Maternal Health Data Reliability: Findings from Sidama Region, Ethiopia

Abstract High-quality routine health information is critical for monitoring maternal health indicators and guiding effective health interventions. However, data quality remains a persistent challenge in low-resource settings like Ethiopia. This study assessed reliability of maternal health service data and its determinants in public health facilities in Sidama Region, Ethiopia. Institution-based cross-sectional study was conducted from January 5 to 30, 2025 on 517 maternal health service units selected by a multistage sampling method. Data were collected through structured interviews and document reviews using tools adapted from the Performance of Routine Information System Management (PRISM) framework. Data quality was measured by accuracy, internal consistency, completeness, and timeliness. Overall, 63.1% of service delivery units demonstrated good data quality. Register content completeness (66.5%), report timeliness (65.0%), and report accuracy (59.2%) showed relatively high performance, while internal consistency (34.0%) and report content completeness (37.9%) remained low. Factors significantly associated with good data quality included the availability of standardized indicators (AOR = 2.30), user-friendly reporting formats (AOR = 2.94), trained staff (AOR = 2.33), and supervisory feedback (AOR = 2.49). Maternal health data quality in Sidama Region was below the national standards. Improving data quality requires strengthening technical capacity and investing in under-resourced health posts.