Interventional pain medicine · 2026
Utilization and perceptions of artificial intelligence in pain medicine practice: An international pain and spine intervention society survey-based analysis.
СтатьяНазвание и аннотация: Перевод в очереди
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Ruan Qing Zhao, Fogarty Alexandra, Duszynski Belinda, Robinson Christopher L
Аннотация
BACKGROUND: Artificial intelligence (AI) is rapidly expanding with Pain medicine, offering applications ranging from clinical documentation to predictive modeling. In view of this growing interest, the characteristics and sentiments of physician AI users in this field ought to be better delineated.
OBJECTIVES: To characterize the demographics of AI users in Pain medicine and evaluate patterns of adoption, utilization and attitudes towards AI integration in the clinical practice of Pain medicine.
METHODS: A web-based survey was distributed via email and social media to US and international clinicians. Survey design was validated by the IPSIS AI Task Force and deemed IRB-exempt. Responses were analyzed descriptively.
RESULTS: Respondents were predominantly male (83.9%) and most commonly anesthesiologists (35.7%) or PM&R physicians (48.2%), with over 60% in practice >10 years. AI familiarity was high, with 75% reporting clinical use and 51% using AI daily. Common applications included ambient documentation (60.8%) and research summarization (56.9%). Most users reported positive impact, particularly in time savings (80%). Key concerns included overreliance (38%), misinformation (38%), and legal liability (32%). Over 80% anticipated increased AI use within 2 years.
CONCLUSIONS: AI adoption among Pain physicians is significant and viewed favorably, though primarily applied to non-specialty-specific tasks. Addressing concerns and enhancing integration and education will be critical for advancing specialty-specific AI utilization.
OBJECTIVES: To characterize the demographics of AI users in Pain medicine and evaluate patterns of adoption, utilization and attitudes towards AI integration in the clinical practice of Pain medicine.
METHODS: A web-based survey was distributed via email and social media to US and international clinicians. Survey design was validated by the IPSIS AI Task Force and deemed IRB-exempt. Responses were analyzed descriptively.
RESULTS: Respondents were predominantly male (83.9%) and most commonly anesthesiologists (35.7%) or PM&R physicians (48.2%), with over 60% in practice >10 years. AI familiarity was high, with 75% reporting clinical use and 51% using AI daily. Common applications included ambient documentation (60.8%) and research summarization (56.9%). Most users reported positive impact, particularly in time savings (80%). Key concerns included overreliance (38%), misinformation (38%), and legal liability (32%). Over 80% anticipated increased AI use within 2 years.
CONCLUSIONS: AI adoption among Pain physicians is significant and viewed favorably, though primarily applied to non-specialty-specific tasks. Addressing concerns and enhancing integration and education will be critical for advancing specialty-specific AI utilization.