2012
by Mark Hagland
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Two CSC experts look at issues around laying the foundations for the use of big data
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In a new white paper from the Falls Church, Va.-based CSC, “Transforming Healthcare through Better Use of Data,” CSC experts  argue strongly for the leaders of patient care organizations to move forward to establish the strong “foundational practices and capabilities” needed to make the most out of the data they already have and to meet the many requirements of healthcare reform mandates, payer demands, and meaningful use.

Among other areas, the white paper covers the topics of data governance, data acquisition, data sharing, data standardization, data integration, and data analytics. The paper’s authors urge healthcare leaders to think very clearly about process before plunging headlong into big data.

Jared Rhoads, who co-authored the report along with Lynette Ferrara, and his colleague Dan Foltz, spoke recently with HCI Editor-in-Chief Mark Hagland regarding the findings in the white paper, and their implications for healthcare IT leaders. The Philadelphia-based Foltz leads CSC’s Health Intelligence Division, while the Rhoads works in the company's Waltham, Mass.-based Global Institute for Emerging Practices. Below are excerpts from that interview with Foltz and Rhoads.

Organizations are confused and overwhelmed by data right now. What do you see as the key foundational steps?

Dan Foltz: From a governance perspective, there are organizational and process steps that have to be taken first. Organizations need to start managing their data as a strategic asset, just as they would manage human resources or real estate or other assets. And there are countless areas where that’s not occurring, and it involves defining data standards, processes, quality. I was at an organization last week with hundreds of systems, and they have the basic problem of identifying who their physicians are. Or you want to develop reporting on visit-related metrics? I was visiting another hospital where they had seven different definitions of what a visit was. In and of themselves, these seem like trivial things, but they all compound problems, and make it very hard to trust—or even produce—the data and analysis to begin with.

Is some of this project management, and some of it data management?

Foltz: We think what’s important is this notion of data stewardship. If you look across possible data domains, if you break it down into the types of data in a hospital—patient data, which is further broken into demographics, billing, laboratory, and then physician data, and so on—well, you need data stewardship—people who are necessary to pull together the different data and establish definitions and standards, and to develop standards for quality.

Dan Foltz

How about the problem that some of the stakeholder groups in patient care organizations, such as physicians, have historically had some of the least profound involvement with data management or “stewardship”?

There’s no single answer, but what we would say is that department chairs, for example, are the least likely people to get involved in deeper data discussions, even as they are held most responsible for outcomes in their departments. So there’s a culture of ownership that has to be created; and there are different people who would serve as stewards of that data. Then you have to come up with different data stewardship processes, to discuss who’s responsible for the quality of the data, to start to set expectations for what has to be done. And that’s irrespective of the information systems themselves.

What you’ll see is that organizations are trying to build data warehouses very quickly, for example, but no one has reached any consensus on what it will do or include.

So what are the proper roles of CIOs, CMIOs, and other informaticists, in all this?

It’s a complex question; and you can’t get there through a single step. So we recommend incremental steps. External drivers like meaningful use will obviously set some of your priorities for you; and then you map those requirements back to what types of data will be required. And what use models will be considered important? For example, infection prevention and control: go into most hospitals, and follow the data through their infection control processes, and it involves a lot of manpower or labor going into mapping processes or doing root-cause analysis. So you can very quickly map something out and say, here’s what we could do together, and you’ll be able to do it faster and more accurately. So the CIOs, if they can facilitate those discussions and that priority-setting, that gives them the language and the tools to hold more meaningful discussions with clinical leaders like CMOs, to discuss what they hope to get out of the process.

And this is culture change and change management 101, right? We had a process recently where we involved over 100 people, and involved 50 different use models, everything from infection control management to emergency room flow management, to producing better outcomes for different clinical conditions, such as otitis media or the overuse of antibiotics, or case studies for clinical research. So you build this long list, and you prioritize it. And that’s a process that the CIOs can deploy teams to facility the activity for, and which can move you forward in those areas.


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