Evidence map›Paper›PMID 21735407›Full record

SynthesisThe Cochrane database of systematic reviews2011

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

Michelle Butler, Rita Collins, Jonathan Drennan, Phil Halligan, Dónal P O'Mathúna, Timothy J Schultz, Ann Sheridan, Eileen Vilis

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 5 pooled it
29.4field-weighted citation impact, top 1% of its field
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

32 citing papers in PubMed, 5 syntheses or guidelines pooled it, 238 citations in OpenAlex.

  1. Pooled it
  2. Hospital nurse-staffing models and patient- and staff-related outcomes.The Cochrane database of systematic reviews · 2019
    Pooled it
  3. Organisation of health services for preventing and treating pressure ulcers.The Cochrane database of systematic reviews · 2018
    Pooled it
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  14. Predictors of Clinical Nurse Leader implementation success across a national sample of settings: A Bayesian multilevel modeling analysis.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 3 countries.

Michelle ButlerSchool of Nursing, Midwifery and Health Systems, University College Dublin, Belfield, Dublin, Ireland, Dublin 4.
Rita Collins
Jonathan Drennan
Phil Halligan
Dónal P O'Mathúna
Timothy J Schultz
Ann Sheridan
Eileen Vilis
University College Dublin · IECochrane · CADublin City University · IEUniversity of Adelaide · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNurse staffing interventions have been introduced across countries in recent years in response to changing patient requirements, developments in patient care, and shortages of qualified nursing staff. These include changes in skill mix, grade mix or qualification mix, staffing levels, nursing shifts or nurses' work patterns. Nurse staffing has been closely linked to patient outcomes, organisational outcomes such as costs, and staff-related outcomes.

objectivesOur aim was to explore the effect of hospital nurse staffing models on patient and staff-related outcomes. SEARCH STRATEGY: We searched the following databases from inception through to May 2009: Cochrane/EPOC resources (DARE, CENTRAL, the EPOC Specialised Register), PubMed, EMBASE, CINAHL Plus, CAB Health, Virginia Henderson International Nursing Library, the Joanna Briggs Institute database, the British Library, international theses databases, as well as generic search engines. SELECTION CRITERIA: Randomised control trials, controlled clinical trials, controlled before and after studies and interrupted time series analyses of interventions relating to hospital nurse staffing models. Participants were patients and nursing staff working in hospital settings. We included any objective measure of patient or staff-related outcome. DATA COLLECTION AND ANALYSIS: Seven reviewers working in pairs independently extracted data from each potentially relevant study and assessed risk of bias. MAIN

resultsWe identified 6,202 studies that were potentially relevant to our review. Following detailed examination of each study, we included 15 studies in the review. Despite the number of studies conducted on this topic, the quality of evidence overall was very limited. We found no evidence that the addition of specialist nurses to nursing staff reduces patient death rates, attendance at the emergency department, or readmission rates, but it is likely to result in shorter patient hospital stays, and reductions in pressure ulcers. The evidence in relation to the impact of replacing Registered Nurses with unqualified nursing assistants on patient outcomes is very limited. However, it is suggested that specialist support staff, such as dietary assistants, may have an important impact on patient outcomes. Self-scheduling and primary nursing may reduce staff turnover. The introduction of team midwifery (versus standard care) may reduce medical procedures in labour and result in a shorter length of stay without compromising maternal or perinatal safety. We found no eligible studies of educational interventions, grade mix interventions, or staffing levels and therefore we are unable to draw conclusions in relation to these interventions. AUTHORS'

conclusionsThe findings suggest interventions relating to hospital nurse staffing models may improve some patient outcomes, particularly the addition of specialist nursing and specialist support roles to the nursing workforce. Interventions relating to hospital nurse staffing models may also improve staff-related outcomes, particularly the introduction of primary nursing and self-scheduling. However, these findings should be treated with extreme caution due to the limited evidence available from the research conducted to date.

Indexed as

Models, NursingClinical Trials as TopicHumansMidwiferyNursing Staff, HospitalOutcome Assessment, Health CarePersonnel Staffing and SchedulingSpecialties, Nursing

Identifiers

PMID21735407
OpenAlexW2164886435

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.