Medical Service Queuing System for Reducing Patient Wait Times
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users often face long waiting times before receiving services, and are sometimes directed to additional service stations without an efficient queuing system, leading to further delays for both users and service staff.
Innovation Solution
A user-oriented queuing method and electronic device that receive user data, determine queuing times based on serial numbers and queue lengths, and direct users to the most efficient service station or stop, minimizing overall waiting time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users are directed to additional service stations without an efficient queuing system, then service completeness is improved, but waiting time increases
Solution Approach 1:
The system performs preliminary actions by calculating optimal service sequences and predicting waiting times before users actually queue. The server determines the best order to visit multiple service stations in advance, allowing users to plan their movement and reduce actual waiting time while ensuring all necessary services are completed.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring queue lengths at different service stations and using this information to dynamically adjust service route recommendations. The server receives real-time queue data and provides updated optimal paths to users, enabling adaptive decision-making that minimizes waiting time while maintaining service completeness.
2Stability of the object's composition
If users wait in traditional sequential queues at multiple service stations, then service order is maintained, but overall service efficiency decreases
Solution Approach 1:
The system applies dynamics by transforming the static, fixed sequential queuing process into a dynamic, flexible service sequence. Instead of requiring users to follow a predetermined rigid order, the system dynamically determines optimal service sequences based on real-time queue conditions, allowing adaptive adjustment while maintaining necessary service dependencies.
Solution Approach 2:
The system changes parameters by optimizing the service sequence based on multiple variables including queue lengths, service durations, and station locations. The server calculates different possible sequences and selects the optimal one by evaluating these parameters, thereby improving service efficiency while maintaining order through calculated optimization rather than fixed rules.
3Loss of time
If a centralized server calculates optimal service sequences, then waiting time is reduced, but system complexity increases
Solution Approach 1:
The centralized server acts as an intermediary that receives queue data from multiple service stations, processes this information to calculate optimal service sequences, and provides recommendations to users. This intermediary approach consolidates the computational complexity in a single central system rather than distributing it across multiple stations, reducing overall system complexity while achieving waiting time reduction.
Data Source
AI summary
A system for maximizing utilizations of medical equipment in a medical facility, including a server configured to receive a medical service station data comprising a quantity of queued people and the medical equipment usage data in the medical service station; and a first stop service station data comprising a quantity of waiting people and the medical equipment usage data in the first stop service station. The server is further configured to classify, by employing a supervised learning classifier, whether or not to first service a user in the first stop service station using the medical service station data and the first stop service station data, so to maximize the probability of continuous utilizations of all medical equipment and to minimize the user's queuing time in the medical service station and waiting time in the first stop service station.