This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2690) Clinical Informatics (1107) Clinical Information and Decision Making (1548) Human Factors and Usability Case Studies (858) E-Health / Health Services Research and New Models of Care (576) Quality Improvement (267) Adoption and Change Management of eHealth Systems (769) New Technologies (91) Artificial Intelligence (1602) Decision Support for Health Professionals (1287)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47335, first published .
Barriers and Enablers for Implementation of an Artificial Intelligence–Based Decision Support Tool to Reduce the Risk of Readmission of Patients With Heart Failure: Stakeholder Interviews

Barriers and Enablers for Implementation of an Artificial Intelligence–Based Decision Support Tool to Reduce the Risk of Readmission of Patients With Heart Failure: Stakeholder Interviews

Barriers and Enablers for Implementation of an Artificial Intelligence–Based Decision Support Tool to Reduce the Risk of Readmission of Patients With Heart Failure: Stakeholder Interviews

Authors of this article:

Monika Nair1 Author Orcid Image ;   Jonas Andersson2 Author Orcid Image ;   Jens M Nygren1 Author Orcid Image ;   Lina E Lundgren3 Author Orcid Image
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JMIR Formative Res: Barriers and Enablers for Implementation of an artificial intelligence (#AI)–Based Decision Support Tool to Reduce the Risk of Readmission of Patients With Heart Failure: Stakeholder Interviews https://t.co/LrrtpBgKsI https://t.co/xgmK89QJRK

1:16 PM · Aug 23, 2023

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RT @jmirpub: JMIR Formative Res: Barriers and Enablers for Implementation of an artificial intelligence (#AI)–Based Decision Support Tool t…

1:16 PM · Aug 23, 2023

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