Surgical Tray Imaging and AI Tracking for Billing Accuracy
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Solution Overview
Problem
Current tracking systems for surgical trays and medical assets lack efficiency and precision, leading to inaccuracies in asset management, billing, and potential clinical consequences due to inadequate digital workflows and high physical handover inefficiencies between vendors and hospitals.
Innovation Solution
A digitized tray management system using computer vision and artificial intelligence to capture and analyze images of surgical trays and assets, creating digital templates, and tracking changes through a lifecycle, integrating with electronic health records for accurate inventory and billing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking and physical handover methods are used for surgical trays and medical assets, then the system is simple to implement, but tracking accuracy and efficiency deteriorate leading to billing errors and clinical consequences
Solution Approach 1:
The patent creates a digital copy (photograph) of the surgical tray and its contents, which is then processed by AI algorithms to generate a digital inventory record. This digital copy replaces manual tracking methods, enabling automatic asset identification and tracking without physically handling each item, thereby improving tracking accuracy while maintaining relative system simplicity.
Solution Approach 2:
The patent replaces manual mechanical tracking methods with an automated system using photographs and AI algorithms. The mechanical process of physically counting and recording assets is substituted with digital image capture and automated image recognition, eliminating human error in tracking while improving efficiency and accuracy.
2Productivity
If automated digital tracking systems are implemented, then tracking efficiency and accuracy improve, but system complexity and implementation burden increase
Solution Approach 1:
The system enables self-service tracking by automatically capturing images of surgical trays and using AI algorithms to identify and record assets without requiring manual intervention. The automated image recognition and inventory generation occur without human input, improving tracking efficiency while minimizing the operational burden on staff.
Solution Approach 2:
The patent introduces a photograph as an intermediary between the physical surgical tray and the digital tracking system. This intermediate digital representation allows the AI system to analyze and track assets without direct physical interaction, simplifying the integration between physical and digital domains while maintaining high tracking efficiency.
3Reliability
If manual inventory recording is used, then the system is easy to operate, but billing accuracy and clinical record-keeping quality deteriorate
Solution Approach 1:
The system provides automated feedback by generating digital inventory records from image analysis, which are then used for billing and clinical documentation. This closed-loop process ensures that the recorded inventory accurately reflects the actual assets used, improving billing accuracy and record-keeping quality while reducing manual operational steps.
Solution Approach 2:
The patent replaces manual inventory recording with automated image recognition and digital record generation. The mechanical process of manually counting and writing down assets is substituted with automated digital capture and processing, eliminating transcription errors and improving billing accuracy while maintaining operational simplicity through automation.
Data Source
AI summary
A system and method for tracking and managing a surgical tray and medical assets loaded thereon comprises a user interface for capturing an image of the surgical tray and medical assets loaded thereon at various points of time and locations; a first tangible non-transitory storage medium storing datasets related to the image of the tray and medical assets as captured by the user interface; a second tangible non-transitory storage medium storing datasets related to configuration of surgical trays comprising information on dimensions, colors, and locations of the tray, device identifiers, information on tray identifiers, and information on customers; one or more non-transitory media being connected to the user interface and storing instructions for execution; and a set of computer algorithms that extract information or features from the image and medical assets loaded on the surgical tray received from the one or more non-transitory media.