{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T08:51:32Z","timestamp":1766739092477,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T00:00:00Z","timestamp":1734393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"FCT (Fundac\u00e3o para a Ci\u00eancia e Tecnologia) within the R&amp;D Units Project Scope","award":["UIDB\/00319\/2020"],"award-info":[{"award-number":["UIDB\/00319\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Technologies"],"abstract":"<jats:p>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 a 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 by enabling an integrated Electronic Health Record. This paper explores these technologies\u2019 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 revolutionize healthcare data management, communication, and analysis, improving patient care and operational efficiency.<\/jats:p>","DOI":"10.3390\/technologies12120265","type":"journal-article","created":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T10:54:02Z","timestamp":1734432842000},"page":"265","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Unlocking Healthcare Data Potential: A Comprehensive Integration Approach with GraphQL, openEHR, Redis, and Pervasive Business Intelligence"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2988-196X","authenticated-orcid":false,"given":"Regina","family":"Sousa","sequence":"first","affiliation":[{"name":"LASI\/Algoritmi Research Centre, Universidade do Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3864-6264","authenticated-orcid":false,"given":"Vasco","family":"Abelha","sequence":"additional","affiliation":[{"name":"LASI\/Algoritmi Research Centre, Universidade do Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3957-2121","authenticated-orcid":false,"given":"Hugo","family":"Peixoto","sequence":"additional","affiliation":[{"name":"LASI\/Algoritmi Research Centre, Universidade do Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4121-6169","authenticated-orcid":false,"given":"Jos\u00e9","family":"Machado","sequence":"additional","affiliation":[{"name":"LASI\/Algoritmi Research Centre, Universidade do Minho, 4800-058 Guimar\u00e3es, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Lawi, A., Panggabean, B.L., and Yoshida, T. (2021). Evaluating graphql and rest api services performance in a massive and intensive accessible information system. Computers, 10.","DOI":"10.20944\/preprints202109.0386.v1"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"V\u00e1zquez-Ingelmo, A., Cruz-Benito, J., and Garc\u00eda-Pe\u00f1alvo, F.J. (2017, January 18\u201320). Improving the OEEU\u2019s data-driven technological ecosystem\u2019s interoperability with GraphQL. Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality, C\u00e1diz, Spain.","DOI":"10.1145\/3144826.3145437"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Schewe, K.D., and Singh, N.K. (2019). GraphQL Schema Generation for Data-Intensive Web APIs. Model and Data Engineering, Springer.","DOI":"10.1007\/978-3-030-32065-2"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Mohammed, S., Fiaidhi, J., and Sawyer, D. (2023, January 18\u201319). Problem-Oriented Medical Records for Describing Care Cases Using Multi-Tenants. Proceedings of the 2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), Casablanca, Morocco.","DOI":"10.1109\/IRASET57153.2023.10153018"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"14604582211043920","DOI":"10.1177\/14604582211043920","article-title":"An HL7 FHIR and GraphQL approach for interoperability between heterogeneous Electronic Health Record systems","volume":"27","author":"Mukhiya","year":"2021","journal-title":"Health Inform. J."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Bryant, M. (2017, January 11\u201314). GraphQL for archival metadata: An overview of the EHRI GraphQL API. Proceedings of the 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, USA.","DOI":"10.1109\/BigData.2017.8258173"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mohammed, S., Fiaidhi, J., and Sawyer, D. (2021, January 15\u201318). GraphQL Patient Case Presentation using the Problem Oriented Medical Record Schema. Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA.","DOI":"10.1109\/BigData52589.2021.9671394"},{"key":"ref_8","first-page":"1","article-title":"GraphQL: A systematic mapping study","volume":"55","author":"Fernandez","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kotiranta, P., Junkkari, M., and Nummenmaa, J. (2022). Performance of Graph and Relational Databases in Complex Queries. Appl. Sci., 12.","DOI":"10.3390\/app12136490"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Marchuk, Y., Dyyak, I., and Makar, I. (2023, January 26\u201328). Performance Analysis of Database Access: Comparison of Direct Connection, ORM, REST API and GraphQL Approaches. Proceedings of the 2023 IEEE 13th International Conference on Electronics and Information Technologies (ELIT), Lviv, Ukraine.","DOI":"10.1109\/ELIT61488.2023.10310748"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s10606-017-9269-x","article-title":"Infrastructuring in Healthcare through the OpenEHR Architecture","volume":"26","author":"Severinsen","year":"2017","journal-title":"Comput. Support. Coop. Work (CSCW)"},{"key":"ref_12","first-page":"153","article-title":"The openEHR foundation","volume":"115","author":"Kalra","year":"2005","journal-title":"Stud. Health Technol. Inform."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Frade, S., Freire, S.M., Sundvall, E., Patriarca-Almeida, J.H., and Cruz-Correia, R. (2013, January 20\u201322). Survey of openEHR storage implementations. Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, Porto, Portugal.","DOI":"10.1109\/CBMS.2013.6627806"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1016\/j.procs.2023.03.118","article-title":"OpenEHR and Business Intelligence in healthcare: An overview","volume":"220","author":"Cunha","year":"2023","journal-title":"Procedia Comput. Sci."},{"key":"ref_15","first-page":"47","article-title":"Comparison of OpenEHR and HL7 FHIR Standards","volume":"69","author":"Kryszyn","year":"2023","journal-title":"Int. J. Electron. Telecommun."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Anutariya, C., and Bonsangue, M.M. (2023). Enhancing Data Science Interoperability: An Innovative System for Managing OpenEHR Structures. Data Science and Artificial Intelligence, Springer.","DOI":"10.1007\/978-981-99-7969-1"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"e48702","DOI":"10.2196\/48702","article-title":"Can OpenEHR, ISO 13606, and HL7 FHIR Work Together? An Agnostic Approach for the Selection and Application of Electronic Health Record Standards to the Next-Generation Health Data Spaces","volume":"25","author":"Frid","year":"2023","journal-title":"J. Med. Internet Res."},{"key":"ref_18","unstructured":"Carlson, J.L. (2013). Redis in Action, Manning."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kumari, A., and Sahoo, B. (2022). Serverless Architecture for Healthcare Management Systems. Handbook of Research on Mathematical Modeling for Smart Healthcare Systems, IGI Global.","DOI":"10.4018\/978-1-6684-4580-8.ch011"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.trpro.2019.07.027","article-title":"Comparison of query performance in relational a non-relation databases","volume":"40","author":"Kvet","year":"2019","journal-title":"Transp. Res. Procedia"},{"key":"ref_21","unstructured":"Choi, D. (2020). Full-Stack React, TypeScript, and Node: Build Cloud-Ready Web Applications Using React 17 with Hooks and GraphQL, Packt Publishing Ltd."},{"key":"ref_22","unstructured":"Saxena, U., Sachdeva, S., and Batra, S. (2015, January 23\u201325). Moving from relational data storage to decentralized structured storage system. Proceedings of the Databases in Networked Information Systems: 10th International Workshop, DNIS 2015, Aizu-Wakamatsu, Japan. Proceedings 10."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Muradova, G., Hematyar, M., and Jamalova, J. (2022, January 12\u201314). Advantages of Redis in-memory database to efficiently search for healthcare medical supplies using geospatial data. Proceedings of the 2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT), Washington, DC, USA.","DOI":"10.1109\/AICT55583.2022.10013544"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Sayar, A., \u015euayip, A., \u00c7akar, T., Ertugrul, S., and Ak\u00e7ay, A. (2023, January 11\u201313). High-Performance Real-Time Data Processing: Managing Data Using Debezium, Postgres, Kafka, and Redis. Proceedings of the 2023 Innovations in Intelligent Systems and Applications Conference (ASYU), Sivas, Turkey.","DOI":"10.1109\/ASYU58738.2023.10296737"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.33039\/ami.2022.12.006","article-title":"Benchmarking Redis and HBase NoSQL Databases using Yahoo Cloud Service Benchmarking tool","volume":"56","author":"Alzaidi","year":"2023","journal-title":"Ann. Math. Informaticae"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.procs.2016.09.055","article-title":"Pervasive Business Intelligence: A New Trend in Critical Healthcare","volume":"98","author":"Pereira","year":"2016","journal-title":"Procedia Comput. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Esteves, M., Miranda, F., and Abelha, A. (2018). Pervasive Business Intelligence Platform to Support the Decision-Making Process in Waiting Lists. Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering, IGI Global.","DOI":"10.4018\/978-1-5225-2851-7.ch012"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.1007\/s11276-018-01911-6","article-title":"The development of a pervasive Web application to alert patients based on business intelligence clinical indicators: A case study in a health institution","volume":"28","author":"Esteves","year":"2022","journal-title":"Wirel. Netw."},{"key":"ref_29","unstructured":"Foad, M., Rafa, I.S., and Navid, S.R.A. (2018). Intelligent Medical Data Recording & Management System. [Ph.D. Thesis, BRAC University]."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Mohammed, S., Fiaidhi, J., and Sawyer, D. (2021, January 9\u201312). Problem Oriented Diagnostic Service for Describing Clinical Cases based on the GraphQL POMR Approach. Proceedings of the 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Houston, TX, USA.","DOI":"10.1109\/BIBM52615.2021.9669364"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Singh, M., and Kaur, K. (2015, January 12\u201313). SQL2Neo: Moving health-care data from relational to graph databases. Proceedings of the 2015 IEEE International Advance Computing Conference (IACC), Banglore, India.","DOI":"10.1109\/IADCC.2015.7154801"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Park, Y., Shankar, M., Park, B.H., and Ghosh, J. (April, January 31). Graph databases for large-scale healthcare systems: A framework for efficient data management and data services. Proceedings of the 2014 IEEE 30th International Conference on Data Engineering Workshops, Chicago, IL, USA.","DOI":"10.1109\/ICDEW.2014.6818295"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Mohammed, S., Fiaidhi, J., and Sawyer, D. (2022, January 17\u201320). Prototyping the Problem Oriented Medical Record for Connected Health Based on TypeGraphQL. Proceedings of the 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan.","DOI":"10.1109\/BigData55660.2022.10020388"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Oliveira, D., Coimbra, A., Miranda, F., Abreu, N., Leuschner, P., Machado, J., and Abelha, A. (2018). New approach to an openEHR introduction in a Portuguese healthcare facility. Trends and Advances in Information Systems and Technologies: Volume 3, Springer.","DOI":"10.1007\/978-3-319-77700-9_21"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Ferrer, A., Peleg, M., Verhees, B., Verlinden, J.M., and Marcos, C. (2012). Data integration for clinical decision support based on openEHR archetypes and HL7 virtual medical record. International Workshop on Process-Oriented Information Systems in Healthcare, Springer.","DOI":"10.1007\/978-3-642-36438-9_5"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Pape\u017e, V., Denaxas, S., and Hemingway, H. (2017, January 22\u201324). Evaluating OpenEHR for storing computable representations of electronic health record phenotyping algorithms. Proceedings of the 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece.","DOI":"10.1109\/CBMS.2017.73"},{"key":"ref_37","unstructured":"Krastev, E., Kovatchev, P., Tcharaktchiev, D., and Abanos, S. (2020, January 21\u201325). Primary Use Case Implementation of International Patient Summary on openEHR Platform. Proceedings of the 12th International Conference on e-Health (EH2020), Lisbon, Portugal."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"e23361","DOI":"10.2196\/23361","article-title":"openEHR archetype use and reuse within multilingual clinical data sets: Case study","volume":"22","author":"Leslie","year":"2020","journal-title":"J. Med. Internet Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.1016\/j.procs.2020.03.075","article-title":"An openehr adoption in a portuguese healthcare facility","volume":"170","author":"Hak","year":"2020","journal-title":"Procedia Comput. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1172\/JCI129197","article-title":"Opportunities and challenges in using real-world data for health care","volume":"130","author":"Rudrapatna","year":"2020","journal-title":"J. Clin. Investig."},{"key":"ref_41","first-page":"281","article-title":"Graph databases for openEHR clinical repositories","volume":"20","author":"Helou","year":"2019","journal-title":"Int. J. Comput. Sci. Eng."},{"key":"ref_42","unstructured":"Werbrouck, J., Senthilvel, M., Beetz, J., and Pauwels, P. (2019, January 19\u201321). Querying heterogeneous linked building datasets with context-expanded graphql queries. Proceedings of the 7th Linked Data in Architecture and Construction Workshop, Lisbon, Portugal."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1782","DOI":"10.14778\/3352063.3352065","article-title":"Synergistic graph and SQL analytics inside IBM Db2","volume":"12","author":"Tian","year":"2019","journal-title":"Proc. VLDB Endow."},{"key":"ref_44","unstructured":"Faridoon, A., and Kechadi, M.T. (2024). Healthcare Data Governance, Privacy, and Security\u2014A Conceptual Framework. arXiv."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Ahmed, A., Karim, M.A.D.B., Islam, R., Ahmed, M.T., and Nakashima, N. (2022). An Affordable and Standard Digital Healthcare management as a Service (HaaS) for Small Clinics in Developing Countries. Human Interaction and Emerging Technologies (IHIET 2022): Artificial Intelligence and Future Applications, AHFE International.","DOI":"10.54941\/ahfe1002786"}],"container-title":["Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-7080\/12\/12\/265\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:53:58Z","timestamp":1760115238000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-7080\/12\/12\/265"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,17]]},"references-count":45,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["technologies12120265"],"URL":"https:\/\/doi.org\/10.3390\/technologies12120265","relation":{},"ISSN":["2227-7080"],"issn-type":[{"type":"electronic","value":"2227-7080"}],"subject":[],"published":{"date-parts":[[2024,12,17]]}}}