Consistently Exploring Nurse Staffing and Neurocritical Care Unit Turnover.

ABSTRACT: BACKGROUND: Staffing models within nursing units have long been a hot topic of discussion. The COVID-19 pandemic exacerbated this discussion by straining the national nursing environment and workforce. Before the pandemic, the neuroscience intensive care unit (NSICU) primarily used an acuity-adjusted staffing model and aimed for a nurse-to-patient ratio of 1:1.5. During and after the pandemic, the NSICU was forced to primarily use a centralized staffing model because of the increased turnover in the hospital at large and a rise in patient census. METHODS : Unit census data in an NSICU were tracked before, during, and after the pandemic alongside utilization of a centralized staffing model in the hospital at large. RESULTS : During this time, the NSICU saw a statistically significant increase in average nurse-to-patient ratio and incidences of both floating and tripled assignments. The NSICU simultaneously saw a 180% increase in nursing turnover. CONCLUSION : Although we cannot prove that a centralized staffing model is directly responsible for higher nursing turnover, its utilization led to greater incidence of poor staffing-reflected in deviation from the nurse-to-patient ratio goal of the unit. Nurse staffing concerns play a large role in nurse satisfaction in the workforce: staffing shortages have been described both as a precursor to and as a consequence of increased nursing turnover.

Reflections on Nursing Ingenuity During the COVID-19 Pandemic.

INTRODUCTION: This reflections article provides insight toward nursing innovations to reduce the overuse of personal protective equipment while maintaining a safe environment for staff taking care of COVID-19 patients. The secondary aim of this article to capitalize on recent advances in mass electronic communication through social media to encourage nurses across the globe to share their knowledge and expertise during this pandemic. INNOVATIONS: The many innovations that have been implemented fall into 3 categories of reducing unnecessary use of personal protective equipment, promoting staff safety and readiness, and reducing foot traffic. SUMMARY: These strategies are being shared to promote dissemination of innovative nursing interventions that will save lives during the COVID-19 pandemic.

Establishing Normative Data for Pupillometer Assessment in Neuroscience Intensive Care: The "END-PANIC" Registry.

BACKGROUND: Trained medical practitioners have been assessing the pupillary light reflex for more than 2 millennia. However, the interrater reliability of the pupillary light reflex remains low. To overcome the drawbacks of a subjective interpretation of pupillary size and reactivity, automated pupillometers are becoming increasingly commonplace, but practitioners do not have adequate data from which to judge whether the numerical values provided by the pupillometer are "within reference limits." METHODS: This article details the methods used to create an extensive database of automated pupillometer readings and associated patient data (eg, intracranial pressure). DISCUSSION/CONCLUSIONS: The "Establishing Normative Data for Pupillometer Assessments in Neuroscience Intensive Care" Registry will provide a large data set of pupillary size, reactivity, and speed of contraction in a cohort of patients admitted to a neuroscience intensive care unit with a variety of conditions. Analysis of this data set will help establish normative data for pupillometer readings for neurologically impaired patients. Exploratory analysis of this data set may also provide preliminary hypothesis generating data for future prospective studies on pupillary findings and trends in acute neurological conditions.