BackgroundSince 2000, international funding for HIV has supported scaling up antiretroviral therapy (ART) in sub-Saharan Africa. However, such funding has stagnated for years, threatening the sustainability and reach of ART programs amid efforts to achieve universal treatment. Improving health system efficiencies, particularly at the facility level, is an increasingly critical avenue for extending limited resources for ART; nevertheless, the potential impact of increased facility efficiency on ART capacity remains largely unknown. Through the present study, we sought to quantify facility-level technical efficiency across countries, assess potential determinants of efficiency, and predict the potential for additional ART expansion.MethodsUsing nationally-representative facility datasets from Kenya, Uganda and Zambia, and measures adjusting for structural quality, we estimated facility-level technical efficiency using an ensemble approach that combined restricted versions of Data Envelopment Analysis and Stochastic Distance Function. We then conducted a series of bivariate and multivariate regression analyses to evaluate possible determinants of higher or lower technical efficiency. Finally, we predicted the potential for ART expansion across efficiency improvement scenarios, estimating how many additional ART visits could be accommodated if facilities with low efficiency thresholds reached those levels of efficiency.ResultsIn each country, national averages of efficiency fell below 50 % and facility-level efficiency markedly varied. Among facilities providing ART, average efficiency scores spanned from 50 % (95 % uncertainty interval (UI), 48–62 %) in Uganda to 59 % (95 % UI, 53–67 %) in Zambia. Of the facility determinants analyzed, few were consistently associated with higher or lower technical efficiency scores, suggesting that other factors may be more strongly related to facility-level efficiency. Based on observed facility resources and an efficiency improvement scenario where all facilities providing ART reached 80 % efficiency, we predicted a 33 % potential increase in ART visits in Kenya, 62 % in Uganda, and 33 % in Zambia. Given observed resources in facilities offering ART, we estimated that 459,000 new ART patients could be seen if facilities in these countries reached 80 % efficiency, equating to a 40 % increase in new patients.ConclusionsHealth facilities in Kenya, Uganda, and Zambia could notably expand ART services if the efficiency with which they operate increased. Improving how facility resources are used, and not simply increasing their quantity, has the potential to substantially elevate the impact of global health investments and reduce treatment gaps for people living with HIV.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0653-z) contains supplementary material, which is available to authorized users.
This study quantitatively assessed the population-wide lead poisoning conditions in Kabwe, Zambia, a town with severe lead pollution. While existing data have reported concerning blood lead levels (BLLs) of residents in pollution hotspots, the data representing the entire population are lacking. Further, selection bias is a concern. Given the lack of compulsory testing schemes, BLLs have been observed from voluntary participants in blood sampling surveys, but such data can represent higher or lower BLLs than the population average because of factors simultaneously affecting participation and BLLs. To illustrate the lead poisoning conditions of the population, we expanded the focus of our surveys and then econometrically estimated the BLLs of individuals representing the population, including those not participating in blood sampling, using background geographic, demographic, and socioeconomic information. The estimated population mean BLL was 11.9 μg/dL (11.6–12.1, 95% CI), lower than existing data because of our wide focus and correction of selection bias. However, the scale of lead poisoning remained immense and 74.9% of residents had BLLs greater than 5 μg/dL, the standard reference level for lead poisoning. Our estimates provide a deeper understanding of the problem and a foundation for policy intervention designs.
Background Zambia has invested in several healthcare financing reforms aimed at achieving universal access to health services. Several evaluations have investigated the effects of these reforms on the utilization of health services. However, only one study has assessed the distributional incidence of health spending across different socioeconomic groups, but without differentiating between public and overall health spending and between curative and maternal health services. Our study aims to fill this gap by undertaking a quasi-longitudinal benefit incidence analysis of public and overall health spending between 2006 and 2014. Methods We conducted a Benefit Incidence Analysis (BIA) to measure the socioeconomic inequality of public and overall health spending on curative services and institutional delivery across different health facility typologies at three time points. We combined data from household surveys and National Health Accounts. Results Results showed that public (concentration index of − 0.003; SE 0.027 in 2006 and − 0.207; SE 0.011 in 2014) and overall (0.050; SE 0.033 in 2006 and − 0.169; SE 0.011 in 2014) health spending on curative services tended to benefit the poorer segments of the population while public (0.241; SE 0.018 in 2007 and 0.120; SE 0.007 in 2014) and overall health spending (0.051; SE 0.022 in 2007 and 0.116; SE 0.007 in 2014) on institutional delivery tended to benefit the least-poor. Higher inequalities were observed at higher care levels for both curative and institutional delivery services. Conclusion Our findings suggest that the implementation of UHC policies in Zambia led to a reduction in socioeconomic inequality in health spending, particularly at health centres and for curative care. Further action is needed to address existing barriers for the poor to benefit from health spending on curative services and at higher levels of care.
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