Inpatient care costs of COVID-19 in South Africa’s public healthcare system

Abstract

Background: Coronavirus disease 2019 (COVID-19) has had a devastating impact globally, with severe health and economic consequences. To prepare health systems to deal with the pandemic, epidemiological and cost projection models are required to inform budgets and efficient allocation of resources. This study estimates daily inpatient care costs of COVID-19 in South Africa, an important input into cost projection and economic evaluation models.

Methods: We adopted a micro-costing approach, which involved the identification, measurement and valuation of resources used in the clinical management of COVID-19. We considered only direct medical costs for an episode of hospitalisation from the South African public health system perspective. Resource quantities and unit costs were obtained from various sources. Inpatient costs per patient day was estimated for consumables, capital equipment and human resources for three levels of inpatient care – general wards, high care wards and intensive care units (ICUs).

Results: Average daily costs per patient increased with the level of care. The highest average daily cost was estimated for ICU admissions – 271 USD to 306 USD (financial costs) and ~800 USD to 830 USD (economic costs, excluding facility fee) depending on the need for invasive vs. non-invasive ventilation (NIV). Conversely, the lowest cost was estimated for general ward-based care – 62 USD to 79 USD (financial costs) and 119 USD to 278 USD (economic costs, excluding facility fees) depending on the need for supplemental oxygen. In high care wards, total cost was estimated at 156 USD, financial costs and 277 USD, economic costs (excluding facility fees). Probabilistic sensitivity analyses suggest our costs estimates are robust to uncertainty in cost inputs.

Conclusion: Our estimates of inpatient costs are useful for informing budgeting and planning processes and costeffectiveness analysis in the South African context. However, these estimates can be adapted to inform policy decisions in other context.

Rights

http://creativecommons.org/licenses/by/4.0/

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Identifiers

DOI

https://doi.org/10.34172/ijhpm.2021.24

Repository URI

https://eprints.gla.ac.uk/279582/