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Nurse Staffing and Healthcare-Associated Infection, Unit-Level Analysis

Shang, Jingjing, PhD, RN; Needleman, Jack, PhD, FAAN; Liu, Jianfang, PhD; Larson, Elaine, PhD, RN, FAAN, CIC; Stone, Patricia W., PhD, RN, FAAN

JONA: The Journal of Nursing Administration: May 2019 - Volume 49 - Issue 5 - p 260–265
doi: 10.1097/NNA.0000000000000748
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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.

Author 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.

Funding was provided by Health Information Technology to Reduce Healthcare-Associated Infections R01NR010822 by the National Institute of Nursing Research.

The authors declare no conflicts of interest.

Correspondence: Dr Shang, 560 West 168th St, New York, NY 10032 (Js4032@columbia.edu).

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