Thinking eHealth: Empowering for Wellbeing With Health Monitoring Systems

Thinking eHealth: Empowering for Wellbeing With Health Monitoring Systems

Izabella V. Lokshina (SUNY Oneonta, USA) and Michael R. Bartolacci (Pennsylvania State University – Berks, USA)
DOI: 10.4018/978-1-5225-8188-8.ch015
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This chapter explains eHealth; discusses experiences, health management strategies, and healthcare models to address overweight and obesity in young population; and focuses on mathematical background of individual health status monitoring system to empower young people to manage their health. The proposed system uses symptoms observed with mobile sensing devices to define individual physical and psychological status. It has flexible logical inference system providing positive psychological influence on young people since full acceptance of recommendations towards healthy lifestyles is reached and correct interpretation is guaranteed. Models and algorithms are developed based on the composition inference rule in fuzzy logic that makes health status identification process faster and obtained results more precise and efficient comparing to traditional identification algorithms.
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Everybody talks about eHealth these days, but few people have come up with a clear definition of this term. The term was apparently first used by industry leaders and marketing people rather than academics, and they used this term in line with other “e”-words such as eCommerce, eBusiness, eTrade and so on. Therefore, how can the authors define eHealth in the academic environment? It seems quite clear that eHealth encompasses more than a technological development (Lokshina & Lanting, 2018a; Lokshina & Lanting, 2018b; Lokshina & Lanting, 2019).

In this chapter, the authors define the term and the notion as follows. eHealth is an emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the communication technology, i.e. the Internet, and related technologies. In a broader sense, the term symbolizes not only a technical development, but also a state-of-mind; a way of thinking; an attitude; and a commitment for networked, global thinking, to improve healthcare locally, regionally, and worldwide by using information and communication technology. As such, the “e” in eHealth does not only stand for “electronic”, but implies many other “e’s,”, which together, perhaps, best describe what eHealth is all about, or what it should be (Lokshina & Lanting, 2018a; Lokshina & Lanting, 2018b; Lokshina & Lanting, 2019).

Eysenbach (2001), when explaining the term eHealth, gave a set of requirements, i.e. the ten plus “e’s” in eHealth. He stated the “e” in eHealth does not only stand for “electronic”, but implies many other “e’s,” which together perhaps best characterize what eHealth should be about:

  • Efficiency: One of the promises of eHealth is to increase efficiency in healthcare, thereby decreasing costs, e.g. avoiding duplicative or unnecessary diagnostic or therapeutic interventions;

  • Enhancing quality of care: Increasing efficiency involves not only reducing costs, but at the same time improving quality; it may enhance the quality of healthcare, e.g. by allowing comparisons;

  • Evidence-based: eHealth interventions should be evidence-based in a sense that their effectiveness and efficiency should not be assumed but proven by rigorous scientific evaluation;

  • Empowerment of consumers and patients: By making the knowledge bases of medicine and personal electronic records accessible to consumers, eHealth opens for patient-centered medicine;

  • Encouragement of a new relationship: Encouragement of a new relationship between the patient and health professional, towards a true partnership, where decisions are made in a shared manner;

  • Education: Education of physicians through online sources (continuing medical education) and consumers (health education, tailored preventive information for consumers);

  • Enabling data exchange: Enabling data and information exchange and communication in a standardized way between healthcare establishments;

  • Extending the scope of healthcare beyond its conventional boundaries: In both a geographical sense as well as in a conceptual sense, eHealth enables access to services online from global providers;

  • Ethics: eHealth involves new forms of patient-physician interaction, posing new challenges and threats to ethical issues as online professional practice, informed consent, privacy and equity issues;

  • Equity: Making healthcare more equitable is one of the promises of eHealth, but at the same time there is a considerable threat that eHealth may deepen the gap between the “haves” and “have-nots”.

Key Terms in this Chapter

Health Management: An evolutionary medicine regulative process in which assessment of fitness and economic-type cost–benefit analysis determines the body’s regulation of its physiology and health.

Symptom: A physical or mental feature that is regarded as indicating a condition of disease, particularly such a feature that is apparent to the patient.

Algorithm: A process or set of rules to be followed in calculations or other problem-solving operations.

Fuzzy Logic: An approach to computing based on “degrees of truth” rather than the usual “true or false” (1 or 0) Boolean logic. The idea of fuzzy logic was first advanced by Dr. Lotfi Zadeh of the University of California at Berkeley in the 1960s.

EHealth: The cost-effective and secure use of information and communication technologies in support of the health and health-related fields including healthcare, health surveillance and health education.

Health Monitoring System: Monitors vital physiologic parameters to watch over changes in a patient’s condition.

Recommendation: A suggestion or proposal as to the best course of action.

Health: A relative state in which a person can function well physically, mentally, socially, and spiritually in order to express the full range of unique potentialities within the environment in which the person is living.

Model: A description of a system using mathematical concepts and language.

Sensing Device: A device that detects and responds to some type of input from the physical environment. The specific input could be light, heat, motion, moisture, pressure, or any one of a great number of other environmental phenomena.

Inference Rule: A logical form consisting of a function that takes premises, analyzes their syntax, and returns a conclusion (or conclusions).

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