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Methods of Enhancing Patient Matching Processes

October 6, 2016 / by Catherine Schulten

In early September, the Interoperability Task Force (IXTF) in conjunction with HITPC and HITSC (Health IT Standards and Policy Committees) sent Dr. Washington (the new National Coordinator for Health Information Technology) a letter describing their charter and recommendations. Not surprisingly the #1 priority need identified from this group was the ability to identify patient's nationwide.

The Task Force held several meetings and subgroup calls that identified 8 distinct priority needs across the 5 use cases detailed in Appendix B:
  • Ability to identify patients nationwide
  • Ability to locate relevant patient records
  • Ability to locate and identify providers
  • Ability to access and interpret consents/authorizations
  • Ability to exchange health information
  • Ability to encode data that is syntactically and semantically interoperable
  • Ability to effectively utilize health information
  • Governance

Appendix B describes identifying patients as consisting of the following elements:
  • Capture standardized demographics for patients
  • Patient matching algorithm
  • Show how to communicate with patients
  • Ability to exchange health information
  • Show proxy relationships and how to communicate with them
  • Show authenticated devices and how to communicate with them

And while the IXTF brought this important topic to light, once again we observe that the mechanisms by which to achieve this goal remain stuck in legacy thinking: a national agreement on demographic attributes and matching logic by which to establish patient matching.

It has been noted by the Sequoia Project that a match rate of 95% to 98% may be the upward limit of accuracy that any healthcare organization can hope to achieve. Once this match rate was identified, a cross-organizational maturity model involving data governance, data cleaning/normalization and supplemental identifiers (just to name a few) were included in the design.

If the best we can hope to achieve is 98% matching accuracy and 2% of the records continue to be mismatched, overlaid or otherwise discounted during a search and match attempt, then it’s time that the industry look at another way to solve this challenge.

We’ve seen that the industry is anticipating a solution that will solve the patient identity challenge once and for all:
  • The CHIME Challenge seeks to “ensure 100% accuracy of every patient’s health info to reduce preventable medical errors and eliminate unnecessary hospital costs/resources”
  • The Sequoia Project in collaboration with the Care Connectivity Consortium drafted a Framework for Cross-Organizational Patient Identity Matching wherein they state “Without a national patient ID system, we must focus on optimizing the current patient matching strategies.”

In order to achieve 100% matching accuracy, the current patient matching approach consisting of additional PII attributes, exhaustive attention to data quality and governance and world class matching algorithms won’t get the healthcare industry there. The only way to achieve this is through the use of what is known as a deterministic match. In other words, a 1:1 match with no chance for a false positive or false negative. Fortunately, this type of design has been in place for years.

As an example, consider your ATM and PIN code. You can withdraw cash from any ATM machine across the U.S. and even globally with a card that was issued by your bank and a PIN code that you personally established. When using your card, the funds are withdrawn directly from your account. There aren’t instances where funds are drawn from an account from someone who has a name similar to yours or who has a checking account that is 1 or 2 digits off from yours. The combination of the card and PIN results in only one match.

Catherine Schulten

About the Author

Catherine Schulten is VP of Product Management at LifeMed ID where she is responsible for orchestrating product roadmap initiatives and ensuring that LifeMed ID’s solution offering meets industry user needs. Catherine has over 25 years of health information technology experience addressing industry challenges from revenue cycle, HIPAA transactions, fraud, waste and abuse, and patient identity management. She has served as a WEDI board member and has co-chaired several WEDI workgroups.

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