Assessing the Quality of Service Using Big Data Analytics: With Application to Healthcare

Many industries are riding the wave of big data as the new era of data-driven decision making is unveiling. The field of big data analytics is gaining fast traction in industry, academia and the government; the healthcare arena is no different. In this paper, big data analytics are applied to healthcare data that is collected from multiple sources to gain quality insights and apprehend best practices of the field (using new healthcare specific big data tools). The US states are unceasingly pursuing potential improvements to their healthcare's Quality of Service (QoS). Recent changes in data sharing provisions, such as the disposition of the recent Affordable Health Care Act (ACA), changed the rules of the game, and provided the US states with a new set of measurable health quality variables that they couldn't overlook anymore. Individuals in those states without health insurance tend to ignore visiting the clinic even if they feel symptoms of a disease; healthy young individuals with insurance can also have the same behavior. Health experts constantly recommend closer immersion in one's health and more engagement with preventive healthcare. In three experimental studies, this multidisciplinary paper examines historical health data from all over the country, assesses the medical QoS for multiple US states using a new healthcare-specific analytical infrastructure, delivers forecasts and correlations for future healthcare activities, and provides data-driven