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Date of Award


Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy in Computational Science and Engineering (PhD)

Administrative Home Department

Department of Electrical and Computer Engineering

Advisor 1

Warren Perger

Committee Member 1

Abdul Nasser Alaraje

Committee Member 2

Yu Cai

Committee Member 3

Evgueny Levin


In the United States' healthcare system, challenges surrounding patient identification, interoperability exchange of health records, and complexities in providing a robust security system capable of protecting patient identifiable information (PII) have been widely documented. Consequences include incomplete and inaccurate electronic patient health records, redundant expensive medical tests caused by the lack of interoperability between healthcare institutions, and a significant amount of cases of medical fraud because of inadequate identification mechanisms. To date, no proven solution has been established to offer consistent and accurate identification for users within America's healthcare system. Past literature describes techniques of developing algorithms used to match duplicate patient records and merge into a single record, however results have not been met with high accuracy. Biometric identification research has been conducted extensively, however there have been no successful attempts to link a scalable National Patient Identifier (NPI) to a user’s biometric output. We introduce a new technique of user identification in healthcare. 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 may be completed using standard smartphones and Web cameras in a touchless method. Patients and healthcare professionals no longer need remember complex passwords or worry about their login credentials being stolen as they authenticate using biometrics. Interoperability and security mechanisms are developed and configured to provide an end-to-end accurate national identification and health data exchange. We call our solution UMBRELLA or Unique Medical Biometric Recognition Enforcement of Legitimate and Large-scale Authentication. We present a series of experiments to demonstrate the formation of an accurate and consistent UHID. We reveal the scalability and security of our identification solution through our large-scale distributed network and use a developed use case to illustrate the functionality and accuracy of our research. We expect the UMBRELLA solution to dramatically reduce the complexities associated with user misidentification in healthcare and enhance the interoperability and security mechanisms affiliated with health data exchange, resulting in lowering healthcare costs, enhancing population health monitoring, and improving patient-safety.