Health care data – consisting of lab tests, medical images, clinical trials and more – make up 30 percent of the world’s data production. As our industry increasingly focuses on analytics, the quality and longevity of data is of upmost importance to cultivate an information-rich organization. For health care organizations, creating this information-rich culture requires a robust data governance strategy, ensuring that data assets are cleansed, managed and protected throughout the enterprise.
Recently, Memorial Hermann Health System (“Memorial Hermann”), the largest not-for-profit health system in southeast Texas, completed its pilot phase of employing a data governance strategy and is continuing its efforts to create a comprehensive, quality data program. We sat down with Paul Lampi, director of enterprise analytics and reporting at Memorial Hermann, to discuss the organization’s data governance journey and challenges.
The importance of a data governance strategy
Why do you feel a data governance strategy is important in today’s data-rich, health care ecosystem?
Paul Lampi: Data must be governed to ensure everyone is playing on the same field. In health care, there are so many interrelated data points, but the way people look at these data points from different views can cause varying interpretations which can lead to misunderstandings, inaccurate decisions or distrust of data. A robust data governance program helps create clear definitions so that everyone is aware of the way in which data is being utilized and what it actually means. A robust program includes not only providing definitions, but also diving down to the data level – locating the source or sources, its table and field locations, acceptable values for the data, abbreviations or alternative names and deriving how the data was calculated.
What are the challenges of deploying a data governance strategy?
The biggest challenge is that it is a lot of work for an already busy workforce. It is not necessarily one of those hard return on investments (ROI) that you are going to realize today or be able to budget down the road. It is going to take a lot of time and effort and many returns will be soft. However, data governance is not necessarily something that organizations are not already doing. We undergo data governance activities all the time; we just do not call it “data governance.” We also do not commonly document information about data in one central location. By deploying a data governance strategy and formalizing the process of documentation and distribution of the information, an organization can define data, build a report and manage its data more effectively based on a documented single source of truth.
Building a data governance program
Who are the people involved in implementing your data governance program?
Our programmatic approach consists of people, processes and technology. On the people side, we will develop a governing council, consisting of mainly of executives and leaders throughout the organization, where everything rolls up to them for ultimate decision-making. The next level down consists of advisory groups that come together and perform special projects on an ad-hoc basis. At the next level we have stewards and governors. This is where the real work of governance takes place. Governors own a functional area within the data governance process, such as physician finance, a clinical service line or our health plan.
Our data governance office supports all these people and activities involved to make the program operate. They are the conductors of the orchestra. Their purpose is to start the data governance process, educate and communicate to others what governance is, guide the governors and stewards through the process and conduct evaluations and audits of the results. Throughout this process, the governing council prioritizes and arbitrates any issues that need to be resolved.
What is the technology aspect of your data governance program?
At first, we are focusing our data governance program on definitions. We will employ a business glossary system that houses our metadata, which is data about data. Our goal is to serve the information to users similar to how Amazon sells products — you can search for a title of the book, and they present you with options and then you can view each title’s description, customer rankings and reviews, condition of the book as well as sources to acquire it. We look at this technology focus the same way as shopping for data. Our goal is to create a glossary where we can search for a term and its definition, find the condition of it, what it means and its usefulness. The glossary also drills down into the data’s related objects, respective system in which it’s located and the specific database table and field. We are creating a one-stop-shop for data assets within our organization. Once the glossary is well underway, we will broaden our scope to tackle data quality and master data management.
Piloting a data governance strategy
Can you tell us about your pilot program and how you strategized who to involve?
We wanted to test out our full programmatic approach of people, processes and technology. We started with a diverse set of participants representing various functions in the System, both clinical and administrative. We also stood up a couple demo versions of the technology in which we loaded our actual content for the pilot. The ultimate goal was to receive input and thoughts on the actual potential tool (the glossary) from various stakeholders across the system.
We started with low hanging fruit by targeting people who were already engaged and actively working on data projects with our team which already involved creating definitions and finding data in various sources. We just continued the process by formalizing the definitions and underlying metadata through a thorough documentation processes. We then asked a person to serve as governor for each pilot and had them recruit people with whom they worked that were either direct reports or colleagues in the same realm of the functional area.
We met with each group, giving them a short explanation of the goal, outlining the process we had devised to implement the strategy and merely started the ball rolling from there. After we confirmed they bought into the concept, all we did was ask for one or two terms, and it exploded from there. As they would define a term, the definition itself had one or more other terms in it. So, they would define length of stay, and then they would say length of stay is the time from admission to discharge. Then we’d say, “Okay, how do we define admission?” Then they would have to define admission, and from there it would blossom into two or three other terms. In about fifteen minutes, it grew to a list of approximately forty terms all of which needed to be defined. Then we broke up the list, assigned each term to someone and they all started creating definitions. The team would reconvene, present their work and the group discussed and refined it to be documented within the glossary.
Treating data like an asset
How is Memorial Hermann using data today, and what potential do you see for it in the future as it relates to your data governance strategy?
Our mission statement for the Memorial Hermann Data Governance Program is that we treat data as an asset. Our goal is to steward and define the data we have, making sure we are using the right information and putting the right parameters around it. We also want to ensure we have the highest quality data. If we don’t take care of our data, we will be wasting time and money coming up with analytics and reports that we would use to make decisions since the data would be unreliable. Memorial Hermann already does data governance, but this new Program will formalize the process by putting a shell around what we are already doing so that we have one source and one truth for our data. I think data governance is going to help us propel forward faster, because it will be easier for us to come up with analytics based on our business glossary that allows us to search for correct terms, locations and calculations, and all the information about that data.
What advice would you give to peer organizations beginning their data governance journey?
Journey is definitely the right way to look at data governance. This is not a destination but a way of life to continue to update and refine. Beyond that, I would say you should define your organization’s definition of data governance and plan out a strategy up front. We took a year to formulate our strategy. We started with a small group of leaders who saw the need and came up with our definition of data governance and initial scope. I think moving too quickly would be a bad thing. You need to figure out how you are going to structure your data governance program and what is going to work best for your organization; then tread lightly from there.
Actually taking the time to document everything regarding data is a great deal of work. But if you look at it, you’re doing most of this work already. You’re already figuring out where the data lives and what the data means. You’re just not formalizing it and collecting it. I think it’s a very steep hill at first but the workload will start to plateau as more people have more data and you’re able to leverage other people’s sources of information.
For more information, attend the “Data governance: Is your organization ready for big data?” session at the Cerner Health Conference featuring Memorial Hermann Health System, Roper St. Francis Healthcare and Children’s National Health System on Wednesday, October 10 at 2:45 p.m. CT in Kansas City, Missouri.
