Biometrics and the future of patient matching and patient identification
Oct | 26 | 2018 —
Biometrics will undoubtedly play a huge role in the future of patient identification and patient matching at health systems. In fact, in a report published earlier this month, The Pew Charitable Trusts highlighted biometric technologies as one of four cornerstone opportunities to improve patient matching and interoperability nationwide (download the report here). And the same report, which was the culmination of two years of research by Pew, found that patients themselves were excited about the prospects of biometric technologies.
However, while biometrics are a key piece of the puzzle in solving our nation’s challenges in identifying patients and linking health data to the correct patients, they are still just one piece of the puzzle.
Let me give three examples to demonstrate why any biometric solution will always have to be complemented by sophisticated demographics-based patient matching technologies and robust patient matching processes.
(1) Biometric solutions will not help reconcile, match, and link existing medical records
Implementing a biometric solution today to help identify your patients will do nothing to resolve any existing duplicate medical records in your systems or to link existing data across your organization. Think about it: if you already have three duplicate records for Jane Smith in your EHR, scanning Jane’s fingerprint at registration the next time she comes in won’t help you find or link those three existing records to Jane’s newly created record.
Instead, the only way to find and resolve these medical records for Jane is by using patient matching technologies and processes that use the demographic data in Jane’s records to identify the duplicates and link them together.
(2) Biometric solutions will not help link patient records across facilities that use different biometric modalities
Consider two facilities in a health system. One uses a fingerprint scanner, the other uses an iris scanner. If Jane Smith gets her fingerprint scanned at the first facility, and her iris scanned at the second, how can the health system link those two records together? The answer is that it will have to rely on demographics-based patient matching technologies that use Jane’s name, address, birthday, and other data to figure out that Jane with fingerprint X and Jane with iris scan Y are really the same person.
This becomes especially important when health systems acquire hospitals or facilities that use different biometric modalities to identify their patients—or that don’t use biometrics at all. In this circumstance, demographics-based patient matching technologies will have to be used to identify common patients shared with any newly acquired facilities and to resolve any duplicate records that arise as a result of integrating the new patient data sources.
(3) Biometric solutions will not help link patient records across organizations that use different biometric modalities
Similar to scenario (2), even if an entire health system adopts the same biometric readers across all of its facilities, that health system will still have to find and identify patient records during health information exchange. And unless every organization in the U.S. adopts the same biometric reader from the same vendor, health systems will still have to fall back on demographics-based patient matching technologies to facilitate interoperability and to find records during health information exchange.
Ultimately, demographic data will always remain the “lowest common denominator” health systems can use to identify, match, and link patient data within their systems and with other organizations. Which means that no matter how sophisticated or robust your biometrics strategy is, you will always need to complement it with an equally sophisticated and robust demographics-based patient matching strategy.
At Verato, we have biometrics partners we work with—and together we can help you architect an end-to-end solution for patient identity and patient matching that incorporates world-class biometrics technologies and the revolutionary Referential Matching technology that we have pioneered. Referential Matching is a revolutionary demographics-based patient matching technology—and it was also one of the other four cornerstone opportunities highlighted by the Pew report to improve patient matching and interoperability nationwide.