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Appl Clin Inform 2022; 13(01): 161-179
DOI: 10.1055/s-0041-1742218
Review Article

Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature

Brian J. Douthit
1   Tennessee Valley Healthcare System, U.S. Department of Veterans Affairs; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Rachel L. Walden
2   Annette and Irwin Eskind Family Biomedical Library, Vanderbilt University, Nashville, Tennessee, United States
,
Kenrick Cato
3   Department of Emergency Medicine, Columbia University School of Nursing, New York, New York, United States
,
Cynthia P. Coviak
4   Professor Emerita of Nursing, Grand Valley State University, Allendale, Michigan, United States
,
Christopher Cruz
5   Global Health Technology and Informatics, Chevron, San Ramon, California, United States
,
Fabio D'Agostino
6   Department of Medicine and Surgery, Saint Camillus International University of Health Sciences, Rome, Italy
,
Thompson Forbes
7   College of Nursing, East Carolina University, Greenville, North California, United States
,
Grace Gao
8   Department of Nursing, St Catherine University, Saint Paul, Minnesota, United States
,
Theresa A. Kapetanovic
9   College of Nursing, East Carolina University, Greenville, North California, United States
,
Mikyoung A. Lee
10   College of Nursing, Texas Woman's University, Denton, Texas, United States
,
Lisiane Pruinelli
11   School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States
,
Mary A. Schultz
12   Department of Nursing, California State University, San Bernardino, California, United States
,
Ann Wieben
13   School of Nursing, University of Wisconsin-Madison, Wisconsin, United States
,
Alvin D. Jeffery
14   School of Nursing, Vanderbilt University; Tennessee Valley Healthcare System, U.S. Department of Veterans Affairs, Nashville, Tennessee, United States
› Institutsangaben Funding This study was funded by the Agency for Healthcare Research and Quality and the Patient-Centered Outcomes Research Institute (grant: K12 HS026395) as well as the resources and use of facilities at the Department of Veterans Affairs, Tennessee Valley Healthcare System.
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Abstract

Background The term “data science” encompasses several methods, many of which are considered cutting edge and are being used to influence care processes across the world. Nursing is an applied science and a key discipline in health care systems in both clinical and administrative areas, making the profession increasingly influenced by the latest advances in data science. The greater informatics community should be aware of current trends regarding the intersection of nursing and data science, as developments in nursing practice have cross-professional implications.

Objectives This study aimed to summarize the latest (calendar year 2020) research and applications of nursing-relevant patient outcomes and clinical processes in the data science literature.

Methods We conducted a rapid review of the literature to identify relevant research published during the year 2020. We explored the following 16 topics: (1) artificial intelligence/machine learning credibility and acceptance, (2) burnout, (3) complex care (outpatient), (4) emergency department visits, (5) falls, (6) health care–acquired infections, (7) health care utilization and costs, (8) hospitalization, (9) in-hospital mortality, (10) length of stay, (11) pain, (12) patient safety, (13) pressure injuries, (14) readmissions, (15) staffing, and (16) unit culture.

Results Of 16,589 articles, 244 were included in the review. All topics were represented by literature published in 2020, ranging from 1 article to 59 articles. Numerous contemporary data science methods were represented in the literature including the use of machine learning, neural networks, and natural language processing.

Conclusion This review provides an overview of the data science trends that were relevant to nursing practice in 2020. Examinations of such literature are important to monitor the status of data science's influence in nursing practice.

Keywords

data analytics - artificial intelligence - nursing research - outcome and process assessment

Protection of Human and Animal Subject

This research does not involve human subjects.


Supplementary Material



Publikationsverlauf

Eingereicht: 24. Juni 2021

Angenommen: 12. Dezember 2021

Artikel online veröffentlicht:
09. Februar 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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