Nurse staffing levels and hospital mortality in critical care settings: literature review and meta‐analysis

AIM: This paper reports a review of the literature on the association between critical care nurse staffing levels and patient mortality. BACKGROUND: Statistically significant inverse associations between levels of nurse staffing and hospital mortality have not been consistently found in the literature. Critical care settings are ideal to address this relationship due to high patient acuity and mortality, high intensity of the nursing care required, and availability of individual risk adjustment methods. METHODS: Major electronic databases were searched, including MEDLINE, EMBASE, and the Cumulative Index of Nursing and Allied Health Literature. The search terms included critical/intensive care, quality of health care, mortality/hospital mortality, personnel staffing and scheduling, and nursing staff (hospital). Only papers published in English were included. The original search was conducted in 2002 and updated in 2005. RESULTS: Nine studies were selected from 251 references screened. All nine were observational. Six were conducted in the United States of America, one in Austria, one in Brazil, and one in Scotland. The unadjusted risk ratio of nurse staffing (high vs. low) on hospital mortality were combined meta-analytically (five studies). The pooled estimate was 0.65 (95% confidence interval 0.47-0.91). However, after adjusting for various covariates within each study, the individually reported associations between high nurse staffing and low hospital mortality became non-significant in all but one study. CONCLUSION: The impact of nurse staffing levels on patients' hospital mortality in critical care settings was not evident in the reviewed studies. Methodological challenges that might have impeded correct assessment of the association include measurement problems in exposure status and confounding factors, often uncontrolled. The lack of association also indicates that hospital mortality may not be sensitive enough to detect the consequences of low nurse staffing levels in critical care settings.