Description
Review the studies and articles consider the strengths and limitations of systematic reviews and meta-analyses. Make sure you are clear on the difference between the two approaches. Topic: Effect of nurse to patient ratio. A brief summary of your informed opinion regarding the validity of the use of systematic reviews and meta-analyses in epidemiological research. Include at least two strengths or limitations of each technique. Provide evidence from at least one of the articles in the Learning Resources to support and justify your position. References Driscoll, A., Grant, M. J., Carroll, D., Dalton, S., Deaton, C., Jones, I., Lehwaldt, D., McKee, G., Munyombwe, T., & Astin, F. (2018). The effect of nurse-to-patient ratios on nurse-sensitive patient outcomes in acute specialist units: A systematic review and meta-analysis. Links to an external site.. European Journal of Cardiovascular Nursing, 17(1), 6–22. https://doi.org/10.1177/1474515117721561Please make sure to include at least three scholarly references within the last 5 years APA.
Unformatted Attachment Preview
721561
review-article2017
CNU0010.1177/1474515117721561European Journal of Cardiovascular NursingDriscoll et al.
EUROPEAN
SOCIETY OF
CARDIOLOGY ®
Review Article
The effect of nurse-to-patient ratios
on nurse-sensitive patient outcomes
in acute specialist units: a systematic
review and meta-analysis
European Journal of Cardiovascular Nursing
2018, Vol. 17(1) 6–22
© The European Society of Cardiology 2017
Reprints and permissions:
sagepub.co.uk/journalsPermissions.nav
https://doi.org/10.1177/1474515117721561
DOI: 10.1177/1474515117721561
journals.sagepub.com/home/cnu
Andrea Driscoll1, Maria J Grant2, Diane Carroll3, Sally Dalton4,
Christi Deaton5, Ian Jones6, Daniela Lehwaldt7, Gabrielle McKee8,
Theresa Munyombwe9 and Felicity Astin10
Abstract
Background: Nurses are pivotal in the provision of high quality care in acute hospitals. However, the optimal dosing of
the number of nurses caring for patients remains elusive. In light of this, an updated review of the evidence on the effect
of nurse staffing levels on patient outcomes is required.
Aim: To undertake a systematic review and meta-analysis examining the association between nurse staffing levels and
nurse-sensitive patient outcomes in acute specialist units.
Methods: Nine electronic databases were searched for English articles published between 2006 and 2017. The primary
outcomes were nurse-sensitive patient outcomes.
Results: Of 3429 unique articles identified, 35 met the inclusion criteria. All were cross-sectional and the majority
utilised large administrative databases. Higher staffing levels were associated with reduced mortality, medication errors,
ulcers, restraint use, infections, pneumonia, higher aspirin use and a greater number of patients receiving percutaneous
coronary intervention within 90 minutes. A meta-analysis involving 175,755 patients, from six studies, admitted to the
intensive care unit and/or cardiac/cardiothoracic units showed that a higher nurse staffing level decreased the risk of
inhospital mortality by 14% (0.86, 95% confidence interval 0.79–0.94). However, the meta-analysis also showed high
heterogeneity (I2=86%).
Conclusion: Nurse-to-patient ratios influence many patient outcomes, most markedly inhospital mortality. More
studies need to be conducted on the association of nurse-to-patient ratios with nurse-sensitive patient outcomes to
offset the paucity and weaknesses of research in this area. This would provide further evidence for recommendations of
optimal nurse-to-patient ratios in acute specialist units.
Keywords
Nursing, workforce, staffing, systematic review, nurse-to-patient ratio
Date received: 14 February 2016; accepted: 28 June 2017
1Quality and Patient Safety Research, School of Nursing and Midwifery,
Deakin University, Australia
2School of Nursing, Midwifery, Social Work & Social Sciences,
University of Salford, UK
3Munn Center for Nursing Research, Massachusetts General Hospital,
USA
4Library, University of Leeds, UK
5Department of Public Health and Primary Care, University of
Cambridge, UK
6School of Nursing and Allied Health, Liverpool John Moores
University, UK
7Department of Nursing and Human Sciences, Dublin City University,
Ireland
8School of Nursing & Midwifery, Trinity College Dublin, Ireland
9Divison of Epidemiology and Biostatistics, University of Leeds, UK
10Research and Development Department, University of Huddersfield
and Calderdale and Huddersfield NHS Foundation Trust, UK
Corresponding author:
Andrea Driscoll, School of Nursing and Midwifery, Quality and Patient
Safety Research (QPS), Deakin University, Locked Bag 20000, Geelong,
VIC 3220, Australia.
Email: [email protected]
7
Driscoll et al.
Introduction
Review objective
Over the past decade there has been a renewed focus on
what constitutes an adequate level of nurse staffing. This is
in part due to some spectacular failures that have occurred in
care provision for hospital inpatients leading to loss of
life.1,2 Organisations across countries have adopted different
approaches to managing the nursing workforce. In Victoria,
Australia, and California, USA, standardised and mandatory nurse staffing levels have been in place for over a decade. In the UK and Ireland there are national nurse staffing
recommendations, but these are not mandated by law.3–5
Wales has a similar situation, they recently introduced the
Nurse Staffing Levels Act 2016; however, there are no mandated nurse-to-patient ratios (NPRs) only recommendations
to guide decisions about nurse staffing levels.6 The notion of
an optimal level of nurse staffing is somewhat controversial
because there is no one-size-fits-all approach to assessing
staffing levels. This lack of clarity is further aggravated by a
lack of consensus about the most appropriate way of estimating the size and mix of nursing teams because all measurement approaches have limitations.4,7
One of the challenges faced by managers responsible
for staffing is finding a way to understand the influence of
the multiple factors that make up each individual care
environment which are likely to differ across organisations
and countries. Donabedian grouped potential factors into
three broad domains: structural factors (the people, paraphernalia and place that make up the healthcare delivery
system); processes of care (how care is done through the
interactions between health professionals and patients);
and subsequent outcomes (the end results of the care that
takes place in the context of the organisation).8
To determine nurse staffing levels, managers need to
understand the underlying determinants which are patient
factors (patient nursing need according to acuity and
dependency levels), ward factors (patient throughput) and
nursing staff factors (number and skill level).9 Findings
from a systematic review and meta-analysis, now a decade
old, reported a significant association between increased
nursing staffing in hospitals and improved nurse-sensitive
patients outcomes.10 A more recent literature review by
Penoyer found an association between nurse staffing levels
and patient outcomes in the intensive care unit (ICU).11
However, their review only included studies from 1998 to
2008. In light of this an updated literature review is warranted. This review will examine recently published studies
investigating associations between nurse staffing levels and
nurse-sensitive patient outcomes in acute specialist units.
To identify studies conducted in acute specialist units,
which examine the association between nurse staffing levels (NPRs) and nurse-sensitive patient outcomes (as
defined below).
Methods
To support the quality of the systematic review, a protocol
was developed based on the PRISMA statement.12 The
review protocol was not registered.
Definitions
Nurse-to-patient ratio. NPRs are typically expressed in two
ways: the number of nurses working per shift or over a 24
hour period divided by the number of beds occupied by a
patient over the same time period; or the number of nursing
hours per patient bed days (NHPPD). There are other more
complex approaches to measure nurse staffing requirements but there is no single recommended approach.3 Many
of the studies included in this review have determined
NPRs. A higher level of nursing staff indicates more nurses
(or higher proportion of nurses) for assigned patients.
Lower nurse staffing is defined as fewer nurses (or lower
proportion) for the number of assigned patients.11
Moreover, little is known about how nurse staffing levels are managed across hospitals in Europe. NPRs are easily and cheaply measured but it is a relatively blunt
instrument that can function as one indicator, and can be
triangulated with other measurement approaches to establish safe nurse staffing levels.
Nurse-sensitive patient outcome measures. The nurse-sensitive patient outcomes measures included in this study were
based on adverse events from previous studies that have
been sensitive to changes in nurse staffing.10,13 The nursesensitive patient outcome measures we included were:
mortality, failure to rescue (FTR), shock (including sepsis
resuscitation), cardiac arrest, unplanned extubation, hospital acquired pneumonia, respiratory failure, surgical bleeding, heart failure/fluid overload, catheter-associated urinary
tract infection, pressure sores, patient falls, nosocomial
bloodstream infection, medication error, length of stay,
hospital-acquired sepsis, deep vein thrombosis, central
nervous system complications, death, wound infection,
pulmonary failure, and metabolic derangement.
Search strategy
The search strategy was developed by the research team
with input from expert information technologists (see
Supplementary Appendix 1). Electronic databases and
grey literature were searched (Medline (OvidSP), Medline
in Process (OvidSP), CINAHL (Cumulative Index to
Nursing and Allied Health Literature) (EBSCO), PsycInfo
(OvidSP), Embase (OvidSP), HMIC (Health Management
Information Consortium) (OvidSP), Cochrane Database of
Systematic Reviews, Web of Science; Science Citation
Index Expanded (ISI Web of Knowledge), Web of Science;
8
European Journal of Cardiovascular Nursing 17(1)
Social Sciences Citation Index (ISI Web of Knowledge),
Web of Science; Conference Proceedings Citation Index
– Science (ISI Web of Knowledge), Web of Science;
Conference Proceedings Citation Index- Social Science
and Humanities (ISI Web of Knowledge), Index to Theses,
Proquest Dissertations and Theses). A combination of keywords was used and controlled vocabulary such as MeSH
(medical subject headings) when available. Search terms
included 18 terms on settings, i.e. coronary care, high
dependency, critical care, intensive care, cardiac ward,
intensive treatment unit and 17 terms relating to nursing or
manpower or skill mix, i.e. nurse staffing, nurse ratio,
nurse mix, nurse dose, nurse workload and 78 nurse-sensitive outcomes, i.e. wound infection, pulmonary failure,
shock, pneumonia, length of stay, outcome, patient safety.
The search was limited to English language and conducted
from January 2006 to February 2017. Conference abstracts
and reference lists of included studies were manually
searched and additional studies identified.
Inclusion criteria
Following the literature search, a team of reviewers worked
in pairs to screen titles and abstracts independently according to the inclusion criteria. Any disagreement between
reviewers was resolved by a third reviewer. Studies that
met the following inclusion criteria were included:
•• Patients admitted to acute specialist units (e.g. intensive therapy units/critical care/intensive care/coronary
care, high dependency, and cardiothoracic surgery
units, where a proportion of the nurses are required to
have a postgraduate critical care qualification) with
care provision for adults (over 18 years of age). Studies
with a mixed population ward were included.
•• Investigating the effect of NPRs using either the
number of nurses divided by the number of patients
over 24 hours or the NHPPD.
•• Published from January 2006 to February 2017 in
English.
•• Quantitative methodology.
•• Primary outcome measures:
|| at least one nurse-sensitive outcome such as
mortality, FTR, shock, cardiac arrest, unplanned
extubation, hospital acquired pneumonia, respiratory failure, surgical bleeding, heart failure/
fluid overload/imbalance, urinary tract infection, pressure sores, patient falls, nosocomial
bloodstream infection, medication error, pain
control, unplanned readmission.
Data extraction
A tailor-made data extraction tool was developed a priori
and piloted and refined.
The tool included six screening questions to ensure
papers fit with the review inclusion criteria (see
Supplementary Appendix 2). Information was also extracted
from each study to record under the following headings:
bibliographic details; setting/country; study design; outcomes, findings/conclusions and quality assessment.
Quality assessment
All included studies were assessed by the Newcastle–
Ottawa scale (NOS) to determine the quality of nonrandomised studies.14 This tool was designed to facilitate
the incorporation of quality assessment into the systematic review. This tool has been used in previous Cochrane
reviews for assessment of risk of bias in non-randomised
studies. The content validity and inter-rater reliability of
this scale was previously established. The NOS consists
of eight items: representativeness of cohort, selection of
cohort, ascertainment of exposure, outcome of interest
was not present at baseline, comparability of cohorts,
assessment of outcome, length of follow-up and adequacy of follow-up.14 Each item was awarded a ‘*’ for
meeting the criterion. A study was also awarded an additional ‘*’ if the analysis was adjusted for potential confounding variables. The quality of each study was graded
as low, medium or high according to the number of stars
(*). The quality assessment was conducted independently
by two reviewers. Disagreements were resolved by a
third reviewer.
Statistical analysis
As this systematic review involved cross-sectional studies
we used adjusted measures, as reported by authors, as the
primary effect measures to control for confounding when
it was available. Odds ratios (ORs) were used as an appropriate effect measure if available. Other effect measures
were: hazard ratios or risk ratios.
A meta-analysis was conducted on homogenous studies
using a random-effect model with inhospital mortality as
the primary outcome. In studies where patient-to-nurse
ratios were used, these were converted to NPRs by calculating the inverse ratio. The overall effect sizes will be presented in a forest plot. In studies in which a pooled
meta-analysis was unable to be performed, a narrative
analysis will be undertaken.
Clinical homogeneity was assessed in terms of study
cohort, hospital units, diagnosis and risk of bias. The I2
was also used to determine statistical heterogeneity. If I2
is greater than 40% a random effects model will be used.
A sensitivity analysis will also be conducted using a
fixed effects model to determine if the conclusions were
different.
Data analysis was conducted using Review Manager
version 5.3.15
9
Driscoll et al.
Figure 1. Flow diagram of study selection.
Results
We identified a total of 4472 studies from the literature
search. After duplicates were removed, 3429 records were
screened using title and abstract. Of these, we identified 196
full-text articles for retrieval. We included 35 articles in the
final analysis (see Figure 1). Reasons for exclusion included
research relating to neonates, non-acute settings, no NPRs
and no nurse-sensitive patient outcomes being reported.
Description of studies
All of the 35 papers were cross-sectional studies except for
one point prevalence study. All of the studies had a large
sample size derived from administrative datasets (Table 1).
Fourteen studies were conducted in the USA/Canada/
Mexico, 17 studies in Europe, three studies in China and
one in Thailand. In terms of study setting, 11 studies
included patients throughout the hospital including critical
care, 19 studies restricted their cohort to ICUs only
(included cardiovascular patients), and five studies were in
specialist cardiac units.16–46
Quality appraisal
The NOS consists of three principal domains: case selection, representativeness of cohorts, and measurement of
outcome.14 All 35 cohort studies met the criterion for representativeness of cohort selection, five studies received one
star and 24 studies received two stars for comparability of
cohorts, 24 studies discussed outcome assessment and 35
studies defined their length of follow-up (Table 2).16–46
There were 24 studies that rated highly on the NOS for
assessing the quality of non-randomised trials (Table 2).
All of these studies controlled for several confounding factors in either their methodology or data analysis. The
majority of these studies adjusted for age, comorbidities
and hospital characteristics as potential confounders.
Seven studies were rated as low quality mainly due to the
lack of comparability of cohorts.
Nurse-to-patient ratios
Various approaches were used to measure NPRs. Schwab
et al. calculated the NPR per shift (number of nurses per
day/three (per shift)/number of patients per day) using
monthly census data.38 Other studies used similar approac
hes.19,25,26,31,33,37 Several authors provided less detail about
how the NPR was calculated.18,28,30,32 Valentin et al. calculated both the NPR by shift and the occupancy rate (maximum number of occupied beds divided by allocated beds),
NPR for each shift in each unit and the relative turnover
(number of admitted and discharged patients divided by
the number of unit beds).43 Cho et al. calculated the NPR
Sample & setting (population)
669 patients in 34 general ICUs in 9
European countries
27 ICUs in 9 European countries.
Recruited 2585 patients who
had mechanical ventilation after
admission for treatment for
pneumonia or who were ventilated
for more than 24 hours irrespective
of diagnosis on admission
69 ICUs (medical and surgical),
in USA were surveyed about
organisation structure. Patient
outcomes were collected
prospectively from US Critical
Illness and Injury Trials Group
Critical Illness Outcomes study
Number of patients was not stated
104,046 admissions to 155 ICUs
in 87 hospitals, January–December
2011, Thailand using hospital
databases from participating ICUs
27,372 ICU patients with 26
primary diagnoses from ICUs in
236 hospitals (42 tertiary and 194
secondary) in Korea. Data were
collected retrospectively from three
national databases: ICU survey data,
medical claims data and the National
Health Insurance database
Study design
Point prevalence
study
Prospective
cross-sectional
study
Prospective
cross-sectional
study
Retrospective
cross-sectional
study
Retrospective
cross-sectional
study
Author, year of
publication
Benbenbishty
et al., 201016
Blot et al., 201117
Checkley et al.,
201418
Chittawatanarat
et al., 201419
Cho et al., 200820
Table 1. Characteristics of included studies.
NPR: number of
nurses on each 8
hour rotation divided
by the number of
patient beds
Patient-to-nurse ratio
calculated each shift
A definition of NPR
was not provided.
However, each site
provided nurse
staffing numbers and
number of beds
NPR was measured
each shift over a 24
hour period
NPR was measured
as the standard ratio
for each unit
Measure of nurse-topatient ratio
Inhospital mortality
Monthly mortality
Ventilator days
ICU length of stay
Annual mortality
Incidence of VAP
Use of physical
restraints
Outcome measures
(Continued)
Secondary care intensive care unit NPR:
1:0.98
Every additional patient per nurse resulted in
a 9% increase in the odds of death (OR 1.09,
95% CI 1.04–1.14)
Each additional patient cared for by a nurse
would result in an additional 15 deaths per
1000 patients
Two and three additional patients were
associated with an 18% and 29% increases in
mortality, equivalent to 28 and 44 additional
deaths per 1000 patients, respectively.
Tertiary care intensive care unit
NPR 1:0.76
No significant findings related to mortality in
these units
Mean NPR 1:0.50
Lower NPRs were associated with lower
ventilator days (OR −2.08, 95% CI −5.377 to
−0.166, P=0.037)
NPR varied from 1:1 to 1:4
Number of restraints increased as the NPR
increased (χ2=17.17 P=0.001)
NPR varied from 1: 1 to 1:3
VAP incidence was significantly lower in ICU
units with 1:1 NPR compared to units with
a ratio of >1:1 (9.3% vs. 24.4%, P=0.002)
(univariate analysis)
However, after adjusting for confounders this
association became not significant
Mean NPR was 1:1.8 (median 1:1.7)
The annual mortality was 1.8% lower when
the NPR decreased from 1:2 to 1:1.5 (95% CI
0.25–3.4%)
For every increase of one patient per nurse
there was a 3.7% increase in annual ICU
mortality (95% CI 0.5–6.8, P=0.02)
Key findings
10
European Journal of Cardiovascular Nursing 17(1)
ICUs from 185 hospitals (40 tertiary
and 145 secondary) in Korea
Acute stroke patients admitted to
ICU during hospitalisation aged
Purchase answer to see full
attachment
