Three Decades (and Counting) of the Patient Record Matching Challenge

Three Decades (and Counting) of the Patient Record Matching Challenge

This monthly blog highlights and discuss emerging trends and challenges related to healthcare data and its ever changing life cycle.

By Lorraine Fernandes, RHIA


The Pew Charitable Trusts (Pew) released their latest white paper, Enhanced Patient Matching is Critical to Achieving Full Promise of Digital Health Records, on October 2 and held a very insightful webcast outlining their key points. The white paper outlines the history of patient record matching and record linkage and introduces key actions that could advance this decades-old topic. All the webcast panelists reinforced the need for a solution approach, as there is no silver bullet.

AHIMA and its members have invested considerable resources and participated in many industry initiatives addressing this topic over the past three decades, so I won’t belabor the past. What’s exciting is that the Pew white paper and AHIMA activities are beginning to converge into actionable steps that may finally transform patient matching.

AHIMA has published widely about the topic and its ties to data governance, including Practice Briefs and member surveys. Last month, I published a blog post that discussed the August 2018 RAND study, funded by Pew, that explored the consumer engagement angle of patient record matching.

I’m discussing records and consumers (not just patients) in this post, as healthcare extends beyond the four walls of an organization to incorporate the shift to wellness and new payment models. Today’s healthcare consumers have different priorities that may vary by the moment. For example, a person with a broken bone is immediately a patient who wants to be treated quickly and have their pain relieved; however, they’re also a consumer as they want to ensure that their insurance will cover the costs or limit their out of pocket expenses.

Pew recommends eight near- and long-term opportunities to advance matching.

  1. Clarify funding. The report states: “Congress should examine whether to maintain the funding ban on the Department of Health and Human Services implementing a unique health identifier, and it should encourage federal agencies to collaborate with the private sector on solution.” The Centers for Medicare and Medicaid Services could also advance clarity by setting matching goals for participating provider organizations.
  2. Agreement on data elements and standards. Technology vendors should agree on which data elements to collect and use in record matching. During the webcast, Dr. Shaun Grannis, MD, MS, FAAFP, director of the Center for Biomedical Informatics at the Regenstrief Institute, shared that his recent research has shown that using standardized name and address fields can improve matching by double digits. While Grannis cautioned during the webcast that “your mileage may vary,” this is certainly a big step forward.
  3. Verification of data. Demographic data used in record matching should be verified by the patient. This might easily be handled with smartphone technology that would not only support data verification, but also increase reliability of the cell phone number as an aid to matching. This ties to #7 in this list, described below.
  4. Assess privacy. Addressing ongoing concerns (both real and perceived) about privacy of consumer/patient data is essential in establishing trust as the various solutions progress. The feedback from the patient focus groups conducted as part of the study clearly illustrated this point.
  5. Examine referential matching. Using data outside healthcare (this goes considerably beyond credit bureau data) to advance the accuracy of patient record matching may be a key step. Referential matching has shown very high match rates. However, independent studies should be done to verify the effectiveness before referential matching could be used on a national scale.
  6. Establish a trusted entity. “A single, national organization should exist to help advance the identification and adoption of standards.” This entity, perhaps as a part of Trusted Exchange Framework and Common Agreement (TEFCA ) rollout, could advance the recommendations more quickly and ensure multi-stakeholder involvement.
  7. Leverage smartphones. Pew’s Patient-Empowered Approaches to Improving Record Matching, released in August 2018, discusses three key steps: engaging consumers in collection of their data, validating matching data accuracy, and using a validated cell phone number as a key matching data element.
  8. Identify infrastructure. “Finally, government, technology developers, health care organizations, and other stakeholders should collaborate on how to establish a federated model where many types of authenticators—including biometrics and smartphones—are able to be used along with demographic data.” This ties to National Institute of Standard and Technology (NIST) activities that are particularly important given the shift to wellness, consumer empowerment, and data challenges that exist in all industries.

As an AHIMA member and health information management (HIM) professional specializing in data governance and patient identity practices, I suggest Pew consider two additional areas that would advance the conversations and inspire action:

  • Engage professional associations that “live in the trenches” with this issue. Pew did a great job engaging C-level executives who can approve, support, and fund actions. I believe that also engaging AHIMA and NAHAM will advanced their causes. I’ve worked with both associations and believe their members will support involvement and add an even greater perspective to this endeavor. Insight from members of NAHAM and AHIMA members on workflow impact and optimization—and on patient/consumer interactions—would be particularly valuable.
  • Promote a study to truly quantify the cost of incorrect matching to patient safety, resources, claims denials, and more. I worked on this need almost a decade ago when HIMSS released their Patient Identity Toolkit. Alas, the complexities of defining how to conduct such a study and secure funding proved to be insurmountable. When records are incorrectly matched, so many things can go wrong, from improper treatment and HIPAA violations to avoidable safety events and delayed claims payments, all of which create lost confidence for both the patient and provider. These costs are hard to quantify, yet so important. Having this type of research data could prove to be an objective, motivating factor for all parties.

I’ve spent three decades addressing this challenge in a variety of roles and settings. I support the recommendations Pew has made and hope the recently intensified drumbeat bodes well for action and the ultimate resolution of this challenge.

HIM professionals need to share this Pew report and its recommendations with healthcare organization leaders throughout the country. From there, it can be used to discuss what each of us can do today—and then tomorrow—to begin making proactive changes. But it will take concerted action at local healthcare organizations, driven by shared goals, to begin improving matching everywhere.


Lorraine Fernandes is principal at Fernandes Healthcare Insights.

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