From Clinical Silos to Population Surveillance: Architecting Interoperability Between Electronic Health Records and Public Health Data Systems in Resource-Constrained Environments

Background: In low-and middle-income countries (LMICs), Electronic Health Record (EHR) platforms operate predominantly as disconnected, facility-level transaction ledgers.Simultaneously, national public health surveillance systems-principally the District Health Information Software 2 (DHIS2)-rely on retrospective, aggregated, manual reporting.This structural decoupling produces reporting latencies spanning weeks, introduces transcription error margins exceeding 20%, and discards critical clinical covariates necessary for precision epidemiology.Objective: To systematically synthesize empirical evidence on technical architectures, semantic standards, and socio-technical governance models required to establish automated, bidirectional interoperability between point-of-care EHRs and national public health surveillance systems in resource-constrained settings.Methods: Following PRISMA 2020 guidelines, we searched PubMed/MEDLINE, Scopus, Web of Science, and Embase for peer-reviewed studies published between January 2016 and mid-2026.Eligible studies evaluated electronic health information exchanges, middleware data pipelines, semantic mediation, or automated case reporting linking clinical systems to population surveillance in resource-limited contexts.Quality appraisal was executed using the Mixed Methods Appraisal Tool (MMAT) and the Critical Appraisal Skills Programme (CASP) checklists.Results: Twenty-eight peer-reviewed publications met all inclusion criteria.The evidence identifies four systemic failure points: physical infrastructure fragility (electrical grid failures and network dropouts), semantic discordance between clinical narratives and structured reporting ontologies, clinical workforce documentation burnout, and legal/governance vacuums surrounding secondary health data custodianship.