DocumentCode :
2745732
Title :
An assessment of visualization tools for patient monitoring and medical decision making
Author :
Craft, Max ; Dobrenz, Bev ; Dornbush, Erik ; Hunter, Molly ; Morris, Jordan ; Stone, Michelle ; Barnes, Laura E.
Author_Institution :
Univ. of Virginia, Charlottesville, VA, USA
fYear :
2015
fDate :
24-24 April 2015
Firstpage :
212
Lastpage :
217
Abstract :
Visualization of health data can increase situational awareness, maximize utility of patient data, and improve the clinical decision-making processes in critical care settings. Many hospitals are burdened by vast quantities and varieties of data and are struggling to manage, analyze, interpret, and present it in a meaningful way. Graphical visualization and predictive modeling are effective mechanisms to aid clinicians in assessing patient status and recognizing critical changes over time. In an analysis of the UVa Hospital´s Surgical Trauma Burn Intensive Care Unit (STBICU), we examined the impacts that technology and data have on workflow and the value added to various stakeholders. An online survey was distributed to Attending Physicians, Residents, Nurse Practitioners, and Nurses. The goal of this survey was to better understand the ways that various clinical positions interact with data visualization technology regarding patient diagnosis and general workflow. The survey results indicated that graphical representations are under-utilized compared to spreadsheets and progress notes. Additionally, clinicians consider current information technology to be sufficient for evaluating patients´ past and current health data, but not for future health status. Data visualization technology and predictive models provide an alternative monitoring solution to overcome existing system limitations.
Keywords :
Big Data; data visualisation; decision making; hospitals; patient diagnosis; patient monitoring; UVa Hospital STBICU; UVa Hospital surgical trauma burn intensive care unit; clinical decision-making processes; graphical visualization; health data visualization; hospitals; medical decision making; patient diagnosis; patient monitoring; predictive modeling; Biomedical monitoring; Data visualization; Decision making; Medical diagnostic imaging; Medical services; Monitoring; Predictive models; Medical informatics; big data; clinical decision support; clinical workflow; monitoring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Information Engineering Design Symposium (SIEDS), 2015
Conference_Location :
Charlottesville, VA
Print_ISBN :
978-1-4799-1831-7
Type :
conf
DOI :
10.1109/SIEDS.2015.7116976
Filename :
7116976
Link To Document :
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