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Comparison of paediatric infectious disease deaths in public sector health facilities using different data sources in the Western Cape, South Africa (2007–2021)
BACKGROUND: Routinely collected population-wide health data are often used to understand mortality trends including child mortality, as these data are often available more readily or quickly and for lower geographic levels than population-wide mortality data. However, understanding the completeness...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945739/ https://www.ncbi.nlm.nih.gov/pubmed/36814192 http://dx.doi.org/10.1186/s12879-023-08012-6 |
Sumario: | BACKGROUND: Routinely collected population-wide health data are often used to understand mortality trends including child mortality, as these data are often available more readily or quickly and for lower geographic levels than population-wide mortality data. However, understanding the completeness and accuracy of routine health data sources is essential for their appropriate interpretation and use. This study aims to assess the accuracy of diagnostic coding for public sector in-facility childhood (age < 5 years) infectious disease deaths (lower respiratory tract infections [LRTI], diarrhoea, meningitis, and tuberculous meningitis [TBM]) in routine hospital information systems (RHIS) through comparison with causes of death identified in a child death audit system (Child Healthcare Problem Identification Programme [Child PIP]) and the vital registration system (Death Notification [DN] Surveillance) in the Western Cape, South Africa and to calculate admission mortality rates (number of deaths in admitted patients per 1000 live births) using the best available data from all sources. METHODS: The three data sources: RHIS, Child PIP, and DN Surveillance are integrated and linked by the Western Cape Provincial Health Data Centre using a unique patient identifier. We calculated the deduplicated total number of infectious disease deaths and estimated admission mortality rates using all three data sources. We determined the completeness of Child PIP and DN Surveillance in identifying deaths recorded in RHIS and the level of agreement for causes of death between data sources. RESULTS: Completeness of recorded in-facility infectious disease deaths in Child PIP (23/05/2007–08/02/2021) and DN Surveillance (2010–2013) was 70% and 69% respectively. The greatest agreement in infectious causes of death were for diarrhoea and LRTI: 92% and 84% respectively between RHIS and Child PIP, and 98% and 83% respectively between RHIS and DN Surveillance. In-facility infectious disease admission mortality rates decreased significantly for the province: 1.60 (95% CI: 1.37–1.85) to 0.73 (95% CI: 0.56–0.93) deaths per 1000 live births from 2007 to 2020. CONCLUSION: RHIS had accurate causes of death amongst children dying from infectious diseases, particularly for diarrhoea and LRTI, with declining in-facility admission mortality rates over time. We recommend integrating data sources to ensure the most accurate assessment of child deaths. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08012-6. |
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