Augmented Communication Tools (Acts)

Technology #ua16-202

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Categories
Researchers
Jane Carrington
Assistant Professor, College of Nursing
Mihai Surdeanu
Associate Professor, Computer Science
Angus Forbes
Assistant Professor, 33
Peter Jansen
Assistant Research Professor, Linguistics
Managed By
Lewis Humphreys
Licensing Manager (520) 626-2574

Title: Enhanced Interface for Electronic Health Records

 

Invention: Inventors at the University of Arizona have developed an augmented electronic health record (EHR) interface for enhancing nurse decision-making and communications processes. The tool is effective at preventing cognitive overload by giving nurses an automated visual representation (via bar charts, line graphs, and other diagrams) of patient’s vital signs, as well as their likely clinical outcomes. Nurses can enter their observations into the EHR using natural language, and the program will automatically couple nurse observations with the related vital signs using color codes and other visual cues. This improves nurse communication about individual patients.

 

Background: EHRs provide new opportunities for nurses to integrate data analyses into their practice. The act of recording, retrieving, and analyzing the data is rife with communications issues, however, and it is difficult to interpret and draw conclusions. The invention was designed to predict a patient’s likelihood for experiencing certain clinical events by using predictive algorithms, thereby improving healthcare efficiency.

 

Applications:

  • Augmenting EHRs
  • Data support for hospitals
  • Potential to be applied to a wide variety of tasks for automation via natural language
  • Improvement of electronic management tools by utilizing both natural language features and graphical communication features

 

Advantages:

  • Understands natural language
  • Designed to streamline and improve the efficiency of nurses using EHRs to document and predict patient outcomes
  • Helps nurses know what they should be looking for and which clinical outcomes are most likely
  • Allows nurses and hospital personnel to focus more on providing care to patients instead of spending time filling out EHRs
  • Observations are correlated and understood in relation to “hard data” on patients’ vital measurements
  • The interface functions on both desktop browsers and tablet computers
  • Can easily be adapted to work on smartphones or for use with different EHRs
  • Eases the cognitive burden of these processes by automatically generating useful graphs to help predict patient outcomes

 

Licensing Manager: 

Lewis Humphreys

LewisH@tla.arizona.edu

(520) 626-1213