Abstract
The public health sector in South Africa generates massive data and it caters to about 71% of the population. The introduction of electronic medical records has made this data difficult to process. The adoption of business intelligence and big data became a solution for processing and analysing this increased data. The research aimed to provide an understanding of the existing contributions of business intelligence and big data in public healthcare in South Africa. Our research question is what are the benefits and challenges of adopting the use of business intelligence and big data in healthcare in South Africa? A systematic search was conducted in seven electronic databases (EbscoHost, Science Direct, ProQuest, Scopus, Sabinet, SpringerLink, and Google Scholar). The inclusion criteria were journal papers, books, book chapters, reviews, and conference proceedings reporting on big data, big data analytics, and business intelligence in South African healthcare. 22 articles were analysed for the study. The findings revealed that business intelligence and big data help by shortening diagnostic tests (through early diagnosis), reducing risks in healthcare services, reducing hospital costs, and improving patients’ health. However, there are issues like privacy, security, and poor data quality that need attention. The study contributes to the body of knowledge on healthcare informatics. Our study provides evidence for practitioners, policymakers, scholars, and technology advocates to advance the adoption and use of big data and business intelligence in the public healthcare system in developing countries. Our research contributes to sustainable development goal 3 (target 3.d).
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References
Pollitzer, E.: Creating a better future: four scenarios for how digital technologies could change the world. J. Int. Aff. 72, 75–90 (2018)
Eberhard, B., et al.: Smart work: the transformation of the labour market due to the fourth industrial revolution (I4.0). Int. J. Bus. Econ. Sci. Appl. Res. 10, 47–66 (2017)
Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)
Basile, L.J., Carbonara, N., Pellegrino, R., Panniello, U.: Business intelligence in the healthcare industry: the utilization of a data-driven approach to support clinical decision making. Technovation 120, 102482 (2023)
Ngwenyama, O., Andoh-Baidoo, F.K., Bollou, F., Olga, M.: Is there a relationship between ICT, health, education and development? An empirical analysis of five West African countries from 1997–2003. Electron. J. Inf. Syst. Dev. Ctries. 23, 1–11 (2006)
Gaardboe, R., Sandalgaard, N., Nyvang, T.: An assessment of business intelligence in public hospitals. Int. J. Inf. Syst. Proj. Manag. 5, 5–18 (2017)
Sun, Z., Zou, H., Strang, K.: Big data analytics as a service for business intelligence. In: 14th IFIP WG 6.11 Conference on e-Business, e-Services and e-Society. pp. 319–25013. Springer International Publishing, Delft, Netherlands (2015).
Mtebe, J.S., Raphael, C.: A critical review of eLearning research trends in Tanzania. J. Learn. Dev. 5, 163–178 (2018)
Lim, E.P., Chen, H., Chen, G.: Business intelligence and analytics: research directions. ACM Trans. Manag. Inf. Syst. 3, 1–10 (2013)
Ram, J., Zhang, C., Koronios, A.: The implications of big data analytics on business intelligence: a qualitative study in China. Procedia Comput. Sci. 87, 221–226 (2016)
Muntean, M.: Considerations regarding business intelligence in cloud context. Inform. Econ. 19, 55–67 (2015)
Botoş, H.M.: Business intelligence and competitive intelligence: the evolution of the terms. Res. Sci. Today. 16, 56–62 (2018)
Vassakis, K., Petrakis, E., Kopanakis, I.: Big data analytics: applications, prospects and challenges. Lect. Notes Data Eng. Commun. Technol. 10, 3–20 (2018)
Wang, Y., Kung, L.A., Byrd, T.A.: Big data analytics: understanding its capabilities and potential benefits for healthcare organizations. Technol. Forecast. Soc. Change. 126, 3–13 (2018)
Yin, J., Fernandez, V.: A systematic review on business analytics. J. Ind. Eng. Manag. 13, 283–295 (2020)
Batko, K., Ślęzak, A.: The use of big data analytics in healthcare. J. Big Data. 9, 3 (2022)
Bayrak, T.: A review of business analytics: a business enabler or another passing fad. Social Behav. Sci. 195, 230–239 (2015)
Halaj, M.: The business intelligence theory jungle. Mlad. Veda. 8, 65–78 (2020)
Michael, M., Lupton, D.: Toward a manifesto for the ‘public understanding of big data.’ Public Underst. Sci. 25, 104–116 (2016)
Khanra, S., Dhir, A., Islam, N., Mäntymäki, M.: Big data analytics in healthcare: a systematic literature review. Enterp. Inf. Syst. 14, 878–912 (2020)
Ngobeni, V., Breitenbach, M.C., Aye, G.C.: Technical efficiency of provincial public healthcare in South Africa. Cost Eff. Resour. Alloc. 18, 1–19 (2020)
Young, M.: Private vs. public healthcare in South Africa, (2016)
Rensburg, R.: Healthcare in South Africa: How inequity is contributing to inefficiency. https://theconversation.com/healthcare-in-south-africa-how-inequity-is-contributing-to-inefficiency-163753
Stuckler, D., Basu, S., Mckee, M.: Health care capacity and allocations among South Africa’s provinces: infrastructure-inequality traps after the end of Apartheid’. Am. J. Public Health 101, 165–172 (2011)
Mogashoa, M.G., Petrus, G.P.J.: An analysis of the implementation of the national core standards in public hospitals. Afr. Insight. 44, 142–147 (2014)
Maphumulo, W.T., Bhengu, B.R.: Challenges of quality improvement in the healthcare of South Africa post-apartheid: a critical review. Curationis 42, 1–9 (2019)
Pastorino, R., et al.: Benefits and challenges of big data in healthcare: an overview of the European initiatives. Eur. J. Public Health 29, 23–27 (2019)
Iyamu, T., Mgudlwa, S.: ANT perspective of healthcare big data for service delivery in South Africa. J. Cases Inf. Technol. 23, 65–81 (2021)
Rowe, F.: What literature review is not: diversity, boundaries and recommendations. Eur. J. Inf. Syst. 23, 241–255 (2014)
Maphosa, V., Maphosa, M.: E-waste management in Sub-Saharan Africa: a systematic literature review. Cogent Bus. Manag. 7, 1814503 (2020)
Nguyen, L., Barton, S.M., Nguyen, L.T.: IP ads in higher education-Hype and hope. Br. J. Educ. Technol. 46, 190–203 (2014)
Templier, M., Paré, G.: Transparency in literature reviews: an assessment of reporting practices across review types and genres in top IS journals. Eur. J. Inf. Syst. 27, 503–550 (2018)
Drucker, A.M., Fleming, P., Chan, A.W.: Research techniques made simple: assessing risk of bias in systematic reviews. J. Invest. Dermatol. 136, e109–e114 (2016)
Chauhan, S.: A meta-analysis of the impact of technology on learning effectiveness of elementary students. Comput. Educ. 105, 14–30 (2017)
Young, S., Chimwaza, G., Eldermire, E.R.B., Ghezzi-Kopel, K., Muziringa, M.: Trends in evidence synthesis publishing across disciplines in Africa: a bibliometric study. Sci. African. 19, e01545 (2023)
Boell, S.K., Cecez-Kecmanovic, D.: A hermeneutic approach for conducting literature reviews and literature searches. Commun. Assoc. Inf. Syst. 34, 257–286 (2014)
Pillay, K., Van der Merwe, A.: Big data driven decision making model: a case of the South African banking sector. South African Comput. J. 33, 55–71 (2021)
Clarke, V., Braun, V.: Thematic analysis. J. Posit. Psychol. 12, 297–298 (2016)
Karatas, M., Eriskin, L., Deveci, M., Pamucar, D., Garg, H.: Big data for healthcare industry 4.0: applications, challenges and future perspectives. Expert Syst. Appl. 200, 116912 (2022)
Thomas, S.: An analysis of the adoption of electronic health records in primary healthcare (2016)
Naik, K., Joshi, A.: Role of big data in various sectors. In: Proceedings of the International Conference on IoT in Social, Mobile, Analytics and Cloud, I-SMAC 2017, pp. 117–122. IEEE (2017)
Jinpon, P., Jaroensutasinee, M., Jaroensutasinee, K.: Business intelligence and its applications in the public healthcare system. Walailak J. Sci. Technol. 8, 97–110 (2011)
Ashrafi, N., Kelleher, L., Kuilboer, J.P.: The impact of business intelligence on healthcare delivery in the USA. Interdisc. J. Inf. Knowl. Manag. 9, 117–130 (2014)
Walls, H.L., et al.: Understanding healthcare and population mobility in southern Africa: the case of South Africa. South African Med. J. 106, 14–15 (2016)
Cozzoli, N., Salvatore, F.P., Faccilongo, N., Milone, M.: How can big data analytics be used for healthcare organization management? Literary framework and future research from a systematic review. BMC Health Serv. Res. 22, 809 (2022)
Brossard, P.Y., Minvielle, E., Sicotte, C.: The path from big data analytics capabilities to value in hospitals: a scoping review. BMC Health Serv. Res. 22, 134 (2022)
Atoum, I.A., AL-Jarallah, N.A.: Big data analytics for value-based care: challenges and opportunities. Int. J. Adv. Trends Comput. Sci. Eng. 8, 3012–3016 (2019)
Sousa, M.J., Pesqueira, A.M., Lemos, C., Sousa, M., Rocha, Á.: Decision-making based on big data analytics for people management in healthcare organizations. J. Med. Syst. 43, 1–10 (2019)
Bates, D.W., Saria, S., Ohno-Machado, L., Shah, A., Escobar, G.: Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff. 33, 1123–1131 (2014)
Mashingaidze, K., Backhouse, J.: The relationships between definitions of big data, business intelligence and business analytics: a literature review. Int. J. Bus. Inf. Syst. 26, 488–505 (2017)
Kaur, P.: Big data analytics in healthcare: a review. Int. J. Eng. Tech. Res. 10, 3–11 (2022)
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Makhaye, N., Mwapwele, S.D. (2024). The Contributions of Business Intelligence and Big Data to Public Healthcare in South Africa. In: Chigona, W., Kabanda, S., Seymour, L.F. (eds) Implications of Information and Digital Technologies for Development. ICT4D 2024. IFIP Advances in Information and Communication Technology, vol 709. Springer, Cham. https://doi.org/10.1007/978-3-031-66986-6_22
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