首页|New Artificial Intelligence Study Findings Have Been Reported from University of Montreal (Understanding the integration of artificial intelligence in healthcar e organisations and systems through the NASSS framework: a qualitative study in a ...)
New Artificial Intelligence Study Findings Have Been Reported from University of Montreal (Understanding the integration of artificial intelligence in healthcar e organisations and systems through the NASSS framework: a qualitative study in a ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting out of the Uni versity of Montreal by NewsRx editors, research stated, "Artificial intelligence (AI) technologies are expected to ‘revolutionise' healthcare." The news journalists obtained a quote from the research from University of Montr eal: "However, despite their promises, their integration within healthcare organ isations and systems remains limited. The objective of this study is to explore and understand the systemic challenges and implications of their integration in a leading Canadian academic hospital. Semi-structured interviews were conducted with 29 stakeholders concerned by the integration of a large set of AI technolog ies within the organisation (e.g., managers, clinicians, researchers, patients, technology providers). Data were collected and analysed using the Non-Adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework. Among enabling factors and conditions, our findings highlight: a supportive organisational cult ure and leadership leading to a coherent organisational innovation narrative; mu tual trust and transparent communication between senior management and frontline teams; the presence of champions, translators, and boundary spanners for AI abl e to build bridges and trust; and the capacity to attract technical and clinical talents and expertise. Constraints and barriers include: contrasting definition s of the value of AI technologies and ways to measure such value; lack of real-l ife and context-based evidence; varying patients' digital and health literacy ca pacities; misalignments between organisational dynamics, clinical and administra tive processes, infrastructures, and AI technologies; lack of funding mechanisms covering the implementation, adaptation, and expertise required; challenges ari sing from practice change, new expertise development, and professional identitie s; lack of official professional, reimbursement, and insurance guidelines; lack of pre- and post-market approval legal and governance frameworks; diversity of t he business and financing models for AI technologies; and misalignments between investors' priorities and the needs and expectations of healthcare organisations and systems."
University of MontrealArtificial Intel ligenceEmerging TechnologiesMachine LearningTechnology
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