Data Collection and Analysis 

Data analytics is an important approach to managing the data in a healthcare organization alongside the practitioners’ needs. Decision-making is also based on the results obtained during data analytics. During the decision-making process, healthcare practitioners are bound to follow the most appropriate metrics in the healthcare system (Cozzoli et al., 2022). Furthermore, accurate data analytics methods help reduce costs since the organization can analyze the measures most appropriate for the overall delivery of services. Cutting costs also arise since proposed mechanisms arise from the data obtained in the analytics. Additionally, when an organization is more focused on data analytics, it can highlight the challenges they are facing, improving the overall quality of healthcare delivery (Cozzoli et al., 2022). Therefore, organizations that utilize data analytics are better positioned to deliver high-quality healthcare services since they have access to better metrics.

As a result of the improvements in big data’s advantages, many firms have turned to data-driven decision-making. The application of analytics in real-time decision-making has substantial effects on the enhancement of corporate operations and performance (Adrian et al., 2018). Implementation of big data analytics (BDA) has benefited the majority of organizations in a variety of ways, including information technology (IT) infrastructure, operational, managerial, strategic, and organizational benefits. IT infrastructure benefits include the use of reusable and shareable IT resources, which reduces IT management operation costs and increases IT infrastructure capability (Sharma et al., 2014). Indirectly, it improves operational activities by reducing information processing cycle time, increasing productivity, and enhancing quality. Similarly, the results of the analytics utilized by company executives have improved decision-making and improved the planning of corporate management activities.

Implementing BDA will also improve strategic long-term planning to promote corporate growth and the production of business value, hence enhancing organizational performance (Wang et al., 2018). Recent research indicates that BDA is revolutionizing healthcare organizations. The SLR has demonstrated that the BDA solutions are now widely regarded as a benchmark for the application of managerial studies to healthcare companies. The coronavirus pandemic served as a useful test case for the use of BDA in the development of health policy measures (Cozzoli et al., 2022).

Saudi Arabia is in the transformative phase, where different strategies have been incorporated to increase the effects that have been actioned towards the said needs. Data analytics is taking the approach of predictive analytics that intends to develop strategies that will increase the effectiveness of health outcomes. Predictive analytics helps draft solutions for ailments, thus improving the facilitation of healthcare solutions (Alharthi, 2018). Additionally, preventative treatments are developed due to the predictive analytics done in healthcare facilities. Healthcare facilities are embracing the need for predictive analytics to increase the quality of healthcare outcomes. Saudi Arabia is more concerned about the healthcare status of the patients. Hence data analytics is a key tool towards how well data is distributed across all health facilities to improve quality and maintain a high standard. Therefore, the emergence of data analytics is very much vested in technology and how well the Kingdom of Saudi Arabia can leverage the benefits of the technology.

Emerging as a revolutionary tool that can enable more proactive and preventive treatment options, health data analytics with a focus on predictive analytics are becoming increasingly important. This article examines how predictive analytics has been employed in the for-profit corporate sector to create well-timed and accurate predictions of critical outcomes, with an emphasis on essential characteristics that may be useful to healthcare-specific applications. A review of published medical research offers evaluations of predictive analytics technology in medical applications, with an emphasis on how hospitals have integrated predictive analytics into routine healthcare services to improve treatment quality (Alharthi, 2018).

References

Adrian, C., Abdullah, R., Atan, R., & Jusoh, Y. Y. (2018). Conceptual model development of big data analytics implementation assessment effect on decision-making. 

Alharthi, H. (2018). Healthcare predictive analytics: An overview with a focus on Saudi Arabia. Journal of infection and public health, 11(6), 749-756.?

Cozzoli, N., Salvatore, F. P., Faccilongo, N., & Milone, M. (2022). How can big data analytics be used for healthcare organization management? Literary framework and future research from a systematic review. BMC Health Services Research, 22(1), 1-14.?

Sharma, R., Mithas, S., & Kankanhalli, A. (2014). Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations. European Journal of Information Systems, 23(4), 433-441.??

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological forecasting and social change, 126, 3-13.