ArticleBMC public health2024
Onsite training-mentoring intervention improves data quality: an implementation research.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Bridging policy and practice: a scoping review of health system implementation research practice in Ethiopia.Implementation science communications · 2026Review
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4 authors.
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Abstract
backgroundThe quality of health data is not satisfactory in Low and Middle Income Countries (LMICs). Haramaya University, in collaboration with Ministry of Health and Regional Health Bureau, conducted an implementation research in selected public health facilities and administrative units. This research was aimed to test the onsite training-mentoring (OTM) intervention and adaptation of the implementation strategy to improve the routine health information system (RHIS) data quality in the context of public health sector.
methodsAn interrupted time series design with an onsite training-mentoring intervention was used to improve data quality in public health sector of Jigjiga Woreda, eastern Ethiopia from July 2021 to June 2022. Both the pre and post intervention assessments data were collected by experienced and trained public health professionals using interviewer guided self-administered interview, record review and observation data collection techniques. Data were analyzed using descriptive, bivariate, and multivariate logistic models to identify predictors of data quality.
resultsThe overall data accuracy was increased from 88.12% before to 95.0% after intervention; and it was above 90% in all the facilities. The overall data content completeness was increased from 75.75% to 89.9%, though it varied among the facilities. The timeliness and report completeness were 100% in all the facilities. The odds of those health workers who had poor knowledge were less likely to ensure data quality (AOR = 0.39; 95%CI: 0.19, 0.83) than their counterparts.
conclusionsThe intervention was brought substantial changes of data quality in the study setting. Knowledge of the workers towards data quality is a crucial factor to ensure data quality in the sector. Thus, collective efforts is required to continue this tested intervention to ensure the quality of the routine health information system in the lower levels of the sector.
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