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 on 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; 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 healthcare. CONCLUSIONS: 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.
ABSTRACT
Objective: This article aims to explore care patterns and understand the impact of telehealth on nursing care in the radiation oncology setting at a comprehensive cancer center during the COVID-19 pandemic. Methods: Focus group interviews of radiation oncology nurses (n â= â18) were used to obtain data and describe current patient care patterns during the study period. Interviews were conducted over Zoom video conference, and content was analyzed. Results: Three major themes were determined: (1) the evolution of nurses' roles during the transition to telehealth, (2) the resilience of the human element, and (3) the benefits and constraints of the institution's infrastructure. Conclusions: Study results support radiation oncology nurses' ability to provide quality patient care using telehealth and can guide the expansion future care models for radiation oncology patients. Research exploring telehealth care outcomes among radiation patients is warranted. Radiation oncology nurses' training and scope of practice must be expanded to include telehealth care. As telehealth care models continue to develop, there will be a need to address training and technical disparities among certain patient demographics.