Abstract:
OBJECTIVE To investigate the relationship between nurse-to-patient ratios and hospital-acquired infections (HAIs) in the intensive care units, and to assess the impact of both average and maximum nurse-to-patient ratios on the risk of HAIs.
METHODS Data were obtained from the hospital information system (including Hospital Information System, nursing sensitive quality indicator monitoring system and hospital infection management system). Inpatients aged 18 years and older in ten intensive care units from 1 Jan. 2022 to 31 Dec. 2023 were included; data on the nurse-to-patient ratios during day shifts, night shifts and the overall period and HAIs cases were collected. Univariate test was conducted to compare differences between the infection group and the non-infection group. Logistic regression models were utilized to evaluate the association between various nurse-to-patient ratio indicators and the risk of HAIs while controlling the covariates.
RESULTS A total of 2 742 patients were included, with an HAIs incidence rate of 18.23%. The average patient-to-nurse ratio was significantly lower in the infection group than in the non-infection group (2.76±0.82 vs. 3.27±1.16, P < 0.001), whereas the maximum nurse-to-patient ratios for the overall period, day and night shifts were 3.57±1.09 (infected) vs. 3.91±1.31 (uninfected), 3.30±1.12 vs. 3.48±1.16, and 4.62±1.85 vs. 5.10±2.08, respectively (all P < 0.001). Regression analysis showed that no significant association between the average nurse-to-patient ratios for the overall period, day and night shifts and the risk of HAIs; whereas the odds ratios (ORs) for the maximum patient-to-nurse ratio greater than 4 were 2.122(1.355-3.324)for the overall period, 2.061(1.333-3.186)for the day shift and 1.495(1.055-2.118)for the night shifts (all nurse-to-patient ratios ≤3 in the reference group).
CONCLUSIONS The maximum nurse-to-patient ratios are important risk factors for HAIs in the intensive care units, whereas the average nurse-to-patient ratios are not significantly associated with HAIs. It is suggested that insufficient nursing resources during peak hours may increase the risk of infection, and optimizing the allocation of nursing care during peak hours will help to reduce the incidence of HAIs.