Literature DB >> 28376546

Association of Nursing Overtime, Nurse Staffing, and Unit Occupancy with Health Care-Associated Infections in the NICU.

Marc Beltempo1, Régis Blais2, Guy Lacroix3, Michèle Cabot4, Bruno Piedboeuf4.   

Abstract

Objective This study aims to assess the association of nursing overtime, nurse staffing, and unit occupancy with health care-associated infections (HCAIs) in the neonatal intensive care unit (NICU). Study Design A 2-year retrospective cohort study was conducted for 2,236 infants admitted in a Canadian tertiary care, 51-bed NICU. Daily administrative data were obtained from the database "Logibec" and combined to the patient outcomes database. Median values for the nursing overtime hours/total hours worked ratio, the available to recommended nurse staffing ratio, and the unit occupancy rate over 3-day periods before HCAI were compared with days that did not precede infections. Adjusted odds ratios (aOR) that control for the latter factors and unit risk factors were also computed. Results A total of 122 (5%) infants developed a HCAI. The odds of having HCAI were higher on days that were preceded by a high nursing overtime ratio (aOR, 1.70; 95% confidence interval [95% CI], 1.05-2.75, quartile [Q]4 vs. Q1). High unit occupancy rates were not associated with increased odds of infection (aOR, 0.85; 95% CI, 0.47-1.51, Q4 vs. Q1) nor were higher available/recommended nurse ratios (aOR, 1.16; 95% CI, 0.67-1.99, Q4 vs. Q1). Conclusion Nursing overtime is associated with higher odds of HCAI in the NICU. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

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Year:  2017        PMID: 28376546     DOI: 10.1055/s-0037-1601459

Source DB:  PubMed          Journal:  Am J Perinatol        ISSN: 0735-1631            Impact factor:   1.862


  3 in total

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Authors:  Sung-Heui Bae; Mom Pen; Chommrath Sinn; Sokry Kol; Bomi An; Sook Ja Yang; Hyang-Yon Rhee; Jaeyoung Ha; Suhyun Bae
Journal:  Int Nurs Rev       Date:  2021-10-02       Impact factor: 3.384

2.  Assessment of Time-Series Machine Learning Methods for Forecasting Hospital Discharge Volume.

Authors:  Thomas H McCoy; Amelia M Pellegrini; Roy H Perlis
Journal:  JAMA Netw Open       Date:  2018-11-02

3.  South Korean nurses' lived experiences supporting maternal postpartum bonding in the neonatal intensive care unit.

Authors:  Sun Young You; Ah Rim Kim
Journal:  Int J Qual Stud Health Well-being       Date:  2020-12
  3 in total

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