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INTRODUCTION: As a result of poor quality administrative data for routine immunisation (RI) in Nigeria, the real coverage of RI remains unknown, constituting a setback in curtailing vaccine preventable diseases (VPDs). Consequently, the purpose of this pilot study is to identify source(s) and evaluate the magnitude of poor data quality as well as propose recommendations to address the problem. METHODS: The authors conducted a cross-sectional study in which 5 out of the 22 health facilities providing routine immunization services in Bunza Local Government Area (LGA), Kebbi State, Nigeria, were selected for data quality assessment. The reported coverage of RI in August and September, 2016 was the primary element of evaluation in the selected Health Facilities (HFs). Administered questionnaires were adapted from WHO Data Quality Assurance and RI monitoring tools to generate data from the HFs, as well as standardised community survey tool for household surveys. RESULTS: Data inconsistency was detected in 100% of the selected HFs. Maximum difference between HF monthly summary and RI registration book for penta 3 data quality report analysis was 820% and 767% in MCH Bunza and PHC Balu respectively. However, a minimum difference of 3% was observed at Loko Dispensary. Maximum difference between HF summary and RI registration for measles was 614% at MCH Bunza and 43% minimum difference at Loko. In contrast to the administrative coverage, 60-80% of the children sampled from households were either not immunised or partially immunised. Further, the main sources of poor data quality include heavy workload on RI providers, over-reliance on administrative coverage report, and lack of understanding of the significance of high data quality by RI providers. CONCLUSION: Substantial data discrepancies were observed in RI reports from all the Health Facilities which is indicative of poor data quality at the LGA level. Community surveys also revealed an over-reporting from administrative coverage data. Consequently, efforts should be geared towards achieving good data quality by immunisation stakeholders as it has implication on disease prevention and control efforts.
Omoleke et al. (Sun,) studied this question.