Health Financing

Financial resources available to decision-makers are limited, resources in healthcare are no exception Globally, decision-makers in healthcare face the same key challenge: how to provide the best health care service for patients with limited resources. This question is hotly debated globally.

Hence, the question of how to best allocate scarce resources to improve the health of a population is relevant to and hotly debated by decision-makers and patients globally. In the health sector, tools are adopted by decision-makers to support the prioritisation of health interventions and technologies. Due to a forever changing financial, technological and health environment, these tools are constantly developed and improved in order to allocate health resources in the most efficiently and effective way.

Researchers from the UCL Institute for Global Health and the UCL Faculty of Population Health Sciences explore two prioritisation tools for healthcare spending and their applications in Zimbabwe and Belarus.

‘HIPtool’ in Zimbabwe

In recent years, Zimbabwe faced a bleak fiscal situation and inefficient health spending. As a result, poor and rural populations have been disproportionately burdened with health risks. Moreover, households are bearing an increasing share of the health sector’s financing. Under these circumstances, the most promising way to achieve better health outcomes is to increase the efficiency of health resource allocation. Dr Lara Gosce, Dr Hassan Haghparast-Bidgoli, Prof Jolene Skordis, Mr Gerard Abou Jaoude and colleagues piloted the Health Interventions Prioritisation Tool (HIPtool) to improve the allocation of health expenditure in Zimbabwe. Three types of data inputs are required to run HIPtool: the cost of the intervention, the burden of disease and the cost-effectiveness of the intervention. Once populated with data, HIPtool can inform which of the 218 interventions in the Essential Universal Health Coverage (EUHC) package developed by the Disease Control Priorities Project (DCP3) should be prioritised and what would be the optimal expenditure for these interventions. Although HIPtool has some limitations, such as neglecting the infectiousness of the diseases and interactions between diseases and interventions, it can provide valuable data for health decision-making.

HIPtool was applied in the fiscal year 2016 and health maximisation was the only objective. Based on the optimisation algorithm, the researchers found that 2.6 million disability-adjusted life years could be avoided through an optimised reallocation of the 2016 national health expenditure. The results also suggest a shift in health expenditure from hospitals to lower-level care platforms, such as community and primary health centres. In addition, a focus on tuberculosis and pneumonia eradication, maternal and child health and non-communicable disease interventions would maximise health gains.

‘Optima TB’ in tuberculosis interventions in Belarus

In addition to tools for prioritising interventions across the health sector, there are approaches for specific diseases. Tuberculosis (TB) remains a leading global cause of death and morbidity, with approximately 85% of TB deaths occurring in low- and middle-income countries. These countries face not only limited health resources for TB care and control, but also limited budget to fund TB interventions. Two economists of health at UCL, Dr Lara Gosce and Dr Hassan Haghparast-Bidgoli, worked with other researchers to investigate the effectiveness of Optima TB tool in prioritising TB interventions. The Optima TB is an open-access tool for allocative efficiency modelling, designed to inform evidence-based priority setting processes for the design of the TB package. This tool uses a compartmental model of disease transmission and the costs and impacts of diseases. In addition, optimisation process is used to identify the best combination of various TB interventions. The Optima TB tool has two major advantages. It allows different populations and co-morbidities to be taken into account to capture heterogeneities and to consider extensively drug-resistant TB cases.

Dr Lara Gosce, Dr Hassan Haghparast-Bidgoli and colleagues explored the application of the Optima TB tool in Belarus, an upper-middle income country with a relatively high TB burden. They found an optimised allocation of TB spending in Belarus that could lead to significant improvements in TB prevalence and incidence. This would include the implementation of population-based mass screening, targeted active case-finding strategies and outpatient treatment. With this new allocation, TB prevalence and mortality among HIV-negative populations could be reduced by 45% and 50% respectively by 2035 compared to 2015. It could be reduced by 30% to 45% for HIV-positive people. Moreover, this reallocation could save about 30% of total treatment expenditure, allowing for increased investment in targeted screening and diagnosis.

Conclusion

The results of these two studies by UCL economists show the potential of prioritisation tools for resource allocation in the health sector. Although the availability and quality of data limits the performance of these tools, the optimised allocation they provide can inform decision-making process.

References: Hou, X., Jaoude, G. A., Gosce, L., Shamu, S., Sisimayi, C. N., Lannes, L., ... & Skordis, J. (2021). Improving Allocative Efficiency in Zimbabwe’s Health Sector. The World Bank Group.         Goscé, L., Abou Jaoude, G. J., Kedziora, D. J., Benedikt, C., Hussain, A., Jarvis, S., ... & Abubakar, I. (2021). Optima TB: A tool to help optimally allocate tuberculosis spending. PLoS computational biology, 17(9), e1009255.