Norwegian Institute of Public Health,
e-mail erik.nord@fhi.no
December 21 2010
Priority to the worse off: Severity of current illness versus shortfall in life
time health.
DRAFT
In evaluating treatment
programs for different diagnostic groups, decision makers and the population at
large in a number of countries wish to give priority to those with more severe
current suffering and/or greater expected future losses of life years and
quality of life. Tools have been developed to incorporate such concerns in
formal economic evaluation of health programs. On the other hand, concerns for
equity in life time health are expressed in comparisons of health in different
socioeconomic or geographical groups. Data on the strength of societal
preferences for group equity in life time health are at present almost
non-existent. To collect such data is an interesting challenge for future
research, but it is not necessarily helpful to measure such preferences at a
cardinal level in terms of numerical trade-offs.
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A common
feature of ethical theories of fairness in resource allocation and of the
thinking of ordinary people about fairness in health care is that benefits are
considered to have greater value the worse off those who receive them are (Rawls,
1971; Daniels, 1993; Nord, 1999). Concerns for the worse off run counter to the
utilitarian idea that resources should be allocated simply with a view to
maximising overall health benefits.
Parfit (1991) refers to concerns for the worse off as ’The Priority View’. Brock (2001) offers a
number of possible justifications for the view, including the argument that the
worse off suffer undeserved relative deprivation, and/or that the worse off
have more urgent needs.
If
priority in health care is to be given to the worse off, there is first a
question of whether one should be concerned about those worse off in health or
those worse off overall, i.e. in their global life situation. While some would
argue in favour of the latter, there is probably less agreement about this than
about giving priority to those who are worse off in terms of health. In this
paper I focus on worse-offness in terms of health. Given this focus, I address
a question that has been raised regarding the time perspective of ‘worse-offness’:
Is being worse off a matter of being in
a bad state at a given point in time, or of having a bad prognosis, or of
having had a poor history of health, or perhaps all of these, i.e. of having large
health losses as judged over a whole lifetime?
The late British economist
Amartya Sen (2001) regards Williams’
approach as an interesting and potentially powerful one, particularly since it
seems to deal with social class inequality in a fulsome way. But he also
stresses its limitations for policy making. For example, Williams claims that
men are not getting their fair innings, insofar as their health adjusted life
expectancy is significantly lower than that of women. While acknowledging the
latter fact, Sen suggests that giving preference to male patients ’cannot but
lack some quality that we would tend to associate with the process (my italicising) of health equity’ (p.21). Sen thus warns against approaches that insist
on taking a single-dimensional view of health equity, stating that ’it is
possible to accept the significance of a perspective, without taking that
perspective to be ground enough for rejecting other ways of lookiing at health
equity, which too can be important’.
My own position is similar to that of Sen.
I hold that health can be defined and measured in several meaningful and policy
relevant ways, including ‘current’, ‘future’, ‘past’ and ‘life time’ health. Individuals’
scores on these different measures are correlated, partly because illness early
in life is empirically correlated with illness later in life, partly because
the concept of life time health subsumes past, current and future health. But the
correlations are not necessarily high. A person may be worse off than another
person an all measures, but he can also be worse off on one measure and at the
same time better off on another one. For
some allocation problems, decision makers may thus find it helpful to have descriptive information on worse-offness
on several or all of the possible health measures. At the same time, ethicists
and policy makers may have normative views
with respect to the relative weights
that should be assigned to different aspects of worse-offness in priority
setting between patients and patient groups.
In my own previous work on worse-offness I
have focussed on so-called ‘severity of illness’
(Nord, 1993; Nord et al, 1999). This includes current impairments and symptoms
and expected future loss of quality of life and/or length of life due to the
illness. The main reason for this focus is that official Norwegian guidelines
for priority setting in health care, proposed by the Ministry of Health and endorsed
by Parliament, since 1987 place great emphasis on severity of illness thus understood
(Norwegian Priorities Commission, 1987). By contrast, health losses in the past
or aggregate health losses over the whole life time have never since been
mentioned as relevant - let alone salient - factors for priority setting in Norwegian
policy documents. The same focus on the severity of current and future illness,
rather than on past health losses or life time health, is to be found in
official guidelines for priority setting in the early 1990s in the Netherlands,
New Zealand and Sweden (Dutch Committee on Choices in Health Care, 1992;
Campbell and Gillett, 1993; Swedish Priorities Commission, 1993), and in the
medical ethics literature (Daniels, 1993). Lately, the Dutch position has been
reinforced by a Government guideline saying that willingness to spend public
money in order to gain a QALY will range from 10.000 euros for conditions of
little severity to 80.000 euros for conditions of great severity (College voor
zorgverzekeringen, 2009)
So what do I then think of proposals – put
forward for instance by Williams (2001) - to focus more on shortfalls in health
over the whole life time and less on the severity of a person’s current and
future health problem?
My first answer is that the younger the person
or group in question, the less difference is there between focussing on current
and future severity and focussing on expected life time health. At birth there
is no difference.
On the other hand, in older intervention groups
focussing on life time health rather than on severity can make a big difference
for the valuation of a given health benefit. For instance, pain acquired at the
age of 70 may be more unpleasant than the symptoms of a pollen allergy acquired
at the age of 10. But the aggregate QALY loss over the whole life time may be
greater in the latter case than in the former. So whom is it more important to
treat with a new medicine – the 70-year old with the new pain or the 70 year
old with the old allergy?
I return to this question below, But first
I want to make a general point. I believe that the relevance of different
measures of worse-offness for societal priority setting and willingness to pay
for health benefits probably depends on the nature of the decision
problem. To see this, consider the two
following examples. In problem A, a national medicine administration is to determine
its willingness to spend public money on reimbursement of a new and better drug
for people with a given chronic illness X, compared to its willingness to pay
for reimbursement of a new and better
drug for people with a given chronic illness Y. Assume that those with
conditions X and Y are of all ages and that the two drugs yield the same health
benefit (measured for instance in QALYs). It then seems ethically plausible
that the willingness to pay be strongly
influenced by the degree of need
in the two patient groups - defined as the current and expected future health
losses associated with the two illnesses. In problem B, on the other hand, a regional
health authority is to determine its willingness to pay for a health education
program targeting adults living in an area where life expectancy at birth is 70
years, compared to its willingness to pay for such a program in an area where
life expectancy at birth is 80 years. In this case, it seems ethically
plausible that the regional health authority’s willingness to pay be higher in
the former area on account of that area’s poorer performance on life time
health.
Many more examples could be given. But I
think these two suffice to demonstrate that more than one measure of health and
worse-offness in health deserve a place in the economic evaluation and priority
setting tool box.
This said, there are some challenges facing
the use of life time health as a statistic for expressing worse-offness.
First, as already touched upon, focussing
on life time health losses may disadvantage elderly people who have lived most
of their life in good health but in old age come to need relief of – perhaps
severe – discomfort. Particularly if the fair innings argument is allowed to
prevail, relief of discomfort in the elderly will – all else equal - be given
less priority than similar relief in younger people (Nord, 2005). I find this
difficult to justify ethically. In publications following his initial 1997
paper,
Second, there is in priority setting in
national health services a de facto focus on current suffering and expected
future health losses. There is thus in a sense an ethical and political burden
of proof resting on those who argue in favour of a larger role for the life
time health approach in priority setting. I believe they need not to argue on a
general basis, but to consider carefully in which specific types of comparisons
and decisions it might be useful to supplement current evaluation practice with
life time health considerations. As indicated above, the usefulness is probably
greater in comparison of preventive programs for different social groups than in
comparison of treatment programs for different diagnostic groups.
Third, in specific decision problems where
life time health considerations are deemed salient, there are measurement
issues. One concerns level of measurement. In decisions about priority setting
between technologies and interventions for different diagnostic groups,
representation of population values in cardinal (numerical) terms has proved interesting
and useful for decision makers, cfr NICE’s heavy reliance on utility
measurements and QALYs in the UK and the recent Dutch introduction of varying
limits to willingness to pay for a QALY depending on the severity of the
targeted condition. The Norwegian Medicine Agency, in its continuous dealing
with applications from the pharmaceutical industry for having new drugs listed
for reimbursement, has expressed interest in numerical guidance similar to that
recently introduced in the
If one nonetheless should wish to incorporate
concerns for equity in life time health in numerical evaluations of health
programs, how should one go about establishing the strength of social preferences for giving priority to groups who
are disadvantaged? On this account, research in the past on the strength of
concerns for severity may have something to offer.
Table 1. Using the time
trade-off (TTO) and the person trade-off (PTO)
to determine weights for life
years gained in different social groups.
Social
group Life expectancy TTO
PTO Weights
1 80 5 30.000 1.0
2 76 2 15.000 1.5
3 72 1
10.000 2.5
Consider
table 1. Assume three different social groups (socioeconomic, geographical,
ethnic or other) with life expectancies at birth of 80, 76 and 72 years
respectively. Appropriate groups of reasonable people could be asked to
deliberate about a time trade-off (TTO) question: How many years of increased
life expectancy in group 1 and 2 would they deem as equally valuable as an
increase by one year of life expectancy in group 3? Median (or mean) answers,
or consensus answers, might for example be 5 and 2 years respectively.
Similarly, they could be asked to
deliberate about a person trade-off (PTO) question: How many persons in group 1
and 2 would have to gain a year of life expectancy for that to be deemed as
valuable as 10.000 people in group 3 obtaining such a one year gain? Median
answers (or the consensus answer) might for example be 30.000 and 15.000
persons respectively. The ratios expressed in the two sets of responses (TTO
and PTO) would most likely not be mathematically consistent with each other,
since different framings of problems are known to lead to different answers
(Kahneman and Tversky, 1979). But policy makers could take both sets of
responses into account and make a rough overall judgement. They might thus decide
that in formal economic evaluation of programs that reduce mortality risks in
different social groups, a set of weights for life years as those in the right
hand column of tablee 1 might be used in order to roughly capture societal
concerns for social group equity in life expectancy. In principle, concerns for
social group inequalities in quality
adjusted life expectancy, as measured in terms of QALYs or DALYs, can be
accommodated in the same way.
Weighting life years or QALYs or DALY gained
in different social groups is a rather simple way to incorporate concerns for
equity in life time health in formal program evaluation. A more sophisticated
approach is to use a societal valuation function of the form SV = Qa
x Eb, where Q is the total number of QALYs gained by a program and E
is the resulting degree of equality in life time health across individuals (Wagstaff,
1991; Norheim, 2010). The values of the parameters ‘a’ and ‘b’ are set such as
to reflect the importance that societal decision makers place on total QALY
gains relative to equality in life time health. The parameters thus express a
trade-off between these two concerns.
One challenge in this approach is to
decide who should be included in the measurement of equality. For instance, if
a program targets a population subgroup A, what is the total population in
which the resulting degree of equality in life time QALYs should be measured?
It can hardly be the whole population, since few programs are big enough to
have a noticeable effect on equality in the whole population. Should it be therefore be subgroup A plus
another subgroup B which is targeted by a competing program? But then, why
particularly program B rather than C or D or E? Presumably one would want to
look at a set of programs and value each of them in turn in the light of
resulting QALY gains and effects on equality measured across all the target
groups in question. The measurement of such equality effects is no small task.
Another challenge is to estimate the
parameters ‘a’ and ‘b’ through preference elicitations. This can be
complicated. For instance, in a study for NICE in the
Figure
1. Example of question about the trade-off between aggregate health and its
distribution.
Scenario
X Group 1: 60 years in full health, 8 years in poor
health.
Group 2: 56 years in full health, 8 years in poor
health.
Scenario
Y Group 1: 72 years in full health, 16 years in poor
health.
Group 2: 48 years in full health, 16 years in poor
health.
I conclude that in evaluating treatment
programs for different diagnostic groups, decision makers and the population at
large in a number of countries wish to give priority to those with more severe
current suffering and/or greater expected future health losses. Representation
of population values in cardinal (numerical) terms seems to be of interest to government
bodies working on a regular basis with technology assessment and priority
setting across diagnostic groups. By contrast, concerns for equity in life time health are mostly expressed in
comparisons of health in different socioeconomic or geographical groups. Data
on the strength of societal preferences for group equity in life time health
are at present almost non-existent. To collect such data is an interesting
challenge for future research. However, it is not clear that decision makers
will find it helpful to have such preference data at a cardinal level of measurement.
Acknowledgement: I am grateful
to Lars Granum and Morten Aaserud at the Norwegian Medicine Agency for earlier exchanges
on which I have drawn in this paper and to Einar Anders Torkilseng at the Norwegian Directorate for Health for
having provided useful comments to a draft version of the paper.
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for prioritising in health care.)’ NOU
1987:23.
Parfit, Derek. ‘Equality or priority.’ The Lindley Lecture. 1991. Copyright:
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