Using a hepatitis B surveillance system evaluation in Fujian, Hainan, and Gansu provinces to improve data quality and assess program effectiveness, China, 2015

利用福建、海南和甘肃三省的乙型肝炎监测系统评估来提高数据质量并评估项目成效,中国,2015年

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Abstract

BACKGROUND: Monitoring hepatitis B surveillance data is important for evaluating progress towards global hepatitis B elimination goals. Accurate classification of acute and chronic hepatitis infections is essential for assessing program effectiveness. METHODS: We evaluated hepatitis B case-reporting at six hospitals in Fujian, Hainan and Gansu provinces in 2015 to assess the accuracy of case classification. We linked National Notifiable Disease Reporting System (NNDRS) HBV case-reports with hospital information systems and extracted information on age, gender, admission ward and viral hepatitis diagnosis from medical records. To assess accuracy, we compared NNDRS reported case-classifications with the national HBV case definitions. Multivariable logistic regression was used to identify factors associated with misclassification. RESULTS: Of the 1420 HBV cases reported to NNDRS, 23 (6.5%) of the 352 acute reports and 648 (60.7%) of the 1068 chronic reports were correctly classified. Of the remaining, 318 (22.4%) were misclassified and 431 (30.4%) could not be classified due to the lack of supporting information. Based on the multivariable analysis, HBV cases reported from Hainan (aOR = 1.8; 95% CI: 1.3-2.4) and Gansu (aOR = 12.7; 95% CI: 7.7-20.1) along with reports from grade 2 hospitals (aOR = 1.6; 95% CI:1.2-2.2) and those from non-HBV related departments (aOR = 5.3; 95% CI: 4.1-7.0) were independently associated with being 'misclassified' in NNDRS. CONCLUSIONS: We identified discrepancies in the accuracy of HBV case-reporting in the project hospitals. Onsite training on the use of anti-HBc IgM testing as well as on HBV case definitions and reporting procedures are needed to accurately assess program effectiveness and ensure case-patients are referred to appropriate treatment and care. Routine surveillance evaluations such as this can be useful for improving data quality and monitoring program effectiveness.

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