Electronic health records (EHRs) offer the promise of improved healthcare coordination, lower cost and improved patient safety. To achieve these benefits providers need to be able to share patient health information, and systems must be able to match patient data from disparate health data silos. Currently, mistakes in patient matching are a substantial contributor to adverse medical events, and correcting mismatched patient records can be as high as several hundred dollars per record. More important than monetary costs are the potential cost in human lives and subsequent legal cost due if a patient receives the wrong treatment. Given the substantive impacts poor patient matching can have on care delivery, population health analyses, and research, it is important for organizations to be able to quantify their patient matching algorithm’s performance and compare the results to industry standard benchmarks and performance metrics.
On this webinar a panel of experts discuss the challenges, such as technical and political hurdles to matching patients. Additionally, hear about current projects underway to advance this challenging problem.