Value Of Life Year Research Articles

The value of aortic valve replacement in elderly patients: An economic analysis

Economists have designed frameworks to measure the economic value of improvements in health and longevity. Heart valve replacement surgery has significantly prolonged life expectancy and quality of life. For the example of aortic valve replacement, what is its economic value according to this framework? From 1961 through 2003, a total of 4617 adult patients underwent aortic valve replacement by one team of cardiac surgeons. These patients were provided with a prospective lifetime follow-up service. As of 2005, observed follow-up was 31,671 patient-years, with a maximum of 41 years. A statistical model was used to generate the future life-years of patients currently alive. The value of life-years proposed by economists was applied to determine the economic value of the additional life given to these patients by aortic valve replacement. The total life-years after aortic valve replacement were 53,323, with a gross value of 14.6 billion dollars. The total expected life-years without surgery were 10,157, with an estimated value of 3.0 billion dollars. Thus the net life-years gained by AVR were 43,166, worth 11.6 billion dollars. Subtracting the 451 million dollars total lifetime cost of surgery, the net value of the life-years gained by AVR was 11.2 billion dollars. The mean net value decreases according to age at surgery but is still worth 600,000 dollars for octogenarians and 200,000 dollars for nonagenarians. According to the economic concept of the value of a statistical life, the return on the investment for aortic valve replacement is enormous for patients of all ages, even very elderly patients.

Limitations of the methods used for calculating quality-adjusted life-year values.

To test the validity of the techniques used to calculate quality-adjusted life-year (QALY) values based on utility functions, using a real population dataset. Using the standard gamble technique, we gathered the preferences of a population sample of 189 individuals on a combination of probabilities concerning four simple health states (no physical disability, limp, walk with crutches and need a wheelchair), and three life-year spans (5, 10 and 15 years). Each of the four assumptions of the multiplicative model was tested based on the results of the experiment. The utility of the health state "limp" was high at 0.89 and that of "walk with crutches" only slightly lower at 0.85. However, of the 189 individuals, only 57 are not in contradiction with the assumption of mutual utility independence since they strictly preferred (15 years, "need a wheelchair") over (10 years, "need a wheelchair") and (15 years, "need a wheelchair") over (5 years, "need a wheelchair"). For these 57 individuals, the results of this study do not fit the assumptions underpinning the multiplicative model. This work suggests that the techniques used as a basis from which to calculate QALY values are flawed. In particular, the underlying assumptions of the multiattribute utility model do not correspond to behaviour patterns observed in a real population. It therefore appears that use of the QALY technique should be questioned in healthcare decision-making settings.

The cost-effectiveness of routine histologic examination.

Although the histologic examination of routine tissues, such as hernia sacs and intervertebral disks, has shown a low incidence of detecting clinically significant unsuspected disease, the cost-effectiveness of histologic examination has not been determined. By using a theoretical model that assumed variable costs and gains in life expectancy secondary to detecting clinically significant disease, a threshold incidence of disease detection at which histologic examination is cost-effective was determined. By using the University of lowa (Iowa City) cost of examination (approximately $25), at least 1 of every 2,000 examinations would have to show clinically significant disease for histologic examination to be cost-effective. This threshold incidence decreases as production costs decrease or life-year values increase. Before definitive policy conclusions can be made, additional studies are needed to better define the trade-off between cost and the value of information and the incidence of detecting clinically significant disease.