Profiling patterns in healthcare system: A preliminary study

Chan, Khin Whai * and Lee, Angela Siew Hoong * and Zuraini Zainol, (2020) Profiling patterns in healthcare system: A preliminary study. International Journal of Advanced Computer Science and Application, 11 (4). pp. 661-668. ISSN 2158-107X

Preview

Text Angela Lee Profiling_Patterns_in_Healthcare_System_Published_AngelaLee2020.pdf - Published Version Available under License Creative Commons Attribution Non-commercial. Download (938kB) | Preview

Abstract

In the 21st century, our planet revolves around data and is known as a digital earth. The astonishing growth in data has resulted in an increase in interest of Big Data Analytics to capture, store, process, analyze and visualize unprecedented amount of information. Big data has undoubtedly and will continue to shape modern information driven society where behind all the available data, there is a hidden potential to discover meaningful insights and patterns which may impact businesses in unexpected measures. The exponential growth of data is also present in the healthcare sector. In Malaysia, most employees are provided with medical benefits which includes general medical costs to hospitalization benefits and insurance coverages. With the healthcare data and information stored with the Human Resource (HR), employers could potentially analyze and identify patterns in the historical medical claims which could then help in making specific decisions to understand their employee population health and the usage of the premium coverage. Therefore, the aim of this research is to better understand the patterns presented in the employees’ healthcare data. Through the analysis and understanding of the patterns in past medical claim history, potential strategies can be proposed to allow employers to provide proactive and reactive measures to potentially help sustain medical expenditure.

Actions (login required)

View Item