Improving data quality across 3 sub-Saharan African countries using the Consolidated Framework for Implementation Research (CFIR): results from the African Health Initiative.

BACKGROUND: High-quality data are critical to inform, monitor and manage health programs. Over the seven-year African Health Initiative of the Doris Duke Charitable Foundation, three of the five Population Health Implementation and Training (PHIT) partnership projects in Mozambique, Rwanda, and Zambia introduced strategies to improve the quality and evaluation of routinely-collected data at the primary health care level, and stimulate its use in evidence-based decision-making. Using the Consolidated Framework for Implementation Research (CFIR) as a guide, this paper: 1) describes and categorizes data quality assessment and improvement activities of the projects, and 2) identifies core intervention components and implementation strategy adaptations introduced to improve data quality in each setting. METHODS: The CFIR was adapted through a qualitative theme reduction process involving discussions with key informants from each project, who identified two domains and ten constructs most relevant to the study aim of describing and comparing each country's data quality assessment approach and implementation process. Data were collected on each project's data quality improvement strategies, activities implemented, and results via a semi-structured questionnaire with closed and open-ended items administered to health management information systems leads in each country, with complementary data abstraction from project reports. RESULTS: Across the three projects, intervention components that aligned with user priorities and government systems were perceived to be relatively advantageous, and more readily adapted and adopted. Activities that both assessed and improved data quality (including data quality assessments, mentorship and supportive supervision, establishment and/or strengthening of electronic medical record systems), received higher ranking scores from respondents. CONCLUSION: Our findings suggest that, at a minimum, successful data quality improvement efforts should include routine audits linked to ongoing, on-the-job mentoring at the point of service. This pairing of interventions engages health workers in data collection, cleaning, and analysis of real-world data, and thus provides important skills building with on-site mentoring. The effect of these core components is strengthened by performance review meetings that unify multiple health system levels (provincial, district, facility, and community) to assess data quality, highlight areas of weakness, and plan improvements

Toward utilization of data for program management and evaluation: quality assessment of five years of health management information system data in Rwanda

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

Investigating access to hepatitis C testing and treatment in Rwanda and beyond

The full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.Medicine, Faculty ofPopulation and Public Health (SPPH), School ofGraduat

Improving data quality across 3 sub-Saharan African countries using the Consolidated Framework for Implementation Research (CFIR): results from the African Health Initiative

Abstract Background High-quality data are critical to inform, monitor and manage health programs. Over the seven-year African Health Initiative of the Doris Duke Charitable Foundation, three of the five Population Health Implementation and Training (PHIT) partnership projects in Mozambique, Rwanda, and Zambia introduced strategies to improve the quality and evaluation of routinely-collected data at the primary health care level, and stimulate its use in evidence-based decision-making. Using the Consolidated Framework for Implementation Research (CFIR) as a guide, this paper: 1) describes and categorizes data quality assessment and improvement activities of the projects, and 2) identifies core intervention components and implementation strategy adaptations introduced to improve data quality in each setting. Methods The CFIR was adapted through a qualitative theme reduction process involving discussions with key informants from each project, who identified two domains and ten constructs most relevant to the study aim of describing and comparing each country’s data quality assessment approach and implementation process. Data were collected on each project’s data quality improvement strategies, activities implemented, and results via a semi-structured questionnaire with closed and open-ended items administered to health management information systems leads in each country, with complementary data abstraction from project reports. Results Across the three projects, intervention components that aligned with user priorities and government systems were perceived to be relatively advantageous, and more readily adapted and adopted. Activities that both assessed and improved data quality (including data quality assessments, mentorship and supportive supervision, establishment and/or strengthening of electronic medical record systems), received higher ranking scores from respondents. Conclusion Our findings suggest that, at a minimum, successful data quality improvement efforts should include routine audits linked to ongoing, on-the-job mentoring at the point of service. This pairing of interventions engages health workers in data collection, cleaning, and analysis of real-world data, and thus provides important skills building with on-site mentoring. The effect of these core components is strengthened by performance review meetings that unify multiple health system levels (provincial, district, facility, and community) to assess data quality, highlight areas of weakness, and plan improvements

Next wave of interventions to reduce under-five mortality in Rwanda: a cross-sectional analysis of demographic and health survey data

Background: Sustained investments in Rwanda’s health system have led to historic reductions in under five (U5) mortality. Although Rwanda achieved an estimated 68% decrease in the national under U5 mortality rate between 2002 and 2012, according to the national census, 5.8% of children still do not reach their fifth birthday, requiring the next wave of child mortality prevention strategies. Methods: This is a cross-sectional study of 9002 births to 6328 women age 15–49 in the 2010 Rwanda Demographic and Health Survey. We tested bivariate associations between 29 covariates and U5 mortality, retaining covariates with an odds ratio p < 0.1 for model building. We used manual backward stepwise logistic regression to identify correlates of U5 mortality in all children U5, 0–11 months, and 12–59 months. Analyses were performed in Stata v12, adjusting for complex sample design. Results: Of 14 covariates associated with U5 mortality in bivariate analysis, the following remained associated with U5 mortality in multivariate analysis: household being among the poorest of the poor (OR = 1.98), child being a twin (OR = 2.40), mother having 3–4 births in the past 5 years (OR = 3.97) compared to 1–2 births, mother being HIV positive (OR = 2.27), and mother not using contraceptives (OR = 1.37) compared to using a modern method (p < 0.05 for all). Mother experiencing physical or sexual violence in the last 12 months was associated with U5 mortality in children ages 1–4 years (OR = 1.48, p < 0.05). U5 survival was associated with a preceding birth interval 25–50 months (OR = 0.67) compared to 9–24 months, and having a mosquito net (OR = 0.46) (p < 0.05 for both). Conclusions: In the past decade, Rwanda rolled out integrated management of childhood illness, near universal coverage of childhood vaccinations, a national community health worker program, and a universal health insurance scheme. Identifying factors that continue to be associated with childhood mortality supports determination of which interventions to strengthen to reduce it further. This study suggests that Rwanda’s next wave of U5 mortality reduction should target programs in improving neonatal outcomes, poverty reduction, family planning, HIV services, malaria prevention, and prevention of intimate partner violence

Approaches and impact of non-academic research capacity strengthening training models in sub-Saharan Africa: a systematic review

Background: Research is essential to identify and prioritize health needs and to develop appropriate strategies to improve health outcomes. In the last decade, non-academic research capacity strengthening trainings in sub-Saharan Africa, coupled with developing research infrastructure and the provision of individual mentorship support, has been used to build health worker skills. The objectives of this review are to describe different training approaches to research capacity strengthening in sub-Saharan Africa outside academic programs, assess methods used to evaluate research capacity strengthening activities, and learn about the challenges facing research capacity strengthening and the strategies/innovations required to overcome them. Methodology The PubMed database was searched using nine search terms and articles were included if 1) they explicitly described research capacity strengthening training activities, including information on program duration, target audience, immediate program outputs and outcomes; 2) all or part of the training program took place in sub-Saharan African countries; 3) the training activities were not a formal academic program; 4) papers were published between 2000 and 2013; and 5) both abstract and full paper were available in English. Results: The search resulted in 495 articles, of which 450 were retained; 14 papers met all inclusion criteria and were included and analysed. In total, 4136 people were trained, of which 2939 were from Africa. Of the 14 included papers, six fell in the category of short-term evaluation period and eight in the long-term evaluation period. Conduct of evaluations and use of evaluation frameworks varied between short and long term models and some trainings were not evaluated. Evaluation methods included tests, surveys, interviews, and systems approach matrix. Conclusions: Research capacity strengthening activities in sub-Saharan Africa outside of academic settings provide important contributions to developing in-country capacity to participate in and lead research. Institutional support, increased funds, and dedicated time for research activities are critical factors that lead to the development of successful programs. Further, knowledge sharing through scientific articles with sufficient detail is needed to enable replication of successful models in other settings

Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis

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

Making progress towards food security: evidence from an intervention in three rural districts of Rwanda

Objective: Determining interventions to address food insecurity and poverty, as well as setting targets to be achieved in a specific time period have been a persistent challenge for development practitioners and decision makers. The present study aimed to assess the changes in food access and consumption at the household level after one-year implementation of an integrated food security intervention in three rural districts of Rwanda. Design: A before-and-after intervention study comparing Household Food Insecurity Access Scale (HFIAS) scores and household Food Consumption Scores (FCS) at baseline and after one year of programme implementation. Setting: Three rural districts of Rwanda (Kayonza, Kirehe and Burera) where the Partners In Health Food Security and Livelihoods Program (FSLP) has been implemented since July 2013. Subjects All 600 households enrolled in the FSLP were included in the study. Results: There were significant improvements (P<0·001) in HFIAS and FCS. The median decrease in HFIAS was 8 units (interquartile range (IQR) −13·0, −3·0) and the median increase for FCS was 4·5 units (IQR −6·0, 18·0). Severe food insecurity decreased from 78 % to 49 %, while acceptable food consumption improved from 48 % to 64 %. The change in HFIAS was significantly higher (P=0·019) for the poorest households. Conclusions: Our study demonstrated that an integrated programme, implemented in a setting of extreme poverty, was associated with considerable improvements towards household food security. Other government and non-government organizations’ projects should consider a similar holistic approach when designing structural interventions to address food insecurity and extreme poverty

Impact of <scp>COVID</scp> ‐19 pandemic on <scp>HCV</scp> care cascade in Rwanda: Ecological study from July 2019 to June 2021

Content available: Author Interview and Audio Recordin