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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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Published in: PLOS ONE
ISSN: 1932-6203
Published: Public Library of Science (PLoS) 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa64442
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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 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.
Keywords: Birth data, hospital discharge, EUROCAT, congenital anomalies, children
College: Faculty of Medicine, Health and Life Sciences
Funders: 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.
Issue: 8
Start Page: e0290711

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