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

Author:

Hallett Timothy B.ORCID,Mangal Tara D.ORCID,Tamuri Asif U.ORCID,Arinaminpathy NimalanORCID,Cambiano ValentinaORCID,Chalkley MartinORCID,Collins Joseph H.ORCID,Cooper JonathanORCID,Gillman Matthew S.,Giordano MosèORCID,Graham Matthew M.ORCID,Graham WilliamORCID,Janoušková EvaORCID,Jewell Britta L.ORCID,Lin Ines LiORCID,Smith Robert ManningORCID,Manthalu GeraldORCID,Mnjowe EmmanuelORCID,Mohan SakshiORCID,Molaro MargheritaORCID,Ng’ambi WingstonORCID,Nkhoma DominicORCID,Piatek StefanORCID,Revill PaulORCID,Rodger AlisonORCID,Salmanidou DimitraORCID,She BinglingORCID,Smit MikaelaORCID,Twea Pakwanja D.,Colbourn TimORCID,Mfutso-Bengo JosephORCID,Phillips Andrew N.ORCID

Abstract

AbstractBackgroundDecisions need to be made in all healthcare systems about the allocation of available resources with the aim of improving population health. Evidence is needed for these decisions, which can have enormous consequences for population health, especially in lower-income settings.MethodsWe address this need using an individual-based simulation model of healthcare need and service delivery that we have developed for Malawi, drawing on demographic, epidemiological and routine healthcare system data (on facilities, staff, and consumables). We compare the model’s simulated outputs with available data and estimate the impact that the healthcare system is having currently. We analyse the effects of improvements in healthcare access, clinician performance and consumables availability.FindingsMalawi’s healthcare system averted 40 million Disability-Adjusted Life-Years (DALYs) in the five-year period to end-2019, which is half of the total DALYS that the population (total size: 19 million in 2020) would otherwise incur. This impact is strongly focussed on young children (mediated largely by programmes addressing respiratory infections, HIV/AIDS and malaria) and also by the HIV/AIDS and TB programmes (among adults). More services seem to be delivered than would be expected based on the number of staff and expected time needed for services. Nevertheless, the additional services that are provided (through service times being reduced or additional HCW hours worked) account for half the impact of the healthcare system (i.e., ∼20 million DALYS averted). If system improvements gave ill persons immediate access to healthcare, led to optimal referral and diagnosis accuracy, and eliminated consumable stock-outs, the overall impact of the healthcare system could increase by up to ∼30% (12 million more DALYS averted).ConclusionsThe healthcare system in Malawi generates substantial health gains to the population with very limited resources. Strengthening interventions could potentially increase these gains considerably and so should be a priority for investigation and investment. A detailed individual-based simulation model of healthcare service delivery is a valuable tool for healthcare system planning and for evaluating proposals for healthcare system strengthening.

Publisher

Cold Spring Harbor Laboratory

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