Health information systems (HISs) have immense value for healthcare institutions, as they provide secure storage, efficient retrieval, insightful analysis, seamless exchange, and collaborative sharing of patient health information. HISs are implemented to meet patient needs, as well as to ensure the security and privacy of medical data, including confidentiality, integrity, and availability, which are necessary to achieve high-quality healthcare services. This systematic literature review identifies various technologies and methods currently employed to enhance the security and privacy of medical data within HISs. Various technologies have been utilized to enhance the security and privacy of healthcare information, such as the IoT, blockchain, mobile health applications, cloud computing, and combined technologies. This study also identifies three key security aspects, namely, secure access control, data sharing, and data storage, and discusses the challenges faced in each aspect that must be enhanced to ensure the security and privacy of patient information in HISs.

Mobile health (mHealth) applications have revolutionized healthcare by offering accessible and efficient services through mobile devices. However, privacy concerns regarding the protection of sensitive health information remain a significant barrier to widespread adoption. This study investigates factors influencing privacy-related behaviours among mHealth users and proposes a user-centric model to address these privacy concerns. This research aims to identify strategies that enhance privacy protections in mHealth applications while maintaining usability. It focuses on transparency, user autonomy, and trust as key factors in fostering responsible data-sharing practices and encouraging broader adoption. An online survey targeting mHealth users in Australia was conducted to assess the relationships between privacy policy effectiveness, perceived benefits and risks, autonomy, trust, and privacy-enhancing behaviours. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) to validate the proposed research model and test key hypotheses. The findings highlight that clear and transparent privacy policies increase trust and enhance perceived benefits, such as personalized health insights. However, detailed policies may also increase user's awareness of risks, making them more cautious. Autonomy emerged as a critical factor for building trust; users who feel empowered to control their data are more likely to positively engage with mHealth platforms. Trust significantly drives privacy-enhancing behaviours, such as active management of data-sharing settings. However, risks and privacy concerns alone did not deter users from engaging with these applications. Effective communication, robust security measures, and user-friendly features were identified as factors that mitigate privacy concerns and enhance adoption. The study highlights the need for a balanced, user-centric approach to privacy in mHealth applications. Transparent policies, robust security features, and empowering user controls are essential to fostering trust and encouraging adoption, ensuring secure and efficient healthcare delivery.