Improve Data Quality Using the Introduction of DHIS2 Content Completeness App

This abstract has been accepted at the 2024 DHIS2 Annual Conference

Improve Data Quality Using the Introduction of DHIS2 Content Completeness App

Ethiopia has undertaken a monumental initiative by deploying the DHIS2 health information management tool over 30,000 health facilities. This strategic implementation has revolutionized the nation’s healthcare landscape, empowering stakeholders at every level with a powerful platform for comprehensive data collection, analysis, reporting, and visualization. Through DHIS2, Ethiopia has transcended traditional data management practices, ushering in an era of informed decision-making and program enhancement. From remote clinics to urban hospitals, healthcare providers now have access to a sophisticated toolset that not only aggregates disparate data sources but also transforms raw information into actionable insights. In their quest to streamline healthcare data management practices, the Ministry of Health (MoH) in Ethiopia undertook an extensive evaluation of data quality, identifying areas in need of improvement through DHIS2 interventions. During this assessment, one of the primary challenges identified at the facility level was the issue of content completeness. Despite DHIS2’s capacity to assess dataset completeness, it lacked the ability to offer detailed insights into the completeness of individual datasets. While the platform provided an overview of dataset completeness, it did not devolve into the specifics of whether all required data elements within each dataset were adequately filled. As a result, there was a gap in understanding the precise completeness levels of essential data elements, hindering efforts to ensure comprehensive and accurate healthcare data collection and reporting. In response, an innovative content completeness app was introduced. This tool goes beyond surface-level assessments, help check dataset completeness by scrutinizing the proportion of assigned data elements that are adequately filled. By contrasting content completeness with dataset completeness, healthcare practitioners gain a nuanced understanding of data entry practices. This novel approach not only sheds light on potential shortcomings but also offers actionable insights to enhance data accuracy and integrity. The introduction of the content completeness app in Ethiopia’s healthcare system represents a significant leap forward in data quality management, poised to transform the landscape of healthcare data analysis and decision-making. This innovation holds profound implications for capturing accurate data and optimizing services by ensuring the completeness of datasets, thereby enhancing data accuracy and improving understanding of healthcare services provided. These advancements support informed resource mobilization and underscore the critical importance of refining data collection processes to maximize the utility of DHIS2. Ultimately, improved data quality enables reliable insights, driving more effective healthcare interventions and leading to better health outcomes.

Primary Author: Redet Assefa

Data quality, Content completeness, Dataset completeness, Innovative app

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