Bridging the Evidence-to-Practice Gap at Scale: Evolving Evidence2Practice Ontario by Using the Pan-Canadian HALO Framework

Clinical decision support tools such as Evidence2Practice Ontario (E2P) can be an effective way to reduce the 17-year gap between clinical innovation and its use in practice. To enhance the interoperability and scalability of E2P we propose leveraging the pan-Canadian Health Application Lightweight Protocol (HALO) framework. Public and private developers could be informed by E2P as the initial use case to test the capability of HALO to support clinical decision support tools.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-02-18
DOI
https://doi.org/10.3233/shti250022
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Bridging the Evidence-to-Practice Gap at Scale: Evolving Evidence2Practice Ontario by Using the Pan-Canadian HALO Framework

Rebecca Ataman, P.S. Duval Co., David K. Kaplan, Alex Reis et al.
Studies in health technology and informatics
Biomedical Text Mining and Ontologies
article

Bridging the Evidence-to-Practice Gap at Scale: Evolving Evidence2Practice Ontario by Using the Pan-Canadian HALO Framework

Rebecca Ataman, P.S. Duval Co., David K. Kaplan, Alex Reis, Kevin K. Chung, Daniel Thamotharem, Karine Baser, Moe Fawal
article en

Abstract

Clinical decision support tools such as Evidence2Practice Ontario (E2P) can be an effective way to reduce the 17-year gap between clinical innovation and its use in practice. To enhance the interoperability and scalability of E2P we propose leveraging the pan-Canadian Health Application Lightweight Protocol (HALO) framework. Public and private developers could be informed by E2P as the initial use case to test the capability of HALO to support clinical decision support tools.

Studies in health technology and informaticsVol. 322
Canada Health Infoway (CA), University of Toronto (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 94%
Biomedical Text Mining and Ontologies
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