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Description

This data-driven study of pain using nurse-generated Omaha System aimed to identify primary and secondary predictors of pain using machine learning techniques and examine the likelihood of having pain across the population based on most common predictors identified. This study demonstrated the potential for pain-related knowledge discovery using large nurse-generated datasets.

Learning Objective: 1.Understand the predictors of pain for cases who received nursing care in the community
2.Understand Omaha System, which is a multi-disciplinary terminology and ontology for health and healthcare

Authors:

Youjeong Kang (Presenter)
The University of Utah

Durga Sanugula, University of Minnesota
Kriti Bagdi, University of Minnesota
Robin Austin, University of Minnesota
Karen Monsen, University of Minnesota

Presentation Materials:

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