Tracking India’s progress on addressing malnutrition: What will it take?

Recommendations

1. Data prioritization

A set of core indicators across the lifecycle should be prioritized and reviewed at all levels (national, state, district, and block).

To track progress towards POSHAN Abhiyaan goals and targets, a set of core indicators across the lifecycle should be prioritized for monitoring the progress, diagnosis, and action in both population-based surveys and administrative data systems. These core indicators should be reviewed at national, state and district levels across existing review mechanisms. The data review highlights that several possible indicators are available for each intervention and from multiple data sources. Therefore, it is important to identify core data sources based on the potential data use scenarios (e.g., use of population-based survey data sources for evaluation of coverage or reach; or use of administrative data sources for program reviews and refinement).

2. Promote data use

Develop guidance on different types of data sources and their use to promote awareness. Strengthen capacities of officials to effectively use data to improve planning and decision making.

There is a need to create a strong culture of data use among officials at all levels in the nutrition space. To promote awareness around available data sources and their use, we need to ensure that all data users are aware of the design elements, challenges, and opportunities of each type of data source. We recognize the need to develop and provide guidance on the different types of data sources, what data are needed and how to effectively use data for progress tracking, strategy development, and program refinement. At the same time, it will be useful to support and incentivize district and sub-district level officials to integrate, analyze and use nutrition data from multiple sectors and systems to improve planning and decision making. As part of this process, it will be important to strengthen the capacities of staff to perform these activities across the data value chain.

3. Tracking progress on inputs and intervention coverage

Multiple data sources for coverage indicators require careful reconciliation of findings from survey data and administrative data systems. Ensure interoperability of nutrition data across data systems to support better-informed decision making. Develop data use cases for survey and administrative data on intervention coverage. 

• Identify a narrow set of input and coverage indicators that should be tracked at all levels to strengthen program actions.
• Prioritize and decide on specific indicators/information and data sources for each of the major POSHAN Abhiyaan inputs.
• Specific indicators/information for each of the major POSHAN Abhiyaan input indicators should come from administrative data systems.
• Build out and test data use cases to help prioritize and sequence the use of data from multiple sources for strengthening programs.

4. Monitoring progress on determinants

Use population-based survey data when available and continue to strengthen data on nutrition behaviors from administrative systems.

On the use of data from diverse sources:

• Include survey data primarily for diagnostic exercises to decide which immediate and underlying determinants, including behaviors, are the major challenge areas for the region.
• Ensure that issues related to underlying determinants are included at review meetings and amplified during public campaigns.
• Include implementers/sectors addressing underlying determinants in POSHAN Abhiyaan monitoring and strategic meetings at all levels (national, state, district).

5. Monitoring progress on outcomes

Use population-based survey data for progress tracking. Strengthen data on nutrition outcomes from administrative systems for program use.

• Ensure that population-based household surveys cover all nutrition target indicators, including indicators on emerging nutrition challenges that should be tracked even if they are not currently a key focus of POSHAN Abhiyaan, such as Non-Communicable Diseases (NCDs).
• Review the quality of measurement processes that generate administrative data on impact indicators.
• Support efforts to improve the quality of data available on outcomes in administrative data systems.
• Identify data use scenarios by building on a good understanding of the current data use culture at different levels.

6. Data stewardship

A single data stewardship entity is essential to ensure coordinated monitoring of progress, strategy refinement and to support data use for program refinement.

A single data stewardship entity must provide guidance to all major committees and review platforms. We recommend a strong role for a data stewardship body, such as NITI Aayog, and related state-level entities. Review mechanisms at each level should include clear guidance on the use of data at all reviews.