5 Patient Matching Best Practices for Providers to Consider

What is Electronic Patient Matching Anyway? According to HealthIT.gov, patient matching is defined as “the identification and linking of one patient’s data within and across health systems to obtain a comprehensive view of that patient’s health care record.” At a minimum, one can accomplish patient matching by automatically linking multiple demographic data fields such as name, birth date, phone number, and address. Therefore, patient matching is a critical component to interoperability and the nation’s health information technology infrastructure. When providers seek to implement patient matching, they ensure the patient’s primary data is entered into the system. Well, if I need records for James Smith, the patient matching algorithm must search multiple entries for this prevalent name by considering all demographic information imputed by staff. The human element is what makes patient matching one of the most frustrating parts of interoperability. Patient matching isn’t a magic bullet to achieve interoperability. Here are a few of the most powerful patient matching solutions offered today and why they are not a one-stop-shop solution for your interoperability challenges. Pump the breaks and invoke the top five patient matching best practices. Any of the aforementioned patient matching tactics can work, but not without the help of providers and clinical teams on the front lines. Before approaching any “big ideas” regarding patient matching in your overall interoperability strategy, I encourage you to implement these five patient matching best practices. In addition, answering these questions can help you think about the impacts of patient matching to set up the best systems and processes. Many approach patient matching implementations with a “set it and forget it mentality.” The number one thing I hear when connecting with providers is, “I put protocols in place so patient matching will automatically happen, right?” or “doesn’t my EHR already do patient matching for me?” The reality is patient matching — and interoperability at large — require consistent and ongoing adjustments.