The University of Vermont Health Network in Burlington is a year and a half into its data governance journey, after two prior unsuccessful attempts that had stalled. The high-profile impending rollout of its Epic electronic health record offered the opportunity to take another look at data governance – and how it might contribute to a more successful implementation.
“There were several factors that made a focus on data governance a priority,” said Dr. Douglas Gentile, chief medical information officer at the University of Vermont Health Network. “The network-wide Epic implementation provided the opportunity to take a look at incorporating data governance and data stewardship principles to support better analytics.”
Additionally, Vermont’s aggressive work toward a value-based, multi-payer population health delivery model drove the provider organization to consider its own data footprint and analytics strategy as critical success factors, Gentile added.
“The specific problem we faced was that internal demands for data and analytics had grown significantly across the network over time, but the consensus was that those expectations were not being met,” he said.
There were several contributing factors, he explained, including: conflicting or redundant reports produced by different departments that used different tools, methods and definitions; lack of trust in reports and analyses due to inconsistent data quality; inconsistent availability of timely data for leaders and staff to make key decisions; and single points of failure for certain reporting functions, such as staff without backup, documentation or reliable tools.
So Gentile sponsored the health system’s current data governance efforts, tapping Stephanie Crabb at data governance, data management, analytics and data security technology and consulting firm Immersive for outside, unbiased guidance.
“Immersive was brought in to create and implement a framework for an enterprise data governance program for the health network,” said Leah Fullem, vice president of enterprise information management and analytics at the University of Vermont Health Network. “Data governance is hard work and most of our workforce had no formal training or practical experience with it.”
Adopting a framework creates structure and context and offers the content and vocabulary that people need to be successful, she contended. It offers guidance regarding the work that needs to be done and provides the guard rails to keep the work on track and measure progress, she said.
“A framework begets the charter, the program plan, the tactics and metrics necessary to ensure progress,” she said.
There are various technology and consulting firms that offer specialized assistance with data governance. Some of these firms include CBIG Consulting, First San Francisco Partners, Infogix, Landoop, Magenic, Protiviti, T/DG The Digital Group and Trianz.
MEETING THE CHALLENGE
An analytics steering committee was formed with senior leader representatives from IT, finance, HR, marketing and communications, population health and quality, clinical integration, physician leadership, and the ACO to review the results of Immersive’s work and guide the development of future program work.
“It was important that the steering committee represent all facets of network business and clinical operations, and that the organization made it a strategic priority,” Gentile said. “The establishment of a network data governance program was made a network strategic objective for FY2018.”
Immersive provided expertise and acted as project managers for the data governance initiative. Virtually every area of the organization was involved in providing input into a full analysis of current state across the health network.
A small team representing key areas of high data consumption (for example, quality, finance, planning, clinical) then worked with Immersive to develop a proposed roadmap and timeline for implementing a comprehensive data governance program.
The analytics steering committee reviewed and revised the roadmap and established clear priorities and metrics, which were incorporated into the health network strategic plan.
“We have implemented a network service called the data management office, led by a single leader to oversee enterprise information management and analytics,” Gentile said. “This centralizes accountability and authority for data management and data governance under a single leadership structure in order to remove silos.”
The health system has convened a network data governance council with subcommittees devoted to specific domains – for example, policy, data quality, education and training, Fullem added.
“The council meets monthly and has decision making authority to implement network policies and standards for data governance,” she explained.
The provider organization has formally adopted a network data governance policy that sets the parameters for scope, roles and responsibilities for data governance. It also is in the process of recruiting the first directors to help design the infrastructure and staffing model for the data management office of the future.
“We have started to train our Epic teams on the basics of data stewardship in order to support better data quality on the front end for use in downstream analytics,” Gentile added.
ADVICE FOR OTHERS
“Ensure that you have senior leadership support and the right ‘tone at the top,'” Gentile advised. “John Brumsted, the health network’s CEO, has repeatedly expressed that ‘failure is not an option’ with regard to improving access to trustworthy, reliable data to make better decisions for our patients, our people and our business.”
Understand that implementing data governance is a change management effort above all else, and that one’s culture needs to be supportive of new processes and ideas around data management, he added.
“Be honest about operational, cultural and tactical readiness, and scope your organization’s expectations and effort based on this readiness,” he said. “Provide a framework and structure for your organization including a charter, program plan, tactics and metrics.”
Ensure that staff have adequate empowerment, authority, accountability and operational support, and that the organization has technical readiness for the journey, Fullem advised.
“Anticipate the future evolutions of data management beyond just data governance – the subcommittees, the working groups, the stewardship structure and the operational processes,” she said.
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