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Data governance is the foundation for organizing and managing data and information assets across the enterprise. It provides healthcare organizations with a means to integrate both clinical and business policy requirements, and it gives leadership quality information that allows them to make timely decisions for continuous improvement through analytics.

Data collected in healthcare organizations is an untapped resource that can help control costs, predict future trends and requirements, and measure performance, enhance patient outcomes, and improve efficiency in care delivery. Analytics is the bridge between amassing information and making evidence-driven decisions. Data governance provides the framework for defining information so that it can be properly interpreted.

Common Challenges

Establishing effective data governance has been a challenge for healthcare providers. The most common sources of these challenges include:

  1. Lack of support  at the executive level to establish an organization-wide system and infrastructure for data governance.
  2. No dedicated resources allocated for data governance. A proper approach to governance would include a team comprised of data owners, stewards, architects, and analysts in addition to executives and other business leaders.
  3. Lack of trust among patient populations in security of health data and confidential information.
  4. Unstructured data stems from combining data siloed in different departments, in different formats, with unverified authenticity, and that are not accessible by standardized systems.

Data governance helps the organization start to move in the right direction and keeps the focus on the highest priorities. As you proceed with your data governance initiative, consider the following commonly recommended best practices:

Identify the Importance of Data

Apart from being used to provide better patient care, data governance impacts nearly every function in the organization, including BI and analytics, IT, finance, sales and marketing, legal, and more. Early on, it is important to clearly articulate the value of data governance to get buy-in not only from executives, but across the organization.

It may be helpful to map out flows of data in the organization, which systems are involved and the roles they play. Doing so will make it easier to identify weaknesses in the current flow and how the right infrastructure — systems, processes, and workflows — will serve to improve data flow and provide the foundation for improving data governance.

Build a Dedicated Team

Essential to the success of data governance is creating a dedicated, cross-functional team with data managers, data owners, and data analysts, as well as relevant functional leaders and executives. For some organizations, it may make sense to add a CDO—Chief Data Officer—position to lead data governance initiatives.

It would be unwise to assume SMEs and other technical resources will be available to take on the added burden and meaningfully contribute towards data governance initiatives. A successful data governance team will almost always require additional resources.

Safeguard Protected Health Information

Interoperability and rising amounts of data leave organizations vulnerable to security breaches that could result in loss of data, a disruption in data infrastructure, and compromised patient privacy and safety. Healthcare organizations should ensure the security and integrity of protected health information and be compliant with the necessary industry and governmental regulations.

A data governance strategy should seek to enhance security measures. Third-party security audits will help organizations assess and understand the current level of cybersecurity, and identify opportunities to strengthen it. They should seek to obtain certifications that verify the organization’s security level to boost confidence among patients and other organizations in the ecosystem.

Focus on Data Quality   

EHRs have improved how healthcare organizations manage and distribute data, but lack of standards in data inhibit the creation of more unified data management systems. However, healthcare organizations can and should focus on standardizing data within their own systems and creating a single source of truth for data in the organization.

A single, shared data source makes it possible to establish controls and processes that will optimize data quality and integrity. The data governance team can easily:

  • Define key controls, metrics, and data thresholds.
  • Develop guidelines for which data is used and how, as well as how it is distributed, consumed, and analyzed.
  • Establish processes for identifying, prioritizing, and resolving data related issues.

It will be crucial to properly educate those accessing and consuming data, enabling them with user-friendly tools and technologies, and training them on how to leverage data insights to be more effective and efficient in their day-to-day work.

From patient outcomes to operational processes, healthcare organizations need data insights in order to implement meaningful improvements. Becoming a data-driven healthcare organization requires investment—proper infrastructure, data-driven processes, dedicated resources, and robust data security—to equip the data governance team to build an effective strategy that enables the organization to reach its goals.


In an industry already shifting toward increased transparency and data sharing, the pandemic and vaccine rollout have given motivation and momentum to the push for interoperability. In our latest ZipRadio podcast, a panel of seasoned HealthTech experts discuss the persisting challenges to interoperability, expected impacts of Covid-19 on recent efforts, and interoperability solution innovations.  

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