https://ojs.luminescience.cn/JDH <p><strong><em>Journal of Digital Health</em></strong> (JDH) is the official journal of the Renmin Hospital of Wuhan University. Publishing services are provided by Luminescience Press. </p> <p> </p> <p>JDH is an open access and peer-reviewed journal that publishes articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI), big data and informatics in medical and healthcare industries to improve the quality and efficiency of healthcare. The journal publishes research articles, reviews, perspectives, research highlights and case reports that present the application of digital technologies in medical diagnostics and treatment, medical devices, machine learning-based decision support, medical record database and intelligent and process-aware information system in healthcare and medicine.</p> Luminescience Press Ltd en-US Journal of Digital Health 2791-1624 <p>Copyright licenses detail the rights for publication, distribution, and use of research. Open Access articles published by Luminescience do not require transfer of copyright, as the copyright remains with the author. In opting for open access, the author(s) should agree to publish the article under the CC BY license (Creative Commons Attribution 4.0 International License). The CC BY license allows for maximum dissemination and re-use of open access materials and is preferred by many research funding bodies. Under this license, users are free to share (copy, distribute and transmit) and remix (adapt) the contribution, including for commercial purposes, providing they attribute the contribution in the manner specified by the author or licensor.</p> https://ojs.luminescience.cn/JDH/article/view/336 <p>Patient autonomy in healthcare has become increasingly significant in the digital age as individuals seek greater control over their health data. This review examines the ethical, legal and technological aspects of patient data ownership, emphasizing the need for privacy models and consent frameworks to empower patients, safeguard privacy and enhance transparency. Traditional doctor-patient confidentiality faces challenges due to advancements such as electronic health records, artificial intelligence and wearable technologies, necessitating updated frameworks to protect patient rights. Privacy models such as private, public and hybrid models present varying implications for data control, security and societal benefits. Emerging technologies such as blockchain and AI are revolutionizing data privacy by decentralizing data storage and enabling patient control while ensuring secure and ethical data utilization. Advanced consent frameworks, including dynamic and granular consent, provide patients with flexibility and transparency and promote trust and active participation in data-sharing decisions. Real-world implementations, such as Australia’s My Health Record and Estonia’s e-Health system, demonstrate the potential of patient-centric privacy frameworks to enhance healthcare quality and innovation. However, significant challenges persist, including regulatory ambiguities, cybersecurity risks and gaps in digital literacy. Addressing these issues requires collaboration among stakeholders to develop adaptable, secure and interoperable systems that prioritize patient autonomy. By integrating patient education, fostering interoperability and leveraging adaptive technologies, healthcare systems can balance privacy and innovation, build trust and ensure ethical data practices that empower individuals while advancing public health objectives.</p> Minal R. Narkhede Nilesh I. Wankhede Akanksha M. Kamble Copyright © 2025 Minal R. Narkhede, Nilesh I. Wankhede, Akanksha M. Kamble https://creativecommons.org/licenses/by/4.0 2025-03-03 2025-03-03 1 23 10.55976/jdh.4202513361-23