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

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.

Validation and usability study of the framework for a user needs-centered mHealth app selection.

BACKGROUND: Most mHealth app users rely on an app's rankings, star ratings, or reviews, which may not reflect users' individual healthcare needs. To help healthcare providers, researchers, and users select an optimal mHealth app, the Method of App Selection based on User Needs (MASUN) 1.01 was developed and tested in prior research. Initial testing found the need for improvement. OBJECTIVE: This multiple-phase study aimed to simplify and improve MASUN 1.0, resulting in MASUN 2.0, and verify the feasibility and usability of MASUN 2.0. METHODS: This study was conducted in three phases: (1) modification of MASUN 1.0 to improve its importance, applicability, relevance, and clarity, in consultation with 21 experts in medical or nursing informatics; (2) validation of the draft MASUN 2.0, with 13 experts; and (3) feasibility testing of MASUN 2.0 and usability evaluation of the best app found through MASUN 2.0. Menstrual apps were used to test the framework. RESULTS: From Phases 1 and 2, MASUN 2.0, the framework for mHealth App selection, was derived with improved simplicity, usability, and applicability through a reduced number of tasks and time required. In Phase 3, after screening and scoring 2377 menstrual apps, five candidate apps were selected and evaluated by five clinical experts, five app experts, and five potential users. Finally, 194 users evaluated the usability of the app selected as the best. The best app helped users understand their health-related syndromes and patterns. Additionally, user-provided scores for impact, usefulness, and ease of use for the app were higher than for others. CONCLUSIONS: This study successfully modified MASUN 1.0 into MASUN 2.0 and verified MASUN 2.0 through content validity, feasibility, and usability testing. The selected apps through MASUN 2.0 helped health consumers more easily address health discomfort. Future research should extend this work to an automated system and different medical conditions with multiple stakeholders for digital health equity.

Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes: The 2019 Literature Year in Review.

Data science continues to be recognized and used within healthcare due to the increased availability of large data sets and advanced analytics. It can be challenging for nurse leaders to remain apprised of this rapidly changing landscape. In this article, we describe our findings from a scoping literature review of papers published in 2019 that use data science to explore, explain, and/or predict 15 phenomena of interest to nurses. Fourteen of the 15 phenomena were associated with at least one paper published in 2019. We identified the use of many contemporary data science methods (eg, natural language processing, neural networks) for many of the outcomes. We found many studies exploring Readmissions and Pressure Injuries. The topics of Artificial Intelligence/Machine Learning Acceptance, Burnout, Patient Safety, and Unit Culture were poorly represented. We hope that the studies described in this article help readers: (1) understand the breadth and depth of data science's ability to improve clinical processes and patient outcomes that are relevant to nurses and (2) identify gaps in the literature that are in need of exploration.

Effects of Reflective Practice on Baccalaureate Nursing Students' Stress, Anxiety and Competency: An Integrative Review.

BACKGROUND: Reflective practice affects all levels of nursing, including students, as well as practicing nurses. Self-reflective practice is a widespread concept in nursing; however, few empirical studies have demonstrated the possible effects of such a practice. The purpose of this integrative literature review was to identify evidence of the effects of self-reflective practice on baccalaureate-level nursing students, especially stress. METHODS: The literature search was conducted utilizing CINAHL and PubMed databases. The inclusion criteria were studies published between 2013 and 2018, articles that were peer-reviewed, written in English, and focused on nursing education of baccalaureate programs only. A total of 15 articles were reviewed. RESULTS: There is limited but growing evidence to suggest self-reflective practices have positive effects on baccalaureate-level nursing students. The self-reflective practices decreased stress and anxiety and increased learning, competency, and self-awareness of nursing practice. While written reflections were most commonly used in the studies, other forms of reflection, such as verbal and photography, were effective as well. LINKING EVIDENCE TO ACTION: Nursing students can benefit from incorporating reflection into the didactic and clinical settings. Nursing faculty are encouraged to integrate reflection into the nursing curriculum. Nurses within the first year of practice could benefit from using reflective practice as well. Experienced nurses and nurse managers can encourage and mentor novice nurses on the use and benefits of reflective practice.