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BackgroundLife expectancy initially improves rapidly with economic development but then tails off. Yet, at any level of economic development, some countries do better, and some worse, than expected - they either punch above or below their weight. Why this is the case has been previously researched but no full explanation of the complexity of this phenomenon is available.New research networkIn order to advance understanding, the newly formed Punching Above Their Weight Research Network has developed a model to frame future research. It provides for consideration of the following influences within a country: political and institutional context and history; economic and social policies; scope for democratic participation; extent of health promoting policies affecting socio-economic inequities; gender roles and power dynamics; the extent of civil society activity and disease burdens.ConclusionFurther research using this framework has considerable potential to advance effective policies to advance health and equity.

Purpose. The diagnosis of tuberculosis remains controversial between clinicians and public health officers. Public health officials fear to treat too many patients; clinicians fear that truly diseased will be denied [...]

While several developing countries have been implementing PBF as a strategy to finance health services, a polarized debate between the 'proponents' and 'opponents' of this approach is gaining prominence.(1-4) Ireland [...]

Background: Performance-based financing (PBF) strategies are promoted as a supply-side, results-based financing mechanism to improve primary health care. This study estimated the effects of Rwanda's PBF program on less-incentivized child health services and examined the differential program impact by household poverty.Methods: Districts were allocated to intervention and comparison for PBF implementation in Rwanda. Using Demographic Health Survey data from 2005 to 2007-08, a community-level panel dataset of 5781 children less than 5 years of age from intervention and comparison districts was created. The impacts of PBF on reported childhood illness, facility care-seeking, and treatment received were estimated using a difference-in-differences model with community fixed effects. An interaction term between poverty and the program was estimated to identify the differential effect of PBF among children from poorer families.Results: There was no measurable difference in estimated probability of reporting illness with diarrhea, fever or acute respiratory infections between the intervention and comparison groups. Seeking care at a facility for these illnesses increased over time, however no differential effect by PBF was seen. The estimated effect of PBF on receipt of treatment for poor children is 45 percentage points higher (p = 0.047) compared to the non-poor children seeking care for diarrhea or fever.Conclusions: PBF, a supply-side incentive program, improved the quality of treatment received by poor children conditional on patients seeking care, but it did not impact the propensity to seek care. These findings provide additional evidence that PBF incentivizes the critical role staff play in assuring quality services, but does little to influence consumer demand for these services. Efforts to improve child health need to address both supply and demand, with additional attention to barriers due to poverty if equity in service use is a concern. [ABSTRACT FROM AUTHOR]

Background: Evaluations of health systems strengthening (HSS) interventions using observational data are rarely used for causal inference due to limited data availability. Routinely collected national data allow use of quasi-experimental designs such as interrupted time series (ITS). Rwanda has invested in a robust electronic health management information system (HMIS) that captures monthly healthcare utilization data. We used ITS to evaluate impact of an HSS intervention to improve primary health care facility readiness on health service utilization in two rural districts of Rwanda. Methods: We used controlled ITS analysis to compare changes in healthcare utilization at health centers (HC) that received the intervention (n = 13) to propensity score matched non-intervention health centers in Rwanda (n = 86) from January 2008 to December 2012. HC support included infrastructure renovation, salary support, medical equipment, referral network strengthening, and clinical training. Baseline quarterly mean outpatient visit rates and population density were used to model propensity scores. The intervention began in May 2010 and was implemented over a twelve-month period. We used monthly healthcare utilization data from the national Rwandan HMIS to study changes in the (1) number of facility deliveries per 10,000 women, (2) number of referrals for high risk pregnancy per 100,000 women, and (3) the number of outpatient visits performed per 1,000 catchment population. Results: PHIT HC experienced significantly higher monthly delivery rates post-HSS during the April-June season than comparison (3.19/10,000, 95% CI: [0.27, 6.10]). In 2010, this represented a 13% relative increase, and in 2011, this represented a 23% relative increase. The post-HSS change in monthly rate of high-risk pregnancies referred increased slightly in intervention compared to control HC (0.03/10,000, 95% CI: [-0.007, 0.06]). There was a small immediate post-HSS increase in outpatient visit rates in intervention compared to control HC (6.64/1,000, 95% CI: [-13.52, 26.81]). Conclusion: We failed to find strong evidence of post-HSS increases in outpatient visit rates or referral rates at health centers, which could be explained by small sample size and high baseline nation-wide health service coverage. However, our findings demonstrate that high quality routinely collected health facility data combined with ITS can be used for rigorous policy evaluation in resource-limited settings.

Background: Mutuelles is a community-based health insurance program, established since 1999 by the Government of Rwanda as a key component of the national health strategy on providing universal health care. The objective of the study was to evaluate the impact of Mutuelles on achieving universal coverage of medical services and financial risk protection in its first eight years of implementation. Methods and Findings: We conducted a quantitative impact evaluation of Mutuelles between 2000 and 2008 using nationally-representative surveys. At the national and provincial levels, we traced the evolution of Mutuelles coverage and its impact on child and maternal care coverage from 2000 to 2008, as well as household catastrophic health payments from 2000 to 2006. At the individual level, we investigated the impact of Mutuelles' coverage on enrollees' medical care utilization using logistic regression. We focused on three target populations: the general population, under-five children, and women with delivery. At the household level, we used logistic regression to study the relationship between Mutuelles coverage and the probability of incurring catastrophic health spending. The main limitation was that due to insufficient data, we are not able to study the impact of Mutuelles on health outcomes, such as child and maternal mortalities, directly. The findings show that Mutuelles improved medical care utilization and protected households from catastrophic health spending. Among Mutuelles enrollees, those in the poorest expenditure quintile had a significantly lower rate of utilization and higher rate of catastrophic health spending. The findings are robust to various estimation methods and datasets. Conclusions: Rwanda's experience suggests that community-based health insurance schemes can be effective tools for achieving universal health coverage even in the poorest settings. We suggest a future study on how eliminating Mutuelles copayments for the poorest will improve their healthcare utilization, lower their catastrophic health spending, and affect the finances of health care providers. [ABSTRACT FROM AUTHOR]

Despite the efforts of educators, public health officials, and HIV/AIDS prevention experts, condom promotion has failed to stop the HIV epidemic in most of sub-Saharan Africa and most researchers and policy makers have focused on risk reductions for interventions for penetrative sex. We consider another HIV prevention option: female-to-male oral sex (fellatio). Extensive medical evidence indicates that fellatio is roughly as protective against HIV transmission as vaginal sex with a condom, and much safer than unprotected sex, but it is rarely emphasized in HIV prevention curricula. Moreover, available data on the practice of oral sex in Africa suggests that the practice is very rare compared to the practice in the United States. This paper reviews some of the existing evidence on the efficacy and prevalence of oral sex, discusses the potential of this safer sex strategy for mitigating the spread of HIV in Africa, and stresses the need for further research. [ABSTRACT FROM AUTHOR]

Background: Health data can be useful for effective service delivery, decision making, and evaluating existing programs in order to maintain high quality of healthcare. Studies have shown variability in data quality from national health management information systems (HMISs) in sub-Saharan Africa which threatens utility of these data as a tool to improve health systems. The purpose of this study is to assess the quality of Rwanda's HMIS data over a 5-year period. Methods: The World Health Organization (WHO) data quality report card framework was used to assess the quality of HMIS data captured from 2008 to 2012 and is a census of all 495 publicly funded health facilities in Rwanda. Factors assessed included completeness and internal consistency of 10 indicators selected based on WHO recommendations and priority areas for the Rwanda national health sector. Completeness was measured as percentage of non-missing reports. Consistency was measured as the absence of extreme outliers, internal consistency between related indicators, and consistency of indicators over time. These assessments were done at the district and national level. Results: Nationally, the average monthly district reporting completeness rate was 98% across 10 key indicators from 2008 to 2012. Completeness of indicator data increased over time: 2008, 88%; 2009, 91%; 2010, 89%; 2011, 90%; and 2012, 95% (p<0.0001). Comparing 2011 and 2012 health events to the mean of the three preceding years, service output increased from 3% (2011) to 9% (2012). Eighty-three percent of districts reported ratios between related indicators (ANC/DTP1, DTP1/DTP3) consistent with HMIS national ratios. Conclusion and policy implications Our findings suggest that HMIS data quality in Rwanda has been improving over time. We recommend maintaining these assessments to identify remaining gaps in data quality and that results are shared publicly to support increased use of HMIS data.

Background: Mutuelles is a community-based health insurance program, established since 1999 by the Government of Rwanda as a key component of the national health strategy on providing universal health care. The objective of the study was to evaluate the impact of Mutuelles on achieving universal coverage of medical services and financial risk protection in its first eight years of implementation. Methods and Findings: We conducted a quantitative impact evaluation of Mutuelles between 2000 and 2008 using nationally-representative surveys. At the national and provincial levels, we traced the evolution of Mutuelles coverage and its impact on child and maternal care coverage from 2000 to 2008, as well as household catastrophic health payments from 2000 to 2006. At the individual level, we investigated the impact of Mutuelles' coverage on enrollees' medical care utilization using logistic regression. We focused on three target populations: the general population, under-five children, and women with delivery. At the household level, we used logistic regression to study the relationship between Mutuelles coverage and the probability of incurring catastrophic health spending. The main limitation was that due to insufficient data, we are not able to study the impact of Mutuelles on health outcomes, such as child and maternal mortalities, directly. The findings show that Mutuelles improved medical care utilization and protected households from catastrophic health spending. Among Mutuelles enrollees, those in the poorest expenditure quintile had a significantly lower rate of utilization and higher rate of catastrophic health spending. The findings are robust to various estimation methods and datasets. Conclusions: Rwanda's experience suggests that community-based health insurance schemes can be effective tools for achieving universal health coverage even in the poorest settings. We suggest a future study on how eliminating Mutuelles copayments for the poorest will improve their healthcare utilization, lower their catastrophic health spending, and affect the finances of health care providers.