Magudulela T. S.1, Kalema B. M.2, Segooa M. A.1
|1 Tshwane University of Technology, South Africa
2 University of Mpumalanga, South Africa
Background and Aim of Study: Real-time access of information in the healthcare environment is essential, as it not only helps medical personnel to have adequate and timely information, but it also assists patients to be served more easily. Hospitals in rural areas are operating at a low bandwidth and have poor IT infrastructure that causes intermittent networks leading to disruptions and slow service delivery. This necessitates the Hospital Management System (HMS) to be deployed in the cloud environment to reduce the challenges leading to poor service delivery.
The aim of the study: to develop a model for cloud-based HMS for the South African public health sector.
Material and Methods: This study identified three public district municipality hospitals in Gauteng Province, South Africa, that were already using HMS and used them for data collection. Each hospital had up to 50 healthcare workers, and this formed the population of 150 from the three hospitals, from which a sample size of 108 respondents was selected. Data were collected using a closed-ended questionnaire and analyzed quantitatively using SPSS v25.
Results: The results demonstrated that the suggested model has a good prediction power of 60.9% (R2=0.609) and that with the exception of environmental aspects, the rest of the constructs has a significant contribution to the successful implementation of the cloud-based HMS. Social aspects had the highest prediction power of 60.0% (β=0.600) at p=0.001; followed by risk analysis and control with 41.3% (β=0.413) at p=0.009. On the other hand, environmental aspects had the least and non-significant prediction of 12.3%.
Conclusions: This study contributes to the ongoing call to have seamless healthcare provision systems. The model developed in this study extends the research of modernizing healthcare provision by leveraging technological innovations.
cloud computing, hospital management systems, healthcare, public, South Africa.
Abbas, I., Ahmad, M., Faizan, M., Arshed, W., & Khalid, J. (2020, June 12-13). Issues and challenges of cloud computing in performance augmentation for pervasive computing [Paper presentation]. 2020 International Conference on Electrical, Communication and Computer Engineering (ICECCE). Istanbul, Turkey. https://doi.org/10.1109/ICECCE49384.2020.9179462
Adler-Milstein, J., DesRoches, C. M., Kralovec, P., Foster, G., Worzala, C., Charles, D., Searcy, T., & Jha, A. K. (2015). Electronic health record adoption in US hospitals: Progress continues, but challenges persist, health affairs, 34(12), 2174-2180. https://doi.org/10.1377/hlthaff.2015.0992
Alipour, J., Mehdipour. Y., Karimi, A., & Sharifian, R. (2021). Affecting factors of cloud computing adoption in public hospitals affiliated with Zahedan University of Medical Sciences: A cross-sectional study in the Southeast of Iran. Digital Health, 7. https://doi.org/10.1177/20552076211033428
Babbie, E. R. (2016). The practice of social research (14th ed.). Cengage Learning. https://www.worldcat.org/title/The-practice-of-social-research/oclc/899217794
Cohen, L., Manion, L., Morrison, K., & Morrison, R. B. (2018). Research methods in education (8th ed.). Routledge. https://doi.org/10.4324/9781315456539
De Pietro, R., Wiarda, E., & Fleischer, M. (1990). The context for change: Organization, technology, and environment. In L. G. Tornatzky & M. Fleischer (Eds.), The processes of technological innovation (pp. 151-175). Lexington Books.
Djock, E. (2023). Trends & technologies shaping the future of the ICT industry. ITONICS. https://www.itonics-innovation.com/blog/trends-and-technologies-ict-industry
Heale, R., & Twycross, A. (2015). Validity and reliability in quantitative studies. Evidence-Based Nursing, 18(3), 66-67. https://doi.org/10.1136/eb-2015-102129
Idoga, P. E., Toycan, M., Nadiri, H., & Celebi, E., (2019). Assessing factors militating against the acceptance and successful implementation of a cloud based health center from the healthcare professionals’ perspective: A survey of hospitals in Benue state, northcentral Nigeria. BMC Medical Informatics and Decision Making, 19, Article 34. https://doi.org/10.1186/s12911-019-0751-x
Kalema, B. M. (2013, August 29-31). The role of moderating factors in ERP systems usage. 2013 Third International Conference on Innovative Computing Technology (INTECH 2013) (pp. 166-172). IEEE. https://doi.org/10.1109/INTECH.2013.6653699
Kalema, B. M. & Busobozi, V. V. (2020). Big data analytics for data quality improvement to enhance evidence-based health care in developing countries. In M. Pant, T. Sharma, S. Basterrech, & C. Banerjee (Eds.), Performance of Integrated Systems and Its Software Engineering Applications. Asset Analytics (pp. 29-42). Springer. https://doi.org/10.1007/978-981-13-8253-6_4
Kalema, B. M. (2022). Developing countries’ continuance usage of e-services after COVID-19 in the 4IR era. In H. Twinomurinzi, N. Msweli, & T. Mawela (Eds.), Proceedings of NEMISA Summit and Colloquium 2022: Vol. 4. The Future of Work and Digital Skills (pp. 1-11). EasyChair. https://doi.org/10.29007/2cdm
Katuu, S. (2018). Healthcare systems: Typologies, framework models, and South Africa’s health sector. International Journal of Health Governance, 23(2), 134-148, https://doi.org/10.1108/IJHG-10-2017-0054
Khan, F. A., Alia, A., Abbas, H., & Haldar, N. H. (2014). A cloud-based health care framework for security and patients’ data privacy using wireless body area networks. Procedia Computer Science, 34, 511–517. https://doi.org/10.1016/j.procs.2014.07.058
Maphumulo, W. T., & Bhengu, B. R. (2019). Challenges of quality improvement in the health care of South Africa post-apartheid: A critical review. Curationis, 42(1), Article 1901. https://doi.org/10.4102/curationis.v42i1.1901
Massyn, N., Barron, P., Day, C., Ndlovu, N., & Padarath, A. (Eds.). (2020). District health barometer 2018/19. Health Systems Trust. https://www.hst.org.za/publications/Pages/DISTRICT-HEALTH-BAROMETER-201819.aspx
Rahim, N. N. A., Humaidi, N., Aziz, S. R. A., & Zain, N. H. M. (2022). Moderating effect of technology readiness towards open and distance learning (ODL) technology acceptance during COVID-19 pandemic. Asian Journal of University Education, 18(2), 406-421. https://doi.org/10.24191/ajue.v18i2.17995
Rahman, A.A.L., Islam, S., Kalloniatis, C. & Gritzalis, S. (2017). A risk management approach for a sustainable cloud migration. Journal of Risk and Financial Management, 10(4), Article 20. https://doi.org/10.3390/jrfm10040020
Sadoughi, F., Ali, O., & Erfannia, L. (2020). Evaluating the factors that influence cloud technology adoption-comparative case analysis of health and non-health sectors: A systematic review. Health Informatics Journal, 26(2), 1363–1391. https://doi.org/10.1177/1460458219879340
Singh, D., Sinha, S. & Thada, V. (2022). A novel attribute based access control model with application in IaaS cloud. Journal of Integrated Science and Technology, 10(2), 79-86. https://www.pubs.iscience.in/journal/index.php/jist/article/view/1424
Tripathi, S. (2018). Moderating effects of age and experience on the factors influencing the actual usage of cloud computing. Journal of International Technology and Information Management, 27(2), 121-158. https://doi.org/10.58729/1941-6679.1373
Venkatesh, V., Thong, J. Y. & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
Walker, P. H. & Walker, J. M. (2022). Citizen generated data: Opening new doors in health IT research and practice. In U. H. Hübner, G. Mustata Wilson, T. S. Morawski, & M. J. Ball (Eds.), Nursing Informatics. Health Informatics (pp. 219-239). Springer, Cham. https://doi.org/10.1007/978-3-030-91237-6_17
Williams, M. D., Rana, N. P., Roderick, S., & Clement, M. (2016, August 11-14). Gender, age, and frequency of internet use as moderators of citizens’ adoption of electronic government [Paper presentation]. 22nd Americas Conference on Information Systems, AMCIS 2016, San Diego, CA, USA. https://core.ac.uk/download/pdf/301368795.pdf
Yin, R. K. (2014). Case study research: Design and methods (5th ed.). SAGE. https://www.worldcat.org/title/Case-study-research-:-design-and-methods/oclc/835951262
Magudulela Thembokuhle Sheshile – https://orcid.org/0000-0001-5192-7621; Master of Computing, Junior Lecturer, Department of End-User Computing, Tshwane University of Technology, Pretoria, South Africa.
Kalema Mathius Billy (Corresponding Author) – https://orcid.org/0000-0002-2405-9088;
Segooa Mmatshuene Anna – https://orcid.org/0000-0002-4190-8256; Doctor of Computing, Lecturer, Department of Informatics, Tshwane University of Technology, Pretoria, South Africa.
Magudulela, T. S., Kalema, B. M., & Segooa, M. A. (2023). Conceptualizing a model for cloud-based hospital management systems for the South African public health sector. International Journal of Science Annals, 6(2), 1–7. https://doi.org/10.26697/ijsa.2023.2.5
Magudulela, T. S., Kalema, B. M., & Segooa, M. A. 2023. "Conceptualizing a model for cloud-based hospital management systems for the South African public health sector". International Journal of Science Annals, [online] 6(2), pp. 1–7. viewed 30 June 2023, https://culturehealth.org/ijsa_archive/ijsa.2023.2.5.pdf
Magudulela T. S., Kalema B. M., & Segooa M. A. Conceptualizing a model for cloud-based hospital management systems for the South African public health sector. International Journal of Science Annals [Internet]. 2023 [cited 30 June 2023]; 6(2): 1–7. Available from: https://culturehealth.org/ijsa_archive/ijsa.2023.2.5.pdf https://doi.org/10.26697/ijsa.2023.2.5