Improving routine health data in Indonesia: Utilising the WHO data quality tool for Aplikasi Satu Data Kesehatan

INTRODUCTION: Assessment of data quality in the era of big data is crucial for effective data management and use. However, there are gaps in data quality assessment for routine health data to ensure accountability. Therefore, this research aims to improve the routine health data quality that have been collected and integrated into Aplikasi Satu Data Kesehatan (ASDK) as the primary health data system in Indonesia.

MATERIALS AND METHODS: This descriptive study utilises a desk review approach and employs the WHO Data Quality Assurance (DQA) Tool to assess data quality of ASDK. The analysis involves measuring eight health indicators from ASDK and Survei Status Gizi Indonesia (SSGI) conducted in 2022. The assessment focuses on various dimensions of data quality, including completeness of variables, consistency over time, consistency between indicators, outliers and external consistency.

RESULTS: Current study shows that routine health data in Indonesia performs high-quality data in terms of completeness and internal consistency. The dimension of data completeness demonstrates high levels of variable completeness with most variables achieving 100% of the completeness.

CONCLUSION: Based on the analysis of eight routine health data variables using five dimensions of data quality namely completeness of variables, consistency over time, consistency between indicators, outliers. and external consistency. It shows that completeness and internal consistency of data in ASDK has demonstrated a high data quality.