Healthcare systems globally continue to face challenges surrounding patient identification. Consequences of misidentification include incomplete and inaccurate electronic patient health records potentially jeopardizing patients' safety, a significant amount of cases of medical fraud because of inadequate identification mechanisms, and difficulties affiliated with the value of remote health self-management application data being aggregated accurately into the user's Electronic Health Record (EHR). We introduce a new technique of user identification in healthcare capable of establishing a global identifier. Our research has developed algorithms capable of establishing a Unique Health Identifier (UHID) based on the user's fingerprint biometric, with the utilization of facial-recognition as a secondary validation step before health records can be accessed. Biometric captures are completed using standard smartphones and Web cameras in a touchless method. We present a series of experiments to demonstrate the formation of an accurate, consistent, and scalable UHID. We hope our solution will aid in the reduction of complexities associated with user misidentification in healthcare resulting in lowering costs, enhancing population health monitoring, and improving patient-safety.