AI-Enabled Mobile Application for Surgical Safety Checklist Automation and Wrong-Patient Surgery Prevention

Abstract

Wrong Site, Wrong Procedure and Wrong Patient adverse events (WSPEs) rank among the most alarming and catastrophic errors in surgical practice. Although such incidents are relatively rare, their impact becomes significant in highly populated countries like India, where the sheer volume of daily procedures amplifies the risk. The wrong procedure and wrong patient adverse event anomaly occur when the surgery is being done on the wrong person, often due to name similarities, leading to unwanted surgery that could cause a lot of damage. Although standardized surgical checklists are implemented to prevent such errors, high surgical volumes often make strict compliance challenging for healthcare teams. The increased workload can lead to oversight, reducing the effectiveness of manual verification processes. To address this issue, this paper presents an AI-driven mobile application employing FaceNet architecture to streamline checklist completion and enhance patient identification accuracy. By automating critical verification steps, the solution minimizes human error and reinforces adherence to safety protocols, ensuring more reliable and efficient surgical procedures. Experimental validation proves that the FaceNet achieved 100% detection and 98.33% recognition accuracy. Hospitals can integrate this technology to strengthen patient safety measures and reduce the incidence of preventable adverse events.

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