6 Steps To A Successful Data Governance Program

By Michael Valitchka and Alex Chang, Point B Management Consultants

Data governance is not exactly the healthcare industry’s most glamorous topic. Yet it’s a necessary evil, one that has several downstream impacts on organizations.

There are several drivers dictating the need for strong data governance in healthcare today including:

• The Centers for Medicare & Medicaid Services’ (CMS) requirement for transparency for incentive programs for compliance and audits.
• Meaningful use audits that rely on strong data standards.
• The demand by large corporate clients in the group health plan space for more complex reporting on their employee populations, outcomes, and cost drivers.
• The need for metrics by organizations wanting to gauge how well they’re performing across a much larger spectrum that drives profitability, quality, and customer satisfaction.
• Complexity in electronic records, which is flattening data ownership across large institutions. The risk with these fewer silos is that accountability for data stewardship can slip between the cracks.

A good data governance program drives confidence and value, but in actuality it can provide the backbone to many important enterprise initiatives such as cost reduction, population health management, and customer experience. While many already understand what data governance is, gaining the right level of traction and visibility within an organization can be a challenge.

Prioritizing Data Governance: 6 Steps

Data governance is critical to an organization and needs to be a priority. However, it does not have to be big and burdensome. A good program can be tailored to the size and culture of any organization. Done correctly, a successful data governance program allows your organization to establish a sustainable practice that will carry on into the future and be an ongoing discussion across the organization.

A quality data governance program includes the following six key steps.

Step one: Assemble a working group. The working group should be comprised of individuals who will form the nucleus of your eventual data governance steering committee. Treat the launch as a mini-project for the working group to accomplish the steps with deadlines and deliverables. Identify a sponsor, typically a business leader, to champion the data governance program and bring together stakeholders, ensure accountability, and drive commitment to the program at a high level.

Step two: Determine your organization’s drivers, opportunities and challenges. Tie data governance to significant organizational drivers and programs. Emulate prior projects that were successful, and determine what factors made previous programs successful. Know what your organization does well, and where it falls down.

As you determine what’s critical to your organization, think about data governance as an enabler to help you achieve those desired outcomes. Oftentimes we think about putting the right people, putting the right technology, as critical success factors for these initiatives. But data governance is just as important, and it’s also a key enabler to help you achieve those outcomes.

Examples of programs that should be focused on data governance include network and provider data programs, health plans, care coordination, ACO or accountable care programs in the provider space, and any program that includes cost or efficiency drivers.

Step three: Identify people and roles, and define the organizational structure. Be realistic about the available resources, and scale the organizational model to fit your organization’s needs. This is not a one size fits all component. At a minimum, recommended roles include the data steward, who is the data owner that makes decisions on behalf of the data governance team; the custodian from the IT side, to help perform data management and technical function; and program co-leaders to support the operation of the data governance program itself. The responsibility of this team is to ensure alignment towards achieving outcomes.

Step four: Define program scope. With the team in place, define how you will run the governance program, and the initial scope of your program.

In many healthcare organizations committee structures can bog down processes due to lack of single-person authority and risk aversion. For example, committees in many hospitals consist of physicians, nurses, and administrative staff. However, meetings are adjourned without decisions being made, due to the risk aversion nature of the organization. Define how you will make decisions, who has final authority, and what the expectations are.

Focus on defining your purpose, the goals you want to achieve, and the initial scope of your data governance program. Remember, this is about pragmatism and getting your team the ability to execute with focus.

Step five: Test pilot your program. Now that you’ve established data governance’s relative importance, operating model, and features, identify a beta project to test out your program and define success and execution plans. There are two major metrics that you should focus on - engagement metrics and effectiveness metrics. Engagement metrics will help you measure how well your team is performing, and effectiveness metrics reveal whether or not your team is accomplishing the organization’s goals.

Successful engagement is about the behavior for data governance team members, so think about their attendance, whether they show up to meetings, and whether quorums are established to make decisions. In terms of effectiveness, determine how your team is managing and resolving issues and making decisions.

Not only do you need to measure the governance program itself, but you’ll also need to measure the quality of the data by ensuring data is accurate, complete, consistent, and meets compliance goals.

As an example: some data quality issues could be as simple as making sure the phone numbers for your providers and members are correct and filled in. As you determine your metrics, think about what’s most important to the organization and the project itself.

Then, you’ll need to test the data. Extract medical records, or call patients to make sure that you have the right number on file. If you’re doing a follow-up call to reduce hospital readmissions, you’ll need accurate patient data in order to reach those patients to ensure they are taking their medication or seeing their outpatient provider on time.

To ensure accuracy, going deep and testing your data is something the data governance committee should be articulating. Whether or not it’s their responsibility, they need to make sure that step is done, and those tasks are accomplished. After KPIs are identified and documented, the execution plan is drafted and finalized, execute. Keep in mind that the plan will be modified, and needs to be something that the organization can use to support transparency and publish expectations, so that leadership and others in the organization know what’s being accomplished, and when they should expect results.

Step six: Execute your data governance plan. Be open-minded as you begin to execute. Seek feedback from your team and from others outside of your team. Now is the time to get it right and make adjustments.

Think about some of those gaps across your organization. Maybe there’s education that’s needed, or a lack of data literacy overall. Try to use these interactions to close some of these gaps. At the same time, as you are executing your first project, think about what the next project should entail.

As you refine your plan, think about whether it will be with similar business owners, or new business owners, how you will stay relevant as a data governance program in the organization, the kind of scopes, and different challenges, and different strategic initiatives, that you would want to help address.

While data governance often gets overlooked in many organizations, as you can see it’s a critical component to every organization. Be strategic, set forth a plan, execute and make refinements to ensure your organization remains competitive for years to come.

About The Authors

Alex Chang is a healthcare consultant with Point B, whose expertise spans project leadership, information architecture, user experience design, web design, system development and usability evaluation.

Michael Valitchka is a healthcare principal with Point B. His experience includes a wide array of operational and strategic issues within hospitals, health systems and health plans. He has worked on a variety of initiatives including strategic service pricing, revenue cycle improvement, patient access, clinical quality improvement and health exchanges.