A quality adjusted life year (QALY) is a common measure of health improvement used in cost-utility analysis; combines mortality and quality of life gains (outcome of a treatment measured as the number of years of life saved, adjusted for quality) (Pharmacoeconomics, 2003). QALY is product of the “quality of well-being” by the scale 0-10 (where 0 – death, 10 – perfect health), statistical probability that the health condition related to the quality of well-being will occur and the expected duration of that health condition. A disability adjusted life year (DALY) is a measure of losses of healthy life rather than life-years gained.
The DALYs integrate values for age-weighting and time-discounting. In other words, there is a unit used for measuring both the global burden of disease and the effectiveness of health interventions, as indicated by reductions in the disease burden. It is calculated as the present value of the future years of disability-free life that are lost as the result of the premature deaths or cases of disability occurring in a particular year (World Bank, 1996). DALY is a measure recommended for monitoring disease burden. The weakness of DALY is the controversy of age-weighting.
The incorporation of an age-weighting function is controversial and some authors recommend excluding this parameter from the calculation of DALYs. DALY has been subject to a number of criticisms as a measure of health status and as a tool for setting health priorities and are not encountered often in economic evaluations in some countries. The DALYs approach presents two methodological weaknesses: 1. the multiplication of disability duration by severity used for its computation has not been validated and 2. the valuation method used for the assessment of disability weight (i. e. disability severity) is hardly reliable and valid.
Therefore, the results depend greatly on the severity scale chosen. Some authors write that DALY approach does not solve the problem of prioritization and of resource allocation. Consequently, for QALY is more applicable in health economics. Do you think it is unethical to put a price on a life year? Assume someone says that the highest priority should be given to treating the patient and extending the life expectancy and that the costs are of no importance. With what estimate of society’s willingness to pay would this correspond? Of course, life is supreme value. Every human life.
But man who tells that costs are of no importance palters with facts. Unfortunately today there are no nations, which can afford to use this principle in their health care systems. It is too expensive. We need to develop the priorities. Ethical issues are very important but if you have no resources to provide proper health care you can only speak about ethics. We need measure which help us to manage promotive, preventive, curative and rehabilitative activities. Like the value of statistical life. The value of a statistical life divided by average life expectancy can be used to determine the value of one year of life.
This index can be determined by use of the three various approaches (W. Kip Viscusi W. K. & Aldy J. E. ): 1. Indirect methods use actual market behavior to infer the value placed on health or risk reduction. This information is used to estimate what individuals are willing to pay for a change in risk (and, indirectly, an increase at the chance of extended life). 2. Direct methods use hypothetical surveys to determine what respondents would be willing to pay for new medical treatment or an increase in safety to determine the value of a statistical life. 3. Conjoint analysis
The estimate of different agencies and researchers can vary in the wide interval. For example Viscusi and Aldy determine the value of statistical life as USD 7 mln. , the US Environmental Protection Agency (EPA, 2004) uses USD 6 mln. as the value of a statistical life in its analyses of regulatory issues. The differences between studies in presenting the value of a statistical year of life may reflect real differences in risk levels and types, their changes. An average value of one year of life for the United States are in the interval of USD 70,000-100,000.
… Do you think that gathering more data on the mortality rate would be helpful? Let’s calculate chances for extending the life of the patient. 1) Variant 1. He will refuse the elective operating. Odds for surviving: 0. 85=0. 7 (=(100-30)/100) + 0. 15 (=30*50/100*100). Odds for lethal exit: 0. 15 (=1. 0-0. 85). Data about the mortality among the non-operated patients with rupture of the aneurysm (i. e. at the pre-hospitals stage) are absent in the case study and ignored in the calculations. 2) Variant 2. This elderly man will have the operation.
Odds for surviving after operating 0. 95 (=(100-5)/100). Odds for the exit is only 0. 05 (1. 0-0. 95), but in the reality the mortality rate from the elective operation ranges from 0. 016 to 0. 11. Odds ratio for the exit without the elective operation: 3. 0=0. 15/0. 05. The variance for this odds ratio ln (ODDS)=1/15+1/5=0. 87. CI for odds (95%) = ln(ODDS)±1. 96 =ln3. 0±1. 82=(-0. 72 to 2. 92) This confidential interval can be converted back to the odds ration scale by taking the exponential of the interval on the log ratio scale (Sutton A.
J. , 2002): 95% CI for OR = (e-0,72 to e-2. 92) = (0. 5 to 18. 5) Thus the risk of the lethal exit during the next 10 years is significantly higher for patients who was not operated electively. We should recommend the operation for this patient. Gathering more information about the mortality in aneurysm treatment could influence on the limits of confidential interval (make it less). It will not crucial for clinical decision making because the statistical pattern will not change with increasing the sample size.
What are the strengths and limitations of the human capital method of valuing a human life? Human capital method is a method of estimating the indirect cost of illness based on the sum of the remaining lifetime earnings of each healthy individual of particular ages valued at labor market rates (eg average salaries). The concept of human capital has been estimated in literature (Vittadini G. ) by either the retrospective or prospective methods. The retrospective method is based on dealing with the cost of production. It is insufficient for various reasons.
It does not take into account the social costs, such as public investment in education, the variables concerning home conditions and community environments, and the genetic contribution to human capital, including health conditions. In the prospective method the human capital can be defined as the present actuarial value of an individual’s expected income related to his skill, acquired abilities, and education. However, the prospective method reduces the human capital investment to its monetary value in terms of an assumed flow of income, and it ignores the amount of investment in education, job training and other investments.
Human capital estimates of the economic value of life have been routinely used in the past to perform cost-benefit analyses of health programs (Landefeld JS, Seskin EP. 1982). The human capital approach values a health improvement on the basis of future productive value to society from being able to return to work. These values have to be added for activities that are outside traditional definitions of paid work, such as staying at home, being retired or unemployed, so this approach suffers from problems of how to value a number of health improvements.This is a narrow view of the value of improved health and is now not often used. (Grossman, M. (2000), Fleurence R. (2003)
1) A Method for The Estimation of The Distribution of Human Capital from Sample Surveys on Income and Wealth by Vittadini G. , Dagum C. , Lovaglio P. G. , Costa M. (nd) retrieved on 11/01/2004 from http://www. csmb. unimo. it/pubblicazioni/soattiva/soatt/costa_dagum_rel. pdf