ETSN  Vol.4 No.1 , March 2015
Implicit, Context Management Systems for Mobile Health Services
Abstract: Objectives: In this paper data flow and executive model of Mobile Health services risk management by the use of context aware systems are provided. Materials and Methods: Mobile health (M-Health) refers to using portable electronic devices having application for delivering health services and patient’s information management. M-Health can offer various services remotely in prevention, detection, control, and treatment of disease or in the conditions of disaster for a patient or an environment. These services can have more acceptable quality by the help of Context Aware Systems which are defined as the capacity of computing equipment for detection, feeling, interpreting, and replying to user’s local environmental aspects and computing equipment itself. In this paper, executive model is offered for managing services of M-Health based on context aware systems. One of the supplies of developing a context aware system is having a clear and well-defined definition of context and developing appropriate context information provider. In order to deliver high quality and well-managed M-Health services in the form of context aware systems, having clinical risk management plan is necessary. Conclusions: M-Health services need to develop appropriate communication strategies for interacting with stockholders at each stage of clinical risk management process. Risks, which are primarily resides in service providers, communicating channels or service receiver sides, can be well identified and managed using clinical risk management, M-Health and context aware systems. Thereby, these systems can offer qualified and precise services.
Cite this paper: Farahmandian, V. and Asosheh, A. (2015) Implicit, Context Management Systems for Mobile Health Services. E-Health Telecommunication Systems and Networks, 4, 1-9. doi: 10.4236/etsn.2015.41001.

[1]   Trust, C. (2014) Mobile Healthcare Solution | Prevention and Intervention.

[2]   Kallander, K., Strachan, D.L. and Conteh, L. (2013) Mobile Health (mHealth) Approaches and Lessons for Increased Performance and Retention of Community Health Workers in Low- and Middle-Income Countries: A Review. Journal of Medical Internet Research.

[3]   Sun, Y., Wang, N., Guo, X. and Peng, Z. (2013) Understanding the Acceptance of Mobile Health Services: A Comparison and Integration of Alternative Models. Journal of Electronic Commerce Research, 14, 183-200.

[4]   Wrona, K. and Gomez, L. (2006) Context-Aware Security and Secure Context-Awareness in Ubiquitous Computing Environments. Annales UMCS, Informatica, Vol. 4. No. 1.

[5]   Dey, A.K. and Abowd, G.D. (1999) Towards a Better Understanding of Context and Context-Awareness.

[6]   Preuveneers, D., Bergh, J.V.D., Wagelaar, D., Georges, A., Rigole, P., Clerckx, T., et al. (1999) Towards an Extensible Context Ontology for Ambient Intelligence.

[7]   Department of Health Government of Western Australia (2006) Clinical Risk Management Pocket Guide for the Western Australian Health System Information. Series No. 8.

[8]   Asosheh, A. (2009) IT Project Management, Services-Based and Knowledge-Oriented.

[9]   Care, C.H. (2004) Effective Health Care Risk Management Programs: Components for Success.

[10]   Berg, H.-P. (2010) Risk Management: Procedures, Methods and Experiences. RT&A, 2.

[11]   Papadopoulos, H., Pappa, D. and Gortzis, L. (2007) A Framework for Dealing with Legal and Clinical Risks Arising from the Use of M-Health Systems. Journal on Information Technology in Healthcare, 5, 182-195.

[12]   Eslami, M.Z., Sapkota, B., Zarghami, A., Vriezekolk, E., van Sinderen, M. and Wieringa, R. (2012) Risk Identification of Tailorable Context-Aware Systems: A Case Study and Lessons Learned.