Quality of Life Newsletter 23/1999.

Erik Nord, National Institute of Public Health, P.O.Box 4404 Torshov, N-0403 Oslo, Norway.

phone: 47 22 04 23 42, fax: 47 22 04 25 95, e-mail:



Health state values from multi-attribute utility instruments such as the EQ-5D and the HUI need to be transformed before they can be used to estimate the societal value of different health interventions. Without transformation the values lead to a very strong overestimation of the value of interventions for moderate conditions relative to interventions for severe or fatal conditions. A rough transformation function is offered for a number of MAU instruments. For a different solution, see paper on cost-value analysis (click).


Cost-utility analysis (CUA) is a widely used technique for judging whether health technologies and programs give adequate value for money. In CUA, the value of health care is measured in terms of the degree to which the care is appreciated personally by the individuals concerned. This concept of value is operationalised as a product ot two factors: The increase in quality of life – often referred to as utility - that follows from an intervention, and the number of years a person gets to enjoy this increase. The unit of measurement of value in this approach is the quality adjusted life year (QALY). The underlying idea of the approach is that medical technologies with low costs per QALY gained should be given priority over those with high costs per QALY gained (1).

The Canadian Coordinating Office for Health Technology Assessment recommends cost-utility analysis as one of two preferred analytical techniques for economic evaluation of pharmaceuticals (2). The other recommended technique is cost-benefit analysis. Similar recommendations, although not as strong, have been published by the Pharmaceutical Benefits Pricing Authority in Australia (3).

A number of so called multi-attribute utility (MAU) instruments are available for assigning quality of life scores (utilities) to health states (for a review, see 4). CCOHTA recommends three of these as particularly suitable for use in QALY calculations: The Quality of Well-Being Scale (5), the Health Utilities Index (6) and the EQ 5-D (7).

In spite of the endorsement of these instruments by CCOHTA, unclarity prevails regarding the meaning of numbers from MAU-instruments (8). The purpose of this paper is to address a problem of validity in using such instruments to estimate the societal value of health programs, and to offer a simple tool that to some degree may remedy this problem.


The problem

The idea of giving priority to health care programs according to their cost per QALY is based on the assumption that society’s appreciation of a health care program is proportional to the sum of QALY gains, regardless of how these gains are distributed across individuals in the program. Given this assumption, utilities for health states have implications for resource allocation decisions in terms of equivalence of numbers of people treated. For example, saving the life of one healthy person will be equivalent to curing two people with utility 0.5 and curing ten people with utility 0.9 (assuming equal duration of benefit). Such equivalence judgements are often referred to as ’person trade-offs’.

CCOHTA notes that society may have concerns for fairness that run counter to simple QALY maximisation. To capture such concerns, it may, according to CCOHTA, be of interest ’in some studies, for some decision makers to explore the impact of using direct person trade-off questions … to establish society’s valuation of different health programs relative to each other’. CCOHTA points out that ’if the approach gives dramatically different answers to the resource allocation question versus QALY methods, then a discussion of the reasons could be quite enlightening for the decision makers’ (2, p.28).

A review of direct person trade-off preference studies in Australia, England, Norway, Spain and the US (9) indicated a strong concern for giving priority to the worst off: Life saving procedures were valued considerably higher than treatments even for severe non fatal conditions and treatments for severe conditions were valued many time higher than treatments for moderate conditions. Later studies support these findings (10-13). If health state values are to be consistent with this structure of concern, scores for severe problems need to be much higher than zero, and scores for moderate problems need to be compressed to the upper end of the 0-1 scale. Table 1, reproduced from (9), uses three example levels of severity to indicate ’rules of thumb’ for scoring health states in accordance with the above person trade-off evidence (line 1: ’societal values’). The table further shows what scores the three example states would roughly obtain if mapped into and scored by various existing MAU-instruments. (Documentation released recently on the scoring function of the latest version of the Health Utilities Index (HUI III) suggests that this instrument yields utilities much similar to those of HUI II (14)).The general picture is that existing MAU-instruments lack the compression of states to the upper end of the scale that is required to encapsulate societal concerns for the worst off.

Table 2 illustrates the problem in the case of the three MAU-instruments that are recommended by the CCOHTA. According to the societal rules of thumb, an intervention that prevents death and instead leaves a person with a considerable problem is valued in the order of ninety times more than an intervention that eliminates a moderate problem (assuming the same duration of the benefit). The former intervention thus justifies in the order of ninety times higher costs per person helped than the latter. By contrast, according to the QWB, HUI-II and the EQ-5D, the former intervention would be less cost-effective than the latter if the cost-ratio exceeds not 90:1, but only 3:1, 9:1 and 2:1 respectively. Similarly, an intervention that reduces a considerable problem to a moderate problem actually justifies seven times higher costs than the cure of a moderate problem. According to the QWB, the HUI-II and the EQ-5D the maximum cost-ratios are 0.5:1, 3:1 and 0.3:1 respectively. The discrepancies are huge.

A suggestion for economic evaluation of pharmaceuticals

Direct person trade-off data are still too scarce to allow precise estimates of societal values for health states for use in resource allocation decisions. On the other hand, the evidence does indicate roughly in what parts of the 0-1 scale health states need to be located if they are to be consistent with societal preferences in such decisions. It seems, therefore, that analysts who wish to use MAU-instruments in economic evaluations of health programs and technologies may already at this stage improve their performance by conducting two analyses: One being a conventional cost-utility study, in which the utilities from generic instruments are used as they stand, and the other being a study in which the utilities are transformed into numbers that also encapsulate concerns for severity. The term ’cost-value analysis’ has been suggested for the latter, broader approach (15).

Figure 1 is offered as a simple tool to help conduct the required transformations. The figure uses the utilities in table 1 and the middle numbers in each of the intervals in the societal values in the first line of the table. The figure indicates the functional relationship between utilities and societal value numbers for each of the MAU- instruments in the table.


Assume that a choice is to be made between a health program that will cure 100 people of a given condition A and an equally costly program that will take 30 people from a condition B to a functional level corresponding to condition A. Assume that life expectancy is 20 years for patients in both programs, and that conditions A and B are assigned utilities 0.8 and 0.4 respectively if the Health Utilities Index (Mark II) is used. The former program then yields 100x(1-0.8)x20 = 400 QALYs (undiscounted), while the latter yields 30x(0.8-0.4)x20 = 240 QALYs. A cost-utility analysis based on HUI-II thus suggests that the former program should have priority. However, according to figure 1, HUI utilities of 0.4 and 0.8 correspond roughly to societal values of 0.75 and 0.96. These numbers encapsulate societal preferences for severity per se. Using these numbers instead of the simple utilities changes the value score of the former program to 100x(1-0.96)x20 = 80 and the value score of the latter program to 30x(0.96-0.75)x20 = 126. In other words, the suggested preference order is reversed, the reason being the explicit introduction of societal concerns for severity per se.


Concluding remarks

Clearly figure 1 is a very rough tool. Considerably more data are needed to estimate the transformation functions more precisely and for a wider range of the 0-1 value scale. Figure 1 could nonetheless presumably be useful, inasmuch as it is better to try to be roughly right rather than precisely and systematically wrong when estimating societal value. By doing a study based on transformed numbers as an add-on to a conventional cost-utility study, one would be complying with the suggestion made by CCOHTA, namely to ’explore the impact of using direct person trade-off questions to establish society’s valuation of different health programs relative to each other’ (2). If the two analyses give different answers, ’then a discussion of the reasons could be quite enlightening for the decision makers’ (2).




1. Weinstein MC, Stason WB. Foundations of cost-effectiveness analysis for health analysis and medical practice. New England Journal ofr Medicine 1977,296,716-721.

2. Canadian Coordinating Office for Health Technology Assessment. Guidelines for economic evaluation of pharmaceuticals: Canada. 2nd ed. Ottawa: CCOHTA 1997.

3.Langley PC. The November 1995 revised Australian guidelines for the economic evaluation of pharmaceuticals. Pharmacoeconomics 1996, 341-352.

4.Nord E. A review of synthetic health indicators. Background paper for the OECD Directorate for Education, Employment, Labour and Social affairs, June 1997.

5.Kaplan RM, Anderson JP. A general health model: Update and applications. Health Services Research, 1988,23,203-235.

6. Feeny D, Furlong W, Torrance G. The Health Utilities Index: An Update. Quality of Life Newsletter no 22/1999.

7. De Charro F, Rabin R. EQ-5D from the EuroQol Group: An Update. Quality of Life Newsletter no 22/1999.

8. Nord E, Wolfson M. Multi-attribute health state valuations: Ambiguities in meaning. Quality of Life Newsletter no 21/1999.

9.Nord E. Health status index models for use in resource allocation decisions. A critical review in the light of observed preferences for social choice. International Journal of Technology Assessment in Health Care 1996, 12,31-44.

10.Pinto Prades, José-Luis. Is the person trade-off a valid method for allocating health care resources? Health Economics 1997,6, 71-81.

11.Richardson J. Critique and some recent contributions to the theory of cost utility analysis. Working paper no 77. Melbourne: Centre for Health Program Evaluation. 1997

12.Ubel PA, Kamlet M, Scanlon D, Loewenstein G. Individual utilities are inconsistent with rationing choices: A partial explanation of why Oregon’s cost-effectiveness list failed. Medical Decision Making 1996,16,108-119.

13.Ubel P. How stable are people’s preferences for giving priority to severely ill patients? Mimeo. Philadelphia: Veterans Affairs Medical Center 1997.

14. Furlong W, Feeny D, Torrance G et al. Multiplicative multi-attribute utility function for the Health Utilities Index Mark 3 (HUI3) system: A technical report. Paper 98-11. Hamilton: CHEPA 1998.

15. Nord E, Pinto JL, Richardson J, Menzel P, Ubel P. Incorporating societal concerns for fairness in numerical valuations of health programs. Health Economics 1999,8,25-39.




Table 1. Societal values for health states versus individual utilities from MAU-instruments.


Problem level (a)






Societal values







< .80




< .85









York EuroQol (TTO)








IHQL (complex)




15 D








(Source: 9)

  1. The three states were described as follows:

Severe: Sits in a wheel-chair, has pain most of the time, is unable to work.

Considerable:   Uses crutches for walking, has light pain intermittently, is unable to work.

Moderate: Has difficulties in moving about outdoors and has slight discomfort, but is able to do some work and has only minor difficulties at home.



Table 2. Values of health improvements according to societal rules of thumb and utilities from three MAU-instruments.


(better state vs initial state:

Societal value




Considerable problem vs ’as bad as dead’





Moderate vs considerable problem





Healthy vs moderate problem