mHealth Environments for Chronic Disease Management

mHealth Environments for Chronic Disease Management

Eleni I. Georga (University of Ioannina, Greece), Athanasios N. Papadopoulos (University of Ioannina, Greece) and Dimitrios I. Fotiadis (University of Ioannina, Greece & Institute of Molecular Biology and Biotechnology, Greece)
DOI: 10.4018/978-1-4666-8828-5.ch024
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Abstract

The management of chronic diseases requires the continuous monitoring and control of an extensive set of medical and lifestyle parameters affecting the health status of patients. The purpose of this chapter is to present an overview of the state of the art in wearable medical systems and mobile self-management support interventions in the daily care of Chronic Obstructive Pulmonary Disease (COPD) and Type 1 and Type 2 diabetes. In both cases, research and commercial approaches to the integration of specialized sensors in a wearable smart module are presented and their ability to provide real-time estimations for crucial parameters is emphasized. Moreover, special emphasis is placed on mobile self-monitoring applications which are progressively enhanced with decision support, pattern recognition and predictive capabilities which can be used by the patient. The way in which mobile health technology can improve health outcomes is discussed and future research directions are described.
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Background

Mobile devices, such as smartphones and tablets are becoming increasingly popular in the provision of services in various fields. In the last 10 years, they have become a central part in the provision of healthcare services as well thanks to a series of unique features, such as:

  • 1.

    Provision of significant computational capabilities and native applications (Andoid, iOS, Windows Phone) which provide Application Programming Interfaces (APIs)

  • 2.

    Incorporation of internet and other connectivity options (e.g. Bluetooth)

  • 3.

    Availability of inbuilt sensors (accelerometers, cameras, GPS, etc.) and associated data analysis algorithms (e.g. heart rate extraction)

  • 4.

    Availability of a great variety of apps as well as app-enabled peripheral devices (connected health and lifestyle gadgets)

  • 5.

    Tendency of people to carry and use mobile phones and smartphones everytime and everywhere

Key Terms in this Chapter

Chronic Disease Management: An approach or a plan to manage a chronic illness. Such methodology includes check-ups, coordinating treatment and patient and caregivers education. It can improve patient’s quality of life while reducing healthcare costs and preventing or minimizing the effects of patient’s condition.

Data Mining: The process of automatically discovering useful information in large datasets. Data mining techniques such as classification, cluster analysis and association analysis provide capabilities to find useful patterns and predict the outcome of a future observation

mHealth (also written as m-Health): An abbreviation for mobile health, a term used for the practice of medicine and public health supported by mobile devices.

Chronic Disease: A long-lasting condition which can be controlled but not cured and which is the leading cause of death and disability in the western world. Chronic diseases are the asthma and chronic obstructive pulmonary disease (COPD), diabetes, heart diseases, obesity, Alzheimer’s disease and others.

mHealth Standards: A group of standards addressing the applied protocols and guidelines, the communication issues and the interoperability of personal health devices (PHDs). Several international standards organizations are publishing reports and directives for the development of healthcare mobile systems. These include Integrating the Healthcare Enterprise (IHE), Health Level 7 (HL7) and International Organization for Standardization (ISO).

Clinical Decision Support System (CDSS): An interactive intelligent system developed with computer software, which is designed to assist physicians and other health professionals in decision making tasks, such as determining diagnosis of patient data or categorizing patients based on their health condition.

Diabetes Mellitus: A group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of diabetes is associated with long-term damage, dysfunction, and failure of various organs, especially the eyes, kidneys, nerves, heart, and blood vessels.

Vital Sign Monitoring: A collection and analysis of several physiological characteristics and biosignals referred to cardiovascular, respiratory, body temperature and activity data to determine and prevent complications.

Interoperability: The ability of health information systems to interact within and across organizational boundaries in order to advance the effective delivery of healthcare services for individuals and communities, while standards define the entities and their interactions.

Chronic Obstructive Pulmonary Disease (COPD): A group of lung diseases that block airflow and make breathing difficult. Emphysema and chronic bronchitis are the two most common conditions that make up COPD.

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