Economic evaluations generally fail to incorporate elements of intangible costs and benefits, such as anxiety and discomfort associated with the screening test and diagnostic test, as well as the magnitude of utility associated with a reduction in the risk of dying from cancer. In the present analysis, 750 respondents were interviewed and asked to rank, according to priority, a number of alternative screening programme set-ups. Focus was on colorectal cancer screening and breast cancer screening. The alternative programmes varied with respect to number of tests performed, risk reduction obtained, probability of a false positive outcome and extent of co-payment. Stated preferences were analysed using discrete ranking modelling and the relative weighting of the programme attributes identified. Applying discrete choice methods to elicit preferences within this area of health care seems justified by the face validity of the results. The signs of the coefficients are in accordance with a priori hypotheses. This paper suggests that large-scale surveys focusing on individuals' preferences for cancer screening programmes may contribute significantly to the quality of economic evaluations within this field of health care.
The cost-effectiveness of a series of mutually exclusive colorectal cancer screening programmes with varying screening interval and target group are analysed. Costs and effects for 60 possible screening programmes are simulated on the basis of data collected from a randomized trial initiated in 1985 in Funen County, Denmark. The screening test applied is the unhydrated Hemoccult-II. The analysis identifies six efficient programmes with cost-effectiveness estimates ranging from 17000 to 42500 Danish kroner (DKK) per life-year.
OBJECTIVE: Economic evaluations such as cost-effectiveness and cost-utility analyses generally fail to incorporate elements of intangible costs and benefits, such as anxiety and discomfort associated with the screening test and diagnostic test, as well as the magnitude of utility associated with a reduction in the risk of dying from cancer. This paper seeks to include all costs and effects incurred by introducing mammography screening through the application of discrete ranking modeling. METHODS: In the present analysis, 207 women were interviewed and asked to rank, according to priority, a number of alternative breast cancer screening setups. The alternative programs varied with respect to number of tests performed, risk reduction obtained, probability of a false-positive outcome, and extent of copayment. Using discrete ranking modeling, the stated preferences were analyzed and the relative weighting of the program attributes identified. For a range of hypothetical breast cancer programs, relative utilities and corresponding willingness-to-pay estimates were derived. RESULTS: A comparison of cost and willingness to pay for each of the programs suggested that net benefits are maximized when screening person aged 50-74 years biennially. More intensive screening produces lower or similar levels of utility at a higher cost. CONCLUSION: Discrete ranking modeling can aid decision making by identifying inferior healthcare programs, i.e., programs that are more costly but less beneficial.
This paper presents a framework for comparison of screening programme designs, based on efficiency and cost effectiveness criteria. The design parameters, such as choice of screening interval, which population segments to screen and expected participation rates in the selected population segments, are varied simultaneously. The costs and effects for a range of existing and hypothetical screening programmes against cervical cancer are estimated, using a mathematical simulation model. On the basis of these estimates average costs per life year and marginal costs per life year are calculated for a range of programmes. These calculations result in the definition of a range of inefficient programmes. Moreover, it is illustrated that the cost effectiveness of the efficient screening programmes decreases at an increasing rate as programmes are intensified either by way of shortening the screening interval or extending the target population segment to encompass the very young and/or the very old. The conclusion of this paper is that one should probably not extend screening programmes against cervical cancer beyond screening women in the age group 25-59 years every 4 years. In addition, increasing the participation rate of this group is a more cost effective way of increasing the number of life years gained, rather than extending the target group or decreasing the screening interval.
This paper presents a framework for comparison of screening programme designs, based on efficiency and cost effectiveness criteria. Design parameters such as choice of screening interval and which population segments to screen are varied simultaneously. The costs and effects for a range of existing and hypothetical screening programmes for cervical cancer are estimated, using a mathematical simulation model. On the basis of these estimations incremental costs per life year are calculated for a range of programmes. Efficiency and cost effectiveness criteria indicate that extending screening programmes for cervical cancer beyond screening women in the age group 25-59 years every four years may not be optimal.
The life expectancy gain produced by a reduction in mortality can be determined by three different methods with respect to the timing of the gained life-years. One method adds the life expectancy gain to the expected end of life. Another method places the gain at the time of occurrence of the mortality reduction. A third method distributes the gained life-years over the maximum lifespan according to the differences in survival probabilities after and before the reduction in mortality. The three methods are all used in the literature together with a quasi-deterministic and a probabilistic approach to the notion of life expectancy. The counted numbers of gained life-years are the same, but due to different timing of life expectancy gains the discounted numbers are different. Several discounting models are identified when combining the three methods of counting with the deterministic and the probabilistic approaches to life expectancy. Some are symmetrical, some are not. However, most importantly, they come out with potentially very large differences in the discounted number of gained life-years. They differ by a factor of approximately (1 + r)e(a)-1, where r is a constant discount rate and e(a) is remaining life expectancy at age a, when the reduction of mortality occurs. For a new-born, discounting at 7% p.a., one discounting model provides a present value that is 150 times larger than another discounting model, the other models being in between. The various counting and discounting models for life expectancy gains are presented formally, graphically, and with numerical examples using Danish male mortality data. We show how three different discounting models provide large differences in discounted life expectancy gains and hence cost-effectiveness ratios in an economic evaluation of a colorectal cancer screening programme in Denmark. These different discounting models co-exist in the evaluation literature. Choice of method is rarely made explicit. Sensitivity analysis with respect to this choice is even rarer. We argue that one counting-discounting model is sufficient and that this should be to discount the differences between the two survival probability curves.
This paper seeks to shed light on the relative cost effectiveness of colorectal cancer by comparing the cost effectiveness of this programme with the economics of another screening programme which is widely implemented: cervical cancer screening. The paper illustrates the principles of optimal resource allocation, and discusses the limitations and strengths of the analysis presented. The paper concludes that colorectal cancer is a cost effective option relative to cervical cancer screening when health is seen as the only outcome of the screening programmes. However, further insight into consumer preferences and inclusion of intangible costs and benefits is necessary in order to guarantee optimal resource allocation.