Language, culture, and ethnicity data collection in pediatric healthcare in Canada: a national environmental scan.

Authors

Victor Do, Amanda S Newton, Rebecca Gokiert, Geoff D C Ball

Published in

Paediatrics & child health. Volume 31. Issue 7. Pages 786-792. Epub Jul 22, 2026.

Abstract

Canada's pediatric healthcare systems serve an increasingly ethnoculturally diverse population, yet the standardized collection of language, culture, and ethnicity (LCE) data remains inconsistent. Without reliable data, health systems cannot identify inequities, monitor disparities, or design targeted interventions. Our purpose was to examine current LCE data collection practices across pediatric healthcare settings in Canada and identify perceived barriers, enablers, and opportunities to strengthen equitable data infrastructure.
A cross-sectional environmental scan was conducted between January and February 2026 using an anonymous online survey of pediatric healthcare clinicians and staff across Canada. The survey included closed- and open-ended questions on LCE data collection practices, tools, effectiveness, data use, training, and organizational supports. Quantitative data were analyzed descriptively; qualitative responses underwent inductive content analysis.
A total of 237 participants from diverse pediatric settings completed the survey. Nearly 60% reported that their organization does not collect LCE data, and 56% were unsure of the effectiveness of existing practices. When collected, LCE data were primarily limited to preferred language and used to identify interpreter needs. Formal training and organizational policies were rare (both 3%). Perceived barriers included a lack of training, time constraints, and the absence of standardized tools. Qualitative findings highlighted strong conceptual support for LCE data collection but emphasized its conditional value, ethical complexity, and need for participatory approaches.
LCE data collection in Canadian pediatric healthcare remains fragmented and underutilized. Advancing equitable data infrastructure will require standardized protocols, targeted training, participatory co-design, and clear accountability for data use.

PMID:
42947918
Bibliographic data and abstract were imported from PubMed on 28 Oct 2026.

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