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HHS, HIMSS Team Up on Patient Data Matching Strategy

December 20, 2013
by Rajiv Leventhal
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The U.S. Department of Health and Human Services (HHS) and the Healthcare Information Management Systems Society (HIMSS) have collaborated to hire an “Innovator in Residence” (IIR) to develop a plan to deploy a consistent patient data matching strategy that builds on the body of work from HHS’s Office of the National Coordinator for Health IT (ONC) and healthcare community partners.

Hired through HHS' existing Innovator in Residence program, the IIR will also assess the longer-term applicability of identity management methods, processes and technologies currently in use in healthcare and other sectors.

The person hired for this two-year opportunity will be a HIMSS employee who will work onsite in the office of the HHS chief technology officer, to foster further collaboration with stakeholders across the healthcare community and in collaboration with ONC. Candidates with experience in innovative approaches to health information technology development and project management are invited to apply, officials say.

“I encourage anyone who wants to have a substantial and transformative effect on healthcare to apply for this exciting opportunity,” Bryan Sivak, HHS chief technology officer, said in a statement.  “The work of the IIR will lead to establishing metrics of patient matching technology approaches and create a pathway for evaluating solutions. When looking back, successes of the IIR will include engaging stakeholders to adopt approaches that will set in motion improvements in technology that improve consistent and reliable patient matching of records.”

HIMSS is one of several groups participating in an ONC Patient Data Matching Initiative announced in September. The project’s recommendations were part of a recent discussion on patient data matching, and provide additional insight into identifying the common attributes that achieve high positive match rates across disparate systems, and begin defining the processes and best practices that are most effective to support high positive patient matching rates utilizing the common attributes.

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