Privacy-preserving Scheme using Secure Group Communication for M-healthcare Information Systems

The expeditious growth of the wearable and implantable body sensors and wireless communication technologies have provided both inspiration and motivation for increasingly development of m-healthcare information systems as a promising next generation e-health system. In m-healthcare systems, the authorized mobile patients with the same disease symptoms can constitute a social group to share their health condition and medical experience. The privacy of social communication transferred over open wireless channels is an essential system requirement. Furthermore, the m-healthcare system on contrary to the traditional e-Health system allows mobile patients to move across distinguished location domains during different time periods. The mobility of patients considerably increases the cost of key management in terms of communication overhead if it is addressed with a naïve solution such as treating as a leave in the old location and a new join in the visited location. This paper proposes a privacy-preserving scheme, which maintains the secrecy of patients’ personal health information using secure group communication in m-healthcare information systems while supporting mobility of patients. The scheme is highly scalable, and treats patients’ mobility with the minimum rekeying cost, as such efficiently preserve secrecy of communication between patients associated with a social group. The security properties of the proposed scheme as well as its performance based on simulation experiments are evaluated. The experimental results demonstrate that the proposed scheme outperforms the existing solution in terms of communication overhead.

The Impact of the Digital Health Interventions in Curbing COVID-19 in Zimbabwe

Amid ongoing research about, Digital Health Interventions (DHI) in Zimbabwe, is the largely overlooked impact of DHI to mitigate the spread of COVID-19. To contribute towards filling this knowledge gap, the study seeks to examine the DHI strategies that have been adopted to curb the inimical effects of COVID-19 in Zimbabwe. DHI such as telemedicine, use of social media, Electronic Medical Records (EMRs), Mobile Health (mHealth), and Healthcare Information Systems (HIS) have been disposed to curtail the spread of COVID-19. The limitations and hurdles crippling DHI are discussed extensively. This study adopts a qualitative research design, comprising personal and targeted interviews and documentary review. Preliminary findings are that DHIs are effectively working for employing routine and innovative forms of Information and Communications Technology (ICT) to address health needs. However, the research noted that various factors such as corruption lack of funding, shortage of qualified workforce and medical expertise, and weak healthcare infrastructure are militating against robust deployment of DHIs. This study includes measures that can be adopted to address these challenges.

A Semantic-Based Approach for Managing Healthcare Big Data: A Survey

Healthcare information systems can reduce the expenses of treatment, foresee episodes of pestilences, help stay away from preventable illnesses, and improve personal life satisfaction. As of late, considerable volumes of heterogeneous and differing medicinal services data are being produced from different sources covering clinic records of patients, lab results, and wearable devices, making it hard for conventional data processing to handle and manage this amount of data. Confronted with the difficulties and challenges facing the process of managing healthcare big data such as volume, velocity, and variety, healthcare information systems need to use new methods and techniques for managing and processing such data to extract useful information and knowledge. In the recent few years, a large number of organizations and companies have shown enthusiasm for using semantic web technologies with healthcare big data to convert data into knowledge and intelligence. In this paper, we review the state of the art on the semantic web for the healthcare industry. Based on our literature review, we will discuss how different techniques, standards, and points of view created by the semantic web community can participate in addressing the challenges related to healthcare big data.