Call for papers - Decentralized approaches to health data

Guest Editors

Alexandre Sztajnberg, PhD, Rio de Janeiro State University, Brazil
Qian Zhu, PhD, National Center for Advancing Translational Sciences; National Institute of Health, USA

Submission Status: Open | Submission Deadline: 21 March 2025

BMC Medical Informatics and Decision Making is calling for submissions to our Collection on Decentralized approaches to health data.

The management and sharing of health data across institutions is an increasingly important challenge in medical informatics. Traditional centralized data systems face challenges related to data storage, data security, and interoperability. Federated health data networks have emerged as a potential solution to extend the access to health data for secondary use: federated, decentralized, or distributed networks and approaches, including blockchain, federated learning, and distributed ledger technology, can effectively handle and exchange health data securely, while ensuring compatibility across different systems.

This collection explores the concept of decentralization and examines the potential benefits and challenges of decentralized approaches to health data, from a technical as well as an ethical and regulatory perspective. It also welcomes studies presenting the design, development, implementation, or use of decentralized networks and their implications for clinical data management, portability, and integration within healthcare systems.

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Meet the Guest Editors

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Alexandre Sztajnberg, PhD, Rio de Janeiro State University, Brazil

Alexandre Sztajnberg received his MSc degree in Electrical Engineering from PUC-RJ in 1995 and his Doctorate degree in Electrical Engineering from COPPE/UFRJ in 2002 in Brazil. He is currently a Full Professor at UERJ, where he is involved in three post-graduate programs: Electronic Engineering (PEL/FEN), Computational Sciences (CComp/IME), and Postgraduate Program in Telemedicine and Telehealth (MPTT/FCM), supervising and co-supervising more than 30 undergraduate and graduate students and publishing over 50 journal and conference papers. He serves as an ad hoc consultant for organizations such as CNPq, FAPERJ, FINEP, and FAPEMG. He is a member of the ACM and IEEE (IEEE Senior Member) societies and is also a member of the Brazilian Computer Society (SBC). His areas of interest are networks and distributed systems, context-aware systems and the Internet of Things (IoT), edge-fog-cloud computing, cluster management systems, and e-health. Currently, he is the principal investigator at the LCC Computer Science Laboratory, where he is supervising ongoing research on IoT middleware with an emphasis on device integration and security aspects.

Qian Zhu, PhD, National Center for Advancing Translational Sciences; National Institute of Health, USA

Qian Zhu serves as the team lead for rare disease translational research in the Informatics Core within NCATS’ Division of Preclinical Innovation and oversees multiple rare disease informatics projects to advance rare disease translational research and support the development of the Genetic and Rare Diseases (GARD) Information Center and the Rare Disease Alert System (RDAS). Zhu’s primary research focuses on biomedical informatics application development for supporting translational research in rare diseases by exploring various types of biomedical and clinical data. This includes rare disease-related data normalization, harmonization, integration, and representation; rare disease-relevant information retrieval and extraction from free text; clinical decision support in rare diseases; and computational drug repositioning for rare diseases.

About the Collection

BMC Medical Informatics and Decision Making is calling for submissions to our Collection on Decentralized approaches to health data.

The management and sharing of health data across institutions is an increasingly important challenge in medical informatics. Traditional centralized data systems face challenges related to data storage, data security, and interoperability. Federated health data networks have emerged as a potential solution to extend the access to health data for secondary use: federated, decentralized, or distributed networks and approaches, including blockchain, federated learning, and distributed ledger technology, can effectively handle and exchange health data securely, while ensuring compatibility across different systems.

This collection explores the concept of decentralization and examines the potential benefits and challenges of decentralized approaches to health data, from a technical as well as an ethical and regulatory perspective. It also welcomes studies presenting the design, development, implementation, or use of decentralized networks and their implications for clinical data management, portability, and integration within healthcare systems.

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select ''Decentralized approaches to health data'' from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.