ONC Releases Findings From Patient Data Matching Study

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During a webinar on Monday, the Office of the National Coordinator for Health IT released initial findings from a patient identification and matching stakeholder study on the health care industry's ability to match patients with their health information, Health Data Management reports.

The study included interviews with more than 50 large health systems and health IT software developers.

According to Health Data Management, ONC does not plan to release the report publicly because the findings are not official policy (Goedert, Health Data Management, 12/16).

Background

In September, ONC announced it would launch a collaborative project to determine "common denominators and best practices" used by private health systems and federal agencies for matching patients with their data during health information exchange.

Lee Stevens -- policy director for ONC's State Health Information Exchange Program -- wrote in a Health IT Buzz post that the project would have two main objectives:

  • To define common features that achieve high positive match rates across different systems; and
  • To define the processes and best practices that are most effective to support high positive matching rates.

The goal of the project is to improve patient safety, care coordination and efficiency, according to Stevens (iHealthBeat, 9/11).

Details of Findings

The report recommended that all relevant health information exchange transactions should include standardized patient identifying attributes, including:

  • Current and past addresses;
  • Date of birth;
  • Full name;
  • Gender; and
  • Phone numbers.

The report also suggested that:

  • Additional data attributes to improve patient matching should be studied;
  • An open source algorithm should be developed to test and build patient matching capabilities;
  • Certified electronic health record systems should be required to generate and provide reports that detail potential duplicate patient records; and
  • EHR certification criteria should include the ability to capture patient identifying attributes.

In addition, the report stated that industry stakeholders should work to develop:

  • Formal best practices for patient matching and data governance;
  • Policies to encourage consumers to keep their health information accurate and up to date; and
  • Educational and training materials for verifying patient data attributes (Health Data Management, 12/16).

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