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Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality

Linking routinely collected healthcare administrative data is a valuable method for conducting research on morbidity outcomes, but linkage quality and accuracy needs to be assessed for bias as the data were not collected for research. The aim of this study was to describe the rates of linking data o...

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Autores principales: Loane, Maria, Given, Joanne E., Tan, Joachim, Barišić, Ingeborg, Barrachina-Bonet, Laia, Cavero-Carbonell, Clara, Coi, Alessio, Densem, James, Garne, Ester, Gissler, Mika, Heino, Anna, Jordan, Sue, Lutke, Renee, Neville, Amanda J., Odak, Ljubica, Puccini, Aurora, Santoro, Michele, Scanlon, Ieuan, Urhoj, Stine K., de Walle, Hermien E. K., Wellesley, Diana, Morris, Joan K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468043/
https://www.ncbi.nlm.nih.gov/pubmed/37647348
http://dx.doi.org/10.1371/journal.pone.0290711
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author Loane, Maria
Given, Joanne E.
Tan, Joachim
Barišić, Ingeborg
Barrachina-Bonet, Laia
Cavero-Carbonell, Clara
Coi, Alessio
Densem, James
Garne, Ester
Gissler, Mika
Heino, Anna
Jordan, Sue
Lutke, Renee
Neville, Amanda J.
Odak, Ljubica
Puccini, Aurora
Santoro, Michele
Scanlon, Ieuan
Urhoj, Stine K.
de Walle, Hermien E. K.
Wellesley, Diana
Morris, Joan K.
author_facet Loane, Maria
Given, Joanne E.
Tan, Joachim
Barišić, Ingeborg
Barrachina-Bonet, Laia
Cavero-Carbonell, Clara
Coi, Alessio
Densem, James
Garne, Ester
Gissler, Mika
Heino, Anna
Jordan, Sue
Lutke, Renee
Neville, Amanda J.
Odak, Ljubica
Puccini, Aurora
Santoro, Michele
Scanlon, Ieuan
Urhoj, Stine K.
de Walle, Hermien E. K.
Wellesley, Diana
Morris, Joan K.
author_sort Loane, Maria
collection PubMed
description Linking routinely collected healthcare administrative data is a valuable method for conducting research on morbidity outcomes, but linkage quality and accuracy needs to be assessed for bias as the data were not collected for research. The aim of this study was to describe the rates of linking data on children with and without congenital anomalies to regional or national hospital discharge databases and to evaluate the quality of the matched data. Eleven population-based EUROCAT registries participated in a EUROlinkCAT study linking data on children with a congenital anomaly and children without congenital anomalies (reference children) born between 1995 and 2014 to administrative databases including hospital discharge records. Odds ratios (OR), adjusted by region, were estimated to assess the association of maternal and child characteristics on the likelihood of being matched. Data on 102,654 children with congenital anomalies were extracted from 11 EUROCAT registries and 2,199,379 reference children from birth registers in seven regions. Overall, 97% of children with congenital anomalies and 95% of reference children were successfully matched to administrative databases. Information on maternal age, multiple birth status, sex, gestational age and birthweight were >95% complete in the linked datasets for most regions. Compared with children born at term, those born at ≤27 weeks and 28–31 weeks were less likely to be matched (adjusted OR 0.23, 95% CI 0.21–0.25 and adjusted OR 0.75, 95% CI 0.70–0.81 respectively). For children born 32–36 weeks, those with congenital anomalies were less likely to be matched (adjusted OR 0.78, 95% CI 0.71–0.85) while reference children were more likely to be matched (adjusted OR 1.28, 95% CI 1.24–1.32). Children born to teenage mothers and mothers ≥35 years were less likely to be matched compared with mothers aged 20–34 years (adjusted ORs 0.92, 95% CI 0.88–0.96; and 0.87, 95% CI 0.86–0.89 respectively). The accuracy of linkage and the quality of the matched data suggest that these data are suitable for researching morbidity outcomes in most regions/countries. However, children born preterm and those born to mothers aged <20 and ≥35 years are less likely to be matched. While linkage to administrative databases enables identification of a reference group and long-term outcomes to be investigated, efforts are needed to improve linkages to population groups that are less likely to be linked.
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spelling pubmed-104680432023-08-31 Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality Loane, Maria Given, Joanne E. Tan, Joachim Barišić, Ingeborg Barrachina-Bonet, Laia Cavero-Carbonell, Clara Coi, Alessio Densem, James Garne, Ester Gissler, Mika Heino, Anna Jordan, Sue Lutke, Renee Neville, Amanda J. Odak, Ljubica Puccini, Aurora Santoro, Michele Scanlon, Ieuan Urhoj, Stine K. de Walle, Hermien E. K. Wellesley, Diana Morris, Joan K. PLoS One Research Article Linking routinely collected healthcare administrative data is a valuable method for conducting research on morbidity outcomes, but linkage quality and accuracy needs to be assessed for bias as the data were not collected for research. The aim of this study was to describe the rates of linking data on children with and without congenital anomalies to regional or national hospital discharge databases and to evaluate the quality of the matched data. Eleven population-based EUROCAT registries participated in a EUROlinkCAT study linking data on children with a congenital anomaly and children without congenital anomalies (reference children) born between 1995 and 2014 to administrative databases including hospital discharge records. Odds ratios (OR), adjusted by region, were estimated to assess the association of maternal and child characteristics on the likelihood of being matched. Data on 102,654 children with congenital anomalies were extracted from 11 EUROCAT registries and 2,199,379 reference children from birth registers in seven regions. Overall, 97% of children with congenital anomalies and 95% of reference children were successfully matched to administrative databases. Information on maternal age, multiple birth status, sex, gestational age and birthweight were >95% complete in the linked datasets for most regions. Compared with children born at term, those born at ≤27 weeks and 28–31 weeks were less likely to be matched (adjusted OR 0.23, 95% CI 0.21–0.25 and adjusted OR 0.75, 95% CI 0.70–0.81 respectively). For children born 32–36 weeks, those with congenital anomalies were less likely to be matched (adjusted OR 0.78, 95% CI 0.71–0.85) while reference children were more likely to be matched (adjusted OR 1.28, 95% CI 1.24–1.32). Children born to teenage mothers and mothers ≥35 years were less likely to be matched compared with mothers aged 20–34 years (adjusted ORs 0.92, 95% CI 0.88–0.96; and 0.87, 95% CI 0.86–0.89 respectively). The accuracy of linkage and the quality of the matched data suggest that these data are suitable for researching morbidity outcomes in most regions/countries. However, children born preterm and those born to mothers aged <20 and ≥35 years are less likely to be matched. While linkage to administrative databases enables identification of a reference group and long-term outcomes to be investigated, efforts are needed to improve linkages to population groups that are less likely to be linked. Public Library of Science 2023-08-30 /pmc/articles/PMC10468043/ /pubmed/37647348 http://dx.doi.org/10.1371/journal.pone.0290711 Text en © 2023 Loane et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Loane, Maria
Given, Joanne E.
Tan, Joachim
Barišić, Ingeborg
Barrachina-Bonet, Laia
Cavero-Carbonell, Clara
Coi, Alessio
Densem, James
Garne, Ester
Gissler, Mika
Heino, Anna
Jordan, Sue
Lutke, Renee
Neville, Amanda J.
Odak, Ljubica
Puccini, Aurora
Santoro, Michele
Scanlon, Ieuan
Urhoj, Stine K.
de Walle, Hermien E. K.
Wellesley, Diana
Morris, Joan K.
Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality
title Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality
title_full Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality
title_fullStr Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality
title_full_unstemmed Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality
title_short Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality
title_sort creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 european regions: assessment of linkage success and data quality
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468043/
https://www.ncbi.nlm.nih.gov/pubmed/37647348
http://dx.doi.org/10.1371/journal.pone.0290711
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