Modeling Historically mHealth Care Environments

Modeling Historically mHealth Care Environments

Sadaf Batool Naqvi (Consultant Family Medicine, Johns Hopkins Aramco, Abqaiq, Saudi Arabia) and Abad A. Shah (IT Research and Education Consultant, San Jose, USA)
Copyright: © 2018 |Pages: 19
DOI: 10.4018/IJRQEH.2018070104
Article PDF Download
Open access articles are freely available for download


This article describes how mobile health (mHealth) has grown from infancy stage to toddler stage due to advances in the technology. It has the potential for further growth as it is low-cost health care. For its further growth, it is necessary to widen its scope. In this article, a proposal is presented to develop a new and advanced mHealth care system, and its first step that is modelling is reported. In modelling, historically, a model of a temporal object system (TOS) is used. The model empowers users of the proposed mHealth care system to define, retrieve and manipulate all objects historically, in a uniform fashion, and also to keep historically the changes that occur to the objects. Later, these historically stored objects can be consulted during making essential and crucial decisions about the patients (objects) and other objects of the system, and it can save both lives and money. Also, the stored objects can be used in the future planning and research.
Article Preview


Health care is a fundamental necessity of a human being, and it should be available: i) at the right time, ii) at the right place, iii) proper treatment, iv) at an affordable cost. Mobile Health (mHealth) care is an attempt to meet these requirements of health care. The main reasons for its popularity are that it addresses the four (4) essential virtues of a good health care system that are mentioned before. The world population and health care cost are increasing at a tremendous rate. Therefore, in this situation, mHealth care becomes more relevant, and its importance is increased. By anticipating the situation, investments have also been made by the private sector in USA (Whittaker, 2012).

Most of the research in mHealth has been done as case studies (Metelmann & Metelmann, 2017; O'Connor, Heavin, & O'Donoghue, 2015; Vaz, 2017). These case studies investigate a single disease; for example, in (R. Katz, Mesfin, & Barr, 2012; Nasi, Cucciniello, & Guerrazzi, 2015), diabetes and cancer diseases, have been studied. Nursing has been examined in (Kirschner, Kirschner, Seebauer, & Bethke, 2017), surgery in (Witzke & Specht, 2017), quality in (Kastania & Moumtzoglou, 2012) issues, ethics in (Bellina & Nucatola, 2017), nutrition and weight management issues in (Dimitriou et al., 2017; Koumpouros, 2017). Moreover, complete medicine disciplines have not been neglected (Machado, Abelha, Santos, & Portela, 2018; Moumtzoglou, 2016; Pouliakis, Archondakis, Margari, & Karakitsos, 2016; Tamposis, Pouliakis, Fezoulidis, & Karakitsos, 2017).

In some cases, it is entirely possible that a patient is suffering from more than one disease at the same time, and they are inter-related. For example, if a patient has diabetes, then there is a good possibility that he/she also has the heart, eye, and/or kidney problems. In such cases, mHealth care needs new wireless and wearable/implantable (or insert-able) devices to monitor the multiple diseases and transmit the data of the patients who have multiple diseases to the mHealth care system. Some hardware, software and biotech requirements of a future mHealth care system are anticipated and given in the next section. Current challenges to computer scientists and medical professionals are to store and maintain the data transmitted by different heterogeneous sources (including wireless devices), and later to make the stored data useful for the future planning, research and other relevant utilization. To meet these challenges, it is essential to widen the scope of mHealth care so that benefits can reach every patient who lives anywhere, and new data management, analysis tools and techniques are needed. In this paper, an attempt has been made to extend the scope of the existing mHealth care environment, and a new and comprehensive database management system (DBMS) has been suggested for the environment, and it is referred to as the mHealth care system. Modeling of the mHealth care system and other requirements are presented in this paper. It is hoped that an utterly developed mHealth care system can increase the use of health care services to remote areas in a better and cost-effective manner. It is further expected that historical data of a mHealth care system can promote the research activities.

Complete Article List

Search this Journal:
Open Access Articles
Volume 9: 4 Issues (2020): 1 Released, 3 Forthcoming
Volume 8: 4 Issues (2019)
Volume 7: 4 Issues (2018)
Volume 6: 4 Issues (2017)
Volume 5: 4 Issues (2016)
Volume 4: 4 Issues (2015)
Volume 3: 4 Issues (2014)
Volume 2: 4 Issues (2013)
Volume 1: 4 Issues (2012)
View Complete Journal Contents Listing