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Appl Clin Inform 2023; 14(03): 585-593
DOI: 10.1055/a-2088-2893
Review Article

Data Science Implementation Trends in Nursing Practice: A Review of the 2021 Literature

Ann M. Wieben
1   University of Wisconsin-Madison School of Nursing, Madison, Wisconsin, United States
,
Rachel Lane Walden
2   Annette and Irwin Eskind Family Biomedical Library, Vanderbilt University, Nashville, Tennessee, United States
,
Bader G. Alreshidi
3   Medical-Surgical Nursing Department, College of Nursing, University of Hail, Hail, Saudi Arabia
,
Sophia F. Brown
4   Walden University School of Nursing, Minneapolis, Minnesota
,
Kenrick Cato
5   Department of Emergency Medicine, Columbia University School of Nursing, New York, New York, United States
,
Cynthia Peltier Coviak
6   Kirkhof College of Nursing, Grand Valley State University, Allendale, Michigan, United States
,
Christopher Cruz
7   Global Health Technology and Informatics, Chevron, San Ramon, California, United States
,
Fabio D'Agostino
8   Department of Medicine and Surgery, Saint Camillus International University of Health Sciences, Rome, Italy
,
Brian J. Douthit
9   Department of Biomedical Informatics, United States Department of Veterans Affairs, Vanderbilt University, Nashville, Tennessee, United States
,
Thompson H. Forbes III
10   Department of Advanced Nursing Practice and Education, East Carolina University College of Nursing, Greenville, North Carolina, United States
,
Grace Gao
11   Atlanta VA Quality Scholars Program, Joseph Maxwell Cleland, Atlanta VA Medical Center, North Druid Hills, Georgia, United States
,
Steve G. Johnson
12   Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States
,
Mikyoung Angela Lee
13   Texas Woman's University College of Nursing, Denton, Texas, United States
,
Margaret Mullen-Fortino
14   Penn Presbyterian Medical Center, Philadelphia, Pennsylvania, United States
,
Jung In Park
15   Sue and Bill Gross School of Nursing, University of California, Irvine, United States
,
Suhyun Park
16   College of Nursing and College of Medicine, University of Florida, Gainesville, Florida, United States
,
Lisiane Pruinelli
16   College of Nursing and College of Medicine, University of Florida, Gainesville, Florida, United States
,
Anita Reger
,
Jethrone Role
17   Loma Linda University Health, Loma Linda, California, United States
,
Marisa Sileo
18   Boston Children's Hospital, Boston, Massachusetts, United States
,
Mary Anne Schultz
19   California State University, Long Beach, California, United States
,
Pankaj Vyas
20   University of Arizona College of Nursing, Tucson, Arizona, United States
,
Alvin D. Jeffery
21   U.S. Department of Veterans Affairs, Vanderbilt University School of Nursing, Tennessee Valley Healthcare System, Nashville, Tennessee, United States
› Author Affiliations Funding Dr. Jeffery received support for this work from the Agency for Healthcare Research and Quality and the Patient-Centered Outcomes Research Institute (grant no.: K12 HS026395); the Gordon and Betty Moore Foundation (grant no.: GBMF9048); as well as the resources and use of facilities at the Department of Veterans Affairs, Tennessee Valley Healthcare System.
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Abstract

Objectives The goal of this work was to provide a review of the implementation of data science-driven applications focused on structural or outcome-related nurse-sensitive indicators in the literature in 2021. By conducting this review, we aim to inform readers of trends in the nursing indicators being addressed, the patient populations and settings of focus, and lessons and challenges identified during the implementation of these tools.

Methods We conducted a rigorous descriptive review of the literature to identify relevant research published in 2021. We extracted data on model development, implementation-related strategies and measures, lessons learned, and challenges and stakeholder involvement. We also assessed whether reports of data science application implementations currently follow the guidelines of the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by AI (DECIDE-AI) framework.

Results Of 4,943 articles found in PubMed (NLM) and CINAHL (EBSCOhost), 11 were included in the final review and data extraction. Systems leveraging data science were developed for adult patient populations and were primarily deployed in hospital settings. The clinical domains targeted included mortality/deterioration, utilization/resource allocation, and hospital-acquired infections/COVID-19. The composition of development teams and types of stakeholders involved varied. Research teams more frequently reported on implementation methods than implementation results. Most studies provided lessons learned that could help inform future implementations of data science systems in health care.

Conclusion In 2021, very few studies report on the implementation of data science-driven applications focused on structural- or outcome-related nurse-sensitive indicators. This gap in the sharing of implementation strategies needs to be addressed in order for these systems to be successfully adopted in health care settings.

Keywords

data science - machine learning - nursing - prediction - implementation - deployment - pilot

Protection of Human and Animal Subjects

This research does not involve human subjects.


Supplementary Material



Publication History

Received: 29 November 2022

Accepted: 03 May 2023

Accepted Manuscript online:
07 May 2023

Article published online:
02 August 2023

© 2023. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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