Implementation of a Sudden Cardiac Death Risk Prediction Tool in Clinical Practice Through Electronic Health Records (INSERT-HCM Study Design)

Sudden cardiac death is a leading cause of mortality in children with hypertrophic cardiomyopathy (HCM). The PRecIsion Medicine in CardiomYopathy consortium developed a validated tool (PRIMaCY) for sudden cardiac death risk prediction to help with implantable cardioverter defibrillator shared decision-making, as recommended by clinical practice guidelines. The <b>I</b>mpleme<b>n</b>ting a <b>S</b>udden Cardiac D<b>e</b>ath <b>R</b>isk Assessment <b>T</b>ool in <b>C</b>hildhood <b>HCM</b> (INSERT-HCM) study aims to implement PRIMaCY into electronic health records (EHRs) and assess implementation determinants and outcomes. INSERT-HCM is a prospective, multicentre, hybrid type-3 mixed-methods implementation study of an EHR-embedded risk calculator across Canadian pediatric hospitals. The Active Implementation Framework will inform a staged implementation process, with organization-based implementation teams facilitating the implementation technical installation and implementation process. PRIMaCY will be installed as a user-tested EHR-integrated tool and implemented in practice using an organization and provider-focused strategy at participating hospitals. Technical installation and implementation strategies will be optimized for each healthcare setting. The Implementation Outcomes Taxonomy will inform implementation outcomes. Back-end EHR data will assess tool adoption, penetration, and fidelity. The Consolidated Framework for Implementation Research will assess implementation determinants (facilitators and barriers), and sustainability in clinical practice will be explored. INSERT-HCM will inform best practices for implementing an evidence-based digital health solution within hospital EHRs and clinical workflows to improve guideline-directed care. Developing an effective implementation strategy will inform the future dissemination of EHR-integrated digital health tools to the broader scientific and clinical community.

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Publication Details

Journal
CJC Open
Published
2024-10-09
DOI
https://doi.org/10.1016/j.cjco.2024.10.002
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00

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article

Implementation of a Sudden Cardiac Death Risk Prediction Tool in Clinical Practice Through Electronic Health Records (INSERT-HCM Study Design)

Tanya Papaz, Robin Z. Hayeems, Sarah J. Pol, Melanie A. Barwick et al.
CJC Open
Machine Learning in Healthcare
article

Implementation of a Sudden Cardiac Death Risk Prediction Tool in Clinical Practice Through Electronic Health Records (INSERT-HCM Study Design)

Tanya Papaz, Robin Z. Hayeems, Sarah J. Pol, Melanie A. Barwick, Emily Seto, Samantha J. Anthony, Seema R. Mital
article en

Abstract

Sudden cardiac death is a leading cause of mortality in children with hypertrophic cardiomyopathy (HCM). The PRecIsion Medicine in CardiomYopathy consortium developed a validated tool (PRIMaCY) for sudden cardiac death risk prediction to help with implantable cardioverter defibrillator shared decision-making, as recommended by clinical practice guidelines. The <b>I</b>mpleme<b>n</b>ting a <b>S</b>udden Cardiac D<b>e</b>ath <b>R</b>isk Assessment <b>T</b>ool in <b>C</b>hildhood <b>HCM</b> (INSERT-HCM) study aims to implement PRIMaCY into electronic health records (EHRs) and assess implementation determinants and outcomes. INSERT-HCM is a prospective, multicentre, hybrid type-3 mixed-methods implementation study of an EHR-embedded risk calculator across Canadian pediatric hospitals. The Active Implementation Framework will inform a staged implementation process, with organization-based implementation teams facilitating the implementation technical installation and implementation process. PRIMaCY will be installed as a user-tested EHR-integrated tool and implemented in practice using an organization and provider-focused strategy at participating hospitals. Technical installation and implementation strategies will be optimized for each healthcare setting. The Implementation Outcomes Taxonomy will inform implementation outcomes. Back-end EHR data will assess tool adoption, penetration, and fidelity. The Consolidated Framework for Implementation Research will assess implementation determinants (facilitators and barriers), and sustainability in clinical practice will be explored. INSERT-HCM will inform best practices for implementing an evidence-based digital health solution within hospital EHRs and clinical workflows to improve guideline-directed care. Developing an effective implementation strategy will inform the future dissemination of EHR-integrated digital health tools to the broader scientific and clinical community.

CJC OpenVol. 7(1)
University Health Network (CA), University of Toronto (CA), Hospital for Sick Children (CA), Toronto General Hospital (CA), Ted Rogers Centre for Heart Research (CA), Public Health Ontario (CA), SickKids Foundation (CA), Institute for Clinical Evaluative Sciences (CA)
Heart and Stroke Foundation of Canada, Canadian Institutes of Health Research
Good health and well-being
Openalex Percentile: Top 85%
Machine Learning in Healthcare
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