Some Strategies to Reduce Risk tion of the methods is found in box 5.1, while full details of the methods and the calcula tions can be found on the WHo web site. 6 It is not much value to provide decision-makers with information on the costs and effectiveness of interventions that are undertaken badly. Accordingly, the results reported here show what would be achieved if the interventions were undertaken in a relatively efficient manner. For example, we assume capacity utilization of 80% in most settings -for example, staff and capital equipment are fully occupied for 80% of the normal working day except when estimating the effect of expanding coverage to very high levels. To reach% of the population it might be necessary to provide facilities in isolated areas where popula tion numbers are insufficient to support such high rates of capacity utilization.The results, therefore, provide guidance on selected interventions that should be given high priority in the policy debate about resource allocation, but only if they are undertaken in an efficient manner Sets of interventions that interact in terms of effectiveness or costs are considered to gether, as stated earlier. For example, interventions to reduce risks associated with hyper- tension and high cholesterol interact. The analysis is based on estimates of the effects on population health of reducing blood pressure alone, reducing cholesterol levels alone, and doing both toget In addition, many of the interventions are evaluated at different levels of coverage. For most, three levels were used (50%, 80%and 95%)and the impact on costs and effects of expanding coverage was incorporated The standard practice in this type of analysis is to discount both the health effects and the costs of the different programmes under consideration. There is no controversy about 5.1 Methods for cost-effectiveness analysis The cost-effectiveness analysis on which this terventions or combinations of interventions. For quantities of inputs required to run each inte reportis based considered what would have hap- example, based on data from earlier chapters, vi- vention were estimated by experts in 17 regions ned if a set of interventions had not been tamin A deficiency increases the risk of dying from of the world and validated against the literature implemented and compared the result with what diarrhoea. The impact of vitamin A supplementa- Some individual-level costs were obtained by happens on their implementation. Through a tion is then mediated in the model by a decrea multiplying unit costs of inputs by the expected four-state population model, the number of in case fatality rate for diarrhoea Effectiveness data utilization of those inputs by the people covered ed over a period of a hun- came from systematic reviews where available. The by the programme. Unit costs for outpatient vis- dred years by a population in the absence of that difference in the healthy life years gained by the its and laboratory tests were obtained from a set of interventions is estimated by inputting population with and without the intervention is review of literature and supplemented by pri parameters of incidence, remission, cause-spe- the impact of the intervention and is entered as mary data from several countries. The total costs valuations reflecting the natural history of the Costs covered in this analysis indude expenses stitutes the denominator of the cost-effective- disease. The parameters reflecting the natural associated with running the intervention, such as ness ratio history of the disease were mostly estimated by administration, training and contact with the me- Stochastic uncertainty analysis was carried back-adjusting current rates using coverage and dia. They also indude costs incurred at the indi- out for key parameters in both the numerator known effectiveness of interventions. The same vidual level such as counselling. Considerableeffort and denominator four-state population model can then be rerun, was exerted to try to standardize the methodol reflecting changes in the parameters due to in- ogy used in collecting and classifying costs. The Sources: (3, 17-19). 5 This is important to keep in mind when benchmarking the estimates in this chapter against those re- sewhere, usually in US dollars. International dollars are derived by dividin by an estimate of their purchasing power parity(PPP)compared to a USS PPPs are the rates of currency onversion that equalize the purchasing power of different currencies by eliminating the differences in s price levels between countries.Some Strategies to Reduce Risk 107 tion of the methods is found in Box 5.1, while full details of the methods and the calcula￾tions can be found on the WHO web site.6 It is not much value to provide decision-makers with information on the costs and effectiveness of interventions that are undertaken badly. Accordingly, the results reported here show what would be achieved if the interventions were undertaken in a relatively efficient manner. For example, we assume capacity utilization of 80% in most settings – for example, staff and capital equipment are fully occupied for 80% of the normal working day – except when estimating the effect of expanding coverage to very high levels. To reach 95% of the population it might be necessary to provide facilities in isolated areas where popula￾tion numbers are insufficient to support such high rates of capacity utilization. The results, therefore, provide guidance on selected interventions that should be given high priority in the policy debate about resource allocation, but only if they are undertaken in an efficient manner. Sets of interventions that interact in terms of effectiveness or costs are considered to￾gether, as stated earlier. For example, interventions to reduce risks associated with hyper￾tension and high cholesterol interact. The analysis is based on estimates of the effects on population health of reducing blood pressure alone, reducing cholesterol levels alone, and doing both together. In addition, many of the interventions are evaluated at different levels of coverage. For most, three levels were used (50%, 80% and 95%) and the impact on costs and effects of expanding coverage was incorporated. The standard practice in this type of analysis is to discount both the health effects and the costs of the different programmes under consideration. There is no controversy about 5 This is important to keep in mind when benchmarking the estimates in this chapter against those re￾ported elsewhere, usually in US dollars. International dollars are derived by dividing local currency units by an estimate of their purchasing power parity (PPP) compared to a US$. PPPs are the rates of currency conversion that equalize the purchasing power of different currencies by eliminating the differences in price levels between countries. 6 www.who.int/evidence Box 5.1 Methods for cost-effectiveness analysis The cost-effectiveness analysis on which this report is based considered what would have hap￾pened if a set of interventions had not been implemented and compared the result with what happens on their implementation. Through a four-state population model, the number of healthy life years lived over a period of a hun￾dred years by a population in the absence of that set of interventions is estimated by inputting parameters of incidence, remission, cause-spe￾cific and background mortality, and health state valuations reflecting the natural history of the disease. The parameters reflecting the natural history of the disease were mostly estimated by back-adjusting current rates using coverage and known effectiveness of interventions. The same four-state population model can then be rerun, reflecting changes in the parameters due to in￾quantities of inputs required to run each inter￾vention were estimated by experts in 17 regions of the world and validated against the literature. Some individual-level costs were obtained by multiplying unit costs of inputs by the expected utilization of those inputs by the people covered by the programme. Unit costs for outpatient vis￾its and laboratory tests were obtained from a review of literature and supplemented by pri￾mary data from several countries. The total costs for implementing a programme for 10 years con￾stitutes the denominator of the cost-effective￾ness ratio. Stochastic uncertainty analysis was carried out for key parameters in both the numerator and denominator. terventions or combinations of interventions. For example, based on data from earlier chapters, vi￾tamin A deficiency increases the risk of dying from diarrhoea. The impact of vitamin A supplementa￾tion is then mediated in the model by a decrease in case fatality rate for diarrhoea. Effectiveness data came from systematic reviews where available. The difference in the healthy life years gained by the population with and without the intervention is the impact of the intervention and is entered as the denominator of the cost-effectiveness ratio. Costs covered in this analysis include expenses associated with running the intervention, such as administration, training and contact with the me￾dia. They also include costs incurred at the indi￾vidual level such as counselling. Considerable effort was exerted to try to standardize the methodol￾ogy used in collecting and classifying costs. The Sources: (3, 17–19)