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Three Keys to a Successful Data Governance Strategy

Article Summary


With data and data sources on the rise in healthcare, organizations need to more effectively organize, track, and distribute data to team members. A data governance strategy gives health systems a standardized approach to manage data, their most precious asset. Effective data governance helps leaders maximize their data, promote systemwide data-informed decision making, and drive sustainable improvement.

Healthcare leaders can operationalize data governance in their organizations by considering three key elements of an effective strategy:

1. Start with the data governance basics.
2. Ensure the data governance strategy supports sustainable improvement.
3.Align the data governance strategy with organizational priorities.

healthcare data governance

As data becomes more important across healthcare decision making, so does the need for an effective healthcare data governance strategy. Without a data governance strategy tailored to the unique needs of the healthcare organization, the data falls short of its potential to advance processes, workflows, and care delivery. Common challenges to implementing data governance include breaking down long-existing data silos, leadership resistance to new data processes, and the expertise needed to create a healthcare data governance strategy that accounts for massive amounts of data and data sources.

While the above challenges persist, effective data governance can alleviate many of these burdens. Data governance varies depending on the healthcare organization, but, in general, it consists of gathering, securing, and accounting for every piece of data, organizing that data based on level of importance, and distributing data. Therefore, a high-quality data governance strategy allows health systems to maximize their most valuable data sets by delivering relevant analytic insight to decision makers when they need it.

Three Keys to Effective Healthcare Data Governance

Organizations can promote systemwide data-informed decision making by considering three keys to an effective data governance strategy:

#1: Start with the Data Governance Basics

As data has become ubiquitous in healthcare, health systems have learned how to aggregate it, but many struggle to effectively distribute the data so team members can use it in daily practice. Health systems often know they need data governance because it leads to effective, systemwide data use, but the challenges of developing a data governance strategy often discourage organizations.

Health systems can start with five data governance basics to navigate the challenges around creating a data governance strategy. This stepwise approach helps health systems get on the right track toward enterprise data governance and better data access:

  1. Identify and align data and analytics to support the organizational priorities.
  2. Identify the data governance priorities.
  3. Identify and recruit the early adopters.
  4. Identify the scope of the opportunity appropriately.
  5. Enable early adopters to become enterprise data governance leaders and mentors.

#2: Ensure the Data Governance Strategy Supports Sustainable Improvement

Because data reveals variations in care, trends over time, and improvement opportunities, health systems understand that the most meaningful change comes from data insight. Therefore, health systems must realize data governance’s role in a system’s overall improvement strategy.

An effective data governance strategy supports sustainable improvement by including defined data priorities and a data governance body with engaged administrators and clinicians. From there, the data governance leaders should adopt data technology and tools that extend the reach of data beyond leadership to team members at every level.

#3: Align the Data Governance Strategy with Organizational Priorities

Healthcare data governance leaders should adopt a flexible mindset toward their data governance strategy. An agile approach is necessary for success because data—and the data needs of team members—constantly changes, requiring data governance leaders from varied disciplines to collaborate regularly to discuss changes in strategy. One way to successfully shift the data governance strategy is to ensure it is in sync with the health system’s organizational priorities so that it supports high-level goals by maximizing data, team members, and resources (e.g., technology).

Once the data governance strategy aligns with the organization’s top priorities, leaders can establish cross-disciplined data governance teams. Cross-disciplined teams allow the health system to spread data resources evenly to support different priorities (e.g., clinical, operational, and financial). From there, assigned team members can start using resources to execute the data governance project. As the data governance strategy gains traction and evolves, team members should consider how to extend data governance efforts beyond a singular project to upcoming projects and priorities.

Healthcare Data Governance: The Bedrock of Data-Informed Decision Making and Measurable Improvement

Data governance is critical to ensuring team members have timely access to the data they need to make the most informed decisions. Large amounts of data make it hard to organize data sets, leaving many health systems with uncoordinated approaches to data operations. Although difficult to navigate—especially in the early stages of governing data—an effective data governance strategy elevates the ease of using data, making it more likely that team members will use data in their everyday decision-making processes.

The most effective healthcare data governance strategy starts with the data governance basics, focuses on sustainable improvements, and aligns with high-level organizational priorities. This approach moves data from spreadsheets to the point of decision making, where data reaches its full potential to drive change.

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

  1. Three Must-Haves for a Successful Healthcare Data Strategy
  2. How to Build a Healthcare Data Quality Coalition to Optimize Decision Making
  3. Why Data-Driven Healthcare Is the Best Defense Against COVID-19
  4. Healthcare Data Quality: Five Lessons Learned from COVID-19
  5. Self-Service Data Tools Unlock Healthcare’s Most Valuable Asset
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