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Appendix to 14 March 2003 NZMJ viewpoint article ‘PHARMAC measures savings elsewhere to the health sector’: Quality-adjusted life years saved (QALYS) and how to measure them Health interventions ultimately aim to extend life expectancy and/or enhance health and independence. They do this by curing or ameliorate illness and disability, and/or preventing or delaying the onset or worsening of illness, disability and premature death. These outcomes, although different, can be in theory covered by single measures such as qualityadjusted life years saved (QALYS), which combine all aspects of benefits in the same way. The concept of the QALY was first introduced in 1968, and QALYs are extensively used in health sectors worldwide to inform resourcing decisions. Further details can be found in standard texts such as Drummond MF, O’Brien B, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes, 2nd edition. Oxford: Oxford University Press, 1997. Common end-points such as QALYS are termed “utilities”, and measure the benefit part of costutility analyses. This differs from what happens in formal cost-benefit analyses, where benefits are all measured in monetary terms. QALYS incorporate an intervention’s impact on both death and illness and the effects of side effects.: Benefits (QALYs) = Number of quality-adjusted years saved through preventing or delaying premature death + number of quality adjusted life years gained through illness avoided or delayed - number of quality-adjusted life years lost from side effects - loss of benefits from substitution for other drugs or treatment regimes.

years gained through premature deaths prevented

quality-adjusted years gained, non-fatal events and illness prevented

net benefits (QALYs)

quality-adjusted years lost, drug side-effects

QALYS therefore measure the product of {change in life expectancy} and {change in quality of life} resulting from treatment.

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We can look at how to calculate marginal QALY gains in a thoertical example of a proposed intervention (“Service A”) versus the default, existing, or alternative (“Service B”, which might be doing nothing) . The formula for assessing the marginal QALY gain obtained from Service A relative to Service B is: [(Qa-Qb)] * Dur] Quality of Life Benefit + [(LEa - LEb) * Qb] Life Expectancy Benefit

The components of this formula are depicted geometrically in Figure 1 below. Note the marginal QALY value will be negative when the QALY gain from Service B exceeds that of Service A. Figure 1

QALYs where QoL improves for some of the time (Dur), then longevity increases (but not QoL)

1.0 0.9 Qa 0.8 0.7 0.6 Qb 0.5 0.4 0.3 0.2 0.1 0.0 0 1 2 3 4 5 6 7 year 8 9 10 11 12 13 14 Dur LEb LEa increased life expectancy = (LEa-LEb)*Qb improved quality of life =(Qa-Qb)*Dur service A service B

In this example, with service B (maybe conventional therapy) quality of life 0.6, with life expectancy of around 9.5 years (i.e. 50% of patients - the average patient - will die by 9.5 years). However, use of Service (or intervention or programme) A improves quality of life in these patients for the first 7.5 years (after which effects fade), moving up to 0.9, i.e. an improvement of (0.9 - 0.6 =) 0.3 over duration 7.5 years. Service A also improves longevity, with life expectancy rising to 11.5 years, i.e. an increase of (11.5 – 9.5 =) 2.0 years. This translates to (0.3*7.5 + 0.6*2 =) 3.4 QALYS through both improving quality of life and increasing life expectancy. There are other possibilities. For instance, both longevity can increase and QoL improve over entire (lengthened) life expectancy, as might happen in life-saving interventions which also prevent the effects of non-fatal sequelae (figure 2):

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quality of life (QLHQ score)

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Figure 2

QALYs where both longevity increases and QoL improves over entire lengthened life expectancy service A

1.0 0.9 Qa service B improved quality of life =(Qa-Qb)*Dur, = (Qa-Qb)*LEb (where Dur = LEb)

quality of life (QLHQ score)

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0

Dur

Qb increased life expectancy = (LEa-LEb)*Qa

LEb 1 2 3 4 5 6 7 year 8 9 10

LEa 11 12 13 14

A variation might be where QoL improves, without any change in life expectancy. Examples might include disability support services that enhance QoL by improving independence (figure 3): Figure 3

QALYs where QoL improves without any effects on life expectancy

1.0 0.9 Qa

quality of life (QLHQ score)

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0

improved quality of life =(Qa-Qb)*Dur, = (Qa-Qb) (where Dur = LEa = LEb)

Dur

Qb (no change in life expectancy; LEa = Leb) service A service B LEb LEa 1 2 3 4 5 6 7 year 8 9 10 11 12 13 14

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On the other hand, life expectancy might increase, but at the expense of worsened QoL over the remainder of life. This might happen, for instance, with some forms of vigorous cancer treatments (figure 4): Figure 4

QALYs where longevity increases but at the expense of worsened QoL

1.0 0.9 worsened quality of life =(Qa-Qb)*Dur, = (Qa-Qb)*LEb (where Dur = LEb) Dur Qa Qb 0.5 0.4 0.3 0.2 0.1 0.0 0 1 2 3 4 5 6 7 year 8 9 10 11 12 13 14 LEb LEa increased life expectancy = (LEa-LEb)*Qb service A service B

quality of life (QLHQ score)

0.8 0.7 0.6

Of course, some interventions may increase both life expectancy and QoL in the medium to long term, but at the expense of some worsening of QoL in the short term. An example of this might be some forms of major surgery (figure 5):

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Figure 5

QALYs where longevity increases and QoL worsens shortterm (yr1) but then improves over rest of lengthened life expectancy 1.0

0.9

quality of life (QLHQ score)

Qa, yr>1 change in quality of life =sum of (Qa-Qb) for each year of Dur (where Dur = LEb) (ie Dur = LEa)

0.8 0.7 Qb 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0 1

service A service B

Qa, yr1

increased life expectancy = (LEa-LEb)*Qa

Dur

LEb 2 3 4 5 6 7 year 8 9 10

LEa 11 12 13 14

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