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

Author

Wieben, Ann, Walden, Rachel, Alreshidi, Bader, Brown, Sophia, Cato, Kenrick, Coviak, Cynthia, Cruz, Christopher, DAgostino, Fabio, Douthit, Brian, Forbes, Thompson, Gao, Grace, Johnson, Steve, Lee, Mikyoung, Mullen-Fortino, Margaret, Park, Jung In, Park, Suhyun, Pruinelli, Lisiane, Reger, Anita, Role, Jethrone, Sileo, Marisa, Schultz, Mary, Vyas, Pankaj, and Jeffery, Alvin

Subjects
Adult, Humans, Data Science, COVID-19, Delivery of Health Care
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.

Published
2023

11. Reinforcement Learning of Graph Neural Networks for Service Function Chaining

Author

Heo, DongNyeong, Lee, Doyoung, Kim, Hee-Gon, Park, Suhyun, and Choi, Heeyoul

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture
Abstract

In the management of computer network systems, the service function chaining (SFC) modules play an important role by generating efficient paths for network traffic through physical servers with virtualized network functions (VNF). To provide the highest quality of services, the SFC module should generate a valid path quickly even in various network topology situations including dynamic VNF resources, various requests, and changes of topologies. The previous supervised learning method demonstrated that the network features can be represented by graph neural networks (GNNs) for the SFC task. However, the performance was limited to only the fixed topology with labeled data. In this paper, we apply reinforcement learning methods for training models on various network topologies with unlabeled data. In the experiments, compared to the previous supervised learning method, the proposed methods demonstrated remarkable flexibility in new topologies without re-designing and re-training, while preserving a similar level of performance., Comment: 5 pages, 2 figures

Published
2020

13. An Empirical Analysis of Complementary and Integrative Health Therapy Documentation in the Electronic Health Record

Author

Austin, Robin R., Lu, Sheng-Chieh, Jantraporn, Ratchada, Park, Suhyun, Geiger-Simpson, Elena, Kreitzer, MaryJo, Koithan, Mary, and Delaney, Connie White

Subjects
United States. National Institutes of Health -- Analysis -- International economic relations, Medical records -- Usage -- Analysis, Electronic records -- Usage, Evidence-based medicine -- Analysis -- Usage, Information management -- Analysis -- Usage, Information accessibility, Health care industry, University of Minnesota
Abstract

This study examined complementary and integrative health therapy documentation in electronic health records (EHRs) using flowsheet artifacts from Epic UserWeb Library. The use of therapies has continued to expand, yet there is limited knowledge of the documentation of complementary and integrative health therapies in EHRs. Keywords: integrative therapies, SNOMED CT, electronic health record, standardized terminology, The use of complementary and integrative health (CIH) therapies, also known as nonpharmacological therapies, has continued to increase in patients in clinical settings (Black et al., 2015; Clarke et al., [...]

Published
2023

29. Fecal Calprotectin in Patients with Crohn's Disease: A Study Based on the History of Bowel Resection and Location of Disease.

Author

Seo, Jeongkuk, Song, Subin, Shin, Seung Hwan, Park, Suhyun, Hong, Seung Wook, Park, Sang Hyoung, Yang, Dong-Hoon, Ye, Byong Duk, Byeon, Jeong-Sik, Myung, Seung-Jae, Yang, Suk-Kyun, and Hwang, Sung Wook

Subjects
CROHN'S disease, INTESTINAL diseases, CALPROTECTIN, SMALL intestine, MAGNETIC resonance
Abstract

Fecal calprotectin (FC) is commonly used to assess Crohn's disease (CD) activity. However, standardized cut-off values accounting for bowel resection history and disease location are lacking. In this study, we analyzed data from patients with CD who underwent magnetic resonance enterography, ileocolonoscopy, and FC measurements from January 2017 to December 2018. In 267 cases from 254 patients, the FC levels in the 'operated' patients were higher when the disease was active compared with those who were in the remission group (178 vs. 54.7 μg/g; p < 0.001), and similar findings were obtained for the 'non-operated' patients (449.5 vs. 40.95 μg/g; p < 0.001). The FC levels differed significantly according to the location of inflammation, with lower levels in the small bowel compared to those in the colon. The FC cut-off levels of 70.8 μg/g and 142.0 μg/g were considered optimal for predicting active disease for operated and non-operated patients, respectively. The corresponding FC cut-off levels of 70.8 μg/g and 65.0 μg/g were observed for patients with disease only in the small bowel. In conclusion, different FC cut-off values would be applicable to patients with CD based on their bowel resection history and disease location. Tight control with a lower FC target may benefit those with a history of bowel resection or small-bowel-only disease. [ABSTRACT FROM AUTHOR]

Published
2024
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