{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T21:35:41Z","timestamp":1775770541843,"version":"3.50.1"},"reference-count":23,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T00:00:00Z","timestamp":1680048000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005381","name":"Financial Markets Foundation for Children","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005381","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Paediatric Perinatal Epid"],"published-print":{"date-parts":[[2023,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Administrative health data has been used extensively to examine congenital heart disease (CHD). However, the accuracy and completeness of these data must be assessed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>To use data linkage of multiple administrative data sources to examine the validity of identifying CHD cases recorded in hospital discharge data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We identified all liveborn infants born 2013\u20132017 in New South Wales, Australia with a CHD diagnosis up to age one, recorded in hospital discharge data. Using record linkage to multiple data sources, the diagnosis of CHD was compared with five reference standards: (i) multiple hospital admissions containing CHD diagnosis; (ii) receiving a cardiac procedure; (iii) CHD diagnosis in the Register of Congenital Conditions; (iv) cardiac\u2010related outpatient health service recorded; and\/or (v) cardiac\u2010related cause of death. Positive predictive values (PPV) comparing CHD diagnosis with the reference standards were estimated by CHD severity and for specific phenotypes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of 485,239 liveborn infants, there were 4043 infants with a CHD diagnosis identified in hospital discharge data (8.3 per 1000 live births). The PPV for any CHD identified in any of the five methods was 62.8% (95% confidence interval [CI] 60.9, 64.8), with PPV higher for severe CHD at 94.1% (95% CI 88.2, 100). Infant characteristics associated with higher PPVs included lower birthweight, presence of a syndrome or non\u2010cardiac congenital anomaly, born to mothers aged &lt;20\u2009years and residing in disadvantaged areas.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Using data linkage of multiple datasets is a novel and cost\u2010effective method to examine the validity of CHD diagnoses recorded in one dataset. These results can be incorporated into bias analyses in future studies of CHD.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ppe.12976","type":"journal-article","created":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T04:29:10Z","timestamp":1680150550000},"page":"303-312","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Examination of validity of identifying congenital heart disease from hospital discharge data without a gold standard: Using a data linkage approach"],"prefix":"10.1111","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7475-8485","authenticated-orcid":false,"given":"Wen\u2010Qiang","family":"He","sequence":"first","affiliation":[{"name":"Child Population and Translational Health Research, Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health University of Sydney  Sydney New South Wales Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3720-9655","authenticated-orcid":false,"given":"Natasha","family":"Nassar","sequence":"additional","affiliation":[{"name":"Child Population and Translational Health Research, Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health University of Sydney  Sydney New South Wales Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6245-7159","authenticated-orcid":false,"given":"Francisco J.","family":"Schneuer","sequence":"additional","affiliation":[{"name":"Child Population and Translational Health Research, Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health University of Sydney  Sydney New South Wales Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8988-7407","authenticated-orcid":false,"given":"Samantha J.","family":"Lain","sequence":"additional","affiliation":[{"name":"Child Population and Translational Health Research, Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health University of Sydney  Sydney New South Wales Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"Congenital Heart Disease Synergy Study group","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,3,29]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/2053951717745678"},{"key":"e_1_2_12_3_1","doi-asserted-by":"crossref","unstructured":"GoldsteinND KahalD TestaK GracelyEJ BurstynI.Data quality in electronic health record research: an approach for validation and quantitative bias analysis for imperfectly ascertained health outcomes via diagnostic codes. 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