Privacy-Preserving Prescription Drug Management Using Fully Homomorphic Encryption

Aria Shahverdi (), Ni Trieu (), Chenkai Weng () and William Youmans ()
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Aria Shahverdi: University of Maryland
Ni Trieu: Arizona State University
Chenkai Weng: Northwestern University
William Youmans: University of South Florida

A chapter in Protecting Privacy through Homomorphic Encryption, 2021, pp 169-176 from Springer

Abstract: Abstract In an effort to combat the ongoing opioid epidemic in the U.S. many states have adopted a Prescription Drug Management Program (PDMP). In most cases, this program has evolved into central state-wide databases for storing sensitive patient prescription records, intended for use by health care professionals to make more accurate prescribing and dispensing decisions per patient. We outline the security and privacy concerns that arise and propose a solution using privacy-preserving machine learning and fully homomorphic encryption.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-77287-1_14

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DOI: 10.1007/978-3-030-77287-1_14

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