Feasibility of routine quality-of-life measurement in residential aged care: Results from a pilot study in Australia

Objective

This study presents findings from a pilot study that aimed to examine the feasibility of routine measurement of quality of life in residential aged care, including the examination of barriers to and facilitators of collecting and using that data to improve quality of care.

Methods

This study was conducted at two not-for-profit residential aged care facilities in Melbourne, VIC, Australia. All residents were eligible to participate if consent was provided. Self-reported quality-of-life data were collected from residents, alongside proxy-reported data from aged care staff and relatives, primarily using the EQ-5D-5L in addition to a randomly assigned second measure (i.e. The Adult Social Care Outcomes Toolkit [ASCOT], Quality of Life-Aged Care Consumers [QOL-ACC], EQ Health and Wellbeing Instrument [EQ-HWB]). Feasibility was assessed in terms of missing data, residents’ level of engagement and understanding, and difficulty experienced by staff and relatives in providing proxy reports. Perceived facilitators and barriers were identified via qualitative interviewers with staff who collected the data.

Results

From 103 consenting participants, we gathered quality-of-life data through self-report (n = 90), staff proxy-report (n = 101) and family proxy-report (n = 49). Most residents (94%) were able to respond to the EQ-5D-5L questions and residents’ level of engagement was rated by staff as good. Only a few missing values (0–10%) were recorded for the EQ-5D-5L. Qualitative findings indicate that while quality-of-life data collection has benefits, barriers include time pressures, residents being too unwell to self-report, staff uncertainty about responding on their behalf and issues with the measure itself.

Conclusions

While it is feasible to routinely collect quality-of-life data in residential aged care, addressing the barriers identified will optimise the efficiency of the process and maximise the use of data to guide quality improvement strategies.