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Augmented Communication Tools (ACTs)

詳細技術說明

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 hospitalsPotential to be applied to a wide variety of tasks for automation via natural languageImprovement of electronic management tools by utilizing both natural language features and graphical communication features Advantages:Understands natural languageDesigned to streamline and improve the efficiency of nurses using EHRs to document and predict patient outcomesHelps nurses know what they should be looking for and which clinical outcomes are most likelyAllows nurses and hospital personnel to focus more on providing care to patients instead of spending time filling out EHRsObservations are correlated and understood in relation to “hard data” on patients’ vital measurementsThe interface functions on both desktop browsers and tablet computersCan easily be adapted to work on smartphones or for use with different EHRsEases the cognitive burden of these processes by automatically generating useful graphs to help predict patient outcomes Licensing Manager:  Lewis HumphreysLewisH@tla.arizona.edu (520) 626-1213

*Abstract

None

*Principal Investigation

Name: Jane Carrington, Assistant Professor

Department: College of Nursing

Name: Mihai Surdeanu, Associate Professor

Department: Computer Science

Name: Angus Forbes, Assistant Professor

Department: 33

Name: Peter Jansen, Assistant Research Professor

Department: Linguistics

國家/地區

美國