Scalable Data Warehousing for Public Health Programmes in Resource-Limited Settings -A Framework for Low- and Middle-Income Countries

Background: Public health programmes in low- and middle-income countries face a fundamental paradox: they generate more health data than ever before, yet rarely translate that data into timely decisions. Fragmented information systems, unreliable connectivity, acute shortages of informatics capacity, and chronic under-investment in analytical infrastructure collectively ensure that most data collected at the point of care never surfaces for programme evaluation or resource planning.

Objective: This paper introduces a comprehensive, field-informed framework for designing and sustaining scalable data warehousing solutions within the real constraints facing LMIC public health programmes. We propose a six-layer reference architecture integrating hybrid- cloud/edge computing, data mesh governance, HL7 FHIR interoperability, and OMOP Common Data Model standardisation, grounded in evidence from four country-level implementations.

Methods: The framework was developed through systematic literature synthesis (2010–2022), structured expert consultations across 15 countries in sub-Saharan Africa, South Asia, and Southeast Asia, comparative technology evaluation, and in-depth case study analysis of implementations in Bangladesh, Tanzania, the East African Community, and Zambia, refined through iterative pilot testing at three district-level sites.

Results: Documented implementations demonstrate consistent improvements: data integration consolidating 5–20 previously siloed sources; missing-record rates reduced by 60– 85%; routine analytical query times falling to sub-second; and total data management costs reduced by 40–70%. The Tanzania district surveillance implementation was achieved for $85,000, demonstrating accessibility at district budget levels.

Conclusion: Scalable data warehousing is achievable in resource-limited settings today. The principal constraints are not technical but organisational: sustained governance commitment, local capacity investment, and institutional integration that convert a donor-funded project into a durable health system asset.