The requirement for a powerful data governance structure has been talked to death in healthcare, but even for entire the ink the topic has acquired, most healthcare agencies lack a sound policy, which could return to haunt them as they embark on analytics and other complex information initiatives.
Without a firm and concrete foundation for assuring the overall management of the presence, usability, integrity and protection of data in healthcare agencies, quality issues could restrict the effectiveness of initiatives that depend on the trustworthiness of the underlying information.
John Moore, founder and managing partner at Boston-based analyst firm Chilmark Research, stated that the firm’s study seeks that most healthcare agencies have “fairly rudimentary” governance structures. Only 15% to 20% have full-fledged data governance deigns and frameworks in place, he further adds.
“You have to keep in mind that a decade ago, the company had very certain EHRs in place, so data governance structures to make decision that how to define and share information across systems was not something persons were working on,” he states. “The healthcare data value chain begins with powerful governance and data management, but we do not have much good models in this industry, so you are analyzing a lot disparate point solutions rather than the integrated solutions actually required to move analytics forward.”
The move to shared saving and risk-based reimbursement has disclosed the cracks in data governance and information management infrastructures at many agencies that are having important issues getting the data pieces in place to keep their heads above water. Michael Hunt, M.D., chief population health officer at St. Vincent’s Health Partners, a 275-physician medical group in Bridgeport, Conn., refers research that demonstrates 70% of ACOs (accountable care organizations) do not make money.
“The data set for the Medicare Shared Savings Program needs reporting for twenty-seven different quality measures, and several of those ACOs apparently could not submit the suitable quality data,” Hunt stated. “Does anyone consider they did not make a huge attempt to hit their objectives and qualify for incentive payments? Right now the industry is trying merely to get an infrastructure in place to apprehend the utilization and quality metrics, and bring few visibilities to costs. It is complicated to initiate thinking about advanced analytics in an atmosphere where you have to jump through so many hoops.”
Joe Kimura, M.D., chief medical officer at the Boston-based Atrius Health, claims the 750-physician medical group alliance would not be capable to begin analytics if it had not implement the extremely hard work—politically and technologically—of discussing the high-level business ideas and clinical definitions that rule its data.
At Atrius Health, those ideas and definitions are directed by medical directors, with assistance from economical and operations staff. Most of the agency’s revenue is under full-risk contracts with the State of Massachusetts, so Atrius, such as St. Vincent’s, poured resources into designing a governance infrastructure that could manage the rigors of quality reporting.
More than 90% of Atrius’ ACO reporting is captured in automated reports, but it yet struggles capturing some discrete data, like details on follow-up measures, for its reporting.
But data governance, fundamentally, is getting together and elaborating the data on hand. For instance, who is a sufferer of Atrius Health? “Marketing needs to count someone we have not see in 4 years; finance needs to say that if we have not observed them in twelve months, they are not on a roster and are not a sufferer; as a physician, I would say someone I have seen in the past 3 years is a patient,” Kimura states. “Persons have different concepts for different business intentions, but the bottom line is that you have to come together as an agency and decide. You cannot have 3 definitions, because if you try to go forward in that way, it takes a brutal rate of work to revise your data infrastructure.”
Another problem is to make sure that an agency is defining data in way that is clinically and financially valuable to its mission. For instance, the Healthcare Effectiveness Data and Information Set (HEDIS) define a diabetic sufferer for reporting purposes. But Atrius has a much more detailed definition of diabetes that involves additional claims, EHR and pharmacy data.
“The HEDIS definition is great for reporting, but we feel our definition offers us a more correct look at our diabetic sufferers and is more clinically valuable,” Kimura states. “Definitions are not essentially universal, which is why governance is an enterprise responsibility, not merely 1 person or department.”
The University of Pittsburgh Medical Center also has contributed heavily in creating a data governance infrastructure years ago when it began having multiple data system go-lives and saw a requirement for those data streams to converge, states Rasu Shrestha, the health systems chief innovation officer and executive vice president at UPMC Enterprises, which funds incubators and leads commercialization attempts for UPMC technology products and services.
“We bet great on interoperability years ago, but to do so mean that right from the beginning, we identified that to converge data you had to have a usual set of rules and definitions,” Shrestha claims. “We operate more than twenty hospitals and a health policy with more than 2.5 million covered lives. Without a framework and principles around data ownership and stewardship, we could not bring those streams together in an appropriate and meaningful way. And just as significantly, a powerful data governance infrastructure means that we can make certain that our data privacy and security policies are implemented consistently to all our data.”
Shrestha further adds that UPMC is describing ways to commercialize its data governance best practices and information management models.
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