Dynamic route optimization system within hospitals

Abstract

The invention relates to a dynamic route optimization system within hospitals that calculates the average service time in hospital units using real-time data from the Hospital Information System (HIS) and compares the distance in the queue with waiting times, depending on the patient's location, then calculates the shortest route to the target location and directs the patient to the units accordingly. With this system, the expected waiting times during examinations and consultations are shown to the user, and if another unit has a shorter waiting queue for the next examination during that time interval, the user is advised to go there first.

Description

[0001] DYNAMIC ROUTE OPTIMIZATION SYSTEM WITHIN HOSPITALS

[0002] Technical Field

[0003] The invention relates to an in-hospitals dynamic route optimization system that calculates the average service time within hospital units using real-time data from the Hospital Information System (HIS) and comparing the queue distance with waiting times based on the patient's location, then calculating the shortest route to the target location and directing the patient accordingly to the units. The invention dynamically calculates the expected waiting times during examinations and consultations and, if the order of units to be visited for another examination within that time period is shorter, advises the user to go there first. This information is displayed to the user via a mobile application or online platform.

[0004] Previous Technics

[0005] Today, hospitals have complex organizational systems and structures due to the various units they accommodate. This complexity can be perceived as overwhelming for patients and visitors who are either visiting the hospital for the first time or not using it regularly. Hospitals should direct individuals directly to their destination from the moment they enter the facility and, after completing the intended process, guide them directly to the exit.

[0006] For medical tests requested by doctors in hospitals, patients need to go to relevant units such as ultrasound, blood sampling, or MRI. Patients who need to visit multiple units end up waiting in the hospital for long periods, leading to long queues in these units. The queue problem results in patients experiencing long wait times and forming queues, which in turn leads to patients taking longer to complete treatment and examination processes and inefficient use of hospital staff resources. Additionally, it negatively affects hospital management and the quality of healthcare services.

[0007] The dynamic route optimization system addresses the aforementioned problem by optimizing patient routing to units using various methods such as genetic algorithms and queue theory, thereby reducing waiting times. Real-time data from the Hospital Information System (HIS) will be used to calculate the average service time in units. The system will calculate the shortest route to the target location based on the patient's location, comparing the queue distance and waiting time, and then guide the patient to the units accordingly.

[0008] When a patient receives information during another examination, they can have the opportunity to collect relevant documents, tests, or other necessary information in advance, speeding up the preparation process for another examination. Optimizing queues in units aims to benefit hospital management, staff, and patients by ensuring more effective and efficient healthcare services are provided.

[0009] Related Patents

[0010] US2015100326A1 describes a framework that facilitates healthcare visit management by obtaining information about a planned appointment with a healthcare service provider, tracking the real-time location of a user, and utilizing this information to facilitate a visit to fulfill the appointment. If it is predicted that the user's waiting time during the visit will exceed a predetermined threshold, recommendations for relevant services, products, or entertainment options may be presented to the user through a user device. However, information about the durations and routes of other service options is not provided, nor is there mention of redirecting individuals to different units based on waiting times.

[0011] JP2020176959A discusses calculating recommended routes from a patient's current location to an examination room. However, it does not mention indicating appointment queue times or directing individuals to other units based on these times.

[0012] US8060500B1 obtains the availability of appointments and / or estimated wait times for one or more healthcare providers. Subsequently, this information, along with information about the current appointments and / or estimated office wait times of one or more healthcare providers, is presented to healthcare service consumers.

[0013] CN114927206A aims to solve problems such as the poor experience of doctor visits and patient discomfort during examinations by facilitating the patient's quick location of the examination place and timely completion of the relevant examination, enabling the patient to learn about the progress of the treatment in time. CN110246574A describes an intelligent navigation and diagnosis guidance system that provides navigation for all diagnostic service locations, times, attention items, and diagnosis process navigation, including real-time positioning, hospital indoor route navigation, diagnosis navigation, department office and clinic navigation, medication collection navigation, examination appointment navigation, and report collection navigation.

[0014] The above patents do not mention redirecting patients to other units based on the current location and the distances to the units they are heading to, along with comparing waiting times in queues.

[0015] Description of The Invention

[0016] The invention is a hospital intra-dynamic route optimization system that efficiently directs patients between different units, contributing to the more effective utilization of hospital services and reducing patient waiting times for procedures such as blood sampling, MRI, ultrasound, etc. It aims to decrease queues in hospital units and ensure that patients exit the hospital in minimum time. Its features include:

[0017] - Real-time data integration module integrated with the Hospital Information System (HIS) to obtain instant congestion data from units such as blood sampling, MRI, ultrasound imaging, etc., and redirecting the current data to the dynamic optimization module.

[0018] Indoor mapping module integrated with the hospital's indoor navigation application to calculate distances that users need to travel to reach their destinations and direct relevant information to the dynamic optimization module.

[0019] - Dynamic optimization module operating in the cloud, which calculates the shortest routes between hospital units and patient locations, predicts and manages patient waiting times in units using queue theory, optimizes multiple objectives simultaneously with genetic algorithms, determines the most suitable route combinations, balances multiple objectives, plans the most optimal route using particles representing the locations of patients and units, combines a series of algorithms to continuously optimize routes to adapt to congestion situations or emergency scenarios, and delivers relevant information to patients through a mobile application or online platform. This system aims to enhance the efficiency of hospital services by dynamically optimizing patient routes and minimizing wait times, thereby improving overall patient experience and resource utilization within the hospital.

[0020] Detailed Description of The Invention

[0021] When a patient is directed to multiple units, the average service time will be calculated using congestion data from the Hospital Information System (HIS). The application will dynamically calculate the shortest route algorithmically based on the user's location, then compare the distance between the current location and the destination locations with the queue waiting times using queue theory, and redirect the patient to different units accordingly. For example, if the queue for blood sampling is long, the system will show the expected wait time and if the queue for another examination is shorter within that time frame, it will calculate that the user should go there first. The application, through which the dynamic route optimization system operates, will provide verbal and visual instructions on how the user will reach their destination point on the map.

[0022] Multiple methods will be employed for this system, including Genetic Algorithm, Pareto Optimality, Particle Swarm Optimization, etc. Patient waiting times will be managed by predicting them using queue theory, while multiple objective functions will be optimized using Genetic Algorithm to determine the best route combinations. Pareto optimality will be utilized to simultaneously optimize multiple objective functions to find optimal solutions. Additionally, reinforced learning will continuously optimize and improve routes to adapt to congestion situations or emergency scenarios by combining a series of algorithms. All these methods are encapsulated within the Dynamic Optimization Development module, making the system unique and enabling it to achieve its stated objectives and benefits.

[0023] As the system aims to discharge patients from the hospital as quickly as possible, it will facilitate completing medical examinations and tests with minimal waiting times. Consequently, patient satisfaction will increase, and the stress levels caused by long waits will decrease.

[0024] Due to the large and complex structures of hospitals, patients often face difficulty in navigation. Effective route management will enable patients to reach their desired unit via the shortest route without getting lost. Optimizing queues in units will ensure that patients receive medical interventions and treatments more quickly and punctually.

[0025] Dynamic route optimization will maximize the utilization of hospital units, ensuring efficient utilization of staff and equipment.

[0026] With patients moving without the need for guidance from hospital staff, the efficiency of staff work will increase. Optimized routes will facilitate more effective management of personnel and resources, minimizing resource wastage.

Claims

CLAIMS1.) The invention contributes to more efficient use of hospital services by directing patients efficiently between different units and by reducing patients' waiting times for treatment, thus reducing queues in hospital units such as blood collection, MRI, ultrasound, etc., and ensuring that the patient leaves the hospital in minimum time.- Real-time data integration module that operates in the cloud, integrated with the Hospital Information Management System (HIMS) to receive real-time congestion data from units such as blood collection, MRI, ultrasound imaging, and similar hospital units, and directs current data to the dynamic optimization module.Indoor mapping module that operates in the cloud, integrating with hospital indoor application's route optimization, calculating distances the user needs to travel to reach destination points, and directing relevant information to the dynamic optimization module. the system includes these and,The invention has a dynamic optimization module operates in the cloud, receiving information from other modules in the system to calculate the shortest route between hospital units and patient locations, predict and manage patient waiting times in units using queue theory, optimize multiple objectives simultaneously with genetic algorithms to determine the most suitable route combinations, balance multiple objectives, plan the most optimal route using particles representing the locations of patients and units, combine a series of algorithms to continuously optimize routes to adapt to congestion situations or emergency scenarios, and deliver relevant information to patients through a mobile application or online platform and is characterized by this module and its features.