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 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.

A Predictive Model for Developing Long- Term Opioid Use After Neurosurgery and Orthopedic Surgery

This study aimed to identify patient characteristics that predict long-term opioid use after an orthopedic or neurosurgery procedure. Long-term opioid use was defined as opioid use for 90 or more days following the surgical procedure. A retrospective analysis was conducted of orthopedic and neurosurgery patients 18 years and older from 01/01/2011 through 12/31/2017 (n = 12,301). Characteristics included age, sex, race, length of hospital stay, body mass index, surgical procedure specialty, presence of opioid use before and after surgery, and opioid use 90 days or more after surgery. A multiple logistic regression model was used to model characteristics predictive of long-term use of opioids. In this cohort, 32.0% of patients had prescriptions for opioids 90 or more days after surgery. Statistically significant risk factors for long-term opioid use were being Caucasian, younger (18-25 years age group) or older than age 45 and being obese. People who were African American or Black, in the 25-45 years age group, underweight, and used opioids before surgery were less likely to use opioids 90 days after surgery. Nurse anesthetist awareness of predictive characteristics of long-term opioid use can lead to alternative options to prevent opioid abuse.

Emergency Remote Learning in Nursing Education During the COVID-19 Pandemic.

Due to the corona (COVID-19) pandemic, several countries are currently conducting non-face-to-face education. Therefore, teachers of nursing colleges have been carrying out emergency remote education. This study developed a questionnaire to understand the status of Emergency Remote Learning (ERL) in nursing education internationally, translated it into 7 languages, and distributed it to 18 countries. A total of 328 nursing educators responded, and the most often used online methods were Social networking technology such as Facebook, Google+ and Video sharing platform such as YouTube. The ERL applied to nursing education was positively evaluated as 3.59 out of 5. The results of the study show that during the two semesters nursing college professors have well adapted to this unprecedent crisis of teaching. The world after COVID-19 has become a completely different place, and nursing education should be prepared for 'untact' education.