IntroductionProgress towards effective service coverage and financial protection—the two dimensions of Universal Health Coverage (UHC)—has been limited in Kenya in the last decade. The government of Kenya has embarked on a highly ambitious reform programme currently being piloted in four Kenyan counties and aiming at national rollout by 2022. This study provides an updated assessment of the performance of the Kenyan health system in terms of financial protection allowing to monitor trends over time. In light of the UHC initiative, the study provides a baseline to assess the impact of the UHC pilot programme and inform scale-up plans. It also investigates household characteristics associated with catastrophic payments.MethodsUsing data from the Kenya Household Health Expenditure and Utilization Survey (KHHEUS) 2018, we investigated the incidence and intensity of catastrophic and impoverishing health expenditure. We used a logistic regression analysis to assess households’ characteristics associated with the probability of incurring catastrophic health expenditures.ResultsThe results show that the incidence of catastrophic payments is more severe for the poorest households and in the rural areas and mainly due to outpatient services. Results for the impoverishing effect suggest that after accounting for out-of-pocket(OOP) payments, the proportion of poor people increases by 2.2 percentage points in both rural and urban areas. Thus, between 1 and 1.1 million individuals are pushed into poverty due to OOP payments. Among the characteristics associated with the probability of incurring OOP expenditures, socioeconomic conditions, the presence of elderly and of people affected by chronic conditions showed significant results.ConclusionKenya is still lagging behind in terms of protecting its citizens against financial risks associated with ill health and healthcare seeking behaviour. More effort is needed to protect the most vulnerable population groups from the high costs of illness.

BackgroundKenya is experiencing persistently high levels of inequity in health and access to care services. In 2018, decades of sustained policy efforts to promote equitable, affordable and quality health services have culminated in the launch of a universal health coverage scheme, initially piloted in four Kenyan counties and planned for national rollout by 2022. Our study aims to contribute to monitoring and evaluation efforts alongside policy implementation, by establishing a detailed, baseline assessment of socio-economic inequality and inequity in health care utilization in Kenya shortly before the policy launch.MethodsWe use concentration curves and corrected concentration indexes to measure socio-economic inequality in care use and the horizontal inequity index as a measure of inequity in care utilization for three types of care services: outpatient care, inpatient care and preventive and promotive care. Further insights into the individual and household level characteristics that determine observed inequality are derived through decomposition analysis.ResultsWe find significant inequality and inequity in the use of all types of care services favouring richer population groups, with particularly pronounced levels for preventive and inpatient care services. These are driven primarily by differences in living standards and educational achievement, while the region of residence is a key driver for inequality in preventive care use only. Pro-rich inequalities are particularly pronounced for care provided in privately owned facilities, while public providers serve a much larger share of individuals from lower socio-economic groups.ConclusionsThrough its focus on increasing affordability of care for all Kenyans, the newly launched universal health coverage scheme represents a crucial step towards reducing disparities in health care utilization. However in order to achieve equity in health and access to care such efforts must be paralleled by multi-sectoral approaches to address all key drivers of inequity: persistent poverty, disparities in living standards and educational achievement, as well as regional differences in availability and accessibility of care.

ObjectiveAssess the quality of healthcare across African countries based on health providers’ clinical knowledge, their clinic attendance and drug availability, with a focus on seven conditions accounting for a large share of child and maternal mortality in sub-Saharan Africa: malaria, tuberculosis, diarrhoea, pneumonia, diabetes, neonatal asphyxia and postpartum haemorrhage.MethodsWith nationally representative, cross-sectional data from ten countries in sub-Saharan Africa, collected using clinical vignettes (to assess provider knowledge), unannounced visits (to assess provider absenteeism) and visual inspections of facilities (to assess availability of drugs and equipment), we assess whether health providers are available and have sufficient knowledge and means to diagnose and treat patients suffering from common conditions amenable to primary healthcare. We draw on data from 8061 primary and secondary care facilities in Kenya, Madagascar, Mozambique, Nigeria, Niger, Senegal, Sierra Leone, Tanzania, Togo and Uganda, and 22 746 health workers including doctors, clinical officers, nurses and community health workers. Facilities were selected using a multistage cluster-sampling design to ensure data were representative of rural and urban areas, private and public facilities, and of different facility types. These data were gathered under the Service Delivery Indicators programme.ResultsAcross all conditions and countries, healthcare providers were able to correctly diagnose 64% (95% CI 62% to 65%) of the clinical vignette cases, and in 45% (95% CI 43% to 46%) of the cases, the treatment plan was aligned with the correct diagnosis. For diarrhoea and pneumonia, two common causes of under-5 deaths, 27% (95% CI 25% to 29%) of the providers correctly diagnosed and prescribed the appropriate treatment for both conditions. On average, 70% of health workers were present in the facilities to provide care during facility hours when those workers are scheduled to be on duty. Taken together, we estimate that the likelihood that a facility has at least one staff present with competency and key inputs required to provide child, neonatal and maternity care that meets minimum quality standards is 14%. On average, poor clinical knowledge is a greater constraint in care readiness than drug availability or health workers’ absenteeism in the 10 countries. However, we document substantial heterogeneity across countries in the extent to which drug availability and absenteeism matter quantitatively.ConclusionOur findings highlight the need to boost the knowledge of healthcare workers to achieve greater care readiness. Training programmes have shown mixed results, so systems may need to adopt a combination of competency-based preservice and in-service training for healthcare providers (with evaluation to ensure the effectiveness of the training), and hiring practices that ensure the most prepared workers enter the systems. We conclude that in settings where clinical knowledge is poor, improving drug availability or reducing health workers’ absenteeism would only modestly increase the average care readiness that meets minimum quality standards.

As effective onchocerciasis control efforts in Africa transition to elimination efforts, different diagnostic tools are required to support country programs. Senegal, with its long standing, successful control program, is transitioning to using the SD BIOLINE Onchocerciasis IgG4 (Ov16) rapid test over traditional skin snip microscopy. The aim of this study is to demonstrate the feasibility of integrating the Ov16 rapid test into onchocerciasis surveillance activities in Senegal, based on the following attributes of acceptability, usability, and cost. A cross-sectional study was conducted in 13 villages in southeastern Senegal in May 2016. Individuals 5 years and older were invited to participate in a demographic questionnaire, an Ov16 rapid test, a skin snip biopsy, and an acceptability interview. Rapid test technicians were interviewed and a costing analysis was conducted. Of 1,173 participants, 1,169 (99.7%) agreed to the rapid test while 383 (32.7%) agreed to skin snip microscopy. The sero-positivity rate of the rapid test among those tested was 2.6% with zero positives 10 years and younger. None of the 383 skin snips were positive for Ov microfilaria. Community members appreciated that the rapid test was performed quickly, was not painful, and provided reliable results. The total costs for this surveillance activity was $22,272.83, with a cost per test conducted at $3.14 for rapid test, $7.58 for skin snip microscopy, and $13.43 for shared costs. If no participants had refused skin snip microscopy, the total cost per method with shared costs would have been around $16 per person tested. In this area with low onchocerciasis sero-positivity, there was high acceptability and perceived value of the rapid test by community members and technicians. This study provides evidence of the feasibility of implementing the Ov16 rapid test in Senegal and may be informative to other country programs transitioning to Ov16 serologic tools.

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.