Evidence map›Paper›PMID 39143622›Full record

ArticleResearch involvement and engagement2024

Person-centred quality indicators for Australian aged care assessment services: a mixed methods study.

Sandra Smith, Catherine Travers, Melinda Martin-Khan, Ivy Webb, Elizabeth Miller, Jane Thompson, Natasha Roberts

Abstract read
In one paragraph

Article in Research involvement and engagement, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Development of a Patient and Carer Advisory Board to Co-Design Health Services Research for the Quality of Care of People With Dementia.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
  2. 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

7 authors.

Sandra SmithThe University of Queensland, Centre for Health Services Research, Brisbane, Australia. sandra.smith@uqconnect.edu.au.
Catherine TraversSchool of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia.
Melinda Martin-KhanThe University of Queensland, Centre for Health Services Research, Brisbane, Australia.
Ivy WebbThe University of Queensland, Centre for Health Services Research, Brisbane, Australia.
Elizabeth MillerThe University of Queensland, Centre for Health Services Research, Brisbane, Australia.
Jane ThompsonThe University of Queensland, Centre for Health Services Research, Brisbane, Australia.
Natasha RobertsCentre for Clinical Research, The University of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAged Care Assessment Teams are the assessment component of the Australian aged care system. Their purpose is to undertake needs-based assessments to determine an older person's eligibility for, and access to Commonwealth-funded aged care services. There are no measures that tell us if the aged care assessment service is of high quality from the perspective of the person being assessed. Quality measures have been developed and introduced in Australian residential aged care facilities. These however, have not considered the perspectives of those living in this setting. Quality measures for home care services have also been recommended. This research aims to address the gap in person-centred quality measures by asking current and future service users of aged care assessment services to vote on the importance of 24 person-centred quality indicators (PC-QIs), that were developed in a previous study using a modified Delphi method approach supported by engagement with a consumer led Advisory Board.

methodsThis mixed methods study used the RAND/UCLA Appropriateness Method to reach consensus on a final set of PC-QIs. Twenty-five community-dwelling older people in Brisbane, Australia, voted on the importance of 24 PC-QIs using a five-point Likert scale. A consensus statement for PC-QI elimination was determined prior to participants voting. Voting was undertaken with participants individually either face-to-face or via telephone, in their homes. To capture any narrative provided by participants regarding each PC-QI, participant voting sessions were audio-recorded and subsequently transcribed verbatim. Quantitative data from participant votes for each PC-QI were calculated and statistically described by median, interquartile range, consensus met, percentile, percentile rank, rank order, median and standard deviation. PC-QIs were then assessed against the consensus statement for elimination and rank ordered according to importance to participants. Content analysis of qualitative data from audio transcriptions was conducted to determine the presence of certain words supporting participant votes for each PC-QI.

resultsNo PC-QIs were eliminated during voting. Variation existed among participants' ratings of importance for each PC-QI. Final quality domains, their respective title, quality indicator descriptor and supporting qualitative data are presented. Five PC-QIs had a median of five, no votes recorded below four, an interquartile range of zero, and a rank order score of one, two and four, out of a possible ten, indicating they were of highest importance to participants.

conclusionParticipants reached consensus on 24 evidence-based PC-QIs that represent measures of quality of aged care assessment services from the perspectives of current and future service users.

Indexed as

Aged care assessment servicesOlder peoplePerson-centred quality indicatorsPolicyQuality measures

Identifiers

PMID39143622
PMCPMC11323374

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.