Nigeria’s digital health records promise stalls at unreliable power and costly infrastructure

Nigeria’s hospitals and clinics have installed digital record systems at a striking pace on paper, but a new mixed-methods study finds that the reality on the clinical front line lags far behind the institutional claims. Researchers from Nigeria report that while roughly 75 percent of 130 facilities documented in secondary institutional records had some form of digital or hybrid electronic health record system in place, only 23 percent of 26 facilities surveyed directly were running fully electronic systems. Another 42 percent were caught in hybrid workflows that juggle both electronic and paper records, and 35 percent still relied entirely on paper. The study, published in BMC Digital Health, describes this disconnect between reported deployment and operational maturity as a substantial socio-technical gap.

The research team, led by Olumhense Adoghe with Braimoh Ikharo and Henry Amhenrior, used an exploratory sequential mixed-methods design to diagnose the electronic health record landscape in Nigeria. Their primary data came from a structured online questionnaire of healthcare professionals involved in patient record management or health information systems, yielding 26 valid responses from facilities across 11 states and all six of Nigeria’s geopolitical zones. Secondary institutional data, drawn from vendor deployment lists, government and regulatory publications, hospital websites and peer-reviewed literature, covered 130 facilities nationwide and served as a national baseline for reported digital presence.

The analytical toolkit went beyond simple descriptive statistics. The team applied descriptive summaries, Chi-square tests of independence, and systems-engineering instruments including Pareto analysis, Fishbone (Ishikawa) diagrams and the Technology Acceptance Model framework to prioritize bottlenecks and assess user acceptance. The authors deliberately framed the work as exploratory and diagnostic rather than confirmatory, arguing that a causal study design would be premature in a region where electronic health record use is still in its early stages and national data remain scarce.

The Pareto analysis identified what the researchers call the vital few barriers. Power instability was reported by 76.9 percent of respondents, high implementation costs by 69.2 percent, and poor information technology infrastructure by 65.4 percent. Together these three factors accounted for 70.5 percent of reported barriers, and when lack of technical support was added, the cumulative contribution rose to 83.3 percent. In other words, four factors explain more than 80 percent of the underperformance of electronic record systems in the surveyed facilities, marking them as the priority targets for systemic intervention.

The infrastructure measurements behind those barriers were stark. Mean reliability ratings on a 10-point scale were just 2.3 out of 10 for power supply and 3.5 out of 10 for network internet connectivity. Perceptions of system reliability were polarized: 53.8 percent of respondents reported rare or no system failures, while 15.4 percent dealt with system failures daily. Some facilities, it appears, have achieved relatively stable electronic record operation, while others face persistent and substantial reliability problems that undermine daily clinical work.

Yet amid these constraints, staff satisfaction with the systems was relatively high at 57.7 percent. Within the Technology Acceptance Model framework, the authors interpret this as a sign that healthcare professionals may recognize the usefulness of electronic health records even when infrastructural failures degrade ease of use and operational reliability. They caution, however, that the study did not directly measure perceived usefulness and perceived ease of use as separate constructs, so this interpretation should be considered exploratory. The practical implication is notable: the main obstacle appears not to be user resistance but a fragile infrastructure envelope.

The study also uncovered a sharp hierarchy by facility type. Adoption of digital records was much greater in tertiary and specialist institutions than in secondary and primary facilities. A Chi-square test of independence yielded a statistic of 8.06 with a p-value below 0.05, indicating an association between facility type and adoption status. Because the primary sample comprised only 26 facilities and used geographically stratified convenience sampling, the authors stress that this is a preliminary indication of possible adoption trends rather than definitive proof. Trends in the secondary data showed a significant rise in adoption after 2019, concentrated in tertiary and specialist institutions, suggesting an uneven, gradual shift toward digitalization.

The hybrid systems that dominate the middle of the adoption spectrum emerged as a bottleneck in their own right. The authors argue that hybrid models, often seen as stepping stones toward full digitalization, carry considerable architectural limitations: manual data entry at the paper-digital interface adds data latency, raises the risk of transcription errors, and doubles the administrative burden on clinicians. More seriously, a mixed environment blocks more advanced digital health capabilities, such as clinical decision support delivered at the point of care or real-time public health analytics, which depend on a fully digital data stream. Without a deliberate transition policy, they warn, this hybrid trap can become more of a barrier than an enabler.

The secondary data also revealed substantial dependence on global cloud hyperscalers such as AWS and Azure, which the authors flag as an economic and regulatory risk. Cloud subscriptions denominated in US dollars expose Nigerian institutions to foreign-exchange risk, and the rollout of the Nigeria Data Protection Act of 2023 raises questions about data sovereignty and compliance when sensitive health records sit on foreign-owned servers. Among their recommendations, the researchers call for national interoperability standards such as HL7 and FHIR to reduce vendor lock-in and fragmentation, tax incentives or subsidies for solar-powered microgrids dedicated to record systems and server rooms, and the development of Naira-denominated domestic cloud hosting to align with national regulatory and economic realities.

The authors are candid about the limits of their evidence. No a priori sample size calculation was performed because the survey was exploratory and not designed to estimate nationally representative prevalence, and convenience sampling may have overrepresented facilities with prior digital health experience. Findings from the primary survey should therefore be read as exploratory observations rather than national estimates, though the consistency between the primary and secondary datasets strengthens the broader picture. For context, the study notes that high-income countries have achieved near-universal adoption, with more than 96 percent of non-federal acute care hospitals in the United States reported to have certified electronic record systems, while EHR use in many African countries remains limited and often tied to donor-supported or disease-specific programs. The team calls for longitudinal studies tracking how specific infrastructural interventions affect system performance, and for wider surveys reaching rural and primary care centers. Their overall conclusion is that Nigeria’s electronic health record transition is real but fragile: institutional ambition is frequently obstructed by unreliable power, high costs and weak infrastructure, and fixing that envelope, rather than training users or adding software features, is where investment will matter most.

Subject of Research: Adoption status, barriers and performance bottlenecks of cloud-based electronic health record systems in Nigerian healthcare facilities

Article Title: Cloud-based Electronic Health Records (EHR) adoption rate in Nigeria: barriers and performance bottlenecks

Article References: Adoghe, O., Ikharo, B., & Amhenrior, H. (2026). Cloud-based Electronic Health Records (EHR) adoption rate in Nigeria: barriers and performance bottlenecks. BMC Digital Health, 4(1), Article 65. https://doi.org/10.1186/s44247-026-00297-2

Image Credits: AI Generated

DOI: 10.1186/s44247-026-00297-2

Keywords: electronic health records, Nigeria, digital health, cloud computing, health informatics, low- and middle-income countries, health infrastructure, Pareto analysis, Technology Acceptance Model, interoperability, power supply reliability, health policy