Van Gool & Bridges
interventions should be chosen to maximise return and to minimise variance. Here the
concepts of portfolio theory can be used to minimise variance7.
The practical application of portfolio theory in a public health setting is problematic, as
there are limitations to current cost data and effectiveness data. There are also a number
of statistical complexities when dealing with the variance of CEA ratios8. The potential
use for portfolio theory is significant as it provides the policy maker with valuable
information on the optimal mix of interventions. This is a body of work that, despite a
number of important contributions over the last few years, requires further research.
Other diseases
This paper only examines one output; namely CHD deaths prevented. The very nature
of a CEA demands a single output measure. This leads to a limited view of the world,
as it can be argued that good nutrition can not only lead to the prevention of CHD, but
also to preventing diseases such as stroke, diabetes and some cancers. An even broader
view of the world would be to argue that good nutrition could lead to better well being.
Due to the parameters of the research question (the cost-effectiveness of nutrition
interventions in the prevention of CHD deaths), it is impossible to make any
conclusions about the cost-effectiveness of nutritional interventions on diseases
beyond CHD. This may result in an under-valuation of the benefits of nutrition
intervention, but we do not know to what extent.
Equity
A CEA examines the issue of producing a set of outcomes for least costs (see section 1
for a more detailed discussion of CEA). A CEA aims to maximise technical efficiency
but is incapable of revealing anything meaningful about equity. This is one of the
limitations of a CEA.
7 See Markowitz (1952) or Brealey and Myers (1991, ppl55-74)
8 See Polsky et al., Confidence Intervals for Cost-Effectiveness Ratios: A Comparison of Four Methods.,
Health Economics, Vol. 6: 243-252 (1997).
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Chere Project Report 11- November 1999