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  • Medknow  (1)
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    In: Nigerian Journal of Clinical Practice, Medknow, Vol. 26, No. Suppl 1 ( 2023), p. S12-S18
    Abstract: Immunization data are critical for the effective delivery of immunization programs, health planning, and-decision-making. It can also help to identify gaps in vaccine coverage and service delivery. Immunization data quality is dependent on the quality of the collection process at individual health facilities and its transmission to an integrated system. Aim: This study set out to appraise the quality of childhood routine immunization data across the different levels of transmission in selected health facilities in Enugu, Nigeria. Materials and Methods: This was a cross-sectional, analytical study of the immunization data of two vaccine antigens in 103 health facilities across 10 local council areas offering routine immunization services in Enugu state. Accuracy, discrepancy consistency, completeness, and timeliness of the data for the year 2020, the study period, were determined using WHO data quality assessment tools. Results: This study noted that childhood routine immunization data from health facilities to the state are inconsistent, incomplete, and untimely in the transmission. Accuracy ratios were 110 and 108, discrepancy -10 and -8 for BCG and Penta III, respectively, at the health facility level. These signify the underreporting of the two vaccine antigens. This pattern was observed to be reversed as the data were transmitted from the local councils to DHIS 2. Timeliness of reporting did not go beyond 65% for the entire year 2020, while the completeness of reporting was below 80% for the same period. Conclusion: There were significant changes in childhood routine immunization data as it were transmitted across the different levels of the data management processes in the state. Routine immunization data from health facilities in the state are inconsistent, incomplete, and untimely in their transmission. This calls for interventions to improve data quality and make use of it in decision-making.
    Type of Medium: Online Resource
    ISSN: 1119-3077 , 2229-7731
    Language: English
    Publisher: Medknow
    Publication Date: 2023
    detail.hit.zdb_id: 2538681-5
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