JID:BDR AID:31 /FLA [m5G; v1.168; Prn:20/11/2015; 12:55] P.1(1-12) Big Data Research ••• (••••) •••–••• Contents lists available at ScienceDirect Big Data Research www.elsevier.com/locate/bdr Assessing the Quality of Service Using Big Data Analytics With Application to Healthcare Feras A. Batarseh a,*,1 , Eyad Abdel Latif b,2 a College of Science, George Mason University (GMU), Fairfax, VA, United States b MedStar Georgetown University Hospital (MGUH), Washington, DC, United States a r t i c l e i n f o a b s t r a c t Article history: Received 28 May 2015 Received in revised form 5 September 2015 Accepted 24 October 2015 Available online xxxx Keywords: Big data analytics Quality of Service (QoS) Healthcare Forecasting 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  2015 Elsevier Inc. All rights reserved. 1. Introduction and background Due to the exponential demand for healthcare-specific analyt- ical tools, many existing software vendors are repositioning their tools to allow for their usage in the healthcare realm. This section discusses the existing data analytics tools, introduces the data an- alytics lifecycle, the processes and the factors that are studied in this paper to analyze healthcare’s QoS in multiple US states. 1.1. Big data analytics in healthcare With the recent mandated adoption of electronic health records (EHRs) by the US Department of Health and Human Services (HHS) [1], healthcare professionals are getting access to abun- dant amounts of data that can provide more insights and better takeaways that were not possible before. EHRs are not the only * Corresponding author. E-mail addresses: fbatarse@gmu.edu (F.A. Batarseh), eyad.abdellatif@gunet.georgetown.edu (E.A. Latif). 1 Research Assistant Professor. 2 Clinical Administrator, Nursing Admin. ample and rich source of healthcare data, for instance, wireless health monitoring devices and behavioral social media sources also provide more opportunities and could be serious game-changers. Multiple data analytics software vendors are building tools that are connected to these sources and are specifically tailored to healthcare; for example, IBM provides a tool for health paper- work content management. The tool helps healthcare providers with recording their patients’ health data, and provides access to tools for data analysis and visualizations [2]. One of the main users of this tool is the State of North Dakota’s (ND) Depart- ment of Human Services (DHS). The department along with the tool provides services that help citizens of all ages with main- taining and enhancing their health. On their website, IBM claims the following: “ND’s DHS replaced paper-based processes with a central electronic content management system that makes infor- mation more accessible and streamlines workflows, helping staff work together more effectively” [2]. SAS [3] on the other hand, is another data-analytics provider that created a dedicated Cen- ter for Health Analytics and Insights to address the increasing de- mand from hospitals, clinics, and health professionals across the world. SAS is a global provider of analytics that covers multi- ple industries, such as financial institutions, education, govern- http://dx.doi.org/10.1016/j.bdr.2015.10.001 2214-5796/ 2015 Elsevier Inc. All rights reserved.