Assessing Outcomes
The type of outcome/consequence used in an economic evaluation defines the type of analysis.
Clinical endpoints can be utilised in a cost-effectiveness analysis; however, the interpretation of the resulting cost-effectiveness ratio can be a problem. For example, if we calculate the cost/point improvement on the MADRS, we don’t have an idea of whether this value is good value for money. What as a society are we willing to spend for a point improvement on the MADRS?
Quality Adjusted Life Years (QALYs)
So, Quality Adjusted Life Years (QALYs) are frequently used as the outcome measure in economic evaluations. This is also known as cost-utility analysis. QALYs incorporate morbidity and mortality. They also have value for money connotations since cost/QALY is used by Health Technology Assessment (HTA) agencies such as the Pharmaceutical Benefits Advisory Committee (PBAC) to make decisions on which medications to subsidise.
The rule of thumb threshold for determining value for money in Australia is commonly noted at $50,000/QALY but empirical research has identified that this threshold may be closer to $28,000/QALY.
| Types of analysis | Costs | Consequences | Result |
|---|---|---|---|
| Cost minimisation | Dollars | Identical in all respects | Least cost alternative |
| Cost effectiveness | Dollars | Different magnitude of a common measure, e.g., LY’s gained, blood pressure reduction | Cost per unit of consequence, e.g., cost per LY gained |
| Cost utility | Dollars | Single or multiple effects not necessarily common. Valued as a ‘utility’, e.g., QALY | Cost per unit of consequence, e.g., per QALY |
| Cost benefit | Dollars | As for CUA but valued in money | Net $ Cost: benefit ratio |
Calculating QALYs
To calculate QALYs, we need utility values for at least 2 time points. The easiest and most pragmatic method to capture a study participant’s utility in a study is to use a multi-attribute utility instrument also known as a MAUI. These are quality of life questionnaires with a preference-based scoring algorithm. There are several quality-of-life questionnaires available for use that capture mental health domains, but not all provide utility values.
The CARE partnership project evaluated the existing quality of life measures for use in people with severe depression. The summary of measures is provided below
Another project compared five multi-attribute utility measures with depression symptom measures (DASS-21 and K10) in people with self-reported depression. All of the MAUIs discriminated between severity levels on DASS-21 and K10. The AQoL-8D had the highest correlation with these symptom measures.
Link to reference: https://doi.org/10.1192/bjp.bp.113.136036