DALY Versus QALY: Two Ways to Measure Health Loss

If a health report hands you a single number that is supposed to capture both how long people live and how well they live, it is almost certainly a QALY or a DALY, and the first thing to work out is which one, because the two run on opposite scales. A quality-adjusted life year (QALY) counts health that is kept or gained, where a full year in perfect health scores 1. A disability-adjusted life year (DALY) counts health that is lost, where a year lost to death or disability scores 1. Same shape, opposite meaning.

Key points#

• Both metrics multiply time by a quality weight to turn length and quality of life into one figure.
• QALYs run upward: 1 is full health, 0 is death, and you want more of them.
• DALYs run downward: 0 is full health, 1 is a year of healthy life lost, and you want fewer of them.
• QALYs drive value-for-money decisions; DALYs describe how much health a population is losing.
• The weights behind them are built differently, so you cannot simply flip one into the other.

Start with the QALY: health you can bank#

The QALY grew out of health economics, and it works like a savings account for health. Take the time someone spends in a given state of health and multiply it by a quality weight, usually called a utility, that runs from 1 for full health down to 0 for death. A year lived at a utility of 0.8 is worth 0.8 QALYs. Five years at that level are worth 4. The better the health and the longer it lasts, the more QALYs pile up.

Where do the utilities come from? Usually from a standardized questionnaire such as the EQ-5D, which describes a health state across a handful of dimensions like mobility, pain, and anxiety. Those descriptions are then converted into a single value using preferences collected from the general public, so the weight reflects how ordinary people rate living in that state rather than a clinician's judgment alone.

Because QALYs accumulate, they are the natural currency for asking whether a treatment is worth its price. Divide the extra cost of an intervention by the extra QALYs it delivers and you get a cost per QALY, a figure that puts a cancer drug, a hip replacement, and a screening program into the same units so a health system can compare them. Bodies that appraise value, such as the United Kingdom's NICE, judge treatments against a cost-per-QALY threshold. Notably, one analysis of NHS spending estimated the real opportunity cost at roughly £10,000 per QALY, below the thresholds often cited in policy debate, a reminder that these anchors are estimates rather than fixed truths.

Now the DALY: health written off as a loss#

The DALY comes from epidemiology rather than economics, and it flips the sign. It is the working currency of the World Health Organization's Global Burden of Disease project, and WHO frames one DALY as one year of healthy life lost. Instead of a savings account, think of it as a ledger of debt: the more disease a population carries, the more DALYs it runs up.

That total is the sum of two parts. Years of life lost (YLL) count premature death, comparing the age at each death against a standard life expectancy, so a death at 30 books far more lost years than a death at 80. Years lived with disability (YLD) count the toll of living with a condition: how many people have it, for how long, and how heavily it presses on their health.

That last piece rests on a disability weight, and its scale is where most confusion starts. A disability weight runs from 0 for a year in full health up to 1 for a state judged as bad as death. A mild, well-managed condition earns a small weight; a severe, disabling one earns a large weight. Because a DALY tallies something unwanted, the arithmetic is set up so that worse health produces a bigger number. That lets public health put very different problems, from road injuries to depression to diabetes, on one footing and see where a population's health is draining away fastest.

The trap: identical-looking numbers, opposite meaning#

The cleanest way to keep the two straight is to watch which way the scale points. A weight of 1 is the best outcome you can have in a QALY analysis and the worst outcome on a disability weight. QALYs are something to maximize; DALYs are something to minimize. Read a table without checking which convention is running and you can take a result exactly backward, mistaking a heavy burden for a strong benefit.

The gap runs deeper than direction. In a careful side-by-side published in Health Policy and Planning, Franco Sassi showed that quality weights and disability weights are constructed differently and are not the same numbers with the signs reversed. QALY utilities are typically preference-based values drawn from population surveys, while DALY disability weights have historically come from separate structured valuation exercises. The two approaches have also differed in details such as age weighting, which classic DALY calculations once applied and QALYs generally did not, and in how future years are discounted. So converting one into the other is an approximation, and Sassi's worked examples show the two can pull apart for the very same intervention.

Burden and value are different questions#

Even set side by side, the two metrics answer different things. A DALY figure describes a burden: how much health a population is losing to a condition, and where the largest gaps sit. A QALY figure feeds a decision: whether the health a specific intervention buys is worth what it costs. High burden does not automatically mean good value. A condition can rack up an enormous DALY total while offering few cost-effective ways to shift it, and a modest-burden condition can still be worth funding because an intervention delivers QALYs cheaply.

Neither number is a verdict on what a person's life is worth. Both are accounting tools that make otherwise incomparable health outcomes comparable, each carrying its own assumptions.

A reading checklist#

When a burden or value study lands on your desk, four quick questions keep you honest:

1. Which metric is it, a QALY or a DALY?
2. Which way does the scale point, is 1 the best state or the worst?
3. Where did the weights come from, whose preferences and which instrument?
4. Is the study describing a burden or appraising a decision?

Answer those four, and the two most common numbers in health policy stop reading as interchangeable jargon and start telling you two genuinely different stories.