ArticleJournal of health, population, and nutrition2025
A comparative assessment of data completeness of the adverse events following immunization (AEFI) in DHIS2 at the early implementation stage in Bangladesh.
Article in Journal of health, population, and nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundData completeness is crucial in making evidence-based decisions in low- and middle-income countries (LMICs). A total of 130 countries have adopted the District Health Information System (DHIS2) platform in the health sector to generate good-quality data. In 2021, Bangladesh implemented DHIS2 as a platform for monitoring and surveillance of adverse events following immunization (AEFI). This study aimed to assess the level of completeness of AEFI data reported in DHIS2 during the early implementation phase through existing AEFI surveillance systems in Bangladesh.
methodsWe conducted a facility-based cross-sectional study. Based on a desk review of the 2023 AEFI data, we selected three divisions (Chattogram, Sylhet, and Rangpur) of Bangladesh based on high-, medium-, and low-performing groups according to the AEFI reporting rate. A total of 97 AEFI cases were found in the DHIS2 system for the assessment from six selected health facilities, which were reported between January and December 2023. The AEFI reporting form contains 50 variables to be completed by health assistants on paper-based forms (established method), and the DHIS2 tracker contains the identical variable set as a paper-based AEFI form. A comparative analysis was conducted between these two data sources, field by field, with the number count and percentages using McNemar's test.
resultsNinety-five paper-based AEFI reporting forms were found to be consistent with the DHIS2 AEFI tracker system (two hard copies were misplaced in two sites), and these matched AEFI cases were assessed for overall data completeness in the paper-based forms and the DHIS2 system. We found that 75.04% of the variable entries were available in paper-based forms, whereas 67.87% were available in the DHIS2 system (p < 0.001). The name of the patient, date of birth, AEFI (signs and symptoms), and date of AEFI onset were documented appropriately in the paper-based AEFI and the DHIS2 Tracker. Other variables were found to be either overreported or underreported in the DHIS2.
conclusionAt this early stage of the DHIS2 implementation, the data completeness of mandatory field entries was moderate. We recommend periodic supportive supervision by health management teams, including regular data feedback to improve completeness.
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