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What Is Data Governance in Healthcare?

UW Extended Campus September 11, 2017

Data governance is an approach to managing data that allows organizations to balance two needs: the need to collect and secure information while also getting value from that information. But it’s much more than that. Health data consists of patients’ personal and health information as well as financial data. If managed and used appropriately, this information can be the most important asset a facility owns.

What Is Data Governance in Healthcare?

Data governance in healthcare, also called information governance, is defined by AHIMA as an organization-wide framework for managing health information throughout its lifecycle—from the moment a patient’s information is first entered in the system until well after they are discharged. The lifecycle includes things like treatment, payment, research, outcomes improvement, and government reporting (i.e. influenza reporting and other diseases tracked by the agencies such as the CDC).  

Having solid enterprise-wide data governance policies and practices helps facilities achieve the Institute for Healthcare Improvement’s Triple Aim:

  1. Improve the patient experience of care (including quality and satisfaction)
  2. Improve the health of populations
  3. Reduce the per capita cost of healthcare

The Health Information and Management Systems Society (HIMSS) noted in an article titled, “Practical Steps to Enterprise Data Governance” that “everyone needs to embrace the role of data steward. If you collect, update, modify, delete, move, store, or utilize data, you are accountable for the best data possible.”  This includes health information management and technology professionals.

Why Is Data Governance in Healthcare Important?

These days, digital information is gold. This is true in many industries, including healthcare. Organizations strategically use health information in all kinds of ways, including to improve operational efficiency, reduce costs, or enhance the safety and quality of patient care.

So to understand why data governance in healthcare is important, you must think of health data as a strategic asset. Like any other organizational asset (e.g., people, capital, or inventory), this information requires ongoing monitoring. Data governance provides a formal structure for data management so organizations can extract clinical and business value.  

Simply stated, data governance in healthcare is important, because it is vital for caregivers and leadership to have access to the right information at the right time and in the right format so that proper clinical and business decisions can be made.

Data Governance: A New Twist on an Old Concept?

Data governance is a fairly new term, but it’s not a new concept in healthcare. In fact, information governance has been at the core of what health information management (HIM) professionals do every day—that is, serve as the guardians of protected health information, helping to ensure its accuracy and protect its privacy and security.

So what has changed within the industry to shine a spotlight on data governance?

Most noticeably, the volume of big data has grown exponentially thanks to electronic health records (EHRs) and interoperability. Organizations can manipulate and analyze data within seconds, allowing them to gain insights that were never possible before.

Access to information has also grown—particularly as organizations strive to engage patients through health information technology. As interoperability continues to grow, patients, providers, and other stakeholders must ensure that information is accurate and reliable.

Finally, new privacy and security risks have emerged in an electronic environment, prompting organizations to anticipate and proactively mitigate risk. All of this requires an organization-wide, top-down approach that aligns information with organizational strategy, ensuring that accurate information is available.

HIM’s Role in Data Governance

Professionals leading data governance initiatives within an organization must be able to:

  • Develop policies and procedures that support data governance efforts.
  • Educate all members of the organization about the importance of data governance and how it relates to their roles.
  • Leverage clinical, financial, and administrative data to support key organizational initiatives.
  • Measure the return on investment on information governance initiatives.

Those working in data governance in healthcare must also be able to bridge gaps between departments so that everyone works together toward the common goal of making information complete, accurate, reliable, available, interoperable, and secure. Skills such as project managementleadership, and team building are critical.

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How to Gain Data Governance Experience

How can HIM professionals hone their data governance skills to lead efforts within their organizations?

Pursuing a Bachelor of Science in Health Information Management and Technology (HIMT) is a great place to start. (A Master of Science in Data Science also may be of interest, since it teaches data governance.) An HIMT degree focuses on many of the ten important data governance core competencies:

  1.     Data governance structure
  2.     Strategic alignment
  3.     Privacy and security
  4.     Legal and regulatory
  5.     Data governance
  6.     IT governance
  7.     Analytics
  8.     Information governance performance
  9.     Enterprise information management
  10.     Awareness and adherence

Students in the four-course, HIMSS-approved UW HIMT technology track explore data governance competencies in depth. Examples of technology track course outcomes include:

HIMT 375 – Database Structures and Management Systems: Analyze and design databases to support computer-based information systems. Develop and implement relational database management systems using SQL. Topics include: data-modeling techniques such as entity-relationship modeling, extended entity-relationship modeling, database constraints, database normalization techniques, and basic and advanced features of database query language SQL, etc.

HIMT 425 – Data Warehousing and Mining: Examine the concept of the data warehouse and its effectiveness in supporting strategic decision making. Address the process of creating data warehouse/data-mart solutions from the identification of the enterprise informational and analytical needs to producing business intelligence by extracting information from the data warehouse by using data-mining methods and models.

How to Get Started in Information Governance in Healthcare

HIM professionals can help organizations get started with information governance by identifying areas of data integrity risk, such as:

  • Duplicate records. Hospitals must provide comprehensive training for patient access staff as well as initiate master patient index cleanup projects.
  • Inconsistent EHR templates. Hospitals must evaluate all existing templates and standardize them for patient care, core measure and quality reporting, and to ensure patient safety.
  • Lack of internal coding guidelines. Hospitals must develop internal guidelines to ensure system-wide coding consistency.
  • No information asset inventory. Hospitals must create a centralized source that includes the asset name, type of information (e.g., electronic, paper, or removable media), database owner, operating unit or department, retention period (taking into account any legal, regulatory, fiscal, operational, and historical requirements), and more.

These are just a few of the information governance projects that HIMT professionals can tackle. Getting the ball rolling with information governance is often the hardest part, but the good news is that HIMT professionals are ready to take on the challenge.

What’s Next?

University of Wisconsin HIMT Course List

HIMT Student Stories

HIM Careers Outlook

Have questions? Contact an enrollment adviser at 608-262-2011 or learn@uwex.edu. Enrollment advisers are available Monday through Friday from 8:30 a.m. to 5:00 p.m. CST, or by appointment.

Programs: Health Information Management and Technology