Journal of Healthcare Management - July/August 2014 - (Page 255)

D ec I sI ons t Hroug H D ata : a nalytIcs INTRODUCTION By 2015, the average hospital will produce more than 665 terabytes of data, which is equivalent to 697,303,040 megabytes (Pogorelc, 2013). While the volume of healthcare data is rapidly increasing, healthcare organizations are searching for better data management solutions. The consulting firm Frost & Sullivan (2012) suggests that "while this data is being hailed as the key to improving health outcomes and reducing healthcare costs, the sheer volume of data is so overwhelming that most organizations are unable to take full advantage of it with their current resources." Indeed, one recent survey of physicians and hospital executives found that too much healthcare data is available and not enough applicable information accompanies the data (Wolters Kluwer Health, 2011). Westby G. Fisher, MD (2012), a physician with NorthShore University HealthSystem, based in Evanston, Illinois, says, "There's so much data that we risk getting lost in it." The increasing amount of healthcare data is a pressing concern that must be addressed because it threatens the efficiency of an organization (Burns, 2013). BACKGROUND Fortunately for the healthcare industry, the business sector has already addressed this problem. To not only manage the overwhelming amount of data but also improve operations, businesses turned to data analytics (Kayyali, Knott, & Van Kuiken, 2013). IBM defines data analytics as "the systematic use of data and related business insights developed through applied In H ealtHcare analytical disciplines (e.g. statistical, contextual, quantitative, predictive, cognitive, other [including emerging] models) to drive fact-based decision making for planning, management, measurement, and learning" (Cortada, Gordon, & Lenihan, 2012). With the need to become increasingly cost efficient, predict health trends, eliminate waste, and implement effective practices, data analytics offers solutions for improving the quality of care, containing costs, and managing operational tasks (Prewitt, 2012). One example of the use of business analytics is the loyalty cards Target Corporation uses with its customers. The loyalty cards allow the company to track a customer's purchases and predict future buying trends. Target can send coupons or advertisements to customers depending on their purchasing patterns. Another example in retail is Amazon.com, which uses business analytics to offer personalized purchase recommendations to customers, accounting for 35% of purchases made. Information offered by data analytics allows companies such as Target and Amazon.com to maximize revenue sources and tailor marketing to customers (Datoo, 2013). While the implementation of data analytics in healthcare is relatively new, it has been met with resistance. The complex nature of the healthcare industry-which includes a provider's desire for independence, inadequate technological infrastructure, and disconnected systems-has, until recently, limited organizations' ability to incorporate the level of sophistication in data analytics that has become common 255 http://www.Amazon.com http://www.Amazon.com

Table of Contents for the Digital Edition of Journal of Healthcare Management - July/August 2014

Journal of Healthcare Management - July/August 2014
Contents
Interview With Charles R. Evans, FACHE, President of the International Health Services Group and Senior Advisor at Jackson Healthcare
The Most Effective Leadership Style for the New Landscape of Healthcare
Exploring Obstacles to Success for Early Careerists in Healthcare Leadership
Decisions Through Data: Analytics in Healthcare
Sustainable Competitive Advantage for Accountable Care Organizations
Hospital Characteristics Associated With Achievement of Meaningful Use
The Effect of Professional Culture on Intrinsic Motivation Among Physicians in an Academic Medical Center
Abstract from the Academy of Management

Journal of Healthcare Management - July/August 2014