Early Lessons From Ethiopia in Establishing a Data Triangulation Process to Analyze Immunization Program and Supply...

Area of Science:

• Public Health
• Health Informatics
• Data Management

Background:

• Equitable immunization coverage relies on robust data use and quality.
• Ethiopia's immunization program faces challenges with data timeliness, completeness, and accuracy due to fragmented reporting systems.
• Data triangulation is recognized as a strategy to enhance data quality and inform public health decisions.

Purpose of the Study:

• To assess the feasibility and impact of the Immunization Data Triangulation Tool (IDTT) in improving immunization program data quality and decision-making in Ethiopia.
• To evaluate the usability and benefits of a data review process combined with the IDTT for health managers.

Main Methods:

• Introduction of a data review process and an Excel-based tool (IDTT) for triangulating immunization program and vaccine supply data.
• Rollout of the IDTT in two Ethiopian regions.
• Qualitative assessment through key informant interviews and observation of IDTT use in monthly data review meetings.

Main Results:

• Health managers reported the IDTT as user-friendly, providing synthesized data that facilitated decision-making and prompted actions like expanding immunization sites.
• The tool effectively highlighted discrepancies between vaccine supply and consumption, guiding programmatic adjustments.
• Challenges in vaccine supply data availability were noted, yet the triangulation process encouraged cross-departmental collaboration to address these gaps.

Conclusions:

• The data review process and IDTT show promise in strengthening immunization programs by improving data quality and enabling data-driven decisions.
• The findings offer valuable lessons for integrating similar data triangulation tools and processes into health systems.
• Cross-departmental collaboration emerged as a key benefit, crucial for overcoming data-related challenges in public health programs.