Background. Effective pain management relies on accurate and timely assessment. Traditional pain assessment tools often suffer from subjectivity, delayed evaluation, and inconsistencies across healthcare providers. Rapid Pain Assessment Tool (R-PAT) integrated with artificial intelligence (AI) support was developed to enhance the precision, consistency, and speed of pain assessment, aiming to redefine the approach to its management. Materials and methods. A pilot study was conducted in a clinical setting with 37 patients experiencing acute or chronic pain. R-PAT system combined patient self-reports, physiological data (e.g., heart rate, facial expression analysis), and AI-driven analysis to generate real-time pain scores. The tool was compared with conventional numeric rating scale assessments conducted by healthcare professionals. Data was collected over a 7-day period, and the correlation between R-PAT and traditional assessments was analyzed along with time efficiency and user satisfaction. Results. The AI-generated pain scores showed a strong positive correlation with traditional pain scores (r = 0.88, p < 0.001). Sensitivity and specificity of R-PAT in detecting moderate-to-severe pain were 92 and 89 %, respectively. The average time taken to assess pain using R-PAT was under 30 seconds compared to 2–3 minutes with conventional methods. R-PAT also allowed dynamic tracking of pain levels, which facilitated timely interventions. Conclusions. R-PAT with AI support proved to be a promising tool for enhancing pain assessment in clinical practice. It offers real-time, objective, and efficient pain evaluation, contributing to improved pain management outcomes. Larger-scale studies are warranted to validate its clinical utility across diverse populations and settings.
Popelnukha et al. (Wed,) studied this question.
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