Literature DB >> 25795017

Assessment of timeliness, representativeness and quality of data reported to Italy's national integrated surveillance system for acute viral hepatitis (SEIEVA).

M E Tosti1, S Longhi2, C de Waure2, A Mele1, E Franco3, W Ricciardi2, A Filia4.   

Abstract

OBJECTIVES: Periodic assessment of surveillance systems is recommended to verify whether they are appropriately monitoring the public health problem under surveillance. The aim of this study was to evaluate timeliness, data quality and representativeness of data reported to the Italian Integrated Epidemiological System for Acute Viral Hepatitis (SEIEVA). STUDY
DESIGN: Cross-sectional analysis of surveillance data.
METHODS: Quantitative indicators were used to evaluate representativeness of reported cases, data quality, and timeliness between surveillance steps, for reports of acute viral hepatitis cases with date of onset of symptoms from 2009 to 2012 (N = 4516).
RESULTS: Representativeness was 75%. Over 95% of records reported information on age, sex, city of residence, risk factors for hepatitis A and vaccination status. Information on risk factors for hepatitis B and C were reported less consistently (83%), as was information on early outcome (60%). Wide delays were found between surveillance steps.
CONCLUSIONS: The system collects high quality data on acute viral hepatitis cases in Italy. Timeliness was found to be the main limit and needs to be improved by optimizing web-based reporting procedures, increasing communication with participating centres, improving feedback and increasing dissemination of surveillance results. The study highlights the importance of reporting timeliness to detect outbreaks of acute viral hepatitis.
Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Acute viral hepatitis; Evaluation; Hepatitis A; Hepatitis B; Hepatitis C; Quality; Representativeness; Surveillance; Timeliness

Mesh:

Year:  2015        PMID: 25795017     DOI: 10.1016/j.puhe.2015.02.015

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


  7 in total

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7.  COVID-19 surveillance data quality issues: a national consecutive case series.

Authors:  Ana Margarida Pereira; Joao A Fonseca; Cristina Costa-Santos; Ana Luisa Neves; Ricardo Correia; Paulo Santos; Matilde Monteiro-Soares; Alberto Freitas; Ines Ribeiro-Vaz; Teresa S Henriques; Pedro Pereira Rodrigues; Altamiro Costa-Pereira
Journal:  BMJ Open       Date:  2021-12-06       Impact factor: 2.692

  7 in total

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