Evidence map›Paper›PMID 35927686›Full record

SynthesisBMC public health2022

Leave events among Aboriginal and Torres Strait Islander people: a systematic review.

J Coombes, K Hunter, K Bennett-Brook, B Porykali, C Ryder, M Banks, N Egana, T Mackean, S Sazali, E Bourke and 1 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Trial
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

J CoombesThe George Institute for Global Health, Newtown, Australia. jcoombes@georgeinstitute.org.au.
K HunterThe George Institute for Global Health, Newtown, Australia.
K Bennett-BrookThe George Institute for Global Health, Newtown, Australia.
B PorykaliThe George Institute for Global Health, Newtown, Australia.
C RyderThe George Institute for Global Health, Newtown, Australia.
M BanksAustralian Commission On Safety and Quality in Health Care, Sydney, Australia.
N EganaAustralian Commission On Safety and Quality in Health Care, Sydney, Australia.
T MackeanThe George Institute for Global Health, Newtown, Australia.
S SazaliThe George Institute for Global Health, Newtown, Australia.
E BourkeThe George Institute for Global Health, Newtown, Australia.
C KairuzThe George Institute for Global Health, Newtown, Australia.
The George Institute for Global Health · AUAustralian Commission on Safety and Quality in Health Care · AUFlinders University · AUUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLeave events are a public health concern resulting in poorer health outcomes. In Australia, leave events disproportionally impact Aboriginal and Torres Strait Islander people. A systematic review was conducted to explore the causes of leave events among Aboriginal and Torres Strait Islander people and strategies to reduce them.

methodsA systematic review was conducted using Medline, Web of Science, Embase and Informit, a database with a strong focus on relevant Australian content. Additionally, we examined the references of the records included, and performed a manual search using Google, Google scholar and the Australia's National Institute for Aboriginal and Torres Strait Islander Health Research. Two independent reviewers screened the records. One author extracted the data and a second author reviewed it. To appraise the quality of the studies the Mixed Methods Appraisal Tool was used as well as the Aboriginal and Torres Strait Islander Quality Appraisal Tool. A narrative synthesis was used to report quantitative findings and an inductive thematic analysis for qualitative studies and reports.

resultsWe located 421 records. Ten records met eligibility criteria and were included in the systematic review. From those, four were quantitative studies, three were qualitative studies and three reports. Five records studied data from the Northern Territory, two from Western Australia, two from New South Whales and one from Queensland. The quantitative studies focused on the characteristics of the patients and found associations between leave events and male gender, age younger than 45 years and town camp residency. Qualitative findings yielded more in depth causes of leave events evidencing that they are associated with health care quality gaps. There were multiple strategies suggested to reduce leave events through adapting health care service delivery. Aboriginal and Torres Strait Islander representation is needed in a variety of roles within health care provision and during decision-making.

conclusionThis systematic review found that multiple gaps within Australian health care delivery are associated with leave events among Aboriginal and Torres Strait Islander people. The findings suggest that reducing leave events requires better representation of Aboriginal and Torres Strait Islander people within the health workforce. In addition, partnership with Aboriginal and Torres Strait Islander people is needed during the decision-making process in providing health services that meet Aboriginal and Torres Strait Islander cultural needs.

Indexed as

Australian Aboriginal and Torres Strait Islander PeoplesHealth Services, IndigenousHealth WorkforceHumansMaleNorthern TerritoryQualitative ResearchAboriginalLeave eventsQuality of careTorres Strait Islander

Identifiers

PMID35927686
PMCPMC9354286
OpenAlexW4289812725

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.