The IDEA review highlights what has worked and what has not worked to improve data use in other immunization programs, allowing implementers to make evidence-based decisions on how to allocate resources to improve data use.

Top findings for implementers


Interconnected Strategies Get Better Results

Immunization data use improves when programs use a comprehensive set of interconnected and mutually reinforcing strategies that address barriers. Successful packages include strategies that address skill and capacity building, behavior change management, user-centered design principles, and long-term resource commitments.


Data Use Leads to Better Data

The relationship between data quality and its use is dynamic and cyclical – one informs and inspires the other. The more data is used, the more its quality improves, and as data quality improves, health care workers are more confident about using it to guide their actions.


Systemizing Data Use Leads to Long-term Success

Data use becomes an integral part of decision-making when it’s built into processes at all levels of the health system. Interventions are more likely to be successful long term if they institutionalize data use through dedicated staff positions for data management, routine data review meetings, and training and guidelines for front-line staff.


HMIS and LMIS Increase Availability of Quality Data

Digital systems such as health management information systems (HMIS) and computerized logistics management information systems (LMIS) have made higher-quality data more available to decision makers in real time. And even greater gains are achieved when digital systems are paired with other activities that reinforce data use.


Digital Systems Show Promise but Barriers Still Exist

The transition from paper to digital systems across all levels of the health system has made higher-quality data more available to decision-makers, but has not automatically translated into greater data use. There is more success at the district level or higher because of fewer operational challenges than at the facility level. This finding shows the need for a phased approach—to make sure data use infrastructure, human resource capacity and skill building are in place before a full digital transition.


Checklist for implementers

The following checklist is designed to support implementers seeking to invest in improving data use for immunization. (Download this checklist.)

Cross-cutting actions:

  • The data use intervention’s design is based on an assessment of current data quality and use challenges and their root causes, including assessing the mechanisms, behavioral drivers, and contextual factors that may act as barriers or facilitators to specific data use actions.   

  • The intervention specifies the data use actions (from the TOC) it aims to support.

  • The data use actions are actionable by the intervention’s intended users and are of significance to the program itself.

  • The intervention has a clear theory for how it will work.

  • It is clear how the intervention will use multiple mechanisms and behavioral drivers to achieve its intended data use actions.

  • The intervention clearly targets specific bottlenecks known to constrain data use in the intervention setting.

  • The intervention aligns with national guidelines on processes and procedures for data collection, analysis, and use by health care workers.

  • All parties are clear which data use action the intervention will reinforce and strengthen.

  • During the design and conception phase of the intervention, an M&E strategy was developed to measure whether data are being used as intended and as defined by the data use actions it is intended to address.

At the health facility level:

  • The intervention establishes or strengthens feedback loops between data collectors (e.g. health care workers in a facility) and decision-makers at higher levels.

  • Implementers support harmonization across projects and alignment with local policies and guidelines on health care workers’ roles and responsibilities in relation to data analysis and use.

At the district level:

  • District level health workers have the needed tools and training to deliver effective supportive supervision, including ways to provide proper feedback to facility health workers and ways to support the intended data use actions.

  • District level staff have clarity on their roles and responsibilities in relation to data analysis and use.

At the national level:

  • Data use strategies focus efforts on increasing use of evidence in policy decision-making.

  • Data Improvement Plans (DIPs) include actionable recommendations.

  • DIPs are monitored to ensure facilities and districts take action on the recommendations.

Download the complete checklist and other resources here.