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Nurse Decision Making in Acute Care

Nibbelink, Christine W., PhD, RN; Carrington, Jane M., PhD, RN

CIN: Computers, Informatics, Nursing: March 2019 - Volume 37 - Issue 3 - p 151–160
doi: 10.1097/CIN.0000000000000521
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Effective nurse decision making is essential for best patient outcomes in the acute care nurse practice environment. The purpose of this study was to explore acute care RNs' perceptions of clinical decision making for a patient who experienced a clinical event. Clinical events include changes in patient condition and are manifested by fever, pain, bleeding, changes in output, changes in respiratory status, and changes in level of consciousness. Naturalistic decision making framework supported the exploration of important contextual factors associated with decision making, provided new information for nursing science, and served as the conceptual framework for this research. Data collected from interviews of 20 acute care nurses were analyzed using qualitative content analysis. The emergent categories included Awareness of Patient Status, Experience and Decision Making, Following Established Routine, Time Pressure, Teamwork/Support From Staff, Goals, Education, Resources, Patient Education, Consideration of Options to Meet Goals, and Nursing Roles. Acute care nurses incorporated a wide variety of complex factors when decision making. This study sought to improve understanding of the factors nurses found important to their decision making for the potential development of improved decision support in the electronic health record.

Author Affiliations: Department of Biomedical Informatics, University of California, San Diego (Dr Nibbelink); and College of Nursing, University of Arizona, Tucson (Dr Carrington).

This article is based on the first author's doctoral dissertation.

This publication was supported by the National Library of Medicine of the National Institutes of Health under award T15LM011271. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Christine W. Nibbelink, PhD, RN, Department of Biomedical Informatics, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093 (cnibbelink@ucsd.edu).

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