Impact of data sources and ascertainment methods on reporting paediatric genetic condition prevalence: A scoping...

Background: Genetic conditions significantly impact health and contribute to paediatric morbidity and mortality. Despite advancements, accurate estimation of the burden of genetic conditions remains complex. Objective: To determine how different data sources and ascertainment methods influence the prevalence of paediatric monogenic and chromosomal conditions in Australia and internationally. Method: Following Arksey and O'Malley's framework for scoping reviews, a systematic search of Medline, CINAHL, Scopus and Google Scholar identified peer-reviewed studies (2004-2024) including snowballing of references. Studies were included if they reported on at least one monogenic and/or chromosomal condition, involved children under 6 years of age, identified the data source, reported prevalence, and were conducted in Australia, New Zealand, Europe or North America. Data sources, type of case ascertainment and prevalence of genetic conditions were extracted from eligible studies. Descriptive analysis was used to summarise study characteristics, including year of publication, region, condition type, data sources and ascertainment methods. Results: Of 58 included studies, 57% originated in Europe, 5% in Australia and 78% were published post-2010. Overall, 36.2% examined monogenic disorders and 29.3% chromosomal. Registries were the most common data source (62.1%), with 78% using active case ascertainment. Main strategies included medical record abstraction (30%), genetic testing (27.5%) and International Classification of Diseases (ICD)-coded data (27.5%). In Australia, genetic testing and medical records yielded higher prevalence than ICD-coded data; internationally, disease-specific registries which use active ascertainment approaches reported greater prevalence than passive ascertainment approaches. Conclusion: Findings highlight how data source selection and ascertainment methods influence prevalence estimates, risking under-ascertainment when relying solely on ICD-coded data. In Australian studies, disease registries were not utilised, reflecting the need to address Australia's fragmented surveillance infrastructure by integrating Orphanet nomenclature of rare diseases (ORPHAcodes) with ICD-coded data and expanding registries. Implications for health information management practice: Strengthening national coordination, training in genetic coding, nomenclature and inheritance mechanisms, and broader workforce competency will improve prevalence estimates of genetic conditions.