Quality Issues in Personalized E-Health, Mobile Health and E-Health Grids

Quality Issues in Personalized E-Health, Mobile Health and E-Health Grids

Anastasia N. Kastania (Athens University of Economics and Business, Greece) and Sophia Kossida (Biomedical Research Foundation of the Academy of Athens, Greece)
Copyright: © 2011 |Pages: 13
DOI: 10.4018/978-1-61692-843-8.ch021
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Abstract

The electronic healthcare in the modern society has the possibility of converting the practice of delivery of health care. Currently, chaos of information is characterizing the public health care, which leads to inferior decision-making, increasing expenses and even loss of lives. Technological progress in the sensors, integrated circuits, and the wireless communications have allowed designing low cost, microscopic, light, and smart sensors. These smart sensors are able to feel, transport one or more vital signals, and they can be incorporated in wireless personal or body networks for remote health monitoring. Sensor networks promise to drive innovation in health care allowing cheap, continuous, mobile and personalized health management of electronic health records with the Internet. The e-health applications imply an exciting set of requirements for Grid middleware and provide a rigorous testing ground for Grid. In the chapter, the authors present an overview of the current technological achievements in the electronic healthcare world combined with an outline of the quality dimensions in healthcare.
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Personalized E-Health

The current tendency towards ubiquitous computing, the new sensor technologies, the powerful mobile devices and the wearable computers support different types of personalized electronic health applications. Telemonitoring applications have adopted this new technology to improve the quality of care and the quality of treatment for the sick and the elderly using questions and actions based on user preferences. The personalized application collects user activities and begins interpreting them to act according to user’s wishes. The study of user activities also allows individualization of content. Reproduction of user experience, emotions, sentiments, thoughts, behavior and their actions is also performed (Lugmayr et al., 2009).

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