Evidence map›Paper›PMID 39876484›Full record

ArticlePaediatric and perinatal epidemiology2025

Recommendations for Improving Surveillance of Congenital Anomalies in Europe Using Healthcare Databases.

Maria Loane, Joan K Morris, Ester Garne

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Article in Paediatric and perinatal epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

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5citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Maria LoaneInstitute of Nursing and Health Research, Ulster University, Belfast, UK.ORCID https://orcid.org/0000-0002-1206-3637
Joan K MorrisSchool of Health & Medical Sciences, City St George's University of London, London, UK.ORCID https://orcid.org/0000-0002-7164-612X
Ester GarneDepartment of Paediatrics and Adolescent Medicine, Lillebaelt Hospital, University Hospital of Southern Denmark, Kolding, Denmark.

Funding

European Union's Horizon 2020 Research and Innovation programme under grant agreement No 733001, from January 2017 to May 2022
6 · The paper itself

Abstract

backgroundAlthough accessing administrative data in healthcare databases may be a more time-efficient and cost-effective method of conducting surveillance, there is evidence suggesting that administrative data alone are not sufficient for population-based surveillance of congenital anomalies.

objectiveTo propose recommendations to maximise the potential use of healthcare databases for surveillance of congenital anomalies based on our data linkage experiences and results from the EUROlinkCAT study.

methodsEUROlinkCAT is a population-based cohort study of 99,416 children with anomalies born between 1995 and 2014. The congenital anomaly case records of children in 11 European congenital anomaly (EUROCAT) registries (eight countries) were linked to standardised administrative healthcare data (birth records, death records and hospital discharge records) to evaluate mortality and morbidity outcomes in these children. Overall, 97% of children with anomalies were successfully matched to their records in their national or regional administrative databases. Recommendations to improve surveillance of anomalies when using healthcare data were developed through establishing and analysing data from this cohort.

resultsThe primary recommendation is to develop systems to report anomalies diagnosed in foetuses who undergo a termination and link these data to their mothers. Each liveborn baby must be assigned a permanent unique identification number at birth to enable accurate linkage across healthcare databases. Implementing and improving existing algorithms to discriminate between major anomalies and suspected or minor anomalies will improve accuracy in coding. Heterogeneity in coding anomalies will improve by avoiding the use of 'unspecified' or 'other specified' codes in hospital databases. Relaxation of country-specific regulations concerning the suppression of small numbers are necessary to enable data to be combined across European countries.

conclusionImplementation of these recommendations will enable the information in electronic healthcare databases, in conjunction with Congenital Anomaly registries, to be fully exploited and hence will improve the surveillance of anomalies in children.

Indexed as

Congenital AbnormalitiesDatabases, FactualPopulation SurveillanceEuropeFemaleHumansInfant, NewbornMalePregnancyRegistriescongenital anomalieshealthcare databaseslinkagequalityrecommendationssurveillance

Identifiers

PMID39876484
PMCPMC11997239

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.