scholarly journals Acuity, nurse staffing and workforce, missed care and patient outcomes: A cluster‐unit‐level descriptive comparison

2020 ◽  
Vol 28 (8) ◽  
pp. 2216-2229
Author(s):  
Maria‐Eulàlia Juvé‐Udina ◽  
Maribel González‐Samartino ◽  
Maria Magdalena López‐Jiménez ◽  
Maria Planas‐Canals ◽  
Hugo Rodríguez‐Fernández ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Nurse Staffing ◽  
Unit Level ◽  
Missed Care ◽  
Cluster Unit

Impact of California’s Licensed Nurse-Patient Ratios on Unit-Level Nurse Staffing and Patient Outcomes

2005 ◽  
Vol 6 (3) ◽  
pp. 198-210 ◽  
Author(s):  
Nancy Donaldson ◽  
Linda Burnes Bolton ◽  
Carolyn Aydin ◽  
Diane Brown ◽  
Janet D. Elashoff ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Nurse Staffing ◽  
Unit Level

scholarly journals The impact of nurse staffing methodologies on nurse and patient outcomes: A systematic review

2021 ◽  
Author(s):  
Diane E. Twigg ◽  
Lisa Whitehead ◽  
Gemma Doleman ◽  
Sonia El‐Zaemey
Keyword(s):  
Systematic Review ◽  
Patient Outcomes ◽  
Nurse Staffing ◽  
The Impact

scholarly journals Patient Outcomes After the Introduction of Statewide ICU Nurse Staffing Regulations*

2018 ◽  
Vol 46 (10) ◽  
pp. 1563-1569 ◽  
Author(s):  
Anica C. Law ◽  
Jennifer P. Stevens ◽  
Samuel Hohmann ◽  
Allan J. Walkey
Keyword(s):  
Patient Outcomes ◽  
Nurse Staffing

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

2017 ◽  
Vol 34 (10) ◽  
pp. 0996-1002 ◽  
Author(s):  
Régis Blais ◽  
Guy Lacroix ◽  
Michèle Cabot ◽  
Bruno Piedboeuf ◽  
Marc Beltempo
Keyword(s):  
Health Care ◽  
Patient Outcomes ◽  
Retrospective Cohort ◽  
Neonatal Intensive Care ◽  
Tertiary Care ◽  
Nurse Staffing ◽  
Occupancy Rate ◽  
Staffing Ratio ◽  
Health Care Associated Infections ◽  
Occupancy Rates

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.

Why Causal Inference Matters to Nurses: The Case of Nurse Staffing and Patient Outcomes

2016 ◽  
Vol 21 (2) ◽  
Author(s):  
Deena Costa ◽  
Olga Yakusheva
Keyword(s):  
Causal Inference ◽  
Patient Outcomes ◽  
Nurse Staffing ◽  
Future Research ◽  
Nursing Research ◽  
Cross Sectional ◽  
Meaningful Improvement ◽  
Causal Pathways ◽  
Causal Pathway ◽  
Study Designs

Since the early 1990s researchers have steadily built a broad evidence base for the association between nurse staffing and patient outcomes. However, the majority of the studies in the literature employ designs that are unable to robustly examine causal pathways to meaningful improvement in patient outcomes. A focus on causal inference is essential to moving the field of nursing research forward, and as part of the essential skill-set for all nurses as consumers of research. In this article, we aim to describe the importance of causal inference in nursing research and discuss study designs that are more likely to produce causal findings. We first review the conceptual framework supporting this discussion and then use selected examples from the literature, typifying three key study designs – cross-sectional, longitudinal, and randomized control trials (RCTs). The discussion will illustrate strengths and limitation of existing evidence, focusing on the causal pathway between nurse staffing and outcomes. The article conclusion considers implications for future research.

Nurse Staffing and Patient Outcomes

2003 ◽  
Vol 23 (1) ◽  
pp. 14-15 ◽  
Author(s):  
Grif Alspach
Keyword(s):  
Patient Outcomes ◽  
Nurse Staffing
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