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Review
. 2022 Jan;13(1):161-179.
doi: 10.1055/s-0041-1742218. Epub 2022 Feb 9.

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

Brian J Douthit  1 , Rachel L Walden  2 , Kenrick Cato  3 , Cynthia P Coviak  4 , Christopher Cruz  5 , Fabio D'Agostino  6 , Thompson Forbes  7 , Grace Gao  8 , Theresa A Kapetanovic  7 , Mikyoung A Lee  9 , Lisiane Pruinelli  10 , Mary A Schultz  11 , Ann Wieben  12 , Alvin D Jeffery  13
Affiliations
Review

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

Brian J Douthit et al. Appl Clin Inform. 2022 Jan.

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.

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Conflict of interest statement

None declared.

Figures

Fig. 1
Fig. 1
Twelve most frequent predictor variables among the data science literature relating to nursing practice.
Fig. 2
Fig. 2
Use of methods among the data science literature relating to nursing practice.
See this image and copyright information in PMC

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References

    1. Johnson K E, McMorris B J, Raynor L A, Monsen K A. What big size you have! Using effect sizes to determine the impact of public health nursing interventions. Appl Clin Inform. 2013;4(03):434–444. - PMC - PubMed
    1. Roosan D, Del Fiol G, Butler J. Feasibility of population health analytics and data visualization for decision support in the infectious diseases domain: a pilot study. Appl Clin Inform. 2016;7(02):604–623. - PMC - PubMed
    1. Zhou Y, Zhao L, Zhou N. Predictive big data analytics using the UK biobank data. Sci Rep. 2019;9(01):6012. - PMC - PubMed
    1. Center for Nursing Informatics 2019 Nursing Knowledge: Big Data Science ConferenceAccessed December 24, 2021 at:https://nursing.umn.edu/centers/center-nursing-informatics/previous-conf...
    1. Grant M J, Booth A. A typology of reviews: an analysis of 14 review types and associated methodologies. Health Info Libr J. 2009;26(02):91–108. - PubMed

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