Supporting the revision of the health benefits package in Uganda: A constrained optimisation approach

Abstract

All public health systems are faced with the crucial question of how best to allocate their limited resources in order to maximise the benefits they produce. This question is particularly pressing in low-and middle-income countries (LMICs) where the resource constraints, financial and other, mean that many health services cannot be provided to all those in need (Glassman et al., 2017). It is widely recognized that there is a considerable gap between the aspirational health plans of LMICs and actually available resources (Glassman and Chalkidou, 2012;Ochalek et al., 2018). Health Benefits Packages offer a potential solution to the implicit sub-optimal rationing of resources (Keliddar et al., 2017) which occurs as a result of this mismatch. By changing from ad hoc or implicit priority setting and rationing of services, to systematic, evidence-based and transparent priority setting

A Healthcare Service Delivery and Epidemiological Model for Investigating Resource Allocation for Health: TheThanzi La OnseModel

“…The systematic integration of the available data for interventions, means that results that relate to different diseases or interventions are comparable, in contrast to results culled from literature that vary in terms of perspective, counterfactual and outcome measurement. 36 Although the approach demands lots of data, these demands have been met in Malawi, and, we believe, will be met in other countries too. Furthermore, using data to inform decision-making in this way provides a key incentive for improving data systems.…”

Using economic analysis to inform health resource allocation: lessons from Malawi

“…Understandably, budgetary restrictions are not the only constraint on the health system. In the short term, there exist diverse constraints on care, both financial and non-financial (e.g., staffing, drug availability) [ 20 – 23 ]. Thus, it is essential to showcase how additional resource constraints can be incorporated alongside the public health budget constraint, offering analytical support for decisions concerning HBP [ 23 ].…”

“…In the short term, there exist diverse constraints on care, both financial and non-financial (e.g., staffing, drug availability) [ 20 – 23 ]. Thus, it is essential to showcase how additional resource constraints can be incorporated alongside the public health budget constraint, offering analytical support for decisions concerning HBP [ 23 ]. Under such circumstances, the simple CEA approach can be augmented to include additional considerations.…”

“…The LCOA-based framework maximizes the net DALYs averted (or net health impact) given the financial and physical resource constraints of Malawi’s public health sector [ 23 ]. The size of the resource envelope allocated for purchasing drugs and consumables represents the financial constraint, while the size of the health workforce, including doctors, clinical officers, nursing staff, and pharmaceutical staff, represents the physical constraint.…”

“…In another scenario, donor constraint was considered alongside the drug budget constraint, while excluding the health workforce constraint, leading to an optimal package of 66 interventions averting 53.4 million net DALYs [ 25 ]. Further, the marginal value analysis, mirroring Mohan and colleagues’ [ 23 ] analysis for Uganda, suggested that the most important bottleneck in the Malawian Health system is the shortage of doctors/clinical officers, which makes it difficult to further expand the HBP. More specifically, $1000 invested towards buying additional doctor/clinical officer time could result in over 275 net DALYs averted.…”