Adoption of Grid Computing Application in Referral Hospitals in Kenya: The Case of Moi Teaching and Referral Hospital
AbstractInformation Communication Technology (ICT) is a major sector in the realization of Kenyan’s vision 2030. Most organizations have embraced the use of ICTs and are looking forward to adopting the upcoming technologies not only to be at per with the changing world, but also to enhance the achievement of their goals. This paper discusses the benefits of grid computing as one of the emerging technologies which allows sharing of ICT resources in a networked environment. The specific objectives for this research were to identify the ICT tools and equipment used in hospitals, establish the challenges faced by referral hospitals in optimizing the use of ICTs and to establish the suitability of implementing grid computing in hospitals. Since most referral hospitals in Kenya are public institution and are non-profit making organizations, they depend on government grants to carry out their operations. Thus adoption of grid computing will help them optimize the use of their available ICT resources. This research adopted a case study research design where data was collected from key employees at Moi Teaching and Referral Hospital - six heads of departments and twelve ICT specialists. Purposive sampling technique was used to determine the respondents who were interviewed. The data was qualitatively analyzed to identify the challenges faced by the hospital and to examine the need of implementing grid computing in referral hospitals. A proposal of implementing grid computing in referral hospitals in Kenya to optimize the utilization of ICT resources is made.
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Buetow, K., Keunchkerian, S., & Frison, G. H. M., (2009). The future of healthcare: eHealth and grid computing. https://ec.europa.eu/digital-single-market/en/ news/ -healthcare-ehealth-and-grid-computing
Cerello, P., INFN, Torino, S. (2006). Grid computing in medical applications. https://indico.cern.ch/event/408139/contributions/979806 / attachments/815730/1117739/chep2006-mga.pdf
Erberich, S. G., Silverstein, J. C., Chervenak, A., Schuler, R., Nelson, M. D., & Kesselman, C., (2007). Globus medicus – federation of dicom medical imaging devices into healthcare grids. In Healthgrid 2007, pages 269–278, Geneva, Switzerland
Kuo, M. A. (2011). Opportunities and challenges of cloud computing to improve health care services. Journal of Medical Internet Research. doi: 10.2196/ jmir.1867
Lekan, O., (2013). Adoption and utilization of ICT in Nigeria hospitals. http:www.
Morin, C., (2007). Xtreemos: A grid operating system making your computer ready for participating in virtual organizations. In Object and Component-Oriented Real-Time Distributed Computing. DOI: 10.1109/ISORC.2007.62
Nasuti, W., SAS Institute Inc., Cary, N. C., (2011). Effective implementing SAS Grid architectures in conjunction with non-grid aware process. Unpublished.
Oso.W. Y., & Onen. D., (2005). A general guide to writing research proposal and report. Kisumu, Kenya: Option Printers and Publishers.
SAS Institute Inc, World Headquarters, Cary, N. C., (2010), Best practices for data sharing in a grid distributed SAS Environment. https://support.sas.com/rnd / scalability/grid/ Shared_FileSystem_GRID.pdf
Senthamarai, C., & Krishnan, A., (2008). Grid computing based model for remote monitoring of energy flow and prediction of HT line loss in power distribution system: Journal of Theoretical Applied Information Technology. E-ISSN
1817-3195 / ISSN 1992-8645.
Strickland, J., (2008). How grid computing works. http://www.howstuffworks.com/
Vannier, M. W., Staab, E. V., & Clarke, L. C., (2002). Medical image archives –
present and future. In H. U. Lemke, M. W. Vannier, K. Inamura, A. G. Farman,
& J. H. C. Reiber, editors, Proceedings of the International Conference on Computer–Assited Radiology and Surgery (CARS 2002), pages 565–576, Paris, France,
Weiss, T. R., (2001). Grid computing to aid breast cancer treatment, research. https://www.computerworld.com/article/2584743/business-intelligence/grid- computing-to-aid-breast-cancer-treatment--research.html
White B. S., A. S. Grimshaw, A. S., & Nguyen-Tuong, A., (2000). Grid-based file access: The legion I/O model. In Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing (HPDC’00), pages
165–173, Pennsylvania: Pittsburgh.
ZHOU, X., Pitk¨anen, M., Depeursinge, A., & Muller, H., (2008). A medical image retrieval application using grid technologies to speed up feature extraction. publications.hevs.ch/index.php/attachments/single/116