Sequoia Project releases revised patient-matching framework
The Sequoia Project and the Care Connectivity Consortium released an updated framework for managing patient identity, including a model for measuring organizations' current ability to correctly match patients to their records.
"With insufficient matching practices, providers may experience a number of clinical workflow inefficiencies that are costly," wrote the authors of the framework.
Matching patients to their records—especially to records across organizations—has long eluded the healthcare industry, sometimes putting patient safety at risk and complicating billing.
"Patient matching continues to be one of the largest impediments to nationwide health data sharing," said Eric Heflin, chief technology officer for The Sequoia Project and one of the authors of the framework, in a statement.
In the framework, Heflin and his co-authors offer guidance to health systems on managing the project of patient matching.
The framework includes a maturity model and also "minimal acceptable principles" for organizations to adopt. For example, the authors recommend that patient identifiers are consistent and that organizations do not change or reuse identifiers.
The latest version of the framework is an update to a document first published in 2015. The revisions reflect public comments on the document and the work of the patient identity management workgroup.
While the authors of this latest version describe the problem of patient matching and suggest guidelines, they do not solve it.
Individual vendors have struggled to solve it too. Some have their own patient identity management tools, but no vendor has a tool that works across all software and all health systems to broadly match patients to their records.
Nor does the government. Though HHS is prohibited from using federal funds to help create a unique patient ID, Congress has suggested that it encourages the ONC to "provide technical assistance to private-sector-led initiatives."
In late 2017, the Office of the National Coordinator for Health Information Technology—which is part of HHS—named Vynca the winner of the Patient Matching Algorithm Challenge. The agency later included the company in its Interoperability in Action webinar.
After winning, Vynca developers found that the second- and third-place winners each found linked records that the other teams did not find. So, since then, Vynca developers have been working on putting in place those teams' algorithms so their system results in more comprehensive matches.
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