Cargando…

Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe

INTRODUCTION: Health-care technologies (HCTs) play an important role in any country’s health-care system. Zimbabwe’s health-care system uses a lot of HCTs developed in other countries. However, a number of local factors have affected the absorption and use of these technologies. We therefore set out...

Descripción completa

Detalles Bibliográficos
Autores principales: Shamu, Shepherd, Rusakaniko, Simbarashe, Hongoro, Charles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5125992/
https://www.ncbi.nlm.nih.gov/pubmed/27920564
http://dx.doi.org/10.2147/CEOR.S95037
_version_ 1782470038596354048
author Shamu, Shepherd
Rusakaniko, Simbarashe
Hongoro, Charles
author_facet Shamu, Shepherd
Rusakaniko, Simbarashe
Hongoro, Charles
author_sort Shamu, Shepherd
collection PubMed
description INTRODUCTION: Health-care technologies (HCTs) play an important role in any country’s health-care system. Zimbabwe’s health-care system uses a lot of HCTs developed in other countries. However, a number of local factors have affected the absorption and use of these technologies. We therefore set out to test the hypothesis that the net benefit regression framework (NBRF) could be a helpful benefit testing model that enables assessment of intra-national variables in HCT transfer. METHOD: We used an NBRF model to assess the benefits of transferring cost-effective technologies to different jurisdictions. We used the country’s 57 administrative districts to proxy different jurisdictions. For the dependent variable, we combined the cost and effectiveness ratios with the districts’ per capita health expenditure. The cost and effectiveness ratios were obtained from HIV/AIDS and malaria randomized controlled trials, which did either a prospective or retrospective cost-effectiveness analysis. The independent variables were district demographic and socioeconomic determinants of health. RESULTS: The study showed that intra-national variation resulted in different net benefits of the same health technology intervention if implemented in different districts in Zimbabwe. The study showed that population data, health data, infrastructure, demographic and health-seeking behavior had significant effects on the net margin benefit for the different districts. The net benefits also differed in terms of magnitude as a result of the local factors. CONCLUSION: Net benefit testing using local data is a very useful tool for assessing the transferability and further adoption of HCTs developed elsewhere. However, adopting interventions with a positive net benefit should also not be an end in itself. Information on positive or negative net benefit could also be used to ascertain either the level of future savings that a technology can realize or the level of investment needed for the particular technology to become beneficial.
format Online
Article
Text
id pubmed-5125992
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Dove Medical Press
record_format MEDLINE/PubMed
spelling pubmed-51259922016-12-05 Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe Shamu, Shepherd Rusakaniko, Simbarashe Hongoro, Charles Clinicoecon Outcomes Res Original Research INTRODUCTION: Health-care technologies (HCTs) play an important role in any country’s health-care system. Zimbabwe’s health-care system uses a lot of HCTs developed in other countries. However, a number of local factors have affected the absorption and use of these technologies. We therefore set out to test the hypothesis that the net benefit regression framework (NBRF) could be a helpful benefit testing model that enables assessment of intra-national variables in HCT transfer. METHOD: We used an NBRF model to assess the benefits of transferring cost-effective technologies to different jurisdictions. We used the country’s 57 administrative districts to proxy different jurisdictions. For the dependent variable, we combined the cost and effectiveness ratios with the districts’ per capita health expenditure. The cost and effectiveness ratios were obtained from HIV/AIDS and malaria randomized controlled trials, which did either a prospective or retrospective cost-effectiveness analysis. The independent variables were district demographic and socioeconomic determinants of health. RESULTS: The study showed that intra-national variation resulted in different net benefits of the same health technology intervention if implemented in different districts in Zimbabwe. The study showed that population data, health data, infrastructure, demographic and health-seeking behavior had significant effects on the net margin benefit for the different districts. The net benefits also differed in terms of magnitude as a result of the local factors. CONCLUSION: Net benefit testing using local data is a very useful tool for assessing the transferability and further adoption of HCTs developed elsewhere. However, adopting interventions with a positive net benefit should also not be an end in itself. Information on positive or negative net benefit could also be used to ascertain either the level of future savings that a technology can realize or the level of investment needed for the particular technology to become beneficial. Dove Medical Press 2016-11-24 /pmc/articles/PMC5125992/ /pubmed/27920564 http://dx.doi.org/10.2147/CEOR.S95037 Text en © 2016 Shamu et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Shamu, Shepherd
Rusakaniko, Simbarashe
Hongoro, Charles
Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe
title Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe
title_full Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe
title_fullStr Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe
title_full_unstemmed Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe
title_short Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe
title_sort prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in zimbabwe
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5125992/
https://www.ncbi.nlm.nih.gov/pubmed/27920564
http://dx.doi.org/10.2147/CEOR.S95037
work_keys_str_mv AT shamushepherd prioritizinghealthsystemanddiseaseburdenfactorsanevaluationofthenetbenefitoftransferringhealthtechnologyinterventionstodifferentdistrictsinzimbabwe
AT rusakanikosimbarashe prioritizinghealthsystemanddiseaseburdenfactorsanevaluationofthenetbenefitoftransferringhealthtechnologyinterventionstodifferentdistrictsinzimbabwe
AT hongorocharles prioritizinghealthsystemanddiseaseburdenfactorsanevaluationofthenetbenefitoftransferringhealthtechnologyinterventionstodifferentdistrictsinzimbabwe