Assessing outcomes for cost-utility analysis in depression: comparison of five multi-attribute utility instruments with two depression-specific outcome measures

• Published in: British journal of psychiatry Vol. 205; no. 5; pp. 390 - 397
• Main Authors: Mihalopoulos, Cathrine, Chen, Gang, Iezzi, Angelo, Khan, Munir A., Richardson, Jeffrey
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01-11-2014; Maney
• Subjects: Adolescent; Adult; Adult and adolescent clinical studies; Aged; Aged, 80 and over; Biological and medical sciences; Cost-Benefit Analysis; Depression; Depression - diagnosis; Depression - therapy; Female; Health Status; Humans; Male; Medical sciences; Middle Aged; Miscellaneous; Mood disorders; Outcome Assessment (Health Care) - methods; Psychology. Psychoanalysis. Psychiatry; Psychopathology. Psychiatry; Quality of Life; Quality-Adjusted Life Years; Sensitivity and Specificity; Severity of Illness Index; Surveys and Questionnaires; Young Adult; Mood disorder; Evaluation; Depression; Utility; Cost analysis; Comparative study
• ISSN: 0007-1250; 1472-1465
• DOI: 10.1192/bjp.bp.113.136036

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.
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.
Individual data from 917 people with self-report depression collected as part of the International Multi-Instrument Comparison Survey.
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.
The algorithms developed in this study can be used to determine cost-effectiveness of services or interventions where utility measures are not collected.