Abstract
The National Health Information System (NHIS) plays a crucial role in collecting, analyzing, and disseminating data required for public health decision-making. However, data quality may be compromised by human, organizational, and technical factors. This retrospective cross-sectional study, conducted in four health zones, aimed to identify factors associated with poor data quality within the Provincial Health Division (DPS) of Kasaï Central, Democratic Republic of the Congo, and to propose operational improvement strategies. Data were collected from monthly activity reports, data collection tools related to selected indicators, and interviews with personnel involved in data management. The data quality assessment showed that the completeness of reports submitted from the central offices of the health zones (BCZs) to the DPS was 100%, while timeliness was 50% and data exhaustiveness was 91.7%. From health facilities to the BCZs, completeness was 85.4%, timeliness was 85.3%, and exhaustiveness was 90.2%; however, data accuracy was 0%. NHIS performance was estimated at 40.3% in the BCZs and 28.2% in health facilities. Knowledge of national reporting guidelines remained limited, at 38.8% in the BCZs and 26.7% in health facilities. The statistical results showed associations between deficient data quality and sociodemographic variables, including age group (χ² = 5.3667; p = 0.047) and occupation (χ² = 5.9643; p = 0.051), as well as organizational and operational factors, such as timely report submission (χ² = 9.5788; p = 0.023), formal designation of the NHIS focal person (χ² = 4.4357; p = 0.035), use of computer-based tools (χ² = 4.4599; p = 0.035), availability of standardized data collection tools (χ² = 17.5154; p = 0.000), availability of indicator dashboards (χ² = 6.9319; p = 0.008), NHIS coaching (χ² = 5.8928; p = 0.015), and conduct of monitoring activities (χ² = 10.7333; p = 0.001). In conclusion, improving NHIS data quality requires strengthening staff capacity, ensuring the effective use of standardized tools, implementing regular monitoring, and improving access to health data. Familiarity with national guidelines and improved data management practices are essential levers for enhancing the reliability of health information and supporting evidence-based decision-making.
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