In the realm of global health, accurate and accessible data is crucial for effective decision-making. In the Democratic Republic of Congo (DRC), fragmented health facility data poses significant challenges to resource allocation and service delivery.
Data Fragmentation Impedes Efficient Health Resource Allocation
In DRC, health facility information was scattered across multiple sources. Additionally, inconsistent naming conventions across different datasets made it difficult to automatically match facilities. These challenges lead to inefficiencies and hinder the accurate mapping of health resources.
Comparing & Merging Geographic Data Sources
IASO, Bluesquare’s geospatial data management platform, offers robust solutions to these issues. IASO simplifies data integration, allowing for the easy import and storage of diverse data sources, including from DHIS2. This integration is crucial for comprehensive data management and synthesis. Furthermore, IASO employs a sophisticated text-matching algorithm, often referred to as the “love machine,” which links facilities with similar names across different datasets, ensuring consistency and accuracy.
To enhance the accuracy of health facility locations, IASO uses a GPS selection algorithm. This algorithm analyzes multiple coordinate points and identifies outliers, determining the most accurate locations for each facility. This method significantly improves the precision of health facility mapping.
Cleaned data could then be sent back to DHIS2 and get visualized through a public dashboard.
Keeping Health Facilities’ Data Updated
After the first geographic data analysis was performed, another challenge was raised: how to keep the health facility data up-to-date? Yearly data collection happens through the “Canevas Annuel” process, where field agents report any changes to the health facility core information: is it still open or has it closed since the last survey? Which key equipment is available and what is missing? etc. They can send the data through the IASO mobile application dedicated to this project. This routine data collection is also being considered for regular surveillance reporting.
Key Results
- health facilities with GPS data increased from 35% to 73%
- +1.800 community health sites added
- Identification of shortages in the community health sites
IASO’s advanced capabilities in data integration and synthesis are transforming health facility registries. By ensuring more accurate and comprehensive data, IASO empowers better decision-making in global health.
