Technology | August 16, 2011

Allocade, University of Utah to Demonstrate Artificial Intelligence Command and Control System at AHRA Meeting

August 16, 2011 – The department of radiology at University of Utah HealthCare, along with Allocade Inc., will present new data highlighting effective, streamlined operational efficiencies through the use of artificial intelligence software. The performance improvement outcomes will be presented during the poster session at the Association for Medical Imaging Management (AHRA) 39th annual meeting and exposition in Grapevine, Texas, on Aug. 17, 2011. 

The poster’s primary presenter is Steven Tew, MHA, MBA, manager of interventional radiology (IR) at the University of Utah Hospitals & Clinics. The session will focus on how the university’s IR services successfully reduced overtime costs by 90 percent; reduced FTE expenses by 10-15 percent; increased patient volume and improved its Press Ganey scores.

Tew will detail the benefits of managing daily operations in the digital world utilizing On-Cue, an artificial intelligence-based command and control system from Allocade. Streamlined communication among staff and caregivers, increased departmental and hospital efficiencies, increased patient satisfaction and improvements to the hospital’s bottom line are among the learning objectives of the session.

“Utilizing advances in healthcare information technology in combination with changes in departmental processes is necessary to increase efficiency, improve operational transparency between staff and physicians, and provide a higher quality of patient care,” said Tew. “New technology enables us to optimize schedules, streamline communication and provides us with real-time visibility, resulting in a significant reduction in patient scheduling delays, as well as an increase in throughput and improvements to our resource utilization.

“In addition, the software provides access to clinical operations data that previously was very difficult to obtain, enabling us to make objective, meaningful business decisions. As a result, we have preserved jobs and are improving our bottom line,” continued Tew.

In today’s digital world, parts of healthcare still operate in printed and hand-written paper. Prior to hospital patient procedures, forms are often filled out electronically – patients are scheduled using the radiology information system (RIS) and inpatients are ordered through the hospital information system (HIS).

On the day of the procedure, however, changes to scheduling due to emergencies or add-ons are handled by paper, phone calls and whiteboards. This results in delays, inefficient use of resources (both in equipment and personnel) and less patient-physician interaction.

The On-Cue system manages and communicates constantly changing patient logistics to improve daily operations for all modalities in the radiology department. This includes computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, IR, nuclear medicine and X-ray.

Receiving information directly from the HIS and RIS, On-Cue utilizes artificial intelligence to prioritize among outpatient, inpatient and emergency department demands as it continuously optimizes operational schedules for available resources. The system delivers real-time visibility of all schedule changes to all interested personnel, thereby improving communication and coordination both inside the department and with other departments.

The theme for AHRA’s poster session is “performance improvement” and measurable outcomes are required.

For more information: www.allocade.com

Related Content

FDA Clears Bay Labs' EchoMD AutoEF Software for AI Echo Analysis
Technology | Cardiovascular Ultrasound | June 19, 2018
Cardiovascular imaging artificial intelligence (AI) company Bay Labs announced its EchoMD AutoEF software received 510(...
News | Remote Viewing Systems | June 14, 2018
International Medical Solutions (IMS) recently announced that the American College of Radiology (ACR) added IMS'...
Wake Radiology Launches First Installation of EnvoyAI Platform
News | Artificial Intelligence | June 13, 2018
Artificial intelligence (AI) platform provider EnvoyAI recently completed their first successful customer installation...
How AI and Deep Learning Will Enable Cancer Diagnosis Via Ultrasound

The red outline shows the manually segmented boundary of a carcinoma, while the deep learning-predicted boundaries are shown in blue, green and cyan. Copyright 2018 Kumar et al. under Creative Commons Attribution License.

News | Ultrasound Imaging | June 12, 2018 | Tony Kontzer
June 12, 2018 — Viksit Kumar didn’t know his mother had...
Zebra Medical Vision Unveils AI-Based Chest X-ray Research
News | Artificial Intelligence | June 08, 2018
June 8, 2018 — Zebra Medical Vision unveiled its Textray chest X-ray research, which will form the basis for a future
Konica Minolta Launches AeroRemote Insights for Digital Radiography
Technology | Analytics Software | June 07, 2018
Konica Minolta Healthcare Americas Inc. announced the release of AeroRemote Insights, a cloud-based, business...
Vinay Vaidya, Chief Medical Information Officer at Phoenix Children’s Hospital

Vinay Vaidya, Chief Medical Information Officer at Phoenix Children’s Hospital

Sponsored Content | Case Study | Artificial Intelligence | June 05, 2018
The power to predict a cardiac arrest, support a clinical diagnosis or nudge a provider when it is time to issue medi
How image sharing through a health information exchange benefits patients while saving time and money is depicted in this slide shown at HIMSS 2018. Graphic courtesy of Karan Mansukhani.

How image sharing through a health information exchange benefits patients while saving time and money is depicted in this slide shown at HIMSS 2018. Graphic courtesy of Karan Mansukhani.

Feature | Information Technology | June 05, 2018 | By Greg Freiherr
A regional image exchange system is saving lives and reducing radiology costs in Maryland by improving the efficiency
Using Imaging Analytics for Radiology, VCU Health in Richmond, Va., has developed a dashboard to view turnaround time analysis. This functionality allows drill down for each technologist and radiologist and looks at the different steps of the imaging cycle.

Using Imaging Analytics for Radiology, VCU Health in Richmond, Va., has developed a dashboard to view turnaround time analysis. This functionality allows drill down for each technologist and radiologist and looks at the different steps of the imaging cycle.

Sponsored Content | Case Study | Information Technology | June 05, 2018
Sharon Gibbs, director of the radiology department at VCU Health in Richmond, Va., aims to provide quality, timely and...
PACS and the Road to Reconstruction
Feature | PACS | June 05, 2018 | By Dave Whitney and Jef Williams
The PACS — picture archiving and communication systems — have been in existence for more than 45 years. One of the...
Overlay Init