Main Article Content

Ricardo Albuquerque
Luís Filipe Seixas Sardinha
Susana Paulo Albuquerque
Maria Romana Salazar Silva
Eduardo Manuel Leite
Isabel Fragoeiro


The Electronic Health Record (EHR) is the result of a transformation in the current healthcare system, influenced by innovation, integration, and sharing of clinical data. The EHR should include a clinical summary of patients, electronic prescriptions, electronic medication dispensing records, laboratory results, medical images and/or reports, and hospital discharge notes. Prescription errors and therapeutic administration are among the most common avoidable errors in healthcare, ranking as the sixth leading cause of death in the United States and a priority for the World Health Organization since the launch of the “Medication Without Harm” initiative. The objectives of this study are: i) to present a digital therapeutic reconciliation model; ii) to propose an interoperable and legally compliant solution; iii) to integrate Blockchain and Artificial Intelligence technologies into the presented model. Through a descriptive and exploratory literature review, the use of HL7 FHIR and SNOMED-CT standards, a client-CA model for Blockchain, and machine learning and natural language processing models for Artificial Intelligence were proposed. Ensuring the interoperable and secure transmission of clinical data is complex but theoretically feasible. The advantages of therapeutic reconciliation will be measurable through the continuous reduction of morbidity and mortality associated with therapeutic errors.


Download data is not yet available.


Metrics Loading ...

Article Details

How to Cite
Albuquerque, R. ., Seixas Sardinha, L. F., Paulo Albuquerque , S. ., Salazar Silva, M. R., Leite, E. M., & Fragoeiro, I. (2023). PROPOSAL OF A DIGITAL MODEL FOR MEDICATION RECONCILIATION USING BLOCKCHAIN AND ARTIFICIAL INTELLIGENCE. E3 - Revista De Economia, Empresas E Empreendedores Na CPLP, 9(1), 23–43.
Author Biographies

Ricardo Albuquerque, USF Rainha D. Leonor

Luís Filipe Seixas Sardinha, ESTG - Universidade da Madeira

PhD student in Economic and Business Sciences at the University of Azores (ongoing); Degree in Business Management, Higher Institute of Administration and Languages ​​(2018); Postgraduate course in Health Service Management and Social Institutions, Higher Institute of Administration and Languages (2015). Degree in Health Technologies, School of Health Technologies of Lisbon (2008); Member of the ISAL Research Center (2019); Support to the Board of Directors of the Higher Institute of Administration and Languages ​​(2018-2021); Assistant Professor at ISAL (2019-2021); Trainer at ISAL (2019); Accounting Trainer at Conta Mais Certa (2019); Business Manager - Dona Estampa (2008); Senior Technician of Pathological, Cytological and Thanatological Anatomy at the Health Service of the Autonomous Region of Madeira, E.P.E. (SESARAM, E.P.E.) (2010). 

Susana Paulo Albuquerque , UCSP Bombarral


Maria Romana Salazar Silva, USF Rainha D. Leonor


Eduardo Manuel Leite, ESTG - Universidade da Madeira


Isabel Fragoeiro, Universidade da Madeira



Alharbi, F., Atkins, A., & Stanier, C. (2017). Holistic strategic assessment and evaluation of cloud computing adoption: Insights from Saudi Healthcare Organisations. 2017 Internet Technologies and Applications, ITA 2017—Proceedings of the 7th International Conference, 75–80.

Alluhaidan, A. S. (2022). Secure Medical Data Model Using Integrated Transformed Paillier and KLEIN Algorithm Encryption Technique with Elephant Herd Optimization for Healthcare Applications. Journal of Healthcare Engineering, 2022.

Amanat, A., Rizwan, M., Maple, C., Zikria, Y. Bin, Almadhor, A. S., & Kim, S. W. (2022). Blockchain and cloud computing-based secure electronic healthcare records storage and sharing. Frontiers in Public Health, 10.

Amazon. (2023). Solutions for Databases | AWS Solutions Library | AWS.

Bamiah, M., Brohi, S., Chuprat, S., & Ab Manan, J. L. (2012). A study on significance of adopting cloud computing paradigm in healthcare sector. Proceedings of 2012 International Conference on Cloud Computing Technologies, Applications and Management, ICCCTAM 2012, 65–68.

Barnsteiner, J. H. (2008). Medication Reconciliation. Agency for Healthcare Research and Quality, AHRQ, 08, 1–1403.

Bincoletto, G. (2019). A Data Protection by Design Model for Privacy Management in Electronic Health Records. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11498 LNCS, 161–181.

Bologna, S., Bellavista, A., Corsob, P. P., & Zangarab, G. (2016). Electronic Health Record in Italy and Personal Data Protection. European Journal of Health Law, 265–277.

Chatterjee, A., Pahari, N., & Prinz, A. (2022). HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study. Sensors, 22(10).

Chukwu, E., & Garg, L. (2020). A Systematic Review of Blockchain in Healthcare: Frameworks, Prototypes, and Implementations. IEEE Access, 8, 21196–21214.

Comissão Europeia. (2019). Recomendação (UE) 2019/243 da comissão europeia.

Comissão Europeia. (2022a). Annexes to the Regulation of the European Parliament and of the Council on the European Health Data Space.

Comissão Europeia. (2022b). Proposta de Regulamento do Parlamento Europeu e do Conselho relativo ao Espaço Europeu de Dados de Saúde.

Comissão Europeia. (2023). Interoperability layers.

Data Standardization – OHDSI. (2023).


Ekblaw, A., & Azaria, A. (2019). MedRec: Medical Data Management on the Blockchain. Viral Communications, 1–11.

Especificação da LIGHt | SPMS. (2023).

Firely. (2023). Reliable and easy FHIR Server for Health Organizations.

Foundation Markle. (2003). The personal health working group final report 2003. In Connecting for Health.

Gil, A. (2017). Como Elaborar Projetos de pesquisa (6th ed.). Atlas.

Haleem, A., Javaid, M., Singh, R. P., Suman, R., & Rab, S. (2021). Blockchain technology applications in healthcare: An overview. International Journal of Intelligent Networks, 2(May), 130–139.

Hameed, R. T., Mohamad, O. A., Hamid, O. T., & Tapus, N. (2016). Design of e-Healthcare management system based on cloud and service oriented architecture. 2015 E-Health and Bioengineering Conference, EHB 2015, 1–4.

Hassan, J., Shehzad, D., Habib, U., Aftab, M. U., Ahmad, M., Kuleev, R., & Mazzara, M. (2022). The Rise of Cloud Computing: Data Protection, Privacy, and Open Research Challenges—A Systematic Literature Review (SLR). Computational Intelligence and Neuroscience, 2022.

Home | SNOMED International. (2023).

ICD—ICD-10—International Classification of Diseases, Tenth Revision. (2023).

Interoperabilidade Técnica: LIGHt; PNB; NCP – SPMS. (2023).

Jornal Oficial da União Europeia. (2016). Conteúdo UE Regulamento Geral sobre a Proteção de Dados. Privacy/Privazy according to plan.

Karnon, J., Campbell, F., & Czoski-Murray, C. (2009). Model-based cost-effectiveness analysis of interventions aimed at preventing medication error at hospital admission (medicines reconciliation). Journal of Evaluation in Clinical Practice, 15(2), 299–306.

Koski, E., & Murphy, J. (2021). AI in Healthcare. Studies in Health Technology and Informatics, 284, 295–299.

Kuo, M. H., Kushniruk, A., & Borycki, E. (2011). Can cloud computing benefit health services?-A SWOT analysis. Studies in Health Technology and Informatics, 169, 379–383.

Kuo, T.-T., & Ohno-Machado, L. (2018). ModelChain: Decentralized Privacy-Preserving Healthcare Predictive Modeling Framework on Private Blockchain Networks. ArXiv.

LOINC and Health Data Standards—Regenstrief Institute. (2023).

Marconi, M., & Lakatos, E. (2017). Fundamentos de metodologia científica (8th ed.). Atlas.

McCarthy, J. (2007). What Is Artificial Intelligence? In Stanford University.

Mena, R., & Aguiar, P. (2016). Health Care Marketing (1st ed.). Leya, S.A.

Microsoft. (2023). Azure Health Data Services—FHIR, DICOM & MedTech | Microsoft Azure.

Mosaico | Interoperabilidade. (2023).

Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System.

Neştian, A. Ștefan, Tiţă, S., & Guţă, A. L. (2020). Incorporating artificial intelligence in knowledge creation processes in organizations. Proceedings of the International Conference on Business Excellence, 14(1), 597–606.

Ntafi, C., Spyrou, S., Bamidis, P., & Theodorou, M. (2022). The legal aspect of interoperability of cross border electronic health services: A study of the european and national legal framework. Health Informatics Journal, 28(3).

Partin, B. (2006). Preventing Medication Errors: An IOM Report. The Nurse Practitioner, 31(12).

Pedro, J., Santos, S. , Vitor De Souza, J., 2, F., Fernandes, L., 3, S., & Rodrigues De Brito, P. H. (2020). Evolução da Inteligência Artificial. Anais Do Congresso Nacional Universidade, EAD e Software Livre, 2(11), 1–6.

Pereira de Lyra Júnior, D., de Souza Siqueira, J., Tenório da Silva, D., Bastos Almeida, L., Barros da Silva, W., Sousa, P., & Pereira Guerreiro, M. (2010). Erro medicamentoso em cuidados de saúde primários e secundários: dimensão, causas e estratégias de prevenção. Revista Portuguesa de Saúde Pública, Tematico(10), 40–46.

Prodanov, C., & Freitas, E. (2013). Metodologia do Trabalho Cientifico: Métodos e Técnicas de Pesquisa e do Trabalho Acadêmico. In Feevale (Ed.), Universidade FEEVALE (2nd ed.). Feevale.

Decreto-Lei n.o 108/2011, 4694 (2011).

Rizk, D., Hosny, H., El-Horbaty, E. S., & Salem, A. B. (2020). A study on cloud computing architectures for smart healthcare services. CEUR Workshop Proceedings, 2753, 302–310.

Rodrigues, B., & Andrade, A. (2021). O potencial da inteligência artificial para o desenvolvimento e competitividade das empresas: uma scoping review. Gestão e Desenvolvimento, 29, 381–422.

Rodrigues, S. M., Kanduri, A., Nyamathi, A., Dutt, N., Khargonekar, P., & Rahmani, A. M. (2022). Digital Health-Enabled Community-Centered Care: Scalable Model to Empower Future Community Health Workers Using Human-in-the-Loop Artificial Intelligence. JMIR Formative Research, 6(4), 1–15.

Roehrs, A., da Costa, C. A., & da Rosa Righi, R. (2017). OmniPHR: A distributed architecture model to integrate personal health records. Journal of Biomedical Informatics, 71, 70–81.

Ross, S., Bond, C., Rothnie, H., Thomas, S., & MacLeod, M. J. (2009). What is the scale of prescribing errors committed by junior doctors? A systematic review. British Journal of Clinical Pharmacology, 67(6), 629–640.

Sassatelli, E. H. (2022). Cause to Pause: Preventing medication errors with high-risk opioids. Nursing, 52(6), 26–30.

Shaban-Nejad, A., Michalowski, M., & Buckeridge, D. L. (2018). Health intelligence: how artificial intelligence transforms population and personalized health. Npj Digital Medicine, 1(53).

Singh, S., Pankaj, B., Nagarajan, K., P. Singh, N., & Bala, V. (2022). Blockchain with cloud for handling healthcare data: A privacy-friendly platform. Materials Today: Proceedings, 62, 5021–5026.

Sun, J., Ren Id, L., Wang, S., & Yao, X. (2020). A blockchain-based framework for electronic medical records sharing with fine-grained access control.

Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., & Sands, D. Z. (2006). Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption. Journal of the American Medical Informatics Association : JAMIA, 13(2), 121–126.

Tariq, R. A., Vashisht, R., Sinha, A., & Scherbak, Y. (2023). Medication Dispensing Errors And Prevention. StatPearls.

Wagner, M. M., & Hogan, W. R. (1996). The accuracy of medication data in an outpatient electronic medical record. Journal of the American Medical Informatics Association, 3(3), 234.

Wartman, S. A., & Combs, C. D. (2019). Reimagining medical education in the age of AI. AMA Journal of Ethics, 21(2), 146–152.

WHO. (2017). Medication Without Harm.

WHO. (2023a). International Classification of Primary Care, 2nd edition (ICPC-2).

WHO. (2023b). WHOCC—Structure and principles.

Wu, H., Chan, N. K., Zhang, C. J. P., & Ming, W. K. (2019). The role of the sharing economy and artificial intelligence in health care: Opportunities and challenges. Journal of Medical Internet Research, 21(10), 1–4.

Young, R. A., Fulda, K. G., Espinoza, A., Gurses, A. P., Hendrix, Z. N., Kenny, T., & Xiao, Y. (2022). Ambulatory Medication Safety in Primary Care: A Systematic Review. Journal of the American Board of Family Medicine : JABFM, 35(3), 610–628.

Zhang, P., White, J., Schmidt, D. C., Lenz, G., & Rosenbloom, S. T. (2018). FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data. Computational and Structural Biotechnology Journal, 16, 267–278.

Most read articles by the same author(s)