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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.
Loane, Maria; Given, Joanne E; Tan, Joachim; Barisic, 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.
Afiliación
  • Loane M; Faculty of Life and Health Sciences, Ulster University, Belfast, Northern Ireland, United Kingdom.
  • Given JE; Faculty of Life and Health Sciences, Ulster University, Belfast, Northern Ireland, United Kingdom.
  • Tan J; Population Health Research Institute, St George's University of London, London, United Kingdom.
  • Barisic I; Children's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, Medical School University of Zagreb, Zagreb, Croatia.
  • Barrachina-Bonet L; Rare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Valencia, Spain.
  • Cavero-Carbonell C; Rare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Valencia, Spain.
  • Coi A; Unit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy.
  • Densem J; Biomedical Computing Limited, Battle, United Kingdom.
  • Garne E; Department of Paediatrics and Adolescent Medicine, Lillebaelt Hospital, University Hospital of Southern Denmark, Kolding, Denmark.
  • Gissler M; Department of Knowledge Brokers, THL Finnish Institute for Health and Welfare, Helsinki, Finland.
  • Heino A; Department of Knowledge Brokers, THL Finnish Institute for Health and Welfare, Helsinki, Finland.
  • Jordan S; Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, Wales, United Kingdom.
  • Lutke R; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Neville AJ; Emilia Romagna Registry of Birth Defects, Center for Clinical and Epidemiological Research, University of Ferrara, Azienda Ospedaliero- Universitaria di Ferrara, Ferrara, Italy.
  • Odak L; Children's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, Medical School University of Zagreb, Zagreb, Croatia.
  • Puccini A; Territorial Care Service, Emilia Romagna Health Authority Bologna, Bologna, Italy.
  • Santoro M; Unit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy.
  • Scanlon I; Public Health Wales, Swansea, United Kingdom.
  • Urhoj SK; Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark.
  • de Walle HEK; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Wellesley D; Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, United Kingdom.
  • Morris JK; Population Health Research Institute, St George's University of London, London, United Kingdom.
PLoS One ; 18(8): e0290711, 2023.
Article en En | MEDLINE | ID: mdl-37647348
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.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Alta del Paciente / Exactitud de los Datos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Alta del Paciente / Exactitud de los Datos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article