Quality-adjusted life years
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Quality-adjusted life years, or QALYs, is a way of measuring both the quality and the quantity of life lived, as a means of quantifying in benefit of a medical intervention. Pliskin, Shepard and Weinstein (1980, Operations Research) have shown that the QALY model requires utility independent, risk neutral, and constant proportional tradeoff behaviour.
They are based on the number of years of life that would be added by the intervention. Each year in perfect health is assigned the value of 1.0 down to a value of 0 for death. If the extra years would not be lived in full health, for example if the patient would lose a limb, or be blind or be confined to a wheelchair, then the extra life-years are given a value between 0 and 1 to account for this.
The meaning and usefulness of QALY is debated. Perfect health is hard, if not impossible, to define. Some argue that there are health states worse than death, and that therefore there should be negative values possible on the health spectrum (indeed, some health economists have incorporated negative values into calculations). Determining the level of health depends on measures that some argue places disproportionate importance on physical pain or disability over mental health. The effects of a patient's health on the quality of life of others - caregivers, family etc. also does not figure into these calculations.
The "weight" values between 0 and 1 are usually determined by methods such as:
- Time-trade-off (TTO) - In this method, respondents are asked to choose between remaining in a state of ill health for a period of time, or being restored to perfect health but having a shorter life expectancy.
- Standard gamble (SG) - In this method, respondents are asked to choose between remaining in a state of ill health for a period of time, or choosing a medical intervention which has a chance of either restoring them to perfect health, or killing them.
- Visual analogue scale (VAS) - In this method, respondents are asked to rate a state of ill health on a scale from 0 to 100, with 0 representing death and 100 representing perfect health. This method has the advantage of being the easiest to ask, but is the most subjective.
Another way of determining the weight associated with a particular health state is to use standard descriptive systems such as the EuroQol EQ-5D questionnaire, which categorise health states according to dimensions such as mobility, pain and anxiety.
However, the weight assigned to a particular condition can vary greatly, depending on the population being surveyed. Those who do not suffer from the affliction in question will, on average, overestimate the detrimental effect on quality of life, compared to those who are afflicted.
QALYs are used in cost-utility analyses to calculate the ratio of cost to QALYs saved for a particular health care intervention. This is then used to allocate healthcare resources, with an intervention with a lower cost to QALY saved ratio being preferred over an intervention with a higher ratio. This method is controversial because it means that some people will not receive treatment as it is calculated that cost of the intervention is not warranted by the benefit to their quality of life. However, its supporters argue that since health care resources are inevitably limited, this method enables them to be allocated in the way that is most beneficial to society.
See also
External links
- CEA Registry Website
- QALY
- What is a QALY? (Hayward Medical Communications)
- Euroqo
- Problems and solutions in calculating quality-adjusted life
years (QALYs)[1]
- Over-Reliance on QALYs Might Be Dangerous [2]
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Some of the initial content on this page may be incorporated in part from copyleft sources in the public domain including wikis such as Wikipedia and AskDrWiki. Drug information for patients came from the The National Library of Medicine. Infectious disease information may have come from the Centers for Disease Control (CDC). Differential Diagnoses are drawn from clinicians as well as an amalgamation of 3 sources: 1.The Disease Database; 2. Kahan, Scott, Smith, Ellen G. In A Page: Signs and Symptoms. Malden, Massachusetts: Blackwell Publishing, 2004:3; 3. Sailer, Christian, Wasner, Susanne. Differential Diagnosis Pocket. Hermosa Beach, CA: Borm Bruckmeir Publishing LLC, 2002:7 .
