Comparison of Manual and AI-Assisted IV Cannulation Techniques among Chemotherapy Patients: A Comparative Simulation Study

Background: Intravenous (IV) cannulation is a routine yet challenging nursing procedure, particularly among chemotherapy patients who often present with fragile or sclerosed veins. First-attempt failure in IV access not only delays treatment but also increases pain, anxiety, and risk of complications. Recent advances in artificial intelligence (AI)-enabled vein visualization devices offer a potential solution to improve success rates. However, clinical evidence comparing traditional manual methods with AI-guided cannulation in oncology settings remains limited in India. Aim: To simulate and compare the effectiveness of manual versus AI-assisted IV cannulation techniques in chemotherapy patients, focusing on first-attempt success, time taken, and patient comfort. Methods: This comparative simulation study was conducted using 10 hypothetical chemotherapy patient scenarios, each assessed through two approaches: manual IV cannulation and AI-enabled vein visualization-assisted technique. Parameters like number of pricks, time required for cannulation, and pain score (on a visual analog scale) were recorded for each method. The findings were tabulated and analyzed to assess comparative efficiency. Results: Simulated outcomes indicated a notable improvement in first-attempt success with AI-assisted techniques, alongside reduced time and lower pain scores. While the manual method showed variability across cases, the AI-based approach demonstrated consistent performance in locating viable veins even in difficult conditions. Conclusion: AI-enabled vein visualization may enhance the accuracy and efficiency of IV cannulation in chemotherapy patients. Although this simulation-based study does not reflect real clinical trials, the findings support the need for further practical research and suggest potential adoption in high-dependency nursing settings.