How many articles and blogs have you read over the last several years about the importance of data in the healthcare industry? How using data in a smart way will lead to more personalized care and lower costs, or how machine learning and artificial intelligence will drive better predictions and health outcomes? As an analytics and data professional, I know I've read a ton. For the most part, I totally agree. The tools and technologies we have available to extract and use data in incredible ways are nothing short of amazing.
So, why do they often fail?
Governance. Well, really, more like a lack of.
I've been a technologist with a focus on data and gleaning insight from data for the entirety of my career. I love learning about new technologies that can help. Also, I love gadgets. I, like many others in an IT role, often make the mistake of jumping headfirst into the "fun" part, directing attention to the new gadget and avoiding the less cool—but arguably more important part—governance.
Compounded with the speed at which healthcare businesses operate, we are often led to craft data related processes and solutions very quickly, with little eye to the future. This approach can easily result in unsustainable, manual, and error-prone outcomes. How often have you looked at different reports that should have had the same values, but didn’t? You’re left asking yourself which one is correct, or contemplating if they could somehow both be correct. These scenarios are often a result of skipping over the very important step of establishing data governance standards.
Why is data governance important?
Data governance is the glue that links data processes to solutions, allowing us to speak the same language across departments and business units of an organization. Creating data governance builds trust in processes and the data that flows through them, while empowering staff to seek and utilize data on their own. Without data governance, cool gadgets and technology like artificial intelligence routinely fall flat.
Successful implementation of robust data and analytics strategies always have governance at the root. When everyone in an organization is ‘speaking the same language,’ time and money are not wasted on researching and fact-checking inconsistent data; rather, resources are spent on new initiatives to move business forward. And in the healthcare industry, this can translate into cost savings and improved health outcomes.
Implementing a Data Governance Initiative
Here are a few simple, but easily overlooked points to consider while employing your own data governance initiatives.
Acknowledge that Data Governance is Hard
Let's not sugarcoat it, implementing a data governance initiative is hard. Getting the right people on board, creating accountability, and driving consensus are all difficult. Often, when companies don't adequately prepare for this effort, complexities and roadblocks can be challenging to overcome and can even result in the initiative fizzling out. Know that it will be hard work, but worth it in the long run.
Create a Vision and Mission
What are your organization's expectations on how you are going to use data? Consider if the goal is a self-service data playground that allows users to explore until their heart's content, a series of prebuilt reports and analysis that are automatically served up, or a combination of both. The answer to this question has a tremendous impact on the architecture and strategies that you may use. Start with your "why" and your "what"—THEN get to your "how."
Build a Cross-Departmental Team
It’s easy for departments to be so focused on their own goals and priorities that they charge ahead without much integration from other areas. A healthy data governance strategy, however, has a foundation built with representation from different business units across your organization. Committee members are the liaisons for their respective departments, charged with interpreting the specifics of the strategy, representing the needs of their department, and continuously driving the governance strategy forward.
Establish Goals and Track Them
Here’s where the “how” of your strategy comes in. Establish specific, timely, and trackable goals to ensure a solid data governance strategy. Without written, explicit goals, your team will likely be spinning their wheels with little accomplishment. Sounds like a simple, common sense step, yet defined goals are often overlooked. Keep your committee moving—and moving all in the same direction—by creating and constantly tracking goals such as systems of record, consensus on business rules, or agreement on high priority metrics.
Keep It Simple
Some advisors may recommend 16 different kinds of data stewards, data czars, and a laundry list of technical tools and software platforms you need to create master data and to implement business rules engines for your data governance initiative. And hey, that's cool, that may work for some larger organizations.
But if that doesn’t work for you, don’t sweat it. In healthcare or any other industry, remember that SOME data governance is better than NO data governance. Keep it simple, manageable, and achievable for the team and resources that you have.
Universal Terms and Definitions
One of the simplest, foundational ways to get a solid data governance strategy rolling is to establish agreement on the exact meaning and definition of various terms. In our business, for example, if I were to ask five people to explicitly define how to measure Medical Loss Ratio, I'm likely to get five similar yet different answers. The answers may all be fundamentally the same, but different enough that when applied to specific reporting, could result in varying numbers and outcomes. Another example would be the definition of a medical "encounter." How does each department define that, and what categories may be included or filtered out differently from team to team?
Once consensus is achieved (and some battles may have to be fought along the way), these terms and definitions must be made available to the entire organization in an easy-to-use and understandable format. This could be a searchable catalog or website, for example, which gives everyone a uniform platform to work from. Gaining agreement on how you calculate or create metrics and data points and apply definitions, as an organization, is key to knowing everyone is speaking the same language and will result in consistent reports and data in the future.
Leadership Must Make the Commitment
Data governance initiatives can make a huge impact for a company, but a successful implementation takes a commitment from leadership to allocate the time, dollars, and an endorsement that the initiative is important to the organization.
Dollars can be budgeted for software and equipment, but maybe more integral, is the support to allocate employees’ time to define all of the information and steps outlined earlier: creating the vision, building the team, setting and tracking the goals, defining the terms and definitions.
In addition, a powerful way to move governance initiatives forward is to find a governance champion. An executive or leader in the organization that understands the benefit and believes in the strategy. Someone who can actively encourage participation and publicly endorse the benefits. It's a hard job, but with consistent messaging and actions, can help rally the team and help realize results.
In the end, a robust healthcare data governance strategy doesn't immediately result in lower costs, a healthier population, or new technology. The journey may be long and bumpy, and tangible outcomes may be difficult to find. But by staying the course, access to actionable, accurate data will be realized, making teams more efficient, moving initiatives forward, and ultimately resulting in a better bottom line for your company and the wellness of our community.
