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Even the federal government must overcome internal data silos, a new report says.
Despite its role in encouraging private healthcare organizations to bust data silos and better leverage medical information, the U.S. Department of Health and Human Services (HHS) is facing several roadblocks that prevent its 29 agencies from using and making available data at scale, according to a new report.
The department’s office of the chief technology officer published the 34-page document (PDF) on the state of data sharing at the HHS with the goal of crafting a data governance strategy. By standardizing data access protocols and being more open with information, patients, entrepreneurs and the value-based care system could all benefit, according to the report.
“A cohesive enterprise-wide data governance strategy that promotes data sharing, drives business value from leveraging data as an asset and bases policies on evidence is essential to a long-term data-driven vision of HHS,” the authors wrote.
But right now, data sharing in the department is fragmented and project-based. Although plenty of health data, from surveillance to claims, live in bodies such as the Centers for Medicare & Medicaid Services, access to these data is governed more by personal relationships and past experience than department-spanning protocols. Each data set may be covered by different regulations, and each agency may have its own rules.
Essentially, the report found, the data are “largely kept in silos with a lack of organizational awareness of what data are collected … and how to request access.”
HHS authors met with senior leaders and agency personnel, examining data sets and data governance policies. After many interviews and hours of review, they wrote the report, which highlighted five challenges that HHS must overcome and next steps it must take if it is to build a successful data governance system. As it turns out, health systems can learn something from this list, too.
This gets at the heart of HHS’s data problem: The department doesn’t have “consistent and standardized” protocols that govern how its many arms request and share data. Agencies aren’t accountable for responding to internal requests, and they face “no consequences” for improperly delaying or denying access.
HHS does not have consistent technical formats and methods for the cross-agency sharing of restricted and nonpublic data, and its analytical tools are sometimes redundant. Although agencies do track who has access to sensitive, covered data, these entities struggle to conduct audits for misinterpretation or misuse of data.
It might be up to lawmakers to fuel across-the-board data governance standards within HHS. The problem is that each data-gathering initiative comes with various regulations surrounding collection and access, and some statutes place limits on access and use. “In order to increase access or broaden use, changes to the relevant statutes may be required,” the authors wrote.
Here’s a simple problem with no easy solution: When more data sharing occurs, it’s more likely that individual privacy will be exposed. Like in the private healthcare sector, this risk can result in “an increase in limits on microdata access,” according to the report.
For now, the status quo prevails. Why? People who work with and guard data don’t always see why their colleagues need restricted and nonpublic data. They think public data can get the job done for most analyses. They sometimes consider such requests “ad-hoc or special,” the authors wrote. Add in “strained resources, fear of misrepresentation of the data and reluctance to critique a sister agency for unsatisfactory data sharing” and efforts to drive change stall.
The department’s push to comprehend its data-sharing landscape is but the first step in creating a stronger data governance framework. From here, officials must address the aforementioned challenges, identify use cases and, like in the private realm, prove the business value of data sharing.
They must focus on the technical end, workflow management and streamlined data acquisition, the authors added. Focusing on data-use agreements and regulatory changes are critical, as are data science training initiatives for staff.
“If data [are] to be leveraged as an asset using advanced analytic tools and predictive modeling,” the report noted, “the use of data must be essential to a departmental strategy rather than purely individual project based.”
For more information regarding the HHS data initiative, click here.
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