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

Abstract

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.

Keywords:

• net benefit
• benefit testing
• health technology
• transferability
• prioritization
• resource allocation

Acknowledgments

We would like to thank the Ministry of Health and Child Care for allowing us to access their database. We also like to thank the University of Zimbabwe, College of Health Sciences Research Support Centre for supporting this work through a grant fellowship.

Funding

This research was supported with funding from the Wellcome Trust (UK).

Disclosure

The authors report no conflicts of interest in this work.