| Title |
Big Data Based m-Health Application to Prevent Health Hazards: A Design Science Framework
|
|---|---|
| Published in |
Telemedicine Journal (now called Telemedicine Journal and e-Health), September 2018
|
| DOI | 10.1089/tmj.2018.0063 |
| Pubmed ID | |
| Authors |
Ibraheem Alharbi, Bader Alyoubi, Rakibul Hoque, Najah Almazmomi |
| Abstract |
Every year about three million Muslims visit the Holy City of Makkah in Saudi Arabia to perform the Hajj. Because of the large number of people present during this period, pilgrims can be subjected to many health hazards. An adequate system to minimize these health hazards is needed to support the pilgrims who attend the Hajj. This study justifies the need for developing a large data-based m-Health application to identify the health hazards encountered during the Hajj. In developing a big data-based m-Health application, this study follows the framework suggested by Hevner. The design of the science framework allows the development of a technological solution (i.e., design artifact) of the problem through a series of actions. The design involves rigorous knowledge of the environmental factors, including knowledge of the construction and evaluation of technological solutions, that are important and relevant to an existing problem. Based on the design science framework, the process of artifact development can be classified into Artifact Design, Artifact Implementation, and Artifact Evaluation. This paper presents the Artifact Design step for the design of the big data-based m-Health application, which has an Environmental Relevance Cycle, a Knowledge-based rigor Cycle, and an Artifice development and design cycle. The big data-based m-Health application is a prototype and must be evaluated using the evaluation-and-feedback loop process until the optimum artifact is completely built and integrated into the system. Development of a big data-based m-Health application using a design science framework can support the effective and comprehensive plan of the government of Saudi Arabia for preventing and managing Hajj-related health issues. Our proposed model for developing and designing a big data-based m-Health application could provide direction for developing the most advanced solution for dealing with the Hajj-related health issues in the future. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 23% |
| Student > Master | 5 | 8% |
| Researcher | 4 | 7% |
| Lecturer | 3 | 5% |
| Student > Bachelor | 3 | 5% |
| Other | 9 | 15% |
| Unknown | 23 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 7 | 11% |
| Computer Science | 6 | 10% |
| Business, Management and Accounting | 5 | 8% |
| Medicine and Dentistry | 4 | 7% |
| Engineering | 4 | 7% |
| Other | 9 | 15% |
| Unknown | 26 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 September 2018.
All research outputs
#22,767,715
of 25,385,509 outputs
Outputs from Telemedicine Journal (now called Telemedicine Journal and e-Health)
#1,837
of 2,048 outputs
Outputs of similar age
#302,884
of 346,007 outputs
Outputs of similar age from Telemedicine Journal (now called Telemedicine Journal and e-Health)
#35
of 47 outputs
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