Describing the resource utilisation and costs associated withvertebral fractures: the Build Better Bones with Exercise (B3E) Pilot Trial
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This analysis examined costs/resources of 141 women with vertebral fractures, randomised to a home exercise programme or control group. Total, mean costs and the incremental cost-effectiveness ratio (ICER) were calculated. Quality of life was collected. Cost drivers were caregiver time, medications and adverse events (AEs). Results show adding an exercise programme may reduce the risk of AEs. INTRODUCTION: This exploratory economic analysis examined the health resource utilisation and costs experienced by women with vertebral fractures, and explored the effects of home exercise on those costs. METHODS: Women ≥ 65 years with one or more X-ray-confirmed vertebral fractures were randomised 1:1 to a 12-month home exercise programme or equal attention control group. Clinical and health system resources were collected during monthly phone calls and daily diaries completed by participants. Intervention costs were included. Unit costs were applied to health system resources. Quality of life (QoL) information was collected via EQ-5D-5L at baseline, 6 and 12 months. RESULTS: One hundred and forty-one women were randomised. Overall total costs (CAD 2018) were $664,923 (intervention) and $614,033 (control), respectively. The top three cost drivers were caregiver time ($250,269 and $240,811), medications ($151,000 and $122,145) and AEs ($58,807 and $71,981). The mean cost per intervention participant of $9365 ± $9988 was higher compared with the mean cost per control participant of $8772 ± $9718. The mean EQ-5D index score was higher for the intervention participants (0.81 ± 0.11) compared with that of controls (0.79 ± 0.13). The differences in quality-adjusted life year (QALY) (0.02) and mean cost ($593) were used to calculate the ICER of $29,650. CONCLUSIONS: Women with osteoporosis with a previous fracture experience a number of resources and associated costs that impact their care and quality of life. Caregiver time, medications and AEs are the biggest cost drivers for this population. The next steps would be to expand this feasibility study with more participants, longer-term follow-up and more regional variability.
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