Medicine (RMH) - Research Publications
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ItemNo Preview AvailableComparison of Health-Related Quality of Life, Work Status, and Health Care Utilization and Costs According to Hip and Knee Joint Disease Severity: A National Australian Study(OXFORD UNIV PRESS INC, 2013-07)BACKGROUND: No population-based studies have investigated how the impact of hip and knee joint disease may vary with increasing severity. OBJECTIVE: The purpose of this study was to evaluate health-related quality of life (HRQoL), work status, and health service utilization and costs according to severity of hip and knee joint disease. DESIGN: A national cross-sectional survey was conducted. METHODS: Five thousand individuals were randomly selected from the Australian electoral roll and invited to complete a questionnaire to screen for doctor-diagnosed hip arthritis, hip osteoarthritis (OA), knee arthritis, and knee OA. Severity was classified by means of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores (range=0-100): <7=asymptomatic, 7-38=mild-moderate, and ≥39=severe. Health-related quality of life was evaluated by means of the Assessment of Quality of Life (AQoL) instrument (range=-0.04 to 1.00; scored worst-best). Self-reported data on work status and health service utilization were collected, with health care costs estimated with the use of government data. RESULTS: Data were available for 1,157 participants, with 237 (20%) reporting hip or knee joint disease. Of these, 16% (n=37) were classified as asymptomatic, 51% (n=120) as mild-moderate, and 27% (n=64) as severe. The severe group reported very low HRQoL (adjusted mean AQoL=0.43, 95% confidence interval [95% CI]=0.38-0.47) compared with the mild-moderate group (adjusted mean AQoL=0.72, 95% CI=0.69-0.75) and the asymptomatic group (adjusted mean AQoL=0.80, 95% CI=0.74-0.86). Compared with the asymptomatic group, the severe group was >3 times less likely to undertake paid work (adjusted odds ratio=0.28, 95% CI=0.09-0.88) and >4 times less likely to undertake unpaid work (adjusted odds ratio=0.24, 95% CI=0.10-0.62). Although physical therapy services were used infrequently, primary and specialist care utilization and costs were highest for the severe group. LIMITATIONS: Other costs (including physical therapy consultations) were unavailable. CONCLUSIONS: A clear pattern of worsening HRQoL, reduced work participation, and higher medical care utilization was seen with increasing severity of joint disease.
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ItemPerformance of the Assessment of Quality of Life Measure in People With Hip and Knee Joint Disease and Implications for Research and Clinical Use(WILEY, 2014-03)OBJECTIVE: To comprehensively evaluate the performance of the Assessment of Quality of Life (AQoL) instrument for measuring health-related quality of life (HRQOL) in people with hip and knee joint disease (arthritis or osteoarthritis). METHODS: Data from 237 individuals were available for analysis from a national cross-sectional, population-based study of hip and knee joint disease in Australia. AQoL-4D data were evaluated using Rasch analysis. A range of measurement properties was explored, including model and item fit, threshold ordering, differential item functioning, and targeting. RESULTS: Good overall fit of the AQoL with the Rasch model was demonstrated across a range of tests, supporting internal validity. Only 1 item (relating to hearing) showed evidence of misfit. Most AQoL items showed logical sequencing of response option categories, with threshold disordering evident for only 2 of the 12 items (items 4 and 9). Minor issues with potential clinical and research implications include limited options for reporting pain and some evidence of measurement bias between demographic subgroups (including age and sex). Participants' HRQOL was generally better than that represented by the AQoL items (mean ± SD for person abilities -2.15 ± 1.39, mean ± SD for item difficulties 0.00 ± 0.67), indicating ceiling effects that could impact the instrument's ability to detect HRQOL improvement in population-based studies. CONCLUSION: The AQoL is a competent tool for assessing HRQOL in people with hip and knee joint disease, although researchers and clinicians should consider the caveats identified when selecting appropriate HRQOL measures for future outcome assessment involving this patient group.
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ItemUsing WOMAC Index scores and personal characteristics to estimate Assessment of Quality of Life utility scores in people with hip and knee joint disease(SPRINGER, 2014-10)PURPOSE: To determine whether Assessment of Quality of Life (AQoL) utility scores can be reliably estimated from Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores in people with hip and knee joint disease (arthritis or osteoarthritis). METHODS: WOMAC and AQoL data were analysed from 219 people recruited for a national population-based study. Generalised linear models were used to estimate AQoL utility scores based on WOMAC total and subscale scores and personal characteristics. Goodness of fit was assessed for each model, and plots of prediction errors versus actual AQoL utility scores were used to gauge bias. RESULTS: Each model closely predicted the average AQoL utility score for the overall sample (actual mean AQoL 0.64, range of predicted means 0.63-0.64; actual median AQoL 0.71, range of predicted medians 0.68-0.69). No clear preferred model was identified, and overall, the models predicted 40-46% of the variance in AQoL utility scores. The WOMAC function subscale model performed similarly to the total score model. The models functioned best at the mid-range of AQoL scores, with greater bias observed for extreme scores. Inaccuracies in individual-level estimates and low/high health-related quality of life (HRQoL) subgroup estimates were evident. CONCLUSION: Reliable overall group-level estimates were produced, supporting the application of these techniques at a population level. Using WOMAC scores to predict individual AQoL utility scores is not recommended, and the models may produce inaccurate estimates in studies targeting patients with low/high HRQoL. Where pain and stiffness data are unavailable, the WOMAC function subscale can be used to generate a reasonable utility estimate.