Verato pens letter to U.S. Senate and House recommending Referential Matching as nationwide strategy
This week, Verato wrote a letter to the Senate Committee on Health, Education, Labor and Pensions (HELP); the Senate Finance Committee; and the House Energy and Commerce Committee urging them to consider a fundamentally different approach to patient matching – called Referential Matching – that will finally enable an accurate, secure, and scalable nationwide patient matching strategy. Read the full contents of the letter below.
To Whom It May Concern:
Patient matching has gained attention on a national scale. In Congress, lawmakers recognize that it is critical to providing better medical care, reducing medical errors, and reducing healthcare costs.
Detailed in this letter is background on a new alternative patient matching technology and a request from Verato to meet and discuss this issue with you. We want to ensure informed public policy and encourage you to reach out to us as a resource.
In the 21st Century Cures Act, Congress requires the GAO to “evaluate the efforts, policies and activities of the Office of the National Coordinator (ONC) for Health Information Technology around patient matching methods and areas of improvement.” Furthermore, Congress included language in the FY17 Omnibus spending bill to “aid in the efforts toward an improved national patient matching strategy,” which is a dramatic change from its previous prohibition of HHS from working with the private sector on the development of a unique patient identifier. This new language encourages the Secretary to “provide technical assistance to private-sector led initiatives to develop a coordinated national strategy that will promote patient safety by accurately identifying patients to their health information.”
Additionally, in early October 2017, a bi-partisan group of senators (Elizabeth Warren, D-Massachusetts, Orrin Hatch, R-Utah, Tammy Baldwin, D-Wisconsin, Sheldon Whitehouse, D-Rhode Island, and Bill Cassidy, R-Louisiana) penned a letter to Gene L. Dodaro, Comptroller General, U.S. GAO requesting that GAO “provide data on the prevalence of patient data mismatches as well as the costs and risks associated with these mismatches.” More importantly, they urge the GAO to “recommend specific strategies that would improve patient matching, including the consideration of a national patient matching strategy.”
There are reasons why patient matching is so difficult. A unique patient identification number creates privacy issues, which explains the prohibition originally imposed by congress on funding it in the first place. Furthermore, there are logistical and technical hurdles associated with distributing such a number to everyone and linking the billions of historical medical records to a patient. Therefore, it’s broadly agreed that the nation must continue to rely on error-prone and constantly changing demographic data to identify patients. Unfortunately, current matching technology cannot handle error-prone data well enough for medical records exchange purposes because it is built on “probabilistic matching” algorithms that have long-reached their mathematical limits. Existing patient matching technologies will never work well enough for health record exchange.
Despite years of investment in master patient index (MPI) matching technology, according to the ONC, hospital systems still suffer from poor patient matching, with matching errors occurring in 1 out of 5 patients within a hospital system. What’s worse is that matching errors increase to about 50% when exchanging medical records between hospitals.
In fact, The College of Healthcare Information Management Executives (CHIME) sponsored a $1 million patient matching challenge and the ONC also launched a $75,000 “Patient Matching Algorithm Challenge” in 2017. Both contests looked at traditional matching technologies and both failed to show any real change in matching success rates.
We need a fundamentally different approach – it’s called Referential Matching.
Verato, and a few other companies, have developed a powerful new matching technology called Referential Matching. It uses a massive reference database of identities curated from commercially available sources that embody a 30-year history of demographics for everyone in the U.S. This database serves as an “answer key” for patient matching, allowing it to see through errors and changes over time. This is something that probabilistic matching alone can never manage.
Verato technology is used by healthcare clients, including the largest Health Information Exchanges (HIE), to accurately match patient records that cover upwards of 15-20% of the US population within and across healthcare enterprises. In benchmark tests, Verato patient matching can achieve match accuracy rates of 98% where the best probabilistic matching can only achieve 70%. Verato has shown that it can solve the problem of patient matching within the four walls of a healthcare institution. But it is also uniquely positioned to address the problem of nationwide patient matching.
Because Verato is a shared system where every participating institution “links” its patients to Verato’s reference identities, it’s a simple step to allow every Verato customer to link its patient identities with each other. This is an incremental, ground-up approach to solving the national problem – as each institution begins using Verato for its internal matching needs, it is automatically able to exchange identities with any other Verato institutions. However, taking this example one step further, if a governing body allows for Verato to be a “clearinghouse” for matching records on a national scale, every healthcare institution would continue to locate records using their preferred regional HIEs and any of the nationwide networks (e.g. CommonWell or Carequality). These networks register their patients with Verato, which links them all together with superior Referential Matching.
In light of the recent congressional requests to the GAO to develop a national patient matching strategy, we request that you consider Referential Matching as an alternative to existing patient matching technologies which have failed our healthcare system. We would welcome the opportunity to brief you on our approach, customer outcomes, and vision for the future. In developing recommendations around a national patient matching strategy, we believe that the healthcare industry would be at a disadvantage by not considering this innovation in patient matching technology.
Thank you for your attention to our request.