Digital Health (Nov 2024)
Assessment of data quality and associated factors in the routine health information system among health workers in public health institutions of Gofa Zone, Southern Ethiopia: A mixed methods study
Abstract
Background Generating high-quality data at health facilities is fundamental for effective decision making, which helps to strengthen health system performance and promote better health outcomes. Previous studies have revealed inconsistent findings and design-related drawbacks regarding the quality of routine health data. This study, therefore, aimed to assess the level of data quality and associated factors in the routine health information system among health workers in public health institutions of Gofa zone, Southern Ethiopia. Methods An institution-based quantitative cross-sectional study was mixed with a phenomenological qualitative study. Data collection was executed from April 1 to 30, 2023. Samples of 304 health workers were randomly selected. A total of six in-depth interviews and three focus group discussions were also done. Multilevel linear regression and thematic analysis were applied. Results The perceived level of good data quality was 59.5% (95% CI = 53.8, 65.1). The report timeliness, data accuracy, and the data completeness were 53.3%, 89.4%, and 93.5%, respectively. Factors that were significantly associated with data quality include culture of information utilization (β = 0.23, 95% CI = 0.20, 0.40), perceived skill of data management (β = 0.10, 95% CI = 0.03, 0.18), and electric power access (β = 0.11, 95% CI = 0.01, 0.21). The data quality was decreased in health posts by −0.20 (95% CI = −0.371, −0.030). Conclusion The overall quality of routine data among health workers was lower. Improving the skills of data management, cultivating a habit of data use, and enhancing the capacity of health workers are the potential interventions for ensuring data quality in health institutions.