This community innovation has been accepted at the 2025 DHIS2 Annual Conference
NHWA Data Quality App: Automating Data Validation
The collection and validation of high-quality health workforce data are essential to inform policy decisions and advance global health. To address challenges in ensuring data quality across WHO member states, EyeSeeTea developed the NHWA (National Health Workforce Accounts) Data Quality App, funded by the WHO Health Workforce Department. This open-source DHIS2 tool automates the detection and management of data quality issues, streamlining validation and enabling efficient collaboration between WHO and its member states. The app integrates with DHIS2 by creating a tracked entity instance for each data quality analysis. Using EyeSeeTea’s d2-logger open-source library, it performs automated data quality checks, generating events in DHIS2 when issues are detected. These events allow analysts to efficiently review, address, or dismiss flagged issues, document actions, and register follow-up activities, such as contacting country focal points for data corrections. Beyond issue resolution, the app serves as a powerful tracking system, providing insights into recurring challenges over time. These insights help WHO refine data collection processes, support data analysts in improving the data quality with systematic documentation and thereby facilitating data validation process, and support member states in achieving more accurate reporting. With its user-friendly interface and advanced functionality, the NHWA Data Quality App enhances the efficiency, transparency, and reliability of the data validation process. By automating quality checks and centralizing issue management, the app reduces manual workload and ensures a consistent approach to data quality, contributing to global efforts to strengthen health information systems.
Primary Author: Ramon Jiménez
Keywords:
Data quality, Health workforce, Data analysis, Automation, Web app, Custom app
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