Evidence map›Paper›PMID 38746592›Full record

ArticleInternational journal of nursing studies advances2023

Key conditions for the successful implementation of evidence-based practice in concurrent disorder nursing care with the ECHO® model: Insights from a mixed-methods study.

Gabrielle Chicoine, José Côté, Jacinthe Pepin, Pierre Pluye, Didier Jutras-Aswad

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Article in International journal of nursing studies advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Gabrielle ChicoineKnowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, ON,Toronto, Canada.
José CôtéFaculty of Nursing, Université de Montréal, Montreal, Quebec (QC), Canada.
Jacinthe PepinFaculty of Nursing, Université de Montréal, Montreal, Quebec (QC), Canada.
Pierre PluyeFaculty of Medicine, Department of Family Medicine, McGill University, Montreal, QC, Canada.
Didier Jutras-AswadUniversité de Montréal Hospital Research Center, Montreal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: People with concurrent mental health and substance use disorders have complex biopsychosocial problems but risk not having their healthcare needs met. Nurses are positioned to meet these needs but often lack training in concurrent disorder management. Extension for Community Healthcare Outcomes (ECHO®, University of New Mexico Health Sciences Center, 2003) is a promising technology-enabled collaborative learning model used to implement evidence-based practice and build capacity among healthcare professionals in managing complex, chronic, health conditions. Objective: To understand how an ECHO program for concurrent disorder management impacts nurses' competency development and clinical practice and uncover key conditions for successful uptake and implementation. Design: A convergent mixed-methods design comprising a quantitative, uncontrolled before-and-after study and a qualitative study using interpretive description methodology. Setting and participants: An ECHO program for concurrent disorder management was implemented in 2018 at a quaternary academic hospital centre in metropolitan Western Canada. All 65 nurses who registered in the program between 2018 and 2020 were invited to participate in the study. Methods: Online surveys completed by the participating nurses ( Results: We identified six interrelated key conditions for successful uptake and implementation of evidence-based practice in concurrent disorder nursing care with ECHO: (1) Practice and validation opportunities; (2) Reciprocal and trusting relationships in an interprofessional education context; (3) Peer-to-peer experience sharing; (4) Collaboration with experts; (5) Reinforcement of positive attitudes towards one's professional role; and (6) Organizational support. Conclusions: Outcome measures, perspectives, and experiences collected over 12 months indicated that ECHO contributed to nurses' competency development and, under some conditions, to effective nursing practice changes. Given the challenges in implementing clinical guidelines in concurrent disorder nursing care, our results highlight the importance of understanding the key conditions for successful uptake and implementation. This informs approaches to optimally adapt implementation strategies to the needs and specificities of nurses to obtain impactful and sustainable results.

Indexed as

Concurrent disordersContinuing professional educationDistance learningDual diagnosisImplementationKnowledge translationMixed methodsNurse

Identifiers

PMID38746592
PMCPMC11080413

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.