Journal of Healthcare Management - July/August 2014 - (Page 259)

D ec I sI ons t Hroug H D ata : a nalytIcs offer suggestions for diagnosis and treatment (Murphy, 2013). Real-time analytics goes beyond the mere collection of patient data. Although currently a great deal of point-of-care patient data can be obtained from equipment, that information is typically recorded but underutilized. Real-time analytics focuses on the recording of point readings and streaming data, but more important, it analyzes the data at the point of care to present immediate and actionable information for providers. For example, the analysis can show possible drug interactions, suggest treatment methods, and provide alerts for future complications or developments (Taylor, 2010). Real-time monitoring of patients continually adds information to the ever-increasing supply of data (Taylor, 2010). Tom Olenzak, director of innovation at Independence Blue Cross in Philadelphia, has high hopes for the expansion of real-time analytics. He believes treatment will become more accurate and efficient once physicians can receive real-time information, such as blood glucose levels, about a patient at the point of care. In another example of integrating real-time analytics, the University of Texas Southwestern Medical Center in Dallas is analyzing data from EHRs. The system, whose deployment is currently limited to readmission rates, helps clinical staff keep track of risks and complications so they can focus in particular on patients with a high risk of readmission within 30 days of discharge. As a result, readmission rates have decreased by 5%, which signals an In H ealtHcare increase in the quality of care as well as a decrease in cost (Bresnick, 2013b). Real-time analytics is the most cutting-edge option of the three discussed here, but it is also the most costly to deploy and requires the most training. It requires complete integration of all data, including registries, silos, hardware systems, and software, as well as internal technical support and technical maintenance. But while the input (financial and technical investment) is great, the output holds even greater possibility for reducing cost and increasing quality (Torres, 2009). Recognizing the promise of realtime analytics, Hunterdon Healthcare System has created a hospital performance management system that includes real-time data. Pressure on executives to support up-to-date data came not only from physicians but also from managers, administrators, and financial advisers. Hunterdon executives realized that the overwhelming amount of mismanaged data was draining their resources and energy (Mamary, 2012). Consequently, they chose to channel the data through a system of real-time analytics that will ultimately transform treatment methods, as it highlights information that may be missed during retrospective review. As a result, Hunterdon has experienced improved outcomes. R E C O M M E N D AT I O N S After exploring three approaches to data analytics-small data, predictive modeling, and real-time analytics-I recommend that healthcare organizations examine all three solutions to determine which suits their particular needs. Each 259

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