1. Strengthen the functionality of the existing nutrition-relevant information system within the health system to cover both long and short-term information requirements. |
- Develop graphic and descriptive illustration of nutrition information within existing health systems. Reach agreement on data standards, purpose, flow, access, use etc. Define roles, responsibilities and accountabilities at national and subnational levels.
- Review and revise the existing data systems (HMIS, NIS, Surveillance) to ensure tools are fit-for-purpose and reduce data-related workload on health facility staff and community health workers.
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2. Address deficits in data quality and reliability. |
- Build confidence in available data through fully functioning data quality mechanisms and checks.
- Identify capacity gaps and design tailored support. Explore opportunities to utilise technology for data entry and transmission.
- Optimise integrity and use of all data to inform decision-making.
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3. Increase relevance of data to strengthen evidence-base for interventions and address data deficits. |
- Address coverage gaps and representation deficits for groups with higher vulnerabilities.
- Ensure availability of timely and disaggregated data on most vulnerable population groups to inform more efficient targeting of appropriate interventions and to monitor impact.
- Support national and critical small-area SMART surveys (which will require close engagement with the DfAs).
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4. Institutionalise multi-sectoral analysis of nutrition information to strengthen the evidence base of recommendations. |
- Support and facilitate periodic multi-sectoral analysis of nutrition.
- Formalise and document approaches used for extrapolation and triangulation of nutrition data in the absence of SMART surveys.
- Intensify existing engagement with initiatives such as IPC and REACH to identify pathways towards inclusion of nutrition data in existing multisectoral analysis and monitoring.
- Identify and include populations who are under-represented or excluded from data to add to the credibility of the analysis.
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5. Ensure coherence and credibility of analysis and recommendations by facilitating a process of consensus building on key messages. |
- Institute systems and mechanisms for reaching agreement or consensus on interpretation of information and communication of consistent evidence-based messages to inform decision-making.
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6. Leadership to guide, advocate for support and ensure intersectoral collaboration for implementation of recommendations. |
- Identify and support leadership to advocate for collaboration and promote access to adequate technical and financial support.
- Ensure all recommended focus areas are addressed, to strengthen evidence-based programming.
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