In Healthcare 4.0, we are witnessing a fundamental shift from provider-centric systems to patient-centric models, where individuals, empowered by technologies such as blockchain, the Internet of Medical Things, and artificial intelligence (AI), assume the role of the Self-Sovereign Patient, exercising control over their health data and care journey. These technologies enable new forms of data ownership, interoperability, and personalized care, building on the structured reliability of legacy systems. However, significant challenges remain. Tensions between blockchain immutability and regulatory rights such as data erasure, the unresolved question of digital inheritance, and ethical concerns surrounding consent, monetization, and health equity must all be addressed. In addition, institutional barriers such as clinical integration, data governance, and uneven access to digital infrastructure pose risks of deepening existing disparities. AI agents, when responsibly deployed, offer promising pathways to augment care delivery and alleviate workforce burdens. Realizing this vision requires coordinated action across clinical, technical, legal, and ethical domains to design trustworthy, privacy-preserving systems that enhance transparency and accountability.

ObjectiveThis research aims to systematically examine the application of blockchain technology in core primary healthcare services, with a particular focus on its ability to enhance data integrity, transparency, and operational efficiency. The objective is to identify and analyze the primary areas where blockchain is being utilized within the health sciences and to evaluate its contributions to secure patient consent, reliable data verification, and the protection of sensitive health information.MethodsThis study conducted a systematic literature review of research and review articles indexed in the Web of Science Core Collection between January 10 and March 15, 2025. Articles were selected based on predefined search strings targeting blockchain applications in health sciences, as detailed in the search strategy (Figure 1). Bibliometric analysis was performed using VOSviewer and the Biblioshiny interface of R Bibliometrix to identify thematic areas, keyword co-occurrences, and research trends. Overlay and network visualizations were used to reveal temporal patterns and relational structures among keywords. To enhance the scope of the review, supplementary searches were also conducted via Google Scholar, providing additional insight into emerging topics not yet indexed in Web of Science.ResultsThe analysis revealed eight major thematic areas where blockchain is prominently applied: secure patient consent and data management, healthcare supply chain processes, clinical research and monitoring, legal and intellectual property concerns, disease tracking and epidemiological management including COVID-19, insurance and billing systems, organ transplantation logistics, and applications in cancer and pharmaceutical research. The data demonstrate an increasing focus on blockchain’s role in enhancing transparency and accountability in both institutional and patient-centered healthcare services.ConclusionsBlockchain holds considerable promise for advancing healthcare systems. However, its effective implementation depends on a comprehensive approach that combines technological innovation with supportive policy frameworks and ethical considerations. These findings provide valuable guidance for stakeholders seeking to integrate blockchain in health service delivery.

The authors assessed how research in primary healthcare was affected by the COVID-19 pandemic and identified the potential of blockchain technology to address pandemic-related challenges. This quantitative bibliometric research study used machine learning techniques. A comprehensive analysis of all primary healthcare (PHC) research was conducted using bibliometric data from the WOs. We examined co-authorship, co-occurrences, citation and co-citation, thematic mapping, factorial, document, and Latent Dirichlet Allocationtopic analyses. Our main dataset was 1,885 articles produced by 9,185 researchers from 3,132 institutions in 113 countries. The most cited studies in the PHC field during the pandemic related to telemedicine and remote consultation, along with clinical conditions such as mental health, diabetes, vaccinations, risks during pregnancy, and healthcare of the elderly. In addition, the impact of COVID-19 on educational outcomes, changes to the organization of care, experiences and challenges to PHC physicians and other health professionals, and the diversity of COVID-19 symptoms were prominent. The PHC researchers adapted quickly to the pandemic and conducted multidisciplinary research that helped to mitigate the impact on individuals, health systems, and society. Within this context, blockchain technology can be used to facilitate the security of health data, resource management (e.g., monitoring of the vaccine supply chain), and global collaboration toward pandemic control. By providing transparency, security, and efficiency in these areas, blockchain technology might lead to more effective pandemic preparedness and management in the future.

Blockchain healthcare insurance offers substantial potential for improving data transparency, efficiency, and security. However, many blockchain healthcare projects struggle to scale up and achieve commercial success. Despite technical feasibility studies, limited research exists on the commercial success of these projects. This study explores the technical, regulatory, and strategic factors that contribute to market success in blockchain healthcare insurance initiatives. Using exploratory mixed methods, we combined quantitative market data analysis from CoinGecko Application Programming Interface (API) with manual metadata curation from publicly available data. We conducted descriptive statistics, Pearson correlation, and multiple regression analysis to evaluate relationships between key variables and market success. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) compliance emerged as a significant predictor of higher market cap (β = +12.6, p = 0.006), while insurance partnerships negatively impacted success due to early-stage complexity (β = -15.3, p = 0.009). The model explains 95.7% of market cap variance (adjusted R² = 0.957). These findings demonstrate how crucial technical preparedness and regulatory alignment are to the successful commercialization of blockchain-based health insurance. The importance of organizational scale is highlighted by a moderate association (r = 0.83) between team size and market success. The importance of strategic alliances and regulatory compliance is further shown by the theme analysis of white papers. Investors should concentrate on projects with well-defined regulatory policies, while entrepreneurs should give HIPAA compliance top priority early on. It is recommended that policymakers create more precise regulatory frameworks for blockchain in the medical field. For more thorough insights, future studies should increase the sample size.

In the context of Code Generation AI (Code Gen AI), "rich" and "quality" data refer to datasets that are not only syntactically and structurally sound but also context-aware, domain-specific, and semantically aligned with the target application. Unlike large-scale, general-purpose code corpora scraped from open repositories, rich datasets are curated to reflect regulatory requirements, architectural patterns, and problem-solving conventions within a given field. This distinction is critically important when deploying Code Gen AI in the healthcare sector, where software must meet rigorous standards for safety, auditability, and compliance. Blindly scaling models with low-quality or irrelevant data may lead to brittle, error-prone systems-posing risks not only to patients and providers but also to the integrity of digital healthcare infrastructure. This issue has not been fully addressed in the Code Gen AI research to date. This article evaluates the critical trade-offs between "rich data" and "data quantity" strategies in Code Gen AI and autonomous code agents, focusing on high-integrity sectors such as healthcare. While Code Gen AI can enhance productivity by up to 55% in controlled environments, models trained on unfiltered, large-scale datasets often increase code duplication, churn, and error rates. The central challenge is balancing performance gains with reliability, maintainability, and ethical accountability. In healthcare, codebases must embody accuracy, traceability, and data privacy-attributes often diluted in large but uncurated training sets. Using Self-Evolving Software as a case study, this article contrasts the outcomes of both approaches and introduces a weighted data selection matrix tailored to Code Gen AI systems. The findings demonstrate that rich, curated, domain-specific datasets consistently produce more robust, compliant, and sustainable code, especially in sectors where quality and governance are non-negotiable.

This ConV2X 2024 fireside chat delves into the critical financial challenges faced by CROs and sites, including delayed payments, unpredictable cash flows, and the impact of inflation on long-term contracts. Speakers present interesting perspectives between a systems vendor and a lifescience leader. Insights from the Society for Clinical Research Sites (SCRS) highlight the precarious financial position many sites find themselves in—26% of sites have a mere six months of financial runway, while 10% are one late payment away from shutting down. Viewers will gain valuable insights into the current financial landscape of clinical trials, understand the pressing need for operational efficiency, and learn about innovative solutions that can help bridge the financial gaps faced by sites and CROs. This session is essential for anyone involved in clinical research who is looking to improve financial sustainability and operational effectiveness. Speakers discuss: The financial challenges impeding site and CRO performance, with a focus on delayed payments, financial forecasting difficulties, and the impact of inflation. Discuss the role of operational inefficiencies in exacerbating financial stress, particularly in the context of budget negotiations and Clinical Trial Agreements (CTAs). Present potential solutions, including how blockchain technology could revolutionize financial management in clinical trials, providing greater transparency, efficiency, and financial stability. To register for ConV2X 2025, please visit https://conv2xsymposium.com Driving Platforms and Decentralized Tech in Healthcare & Life Sciences September 25 & 26, 2025 | In Person EventThe Foundry101 Rogers St. | Cambridge, MA 02142 Special thanks to the ConV2X 2024 host, Boston Blockchain Week!

The authors propose and evaluate a novel cybersecurity architecture for telehealth that is resilient against future quantum computing cyber threats. By integrating post-quantum cryptography (PQC) with quantum key distribution (QKD) and privacy-preserving mechanisms, data confidentiality and immutability for patient records in a post-quantum era are ensured. A multi-layered design approach was adopted. The PQC algorithms (e.g. CRYSTALS-Dilithium) were integrated at the blockchain consensus layer to resist quantum attacks. A directed acyclic graph (DAG)-based ledger managed high transaction throughput and latency constraints typical of telehealth. A QKD-enhanced key management protocol leveraged quantum channels for secure exchanges. Zero-knowledge proofs (ZKPs) and secure multiparty computation (MPC) verified transactions without exposing sensitive patient data. A granular access control model used attribute-based encryption and smart contracts to govern which participants could view or modify encrypted medical records. The prototype was developed within a simulated telehealth network comprising hospitals, clinics, and patient devices. The PQC signatures at the consensus layer provided effective resistance to both classical and anticipated quantum attacks. The QKD facilitated secure key distribution, while ZKPs and MPC enabled validation of healthcare transactions without compromising patient privacy. Despite increased computational overhead, the DAG approach efficiently handled parallel transactions, indicating improved scalability compared to traditional linear blockchains. A QKD-enhanced, PQC-driven framework successfully addresses critical security and privacy requirements, safeguarding medical data from emerging quantum threats. Although overhead and infrastructural costs are significant, sustained cryptographic resilience and robust patient confidentiality underscore its suitability for next-generation healthcare systems. Future studies should explore additional optimizations, homomorphic encryption, and larger-scale pilots under regulatory standards.

Key discussion points Decentralized identity in healthcare State of the market Key technologies Deployments and real world use cases Hear from those on the front lines implementing this technology successfully for healthcare clients. Learn where the state of business adoption and success stands. Listeners will gain an overall market education in the first of this series featuring Linux Foundation Decentralized Trust and companies demonstrating successful use cases. Questions What’s the role of decentralized identity in healthcare, and how do you define it? What are some of the key use cases you can highlight for the audience? What are the key technologies used? What does the tech stack look like? What’s the role of verifiable credentials? Blockchain? Agents? How do open source, standards, and community development projects drive progress in healthcare and interoperability? What are the business implications and drivers for decentralized ID in healthcare today? Where is it getting traction? Are there success stories to share? What should we expect next in the USA? Audience: providers, regulators, health system leaders, public health leaders, and CTOs

As healthcare institutions face Medicare funding challenges, blockchain technology offers solutions for financial stability and improved patient care. This paper examines how decentralized systems create new revenue streams while addressing transparency and efficiency, highlighting the convergence of traditional healthcare with network states and emerging technologies.

The authors explored the primary organizational and environmental factors that influence the adoption of blockchain-integrated artificial intelligence systems aimed at enhancing financial transparency within health insurance institutions. Building on established models of technology acceptance and organizational change, a conceptual framework was developed to examine the interaction of technological readiness, management support, regulatory compliance, and workforce capability. Data collected from 272 professionals working in various health insurance entities were analyzed using structural equation modeling to assess direct and indirect pathways. The findings underscore that internal drivers-particularly employee training, executive leadership commitment, and digital infrastructure-are far more significant in shaping adoption outcomes than external forces like regulatory mandates or market competition. Moreover, financial transparency emerges as a critical outcome and a mediating factor that reinforces trust in technology adoption. This article presents practical insights for policymakers and healthcare administrators to promote ethical, efficient, and transparent digital transformation in the insurance sector.