Data quality and associated factors of routine health information system among health centers of West Gojjam Zone, northwest Ethiopia, 2021.

Abstract

Data quality is a multidimensional term that includes accuracy, precision, completeness, timeliness, integrity, and confidentiality. The quality of data generated by a routine health information system (RHIS) is still very poor in low- and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, the aim of the present study was to assess the magnitude of the quality of routine health information system data and its determinants among health centers. A facility-based quantitative study design triangulated by the qualitative method was conducted. A total of 314 health professionals from 32 health centers were selected using a simple random sampling procedure. Data were gathered using a standardized checklist, interviewer-administered questionnaires, and key informant interview guidelines. Descriptive statistics were used to describe variables and binary logistic regression was used to identify factors associated with data quality using STATA version 14. Variables with p-value <0.25 in the bivariate analysis were entered to a multivariable logistic regression analysis. P-values <0.05 at 95% confidence intervals (CI) were taken to be statistically significant. A manual analysis was conducted for the qualitative data collected from purposively selected key informants. The study found that the overall data quality at the health centers of West Gojjam Zone was 74% (95% CI 68-78). The complexity of the routine health information system format [adjusted odds ratio (AOR) 3.8; 95% CI 1.7-8.5], problem-solving skills for RHIS tasks (AOR 2.8; 95% CI 1.2-6.4), and knowing duties, roles, and responsibilities were significantly associated with data quality (AOR 12; 95% CI 5.6-25.8), and lack of human resources, poor feedback mechanisms, delay in completing data records, lack of data use, and inadequate training on health information systems were barriers affecting data quality. The level of data quality among public health centers in the Amhara region was lower than expected at the national level.