Health Data Analytics: Frameworks, Tools, and Impact on the Administration Efficiency and Performance in Healthcare

The view—‘Our access to more information has resulted in finding new ways in order to correspond to the most difficult of the situations’—coincides with the recent phenomenon, where the governments, nations, and managers take an effort in the quest for more and more information. Especially, in the health sector, which includes great quantities of data, the use of big data through specialized applications can lead to developments in management, decision-making, forecasting, and significant reductions in healthcare costs. Now, when the public healthcare service sector is facing increased costs of healthcare services and inefficient staff positioning, it becomes obvious that the right application of health data can provide solutions for economic efficiency, better performance and better healthcare service provision for the people. This chapter makes an effort to examine the use of health analytic methods and add in discovering ways of financial efficiency, cost reduction, and potential improvements in the field of administration in the healthcare service sector. First, this study presents a definition and discussion on Health Data Analytics with examples. Second, Big Data Analytics is classified into four types according to previous papers regarding health analytics applications. Then, the application areas of health analytics for creating better results are presented. Moreover, architectural framework of health analytics and the tools and platforms, which are popular, are also shown. Based on results from previous researchers, I try to explain how Health Data Analytics application can be helpful for managers in order to provide better healthcare services for people. For a methodological view, a bibliographic review was performed, based on research for related papers in a number of online databases such as Science Direct, Google Scholar, Pub Med, Research Gate, SpringerLink, IEEE Xplore, books, articles, proceedings, conference papers, and other sources. Finally, conclusions and future directions are presented. Data was collected from the work published during 2006 to 2023 (in order to capture the introduction of health analytics implementation in healthcare and the progress that has taken place in the field).