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Leveraging ANACONDA for Data Quality Assessment in National Mortality Databases: The Serbian Case Study
Marija Anđelković Apostolović1,2, Aleksandra Ignjatović1,2, Miodrag Stojanović1,2
1Medical Faculty, University of Niš, Serbia, Medical statistics and informatics.
None:
Reliable mortality statistics are essential for evidence-based public health policy, Sustainable Development Goal (SDG) monitoring, and health system performance evaluation. The WHO-developed ANACONDA framework provides standardised algorithmic metrics to assess cause-of-death (CoD) data quality within Civil Registration and Vital Statistics (CRVS) systems. This study applied ANACONDA (v5.0) to Serbian mortality data (2005-2019), encompassing 1.54 million deaths coded using ICD-10. Key indicators included garbage codes (GC), high-impact GC (Levels 1-3), and the Vital Statistics Performance Index for Quality (VSPI(Q)). The VSPI(Q) improved from medium to high quality, while overall GC declined from 47.3% to 40.5%. The findings demonstrate how algorithmic quality auditing strengthens national mortality intelligence systems and supports data-driven health governance.
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