Research Involvement and Engagement (Aug 2024)

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

DOI
https://doi.org/10.1186/s40900-024-00606-x
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 17

Abstract

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Abstract Background Aged 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. Methods This 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. Results No 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. Conclusion Participants 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.

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