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

PLOS ONE, Aug 2023

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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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

PLOS ONE RESEARCH ARTICLE a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Loane M, Given JE, Tan J, Barišić I, Barrachina-Bonet L, Cavero-Carbonell C, et al. (2023) 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. PLoS ONE 18(8): e0290711. https://doi.org/ 10.1371/journal.pone.0290711 Editor: Tamirat Getachew, Haramaya University Faculty of Health Sciences: Haramaya University College of Health and Medical Sciences, ETHIOPIA 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 ID1*, Joanne E. Given1, Joachim Tan2, Ingeborg Barišić3, Laia BarrachinaBonet ID4, Clara Cavero-Carbonell ID4, Alessio Coi ID5, James Densem6, Ester Garne7, Mika Gissler8, Anna Heino8, Sue Jordan9, Renee Lutke ID10, Amanda J. Neville11, Ljubica Odak ID3, Aurora Puccini12, Michele Santoro5, Ieuan Scanlon13, Stine K. Urhoj ID14, Hermien E. K. de Walle10, Diana Wellesley15, Joan K. Morris ID2 1 Faculty of Life and Health Sciences, Ulster University, Belfast, Northern Ireland, United Kingdom, 2 Population Health Research Institute, St George’s University of London, London, United Kingdom, 3 Children’s Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, Medical School University of Zagreb, Zagreb, Croatia, 4 Rare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Valencia, Spain, 5 Unit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy, 6 Biomedical Computing Limited, Battle, United Kingdom, 7 Department of Paediatrics and Adolescent Medicine, Lillebaelt Hospital, University Hospital of Southern Denmark, Kolding, Denmark, 8 Department of Knowledge Brokers, THL Finnish Institute for Health and Welfare, Helsinki, Finland, 9 Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, Wales, United Kingdom, 10 Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands, 11 Emilia Romagna Registry of Birth Defects, Center for Clinical and Epidemiological Research, University of Ferrara, Azienda Ospedaliero- Universitaria di Ferrara, Ferrara, Italy, 12 Territorial Care Service, Emilia Romagna Health Authority Bologna, Bologna, Italy, 13 Public Health Wales, Swansea, United Kingdom, 14 Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark, 15 Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, United Kingdom * Received: October 31, 2022 Accepted: August 14, 2023 Abstract Published: August 30, 2023 Copyright: © 2023 Loane et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: We are legally not allowed to share the third-party administrative data used in this study as it belongs to the data providers in each of the regions i.e. the regional or national statistical organisations. The study team had access to aggregate data only from each region i.e. the linked patient level data remained in the local region. The authors did not receive any 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 PLOS ONE | https://doi.org/10.1371/journal.pone.0290711 August 30, 2023 1 / 16 PLOS ONE special privileges in accessing the data, and had to abide by the same rules and regulations pertaining to the data as other researchers. All the variables included in the study are found in the S1 Table, which includes the variable names, description, format, and coding scheme. All our documentation is available on the EUROlinkCAT website (http:// www.EUROlinkCAT.eu/wp2buildingresultsrepository). and we encourage any interested parties to apply to the EUROlinkCAT management team to assist them in obtaining approval from the data providers in each region/ country to use the aggregated data for an approved study http://www.EUROlinkCAT.eu/ contactinformationanddatarequests. Funding: 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. https://research-and-innovation.ec. europa.eu/funding/funding-opportunities/fundingprogrammes-and-open-calls/horizon-2020_en The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Linking children with and without congenital anomalies to hospital discharge databases 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; (...truncated)


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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. 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, PLOS ONE, 2023, Volume 18, Issue 8, DOI: 10.1371/journal.pone.0290711