Establishing Data Governance – Part 1

As we begin a new year it is only natural to reflect on all that has been learned the year prior. I’ve learned that a warm iron and newspaper can help lift candle wax off carpet (sorry mom and dad!) and recently, while on a project, I learned a new word- “propitious”-meaning, good chance of success. However, it seems as though I am not the only one learning new terms. The healthcare industry has become increasingly familiar with a particular term as well – data governance.

In my last blog post we looked at the importance of data quality to improve overall healthcare, but it is one thing to have quality data and another thing to know how to manage that data to drive better decisions. Enter data governance.

What is Data Governance and Why the Need?

The healthcare industry has loosely thrown the term data governance around for many years. However, in light of external regulatory bodies, hospital executives, and patients more consistently enforcing, demanding, and expecting better quality of care, healthcare organizations have begun investing a lot of time and dollars seeking the true meaning behind data governance.

Healthcare organizations currently own significant amounts of data and data resources, but turning that data into an information asset that can be managed for effective decision making is simply not happening at an enterprise level¹. Managing information as an enterprise asset requires effective data governance¹.

Data governance is the overall management of enterprise data. It encompasses the people, processes, and information technology required to consistently ensure data value, quality and integrity, improvement, development, and maintenance. It also includes a single shared definition for all data, data security, and availability of the right data at the right time to the right people in the right format across the organization².

Universal Goals and Guiding Principles

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Before beginning any new program, an organization needs to understand what the program is trying to accomplish and how it will go about doing so. The Data Governance Institute highlights some of the typical goals and principles surrounding data goverance³:

Goals:

1. Enable better decision-making
2. Reduce operational friction
3. Protect the needs of data stakeholders
4. Train management and staff to adopt common approaches to data issues
5. Build standard, repeatable processes
6. Reduce costs and increase effectiveness through coordination of efforts
7. Ensure transparency of processes

1. Integrity
2. Transparency
3. Auditability
4. Accountability
5. Stewardship
6. Checks-and-Balances
7. Standardization
8. Change Management

A data governance program allows for a structure and framework to help an organization achieve the aforementioned goals while adhering to the highlighted principles. However, the manner in which data governance is implemented from organization to organization can vary. Broken into three main areas and following the “who, what, when, why and how” model, the Data Governance Institute recommends ten universal components of data governance that organizations should include to build a successful data governance foundation⁴:

Source: http://www.datagovernance.com/wp_how_to_use_the_dgi_data_governance_framework.pdf The DGI Data Governance Framework is trademarked by the Data Governance Institute, LLC

Rules and Rules of Engagement

• Mission and Vision
• Goals, Governance Metrics and Success Measures, and Funding Strategies
• Data Rules and Definitions
• Decision Rights
• Accountabilities
• Controls

People and Organizational Bodies

• Data Stakeholders
• A Data Governance Office
• Data Stewards

Processes

• Proactive, Reactive, and Ongoing Data Governance Processes