9 best practices for data governance in a healthcare setting

May 8, 2023
Karthik Krishnan
5 min read

In the era of big data and massive cloud migration, the importance of effective data governance cannot be overstated, especially in the healthcare industry, where patient data privacy and security are paramount.  

In the healthcare sector, data governance is crucial for ensuring patient safety, improving clinical outcomes, and complying with industry regulations.  

It’s important to make the distinction between data governance and data access governance. Data access governance is the process of defining and enforcing policies for how data is accessed and used and is a term to describe the tools and solutions that enable the function. It includes defining roles and responsibilities for those who have access to data, setting up processes for granting and revoking access, and auditing data access. Data access governance plays an essential role in ensuring that data is used appropriately and safeguarded from unauthorized access. 

On a broader scale, data access governance may also include: 

  • Risk assessments 
  • Privacy policy implementation 
  • Deploying access controls 
  • Discovering and classifying sensitive data 
  • Monitoring access to critical assets 

Also critical to data access governance is network traffic analysis, security awareness training, and staying current about new threats, tools, trends and compliance requirements. 

For the purposes of this article, however, the focus will be on data governance in healthcare, highlighting the principles, challenges, best practices, and compliance mandates that healthcare organizations must consider to manage data risk. 

Defining data governance in healthcare 

Data governance in healthcare involves the management of data policies, procedures, and standards to ensure the accuracy, consistency, and security of data. The key objectives of proper data governance are focused on patient safety, improved clinical outcomes, and compliance with industry regulations.  

The principles of data governance in healthcare involve managing data as an asset, ensuring data quality and accuracy, and establishing clear data ownership and accountability.  

For healthcare organizations, a data governance framework must be established.  

The framework should include: 

  • A clear definition of roles and responsibilities  
  • Policies and procedures for data management  
  • Processes for data quality management, data security, and privacy 

Successful data governance frameworks are tailored to the healthcare organization’s specific needs, and consider compliance mandates such as HIPAA, HITECH, and GDPR. 

Compliance mandates and data risk in healthcare 

The healthcare sector is heavily regulated, and organizations within the industry must comply with various laws and regulations related to patient data privacy and security. The most significant compliance mandates include HIPAA, HITECH, and GDPR, as briefly defined below.  

HIPAA (Health Insurance Portability and Accountability Act): a U.S. law which regulates the use and disclosure of protected health information (PHI).  

HITECH (Health Information Technology for Economic and Clinical Health Act): an extension of HIPAA that strengthens the security and privacy protections for PHI (personal health information).  

GDPR (General Data Protection Regulation): a European Union regulation that protects the privacy of personal data. 

The most prominent regulation is HIPAA. Compliance is regulated by the Office for Civil Rights (OCR). Since the April 2003 compliance date of the Privacy Rule, OCR has received over 319,816 HIPAA complaints, has initiated over 1,154 compliance reviews, and “settled or imposed a civil money penalty in 130 cases resulting in a total dollar amount of $134,828,772.00.” 

To stay compliant (as well as adhere to best data security practices), healthcare organizations must implement data risk management strategies to protect patient data from breaches, cyber attacks, and other security threats. This includes access controls, a critical component of data risk management.  

What this means is that healthcare organizations must implement appropriate access controls to ensure that only authorized personnel can access patient data. Access controls can include user authentication, user authorization, and audit trails. 

The importance of data governance in healthcare 

Data plays a critical role in healthcare, and effective data governance is essential for improving patient outcomes, ensuring patient safety, and complying with industry regulations. By establishing clear policies and procedures for data management, healthcare organizations can ensure the accuracy, consistency, and security of patient data.  

Effective data governance can also lead to:  

  • Improved clinical decision-making 
  • Increased operational efficiency 
  • Reduced costs 

On the other hand, poor data governance can have significant negative impacts on healthcare organizations.  

Data breaches and cyber attacks can result in:  

  • Exposure of sensitive patient information 
  • Damage to the reputation of the healthcare organization 
  • Potential legal and financial consequences 

It’s not just about breaches: inaccurate or inconsistent data can also bring about disastrous outcomes, such as incorrect diagnoses and treatment plans, which can harm the patient and increase healthcare costs. 

9 best practices for data governance in a healthcare setting

For effective data governance in healthcare, there are several key strategies that healthcare organizations can deploy, including: 

Establish a data governance framework: As noted above, a well-defined data governance framework is the foundation of effective data governance in healthcare. This framework should include policies and procedures for data management, data quality management, data security, and privacy. 

Implement access controls: Access controls should be implemented to ensure that only authorized personnel have access to patient data. This includes user authentication, user authorization, and audit trails. 

Discover where PHI (protected health information) is located: Ensure file systems are organized and classified. Without knowing where data resides, it’s difficult to govern and protect it. Collect information on folder and file permissions for all data storage and search for any PHI-containing files, tagging them as sensitive. Compile all this information and use it to create a comprehensive risk profile, which will improve the data governance process. 

Define roles and responsibilities: Clear roles and responsibilities should be established for data governance, including a data governance committee, data stewards, and data owners. 

Ensure data quality and accuracy: Ensure the accuracy and consistency of data through processes such as data profiling, data cleansing, and data standardization. 

Monitor and audit data use: Healthcare organizations should monitor and audit data use to ensure compliance with industry regulations and detect any potential data breaches or security threats. 

Reassess privileges: One of the main goals of data governance is to achieve a “least privilege access” state — like zero trust — where users only have permissions necessary for their job. To reach this state, remove any global access groups and fix inheritance issues before adjusting permissions or group memberships. Once this is achieved, maintain it by implementing a process that allows data owners to control their data, add or remove access as needed, and regularly audit permissions. 

Sanitize stale data: For unstructured data, stale data (data no longer used or required) represents a significant risk and an attractive target for data thieves. Ensure stale data is locked down and deleted if possible. 

Train employees in data governance: Employees should be trained in data governance policies and procedures to ensure compliance and reduce the risk of data breaches. 

By following these best practices, healthcare organizations can establish effective data governance and protect the privacy and security of patient data. 



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