ONC Launches Patient Matching Initiative

As part of our ongoing effort to improve patient matching across disparate systems, we are beginning a collaborative project to help identify the common denominators and best practices being used by private sector health care delivery systems and Federal agencies. By identifying and recommending standardization of the basic attributes most commonly used for patient matching, we are looking to improve patient safety, care coordination and efficiency.

This new project will focus on two specific objectives related to patient matching:

  • Identifying the common attributes that achieve high positive match rates across disparate systems. The attributes may include common fields such as name, date of birth, address, sex, cell phone number and new criteria such as emergency contact and insurer.
  • Defining the processes and best practices that are most effective to support high positive patient matching rates utilizing these attributes.

As part of the new Patient Matching Initiative, environmental scans and widespread literature reviews will be conducted to inform the next steps in the project. Partners in the project include the Federal Health Architecture – which is made up of more than 20 federal agencies (Department of Health & Human Services, Department of Defense, Department of Veterans Affairs and the Social Security Administration) and CHIME, HIMSS, the Bipartisan Policy Center, HealtheWay, the EHR/HIE Interoperability Work Group, many large integrated delivery networks and state and local health information exchange organizations. The Patient Matching Initiative will end later this year and participants will present a list of recommendations to The National Coordinator for consideration.

Audacious Inquiry (Ai) will support these activities. Ai has provided market reports on patient matching and other critical topics to support the implementation of health information exchange by the Office of the National Coordinator. Ai also provides technical support for the Maryland Health Information Exchange (CRISP) and developed, implemented and oversees patient matching activities in the state.



  1. Paula Steeper says:

    This sounds interesting. I’m a physical therapist and in the healthcare field for 30+ years. I’ve been through lots of changes in that time. I’d like to learn more about this initiative. Paula Steeper

  2. Joel Kallich says:

    suggest you look at using encryption technology – IMS has the patents on it right now, but others could develop. Talk to Daniel Barth-Jones at Columbia about it.

  3. Robert E. Connors says:

    Are you aware of the significant work performed by Sysnet International, Inc. on creating a scalable patient identity matching service for the NHIN, using Open EMPI? This was funded by SBIR dollars. I was the government contracting officer representative. Lauren Thompson is aware of this work. Why not leverage it. Bob Connors, Henry Jackson Foundation, on contract to U.S. Army Telemedicine and Advanced Technology Research Center, Fort Detrick, MD.

  4. Hemant Shah says:

    At first I thought this was an exciting idea but on reading further, it just seems to be about reconciling patient IDs.

    However, won’t it be cool, if you could create a service that matches patients, no matter which system or geographical region they belong to, based on their clinical characteristics. They can then be studied together. They could even be encouraged form a community or pairings with each other and then share their experiences.

  5. Lynn Hickey says:

    We are standing up our private HIE with eClinicalWorks eHX and I’ve been watching for industry standards about “patient matching.” There are considerable workflow considerations (devil in the details) that can make this decision making tricky. However, in working with innovative companies like AInq …they stay open to those workflows and have worked with us to implement creative alternatives. For example, baby’s first name is not available during registration and the registrar is suppose to adhere to a standard which allows for filtering out until…first name is given, then subsequent messages can be matched. Fictitous names are also tricky…jane and john doe processing.

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