Convention Q&A: Crawl, Walk, Run: Three Easy Ways to Solve Patient Matching at Your Organization

Mark LaRow, MS

The 2018 AHIMA convention session, “Crawl, Walk, Run: Three Easy Ways to Solve Patient Matching at Your Organization,” will take place Monday, September 24 in room 229 AB of the Miami Convention Center. The Journal of AHIMA recently spoke with presenter Mark LaRow, MS, for a preview of his session.

Journal of AHIMA: What are you hoping members will take away from your session?

LaRow: I hope attendees take away that there is a powerful new and entirely different patient-matching technology called Referential Matching that is a quantum leap more accurate than the matching technologies currently found in EHRs and EMPIs. I also hope attendees take away that any organization can quickly, easily, and dramatically improve its patient matching and reduce its duplicate records using this new Referential Matching technology—without disrupting any existing processes or technologies they already have in place.

Journal of AHIMA: What should HIM professionals be focusing on now in terms of patient matching?

LaRow: HIM professionals should think of Referential Matching technology as the easiest way to assist them in keeping patient data clean and correctly linked to the right patient, without disrupting existing technologies or processes. Because it is such a new technology—and a totally different paradigm in patient matching—AHIMA members should focus on familiarizing themselves with what Referential Matching technology is, how it works, and the benefits.

Journal of AHIMA: Can you tell me more about Referential Matching?

LaRow: Simply put, Referential Matching is the new gold standard in patient matching technology. To understand, it first helps to understand conventional matching technologies, which operate by directly comparing the demographic data from two patient records to see if that data is the same—data like names, addresses, and birthdates. If the demographic data from two patient records perfectly aligns or is very close, the conventional patient matching technology will say those records match—in other words, that they must belong to the same person. But this means that conventional patient matching technologies are fundamentally limited by the quality and completeness of the underlying patient demographic data they are comparing. For example, no conventional matching technology, no matter how sophisticated, can match two records if one contains a patient’s maiden name, old address, and phone number, and the other contains that patient’s married name, new address, and birthdate.

On the other hand, Referential Matching technology compares the demographic data from two patient records to a comprehensive and continuously updated reference database of identities. This proprietary database contains over 300 million identities spanning the entire US population, and each identity contains a complete profile of demographic data spanning a 30-year history. This reference database is essentially a pre-built answer key for patient demographic data. By referencing this answer key during matching, Referential Matching technology can make matches that conventional patient matching technologies could never make, including patient records that have out-of-date, incomplete, incorrect, or very different demographic data. In other words, unlike conventional patient matching technologies, Referential Matching technology is not limited by the quality of underlying patient demographic data it is matching; and maintains its accuracy even in the face of very low quality or incomplete data.

Journal of AHIMA: How should AHIMA members be preparing for these changes to the patient matching system?

LaRow: Users of Referential Matching services will see massive productivity improvements in their HIM processes. For example, they can use Referential Matching services to automatically remediate many of the suspected duplicate records their EHR or EMPI has flagged for manual remediation. And because Referential Matching technology can dramatically improve patient matching accuracy, reduce duplicate records, and accelerate HIM processes—thereby reducing costs and improving patient care and safety—AHIMA members should prepare themselves to champion Referential Matching technology at their organizations.

Journal of AHIMA: How can attendees start incorporating the lessons from your session in their organization right away?

LaRow: Attendees can start incorporating the lessons from my session in two ways. First, if they don’t know how bad their duplicate patient record problem is—or even if they think they know—they should look to Referential Matching diagnostic services to gain an x-ray of their EHR or EMPI. This scan can help attendees understand how many duplicate patient records they truly have and what specific data issues are causing these duplicates to be generated. Second, HIM professionals who have a long task queue of duplicate records that need to be manually remediated should look to Referential Matching services to help them automate this remediation and accelerate HIM processes.

Journal of AHIMA: Is there anything else you would like members to know about your session or data analytics in general?

LaRow: Accurate patient matching has become 10 times more critical but also 10 times more challenging. The weight of this critical challenge rests squarely on the shoulders of HIM professionals, whose work often goes unsupported and unrecognized. HIM professionals should view Referential Matching as a silver bullet for their organization’s patient matching challenges, as it can significantly improve their productivity, improve their day-to-day work, improve their patient matching, and help automate the remediation of their organization’s duplicate patient records.

Mark LaRow, MS, is the chief executive officer of Verato in McLean, VA.

The session “Crawl, Walk, Run: Three Easy Ways to Solve Patient Matching at Your Organization” will take place Monday, September 24 at the Miami Convention Center, 4:30 – 5:15 p.m., Art Deco Ballroom—Room 229 AB.

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