Table 1 Hierarchical structure of the health data ecosystem in Africa
From: Enabling data-driven decision-making for innovative health care and delivery in Africa
Level | Key function | Primary data needs | Data sources | Actors | Data tools | Data flow | Key challenge |
|---|---|---|---|---|---|---|---|
Community | Early detection, referral, health promotion, community engagement | Individual health status, immunization, births/deaths, disease symptoms | Household visits, outreach programs, immunization campaigns, maternal and child health tracking | Community Health Workers (CHWs), traditional birth attendants, local volunteers | Paper-based registers, mobile health (mHealth) apps, SMS reporting | Collected data is submitted to the nearest health facility or district office | Limited training in data collection and reporting Inconsistent use of digital tools (e.g., mobile apps) Lack of standardized data formats. |
Health facility | Case management, service delivery, facility performance monitoring | Clinical data, diagnostics, treatment outcomes, service utilization | Patient records, laboratory results, pharmacy logs, outpatient and inpatient registers | Nurses, doctors, data clerks, lab technicians | Electronic Medical Records (EMRs), District Health Information Software (DHIS2), paper-based systems | Aggregated and reported to district health offices | Fragmented data systems (paper-based vs. EMRs) Limited interoperability between systems Data quality issues |
District | Supervision, resource allocation, outbreak response coordination | Aggregated facility data, disease trends, resource needs | Facility-level reports, community-level summaries | District Health Management Teams (DHMTs), data managers | DHIS2, DHIMS2, Excel-based tools, dashboards | Data is cleaned, validated, and forwarded to provincial or national levels | Limited analytical capacity and tools Inconsistent reporting formats across districts |
Provincial / Regional | Strategic planning, inter-district coordination, regional reporting | Regional health indicators, program performance, epidemiological trends | District-level reports, sentinel surveillance sites | Regional health directors, epidemiologists, statisticians | Regional dashboards, GIS tools, statistical software | Data is analyzed for trends and forwarded to national health authorities | Insufficient integration of district-level data Weak infrastructure for regional data analysis Lack of harmonized indicators across regions |
National | Policy development, national planning, international reporting | National health statistics, surveillance data, health system performance | Aggregated provincial data, national surveys (DHS, MICS), disease surveillance systems | Ministry of Health (MoH), National Public Health Institutes, National Statistics Offices | National Health Information Systems (HIS), DHIS2, HMIS, national data warehouses | Used for national planning, policy-making, and reporting to international bodies | Centralized systems that may not reflect local realities Data silos across departments and programs Inadequate investment in national data infrastructure |
Global | Global health monitoring, funding allocation, technical support | Standardized indicators, comparative metrics, SDG/health targets | National reports, global health observatories, research collaborations | WHO, UNICEF, World Bank, Africa CDC, international donors | Global Health Observatory, SDG monitoring platforms, international databases | Supports global health monitoring, funding decisions, and comparative analysis | Data sovereignty concerns and trust issues |
