John McKie

Double jeopardy and the use of QALYs in health care allocation.

The use of the Quality Adjusted Life-Year (QALY) as a measure of the benefit obtained from health care expenditure has been attacked on the ground that it gives a lower value to preserving the lives of people with a permanent disability or illness than to preserving the lives of those who are healthy and not disabled. The reason for this is that the quality of life of those with illness or disability is ranked, on the QALY scale, below that of someone without a disability or illness. Hence we can, other things being equal, gain more QALYs by saving the lives of those without a permanent disability or illness than by saving the lives of those who are disadvantaged in these ways. But to do so puts these disadvantaged people under a kind of double jeopardy. Not only do they suffer from the disability or illness, but because of it, a low priority is given to forms of health care that can preserve their lives. This, so the objection runs, is unjust or unfair. This article assesses this objection to the use of QALYs as a basis for allocating health care resources. It seeks to determine what is sound in the double jeopardy objection, and then to show that the defender of QALYs has an adequate response to it.

Multiattribute Utility Instruments and Their Use

Health-related multiattribute utility (MAU) instruments are questionnaires, which measure an individuals health-related quality of life. They provide a formula for calculating a utility score from every combination of answers, i.e., for every health state defined by the questionnaire. The utility scores are designed primarily for economic evaluation of health-related programs. However, their use is not limited to this.

Who Should be Involved in Health Care Decision Making? A Qualitative Study

Most countries appear to believe that their health system is in a state of semi-crisis with expenditures rising rapidly, with the benefits of many services unknown and with pressure from the public to ensure access to a comprehensive range of services. But whose values should inform decision-making in the health area, and should the influence of different groups vary with the level of decision-making? These questions were put to 54 members of the public and health professionals in eight focus groups. Adopting a different perspective from other studies, participants were not asked if particular groups should be involved in decisions but rather through deliberation and discussion nominated their own potential decision makers. This delivered a clear message that participants saw a legitimate role for a broad range of stakeholders in priority-setting decisions so as to incorporate a diversity of expertise and opinion. Companion themes were the acknowledgment that decisions involve ethical judgments and are not purely technical, that the power of special interest groups (such as clinicians) should be kept in check, and that the process by which decisions are reached is important. The results suggest that qualitative methods of investigation have the potential to improve the legitimacy of policy decisions by contributing to a better understanding of the values of the public and health professionals, and by expanding the range of options available for further research.

The allocation of health care resources : an ethical evaluation of the 'QALY' approach

Contents: Introduction The background to the QALY Age discrimination Quality of life Double jeopardy Public opinion Conclusion Bibliography Index.

Severity as an independent determinant of the social Value of a health service

This paper has two objectives, first to review the relevant literature concerning the social importance of severity of pre-treatment condition, and second to present the results of a new analysis of the relationship between social value, individual assessment of health improvement and the severity of illness. The present study differs methodologically from others reported in the literature. The underlying hypothesis is that members of the public have an aversion to patients being in a severe health state irrespective of the reason for their being there, and that this aversion will affect the social valuation of a health program after taking account of the magnitude of the health improvement. This effect will be observable in a program which (compared to another) takes a person out of a severe health state—the usual case discussed in the literature—or in a program which (compared to another) leaves a person in a severe health state. The present study tests this second implication of the hypothesis. We present data consistent with the view that after taking account of health improvement, health programs are preferred which do not leave people in severe health states. Alternative explanations are considered and particularly the possibility that data reflect a social preference for individuals achieving their health potential. Both explanations imply the need to reconsider the rules for prioritising programs. In this analysis, Person Trade-Off (PTO) scores are used to measure social preferences (‘value’ or ‘social utility’) and Time Trade-Off (TTO) scores are used to measure individual assessments of health improvement and initial severity. Econometric results suggest that severity is highly significant and may more than double the index of social value of a health service.

Double jeopardy, the equal value of lives and the veil of ignorance: a rejoinder to Harris.

Harris levels two main criticisms against our original defence of QALYs (Quality Adjusted Life Years). First, he rejects the assumption implicit in the QALY approach that not all lives are of equal value. Second, he rejects our appeal to Rawlss veil of ignorance test in support of the QALY method. In the present article we defend QALYs against Harriss criticisms. We argue that some of the conclusions Harris draws from our view that resources should be allocated on the basis of potential improvements in quality of life and quantity of life are erroneous, and that others lack the moral implications Harris claims for them. On the other hand, we defend our claim that a rational egoist, behind a veil of ignorance, could consistently choose to allocate life-saving resources in accordance with the QALY method, despite Harriss claim that a rational egoist would allocate randomly if there is no better than a 50% chance of being the recipient.

Deriving health utilities from the MacNew Heart Disease Quality of Life Questionnaire

Introduction: Quality of life is included in the economic evaluation of health services by measuring the preference for health states, i.e. health state utilities. However, most intervention studies include a disease-specific, not a utility, instrument. Consequently, there has been increasing use of statistical mapping algorithms which permit utilities to be estimated from a disease-specific instrument. The present paper provides such algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and six multi-attribute utility (MAU) instruments, the Euroqol (EQ-5D), the Short Form 6D (SF-6D), the Health Utilities Index (HUI) 3, the Quality of Wellbeing (QWB), the 15D (15 Dimension) and the Assessment of Quality of Life (AQoL-8D). Methods: Heart disease patients and members of the healthy public were recruited from six countries. Non-parametric rank tests were used to compare subgroup utilities and MacNew scores. Mapping algorithms were estimated using three separate statistical techniques. Results: Mapping algorithms achieved a high degree of precision. Based on the mean absolute error and the intra class correlation the preferred mapping is MacNew into SF-6D or 15D. Using the R squared statistic the preferred mapping is MacNew into AQoL-8D. Implications for research: The algorithms reported in this paper enable MacNew data to be mapped into utilities predicted from any of six instruments. This permits studies which have included the MacNew to be used in cost utility analyses which, in turn, allows the comparison of services with interventions across the health system.

Allocating Healthcare By QALYs: The Relevance of Age

What proportion of available healthcare funds should be allocated to hip replacement operations and what proportion to psychiatric care? What proportion should go to cardiac patients and what to newborns in intensive care? What proportion should go to preventative medicine and what to treating existing conditions? In general, how should limited healthcare resources (people, facilities, equipment, drugs…) be distributed If not all demands can be met?

Diabetes and quality of life: Comparing results from utility instruments and Diabetes-39

OBJECTIVE To compare the Diabetes-39 (D-39) with six multi-attribute utility (MAU) instruments (15D, AQoL-8D, EQ-5D, HUI3, QWB, and SF-6D), and to develop mapping algorithms which could be used to transform the D-39 scores into the MAU scores. RESEARCH DESIGN AND METHODS Self-reported diabetes sufferers (N=924) and members of the healthy public (N=1760), aged 18 years and over, were recruited from 6 countries (Australia 18%, USA 18%, UK 17%, Canada 16%, Norway 16%, and Germany 15%). Apart from the QWB which was distributed normally, non-parametric rank tests were used to compare subgroup utilities and D-39 scores. Mapping algorithms were estimated using ordinary least squares (OLS) and generalised linear models (GLM). RESULTS MAU instruments discriminated between diabetes patients and the healthy public; however, utilities varied between instruments. The 15D, SF-6D, AQoL-8D had the strongest correlations with the D-39. Except for the HUI3, there were significant differences by gender. Mapping algorithms based on the OLS estimator consistently gave better goodness-of-fit results. The mean absolute error (MAE) values ranged from 0.061 to 0.147, the root mean square error (RMSE) values 0.083 to 0.198, and the R-square statistics 0.428 and 0.610. Based on MAE and RMSE values the preferred mapping is D-39 into 15D. R-square statistics and the range of predicted utilities indicate the preferred mapping is D-39 into AQoL-8D. CONCLUSIONS Utilities estimated from different MAU instruments differ significantly and the outcome of a study could depend upon the instrument used. The algorithms reported in this paper enable D-39 data to be mapped into utilities predicted from any of six instruments. This provides choice for those conducting cost-utility analyses.

Health Care Decision‐Making ‐ A Focus Group Study Involving Health Professionals and the General Public

Faced with an ageing population and newspaper warnings that escalating costs are leading to a health crisis, debate has intensified in Australia and elsewhere on the allocation of limited health resources. But whose values should inform decision-making in the health area, and should the influence of different groups vary with the level of decision-making? These questions were put to 54 members of the public and health professionals in eight focus groups. Unlike previous studies, participants were not asked if particular groups should be involved in decisions but rather through deliberation and discussion nominated their own potential decision-makers. This delivered a clear message that participants saw a legitimate role for a broad range of stakeholders in priority-setting decisions. The results suggest that qualitative methods of investigation have the potential to improve the legitimacy and accountability of policy decisions by contributing to a better understanding of the values of the public and health professionals.