Please use this identifier to cite or link to this item: /library/oar/handle/123456789/129597
Title: A blockchain-based framework and process guide for intelligent exchange and use of health information in low resource environments
Authors: Chukwu, NnaEmeka (2024)
Keywords: Medical records -- Data processing
Medical informatics
Blockchains (Databases)
Public health
Health informatics
Management information systems
Issue Date: 2024
Citation: Chukwu, N. (2024). A blockchain-based framework and process guide for intelligent exchange and use of health information in low resource environments (Doctoral dissertation).
Abstract: Enterprise software systems integration can be simple or complicated depending on the number of components and predictability of component interactions. Designing enterprise software systems with many adaptive components that learn as they interact is not easy. Software systems are often designed as function-specific systems that mimic user concerns modeled around organizational structure and communication patterns. Even a single and simple enterprise now has multiple integrated applications. Traditional integration styles are file sharing, shared databases, remote procedure calls, and messaging. These traditional approaches often require a trusted and centralized access-issuing database owner for multi-stakeholder enterprise systems. In the last decade, a new trustless software integration pattern has been facilitated by blockchain. Enterprise blockchain frameworks have been developed, yet practical use cases are few. Use cases still require domain data standardization, token modeling, and interface for regulatory intervention while preserving participants' privacy. This Thesis investigates enterprise integration using the Health 福利在线免费 Exchange (HIE) use case whose value proposition to healthcare stakeholders is well established. Governments, software vendors, non-profits, and private players traditionally perform the central HIE intermediation role. These intermediation efforts faced many bottlenecks. One main challenge is exchanging large numbers of structured, unstructured, and standardized datasets and terminology sets. This complexity has, over the years, resulted in many healthcare data standards.
Description: Ph.D.(Melit.)
URI: https://www.um.edu.mt/library/oar/handle/123456789/129597
Appears in Collections:Dissertations - FacICT - 2024
Dissertations - FacICTCIS - 2024

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