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Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa

BACKGROUND: Evidence on the relative costs and effects of interventions that do not consider ‘real-world’ constraints on implementation may be misleading. However, in many low- and middle-income countries, time and data scarcity mean that incorporating health system constraints in priority setting c...

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Autores principales: Bozzani, Fiammetta M., Mudzengi, Don, Sumner, Tom, Gomez, Gabriela B., Hippner, Piotr, Cardenas, Vicky, Charalambous, Salome, White, Richard, Vassall, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065151/
https://www.ncbi.nlm.nih.gov/pubmed/30069166
http://dx.doi.org/10.1186/s12962-018-0113-z
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author Bozzani, Fiammetta M.
Mudzengi, Don
Sumner, Tom
Gomez, Gabriela B.
Hippner, Piotr
Cardenas, Vicky
Charalambous, Salome
White, Richard
Vassall, Anna
author_facet Bozzani, Fiammetta M.
Mudzengi, Don
Sumner, Tom
Gomez, Gabriela B.
Hippner, Piotr
Cardenas, Vicky
Charalambous, Salome
White, Richard
Vassall, Anna
author_sort Bozzani, Fiammetta M.
collection PubMed
description BACKGROUND: Evidence on the relative costs and effects of interventions that do not consider ‘real-world’ constraints on implementation may be misleading. However, in many low- and middle-income countries, time and data scarcity mean that incorporating health system constraints in priority setting can be challenging. METHODS: We developed a ‘proof of concept’ method to empirically estimate health system constraints for inclusion in model-based economic evaluations, using intensified case-finding strategies (ICF) for tuberculosis (TB) in South Africa as an example. As part of a strategic planning process, we quantified the resources (fiscal and human) needed to scale up different ICF strategies (cough triage and WHO symptom screening). We identified and characterised three constraints through discussions with local stakeholders: (1) financial constraint: potential maximum increase in public TB financing available for new TB interventions; (2) human resource constraint: maximum current and future capacity among public sector nurses that could be dedicated to TB services; and (3) diagnostic supplies constraint: maximum ratio of Xpert MTB/RIF tests to TB notifications. We assessed the impact of these constraints on the costs of different ICF strategies. RESULTS: It would not be possible to reach the target coverage of ICF (as defined by policy makers) without addressing financial, human resource and diagnostic supplies constraints. The costs of addressing human resource constraints is substantial, increasing total TB programme costs during the period 2016–2035 by between 7% and 37% compared to assuming the expansion of ICF is unconstrained, depending on the ICF strategy chosen. CONCLUSIONS: Failure to include the costs of relaxing constraints may provide misleading estimates of costs, and therefore cost-effectiveness. In turn, these could impact the local relevance and credibility of analyses, thereby increasing the risk of sub-optimal investments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12962-018-0113-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-60651512018-08-01 Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa Bozzani, Fiammetta M. Mudzengi, Don Sumner, Tom Gomez, Gabriela B. Hippner, Piotr Cardenas, Vicky Charalambous, Salome White, Richard Vassall, Anna Cost Eff Resour Alloc Research BACKGROUND: Evidence on the relative costs and effects of interventions that do not consider ‘real-world’ constraints on implementation may be misleading. However, in many low- and middle-income countries, time and data scarcity mean that incorporating health system constraints in priority setting can be challenging. METHODS: We developed a ‘proof of concept’ method to empirically estimate health system constraints for inclusion in model-based economic evaluations, using intensified case-finding strategies (ICF) for tuberculosis (TB) in South Africa as an example. As part of a strategic planning process, we quantified the resources (fiscal and human) needed to scale up different ICF strategies (cough triage and WHO symptom screening). We identified and characterised three constraints through discussions with local stakeholders: (1) financial constraint: potential maximum increase in public TB financing available for new TB interventions; (2) human resource constraint: maximum current and future capacity among public sector nurses that could be dedicated to TB services; and (3) diagnostic supplies constraint: maximum ratio of Xpert MTB/RIF tests to TB notifications. We assessed the impact of these constraints on the costs of different ICF strategies. RESULTS: It would not be possible to reach the target coverage of ICF (as defined by policy makers) without addressing financial, human resource and diagnostic supplies constraints. The costs of addressing human resource constraints is substantial, increasing total TB programme costs during the period 2016–2035 by between 7% and 37% compared to assuming the expansion of ICF is unconstrained, depending on the ICF strategy chosen. CONCLUSIONS: Failure to include the costs of relaxing constraints may provide misleading estimates of costs, and therefore cost-effectiveness. In turn, these could impact the local relevance and credibility of analyses, thereby increasing the risk of sub-optimal investments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12962-018-0113-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-30 /pmc/articles/PMC6065151/ /pubmed/30069166 http://dx.doi.org/10.1186/s12962-018-0113-z Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Bozzani, Fiammetta M.
Mudzengi, Don
Sumner, Tom
Gomez, Gabriela B.
Hippner, Piotr
Cardenas, Vicky
Charalambous, Salome
White, Richard
Vassall, Anna
Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa
title Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa
title_full Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa
title_fullStr Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa
title_full_unstemmed Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa
title_short Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa
title_sort empirical estimation of resource constraints for use in model-based economic evaluation: an example of tb services in south africa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065151/
https://www.ncbi.nlm.nih.gov/pubmed/30069166
http://dx.doi.org/10.1186/s12962-018-0113-z
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