Browse > Article
http://dx.doi.org/10.13106/kjfhc.2022.vol8.no6.19.

The Necessity of Business Intelligence as an Indispensable Factor in the Healthcare Sector  

KANG, Eungoo (Becamex School of Business, Eastern International University)
Publication Information
The Korean Journal of Food & Health Convergence / v.8, no.6, 2022 , pp. 19-29 More about this Journal
Abstract
Business intelligence (BI) is a process for turning data into insights that inform an organization's strategic and tactical decisions. BI aims to give decision-makers the information they need to make better decisions Patient safety analysis, illness surveillance, and fraud identification are just a few healthcare decision-making processes that can be supported by data mining. Thus, the purpose of the current research is to outline the need if BI as an essential factor in the healthcare sector by reviewing various scholarly materials and the findings. The present author conducted one of the most famous qualitative literature approach which has been called as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. The selecting criteria for eligible prior studies were estimated by whether studies are suitable for the current research, identifying they are peer-reviewed and issued by notable publishers between 2017 and 2022. According to the result based on the PRISMA analysis, BI plays a vital role in the healthcare sector and there are four business intelligence factors (Data, Analytic, Reporting, and Visualization) that will ensure that the healthcare sector provides the right healthcare services to the customers to be addressed in this section include; data, analytics, reporting, and visualization.
Keywords
Healthcare Business; Healthcare Decision Processes; Business Intelligence; PRISMA Statement;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Alhashmi, S. F., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2020, April). A systematic review of the factors affecting the artificial intelligence implementation in the health care sector. In The International Conference on Artificial Intelligence and Computer Vision (pp. 37-49). Springer, Cham.
2 Bozic, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International journal of information management, 46(June), 93-103.   DOI
3 Gaardboe, R., & Svarre, T. (2018, September). BI end-user segments in the public health sector. In International Conference on Electronic Government and the Information Systems Perspective (pp. 231-242). Springer, Cham.
4 Hamouche, S. (2021). Human resource management and the COVID-19 crisis: Implications, challenges, opportunities, and future organizational directions. Journal of Management & Organization, 1, 1-16.   DOI
5 Kamble, S. S., Gunasekaran, A., Goswami, M., & Manda, J. (2018). A systematic perspective on the applications of big data analytics in healthcare management. International Journal of Healthcare Management, 15(3), 267-275.
6 Moita, G. F., Bernardo, C. G., Costa, J. C., & Azevedo, D. A. (2018). Business Intelligence Application in Adaptation of Servqual Scale at Brazilian Health System. In Proceedings of 11th IADIS International Conference Information Systems, Lisbon.
7 Ramakrishnan, T., Kathuria, A., & Saldanha, T. J. (2020). Business intelligence and analytics (BI&A) capabilities in healthcare. In Theory and Practice of Business Intelligence in Healthcare (pp. 1-17). IGI Global.
8 Salisu, I., Bin Mohd Sappri, M., & Bin Omar, M. F. (2021). The adoption of businesintelligence systems in small and medium enterprises in the healthcare sector: A systematic literature review. Cogent Business & Management, 8(1), 193-566.
9 Tariq, N., Qamar, A., Asim, M., & Khan, F. A. (2020). Blockchain and smart healthcare security: a survey. Procedia Computer Science, 175, 615-620.   DOI
10 Yiu, L. D., Yeung, A. C., & Cheng, T. E. (2021). The impact of business intelligence systems on profitability and risks of firms. International Journal of Production Research, 59(13), 3951-3974.   DOI
11 Yee, J. M., Cross, N., & Bhargava, P. (2022). Do-It-Yourself Business Intelligence for the Radiologist-Lessons Learned From 10-Year Trends in an Abdominal Imaging Division at a Tertiary Medical Center. Journal of the American College of Radiology, 19(2), 329-335.   DOI
12 El Morr, C., & Ali-Hassan, H. (2019). Healthcare, data analytics, and business intelligence. In Analytics in Healthcare (pp. 1-13). Springer, Cham.
13 Gaardboe, R., Sandalgaard, N., & Jonasen, T. S. (2018, August). Which factors of business intelligence affect individual impact in public healthcare?. In Proceedings from The 16th Scandinavian Conference on Health Informatics 2018, Aalborg, Denmark August 28-29, 2018 (pp. 96-100). Linkoping University Electronic Press.
14 Marzouk, M., & Hanafy, M. (2022). Modelling maintainability of healthcare facilities services systems using BIM and business intelligence. Journal of Building Engineering, 46(April), 103820.   DOI
15 Sorrentino, M., Sicilia, M., & Howlett, M. (2018). Understanding co-production as a new public governance tool. Policy and Society, 37(3), 277-293.   DOI
16 Khedr, A., Kholeif, S., & Saad, F. (2017). An integrated business intelligence framework for healthcare analytics. International Journal of Advanced Research in Computer Science and Software Engineering, 7(5), 263-270.   DOI
17 Ain, N., Vaia, G., DeLone, W. H., & Waheed, M. (2019). Two decades of research on business intelligence system adoption, utilization and success-A systematic literature review. Decision Support Systems, 125(October), 113-113.
18 Galetsi, P., Katsaliaki, K., & Kumar, S. (2019). Values, challenges and future directions of big data analytics in healthcare: A systematic review. Social science & medicine, 241(November), 112533.   DOI
19 Arefin, M. S., Hoque, M. R., & Rasul, T. (2020). Organizational learning culture and business intelligence systems of health-care organizations in an emerging economy. Journal of Knowledge Management, 25(3), 573-594.   DOI
20 El-Adaileh, N. A., & Foster, S. (2019). Successful business intelligence implementation: a systematic literature review. Journal of WorkApplied Management, 11(2), 121-132.
21 Hong, J. H. (2021). A global strategy of a company that uses culture content as its core business. The Journal of Industrial Distribution & Business, 12(6), 37-46.   DOI
22 Isazad Mashinchi, M., Ojo, A., & Sullivan, F. J. (2019, January). Analysis of business intelligence applications in healthcare organizations. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
23 Kamruzzaman, M. M. (2020, July). Architecture of smart health care system using artificial intelligence. In 2020 IEEE international conference on multimedia & expo workshops (ICMEW) (pp. 1-6). London, UK: IEEE.
24 Kang, E. (2021). Qualitative content approach: Impact of organizational climate on employee capability. East Asian Journal of Business Economics, 9(4), 57-67.   DOI
25 Khuntia, J., Ning, X., & Tanniru, M. (Eds.). (2019). Theory and Practice of Business Intelligence in Healthcare. IGI Global.
26 Kim, J. H., & Kang, E. (2022). The Role of Wearable Devices for the Success of the Healthcare Business: Verification from PRISMA Approach. Journal of Economics Marketing, and Management, 10(4), 13-24.   DOI
27 Liang, T. P., & Liu, Y. H. (2018). Research landscape of business intelligence and big data analytics: A bibliometrics study. Expert Systems with Applications, 111, 2-10.   DOI
28 Bordeleau, F. E., Mosconi, E., & de Santa-Eulalia, L. A. (2020). Business intelligence and analytics value creation in Industry 4.0: a multiple case study in manufacturing medium enterprises. Production Planning & Control, 31(2-3), 173-185.   DOI
29 Kudyba, S. P., & Temple, R. (2021). An Introduction to the US Healthcare Industry, Digital Technologies, and Informatics. In Healthcare Informatics (pp. 11-29). Auerbach Publications.
30 Lambay, M. A., & Mohideen, S. P. (2020, July). Big data analytics for healthcare recommendation systems. In 2020 International Conference on System, Computation, Automation and Networking (ICSCAN) (pp. 1-6). ). Pondicherry, India: IEEE.
31 Liu, Y., Han, H., DeBello, J. (2018). The challenges of business analytics: successes and failures. Proceedings of the 51th Hawaii International Conference on Systems Sciences.
32 Liyanage, H., Liaw, S. T., Jonnagaddala, J., Schreiber, R., Kuziemsky, C., Terry, A. L., & de Lusignan, S. (2019). Artificial intelligence in primary health care: perceptions, issues, and challenges. Yearbook of medical informatics, 28(1), 041-046.   DOI
33 Manikam, S., Sahibudin, S., & Kasinathan, V. (2019). Business intelligence addressing service quality for big data analytics in public sector. Indonesian Journal of Electrical Engineering and Computer Science, 16(1), 491-499.   DOI
34 Nguyen, L. T., Nantharath, P., & Kang, E. (2022). The Sustainable Care Model for an Ageing Population in Vietnam: Evidence from a Systematic Review. Sustainability, 14(5), 18-25.
35 Shahbaz, M., Gao, C., Zhai, L., Shahzad, F., & Hu, Y. (2019). Investigating the adoption of bigdata analytics in healthcare: the moderating role of resistance to change. Journal of Big Data, 6(1), 1-20.   DOI
36 Nuseir, M. T., Aljumah, A., & Alshurideh, M. T. (2021). How the business intelligence in the new startup performance in UAE during COVID-19: The mediating role of innovativeness. In The effect of coronavirus disease (covid-19) on business intelligence (pp. 63-79). Springer, Cham.
37 Ratia, M., Myllarniemi, J., & Helander, N. (2018). The new era of business intelligence: Big Data potential in the private health care value creation. Meditari Accountancy Research, 26(3), 531-546.   DOI
38 Rikhardsson, P., & Yigitbasioglu, O. (2018). Business intelligence & analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29(June), 37-58.   DOI
39 Teixeira, V., Mori, A., Usera, A., Bacigalupo, J. C., & Luna, D. (2019). Performance evaluation of clinical decision support systems (CDSS): Developing a business intelligence (BI) dashboard. In MEDINFO 2019: Health and Wellbeing e-Networks for All (pp. 829-833). IOS Press.
40 Trabold, N., McMahon, J., Alsobrooks, S., Whitney, S., & Mittal, M. (2020). A systematic review of intimate partner violence interventions: State of the field and implications for practitioners. Trauma, Violence, & Abuse, 21(2), 311-325.   DOI
41 Wang, Y., & Byrd, T. A. (2017). Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care. Journal of Knowledge Management, 21(3), 517-539.   DOI
42 Ajah, I. A., & Nweke, H. F. (2019). Big data and business analytics: Trends, platforms, success factors and applications. Big Data and Cognitive Computing, 3(2), 32.   DOI
43 von Bary, B., Westner, M., & Strahringer, S. (2019). IT Backsourcing: Insights and Implications From a Global Survey With IT Practitioners. International Journal of IT/Business Alignment and Governance (IJITBAG), 10(2), 20-34.   DOI
44 Lee, J. W., & Cormier, J. F. (2010). Effects of consumers' demographic profile on mobile commerce Adoption. Journal of Distribution Science, 8(1), 5-11.   DOI
45 Abraham, C., Chatterjee, D., & Sims, R. R. (2019). Muddling through cybersecurity: Insights from the US healthcare industry. Business horizons, 62(4), 539-548.   DOI