Abstract
Background
Mass drug administration (MDA) is the main intervention strategy for the elimination of several neglected tropical diseases (NTDs). In many endemic settings, monitoring and collation of MDA treatment data are conducted through paper-based forms and Excel-based spreadsheets. These methods are often slow, prone to errors and do not facilitate timely evidence-based decision making during and after MDA campaigns. The Nigerian National NTD programme and Sightsavers, developed a DHIS2 based platform for real-time collection, monitoring, and reporting of MDA treatment data. We piloted and scaled this DHIS2-based platform, monitoring the data quality, access, government ownership and utility of data for programmatic action at all levels.
Methods
Three study areas (Jigawa, Enugu and Kwara States), with upcoming MDA campaigns were selected based on geographic spread and model of non-governmental development organisation (NGDO) implementing partner support. Following a pilot in Jigawa State, the DHIS2 platform was scaled-up across all three study areas, alongside the existing Excel-based systems. Programmatic data routinely collected via the two platforms were compared. Instances of data entry and access were monitored via the platform’s metadata and a monitored helpline. Data was collected from participants through a self-administered questionnaire, field diaries and focus group discussions/key informant interviews. Quantitative data was analysed using Stata analytical software, while qualitative data was thematically analysed.
Results
There was increased access and use of data at all levels within the DHIS2 system along with improved perceptions of government ownership of the data. Participants reported the ability to address errors and improve decision-making during campaigns as significant benefits of the platform. Scaling up DHIS2 was feasible, and similar benefits were observed in all the models of NGDO partner assistance.
Conclusion
The DHIS2 platform enhanced all components of ownership, as well as demonstrated ability to be replicated in different settings. However, operating models, cultural contexts, and technical capacities across the diverse locations need to be considered when scaling up the platform.