Electronic health records in Africa have moved from exception to norm in many countries faster than most outside observers expected. A decade ago, the majority of clinical encounters across Sub-Saharan Africa were documented on paper registers, if documented at all. Today, Kenya's national HIV programme spans over 3,700 treatment facilities with approximately 1.3 million patients on ART, supported by KenyaEMR, deployed across over 2,300 facilities and covering more than 90 percent of ART patients in the country. Rwanda's public health system has been rolling out its e-Ubuzima integrated EHR across public-sector facilities, with a target of nationwide coverage by end of 2025. Nigeria's largest tertiary hospitals run cloud-based EMR systems serving millions of outpatient visits annually. The adoption is real, but it is uneven, fragmented, and often incomplete in ways that matter for both patient care and research. This article maps the current state of electronic health records across Africa, the systems driving adoption, the barriers limiting impact, and what better EHR infrastructure would mean for the continent's health and research capacity.
The current state of electronic health records in Africa
Estimating EHR coverage across Africa requires distinguishing between aggregate data systems and patient-level record systems. DHIS2 (the District Health Information Software 2) is deployed across dozens of African countries (part of a global footprint spanning more than 70 low- and middle-income countries) and provides a standardised platform for aggregate health statistics: facility-level counts of patient visits, disease notifications, vaccine doses administered, and essential medicines dispensed. DHIS2 is not an EHR; it does not record individual patient encounters. But it forms the backbone of national health information systems across the continent and provides population-level data that EMR systems cannot yet match in geographic coverage.
True electronic health records, systems that capture individual patient-level data across encounters, are concentrated in specific programme areas and specific countries. HIV treatment programmes, supported by PEPFAR funding, drove much of the early EMR adoption across East and West Africa from the mid-2000s onwards. The requirement for patient-level reporting on treatment outcomes created a funding stream and technical mandate that general health services lacked. The result is that HIV clinics in Kenya, Uganda, Tanzania, and Nigeria are often significantly better digitised than the general outpatient departments of the same facilities.
The digital health sector's growth has accelerated EHR adoption beyond HIV into general clinical settings. Private hospitals and clinic networks in Nigeria, Kenya, and South Africa have adopted commercial and cloud-based EMR platforms at scale. Public-sector adoption beyond HIV remains more limited, concentrated in urban teaching hospitals and facilities in countries with strong central coordination, most prominently Rwanda, Kenya, and Ethiopia.
Major EHR systems across the continent
EHR systems in Africa span a spectrum from globally deployed open-source platforms to country-specific national systems to commercial solutions serving private-sector providers. Several dominate the landscape.
OpenMRS is the most widely deployed patient-level EMR platform in Sub-Saharan Africa. Originally developed in 2004 through a collaboration between Partners in Health, the Regenstrief Institute, and African implementers, OpenMRS is an open-source, modular system designed for resource-limited settings. It has been deployed in over 80 countries globally, with particularly strong presence in Kenya, Uganda, Rwanda, Tanzania, Ethiopia, Nigeria, and Mozambique. OpenMRS is not a single system; it is a framework on which country-specific implementations are built, each tailored to local clinical workflows, reporting requirements, and data standards.
DHIS2 Tracker extends the aggregate DHIS2 system to allow individual patient tracking. Several countries have deployed DHIS2 Tracker for maternal and child health, malaria, and nutrition programmes, creating patient-level longitudinal records within the existing DHIS2 infrastructure. This approach simplifies integration with national reporting systems but has limitations in clinical depth compared to full EMR implementations.
Helium Health is the largest commercial EMR provider in West Africa, particularly Nigeria. Its cloud-based platform covers inpatient and outpatient management, billing, pharmacy, laboratory, and analytics. The company serves healthcare providers across Nigeria, Ghana, Senegal, and other markets, and has expanded into East Africa, generating structured clinical data from private-sector facilities that historically had no systematic recording.
CommCare, developed by Dimagi, is widely used for community health worker programmes across Sub-Saharan Africa. It is not a hospital EMR, but it captures patient-level data for community-based interventions, maternal health tracking, and disease surveillance. CommCare data from community programmes represents a significant source of health records in countries with strong community health worker networks.
Epic and Oracle Health (formerly Cerner) have limited but growing presence in higher-resource private-sector facilities, particularly in South Africa and Kenya. These systems are typically too expensive for most African public-sector settings but are used by private hospital groups with the budget and IT infrastructure to support them.
OpenMRS: the open-source foundation
OpenMRS warrants a closer look because of its foundational role in African EMR infrastructure. The system's design philosophy (modular, adaptable, and open) made it uniquely suited to the heterogeneous technical and clinical environments of African health systems.
The OpenMRS community has developed a concept dictionary, the OpenMRS concept database, that provides standardised definitions for clinical data elements. This standardisation is what makes cross-facility and cross-country data linkage possible in theory, though achieving it in practice requires disciplined implementation across facilities, which is rarely the norm.
KenyaEMR, Kenya's national HIV EMR system, is built on OpenMRS. The Ministry of Health has deployed KenyaEMR across over 2,300 facilities in Kenya, covering more than 90 percent of patients on ART. Kenya's broader HIV treatment network spans over 3,700 facilities with approximately 1.3 million patients in HIV care as of 2023. The Kenya Health Information System (KHIS), which runs on DHIS2, receives aggregate reports from KenyaEMR facilities, creating a reasonably integrated national HIV data ecosystem.
Rwanda's national EMR implementation, coordinated by the Rwanda Biomedical Centre (RBC), uses an OpenMRS-based system deployed across public health facilities nationwide. Rwanda's relatively small size, strong central government coordination, and sustained investment in health IT have produced one of Africa's most comprehensive national EMR coverage rates, with the majority of public-sector facilities connected to a shared electronic system. The data generated through Rwanda's system has supported multiple published research studies and contributes to the health indicators that make Rwanda's health outcomes notable relative to its income level.
In Uganda, the UgandaEMR programme, a Ministry of Health-mandated OpenMRS distribution, has been deployed across hundreds of facilities, starting with the HIV programme but expanding to maternal and child health and tuberculosis care. The programme is managed by the Monitoring and Evaluation Technical Support (METS) team at Makerere University School of Public Health, with the Infectious Diseases Institute at Makerere also operating EMR systems within its own clinic and serving as a research partner.
Country-level EMR adoption profiles
EMR adoption across Africa varies significantly by country, income level, and programme area. A brief comparative picture:
Kenya has the continent's most advanced national EMR programme in the HIV space, with KenyaEMR covering most PEPFAR-supported facilities. The private sector uses a range of commercial systems. General public-sector EMR beyond HIV is less developed but expanding through the Ministry of Health's Digital Health Division.
Rwanda is pursuing one of the most ambitious public-sector EMR rollouts in Sub-Saharan Africa, with its e-Ubuzima system being deployed across district hospitals and health centres toward a target of nationwide coverage. The data quality from Rwandan facilities is generally higher than regional peers, due to sustained supervision and quality improvement investment.
Nigeria presents a mixed picture. Lagos and Abuja host some of the continent's most sophisticated private EMR deployments, while many public facilities in rural states remain on paper. NCDC (Nigeria Centre for Disease Control) and FMOH have invested in DHIS2 and some patient-level tracking for priority programmes, but a unified national EMR strategy is still developing.
Ethiopia has made significant investments in iHRIS (Integrated Human Resources Information System) for health workforce management and in DHIS2 for national reporting. EMR coverage in public facilities is growing but remains limited outside major cities and teaching hospitals.
South Africa's private sector has sophisticated EMR and claims data systems, while the public sector's EMR coverage is more variable across provinces. The Western Cape is the most advanced province for public-sector health IT.
Ghana and Tanzania have active DHIS2 national reporting systems and growing PEPFAR-supported EMR coverage in HIV clinics, with general health EMR still concentrated in urban hospitals.
Barriers to health records digitization
Health records digitization in Africa faces barriers at every level of the health system. Understanding them is essential for any organisation planning to work with African health data.
Infrastructure constraints are the most fundamental barrier. Reliable electricity is not available at all hours in many facilities. Power outages require UPS systems and generator backups that add cost and maintenance burden. Internet connectivity for cloud-based systems is inconsistent outside urban centres. Some rural facilities operate essentially offline, syncing data when connectivity is available.
Workforce capacity is the second major barrier. EMR systems require clinicians and records staff to change established workflows, often adding time to patient encounters in already overloaded settings. Training takes time and must be repeated as staff turn over. Technical support for system maintenance and troubleshooting is scarce in rural settings.
Funding sustainability is a structural challenge. Most large-scale EMR deployments in Africa have been funded by donor organisations: PEPFAR, the Global Fund, the Gates Foundation, and bilateral aid agencies. When donor projects end, systems often degrade or fall into disuse because government budgets cannot absorb the ongoing costs of maintenance, upgrades, and support.
Fragmentation is perhaps the most damaging barrier to using EHR data for research. A facility may run three different systems for HIV, maternal health, and general outpatient care, each capturing overlapping patient data in incompatible formats. Patients do not have unique national identifiers in most African countries, making cross-system patient matching difficult. The result is data silos that cannot be integrated without substantial technical investment.
Legal and governance uncertainty around health data use has slowed some EHR deployments. As data protection laws have become more stringent across the continent, facility operators and ministries have become more cautious about deploying systems that collect sensitive patient data without clear legal frameworks for data access and use.
Interoperability and data standards
Interoperability, the ability of different health systems to exchange and use data, is the central challenge in translating Africa's growing EHR base into actionable health intelligence.
The global standard for health data exchange, HL7 FHIR (Fast Healthcare Interoperability Resources), has gained adoption in Africa, particularly in countries building or upgrading national health information exchanges. South Africa has been an early FHIR adopter, and Kenya's national digital health architecture references FHIR as the standard for integration. Rwanda's Health Information Exchange uses FHIR for communication between its national OpenMRS system and DHIS2.
OpenHIE (Open Health Information Exchange) provides an open-source architecture framework specifically designed for resource-limited settings. It defines a reference architecture for health information exchanges, including a shared health record, a terminology service, and a facility registry. Several African countries have adopted OpenHIE components as the foundation for their national health information exchanges.
IHE (Integrating the Healthcare Enterprise) standards, particularly IHE profiles for document sharing (XDS), care management (PCC), and patient identity management (PIX/PDQ), are referenced in several African EMR implementations, though full compliance is rare outside well-resourced private-sector deployments.
The gap between standards adoption on paper and working interoperability in practice remains wide. Even where facilities use the same EMR system, variations in implementation (different concept mappings, different data entry practices, different local customisations) make data aggregation technically complex. Organisations like Kapsule that aggregate data across facilities must invest substantial effort in data harmonisation, mapping local coding to standardised terminologies, and resolving patient deduplication before the data can be used for analysis.
What health records digitization means for research
Better health records digitization across Africa would transform the continent's research capacity in ways that go well beyond administrative efficiency.
Clinical trial feasibility analysis becomes practical at scale. Sponsors can use structured EMR data to model eligible patient populations before committing to site activation. A query across an EMR network can estimate how many patients meet specific eligibility criteria (age, diagnosis, lab values, prior treatment history) at each potential trial site, enabling evidence-based site selection rather than reliance on site coordinator estimates.
Real-world evidence generation becomes possible. Longitudinal EMR records, capturing diagnoses, treatments, lab results, and outcomes over time, are the raw material for real-world evidence studies. Africa's disease burden makes it a critical geography for understanding treatment effectiveness in conditions like HIV, TB, diabetes, and hypertension in populations that are biologically and socioeconomically distinct from Western trial cohorts.
Pharmacovigilance improves substantially. Post-market safety surveillance requires systematic capture of adverse events across a broad patient population. EMR systems that flag potential adverse events and link prescriptions to outcomes enable pharmacovigilance programmes that are currently not possible in paper-based settings.
Health system performance monitoring becomes actionable. Aggregated facility-level data from EMR systems enables governments and donors to identify facilities with poor outcomes, high loss-to-follow-up rates, or drug stock-outs, and intervene before problems become crises.
Best practices for EHR implementation in African settings
For organisations involved in EHR deployment, whether as technology providers, donors, government implementers, or research partners, several practices consistently distinguish successful implementations from failed ones.
Design for the local workflow, not the ideal workflow. Systems designed by international developers who have not spent time in African clinical settings often impose workflows that make no sense locally. Successful implementations involve extensive user research and iterative design with frontline clinicians.
Invest in change management, not just technology. The technology is often the easier part. Getting clinical staff to adopt new workflows, managers to use data for decisions, and IT teams to maintain systems requires sustained change management investment that most implementation budgets undervalue.
Build for offline-first. Systems that fail when the internet is unavailable cannot be relied upon in most African clinical settings. Offline-capable architectures with background synchronisation are essential for facilities outside major urban centres.
Align with national standards from day one. Deploying a system that cannot integrate with the national reporting framework creates a data silo. Implementing HL7 FHIR, OpenHIE, and country-specific coding standards from the start avoids costly retrofitting later.
Plan for sustainability from the proposal stage. Donor-funded EHR deployments that do not have a government budget line for ongoing costs by the end of the grant period rarely survive the transition. Sustainability planning should begin before implementation, not after.
Kapsule provides access to structured, de-identified health records covering over 75 million patients across 9 African countries. Contact our team to discuss how aggregated EHR data from African facilities can support your research, market analysis, or product development.
This article is intended for informational purposes only and does not constitute legal, medical, or regulatory advice. Readers should obtain independent professional counsel for their specific circumstances.