IntroductionAlthough Rwanda’s health system underwent major reforms and improvements after the 1994 Genocide, the health system and population health in the southeast lagged behind other areas. In 2005, Partners In Health and the Rwandan Ministry of Health began a health system strengthening intervention in this region. We evaluate potential impacts of the intervention on maternal and child health indicators.MethodsCombining results from the 2005 and 2010 Demographic and Health Surveys with those from a supplemental 2010 survey, we compared changes in health system output indicators and population health outcomes between 2005 and 2010 as reported by women living in the intervention area with those reported by the pooled population of women from all other rural areas of the country, controlling for potential confounding by economic and demographic variables.ResultsOverall health system coverage improved similarly in the comparison groups between 2005 and 2010, with an indicator of composite coverage of child health interventions increasing from 57.9% to 75.0% in the intervention area and from 58.7% to 73.8% in the other rural areas. Under-five mortality declined by an annual rate of 12.8% in the intervention area, from 229.8 to 83.2 deaths per 1000 live births, and by 8.9% in other rural areas, from 157.7 to 75.8 deaths per 1000 live births. Improvements were most marked among the poorest households.ConclusionWe observed dramatic improvements in population health outcomes including under-five mortality between 2005 and 2010 in rural Rwanda generally and in the intervention area specifically.

BackgroundAchieving the United Nations Sustainable Development Goals in sub-Saharan Africa will require substantial improvements in the coverage and performance of primary health care delivery systems. Projects supported by the Doris Duke Charitable Foundation’s (DDCF) African Health Initiative (AHI) created public-private-academic and community partnerships in five African countries to implement and evaluate district-level health system strengthening interventions. In this study, we captured common implementation experiences and lessons learned to understand core elements of successful health systems interventions.MethodsWe used qualitative data from key informant interviews and annual progress reports from the five Population Health Implementation and Training (PHIT) partnership projects funded through AHI in Ghana, Mozambique, Rwanda, Tanzania, and Zambia.ResultsFour major overarching lessons were highlighted. First, variety and inclusiveness of concerned key players (public, academic and private) are necessary to address complex health system issues at all levels. Second, a learning culture that promotes evidence creation and ability to efficiently adapt were key in order to meet changing contextual needs. Third, inclusion of strong implementation science tools and strategies allowed informed and measured learning processes and efficient dissemination of best practices. Fourth, five to seven years was the minimum time frame necessary to effectively implement complex health system strengthening interventions and generate the evidence base needed to advocate for sustainable change for the PHIT partnership projects.ConclusionThe AHI experience has raised remaining, if not overlooked, challenges and potential solutions to address complex health systems strengthening intervention designs and implementation issues, while aiming to measurably accomplish sustainable positive change in dynamic, learning, and varied contexts.

BackgroundRwanda has dramatically reduced child mortality, but the causes and sociodemographic drivers for mortality are poorly understood.MethodsWe conducted a matched case-control study of all children who died before 5 years of age in eastern Rwanda between 1st March 2013 and 28th February 2014 to identify causes and risk factors for death. We identified deaths at the facility level and via a community health worker reporting system. We used verbal social autopsy to interview caregivers of deceased children and controls matched by area and age. We used InterVA4 to determine probable causes of death and cause-specific mortality fractions, and utilized conditional logistic regression to identify clinical, family, and household risk factors for death.ResultsWe identified 618 deaths including 174 (28.2%) in neonates and 444 (71.8%) in non-neonates. The most commonly identified causes of death were pneumonia, birth asphyxia, and meningitis among neonates and malaria, acute respiratory infections, and HIV/AIDS-related death among non-neonates. Among neonates, 54 (31.0%) deaths occurred at home and for non-neonates 242 (54.5%) deaths occurred at home. Factors associated with neonatal death included home birth (aOR: 2.0; 95% CI: 1.4–2.8), multiple gestation (aOR: 2.1; 95% CI: 1.3–3.5), both parents deceased (aOR: 4.7; 95% CI: 1.5–15.3), mothers non-use of family planning (aOR: 0.8; 95% CI: 0.6–1.0), lack of accompanying person (aOR: 1.6; 95% CI: 1.1–2.1), and a caregiver who assessed the medical services they received as moderate to poor (aOR: 1.5; 95% CI: 1.2–1.9). Factors associated with non-neonatal deaths included multiple gestation (aOR: 2.8; 95% CI: 1.7–4.8), lack of adequate vaccinations (aOR: 1.7; 95% CI: 1.2–2.3), household size (aOR: 1.2; 95% CI: 1.0–1.4), maternal education levels (aOR: 1.9; 95% CI: 1.2–3.1), mothers non-use of family planning (aOR: 1.6; 95% CI: 1.4–1.8), and lack of household electricity (aOR: 1.4; 95% CI: 1.0–1.8).ConclusionIn the context of rapidly declining childhood mortality in Rwanda and increased access to health care, we found a large proportion of remaining deaths occur at home, with home deliveries still representing a significant risk factor for neonatal death. The major causes of death at a population level remain largely avoidable communicable diseases. Household characteristics associated with death included well-established socioeconomic and care-seeking risk factors.

IntroductionThe shortage and maldistribution of health care workers in sub-Saharan Africa is a major concern for rural health facilities. Rural areas have 63% of sub-Saharan Africa population but only 37% of its doctors. Although attrition of health care workers is implicated in the human resources for health crisis in the rural settings, few studies report attrition rates and risk factors for attrition in rural district hospitals in sub-Saharan Africa.MethodsWe assessed attrition of health care workers at a Kirehe District Hospital in rural Rwanda. We included all hospital staff employed as of January 1, 2013 in this retrospective cohort study. We report the proportion of staff that left employment during 2013, and used a logistic regression to assess individual characteristics associated with attrition.ResultsOf the 142 staff employed at Kirehe District Hospital at the start of 2013, 31.7% (n=45) of all staff and 81.8% (n=9) of doctors left employment in 2013. Being a doctor (OR=10.0, 95% CI: 1.9-52.1, p=0.006) and having up to two years of experience at the hospital (OR=5.3, 95% CI: 1.3-21.7, p=0.022) were associated with attrition.ConclusionKirehe District Hospital experienced high attrition rates in 2013, particularly among doctors. Opportunities for further training through Rwanda’s Human Resources for Health program in 2013 and a two-year compulsory service program for doctors that is not linked to interventions for rural retention may have driven these patterns. Efforts to link these programs with rural placement and retention strategies are recommended.

BackgroundEvaluations 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.MethodsWe 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.ResultsPHIT 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]).ConclusionWe 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.