Data Analytics In Preventive Health Care With Total Quality Management Approach - Özlem Akcay Kasapoğlu (European Scientific Journal, ESJ, 2016)
In this new era where people are more concerned about their health, they are trying to follow a healthy life style. The hospital and health care units is continually improving their value to their patients. This they accomplish through the provision of high quality services. Since there is a worldwide rise in the prevalence of chronic diseases, preventive healthcare should be one of the services that should be given to patients in the customer relationship management concept. This service could be integrated to the hospitals and local healthcare units with an understanding of total quality management and with a strong top management support. Being the customer’s focus, understanding the customer is an important total quality management principle. Health care is the most crucial and delicate service that could be given. With preventive health care practices, effective patient data tracking, and data analytics, patients with potential diseases could be identified. Also, better life choice practices could be recommended which would prolong their life expectancy. Health promotional activities do not target a specific disease or condition, but rather promote the health and wellbeing on a general level. In this article, with the help of data mining tools, the patients’ potential risks were identified. In addition, different health promotion and training services were recommended to be given to the patients. In training the patients, the effects of life choices from nutritious meals to daily exercising, increase the overall well besides preventing some of the potential threats. Data mining methods were seen as a useful supplementary method in analysing preventive health care data and its capability to illustrate a large dataset. Therefore, its relationships between variables are the reason it was selected in this study.