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Assessing outcomes for cost-utility analysis in depression: comparison of five multi-attribute utility instruments
Cathrine Mihalopoulos1, Gang Chen1, Angelo Iezzi1
1Cathrine Mihalopoulos, BBSc(Hons), GDEcSt, PGDHthEc, PhD, Deakin Health Economics, Deakin University, Burwood, Victoria; Gang Chen, BMed, MSc, PhD, Flinders Health Economics Group, School of Medicine, Flinders University, Repatriation General Hospital, Daw Park, South Australia; Angelo Iezzi, BE (civil), MSc, Munir A. Khan, BA(Hons), MSc, MA, PhD, Jeffrey Richardson, BA(Hons), PhD, Centre for Health Economics, Faculty of Business and Economics, Monash University, Victoria, Australia.
Background:
Many mental health surveys and clinical studies do not include a multi-attribute utility instrument (MAUI) that produces quality-adjusted life-years (QALYs). There is also some question about the sensitivity of the existing utility instruments to mental health.
Aims:
To compare the sensitivity of five commonly used MAUIs (Assessment of Quality of Life - Eight Dimension Scale (AQoL-8D), EuroQoL-five dimension (EQ-5D-5L), Short Form 6D (SF-6D), Health Utilities Index Mark 3 (HUI3), 15D) with that of disease-specific depression outcome measures (Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K10)) and develop 'crosswalk' transformation algorithms between the measures.
Method:
Individual data from 917 people with self-report depression collected as part of the International Multi-Instrument Comparison Survey.
Results:
All the MAUIs discriminated between the levels of severity measured by the K10 and the DASS-21. The AQoL-8D had the highest correlation with the disease-specific measures and the best goodness-of-fit transformation properties.
Conclusions:
The algorithms developed in this study can be used to determine cost-effectiveness of services or interventions where utility measures are not collected.
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