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Douthit BJ, Walden RL, Cato K, Coviak CP, Cruz C, D'Agostino F, Forbes T, Gao G, Kapetanovic TA, Lee MA, Pruinelli L, Schultz MA, Wieben A, Jeffery AD. Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature. Appl Clin Inform 2022; 13:161-179. [PMID: 35139564 PMCID: PMC8828453 DOI: 10.1055/s-0041-1742218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
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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Affiliation(s)
- Brian J. Douthit
- 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
- Annette and Irwin Eskind Family Biomedical Library, Vanderbilt University, Nashville, Tennessee, United States
| | - Kenrick Cato
- Department of Emergency Medicine, Columbia University School of Nursing, New York, New York, United States
| | - Cynthia P. Coviak
- Professor Emerita of Nursing, Grand Valley State University, Allendale, Michigan, United States
| | - Christopher Cruz
- Global Health Technology and Informatics, Chevron, San Ramon, California, United States
| | - Fabio D'Agostino
- Department of Medicine and Surgery, Saint Camillus International University of Health Sciences, Rome, Italy
| | - Thompson Forbes
- College of Nursing, East Carolina University, Greenville, North California, United States
| | - Grace Gao
- Department of Nursing, St Catherine University, Saint Paul, Minnesota, United States
| | - Theresa A. Kapetanovic
- College of Nursing, East Carolina University, Greenville, North California, United States
| | - Mikyoung A. Lee
- College of Nursing, Texas Woman's University, Denton, Texas, United States
| | - Lisiane Pruinelli
- School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States
| | - Mary A. Schultz
- Department of Nursing, California State University, San Bernardino, California, United States
| | - Ann Wieben
- School of Nursing, University of Wisconsin-Madison, Wisconsin, United States
| | - Alvin D. Jeffery
- School of Nursing, Vanderbilt University; Tennessee Valley Healthcare System, U.S. Department of Veterans Affairs, Nashville, Tennessee, United States,Address for correspondence Alvin D. Jeffery, PhD, RN-BC, CCRN-K, FNP-BC 461 21st Avenue South, Nashville, TN 37240United States
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Qian J, Zhou T, Qiu BJ, Xiang L, Zhang J, Ning BT, Ren H, Li BR, Xia Q, Wang Y. Postoperative Risk Factors and Outcome of Patients With Liver Transplantation Who Were Admitted to Pediatric Intensive Care Unit: A 10-Year Single-Center Review in China. J Intensive Care Med 2019; 35:1241-1249. [PMID: 31088192 DOI: 10.1177/0885066619849558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
Abstract
INTRODUCTION The aim of this study was to present our 10-year experience of pediatric intensive care unit (PICU) management with pediatric liver recipients and to understand the importance of close interdisciplinary cooperation in 2 hospitals. METHODS A retrospective chart review study was performed according to our hospital's medical records and the pediatric liver transplant database of Renji hospital. RESULTS A total of 767 patients received liver transplantation (LT) performed in Renji hospital between October 2006 and December 2016, of which 97 of them were admitted to PICU in our center for various complications developed after transplantation. 8.8% (16/208) and 14.4% (81/559) of patients were transferred to PICU in stages I and II, respectively, and was comparable in the 2 stages (P = .017). The majority of patients was late postoperative children (median 185 post-LT days) in stage I. More patients were transferred to PICU directly in stage II. PICU admitted more younger (median 8.2 months) and early postoperative patients in stage II. The median length of PICU stay was 11.0 (6.0-20.5) days. The median length of mechanical ventilation was 5.0 (0.0-12.0) days. The most frequent complications were pulmonary complications (52 [53.6%] patients), surgical complications (22 [22.7%] patients), sepsis (7 [7.2%]), and other miscellaneous complications (16 [16.5%] patients). The overall 28-day PICU mortality was 25.8% (n = 25) and 64.0% (n = 16) of the deaths happened in the early postoperative period. There was significant difference concerning mortality in children with surgical complications and medical problems (54.5% [12/22] vs 17.3% [13/75], P = .001). Multivariate analysis by regression showed that the pediatric risk of mortality III score was the only independent prognostic factor (P = .031). CONCLUSIONS Multiple complications occur in children with LT. Although challenging, interdisciplinary cooperation between different hospitals is an effective mean to enable children to maximize the benefit gained from LT in China.
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Affiliation(s)
- Juan Qian
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Tao Zhou
- Department of Liver Surgery and Liver Transplantation, 71140Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Bi-Jun Qiu
- Department of Liver Surgery and Liver Transplantation, 71140Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Long Xiang
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Jian Zhang
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Bo-Tao Ning
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Hong Ren
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Bi-Ru Li
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Qiang Xia
- Department of Liver Surgery and Liver Transplantation, 71140Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Ying Wang
- Pediatric Intensive Care Unit, 71140Shanghai Children's Medical Center, School of Medicine, Shanghai Jiaotong University, Shanghai, People's Republic of China
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