Evidence map›Paper›PMID 31012954›Full record

SynthesisThe Cochrane database of systematic reviews2019

Hospital nurse-staffing models and patient- and staff-related outcomes.

Michelle Butler, Timothy J Schultz, Phil Halligan, Ann Sheridan, Leigh Kinsman, Thomas Rotter, Jonathan Beaumier, Robyn Gail Kelly, Jonathan Drennan

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  6. Initiatives to support nursing workforce sustainability: A rapid umbrella review.International journal of nursing studies advances · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Michelle ButlerFaculty of Science and Health, Dublin City University, Collins Avenue, Glasnevin, Dublin, Ireland, Dublin 9.
Timothy J Schultz
Phil Halligan
Ann Sheridan
Leigh Kinsman
Thomas Rotter
Jonathan Beaumier
Robyn Gail Kelly
Jonathan Drennan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNurses comprise the largest component of the health workforce worldwide and numerous models of workforce allocation and profile have been implemented. These include changes in skill mix, grade mix or qualification mix, staff-allocation models, staffing levels, nursing shifts, or nurses' work patterns. This is the first update of our review published in 2011.

objectivesThe purpose of this review was to explore the effect of hospital nurse-staffing models on patient and staff-related outcomes in the hospital setting, specifically to identify which staffing model(s) are associated with: 1) better outcomes for patients, 2) better staff-related outcomes, and, 3) the impact of staffing model(s) on cost outcomes. SEARCH

methodsCENTRAL, MEDLINE, Embase, two other databases and two trials registers were searched on 22 March 2018 together with reference checking, citation searching and contact with study authors to identify additional studies. SELECTION CRITERIA: We included randomised trials, non-randomised trials, controlled before-after studies and interrupted-time-series or repeated-measures studies of interventions relating to hospital nurse-staffing models. Participants were patients and nursing staff working in hospital settings. We included any objective reported measure of patient-, staff-related, or economic outcome. The most important outcomes included in this review were: nursing-staff turnover, patient mortality, patient readmissions, patient attendances at the emergency department (ED), length of stay, patients with pressure ulcers, and costs. DATA COLLECTION AND ANALYSIS: We worked independently in pairs to extract data from each potentially relevant study and to assess risk of bias and the certainty of the evidence. MAIN

resultsWe included 19 studies, 17 of which were included in the analysis and eight of which we identified for this update. We identified four types of interventions relating to hospital nurse-staffing models:- introduction of advanced or specialist nurses to the nursing workforce;- introduction of nursing assistive personnel to the hospital workforce;- primary nursing; and- staffing models.The studies were conducted in the USA, the Netherlands, UK, Australia, and Canada and included patients with cancer, asthma, diabetes and chronic illness, on medical, acute care, intensive care and long-stay psychiatric units. The risk of bias across studies was high, with limitations mainly related to blinding of patients and personnel, allocation concealment, sequence generation, and blinding of outcome assessment.The addition of advanced or specialist nurses to hospital nurse staffing may lead to little or no difference in patient mortality (3 studies, 1358 participants). It is uncertain whether this intervention reduces patient readmissions (7 studies, 2995 participants), patient attendances at the ED (6 studies, 2274 participants), length of stay (3 studies, 907 participants), number of patients with pressure ulcers (1 study, 753 participants), or costs (3 studies, 617 participants), as we assessed the evidence for these outcomes as being of very low certainty. It is uncertain whether adding nursing assistive personnel to the hospital workforce reduces costs (1 study, 6769 participants), as we assessed the evidence for this outcome to be of very low certainty. It is uncertain whether primary nursing (3 studies, > 464 participants) or staffing models (1 study, 647 participants) reduces nursing-staff turnover, or if primary nursing (2 studies, > 138 participants) reduces costs, as we assessed the evidence for these outcomes to be of very low certainty. AUTHORS'

conclusionsThe findings of this review should be treated with caution due to the limited amount and quality of the published research that was included. We have most confidence in our finding that the introduction of advanced or specialist nurses may lead to little or no difference in one patient outcome (i.e. mortality) with greater uncertainty about other patient outcomes (i.e. readmissions, ED attendance, length of stay and pressure ulcer rates). The evidence is of insufficient certainty to draw conclusions about the effectiveness of other types of interventions, including new nurse-staffing models and introduction of nursing assistive personnel, on patient, staff and cost outcomes. Although it has been seven years since the original review was published, the certainty of the evidence about hospital nurse staffing still remains very low.

Indexed as

Models, NursingNursing Staff, HospitalQuality of Health CareHospital MortalityHumansOutcome Assessment, Health CarePatient ReadmissionPersonnel Staffing and SchedulingSpecialties, NursingWorkforce

Identifiers

PMID31012954
PMCPMC6478038

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.