Background
The quality of healthcare relies on evidence-based decisions backed by high-quality routine health information (RHI). Evaluating RHI quality and factors associated with it is crucial for advancing healthcare information systems and improving overall healthcare quality. This study assesses RHI quality and its influencing factors in health facilities, specifically in primary healthcare facilities in Eastern Tigray, Ethiopia.
Methods
A comparative cross-sectional study was conducted in selected health facilities in Eastern Tigray, supported by the Mekelle University Capacity Building and Monitoring program. Simple random sampling was used to select the woredas, with 224 departments assessed. Data was collected through questionnaires, observation checklists, and registry review. Descriptive statistics and ordinal logistic regression were used to analyze the routine health information quality and associated factors. The significance level was set at p-value < 0.05 with a 95% confidence interval.
Result
Only 13.39% of health facility departments meet the acceptable limit for routine health information quality (85% completeness, timeliness on 23–25 of the month, and accuracy of 90–110% verification factor). Being supported by the project is significantly associated with quality (Pearson X2 = 14.703, P = 0.001). Factors such as training on health information systems (2.173, 95% CI: 1.018, 4.638), display of targets (2.853, 95% CI: 1.10, 7.752), feedback (2.836, 95% CI: 1.267, 6.345), and perception of the importance of routine health information (5.330, 95% CI: 1.403, 20.254) are associated with quality in facilities not supported by the Capacity Building program. Supervision is a factor associated with quality in facilities supported by the program (adjusted proportional odds ratio and 95% confidence interval: 3.806, 1.66-12.427).
Conclusion
The data quality was below national expectations. Health centers had lower RHI quality compared to hospitals. Support from projects and training, supervision, and feedback improved data quality. Scaling up training, monitoring, and written feedback at various health system levels is recommended.