Dataset Information

Determinants of healthcare worker turnover in intensive care units: A micro-macro multilevel analysis.

ABSTRACT:

Background

High turnover among healthcare workers is an increasingly common phenomenon in hospitals worldwide, especially in intensive care units (ICUs). In addition to the serious financial consequences, this is a major concern for patient care (disrupted continuity of care, decreased quality and safety of care, increased rates of medication errors, …).

Objective

The goal of this article was to understand how the ICU-level nurse turnover rate may be explained from multiple covariates at individual and ICU-level, using data from 526 French registered and auxiliary nurses (RANs).

Methods

A cross-sectional study was conducted in ICUs of Paris-area hospitals in 2013. First, we developed a small extension of a multi-level modeling method proposed in 2007 by Croon and van Veldhoven and validated its properties using a comprehensive simulation study. Second, we applied this approach to explain RAN turnover in French ICUs.

Results

Based on the simulation study, the approach we proposed allows to estimate the regression coefficients with a relative bias below 7% for group-level factors and below 12% for individual-level factors. In our data, the mean observed RAN turnover rate was 0.19 per year (SD = 0.09). Based on our results, social support from colleagues and supervisors as well as long durations of experience in the profession were negatively associated with turnover. Conversely, number of children and impossibility to skip a break due to workload were significantly associated with higher rates of turnover. At ICU-level, number of beds, presence of intermediate care beds (continuous care unit) in the ICU and staff-to-patient ratio emerged as significant predictors.

Conclusions

The findings of this research may help decision makers within hospitals by highlighting major determinants of turnover among RANs. In addition, the new approach proposed here could prove useful to researchers faced with similar micro-macro data.

SUBMITTER: Daouda OS

PROVIDER: S-EPMC8121288 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Healthcare-associated infections (HAIs) represent serious complications for patients within pediatric cardiac intensive care units (CICU). HAIs are associated with increased morbidity, mortality and resource utilization. There are few studies describing the epidemiology of HAIs across the entire spectrum of patients (surgical and nonsurgical) receiving care in dedicated pediatric CICUs. METHODS:Retrospective analyses of 22,839 CICU encounters from October 2013 to September 2016 across 22 North American CICUs contributing data to the Pediatric Cardiac Critical Care Consortium clinical registry. RESULTS:HAIs occurred in 2.4% of CICU encounters at a rate of 3.3 HAIs/1000 CICU days, with 73% of HAIs occurring in children <1 year. Eighty encounters (14%) had ≥2 HAIs. Aggregate rates for the 4 primary HAIs are as follows: central line-associated blood stream infection, 1.1/1000 line days; catheter-associated urinary tract infections, 1.5/1000 catheter days; ventilator-associated pneumonia, 1.9/1000 ventilator days; surgical site infections, 0.81/100 operations. Surgical and nonsurgical patients had similar HAIs rates/1000 CICU days. Incidence was twice as high in surgical encounters and increased with surgical complexity; postoperative infection occurred in 2.8% of encounters. Prematurity, younger age, presence of congenital anomaly, Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories (STAT) 4-5 surgery, admission with an active medical condition, open sternum and extracorporeal membrane oxygenation were independently associated with HAIs. In univariable analysis, HAI was associated with longer hospital length of stay and durations of urinary catheter, central venous catheter and ventilation. Mortality was 24.4% in patients with HAIs versus 3.4% in those without, P < 0.0001. CONCLUSIONS:We provide comprehensive multicenter benchmark data regarding rates of HAIs within dedicated pediatric CICUs. We confirm that although rare, HAIs of all types are associated with significant resource utilization and mortality.