Enhancing Data Provenance in mHealth: An Architecture Integrating FHIR with Blockchain
Resumo
The advancement of digitalization in healthcare, driven by mobile health (mHealth) applications, has expanded the collection and sharing of clinical data, making information traceability a significant challenge. Data provenance mechanisms are essential to record the origin, modifications, and access to information, thereby promoting transparency, trustworthiness, and security. Although models such as W3C PROV and FHIR Provenance exist, their adoption in mHealth remains limited, primarily due to the lack of compatible architectures and the scarcity of specific technical knowledge. This paper proposes a client-server architecture compatible with W3C PROV and FHIR Provenance, integrating a Provenance Gateway responsible for transforming clinical data into FHIR resources enriched with provenance information. Hyperledger Fabric also stores traceability metadata, ensuring immutability, integrity, and auditability without exposing sensitive data. Preliminary results indicate that the proposed approach enables integrating existing mHealth applications with data provenance mechanisms, promoting interoperability and control over information traceability.
Palavras-chave:
Data Provenance, W3C PROV, mHealth, Blockchain
Referências
Mansoor Ahmed, Amil Rohani Dar, Markus Helfert, Abid Khan, and Jungsuk Kim. 2023. Data Provenance in Healthcare: Approaches, Challenges, and Future Directions. Sensors 23, 14 (2023). DOI: 10.3390/s23146495
Bakheet Aljedaani et al. 2021. Challenges with developing secure mobile health applications: systematic review. JMIR mHealth and uHealth 9, 6 (2021), e15654.
Muhammad Ayaz et al. 2021. The Fast Health Interoperability Resources (FHIR) standard: systematic literature review of implementations, applications, challenges and opportunities. JMIR medical informatics 9, 7 (2021), e21929.
Ana González Bermúdez et al. 2024. A fusion architecture to deliver multipurpose mobile health services. Computers in Biology and Medicine 173 (2024), 108344.
Blind Peer Review. 2024. Blind peer review. (2024).
Ozgu Can and Dilek Yilmazer. 2020. Improving privacy in health care with an ontology-based provenance management system. Expert Systems 37, 1 (2020), e12427.
Faizel Faker. 2018. Mobile Health Data: Investigating the data used by an mHealth app using different mobile app architectures. Ph.D. Dissertation. Department of Computer Science. [link]
Yolanda Gil et al. 2010. Provenance XG final report. (2010).
Robert SH Istepanian. 2022. Mobile health (m-Health) in retrospect: the known unknowns. International journal of environmental research and public health 19, 7 (2022), 3747.
Uzair Javaid, Muhammad Naveed Aman, and Biplab Sikdar. 2018. Blockpro: Blockchain based data provenance and integrity for secure iot environments. In Proceedings of the 1st workshop on blockchain-enabled networked sensor systems. 13–18.
Marco Johns, Lena Baum, and Fabian Prasser. 2025. Tracking provenance in clinical data warehouses for quality management. International Journal of Medical Informatics (2025). DOI: 10.1016/j.ijmedinf.2024.105690
Tsung-Ting Kuo, Hyeon-Eui Kim, and Lucila Ohno-Machado. 2017. Blockchain distributed ledger technologies for biomedical and health care applications. Journal of the American Medical Informatics Association 24, 6 (2017), 1211–1220.
Xueping Liang, Sachin Shetty, Deepak Tosh, Charles Kamhoua, Kevin Kwiat, and Laurent Njilla. 2017. Provchain: A blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability. In 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). IEEE, 468–477.
Richard K. Lomotey and Ralph Deters. 2014. Mobile-Based Medical Data Accessibility in mHealth. In 2014 2nd MobileCloud. 91–100. DOI: 10.1109/MobileCloud.2014.24
Dounia Marbouh et al. 2022. A blockchain-based regulatory framework for mHealth. Data 7, 12 (2022), 177.
Mario Nacinovich. 2011. Defining mHealth. , 3 pages.
Simon P Rowland et al. 2020. What is the clinical value of mHealth for patients? NPJ digital medicine 3, 1 (2020), 4.
Marcio Jose Sembay. 2023. PROV-Health: método para gerenciamento de dados de proveniência em sistemas de informação em saúde. Ph.D. Dissertation. UFSC. [link]
Sachin Shetty, Val Red, Charles Kamhoua, Kevin Kwiat, and Laurent Njilla. 2017. Data provenance assurance in the cloud using blockchain. In Disruptive Technologies in Sensors and Sensor Systems, Vol. 10206. SPIE, 125–135.
Marten Sigwart et al. 2020. A secure and extensible blockchain-based data provenance framework for the Internet of Things. Personal and Ubiquitous Computing (2020), 1–15.
Maria Judith Velez De Villa Rojas. 2024. Provenance information in eHealth. Ph.D. Dissertation. UPC, Facultat d’Informàtica de Barcelona, Departament d’Arquitectura de Computadors. [link]
Bakheet Aljedaani et al. 2021. Challenges with developing secure mobile health applications: systematic review. JMIR mHealth and uHealth 9, 6 (2021), e15654.
Muhammad Ayaz et al. 2021. The Fast Health Interoperability Resources (FHIR) standard: systematic literature review of implementations, applications, challenges and opportunities. JMIR medical informatics 9, 7 (2021), e21929.
Ana González Bermúdez et al. 2024. A fusion architecture to deliver multipurpose mobile health services. Computers in Biology and Medicine 173 (2024), 108344.
Blind Peer Review. 2024. Blind peer review. (2024).
Ozgu Can and Dilek Yilmazer. 2020. Improving privacy in health care with an ontology-based provenance management system. Expert Systems 37, 1 (2020), e12427.
Faizel Faker. 2018. Mobile Health Data: Investigating the data used by an mHealth app using different mobile app architectures. Ph.D. Dissertation. Department of Computer Science. [link]
Yolanda Gil et al. 2010. Provenance XG final report. (2010).
Robert SH Istepanian. 2022. Mobile health (m-Health) in retrospect: the known unknowns. International journal of environmental research and public health 19, 7 (2022), 3747.
Uzair Javaid, Muhammad Naveed Aman, and Biplab Sikdar. 2018. Blockpro: Blockchain based data provenance and integrity for secure iot environments. In Proceedings of the 1st workshop on blockchain-enabled networked sensor systems. 13–18.
Marco Johns, Lena Baum, and Fabian Prasser. 2025. Tracking provenance in clinical data warehouses for quality management. International Journal of Medical Informatics (2025). DOI: 10.1016/j.ijmedinf.2024.105690
Tsung-Ting Kuo, Hyeon-Eui Kim, and Lucila Ohno-Machado. 2017. Blockchain distributed ledger technologies for biomedical and health care applications. Journal of the American Medical Informatics Association 24, 6 (2017), 1211–1220.
Xueping Liang, Sachin Shetty, Deepak Tosh, Charles Kamhoua, Kevin Kwiat, and Laurent Njilla. 2017. Provchain: A blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability. In 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). IEEE, 468–477.
Richard K. Lomotey and Ralph Deters. 2014. Mobile-Based Medical Data Accessibility in mHealth. In 2014 2nd MobileCloud. 91–100. DOI: 10.1109/MobileCloud.2014.24
Dounia Marbouh et al. 2022. A blockchain-based regulatory framework for mHealth. Data 7, 12 (2022), 177.
Mario Nacinovich. 2011. Defining mHealth. , 3 pages.
Simon P Rowland et al. 2020. What is the clinical value of mHealth for patients? NPJ digital medicine 3, 1 (2020), 4.
Marcio Jose Sembay. 2023. PROV-Health: método para gerenciamento de dados de proveniência em sistemas de informação em saúde. Ph.D. Dissertation. UFSC. [link]
Sachin Shetty, Val Red, Charles Kamhoua, Kevin Kwiat, and Laurent Njilla. 2017. Data provenance assurance in the cloud using blockchain. In Disruptive Technologies in Sensors and Sensor Systems, Vol. 10206. SPIE, 125–135.
Marten Sigwart et al. 2020. A secure and extensible blockchain-based data provenance framework for the Internet of Things. Personal and Ubiquitous Computing (2020), 1–15.
Maria Judith Velez De Villa Rojas. 2024. Provenance information in eHealth. Ph.D. Dissertation. UPC, Facultat d’Informàtica de Barcelona, Departament d’Arquitectura de Computadors. [link]
Publicado
27/10/2025
Como Citar
VELASCO, Gislainy Crisostomo; VAZ, Noeli Antônia Pimentel; VIEIRA, Marcos Alves; CARVALHO, Sergio T..
Enhancing Data Provenance in mHealth: An Architecture Integrating FHIR with Blockchain. In: LABLOCK ARTIGOS CURTOS - LATIN-AMERICAN SYMPOSIUM ON DEPENDABLE COMPUTING (LADC), 14. , 2025, Valparaíso/Chile.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 49-53.
DOI: https://doi.org/10.5753/ladc_estendido.2025.16887.
