HSRC IR Repository

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

Show simple item record

dc.date.accessioned 2018-03-12T15:22:35Z
dc.date.available 2018-03-12T15:22:35Z
dc.date.issued 2017-05-15 en
dc.identifier.uri http://hdl.handle.net/20.500.11910/10925
dc.description.abstract Health-care technologies (HCTs) play an important role in any country's healthcare 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. 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. 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. 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. en
dc.format.medium Print en
dc.subject ZIMBABWE en
dc.subject PUBLIC HEALTH en
dc.subject HEALTH SERVICES en
dc.subject DISEASE en
dc.title Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe en
dc.type Journal Article en
dc.description.version Y en
dc.ProjectNumber N/A en
dc.Volume 8 en
dc.BudgetYear 2017/18 en
dc.ResearchGroup Population Health, Health Systems and Innovation en
dc.SourceTitle ClinicoEconomics and Outcomes Research en
dc.ArchiveNumber 9779 en
dc.PageNumber 695-705 en
dc.outputnumber 8670 en
dc.bibliographictitle Shamu, S., Rusakaniko, S, & Hongoro, C. (2016) Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe. <i>ClinicoEconomics and Outcomes Research</i>. 8:695-705. en
dc.publicationyear 2016 en
dc.contributor.author1 Shamu, S. en
dc.contributor.author2 Rusakaniko, S, en
dc.contributor.author3 Hongoro, C. en


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search HSRC IR


Browse

My Account