Remote Patient Assignment System for Urgency-Based Triage
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Solution Overview
Problem
Current patient scheduling methods are inefficient and often rely on human interaction, leading to delays and long queues at medical facilities, particularly during crises like the COVID-19 pandemic, where healthcare systems face unprecedented pressure.
Innovation Solution
A system and method for remote patient assignment that uses a processor to receive scheduling requests, determine estimated service times across multiple medical facilities, and prioritize patients based on urgency, minimizing the sum of expected service time and its tail probability, utilizing a combination of model-based and reinforcement learning approaches to optimize patient distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patient scheduling is based on screening and triaging process after patient enters treatment area, then patients can be properly triaged, but long queues form and patient stay time is prolonged
Solution Approach 1:
The system performs preliminary scheduling and triaging actions before patients arrive at the medical facility. The remote patient assignment system evaluates patient needs, facility capacity, and optimizes assignments in advance, allowing patients to be directed to appropriate facilities before arrival, thereby eliminating long queues and reducing wait times while maintaining proper triaging accuracy
Solution Approach 2:
The patent introduces a remote patient assignment system as an intermediary between patients and medical facilities. This intermediary system processes scheduling requests, evaluates facility capacity, and makes optimal assignments remotely, preventing the formation of queues at facility entrances while ensuring proper triaging through automated evaluation protocols
2Adaptability or versatility
If independent patient scheduling is used across hospitals, then each facility maintains autonomy, but scheduling efficiency is reduced and delays occur
Solution Approach 1:
The patent implements a universal remote patient assignment system that serves multiple medical facilities simultaneously while respecting each facility's autonomy. The system performs multiple functions including receiving scheduling requests, evaluating facility capacity, determining optimal assignments, and coordinating across heterogeneous facilities, thereby improving overall scheduling efficiency without sacrificing individual facility independence
Solution Approach 2:
The system incorporates feedback mechanisms where medical facilities provide real-time information about their capacity and availability, and the remote assignment system uses this feedback to dynamically optimize patient assignments. This feedback loop enables coordinated scheduling across multiple facilities while maintaining their autonomous decision-making capabilities, resolving the contradiction between autonomy and efficiency
3Speed
If patients are assigned to nearest medical facility, then travel time is minimized, but facility overcrowding occurs and service quality deteriorates
Solution Approach 1:
The patent applies local quality by making patient assignment decisions based on local facility conditions such as current capacity, specialized equipment availability, and staff expertise. Rather than uniformly assigning patients to the nearest facility, the system evaluates local characteristics of each facility and matches patients to facilities where they can receive appropriate care, preventing overcrowding while maintaining reasonable travel times
Solution Approach 2:
The system dynamically adjusts patient assignments based on real-time facility capacity and demand conditions. As facility loads change, the assignment algorithm adapts to redistribute patients optimally, preventing overcrowding at any single facility while considering travel time implications. This dynamic approach balances travel speed and service quality by allowing assignments to fluctuate with changing conditions
Data Source
AI summary
The provided systems and methods are designed to account for the requests of multiple patients demanding a form of medical intervention from a medical facility (MF) in their vicinity. Unlike the majority of existing approaches, the provided systems and methods differentiate between patient requests by prioritizing the requests with higher urgency over others that can tolerate more delay. Moreover, the provided systems and methods enjoy lower design complexity since the instantaneous queue length (number of patients) in each medical facility is not necessarily needed in at least some aspects. Instead, in such aspects, only average queue length is involved in taking the dispatch actions for patient requests to medical facilities. The intervention can vary from a routine consultation/meeting with a healthcare service provider to urgent hospital admission.