Abstract
BackgroundQuality of life weights based on valuations of health states are often used in cost utility analysis and population health measures. This paper reports on an attempt to develop quality of life weights within the Zimbabwe context.Methods2,384 residents in randomly selected small residential plots of land in a high-density suburb of Harare valued descriptors of 38 health states based on different combinations of the five domains of the EQ-5D (mobility, self-care, usual activities, pain or discomfort and anxiety or depression). The English version of the EQ-5D was used. The time trade-off method was used to determine the values, and 19,020 individual preferences for health states were analysed. A residual maximum likelihood linear mixed model was used to estimate a function for predicting the values of all possible combinations of levels on the five domains. The model was fit to a random subset of two-thirds of the observations, with the remaining observations reserved for analysis of predictive validity. The results were compared to a similar study undertaken in the United Kingdom.ResultsA credible model was developed to predict the values of states that were not valued directly. In the subset of observations reserved for validation, the mean absolute difference between predicted and observed values was 0.045. All domains of the EQ-5D were found to contribute significantly to the model, both at the moderate and severe levels. Severe pain was found to have the largest negative coefficient, followed by the inability to wash and dress oneself.ConclusionDespite a generally lower education level than their European counterparts, urban Zimbabweans appear to value health states in a consistent manner, and the determination of a global method of establishing quality of life weights may be feasible and valid. However, as the relative weightings of the different domains, although correlated, differed from the standard set of weights recommended by the EuroQol Group, the locally determined coefficients should be used within the Zimbabwean context.
Highlights
Quality of life weights based on valuations of health states are often used in cost utility analysis and population health measures
Instruments English descriptors of 38 different health states based on the different combinations of the five EQ-5D domains used in the original Measurement and Valuation of Health Group (MVH) study [8] were compiled on flash cards (See Appendices I and II). (Thirty-eight, rather than the original 42 health states were used, as unconscious and death were not valued, and two other states were excluded due to an administrative error)
Inconsistent data included responses in which all states were given the same value, fewer than three states were valued, or there were more than three logical inconsistencies
Summary
Quality of life weights based on valuations of health states are often used in cost utility analysis and population health measures. Cost-utility analysis is one method of investigating the relationship between the costs and benefits of health care that allows for comparison of different interventions across different health states. The quality-adjusted life year (QALY) forms the basic unit of measure in such evaluation and is the most widely used method for measuring health outcomes [2]. The QALY is the arithmetic product of data on quantity of life and quality of life. Whilst the former is typically measured in life years, the latter is measured in terms of utility weights. There is little consensus as to how these weights should be developed, but the measure should have at least interval properties and should represent the preferences of society [3]
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