Other Titles

Rising Star Poster

Abstract

Machine Learning-driven decision support systems are being incorporated into nursing practice at an ever increasing rate. This study describes nurses perceptions and design preferences for these tools. This research is intended to inform successful design, implementation, and adoption of these emerging technologies.

Notes

This poster presentation was given at a virtual event. In lieu of a poster pdf file, this item record has an embedded video presentation. Scroll down to view/play.

Author Details

Ann Wieben, MS, BSN - School of Nursing, UW-Madison, Madison, WI, USA; Linsey M. Steege, PhD - School of Nursing, University of Wisconsin-Madison, Madison, WI, USA; Andrea Gilmore-Bykovskyi, PhD, RN - BerbeeWalsh Department of Emergency Medicine, UW-Madison, Madison, WI, USA

Sigma Membership

Beta Eta at-Large

Lead Author Affiliation

University of Wisconsin-Madison, Madison, Wisconsin, USA

Type

Poster

Format Type

Text-based Document, Video Recording

Study Design/Type

Descriptive/Correlational

Research Approach

Qualitative Research

Keywords:

Perceptions, Clinical Decision Support, Machine Learning

Conference Name

Creating Healthy Work Environments 2023

Conference Host

Sigma Theta Tau International

Conference Location

Virtual Event

Conference Year

2023

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Rights Holder

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All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Review Type

Abstract Review Only: Reviewed by Event Host

Acquisition

Proxy-submission

Additional Files

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Nurses' perceptions of machine learning clinical decision support: A descriptive aualitative study

Virtual Event

Machine Learning-driven decision support systems are being incorporated into nursing practice at an ever increasing rate. This study describes nurses perceptions and design preferences for these tools. This research is intended to inform successful design, implementation, and adoption of these emerging technologies.