Empowering Public Health: A Closer Look at EQA Training in Somali State

A report on the successful EQA Data Base Training in Jijiga, Ethiopia. Lab professionals enhanced skills in data management for malaria and TB.

Empowering Public Health

A four-day External Quality Assessment (EQA) Data Base Training was successfully conducted at the Jijiga Istanbul Hotel from September 6-9, 2025. This training was a collaborative initiative between the Ethiopian Public Health Institute (EPHI) and the Somali Regional Public Health Laboratory and Research Directorate. It aimed to improve data management skills for lab professionals.

The training was attended by 18 lab professionals from six key EQA centers and the Regional Public Health Laboratory. The main goal was to enhance their proficiency in using the ET-EQAS web application for data management, analysis, and reporting.

A Comprehensive Agenda for Lasting Impact

The comprehensive curriculum covered the ET-EQAS system's foundational use. The training was split into four days, with each day focusing on different modules and skills.

Day 1 focused on system fundamentals, including account activation, user management, and an overview of the main Dashboard.
Day 2 was dedicated to the Malaria RBR module, covering dashboard navigation, key performance indicators, and report generation.
Day 3 extended the training to the TB RBR and Onsite Evaluation modules, with a focus on analyzing unique metrics and tracking facility performance.
Day 4 was a hands-on session where participants engaged in practical exercises and discussed the six pillars of data quality (accuracy, completeness, timeliness, consistency, uniqueness, and relevance).

Commitment to Data Quality and Future Recommendations

The training successfully equipped participants with the skills to ensure data accuracy and integrity, which is vital for the credibility and effectiveness of the EQA program. Maintaining high data quality is essential for the integrity of any EQA program.

The training emphasized three key best practices for ensuring data integrity:

Data Governance: Establishing a clear framework with defined roles and protocols for data collection and entry.
Validation and Audits: Implementing automated data validation rules and regular audits to prevent incorrect entries and correct inconsistencies.
Continuous Monitoring: Designing systems with features for ongoing data monitoring and having a robust feedback mechanism to communicate issues.

The training was a success, equipping lab professionals with the necessary skills to effectively use the ET-EQAS system. To further strengthen data quality, the report recommends implementing a regular schedule for data quality audits, establishing a peer-review process, and conducting annual refresher training sessions.