Operationalizing the Pan-Canadian Health Data Charter Through Common Standards and AI-Enabled Nursing Data

Principle 4 of the Pan-Canadian Health Data Charter calls for common standards to enable interoperability, access, and portability of health data. Yet clinically meaningful information, particularly nursing documentation, remains largely unstructured and siloed across care settings. This article argues that nursing data represent a critical but under-leveraged asset for improving patient safety and continuity of care, as it captures early indicators of deterioration, functional decline, and social context often absent from structured datasets. While traditional approaches to standardization have relied on behavioural change, emerging Artificial Intelligence (AI) tools offer a practical alternative by translating narrative documentation into standardized, interoperable formats. Drawing on institutional examples and current evidence, the article examines the possibilities and potential benefits of leveraging AI to fully realize the promise of common standards in practice without creating undue burdens for clinicians.

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Publication Details

Journal
Healthcare Management Forum
Published
2026-06-16
DOI
https://doi.org/10.1177/08404704261458190
Primary Topic
Nursing Diagnosis and Documentation
Type
article
Field-Weighted Citation Impact
0.00
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article

Operationalizing the Pan-Canadian Health Data Charter Through Common Standards and AI-Enabled Nursing Data

Glynda Rees, Pegg White, Lynn Nagle, Steven Tam
Healthcare Management Forum
Nursing Diagnosis and Documentation
article

Operationalizing the Pan-Canadian Health Data Charter Through Common Standards and AI-Enabled Nursing Data

Glynda Rees, Pegg White, Lynn Nagle, Steven Tam
article en

Abstract

Principle 4 of the Pan-Canadian Health Data Charter calls for common standards to enable interoperability, access, and portability of health data. Yet clinically meaningful information, particularly nursing documentation, remains largely unstructured and siloed across care settings. This article argues that nursing data represent a critical but under-leveraged asset for improving patient safety and continuity of care, as it captures early indicators of deterioration, functional decline, and social context often absent from structured datasets. While traditional approaches to standardization have relied on behavioural change, emerging Artificial Intelligence (AI) tools offer a practical alternative by translating narrative documentation into standardized, interoperable formats. Drawing on institutional examples and current evidence, the article examines the possibilities and potential benefits of leveraging AI to fully realize the promise of common standards in practice without creating undue burdens for clinicians.

Healthcare Management Forum
Canadian Nurses Association (CA), British Columbia Institute of Technology (CA), Associates Research (UG)
Openalex Percentile: Top 4%
Nursing Diagnosis and Documentation
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Operationalizing the Pan-Canadian Health Data Charter Through Common Standards and AI-Enabled Nursing Data — Glynda Rees, Pegg White, et al. · Healthcare Management Forum (2026) | TGRS Research Map | TGRS