Who Is Responsible for Data and AI Literacy?
Defining roles is a long-standing challenge when rolling out any form of governance, but particularly data governance. In the minds of many business leaders, “data” belongs in IT. And that may be true for moving and processing data. But the “how” of moving and processing data is a business responsibility. Unfortunately, in most organizations, IT ends up with all the data that’s been filtered into the enterprise, and it’s required to make sense of that and deal with any related challenges with sporadic business input.
In an ideal state, data governance is seen as a business process. It lives under a COO, CIO or (even better) a chief data officer — someone at a high level in the operational side of the organization. That person is responsible for ensuring that data management and data quality are everybody’s job.
Everyone has a responsibility to make sure the data is complete, from nurses and providers entering patient data in the electronic health record to the quality staff that changes the definition of a bed-day based on government program requirements. It’s important that the correct code sets and vernacular are used. And if there’s bad data somewhere, clinicians need to be empowered to act on that and raise the issue. There should be a portal available for them to look up the correct definition of the data and to mark bad data for review. When someone sees a red flag, they must be able to act on it, and that capability doesn’t exist in a lot of organizations.
Data governance ROI can be difficult to prove because it’s a broad initiative that touches all areas of an organization and can take years to fully put in place. The ROI also depends on management buy-in. If leadership isn’t on board, it’s going to be hard for the benefits of data governance to trickle down. ROI can be an obstacle for data governance initiatives, and IT leaders may have to get creative in monetizing the benefits.
EXPLORE: This AI and data readiness checklist can help guide your organization toward AI adoption.
What Can Healthcare IT Leaders Do To Improve Data Literacy?
The single biggest thing IT leaders can do is create a culture that is data-centric, data-aware and data-driven. It’s hard to do. It has to start at the very top. Leaders need to walk the talk; they must exemplify the use of data in every decision. For every recommendation they receive or decision they make, leaders should ask to see the data, analysis and ROI, and they should probe the assumptions and quality of the data.
Data quality and management need to be written into job descriptions and evaluated as part of performance reviews. Often, a focus on data isn’t absent, but it needs to be called out and exist as a specific goal across the organization, and be actively measured.
Proper data assessments are crucial to understanding the organization’s data ecosystem and measuring the quality of the data. Do you know where your data is and how much of it you’ve got? Do you know how frequently it arrives? How much does the company rely on each data set? What is the lineage of the data — where does it come from, what is done to it and where does it go? This isn’t something an organization needs to do all at once, but it should have a roadmap that includes all of those steps prioritized for each data domain to be able to drive change.
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