Data quality of routine health information systems and associated factors among public health facilities in Banadir region, Somalia: A cross-sectional

Abstract

Data quality encompasses completeness, accuracy, integrity, timeliness, and confidentiality. In many low- and middle-income countries, including Somalia, data from RHIS are often poor, limiting their usefulness for public health actions. This study assessed the quality of RHIS data and associated factors among public health facilities in the Banadir region, Somalia. A facility-based cross-sectional study was conducted from October to December 2024 across 36 public health facilities using a multistage sampling approach. Data were collected through document reviews, interviews, and observations using PRISM-based standardized tools. Data were analyzed in SPSS version 27 after checking logistic regression assumptions. Data quality was assessed by the dimensions of accuracy (≥80%), completeness (≥85%), and timeliness (≥85%). Bivariable and multivariable logistic regression analyses identified associated factors. A total of 398 healthcare workers (59.5% female) participated, yielding a 98% response rate. Overall, good-quality data were observed in 65.3% of departments. Departments in health centers were 2.7 times more likely to report good-quality data than hospitals. Feedback, refresher training, and user-friendly reporting formats were significantly associated with better data quality. Data quality across the three dimensions was scored at (65.3%). Strengthening supervision, feedback, and context-specific training can improve data reporting and management.