Patient safety and quality implications of large language model use in healthcare: a risk-stratified assessment of artificial intelligence-assisted medical consultations

These preliminary findings suggest that implementation of AI-assisted healthcare consultations may benefit from risk-stratified deployment strategies, pending validation in larger studies. Current findings inform the development of safety frameworks and quality indicators essential for maintaining high standards of care while leveraging the benefits of AI.

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Publication Details

Journal
International Journal for Quality in Health Care
Published
2025-12-23
DOI
https://doi.org/10.1093/intqhc/mzaf134
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
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article

Patient safety and quality implications of large language model use in healthcare: a risk-stratified assessment of artificial intelligence-assisted medical consultations

Pouyan Esmaeilzadeh
1 citations
International Journal for Quality in Health Care
Artificial Intelligence in Healthcare and Education
0.65
article

Patient safety and quality implications of large language model use in healthcare: a risk-stratified assessment of artificial intelligence-assisted medical consultations

Pouyan Esmaeilzadeh
article en
1 citations

Abstract

These preliminary findings suggest that implementation of AI-assisted healthcare consultations may benefit from risk-stratified deployment strategies, pending validation in larger studies. Current findings inform the development of safety frameworks and quality indicators essential for maintaining high standards of care while leveraging the benefits of AI.

International Journal for Quality in Health CareVol. 38(1)
Florida International University (US)
Openalex Percentile: Top 18%
Artificial Intelligence in Healthcare and Education
0.65
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