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Strengthening nutrition routine data using institutionalized health management information systems for decision
Ousmane Ouedraogo1, Mahamadi Tassembedo2, Assane Ouangare2
1UNICEF, Ouagadougou, Burkina Faso. ouedou2@yahoo.fr.
Abstract:
Strengthening nutrition routine information system is critical to support nutrition programs with relevant data to inform decision-making. This study analyzed the practices and lessons learned from the implementation in Burkina Faso in strengthening nutrition routine data using institutionalized health management information systems for decision making.Methods This qualitative study was conducted in Burkina Faso in 2022 on the capitalization of best practices after 3 years of implementation through documentary review, semi-structured individual interviews with 64 key implementing informants spread over 2 health districts, 2 regional hospital centers and 2 health regions, and a national triangulation workshop with 40 implementing actors, including 20 from the central level, 15 from the decentralized level, and 5 partners.Results The results of the study show the best practices and progress identified: (i) the integration of new routine data elements and nutrition indicators into District Health Information Software (DHIS2), which filled the data gap for adequate monitoring of the nutrition program; (ii) the design and use of the nutrition indicator dashboard; (iii) data validation and performance review sessions which have improved the quality and use of routine data in decision-making; and (iv) decentralization of data entry of monthly activity reports of health facilities. Lessons learned included: (i) conducting a small-scale phase to test the indicators is an important step to take before national scale-up of the indicators; (ii) a participatory approach involving all actors at different levels is important; (iii) advocacy is important to integrate prevention indicators into health facilities information systems in a more curative-oriented health system; (iv) the decentralized entry of data is a best practice that improves data quality in terms of timeliness, completeness, and internal consistency.Conclusion Beyond the inclusion of indicators, special emphasis should be placed on working on data quality. Future experiences in refining routine data related to nutrition-sensitive interventions in the non-health sectors are key next steps that would further contribute to strengthening the national nutrition information system.
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