Strengthening Health Systems Through Evidence
From maternal and child health to disease surveillance and health financing, D4Act helps governments, donors, and NGOs make data-driven decisions that improve healthcare access, quality, and accountability across Africa.
Governance & Service Delivery Evaluation
Africa's health systems face immense challenges: the continent carries 24% of the global disease burden yet has only 3% of the world's health workforce (WHO Africa, 2023). D4Act's health practice helps close this gap by generating actionable evidence on what interventions actually improve health outcomes.
We conduct rigorous evaluations of health programs including: community health worker effectiveness, results-based financing schemes, immunization coverage interventions, and reproductive health service delivery models. Our evaluations use mixed-methods approaches - combining quantitative household surveys with qualitative interviews with frontline health workers and community members.
"The challenge in Africa is not a lack of health data - it is the gap between data collection and evidence-informed decision-making. D4Act exists to bridge that gap."
- D4Act Health PracticeKey Focus Areas
Maternal & Child Health
Evaluating prenatal care programs, facility-based delivery interventions, and nutrition supplementation schemes. Sub-Saharan Africa accounts for 66% of global maternal deaths - our evidence helps target resources where impact is greatest.
Health Financing & RBF
Assessing the effectiveness of results-based financing, community health insurance (mutuelles), and performance incentive programs. Our evaluations have shown that RBF can increase facility utilization by 15-25% when properly designed.
Disease Surveillance & Epidemiology
Supporting real-time disease surveillance systems, outbreak response evaluation, and pandemic preparedness assessments. Lessons from COVID-19 and Ebola responses have reshaped our approach to rapid evidence generation.
Digital Health & mHealth
Evaluating mobile health interventions, telemedicine platforms, and digital record systems. Africa's 900M+ mobile phone users represent a massive opportunity for health system leapfrogging through technology.
Our Health Sector Approach
Our end-to-end methodology - from initial assessment to sustainable impact.
Frequently asked questions
Which evaluation standards and donor frameworks do you align with?
Our health evaluations align with OECD-DAC criteria (relevance, coherence, effectiveness, efficiency, impact, sustainability) and donor-specific frameworks - PEPFAR MER 2.0, Global Fund Performance Framework, Gavi Strategic Frameworks, USAID Standard Foreign Assistance Indicators, and WHO MERG guidance. Evaluation matrices and analysis plans are documented up front; results pass internal peer review before delivery.
What kinds of health programmes have you evaluated, and at what scale?
Routine immunisation (UNICEF, Gavi, WHO), HIV / TB / PMTCT cascades (PEPFAR / EGPAF / Global Fund), reproductive health and family planning (USAID, Gates Foundation), community health worker programmes, and national digital-health investments. Engagements range from single-district baseline surveys to multi-country evaluations covering 50+ facilities and 4,000+ households.
How do you handle health-data systems like DHIS2 and CommCare?
We extract from DHIS2 (REST API, Tracker, Capture), reconcile with CommCare submissions, ODK forms, paper registers and partner-specific systems through our Data Bridge platform, and run automated quality checks via DataPulse. Where ministries lack interoperability, we design the bridges - typically using FHIR, ADX, or custom adapters depending on the receiving system.
How do you ensure ethics and equity in your health evaluations?
Every health evaluation passes a written ethics protocol with IRB approval where applicable, do-no-harm safeguards, informed consent in local languages, and gender-disaggregated outcomes by default. We use intersectional analysis (geography, socio-economic status, age, disability via the Washington Group Short Set) and report effect heterogeneity as a first-class result, not an annex.