scholarly journals Reduced Clostridium difficile Tests and Laboratory-Identified Events With a Computerized Clinical Decision Support Tool and Financial Incentive

2018 ◽  
Vol 39 (6) ◽  
pp. 737-740 ◽  
Author(s):  
Gregory R. Madden ◽  
Ian German Mesner ◽  
Heather L. Cox ◽  
Amy J. Mathers ◽  
Jason A. Lyman ◽  
...  
Keyword(s):  
Decision Support ◽  
Clostridium Difficile ◽  
Clinical Decision Support ◽  
Financial Incentive ◽  
Decision Support Tool ◽  
Interrupted Time Series ◽  
Clinical Decision ◽  
Support Tool ◽  
Time Series Analyses ◽  
Clinical Decision Support Tool

We hypothesized that a computerized clinical decision support tool for Clostridium difficile testing would reduce unnecessary inpatient tests, resulting in fewer laboratory-identified events. Census-adjusted interrupted time-series analyses demonstrated significant reductions of 41% fewer tests and 31% fewer hospital-onset C. difficile infection laboratory-identified events following this intervention.Infect Control Hosp Epidemiol 2018;39:737–740

scholarly journals Challenges involved in establishing a web-based clinical decision support tool in community health centers

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 100488
Author(s):  
Rachel Gold ◽  
Mary Middendorf ◽  
John Heintzman ◽  
Joan Nelson ◽  
Patrick O'Connor ◽  
...  
Keyword(s):  
Decision Support ◽  
Community Health ◽  
Clinical Decision Support ◽  
Community Health Centers ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Health Centers ◽  
Web Based ◽  
Support Tool ◽  
Clinical Decision Support Tool

scholarly journals Duplicate Laboratory Test Reduction Using a Clinical Decision Support Tool

2014 ◽  
Vol 141 (5) ◽  
pp. 718-723 ◽  
Author(s):  
Gary W. Procop ◽  
Lisa M. Yerian ◽  
Robert Wyllie ◽  
A. Marc Harrison ◽  
Kandice Kottke-Marchant
Keyword(s):  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Clinical Decision Support Tool

41 Enhancing Burn Medical Care During a Disaster Using a Novel Augmented-Reality Application

2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S31-S31
Author(s):  
Sena Veazey ◽  
Maria SerioMelvin ◽  
David E Luellen ◽  
Angela Samosorn ◽  
Alexandria Helms ◽  
...  
Keyword(s):  
Decision Support ◽  
Augmented Reality ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Burn Injuries ◽  
Medical Decision ◽  
Support Tool ◽  
Burn Care ◽  
Clinical Decision Support Tool

Abstract Introduction In disaster or mass casualty situations, access to remote burn care experts, communication, or resources may be limited. Furthermore, burn injuries are complex and require substantial training and knowledge beyond basic clinical care. Development and use of decision support (DS) technologies may provide a solution for addressing this need. Devices capable of delivering burn management recommendations can enhance the provider’s ability to make decisions and perform interventions in complex care settings. When coupled with merging augmented reality (AR) technologies these tools may provide additional capabilities to enhance medical decision-making, visualization, and workflow when managing burns. For this project, we developed a novel AR-based application with enhanced integrated clinical practice guidelines (CPGs) to manage large burn injuries for use in different environments, such as disasters. Methods We identified an AR system that met our requirements to include portability, infrared camera, gesture and voice control, hands-free control, head-mounted display, and customized application development abilities. Our goal was to adapt burn CPGs to make use of AR concepts as part of an AR-enabled burn clinical decision support system supporting four sub-applications to assist users with specific interventional tasks relevant to burn care. We integrated relevant CPGs and a media library with photos and videos as additional references. Results We successfully developed a clinical decision support tool that integrates burn CPGs with enhanced capabilities utilizing AR technology. The main interface allows input of patient demographics and injuries with step-by-step guidelines that follow typical burn management care and workflow. There are four sub-applications to assist with these tasks, which include: 1) semi-automated burn wound mapping to calculate total body surface area; 2) hourly burn fluid titration and recommendations for resuscitation; 3) medication calculator for accurate dosing in preparation for procedures and 4) escharotomy instructor with holographic overlays. Conclusions We developed a novel AR-based clinical decision support tool for management of burn injuries. Development included adaptation of CPGs into a format to guide the user through burn management using AR concepts. The application will be tested in a prospective research study to determine the effectiveness, timeliness, and performance of subjects using this AR-software compared to standard of care. We fully expect that the tool will reduce cognitive workload and errors, ensuring safety and proper adherence to guidelines.

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