Dynamic Medical Queuing Platform Using Geofencing and ML
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Urgent care facilities face inefficiencies due to static slotted appointment systems that fail to account for individual patient needs, leading to long wait times and rushed appointments, as they are inflexible and do not adapt to real-time patient flow and location dynamics.
Innovation Solution
A dynamic medical practice queuing platform that uses geofencing and machine learning algorithms to manage virtual waiting rooms, allowing patients to be placed in a virtual queue based on their location and travel time, providing real-time updates and personalized appointment durations, and enabling healthcare providers to tailor appointment lengths according to patient needs and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static slotted appointment systems are used, then appointment scheduling is simplified, but patient wait times increase and individual patient needs are not accommodated
Solution Approach 1:
The patent implements a dynamic queue management system that transitions from static pre-scheduled appointments to real-time dynamic queuing. The system continuously monitors patient arrival times, provider availability, and queue lengths to dynamically adjust appointment scheduling, thereby reducing wait times while maintaining operational simplicity through automated real-time coordination.
Solution Approach 2:
The system incorporates real-time feedback loops that monitor actual patient flow, queue lengths, and provider schedules. This feedback enables the system to automatically adjust appointment times and queue positions based on current conditions, optimizing patient wait times while keeping the scheduling process simple through automated responses to changing conditions.
2Ease of operation
If static slotted appointment systems are used, then scheduling is straightforward, but flexibility to accommodate individual patient needs is reduced
Solution Approach 1:
The system transforms rigid static slots into flexible dynamic time windows. Appointment times are no longer fixed but adjust automatically based on patient needs, queue positions, and provider availability. This maintains ease of operation through automated adaptation while providing the flexibility needed to accommodate individual patient requirements such as extended examination times or priority scheduling.
Solution Approach 2:
The system changes the parameters of appointment scheduling from fixed time slots to variable time windows. By allowing appointment durations and times to change dynamically based on patient needs and real-time conditions, the system maintains scheduling simplicity through automation while achieving the flexibility required for individualized patient care.
3Device complexity
If manual waitlist updates are used, then system complexity is minimized, but patient treatment order becomes inefficient and wait times increase
Solution Approach 1:
The system implements self-service automation where the queue management system automatically monitors patient arrivals, updates waitlists, and coordinates treatment orders without manual intervention. This maintains relatively simple system architecture through automated algorithms while dramatically improving patient treatment efficiency by ensuring optimal sequencing based on real-time conditions such as patient urgency and provider availability.
Solution Approach 2:
The patent replaces manual mechanical processes of waitlist updates with automated digital systems. Instead of administrators manually updating waitlists, the system uses automated software that continuously monitors patient flow and automatically manages treatment sequencing, thereby reducing system complexity through automation while improving productivity through efficient real-time coordination.
4Ease of operation
If fixed timeslots are used for all patients, then scheduling is uniform and simple, but time is wasted when patients require less time and appointments are rushed when more time is needed
Solution Approach 1:
The system applies local quality customization by allowing different appointment durations and scheduling parameters for different patients based on their specific needs. Instead of uniform fixed slots for all patients, the system tailors time allocations to individual patient requirements, thereby reducing time waste from rushed or excessively long appointments while maintaining operational simplicity through automated differentiation.
Solution Approach 2:
The system transforms static uniform timeslots into dynamic variable durations. Appointment lengths automatically adjust based on patient needs, provider expertise, and queue conditions. This maintains scheduling simplicity through automated adaptation while eliminating time waste by ensuring each patient receives appropriate time allocation without rushing or excessive waiting.
Data Source
AI summary
Systems and methods for providing a dynamic medical practice queueing platform via at least one patient user mobile device in operable connection with a network. An application server is in operable communication with the network to host an application program for displaying, via a display module, a virtual patient queue. The application program includes a user interface module for providing access to the virtual patient queue through the display module. A geofencing module determines the location of a user in reference to a geofenced location. A virtual patient queue module determines a time of arrival of a patient using the current location of the patient and positions the patient within a virtual queue.