In Côte d’Ivoire, planning antiretroviral stocks depended on knowing how many people were on treatment at each facility, at any given time. That number used to come from Excel files: one per site, updated at different times, in different formats, impossible to consolidate into a single, reliable national count. This gap in the data behind HIV logistics planning is what led to a national system for managing cohort data on people living with HIV, built on OpenHEXA as part of the Local Health Supplies Procurement and Logistics Activity project, supported by USAID through NPSP (Nouvelle Pharmacie de la Santé Publique), in partnership with the Ministry of Health of Côte d’Ivoire.
The “file active” is the full list of people currently on HIV treatment. Planning how many antiretrovirals a facility, district, or the country needs starts with this number. Before this system existed, it was never fully reliable.
Each facility tracked the people it cared for in its own Excel file. Without a shared system to bring these files together, no one, at district or national level, had a real-time, consolidated view of who was on treatment, where, and since when, which is the exact information antiretroviral supply planning depends on.
Fragmentation also raised a reliability problem: figures compiled by hand from dozens of separate files are harder to check and to trust. When the count of people on treatment is uncertain, so is the resupply order built on top of it, whether that means ordering too much or not enough antiretroviral stock.
Closing this gap meant building a system able to turn scattered individual-level records into a number logistics teams could plan around.
A national system, built on OpenHEXA, centralizes in a secure way the longitudinal, individual-level data of each person under HIV treatment, recorded at the health facility where they receive care.
Instead of a spreadsheet per facility, health workers now feed individual-level data into a single national system. Each record follows the person over time, giving national and subnational teams a live, unified view of the active cohort instead of a patchwork of static files.
Knowing the exact, current number of active people on treatment at each facility feeds directly into antiretroviral stock planning, reducing the risk of both stockouts and overstocking. A complementary data triangulation tool, developed in parallel, cross-checks service-delivery data from DHIS2 against logistics data from eSIGL, helping teams catch discrepancies between care delivery and stock movements before they turn into shortages. This is where this national HIV data system meets Bluesquare’s other logistics work in Côte d’Ivoire: the order fulfillment satisfaction tool tracks antiretroviral orders and deliveries once the resupply request has been placed, while this data system supplies the numbers that request should be based on.
OpenHEXA is the data integration and orchestration layer behind this system. Three technical functions make this possible.
OpenHEXA extracts, cleans, and structures complex data flows, including clinical active-file records, facility-level Excel exports, and national logistics databases, and transforms them into a single, unified data warehouse feeding both individual monitoring and antiretroviral planning.
Individual records for people living with HIV require strict confidentiality. OpenHEXA provides a secure cloud environment with highly structured, differentiated access rights, so each user, whether reviewing clinical data or logistics figures, sees only what is relevant to their role.
OpenHEXA operates in synergy with IASO, Bluesquare’s geo-registry tool used to collect, locate, and validate the structure of health facilities across the country. It also feeds analytics tools such as Power BI and Apache Superset, which decision-makers use to visualize both individual-level and antiretroviral supply data through interactive dashboards.
Since this system went live, the completeness and timeliness of HIV data reaching the national level have measurably improved. National and subnational decision-makers now plan antiretroviral needs on structured, secure, individual-level data, rather than waiting for facilities to compile and send spreadsheets by hand.
Demand and supply, people on treatment counts and stock movements, now draw on the same underlying data infrastructure. That is what makes it possible to plan antiretroviral logistics around how many people actually need treatment, not an estimate.
