Computer Vision Surgical Item Tracking to Reduce Retention Risk
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Solution Overview
Problem
Current methods for tracking surgical items during medical procedures are prone to errors due to manual counting, fatigue, complex operations, and poor counting systems, leading to a significant risk of items being inadvertently retained in patients, which poses health risks and increases the time and cost of medical care.
Innovation Solution
Implementing computational techniques such as computer vision, machine learning, and deep learning to automate the tracking and counting of surgical items, using special-purpose machines and mobile devices to ensure accurate identification and reconciliation of item counts, and providing notifications based on comparisons between initial and final counts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking and counting methods are used, then the system is simple and easy to operate, but the accuracy and reliability of surgical item tracking deteriorates due to fatigue and human error
Solution Approach 1:
The patent replaces manual mechanical counting methods with automated image processing and computer vision systems. Cameras capture images of surgical items, and algorithms automatically identify, count, and track them, eliminating human fatigue and error while maintaining system simplicity through software-based solutions.
Solution Approach 2:
The system creates digital copies (images) of surgical items and processes these copies computationally to determine item counts and track their movement. This allows accurate tracking without requiring direct physical manipulation or complex mechanical counting devices.
2Productivity
If manual counting methods are used, then the system is easy to operate, but the productivity and efficiency of the surgical process deteriorates due to time-consuming counting procedures
Solution Approach 1:
The image processing system operates continuously throughout the surgical procedure, automatically capturing and analyzing images of surgical items as they are introduced, used, and removed. This eliminates interruptions for manual counting and maintains continuous tracking, significantly improving productivity without time loss.
Solution Approach 2:
The system performs self-counting and self-tracking of surgical items through automated image recognition and processing. The computer vision algorithms independently identify and count items without requiring surgical staff to perform manual counting tasks, freeing them to focus on patient care and improving overall surgical efficiency.
3Reliability
If manual tracking methods are used, then the system is simple, but the reliability of preventing retained surgical items deteriorates due to compliance issues and errors
Solution Approach 1:
The system provides real-time feedback by continuously monitoring surgical item counts and comparing them against expected values. When discrepancies are detected, the system generates alerts to notify surgical staff immediately, enabling prompt correction and preventing retained items. This automated feedback loop significantly improves reliability compared to manual tracking.
Solution Approach 2:
The patent replaces unreliable manual tracking with automated computer vision and image processing systems that objectively identify and count surgical items. This substitution eliminates human error, fatigue, and compliance issues inherent in manual methods, providing reliable and consistent tracking throughout the procedure.
Data Source
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AI summary
Described herein are methods and systems for tracking surgical items. The methods may be performed by one or more processors, and may include receiving a first count of surgical items, receiving one or more images, wherein each image is a field of view comprising one or more surgical items, determining a second count of surgical items based at least in part on the one or more received images, and providing a notification based on the comparison between the first count of surgical items and the second count of surgical items.