Critical care staffing ratio and outcome of COVID-19 patients requiring intensive care unit admission during the first pandemic wave: a retrospective analysis across Switzerland from the RISC-19-ICU observational cohort

Background The modifications to the standard intensive care unit (ICU) organization that had to be urgently implemented worldwide to overcome the surge of ICU admissions due to patients with a severe coronavirus disease 2019 (COVID-19) have resulted in increased workload and patients-to-nurse ratio. The aim of this study was to investigate whether level of critical care staffing could be associated with an increased risk of ICU mortality (primary endpoint), length of stay, mechanical ventilation and the evolution of disease (secondary study endpoints) in critically ill patients with COVID-19. Methods Retrospective multicenter analysis of the international Risk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry that prospectively enrolls patients developing critical illness due to COVID-19 in several countries worldwide. The analysis was limited to the period between March 1st, 2020 and May 31st, 2020, to ICUs in Switzerland that have collected additional data on nurse and physician staffing. Hierarchical regression models were used to investigate crude and adjusted effects of critical care staffing ratio on study endpoints. We adjusted for diseases severity and weekly caseload. Results Among the 38 Swiss participating ICUs, 17 recorded critical care staffing information. The study population included 437 patients and 2342 daily assessments of patient-to-nurse/physician ratio. Median of daily patient-to-nurse ratio started at 1.0 ([IQR] 0.5–1.5; calendar week 9) and peaked at 2.4 (IQR 0.4-2.0; calendar week 16), while the median of daily patient-to-physician ratio started at 4.0 (IQR 2.1-5.0; calendar week 9) and peaked at 6.8 (IQR 6.3–7.3; calendar week 19). Neither the patient-to-nurse ratio [adjusted Odds Ratio (OR) 1.28, 95% confidence interval (CI) 0.85–1.94; doubling of ratio] nor the patient-to-physician ratio [adjusted OR 1.08, 95% CI 0.87–1.32; doubling of ratio] was associated with ICU mortality. We found no association of critical care staffing on the investigated secondary study endpoints in adjusted models. COnclusion The Swiss health care system successfully overcame the first wave of the COVID-19 pandemic with regards to the unprecedented demand for ICU treatments. The reduced availability of critical care staffing resources per critically ill patient in Swiss ICUs did not translate in an overall increased risk of mortality.

Association of Nursing Overtime, Nurse Staffing, and Unit Occupancy with Health Care–Associated Infections in the NICU

Objective This study aims to assess the association of nursing overtime, nurse staffing, and unit occupancy with health care–associated infections (HCAIs) in the neonatal intensive care unit (NICU). Study Design A 2-year retrospective cohort study was conducted for 2,236 infants admitted in a Canadian tertiary care, 51-bed NICU. Daily administrative data were obtained from the database “Logibec” and combined to the patient outcomes database. Median values for the nursing overtime hours/total hours worked ratio, the available to recommended nurse staffing ratio, and the unit occupancy rate over 3-day periods before HCAI were compared with days that did not precede infections. Adjusted odds ratios (aOR) that control for the latter factors and unit risk factors were also computed. Results A total of 122 (5%) infants developed a HCAI. The odds of having HCAI were higher on days that were preceded by a high nursing overtime ratio (aOR, 1.70; 95% confidence interval [95% CI], 1.05–2.75, quartile [Q]4 vs. Q1). High unit occupancy rates were not associated with increased odds of infection (aOR, 0.85; 95% CI, 0.47–1.51, Q4 vs. Q1) nor were higher available/recommended nurse ratios (aOR, 1.16; 95% CI, 0.67–1.99, Q4 vs. Q1). Conclusion Nursing overtime is associated with higher odds of HCAI in the NICU.

Abstract WP409: Impact of Nursing Expertise and Staffing Ratio on Compliance with Post-tPA/Endovascular Patient Monitoring

Introduction: In 2014, the Post-tPA/Endovascular nursing monitoring flow sheet was revised to harmonize with the NIHSS exam. The challenges to performance and documentation compliance posed by the intensity and frequency of assessments have been the focus of an ongoing quality improvement initiative. Methods: All Post-tPA/Endovascular monitoring flow sheets from June 2014- June 2016 at University Hospitals Case Medical Center were reviewed for presence of neurologic assessments, vital signs, and management of hypertension per protocol. Stroke staff conducted in-services on the enhanced assessments and modified NIHSS training and house staff mentored bedside RNs in performing the NIHSS. A tip sheet was developed for staff on the modified NIHSS and real time feedback was given on all outliers. Results: Of 459 patients, compliance with all of the 684 monitoring data points ranged from 67-100% in the Neuroscience ICU (Patient: RN ratio 2:1), 75-100% in the Neuro-Intermediate Unit (Patient: RN ratio 3:1) and 40-100% in the Emergency Department (Patient: RN ratio 4:1). Overall compliance to > 95% of data points was seen in all but 5 patients with missing flow sheets. Symptomatic hemorrhagic complications after IVtPA decreased from 6.5% to 2.7%. Root-cause analysis of missing data points revealed seven areas of opportunity: Interference by diagnostic testing (29%), during patient transportation (22%), and following endovascular treatment (15%) or due to travelling RNs (8%). Missing documentation was most frequent during the q15 minute phase due to the intensity of monitoring (11%)- with the Emergency Department the most vulnerable location- and less during the q30 minute (4%) or q1 hour (3%) assessments. Units with dedicated neuroscience nursing adjusted more rapidly to the revision compared to units that do not routinely perform such assessments. Conclusions: Optimum compliance with nursing assessments and monitoring occur when there is no interference with diagnostic testing or procedures, the patient needs were a high priority and the patient acuity was well matched to the RN staffing ratio. This data supports a care model where a neuroscience trained RN nurse transitions with the patient during the first 24 hours after tPA/Endovascular therapy.

Assessing Occupancy and Its Relation to Healthcare-Associated Infections

Occupancy has been associated with risk for healthcare-associated infections, yet its definition varies widely. Occupancy can be modeled as a function of census, acuity of the patient care unit, staffing ratio, or some combination. This article discusses the appropriate parameterization of these measures and how to interpret their impact.Infect Control Hosp Epidemiol 2016:1–3