Elaborating the Role of Business Intelligence (BI) in Healthcare Management

Mati Ur Rehman; Rooh  Ullah; Hawraa Allowatia; Shabana Perween; Qurat Ul Ain; Muhammad Ammad; Tarique Noorul Hasan

doi:10.37380/jisib.v12i2.952

Authors

Mati Ur Rehman Pure Health Laboratory, Mafraq Hospital, Abu Dhabi
Rooh Ullah Pure Health Laboratory, Mafraq Hospital, Abu Dhabi
Hawraa Allowatia Quality Management Department, Pure Lab, Dubai
Shabana Perween Pure Health Laboratory, Mafraq Hospital, Abu Dhabi
Qurat Ul Ain Pure Health Laboratory, Mafraq Hospital, Abu Dhabi
Muhammad Ammad Pure Health Laboratory, Mafraq Hospital, Abu Dhabi
Tarique Noorul Hasan Pure Health Laboratory, Mafraq Hospital, Abu Dhabi

DOI:

https://doi.org/10.37380/jisib.v12i2.952

Keywords:

Business Intelligence, BI, Healthcare, Management, Medical

Abstract

The sector of healthcare is one of the most growing and developing sector of the current economy. The leaders of healthcare system need keys that would help them to advance business processes, decision-making, communication between physicians, administration and
patients, as-well-as effective data access. In this case, Business Intelligence (BI) systems may be useful.
BI is a new multidisciplinary research field that is being used in a variety of industries. It entails extracting information from large amounts of data and delivering it to stakeholders in a decision-making context that is correct. Many BI applications in the healthcare industry
attempt to analysing data, predictions, supporting decision-making, and attaining total sector improvements. In today’s rapidly evolving health-care industry, decision-makers must cope with increasing demands for administrative and clinical data in order to meet regulatory and public-specific standards. The application of BI is realized as a viable resolution to this problem.As the current data on BI is mainly focusing on the area of industry, So the aim of the current input is to adapt and translate the present research findings for the health-care industry.
For this reason, various BI definitions are explored and consolidated into a framework. The objective of this review is to give an overview of how to use BI to aid decision-making in healthcare companies. Along these the sector specific requisites for effective BI-application and role in future are discussed.

References

Ahn, S., Couture, S. V., Cuzzocrea, A., Dam, K., Grasso, G. M., Leung, C. K., McCormick, K. L., & Wodi, B. H. (2019). A fuzzy logic based machine learning tool for supporting big data business analytics in complex artificial intelligence environments. 2019 IEEE international conference on fuzzy systems (FUZZ-IEEE).

Al-Sarawi, S., Anbar, M., Abdullah, R., & Al Hawari, A. B. (2020). Internet of things market analysis forecasts, 2020–2030. 2020 Fourth World Conference on smart trends in systems, security and sustainability (WorldS4).

Alloghani, M., Al-Jumeily, D., Hussain, A., Aljaaf, A. J., Mustafina, J., & Petrov, E. (2018). Healthcare services innovations based on the state of the art technology trend industry 4.0. 2018 11th International Conference on Developments in eSystems Engineering (DeSE).

Ameen, A. M., Ahmed, M. F., & Abd Hafez, M. A. (2018). The impact of management accounting and how it can be implemented into the organizational culture. Dutch Journal of Finance and Management, 2(1), 02.

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.

Aruldoss, M., Travis, M. L., & Venkatesan, V. P. (2014). A survey on recent research in business intelligence. Journal of Enterprise Information Management.

Ashrafi, N., Kelleher, L., & Kuilboer, J.-P. (2014). The impact of business intelligence on healthcare delivery in the USA. Interdisciplinary Journal of Information, Knowledge, and Management, 9, 117.

Azizi, S. M., Soroush, A., & Khatony, A. (2019). The relationship between social networking addiction and academic performance in Iranian students of medical sciences: a cross-sectional study. BMC psychology, 7(1), 1–8.

Bisheh, M., Raissi, A., & Mokhtari, S. (2021). Combination of Backward and Forward Approaches for Future Prediction by Business Intelligence Tools. American Journal of Engineering and Applied Sciences.

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.

Bordeleau, F.-E., Mosconi, E., & Santa-Eulalia, L. A. (2018). Business Intelligence in Industry 4.0: State of the art and research opportunities. Proceedings of the 51st Hawaii International Conference on System Sciences.

Bu, N., & Wu, T. (2022). The Asia-Pacific region: The new center of gravity for international business. In International Business in the New Asia-Pacific (pp. 3–29). Springer.

Carlisle, S. (2018). Software: Tableau and microsoft power bi. Technology| Architecture+ Design, 2(2), 256–259.

Conboy, K., Mikalef, P., Dennehy, D., & Krogstie, J. (2020). Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda. European Journal of Operational Research, 281(3), 656–672.

Diamandis, P. H., & Kotler, S. (2020). The future is faster than you think: How converging technologies are transforming business, industries, and our lives. Simon & Schuster.

Esteves, M., Abelha, A., & Machado, J. (2019). The development of a pervasive Web application to alert patients based on business intelligence clinical indicators: a case study in a health institution. Wireless Networks, 1–7.

Gastaldi, L., Pietrosi, A., Lessanibahri, S., Paparella, M., Scaccianoce, A., Provenzale, G., Corso, M., & Gridelli, B. (2018). Measuring the maturity of business intelligence in healthcare: Supporting the development of a roadmap toward precision medicine within ISMETT hospital. Technological Forecasting and Social Change, 128, 84–103.

Goodman, J., Gorman, L., & Herrick, D. (2010). Health information technology: Benefits and problems. National Center for Policy Analysis, Washington.

Gurjar, Y. S., & Rathore, V. S. (2013). Cloud business intelligence–is what business need today. International Journal of Recent Technology and Engineering, 1(6), 81–86.

Jinpon, P., Jaroensutasinee, M., & Jaroensutasinee, K. (2011). Business intelligence and its applications in the public healthcare system. Walailak Journal of Science and Technology (WJST), 8(2), 97–110.

Johnson, K. B., Wei, W. Q., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2021). Precision medicine, AI, and the future of personalized health care. Clinical and translational science, 14(1), 86–93.

Kamble, S. S., & Gunasekaran, A. (2020). Big data-driven supply chain performance measurement system: a review and framework for implementation. International Journal of Production Research, 58(1), 65–86.

Kumari, N. (2013). Business intelligence in a nutshell. International journal of innovative research in computer and communication engineering, 1(4), 969–975.

Lale, A. W. (2022). Business intelligence implementation in different organizational setup evidence from reviewed literatures. Knowledge Engineering for Modern Information Systems: Methods, Models and Tools, 173.

Lee, S., Lim, D., Moon, Y., Lee, H., & Lee, S. (2022). Designing a business intelligence system to support industry analysis and innovation policy. Science and Public Policy.

Liu, Y., Lee, J. M., & Lee, C. (2020). The challenges and opportunities of a global health crisis: the management and business implications of COVID-19 from an Asian perspective. Asian Business & Management, 19(3), 277–297.

Lousa, A., Pedrosa, I., & Bernardino, J. (2019). Evaluation and Analysis of Business Intelligence Data Visualization Tools. 2019 14th Iberian Conference on Information Systems and Technologies (CISTI).

Luhn, H. P. (1958). A business intelligence system. IBM Journal of research and development, 2(4), 314–319.

Malik, M. A. (2022). Fragility and challenges of health systems in pandemic: early lessons from India’s second wave of coronavirus disease 2019 (COVID-19). Global Health Journal.

Massey, A. P. (2008). Collaborative Technologies. Handbook on Decision Support Systems 1. Editors: F. Burstein, CW Holsapple. In: Springer.

Monteiro, M. (2021). Business Intelligence systems development in hospitals using an Agile Project Management approach.

Olszak, C. M., & Batko, K. (2012). The use of business intelligence systems in healthcare organizations in Poland. 2012 Federated Conference on Computer Science and Information Systems (FedCSIS).

Powell, B. (2018). Mastering Microsoft Power BI: expert techniques for effective data analytics and business intelligence. Packt Publishing Ltd.

Rouhani, S., Asgari, S., & Mirhosseini, S. V. (2012). Review study: business intelligence concepts and approaches. American Journal of Scientific Research, 50(1), 62–75.

Shao, C., Yang, Y., Juneja, S., & GSeetharam, T. (2022). IoT data visualization for business intelligence in corporate finance. Information Processing & Management, 59(1), 102736.

Singh, H. (2012). Implementation benefit to business intelligence using data mining techniques. International Journal of Computing & Business Research, 1–6.

Tavera Romero, C. A., Ortiz, J. H., Khalaf, O. I., & Ríos Prado, A. (2021). Business intelligence: business evolution after industry 4.0. Sustainability, 13(18), 10026.

Thuo, D. N. (2021). Business Intelligence Systems And Performance Of Commercial.

Zeng, L., Xu, L., Shi, Z., Wang, M., & Wu, W. (2006). Techniques, process, and enterprise solutions of business intelligence. 2006 IEEE International Conference on Systems, Man and Cybernetics.