Computer Virus Models and Analysis in M-Health IT Systems

Computer viruses have been studied for a long time both by the research and by the application communities. As computer networks and the Internet became more popular from the late 1980s on, viruses quickly evolved to be able to spread through the Internet by various means such as file downloading, email, exploiting security holes in software, etc. Epidemiological models have traditionally been used to understand and predict the outcome of virus outbreaks in human or animal populations. However, the same models were recently applied to the analysis of computer virus epidemics. In this work we present various computer virus spread models combined with applications to e-health systems.

The Contribution of mHealth in the Care of Obese Pediatric Patients

In this chapter the evolution of mHealth solutions for monitoring and treatment of children suffering from obesity is discussed. Nowadays, obesity emerges as a major chronic health condition that affects the general population, both children and adults. mhealth solutions are already used for self-management, remote monitoring and counseling of several chronic conditions, including diabetes mellitus, heart failure, Parkinson's disease, etc. Today, those solutions can result to closed loops, which support health self-management for chronic diseases, in a personalized manner. Concerning childhood obesity, those solutions can combine targeted games and motivational approaches towards both physical activity and diet, which could help in addressing this serious and global health issue, in the direction of minimizing co-morbidities and eventually preventing serious, life threatening events.

Information Security Threats in Patient-Centred Healthcare

Healthcare is taking an evolutionary approach towards the adoption of Patient-Centred (PC) delivery approach, which requires the flow of information between different healthcare providers to support a patient's treatment plan, so the Care Team (CT) can seamlessly and securely access relevant information held in the different discrete Legacy Information Systems (LIS). Each of these LIS deploys an organisational-driven information security policy that meets its local information sharing context needs. Nevertheless, incorporating these LIS in collaborative PC care brings multiple inconsistent policies together, which raises a number of information security threats that can block the CT access to critical information across a patient's treatment journey. Using an empirical study, this chapter identifies information security threats that can cause the issue, and defines a common collaboration-driven information security design. Finally, it identifies requirements in LIS to address the inconsistent policies in modern PC collaborative environments that would help improve the quality of care.

Mobile Health Applications Assisting Patients with Chronic Diseases

This chapter analyzes the role of m-health applications supporting patients with chronic diseases (based on examples from asthma care). The purpose of the chapter is to describe the mobile health application development cycle. The chapter begins with a presentation of asthma as a chronic disease and its prevalence and costs for society, as a determinant of the role and place of m-health applications in chronic disease management. Subsequent sections analyze trends in the development of health care, information systems, and health care payment systems as components of the environment for the implementation of m-health applications. The chapter focuses on prerequisites for the introduction of this type of solutions, presents existing applications, and discusses how to define the key functionalities and benefits for patients, payers, and doctors. The financing cycle, barriers to implementation, and future trends are also addressed.

mHealth

The increasing computing power of mobile electronic devices coupled with advances in sensing and wireless technology have paved the way for mobile health (mHealth) to play a major and innovative role in the health sector. This chapter discusses the use of mHealth in the monitoring and diagnosis of sleep-related diseases with a particular emphasis on sleep apnea since it is considered to be one of the most prevalent disorders. Apnea symptoms and the physiological signals associated with it are described with an overview of the current sensing technology used to capture and record these signals. The chapter continues to discuss the integration of sensors with todays' mobile devices to offer mhealth platforms that allow for the monitoring, diagnosis and management of sleep apnea. We conclude by discussing the current limitations of the mHealth technology and discuss possible future enhancements.

Integrated Platform for the Lifestyle Change and Holistic Approach to Personalized Prevention and Self-Management of Patients with High Blood Pressure

High Blood Pressure (BP) is the main risk factor for stroke and a major risk factor for heart attack and kidney disease. EU countries policies on lifestyle measures and self-management in lowering BP including making dietary changes and exercising are emerging and increasing. We aim to addresses preventive solutions for citizens by improving adherence to life style changes as well as therapy compliance by patients' education and monitoring of compliance. Our vision is aimed at creating a systemic solution for health promotion and disease prevention to support hypertensive citizens and healthcare professionals in co-producing healthy management and preventive care actions leading to behavioral changes. We will try to join the concept of prevention centered on a) promotion of subject empowerment, b) engagement of citizen at risk, c) provision of physicians with user-friendly devices, d) supporting behavioural changes of citizens in the adherence of lifestyle protocols, e) introduction of innovative organizational models to improve healthcare system performance

A Collaborative m-Health Platform for Evidence-Based Self-Management and Detection of Chronic Multimorbidity Development and Progression

The ageing process of EU population has played a key role raising the prevalence of chronic disease, with more than 80% of people in the last age group (65-74) reported to be having three or more long-term Multimorbidity or Multiple Chronic Conditions (MCCs). The main problem is that currently, clinicians have limited guidance, as well as evidence of how to approach care decisions for such patients. As a consequence, the understanding of how to best take care of patients with multimorbidity conditions, may lead to improvements in Quality of Life (QoL), utilization of healthcare, safety, morbidity and mortality. The root of this problem is not narrowly confined to guidelines development and application, but is inherent throughout the translational path from the generation of evidence to the synthesis of the evidence upon which guidelines depend.

mHealth

mHealth systems have been maturing since 1995, yet there remains no common definition. The widest definition encompasses not only mobile devices and digital communication systems, but also the multitudes of apps and add-ons for those mobile devices and systems. Accordingly, mHealth is an indicator of emerging communication-based healthcare and an enabler of participatory health. mHealth implementation and user acceptance vary by geographical region. In the most advanced regions, mobile devices and new communication systems lead to disruptive changes that improve the quality of care and reduce healthcare costs. At the same time, providers and public authorities are challenged with designing and implementing mHealth policies and security measures. Ultimately, mHealth will change healthcare policies and procedures, the structures of healthcare, and the roles of patients and healthcare professionals.

The Nexus of M-Health and Self-Efficacy

Self-care emerged from the concept of health promotion in the 1970s while from 2000 onwards the term ‘self-management' gained popularity, with a greater focus on long-term conditions and the trend towards more holistic models of care. Although ‘self-management' and ‘self-care' are often used interchangeably, a distinction between the two concepts can be made. Both can be considered in terms of a continuum, with self-care at one end as ‘normal activity' and self-management an extension of this. Self-management support is the assistance given to patients in order to encourage daily decisions that improve health-related behaviors and clinical outcomes. Self-efficacy, which is grounded in social cognitive theory, is defined as confidence in one's ability to perform given tasks. The chapter envisions these concepts on a continuum with one pole representing mobile health and the other self-efficacy. It concludes that self-management support is the nexus of mobile health and self-efficacy.

From Telecytology to Mobile Cytopathology

Cytopathology is a popular discipline since George Papanicolaou proposed the famous test pap about 60 years ago. Today modern cytopathology laboratories still use the microscope as the primary diagnostic device and additionally they host modalities performing medical tests and exchange data via networks and have imaging systems producing pictures and virtual slides; the volume of produced data nowadays is enormous. Simultaneously mobile phones and tablets have evolved; their capabilities compete desktop computers and have the advantage of being always connected and at the side of users. Despite there are rather limited applications relevant to cytopathology for the mobile device, there is potential for uses in numerous activities of the cytopathology laboratory, including and not limited to: training, reporting, diagnosis and consultation, laboratory management, whole slide imaging, interactions between patient-doctor, doctor-doctor and within the laboratory personnel, quality control and assurance. Mobile devices can offer important benefits to the modern cytopathology laboratory.