Publications by authors named "I A Kagan"
Background: The concept of 'EntrepreNursing' improves healthcare outcomes by enhancing quality, accessibility, and cost-effectiveness, but remains underutilized by clinical nurses. Research on how to promote EntrepreNursing is scant.
Purpose: To examine how personal characteristics (internal locus of control, capacity to innovate) and organizational innovativeness influence nurses' innovative behaviors.
Purpose: To investigate community-acquired pressure injuries (CAPIs) in older people by utilizing big data.
Design: Retrospective data curation and analysis of inpatient data from two general medical centers between 1 January 2016 and 31 December 2018.
Methods: Nursing assessments from 44,449 electronic medical records of patients admitted to internal medicine departments were retrieved, organized, coded by data engineers, and analyzed by data scientists.
Predictors of intention to stay in the profession among novice nurses: a cross-sectional study.
Isr J Health Policy Res
December 2024
Background: Preserving new graduate nurses in the profession is an essential step for addressing the nursing shortage and sustaining the future of the profession. This study aimed to examine the relationship between employment characteristics and job satisfaction of novice nurses and their willingness to stay in the nursing profession in the next 5 years.
Methods: Novice nurses' intention to stay in the profession was assessed, considering demographics, employment characteristics, and components of job satisfaction.
A positive-sense single-stranded RNA virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), caused the coronavirus disease 2019 (COVID-19) pandemic that devastated the world. While this is a respiratory virus, one feature of the SARS-CoV-2 infection was recognized to cause pathogenesis of other organs. Because the membrane fusion protein of SARS-CoV-2, the spike protein, binds to its major host cell receptor angiotensin-converting enzyme 2 (ACE2) that regulates a critical mediator of cardiovascular diseases, angiotensin II, COVID-19 is largely associated with vascular pathologies.
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- Acinetobacter baumanni infections are common and serious in ICUs, making early detection crucial for better patient outcomes.
- This study developed a Machine Learning prediction tool using data from nearly 20,000 ICU patients to identify those at risk for these infections.
- The tool showed moderate predictive ability, with key risk factors being respiratory function, metabolic issues, and antibiotic use, suggesting areas for improving prediction accuracy in the future.*