Nurse staffing and postsurgical adverse events: an analysis of administrative data from a sample of U.S. hospitals, 1990-1996
- PMID: 12132597
- PMCID: PMC1434654
- DOI: 10.1111/1475-6773.00040
Nurse staffing and postsurgical adverse events: an analysis of administrative data from a sample of U.S. hospitals, 1990-1996
Abstract
Objective: To examine the impact of nurse staffing on selected adverse events hypothesized to be sensitive to nursing care between 1990 and 1996, after controlling for hospital characteristics.
Data sources/study setting: The yearly cross-sectional samples of hospital discharges for states participating in the National Inpatient Sample (NIS) from 1990-1996 were combined to form the analytic sample. Six states were included for 1990-1992, four states were added for the period 1993-1994, and three additional states were added in 1995-1996.
Study design: The study design was cross-sectional descriptive.
Data collection/extraction methods: Data for patients aged 18 years and older who were discharged between 1990 and 1996 were used to create hospital-level adverse event indicators. Hospital-level adverse event data were defined by quality indicators developed by the Health Care Utilization Project (HCUP). These data were matched to American Hospital Association (AHA) data on community hospital characteristics, including registered nurse (RN) and licensed practical/vocational nurse (LPN) staffing hours, to examine the relationship between nurse staffing and four postsurgical adverse events: venous thrombosis/pulmonary embolism, pulmonary compromise after surgery, urinary tract infection, and pneumonia. Multivariate modeling using Poisson regression techniques was used.
Principal findings: An inverse relationship was found between RN hours per adjusted inpatient day and pneumonia (p < .05) for routine and emergency patient admissions.
Conclusions: The inverse relationship between pneumonia and nurse staffing are consistent with previous findings in the literature. The results provide additional evidence for health policy makers to consider when making decisions about required staffing levels to minimize adverse events.
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