Proposed Privacy-Preserving Framework on Medical Handwritten Prescription Using Blockchain

Kunal Kumar Mandal () and Abhoy Chand Mondal ()
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Kunal Kumar Mandal: Mankar College, The Department of Computer Science
Abhoy Chand Mondal: The University of Burdwan, The Department of Computer Science

A chapter in AI in Smart and Secure Healthcare, 2026, pp 361-377 from Springer

Abstract: Abstract Therapeutically manually written medicines are still a backbone of healthcare communication within the wake of electronic health records (EHRs). Medically handwritten prescriptions, however, suffer from problems of confusion, ambiguity, and waste, leading to medication errors and safety concerns. The taking after paper presents an all-encompassing outline of remedial transcribed medicines, their history, and innovative advancements that overcome their confinements. This research proposes the PharmaChain-Secure (PCS) framework as a secure and privacy-preserving solution for the growing scope of the various issues of handwritten medical prescriptions in Indian healthcare organizations. The system leverages blockchain technology and advanced cryptographic tools like Zero-Knowledge Proofs (ZKPs) and Homomorphic Encryption (HE) to create a decentralized, trustworthy platform that puts prescription lifecycle management back in the patient’s control.

Keywords: Electronic health records; Optical character recognition; Machine learning; Deep learning; Natural language processing; Convolutional recurrent neural network; Zero-knowledge proof; Homomorphic encryption; Blockchain (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-15092-9_14

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