Version 1
: Received: 6 November 2024 / Approved: 7 November 2024 / Online: 7 November 2024 (15:16:31 CET)
How to cite:
Sousa, R.; Abelha, V.; Peixoto, H.; Machado, J. Unlocking healthcare data potential: A comprehensive integration approach with GraphQL, openEHR, Redis, and Pervasive Business Intelligence. Preprints2024, 2024110538. https://doi.org/10.20944/preprints202411.0538.v1
Sousa, R.; Abelha, V.; Peixoto, H.; Machado, J. Unlocking healthcare data potential: A comprehensive integration approach with GraphQL, openEHR, Redis, and Pervasive Business Intelligence. Preprints 2024, 2024110538. https://doi.org/10.20944/preprints202411.0538.v1
Sousa, R.; Abelha, V.; Peixoto, H.; Machado, J. Unlocking healthcare data potential: A comprehensive integration approach with GraphQL, openEHR, Redis, and Pervasive Business Intelligence. Preprints2024, 2024110538. https://doi.org/10.20944/preprints202411.0538.v1
APA Style
Sousa, R., Abelha, V., Peixoto, H., & Machado, J. (2024). Unlocking healthcare data potential: A comprehensive integration approach with GraphQL, openEHR, Redis, and Pervasive Business Intelligence. Preprints. https://doi.org/10.20944/preprints202411.0538.v1
Chicago/Turabian Style
Sousa, R., Hugo Peixoto and José Machado. 2024 "Unlocking healthcare data potential: A comprehensive integration approach with GraphQL, openEHR, Redis, and Pervasive Business Intelligence" Preprints. https://doi.org/10.20944/preprints202411.0538.v1
Abstract
This paper investigates the transformative potential of integrating technical and methodological tools such as GraphQL, openEHR, Redis, and Pervasive Business Intelligence in healthcare. Modern healthcare systems face data silos, interoperability, and efficient data communication challenges. The integration of these technologies offers innovative solutions to address these challenges. GraphQL, known for its flexible data retrieval capabilities, simplifies data communication and integration. openEHR, a standards-based approach to healthcare data management, fosters interoperability through an unified data model. Redis, a scalable data storage and caching system, enhances application performance and real-time data processing. Pervasive Business Intelligence empowers healthcare analytics, aiding data-driven decision-making. This paper explores these technologies’ benefits, integration possibilities, and synergies. The practical implications of this integration are demonstrated through a real-world case study. The findings underscore the potential to revolutionise healthcare data management, communication, and analysis, improving patient care and operational efficiency.
Keywords
Data interoperability; Healthcare analytics; openEHR; Healthcare data management; Integration technologies; Real-time data processing
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
