- The Sequoia Project recently released an updated national patient EHR matching framework to streamline health data exchange across healthcare organizations.
The framework is detailed in a revised white paper titled “A Framework for Cross-Organizational Patient Identity Management 2018” and includes a matching maturity model, a case study, and best practices for implementing and utilizing a national patient matching framework.
The patient matching maturity model is designed to help healthcare organizations assess their current ability to accurately identify patients and provide a roadmap for methodically improving patient matching accuracy.
The Sequoia Project also included a list of minimally accepted patient matching practices for healthcare organization leadership such as CIOs, CTOs, and other technology leaders to adopt and implement.
“A number of specific rules are presented, such as the prohibition of using exact character-by-character matching, the corresponding responsibilities on both partners to an exchange of patient data, and similar practices,” stated framework authors.
“Other principles include not relying on any specific identifier (such as a social security number), not making any assumptions about the life cycle of a patient identifier, using normalized traits, and more,” the team continued.
In collaboration with the Care Connectivity Consortium, the Sequoia Project released the framework after years of development and discussion with a diverse workgroup of stakeholders across the industry.
“When we released the proposed minimal practices document a few years ago we knew patient matching was one of the most significant challenges to nationwide health information sharing,” said Sequoia Project Chief Technology Offer and lead author Eric Heflin.
“So, we were pleased to receive robust and detailed feedback during the public comment period, as well as many experts volunteering their time and considerable operational knowledge to improve the national-level guidance,” he continued.
The workgroup included healthcare industry, academic, health IT standards, and federal government experts. Stakeholders convened over several years to devise commentary and final recommendations to improve patient identity management.
HIMSS Innovator in Residence Adam Culbertson, Kaiser Permanente IT Senior Director of Care Delivery Technology Services Zachary Gillen, Surescripts Vice President of Information Management & Systems Performance Al Jackson, and Veterans Health Administration Healthcare Systems Specialist Jamie Bennet were among the workgroup members who assisted with the framework’s development.
Representatives from health information exchanges (HIEs) including CRISP, Alaska eHealth Network, and Coastal Connect Health Information Exchange also contributed to the framework’s development.
As part of its efforts to update the framework, the workgroup incorporated new proposals to support patient identifier challenges unique to pediatric care.
Presently, there is no widely-used standard for identifying newborns — patients who have not yet received their legal name and have a temporary name. Newborns also do not yet have Social Security numbers or other government-assigned identification.
Problems with identifying newborns is further complicated by instances of twins or triplets.
The framework presents proposals to address these and other problems specific to pediatrics.
“This paper provides a roadmap for advancing our national patient matching strategy,” said Heflin. “We hope to see organizations adopt these minimal practices and maturity model for patient matching with their external health information exchange partners.” said Heflin.
The Sequoia project developed the patient matching framework and created the workgroup as part of a new model for transparently solving specific interoperability problems.
In the future, the Sequoia Project will replicate this public-private collaborative effort to address additional challenges facing the industry.
“If we can standardize, in practice, how EMRs and HIOs leverage existing standards, we will increase patient match rates dramatically even in the absence of having a national unique patient identifier,” concluded Heflin.