Nurse staffing and patient outcomes: Strengths and limitations of the evidence to inform policy and practice. A review and discussion paper based on evidence reviewed for the National Institute for Health and Care Excellence Safe Staffing guideline development

Abstract Clinical question What is the role of drugs in preventing covid-19? Why does this matter? There is widespread interest in whether drug interventions can be used for the prevention of covid-19, but there is uncertainty about which drugs, if any, are effective. The first version of this living guideline focuses on the evidence for hydroxychloroquine. Subsequent updates will cover other drugs being investigated for their role in the prevention of covid-19. Recommendation The guideline development panel made a strong recommendation against the use of hydroxychloroquine for individuals who do not have covid-19 (high certainty). How this guideline was created This living guideline is from the World Health Organization (WHO) and provides up to date covid-19 guidance to inform policy and practice worldwide. Magic Evidence Ecosystem Foundation (MAGIC) provided methodological support. A living systematic review with network analysis informed the recommendations. An international guideline development panel of content experts, clinicians, patients, an ethicist and methodologists produced recommendations following standards for trustworthy guideline development using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Understanding the new recommendation The linked systematic review and network meta-analysis (6 trials and 6059 participants) found that hydroxychloroquine had a small or no effect on mortality and admission to hospital (high certainty evidence). There was a small or no effect on laboratory confirmed SARS-CoV-2 infection (moderate certainty evidence) but probably increased adverse events leading to discontinuation (moderate certainty evidence). The panel judged that almost all people would not consider this drug worthwhile. In addition, the panel decided that contextual factors such as resources, feasibility, acceptability, and equity for countries and healthcare systems were unlikely to alter the recommendation. The panel considers that this drug is no longer a research priority and that resources should rather be oriented to evaluate other more promising drugs to prevent covid-19. Updates This is a living guideline. New recommendations will be published in this article and signposted by update notices to this guideline. Readers note This is the first version of the living guideline for drugs to prevent covid-19. It complements the WHO living guideline on drugs to treat covid-19. When citing this article, please consider adding the update number and date of access for clarity.

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Medicare reimbursement, nurse staffing, and patient outcomes

Journal of Health Economics ◽

10.1016/j.jhealeco.2007.04.003 ◽

2008 ◽

Vol 27 (2) ◽

pp. 339-361 ◽

Cited By ~ 9

Author(s):

Robert Kaestner ◽

Jose Guardado

Keyword(s):

Patient Outcomes ◽

Nurse Staffing ◽

Medicare Reimbursement

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

Critical Care Medicine ◽

10.1097/ccm.0000000000003286 ◽

2018 ◽

Vol 46 (10) ◽

pp. 1563-1569 ◽

Cited By ~ 8

Author(s):

Anica C. Law ◽

Jennifer P. Stevens ◽

Samuel Hohmann ◽

Allan J. Walkey

Keyword(s):

Patient Outcomes ◽

Nurse Staffing

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

American Journal of Perinatology ◽

10.1055/s-0037-1601459 ◽

2017 ◽

Vol 34 (10) ◽

pp. 0996-1002 ◽

Cited By ~ 3

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.

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

OJIN: The Online Journal of Issues in Nursing ◽

10.3912/ojin.vol21no02man02 ◽

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.

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