Technology | October 09, 2014

Intelerad Launches Assignment Engine Module for Radiologists

New module automates case assignment across the enterprise and prioritizes cases within radiologists’ worklists

October 9, 2014 — Intelerad Medical Systems launched its Assignment Engine module, which automatically assigns pending cases from across the enterprise to the most suitable radiologist, and prioritizes the cases within the radiologist's own dynamic worklist.

“Intelerad’s Assignment Engine is a game-changing module that optimizes imaging operations by automating case assignment and prioritization,” said Frederic Lachmann, vice president of clinical decision support, Intelerad. “By eliminating the amount of time and guesswork involved with these complex tasks, enterprises are able to experience tremendous gains in terms of both efficiency and patient care.”

Designed to optimize efficiency and radiologist utilization, the Assignment Engine adds cases to worklists using a number of real-time variables that are set by the organization, including reader availability, subspecialty, workload, location, the relative amount of time and effort required to read the exam, and more. In doing so, the module raises patient care levels by distributing exams to the most qualified radiologist.

Ideal for large hospitals, multi-facility imaging providers and teleradiology enterprises, the Assignment Engine’s automated case assignment functionality creates balanced caseloads across the enterprise. In addition to driving the enterprise’s productivity, this provides insight into staffing needs while helping them meet service-level agreements and internal benchmarks for key metrics.

For radiologists, leveraging the module’s automated worklist prioritization functionality eliminates the time they need between cases to evaluate their caseload and determine which case should be read next. This drives productivity by eliminating the amount of downtime that radiologists spend between cases, thus allowing them to evaluate more studies per shift and deliver patient diagnostics in less time.

Intelerad’s Assignment Engine is an optional module that will be available for IntelePACS and InteleOne.

For more information: www.rsna.intelerad.com, www.intelerad.com

Related Content

Guerbet, IBM Watson Health Partner on Artificial Intelligence for Liver Imaging
News | Clinical Decision Support | July 10, 2018
Guerbet announced it has signed an exclusive joint development agreement with IBM Watson Health to develop an...
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...
Overlay Init