Intelligent Operating Room Schedule Board with Real-Time Tracking
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Solution Overview
Problem
Current operating room management systems face inefficiencies and errors due to manual coordination between staff, inaccurate estimation of surgery durations, and manual updates of static schedules, leading to disruptions, extended patient wait times, and underutilization of equipment.
Innovation Solution
An intelligent operating room scheduling system comprising a visualization engine, tracking engine, and predictive optimization engine that automatically updates schedules based on real-time patient location and status, estimates procedure durations using machine learning, and proposes rescheduling to optimize surgical center operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual coordination and updating of schedules is used, then staff can communicate and adjust schedules flexibly, but labor intensity increases and human errors occur
Solution Approach 1:
The system enables automatic self-adjustment of schedules through real-time event detection and constraint-based optimization. The scheduling system autonomously detects events (patient delays, equipment failures, staff availability changes), evaluates their impact on the schedule, and automatically generates optimized reschedules without requiring manual intervention from coordinators, thereby eliminating labor-intensive manual updates while maintaining operational flexibility
Solution Approach 2:
The patent replaces the mechanical manual coordination system with an automated computational system. Instead of staff manually communicating and updating schedules through phone calls, emails, and whiteboards, the system uses software agents, event detection algorithms, and constraint satisfaction solvers to automatically manage schedule changes, reducing human labor while improving accuracy and efficiency
2Ease of operation
If static white board schedules are used, then schedule information is simple to display, but real-time updates and dynamic adjustments are difficult
Solution Approach 1:
The system transforms the static white board schedule into a dynamic digital display system that automatically updates in real-time. The electronic schedule board receives continuous input from event detection mechanisms, automatically recalculates optimized schedules based on current conditions, and displays updated information without manual intervention, thereby achieving both simplicity of display and real-time adaptability
Solution Approach 2:
The system implements continuous feedback loops where the schedule display is automatically updated based on real-time event detection and optimization results. The system monitors events, evaluates their impact on schedule constraints, generates optimized reschedules, and feeds these updates back to the electronic display and stakeholder notification systems, creating a dynamic adaptive schedule that responds automatically to changing conditions
3Device complexity
If surgery duration estimates are static and predetermined, then scheduling is simpler to plan, but disruptions occur when surgeries exceed allocated time
Solution Approach 1:
The system performs preliminary actions by proactively detecting events that may impact surgery duration before they cause disruptions. Event detection mechanisms monitor patient preparation status, equipment readiness, and surgeon availability, allowing the system to anticipate potential delays and adjust schedules in advance, thereby maintaining both planning simplicity and schedule reliability
Solution Approach 2:
The system dynamically changes scheduling parameters such as surgery duration estimates and start times based on real-time conditions. Instead of using fixed predetermined durations, the system adjusts these parameters automatically based on event detection results and optimization calculations, allowing flexible adaptation while maintaining overall schedule structure and simplicity
4Reliability
If multiple operating rooms are run simultaneously with conservative scheduling, then equipment utilization is ensured, but patient waiting time increases
Solution Approach 1:
The system optimizes scheduling parameters such as surgery duration estimates, start times, and operating room assignments by analyzing historical data and real-time conditions. This allows the system to reduce conservative buffer times while maintaining equipment utilization, thereby decreasing patient waiting time without compromising reliable resource allocation
Solution Approach 2:
The system autonomously optimizes the balance between equipment utilization and patient waiting time through automatic schedule generation and adjustment. The optimization algorithms evaluate multiple scenarios, consider equipment availability constraints, and automatically generate schedules that minimize waiting time while ensuring adequate equipment utilization, without requiring manual intervention to balance these competing objectives
Data Source
AI summary
A method for providing an intelligent schedule board for operating rooms in surgical centers and hospitals is provided. The method comprises displaying an estimated location of a patient on an operating room schedule board and displaying status information on the operating room schedule board. The method also comprises automatically updating the schedule dashboard as at least one of the location and the status of the patient changes. Patient location is estimated using an indoor tracking system and wherein the system is an RTLS system. Patient status information is entered by staff members by means of at least one of a tablet device, a phone device, and a computer. Patient status information is entered automatically by means of a computer vision scheme that detects patient status comprising at least one of a start of surgery and an end of surgery. Patient status information is entered using a voice recognition scheme.