A new approach to Health Benefits Package design: an application of the Thanzi La Onse model in Malawi.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
30 Sep 2024
Historique:
received: 08 02 2024
accepted: 05 09 2024
medline: 30 9 2024
pubmed: 30 9 2024
entrez: 30 9 2024
Statut: aheadofprint

Résumé

An efficient allocation of limited resources in low-income settings offers the opportunity to improve population-health outcomes given the available health system capacity. Efforts to achieve this are often framed through the lens of "health benefits packages" (HBPs), which seek to establish which services the public healthcare system should include in its provision. Analytic approaches widely used to weigh evidence in support of different interventions and inform the broader HBP deliberative process however have limitations. In this work, we propose the individual-based Thanzi La Onse (TLO) model as a uniquely-tailored tool to assist in the evaluation of Malawi-specific HBPs while addressing these limitations. By mechanistically modelling-and calibrating to extensive, country-specific data-the incidence of disease, health-seeking behaviour, and the capacity of the healthcare system to meet the demand for care under realistic constraints on human resources for health available, we were able to simulate the health gains achievable under a number of plausible HBP strategies for the country. We found that the HBP emerging from a linear constrained optimisation analysis (LCOA) achieved the largest health gain-∼8% reduction in disability adjusted life years (DALYs) between 2023 and 2042 compared to the benchmark scenario-by concentrating resources on high-impact treatments. This HBP however incurred a relative excess in DALYs in the first few years of its implementation. Other feasible approaches to prioritisation were assessed, including service prioritisation based on patient characteristics, rather than service type. Unlike the LCOA-based HBP, this approach achieved consistent health gains relative to the benchmark scenario on a year- to-year basis, and a 5% reduction in DALYs over the whole period, which suggests an approach based upon patient characteristics might prove beneficial in the future.

Identifiants

pubmed: 39348389
doi: 10.1371/journal.pcbi.1012462
pii: PCOMPBIOL-D-24-00243
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1012462

Informations de copyright

Copyright: © 2024 Molaro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Margherita Molaro (M)

MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.

Sakshi Mohan (S)

Centre for Health Economics, University of York, York, United Kingdom.

Bingling She (B)

MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.

Martin Chalkley (M)

Centre for Health Economics, University of York, York, United Kingdom.

Tim Colbourn (T)

Institute for Global Health, University College London, London, United Kingdom.

Joseph H Collins (JH)

Institute for Global Health, University College London, London, United Kingdom.

Emilia Connolly (E)

London School of Hygiene and Tropical Medicine, London, United Kingdom.

Matthew M Graham (MM)

Centre for Advanced Research Computing, University College London, London, United Kingdom.

Eva Janoušková (E)

Institute for Global Health, University College London, London, United Kingdom.

Ines Li Lin (I)

Institute for Global Health, University College London, London, United Kingdom.

Gerald Manthalu (G)

Department of Planning and Policy Development, Ministry of Health and Population, Lilongwe, Malawi.

Emmanuel Mnjowe (E)

Kamuzu University of Health Sciences, Blantyre, Malawi.

Dominic Nkhoma (D)

Kamuzu University of Health Sciences, Blantyre, Malawi.

Pakwanja D Twea (PD)

Department of Planning and Policy Development, Ministry of Health and Population, Lilongwe, Malawi.

Andrew N Phillips (AN)

Institute for Global Health, University College London, London, United Kingdom.

Paul Revill (P)

Centre for Health Economics, University of York, York, United Kingdom.

Asif U Tamuri (AU)

Centre for Advanced Research Computing, University College London, London, United Kingdom.

Joseph Mfutso-Bengo (J)

Kamuzu University of Health Sciences, Blantyre, Malawi.

Tara D Mangal (TD)

MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.
Centre for Health Economics, University of York, York, United Kingdom.

Timothy B Hallett (TB)

MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.

Classifications MeSH