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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

Maria Loane Orcid Logo, Joanne E. Given, Joachim Tan, Ingeborg Barišić, Laia Barrachina-Bonet Orcid Logo, Clara Cavero-Carbonell Orcid Logo, Alessio Coi Orcid Logo, James Densem, Ester Garne, Mika Gissler, Anna Heino, Sue Jordan Orcid Logo, Renee Lutke Orcid Logo, Amanda J. Neville, Ljubica Odak Orcid Logo, Aurora Puccini, Michele Santoro, Ieuan Scanlon, Stine K. Urhoj Orcid Logo, Hermien E. K. de Walle, Diana Wellesley, Joan K. Morris Orcid Logo

PLOS ONE, Volume: 18, Issue: 8, Start page: e0290711

Swansea University Author: Sue Jordan Orcid Logo

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DOI (Published version): 10.1371/journal.pone.0290711

Abstract

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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ISSN: 1932-6203
Published: Public Library of Science (PLoS) 2023
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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 &gt;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 &lt;20 and ≥35 years are less likely to be matched. 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spelling v2 64442 2023-09-05 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 24ce9db29b4bde1af4e83b388aae0ea1 0000-0002-5691-2987 Sue Jordan Sue Jordan true false 2023-09-05 HNU 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. Journal Article PLOS ONE 18 8 e0290711 Public Library of Science (PLoS) 1932-6203 Birth data, hospital discharge, EUROCAT, congenital anomalies, children 30 8 2023 2023-08-30 10.1371/journal.pone.0290711 http://dx.doi.org/10.1371/journal.pone.0290711 COLLEGE NANME Nursing COLLEGE CODE HNU Swansea University All authors (ML, JEG, JT, IB, LBB, CCC, AC, JD, EG, MG, AH, SJ, LRL, AJN, LO, AP, MS, IS, SKU, HEKdeW, DW, and JKM) were funded by the European Union’s Horizon 2020 Research and Innovation programme. Grant agreement number 733001. 2023-12-20T15:53:33.6191482 2023-09-05T18:16:15.9059616 Faculty of Medicine, Health and Life Sciences School of Health and Social Care - Nursing Maria Loane 0000-0002-1206-3637 1 Joanne E. Given 2 Joachim Tan 3 Ingeborg Barišić 4 Laia Barrachina-Bonet 0000-0002-5272-265x 5 Clara Cavero-Carbonell 0000-0002-4858-6456 6 Alessio Coi 0000-0002-9816-3144 7 James Densem 8 Ester Garne 9 Mika Gissler 10 Anna Heino 11 Sue Jordan 0000-0002-5691-2987 12 Renee Lutke 0000-0002-8470-7606 13 Amanda J. Neville 14 Ljubica Odak 0000-0001-9023-5142 15 Aurora Puccini 16 Michele Santoro 17 Ieuan Scanlon 18 Stine K. Urhoj 0000-0002-2069-9723 19 Hermien E. K. de Walle 20 Diana Wellesley 21 Joan K. Morris 0000-0002-7164-612x 22 64442__28742__d4a40119cad34ffbac874056957aa2c4.pdf 64442.VOR.pdf 2023-10-09T17:36:26.9156200 Output 1134486 application/pdf Version of Record true © 2023 Loane et al. Distributed under the terms of a Creative Commons Attribution 4.0 License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/
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
spellingShingle 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
Sue Jordan
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_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_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
author_id_str_mv 24ce9db29b4bde1af4e83b388aae0ea1
author_id_fullname_str_mv 24ce9db29b4bde1af4e83b388aae0ea1_***_Sue Jordan
author Sue Jordan
author2 Maria Loane
Joanne E. Given
Joachim Tan
Ingeborg Barišić
Laia Barrachina-Bonet
Clara Cavero-Carbonell
Alessio Coi
James Densem
Ester Garne
Mika Gissler
Anna Heino
Sue Jordan
Renee Lutke
Amanda J. Neville
Ljubica Odak
Aurora Puccini
Michele Santoro
Ieuan Scanlon
Stine K. Urhoj
Hermien E. K. de Walle
Diana Wellesley
Joan K. Morris
format Journal article
container_title PLOS ONE
container_volume 18
container_issue 8
container_start_page e0290711
publishDate 2023
institution Swansea University
issn 1932-6203
doi_str_mv 10.1371/journal.pone.0290711
publisher Public Library of Science (PLoS)
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Health and Social Care - Nursing{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Health and Social Care - Nursing
url http://dx.doi.org/10.1371/journal.pone.0290711
document_store_str 1
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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.
published_date 2023-08-30T15:53:34Z
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