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Nurse Staffing and Healthcare-Associated Infection, Unit-Level Analysis
Jingjing Shang1, Jack Needleman, Jianfang Liu
1Author Affiliations: Associate Professor (Dr Shang), Assistant Professor of Quantitative Research (Dr Liu), Professor and Associate Dean for Research (Dr Larson), Professor and Director of Center for Health Policy (Dr Stone), School of Nursing, Columbia University, New York; and Professor and Chair (Dr. Needleman), Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, California.
Objective:
To examine whether healthcare-associated infections (HAIs) and nurse staffing are associated using unit-level staffing data.
Background:
Previous studies of the association between HAIs and nurse staffing are inconsistent and limited by methodological weaknesses.
Methods:
Cross-sectional data between 2007 and 2012 from a large urban hospital system were analyzed. HAIs were diagnosed using the Centers for Disease Control and Prevention's National Healthcare Safety Network definitions. We used Cox proportional-hazards regression model to examine the association of nurse staffing (2 days before HAI onset) with HAIs after adjusting for individual risks.
Results:
Fifteen percent of patient-days had 1 shift understaffed, defined as staffing below 80% of the unit median for a shift, and 6.2% had both day and night shifts understaffed. Patients on units with both shifts understaffed were significantly more likely to develop HAIs 2 days later.
Conclusions:
Understaffing is associated with increased risk of HAIs.
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