HSSP outputs and outcomes using the Malawi cost model
HSSP outputs and outcomes using the Malawi cost model
Introduction
The cost model of the Essential Health Package (EHP) was developed by the Ministry of Health in 2002-3 prior to the Programme of Work and the
first SWAp for health. It has been checked, modified, re-costed and improved for the HSSP. Other models are being developed such as the United
Nations OneHealth Costing Tool. This paper describes how the Malawi cost model can be used to calculate the overall cost-effectiveness of the
EHP and targets based on activity for each year.
Methods
The MOH cost model used for the first EHP has been adapted by the Ministry of Health (MOH) for EHP2. The costs have been revised. Staff
numbers have been revised to accommodate recent revisions of the staff establishment. A number of assumptions have been used to derive the
activity estimated from the model under different funding scenarios. They are:1. The model has been calibrated using 2009/10 activity based on HMIS data and 2010/11 estimated costs. The model over-predicts costs by
45%. This is due to drug and staff costs being less than predicted by the model because of staff absences and drug stock-outs. The effect is
that activity over-predicts beneficial effect by some 20%. The budget estimates for 2010/11 were based on Department of Finance analysis of
donor funding and the MOH budget. No deduction of transaction costs of donor contributions was made. To allow comparison with the
HSSP, for which donor contributions have had transaction costs deducted, 19% (estimated as the average transaction costs in 2010/11)
reduction in donor funding has been used as part of the calibration exercise. The model has been re-calibrated to take these factors into
account.
2. The core scenario used is based on the MOH resource based estimate of budgets in 2011/12 and 2015/6. Unlike the POW cost model the
revised model includes zone and central hospital cost centres and so it is relatively easy to identify EHP and non-EHP costs funded by the
budget. 75% of direct HQ and 70% (previously found to be the primary and secondary care component of central hospital services) of
central hospital and 90% of district service costs are allocated to the EHP. All central hospital indirect costs including HR and 25% of HQ
indirect costs are allocated to non-EHP services, while 100% of district and CHAM HR costs are allocated to the EHP. Two versions are
available, one using the resource based budgets of the HSSP and the other an ideal budget which would allow all targets to be achieved.
3. Staff levels and costs are based on actual budget plans. Direct costs, which include those for drugs and equipment, are assumed to increase by
7% in year 1. Earmarked funded activities are those such as ARTs which have funding specifically earmarked for that activity. Malaria, EPI
and HIV/AIDS are the main sets of such activities. Pooled funded activities are the remainder, such as RH and ARI treatment.
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HSSP outputs and outcomes using the Malawi cost model
4. By 2016 the effectiveness of patient care is assumed to remain at 80% for the resource based scenario. An ideal scenario has also been
modelled to estimate activity and effect on the burden of disease using the activity to meet all targets and the resources required to do this.
The ideal scenario will achieve 100% staffing and no stock outs.
Prevention interventions
Various assumptions were used to estimate the burden of disease that has already been prevented by prevention interventions such as immunisations
as to stop these would have the effect of increasing these diseases in future. To gauge what would happen if immunisations were reduced, the SubSaharan incidence rates of vaccine preventable diseases have been used to calculate the effect of a suboptimal immunisation programme, adjusted by
the estimated levels of disease pre-immunisation era.
Clinical treatments
For those interventions involving clinical treatment 2009/10 HMIS data have been used, being the most recent year of currently available data.
Treatments have been adjusted in two ways; by a factor for treatment effectiveness (as an example, antibiotics work in 84% of times for pneumonia in
children); and by a factor measuring the affected population (as an example, 50% of adults and 70% of children registered in HMIS as malaria are not,
so only half or less of the number treated will benefit from antimalarial drugs). Treatment effectiveness factors are taken from recent authoritative
sources and referenced in the table.
Summation of benefits of the EHP
The burden of disease calculated in DALYS for each intervention for 2011 (and succeeding years) can be summed to provide an overall estimate of
burden averted by the programme. As the costs are also contained in the EHP model it is possible to measure the cost effectiveness of each and all
interventions combined at the levels of activity agreed once funding is known.
Results
Three scenarios are provided. The first scenario assumes the resource based budget will be available and earmarked activity reduced to 75% and
pooled activity to 32% to work within the limited budget. The second scenario assumes the same budget in 2015/6 but all capital funds are
transferred to recurring budgets and indirect costs are reduced by 20%. The third scenario assumes the ideal budget will be available and assumes that
all targets are achieved. The table shows the burden of disease averted by the HSSP in each year, the cost-effectiveness of the EHP and the
proportion of planned activity which will be achieved.
A baseline for 2010/11 is also shown. From previous research approximately 70% of earmarked funded activity and 40% of pooled funded activity
was achieved at a cost of $389m. The package was cost effective at $170 per DALY. Anything less than $350 per DALY is thought to be affordable
for a country such as Malawi with a Gross National Product of $350 per capita.
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To achieve all targets (ideal based scenario) would require $453m in 2011/2 rising to $814m in 2015/6. This assumes full staffing of established posts
by the end of the programme.
The current resource based budget of $416m in 2011/12 rising to $541m in 2015/6 will reach 90% of earmarked activity and targets and 74% of
pooled activity in 2011/2 falling to 75% of earmarked and 32% of pooled activity. This is a little less activity in 2010/11 because of the increase in
size of the population and the extra activity, raised targets and pessimistic funding assumptions particularly in the later years of the HSSP.
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Discussion
The results are based on a number of assumptions that can be modified after discussion and further research. The model still has some inaccuracies
in the data on which it relies. It needs to be validated by an expert team from the MOH, who can look at the financial assumptions, the activity and
target assumptions and the model itself. A number of improvements would make the model more useful and these will not need a huge amount of
investment – probably a full time researcher in the Planning Department for a year. In the meantime the results can be used for planning purposes
now.
The results highlight the effect of underfunding. The marginal benefit of additional funds is substantial as shown by the different in activity found if
less pessimistic assumptions about overall funding are used. The results, which demonstrate the overall cost-effectiveness of the proposed plan and
the marginal benefit of additional funding, can be used to encourage government and donors to find more money for the EHP.
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Conclusion
The appropriate technical working group can consider these results and recommend possible modifications to targets and activity in Year 1 of the
plan. They might also consider seeking some support to improve the model for future use and collaborate with the United Nations OneHealth
Costing Tool team.
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