THE LEVEL OF ROUTINE HEALTH INFORMATION SYSTEM DATA QUALITY AND ASSOCIATED FACTORS AT PUBLIC HOSPITAL IN SILTE ZONE, CENTRAL REGION, ETHIOPIA, 2023

Abstract

Background: Routinely collected data of poor quality can compromise the validity of effect evaluations and lead to poor decision-making, inappropriate resource allocation, and a loss of trust in the health system. Routine health information system data are seen as poor in quality and are not used for decisions in Ethiopia, and continues to be a significant problem. Objectives: To assess the level and associated factors of routine health information system data quality; and explore the factors affecting data quality at public hospitals in Silte Zone, Central Region Ethiopia, 2023 Methods and materials: Facility based mixed method with an embedded study design was conducted. A total of four public hospitals, 32 units or departments, 605 health care workers, and 12 key informant interviews were selected. Simple random sampling and purposive sampling techniques were used for selecting study participants in quantitative and qualitative study. The data was entered into Epi-data version 4.4, open code 4.03 and exported to SPSS version 26, and descriptive statistics were used to assess the level of data quality, and Binary logistic regression and thematic analysis was run to identify factors affecting data quality. Adjusted odds ratios with 95% confidence intervals and themes or subthemes were reported. Result: The overall study conducted facility data quality level was 90.84%; completeness and consistence of data in this study were 85.5% and 85.3% respectively. Easily understandability of registration and report format [AOR 1.92; CI 1.11-3.33], receive training [AOR 1.62; CI 1.07- 2.44], getting supervision [AOR 1.66 CI 1.05-2.61], provide regular feedback [AOR 1.72 CI 1.07- 2.75], team’s work appreciated and valued by supervisors [AOR 1.61; CI 1.04-2.75] and decisions and follow up actions identified in Performance monitoring team meetings [AOR 1.73; CI 1.12- 2.67] were significantly associated with data quality ; and thematic analysis was done and categorized into four themes and twelve sub-themes. Conclusion and recommendation: The level of data quality at the public hospital in Silte Zone is almost equal to the national expected level of data quality, but completeness &consistency of the data were lower than the national expected level. For MOH and other supporting organization to fully transforming the paper based service registration to an electronic-based medical recording system in which it will reduce incompleteness and inconsistency of data and to increase data quality