Using stated preference discrete choice modelling to evaluate the introduction of varicella vaccination |
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Authors: | Hall Jane Kenny Patricia King Madeleine Louviere Jordan Viney Rosalie Yeoh Angela |
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Affiliation: | Centre for Health Economics Research and Evaluation (CHERE), Central Sydney Area Health Service and University of Techology, Sydney, Australia. janeh@chere.usyd.edu.au |
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Abstract: | Applications of stated preference discrete choice modelling (SPDCM) in health economics have been used to estimate consumer willingness to pay and to broaden the range of consequences considered in economic evaluation. This paper demonstrates how SPDCM can be used to predict participation rates, using the case of varicella (chickenpox) vaccination. Varicella vaccination may be cost effective compared to other public health programs, but this conclusion is sensitive to the proportion of the target population immunised. A choice experiment was conducted on a sample of Australian parents to predict uptake across a range of hypothetical programs. Immunisation rates would be increased by providing immunisation at no cost, by requiring it for school entry, by increasing immunisation rates in the community and decreasing the incidence of mild and severe side effects. There were two significant interactions; price modified the effect of both support from authorities and severe side effects. Country of birth was the only significant demographic characteristic. Depending on aspects of the immunisation program, the immunisation rates of children with Australian-born parents varied from 9% to 99% while for the children with parents born outside Australia they varied from 40% to 99%. This demonstrates how SPDCM can be used to understand the levels of attributes that will induce a change in the decision to immunise, the modification of the effect of one attribute by another, and subgroups in the population. Such insights can contribute to the optimal design and targeting of health programs. |
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Keywords: | stated preference discrete choice modelling immunisation |
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