What question did this study set out to answer?

To develop a comprehensive evaluation framework that assesses the long-term, real-world clinical, organizational, and economic impacts of artificial intelligence tools in healthcare.

October 14, 2024Open Access

AI for IMPACTS: A Comprehensive Framework for Evaluating the Long-term Real-world Impacts of AI-powered Clinician Tools (Preprint)

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Authors

CJChristine JacobFHNW University of Applied Sciences and Arts NBNoé BrasierUniversity of Basel ELEmanuele LaurenziFHNW University of Applied Sciences and Arts

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Implication

Systematic review reveals a seven-domain framework to assess long-term impacts of clinical AI tools across 44 studies, highlighting the need to evaluate workflow, safety, and economic factors.

Key Points

To develop a comprehensive evaluation framework that assesses the long-term, real-world clinical, organizational, and economic impacts of artificial intelligence tools in healthcare.
Conducted a systematic review following PRISMA guidelines across PubMed, Cochrane, Scopus, and IEEE Xplore for studies published between January 2019 and July 2024.
Screened 3,528 records to identify 44 studies meeting the inclusion criteria for evaluating clinical artificial intelligence implementations.
Synthesized recurring evaluation criteria using thematic analysis and narrative synthesis in NVivo.
Established the 'AI for IMPACTS' evaluation framework structured around seven major domains and 32 specific sub-criteria.
Defined core assessment clusters: integration, interoperability, and workflow; monitoring, governance, and accountability; performance and quality; acceptability, trust, and training; cost and economic evaluation; technological safety and transparency; and scalability and impact.

Cite This Study

Jacob et al. (2024) studied this question.

synapsesocial.com/papers/6a11fead0514fa642cccd9cc https://doi.org/10.2196/preprints.67485

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Implication

Systematic review reveals a seven-domain framework to assess long-term impacts of clinical AI tools across 44 studies, highlighting the need to evaluate workflow, safety, and economic factors.

AI for IMPACTS: A Comprehensive Framework for Evaluating the Long-term Real-world Impacts of AI-powered Clinician Tools (Preprint)

Discussion

Member takes

Implication

Key Points

Cite This Study

AI for IMPACTS: A Comprehensive Framework for Evaluating the Long-term Real-world Impacts of AI-powered Clinician Tools (Preprint)

Discussion

Member takes

Implication

Key Points

Cite This Study

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