A Patient Matching Blind Spot

As a member of HIMSS, you likely know that patient matching is one of the most significant (and persistent!) barriers to accurate and useful health information exchange. Working with the Care Connectivity Consortium (CCC), The Sequoia Project has invested two years exploring this issue and developing best practices to guide the industry.

Organizations providing healthcare often believe they have good patient identity management strategies. In fact, many progressive organizations do have great patient matching success rates – internally. But when patient matching is extended across cross organizational boundaries, as our forth-coming case study illustrates, match rates can plummet. So the question becomes why?

Part of the solution, I feel, is due to lack of adequate industry tools to assess patient matching capabilities.

The Sequoia Project is publishing soon A Framework for Cross-Organization Patient Identity Management for public comment. The framework includes several detailed proposals to enhance patient matching capabilities nationwide. One key proposal is the creation of a patient matching maturity model designed to help organizations assess their current state of cross-organizational identity management and provide a roadmap towards methodically improving.

I believe that the creation of the maturity model will give organizations the ability to adopt more advanced patient identity management in a methodical manner. The levels currently being contemplated in our proposed maturity model include:


These levels are based in part on an International Organization for Standardization (ISO) framework, which includes people, process, and technology, with the added dimension of governance. Current topics associated with the various levels include patient matching validation plans, community collaboration, use of standards, quality metrics, knowledge sharing, partner onboarding maturity, and more. Each of these topics is defined and mapped to appropriate maturity levels.

I’m very excited to share our detailed proposal defining each of these levels of the maturity model and optimistic that it help give us a much-needed tool to assess and measure improvement. Watch for our initial release of the framework in coming days, when we will also open the public comment period. I hope that the HIMSS community will contribute and be instrumental in shaping the national dialogue of identity management strategies.

Even after the public comment period, the proposed patient matching maturity model will continue to be a living document. It will be refined through a public disposition process and higher levels of maturity will be more broadly defined and illustrated going-forward, whereas the initial release will focus on Level 0 and Level 1.

In addition to the patient matching maturity model, the robust A Framework for Cross-Organization Patient Identity Management paper includes a compelling, real-world case study, with actionable insights and replicate-able strategies for all organizations seeking more accurate and useful data exchange. It also offers a very low-level, and concrete, list of cross-organizational patient matching practices for CIOs, CTOs and other technology leaders to adopt and implement minimally acceptable patient matching practices.

With the support of the entire healthcare industry continuum, I hope the framework will expand to meet newly discovered challenges in patient matching across health information exchange partners. In addition to publishing this framework for public comment, we are planning a series of webinars on the topic of patient matching and some proposed solutions.

I look forward to continued engagement by the HIMSS community as we strive for a better national patient matching framework for the benefit of all our patients.

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