Method and system for automatically updating patient treatment order

Abstract

The present invention is characterized by including: at least one camera installed at a predetermined position in a patient waiting room to capture an image; a movement detection unit for detecting movement of a patient in the image; a face recognition unit for recognizing the face of the patient in the image and specifying the identity of the patient; a medical treatment queue generation unit for comparing the identity of the patient approaching the camera with medical treatment reservation details so as to automatically update a medical treatment queue position of the patient; and an absence and departure detection unit for comparing the identity of at least one patient in the image captured in real time by the at least one camera with the identity of a patient in the treatment queue to detect a departed patient or comparing the identity of at least one patient in the image captured in real time by the at least one camera with the identify of a patient in the medical treatment reservation details to detect an absent patient.

Description

Method and system for automatically updating patient treatment sequences

[0001] The present invention relates to a method and system for automatically updating a patient treatment order, and more particularly, to a method and system for automatically updating a patient treatment order for automatically registering a patient waiting in a patient waiting room in a treatment queue.

[0002] Recently, hospitals, especially general hospitals, have been undergoing a massive expansion. While this expansion offers the advantage of providing patients with a wider range of high-quality services, it also presents a challenge: managing the large number of patients waiting for treatment and the frequent movement of patients. Furthermore, patients often find themselves having to wait for treatment again because their turn has already passed while they're out for urgent matters like restroom visits or phone calls, creating inconvenience.

[0003] In the past, when a patient registered for treatment at the hospital desk, the patient was automatically registered in the waiting line and a device was used to display the treatment order on a monitor in the patient waiting room. However, this had limitations in that the patient had to register for treatment at the desk and the waiting line could not be updated to reflect the absence / departure of the patient.

[0004] In this regard, Korean Patent No. 10-1916356 discloses a patient recognition waiting system equipped with a visiting patient recognition probability enhancement unit applicable to hospitals. This system recognizes the faces of patients visiting the hospital, receives information about the recognized patient from a database, and automatically places the patient on a waiting list so that they can receive treatment from a specialist in charge. While the aforementioned prior art document allows patients to register in the waiting list through facial recognition without going through a hospital desk, it still fails to reflect patient departures / absences.

[0005] Accordingly, the present invention aims to provide a method and system for automatically updating the patient treatment order by identifying patients who have left / are absent from the patient waiting room and automatically updating the treatment waiting line.

[0006] Accordingly, the present invention aims to provide a method and system for automatically updating the patient treatment order by identifying patients who have left / are absent from a patient waiting room and automatically updating the treatment waiting line.

[0007] In addition, the present invention seeks to automatically update the waiting order of patients currently waiting by comparing the appointment history with one or more patients whose identities are specified.

[0008] In order to achieve the above object, the present invention is characterized by including: one or more cameras installed at a predetermined location in a patient waiting room to capture images; a motion detection unit for detecting movement of a patient in the image; a facial recognition unit for recognizing the face of a patient in the image to identify the patient; a treatment queue generation unit for automatically updating a patient treatment queue by comparing the identity of a patient approaching the camera with a treatment appointment history; and an absence / absence detection unit for detecting a patient who has left the waiting room by comparing the identity of one or more patients in an image captured in real time by the one or more cameras with the identity of a patient in the treatment queue, or detecting an absent patient by comparing the identity of one or more patients in an image captured in real time by the one or more cameras with the identity of a patient in a treatment appointment history.

[0009] Preferably, the treatment queue generation unit can reflect the absent or departing patient detected by the absence detection unit into the treatment queue.

[0010] Preferably, the absence detection unit can request information including the reason for absence / absence and the expected return time from the absent patient or the absent patient.

[0011] Preferably, the treatment queue generation unit may not update the treatment queue if the absence / absence detection unit receives information requested from the departing patient or the absent patient, and if the departure / absence reason is a pre-specified legitimate reason and the expected return time is within the expected waiting time.

[0012] Preferably, the treatment queue generation unit receives information requested by the absence / absence detection unit to a patient who has left or is absent, and if the reason for leaving / absence is a pre-specified legitimate reason, the treatment order of the patient who has left or is absent can be changed to the next order when the treatment order of the patient who has left or is absent returns within the expected return time.

[0013] Preferably, the treatment queue generation unit can automatically update the patient treatment order by receiving information requested by the absence / absence detection unit to a departing patient or an absent patient, and if the departure / absence reason is a pre-specified legitimate reason, and if the departing patient or the absent patient does not return after the expected return time, but the treatment order of the departing patient or the absent patient returns within a preset maximum return time, changing the treatment order of the departing patient or the absent patient to the next order.

[0014] Preferably, the treatment queue generation unit receives information requested by the absence / absence detection unit to the departing patient or the absent patient, and if the departure / absence reason is a pre-specified legitimate reason, if the departing patient or the absent patient does not return within a preset maximum return time, the treatment order of the departing patient or the absent patient can be changed to the last.

[0015] Preferably, if the absence / absence detection unit does not receive the information requested from the departing patient or the absent patient, or if the departure / absence reason is not a pre-specified legitimate reason, the treatment order of the departing patient or the absent patient can be changed to the next order when the treatment order of the departing patient or the absent patient returns within a preset maximum return time.

[0016] Preferably, the treatment queue generation unit can change the treatment order of the departing patient or the absent patient to the last if the absence / absence detection unit does not receive the information requested from the departing patient or the absent patient or if the departing / absent patient does not return within a preset maximum return time.

[0017] Preferably, the system may further include an identity verification unit that outputs a specific identity to a patient who has approached within a certain distance and receives an input as to whether the specific identity is correct for the patient who has approached.

[0018] In addition, the present invention has another feature including the steps of: capturing an image with one or more cameras installed at a certain location in a patient waiting room; detecting the movement of a patient in the image; recognizing the face of the patient in the image to identify the patient; comparing the identity of the patient approaching through the camera with the appointment details to automatically update the patient waiting line; and detecting a patient who has left or is absent from the patient waiting room and reflecting the result in the waiting line.

[0019] The present invention has the advantage of being able to identify patients who have left / are absent and automatically update the treatment queue, thereby providing patients with an accurate treatment queue in real time.

[0020] In addition, the present invention has the advantage of requiring a patient who is absent or has left the hospital to provide the reason for the absence and the expected time of return, and providing a reasonable waiting policy for treatment to a patient who is inevitably absent or has left the hospital based on the reason and the expected time of return.

[0021] Figure 1 shows a configuration diagram of a system for automatically updating a patient treatment order according to an embodiment of the present invention.

[0022] Figure 2 shows a flowchart of registering a patient who has entered a treatment room in a treatment waiting line in a treatment waiting line generation unit according to an embodiment of the present invention.

[0023] FIG. 3 is a flowchart showing a process for selecting an algorithm based on information received from an absent / absent patient in an absence detection unit according to an embodiment of the present invention.

[0024] Figure 4 shows a flowchart of the first algorithm performed in the treatment queue generation unit according to an embodiment of the present invention.

[0025] Figure 5 shows an example of a treatment queue generated by a treatment queue generation unit according to an embodiment of the present invention.

[0026] Figure 6 shows a flowchart of a second algorithm performed in a treatment queue generation unit according to an embodiment of the present invention.

[0027] One or more cameras installed at specific locations within the patient waiting room to capture images;

[0028] A motion detection unit that detects the patient's movement within the image;

[0029] A facial recognition unit that recognizes the patient's face in the above image and identifies the patient;

[0030] A treatment queue generation unit that automatically updates the patient's treatment queue by comparing the patient's identity and treatment appointment details accessed through the above camera; and

[0031] An absence detection unit that detects a patient who has left the clinic by comparing the identity of one or more patients in real-time images captured by one or more cameras with the identity of patients in the treatment waiting line, or detects an absent patient by comparing the identity of one or more patients in real-time images captured by one or more cameras with the identity of patients in the treatment reservation history;

[0032] A system that automatically updates the patient treatment sequence including:

[0033] Hereinafter, the present invention will be described in detail with reference to the contents described in the attached drawings. However, the present invention is not limited or restricted by the exemplary embodiments. The same reference numerals in each drawing indicate components that perform substantially the same functions.

[0034] The purpose and effects of the present invention can be naturally understood or made clearer by the following description, and the purpose and effects of the present invention are not limited solely by the following description. Furthermore, in describing the present invention, if a detailed description of known technologies related to the present invention is deemed to unnecessarily obscure the gist of the present invention, such detailed description will be omitted.

[0035] The terminology used herein is merely used to describe specific embodiments and is not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, it should be understood that the terms "comprise" or "have" indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the description of the invention, but do not preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0036] While terms like "first" and "second" may be used to describe various components, these components should not be limited by these terms. These terms are used solely to distinguish one component from another. For example, without departing from the scope of the present invention, a first component could be referred to as a "second component," and similarly, a second component could also be referred to as a "first component."

[0037] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0038] When interpreting components, even if there is no explicit description, it is interpreted as including the margin of error. When describing temporal relationships, for example, when temporal continuity is described with phrases such as "after," "following," "next to," or "before," this also includes cases where the relationship is not continuous, unless "immediately" or "directly" is used.

[0039] Hereinafter, the technical configuration of the present invention will be described in detail with reference to the attached drawings.

[0040] FIG. 1 illustrates a configuration diagram of a system (100) for automatically updating a patient treatment order according to an embodiment of the present invention. Referring to FIG. 1, the system (100) for automatically updating a patient treatment order may include one or more cameras (110), a motion detection unit (120), a facial recognition unit (130), a treatment queue generation unit (140), an absence detection unit (150), and an identity verification unit (160).

[0041] Previously, nurses would call out specific patients in the waiting room when their turn arrived, and if no one responded, they would call the next patient in line. In this situation, if a patient left their seat during their turn, they would either be moved to the end of the waiting line or, at the hospital's discretion, be treated next. Furthermore, identification numbers, such as resident registration numbers, were double-checked before entering the examination room to prevent other patients from receiving treatment in the wrong place. However, this method was cumbersome and raised concerns about personal information being exposed in public places.

[0042] A system (100) for automatically updating patient treatment sequences can identify absent / departed patients and automatically update the treatment queue, thereby providing patients with accurate treatment queues in real time. The system (100) for automatically updating patient treatment sequences can request absent / departed patients to provide the reason for their absence and their expected return time, and can provide reasonable treatment waiting policies to patients who are inevitably absent / departed based on the reason and expected return time.

[0043] A system (100) for automatically updating a patient treatment order may be equipped with an image sensor such as a camera. RFID (Radio Frequency IDentification) and UWB (Ultra-wideband) sensors can identify a person, but cannot individually identify the identity of multiple people moving at the same time, and cannot identify individual body movements, and each individual must carry an RFID or UWB sensing device. Radar can identify body movements, but cannot individually identify a person. On the other hand, a system (100) for automatically updating a patient treatment order according to an embodiment of the present invention can individually identify the identities of multiple people and their body movements at the same time using an image sensor, and each individual does not need to carry a sensing device.

[0044] The system (100) for automatically updating patient treatment sequences can perform two functions. First, the system (100) for automatically updating patient treatment sequences automatically recognizes the patient's movements and face when the next patient is displayed on a display in the waiting room and approaches the display device. If the facial recognition results indicate that the patient is the patient, the system automatically performs a double-check procedure to verify that the patient's turn is correct by displaying the patient's name and double-check information (such as the resident registration number) from EMR data.

[0045] Next, the system (100) for automatically updating the patient treatment order can automatically identify each individual patient in the waiting room through automatic facial recognition in a patient waiting room situation where multiple patients are entering and exiting at the same time, identify absent / withdrawn patients by comparing them with reservation details in EMR data, and automatically update the waiting line centered on the patients currently waiting.

[0046] A camera (110) can be installed at a specific location within the patient waiting room to capture images. One or more cameras (110) can be installed at a specific location within the patient waiting room. The camera (110) can capture images in real time and provide the captured images to a motion detection unit (120) or a facial recognition unit (130). The camera (110) can be installed inside or outside the patient waiting room to capture images of patients waiting for treatment or patients leaving the treatment room.

[0047] The motion detection unit (120) can detect the patient's movement within the video. Through automatic motion recognition, the motion detection unit (120) can detect whether the patient is approaching, moving away, or stationary from the camera (110). The motion detection unit (120) can detect the direction of movement of the patient within the video. The motion detection unit (120) can detect whether the patient is entering or leaving the examination room.

[0048] The motion detection unit (120) can detect the patient's movements by recognizing the patient's actions in real time. Specifically, the motion detection unit (120) can detect the patient's movements using artificial intelligence.

[0049] The facial recognition unit (130) can identify a patient by recognizing the patient's face in the image. The facial recognition unit (130) can identify the patient by comparing the patient's face recognized in the image with patient information in the database. The facial recognition unit (130) can identify the face of any person, not just the patient in the image. For example, the facial recognition unit (130) can identify the identities of patients, general visitors, medical staff, and other individuals.

[0050] The facial recognition unit (130) can recognize the patient's face in real time and identify the patient. Specifically, the facial recognition unit (130) can detect the patient's movement using artificial intelligence. The facial recognition unit (130) can provide high accuracy (over 99.9%) that is robust to time and environmental changes. The facial recognition unit (130) can provide a fast and easy identity verification function through high-speed / high-efficiency facial recognition. The facial recognition unit (130) provides a powerful anti-spoofing function to distinguish whether the face being filmed is a real person or a fake video. The motion detection unit (120) and the facial recognition unit (130) can utilize existing video devices such as CCTVs installed in hospitals.

[0051] The AI ​​for motion detection and facial recognition mentioned above can be based on a Deep Neural Network (DNN) or a Convolutional Neural Network (CNN). A convolutional neural network (CNN) is a type of deep learning model inspired by the structure of the visual cortex of animals, designed to process data with grid patterns, such as images. A convolutional neural network typically includes convolutional layers, pooling layers, and fully connected layers. Convolutional and pooling layers can be repeated within a neural network, and input data can be transformed into output through these layers. Convolutional layers utilize a kernel (or mask) to extract features. The element-wise product between each element of the kernel and the input value is calculated at each location and summed to obtain the output value, which is called a feature map. This process can be repeated by applying multiple kernels to form an arbitrary number of feature maps. In a convolutional neural network, convolutional and pooling layers perform feature extraction, while fully connected layers map the extracted features to the final output, such as classification operations.

[0052] Convolutional neural networks, such as neural networks, can be trained to minimize output errors. Separate from the forward propagation process, which extracts values ​​from the input layer to the output layer, backpropagation occurs within the neural network, calculating the error between the input training data and the corresponding neural network output values ​​and updating the weights of the nodes in each layer to reduce this error. The training process in convolutional neural networks can be summarized as finding the kernel that extracts the output values ​​with the lowest error based on the given training data. The kernel is the only parameter that is automatically learned during the training of the convolutional layer. On the other hand, in convolutional neural networks, kernel size, number of kernels, padding, etc. are hyperparameters that must be set before the training process begins. Therefore, convolutional neural network models can be distinguished based on the kernel size, number of kernels, and number of convolutional and pooling layers.

[0053] The treatment queue generation unit (140) can automatically update the patient's treatment queue by comparing the patient's identity and treatment reservation details when approaching through the camera (110). Typically, patients enter the hospital and register for treatment through the desk or the administration office, or through a kiosk. This method can make the interior of the treatment waiting room crowded when there are many patients, and a situation may arise where a patient who arrived earlier but registered late receives treatment later than a later patient. The treatment queue generation unit (140) according to an embodiment of the present invention can solve the conventional problem by automatically registering a patient in the treatment queue if the patient is identified through the camera (110) filming the interior or exterior of the treatment waiting room and has a treatment reservation.

[0054] The treatment queue generation unit (140) can input the identification information of an identified patient and check whether there is a treatment appointment history at the time of input. If there is a treatment appointment history, the treatment queue generation unit (140) can automatically register the patient in the treatment queue. If there is no treatment appointment history, the treatment queue generation unit (140) can notify the patient that there is no treatment appointment history through text message, email, application, speaker, or display device in the patient waiting room. If there is no treatment appointment history, the treatment queue generation unit (140) can automatically register the patient for treatment at a time when there is no appointment history.

[0055] FIG. 2 is a flowchart illustrating a process for registering a patient who has entered a treatment room in a treatment queue in a treatment queue generation unit (140) according to an embodiment of the present invention. Referring to FIG. 2, first, the treatment queue generation unit (140) compares the identity of the patient identified by the facial recognition unit (130) with the treatment reservation details existing in the EMR data (S110). Next, it is checked whether there is a treatment reservation details reserved with the patient's identity (S120). At this time, if there is no treatment reservation details, the process returns to the beginning, and if there is a treatment reservation details, it is checked whether the identified patient is the first patient to enter the hospital on that day (S130). If the patient is the first patient to enter, the treatment queue generation unit (140) registers the patient in the treatment queue (S140), and if the patient has returned after leaving / being absent, it processes the patient according to the departure / absence patient policy to be described below (S150).

[0056] The treatment queue generation unit (140) can reflect the patients who have left or are absent detected by the absence detection unit (150) in the treatment queue. The treatment queue generation unit (140) can classify the patients who have left or are absent based on whether they respond to information requests and whether the reasons for their departure or absence are justified, according to an algorithm described below. The treatment queue generation unit (140) can update the treatment queue in different ways depending on the classified patients who have left or are absent.

[0057] FIG. 3 is a flowchart illustrating a method for selecting an algorithm according to information received from an absent / absent patient by an absence / absence detection unit (150) according to an embodiment of the present invention. Referring to FIG. 3, first, the treatment queue generation unit (140) can receive information about a patient who has left the treatment waiting room or is absent from the absence / absence detection unit (150) (S210). When an absent / absent patient is identified, the treatment queue generation unit (140) can request information about the reason for the absence / absence and the expected return time according to the reason for the absence / absence from the absent / absent patient via text message, email, application, etc. (S220).

[0058] Next, the treatment queue generation unit (140) checks whether the information requested from the absent / absent patient has been received (S230), and if the requested information has been received, it checks whether the reason for the absence / absence is justified (S240). The treatment queue generation unit (140) receives the information requested from the absent / absent patient, and if the reason for the absence / absence is justified, it performs the first algorithm (S250). The treatment queue generation unit (140) performs the second algorithm (S260) if the information requested from the absent / absent patient has not been received, or if the information requested from the absent / absent patient has been received but the reason for the absence / absence is not justified.

[0059] Here, a legitimate reason means a reason such as a bathroom or an emergency, and a legitimate reason can be determined in advance.

[0060] FIG. 4 is a flowchart of a first algorithm performed in a treatment queue generation unit (140) according to an embodiment of the present invention. Referring to FIG. 4, when the first algorithm is performed (S250), the treatment queue generation unit (140) first checks whether the current time is within the expected return time transmitted by the absent / absent patient (S251). If the current time is within the expected return time, the treatment queue generation unit (140) checks whether the absent / absent patient has returned (S252). If the absent / absent patient has returned, the treatment queue generation unit (140) does not update the treatment queue (S253). If the absent / absent patient has not returned, the treatment queue generation unit (140) checks whether the treatment turn of the absent / absent patient has arrived (S254). The treatment queue generation unit (140) does not update the treatment queue if the treatment order has not arrived (S253), and changes the treatment order to the next order if the treatment order has arrived (S255).

[0061] The treatment queue generation unit (140) verifies whether the current time exceeds the expected return time and whether it is within the preset maximum return time (S256). If it is within the maximum return time, the treatment queue generation unit (140) changes the treatment order to the next order (S255). If it exceeds the maximum return time, the treatment order is changed to the last order (S257).

[0062] Here, the expected return time can refer to a user-specified time or an expected wait time. If the expected return time is an expected wait time, it can be calculated by multiplying the average treatment time by the number of patients in line before the absent / dropped patient.

[0063] That is, the treatment queue generation unit (140) receives information requested by the absence / absence detection unit (150) for a patient who has left or is absent, and if the reason for leaving / absence is a pre-specified legitimate reason and the expected return time is within the expected waiting time, the treatment queue may not be updated.

[0064] The treatment queue generation unit (140) receives the information requested by the absence / absence detection unit to the patient who has left or is absent, and if the reason for the departure / absence is a pre-specified legitimate reason, when the treatment turn of the patient who has left or is absent returns within the expected return time, the treatment queue generation unit (140) can change the treatment turn of the patient who has left or is absent to the next turn. The treatment queue generation unit (140) can repeat this process until the absent / absent patient returns.

[0065] The treatment queue generation unit (140) receives the information requested by the absence / absence detection unit (150) to a patient who has left or is absent, and if the reason for the leave / absence is a pre-specified legitimate reason, and if the patient who has left or is absent does not return after the expected return time, but the turn for the treatment of the patient who has left or is absent returns within a preset maximum return time, the treatment order of the patient who has left or is absent can be changed to the next turn. Here, the maximum return time may be a time preset by hospital regulations (waiting room patient management rules, etc.).

[0066] The treatment queue generation unit (140) receives information requested by the absence / absence detection unit (150) regarding a patient who has left or is absent, and if the reason for the leave / absence is a pre-specified legitimate reason, the treatment order of the left or absent patient can be changed to the last if the left or absent patient does not return within the set maximum return time. The treatment queue generation unit (140) can repeat this process until the left or absent patient returns.

[0067] FIG. 5 illustrates an example of a waiting line generated by a waiting line generation unit (140) according to an embodiment of the present invention. Referring to FIG. 5, one patient (Park Chung-hyun) is undergoing a vision test in the optometry room, and four patients (Kim Dae-myung, Lee Eun-hye, Hong Gil-dong, Lee Ji-yeon) are waiting in the waiting room. At this time, if patient Kim Dae-myung sends information after leaving / being absent, and if the reason for leaving / being absent is a pre-specified legitimate reason, the waiting line is changed to the next waiting line, as in C1, when the waiting line for treatment returns. This process is repeated until patient Kim Dae-myung returns. If patient Kim Dae-myung does not return even after exceeding the maximum return time, the waiting line for treatment is changed to the last line, as in C2. Similarly, this process is repeated until patient Kim Dae-myung returns.

[0068] FIG. 6 is a flowchart of a second algorithm performed in a treatment queue generation unit (140) according to an embodiment of the present invention. Referring to FIG. 6, when the second algorithm is performed (S260), the treatment queue generation unit (140) can first check whether the current time is within the maximum return time (S261). If the current time is within the maximum return time, the treatment queue generation unit (140) can check whether the turn of an absent / absent patient has arrived (S262). If the turn of an absent / absent patient has not arrived, the treatment queue generation unit (140) changes the treatment order to the next order (S263). This process can be repeated until the absent / absent patient returns. If the turn of an absent / absent patient has arrived, the treatment queue generation unit (140) does not update the treatment queue (S264). The treatment queue generation unit (140) changes the treatment order of the departing / absent patient to the last order when the current time exceeds the maximum return time.

[0069] That is, if the absence / absence detection unit (150) does not receive the information requested from the patient who has left or is absent, or if the reason for the leave / absence is not a pre-specified legitimate reason, and if it is within the preset maximum return time, the treatment order of the patient who has left or is absent can be changed to the next order when the treatment order of the patient who has left or is absent returns.

[0070] If the absence / absence detection unit (150) does not receive the information requested from the patient who has left or is absent, or if the reason for the leave / absence is not a pre-specified legitimate reason, the treatment queue generation unit (140) can change the treatment order of the left or absent patient to the last if the left or absent patient does not return within the preset maximum return time.

[0071] The absence detection unit (150) can detect an absent patient by comparing the identity of one or more patients in an image captured in real time by one or more cameras (110) with the identity of a patient in a waiting line for treatment, or can detect an absent patient by comparing the identity of one or more patients in an image captured in real time by one or more cameras with the identity of a patient in a treatment reservation history.

[0072] The absence / absence detection unit (150) can request information including the reason for the absence / absence and the expected return time from the patient who has left or is absent. If the requested information is transmitted from the patient who has left or is absent, the absence / absence detection unit (150) can transmit it to the treatment queue generation unit (140).

[0073] The identity verification unit (160) can output a specific identity to a patient who has approached within a certain distance and receive input on whether the specific identity of the patient who has approached is correct.

[0074] Another embodiment of the present invention, a method for automatically updating a patient treatment order, is described below.

[0075] A method for automatically updating a patient treatment order may include a step of capturing an image with one or more cameras installed at a certain location in a patient waiting room, a step of detecting the movement of a patient in the image, a step of recognizing the face of a patient in the image to identify the patient, a step of automatically updating a patient treatment queue by comparing the identity of a patient approaching through the camera with treatment appointment details, and a step of detecting a patient who has left or is absent from the patient waiting room and reflecting the detected patient in the treatment queue.

[0076] The step of capturing images with one or more cameras installed at a certain location in the patient waiting room refers to an operation performed by the aforementioned camera (110).

[0077] The step of detecting the patient's movement in the image refers to the operation performed in the aforementioned motion detection unit (120).

[0078] The step of recognizing the patient's face in the image and identifying the patient means the operation performed in the aforementioned facial recognition unit (130).

[0079] The step of automatically updating the patient's treatment queue by comparing the patient's identity and treatment appointment details accessed by the camera refers to the operation performed in the treatment queue generation unit (140) described above.

[0080] The step of detecting a patient who has left or is absent from the patient waiting room and reflecting it in the above-mentioned waiting line refers to an operation performed in the waiting line generation unit (140) and the absence detection unit (150) described above.

[0081] A method for automatically updating patient care order may further include a step of outputting a specific identity to a patient who approaches within a certain distance and receiving input regarding whether the specific identity is correct. This step refers to the operation performed by the aforementioned identity verification unit (160).

[0082] While the present invention has been described in detail through representative examples above, those skilled in the art will understand that various modifications to the above-described embodiments are possible without departing from the scope of the present invention. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be defined not only by the claims described below but also by all changes or modifications derived from the claims and equivalent concepts.

[0083] Accordingly, the present invention aims to provide a method and system for automatically updating the patient treatment order by identifying patients who have left / are absent from a patient waiting room and automatically updating the treatment waiting line.

[0084] In addition, the present invention seeks to automatically update the waiting order of patients currently waiting by comparing the appointment history with one or more patients whose identities are specified.

Claims

1. One or more cameras installed at a specific location in the patient waiting room to capture images; A motion detection unit that detects the patient's movement within the image; A facial recognition unit that recognizes the patient's face in the above image and identifies the patient; A treatment queue generation unit that automatically updates the patient's treatment queue by comparing the patient's identity and treatment appointment details accessed through the above camera; and An absence detection unit that detects a patient who has left the clinic by comparing the identity of one or more patients in real-time images captured by one or more cameras with the identity of patients in the treatment waiting line, or detects an absent patient by comparing the identity of one or more patients in real-time images captured by one or more cameras with the identity of patients in the treatment reservation history; A system that automatically updates the patient treatment sequence including:

2. In paragraph 1, The above treatment waiting line generation unit is, A system for automatically updating the patient treatment order, characterized in that the absent or departing patient detected by the above absence detection unit is reflected in the treatment waiting list.

3. In paragraph 1, The above absence detection unit is, A system for automatically updating a patient care order, characterized by requesting information including the reason for leaving / absenteeism and the expected time of return from a departing or absent patient.

4. In paragraph 3, The above treatment waiting line generation unit is, If the above absence detection unit receives information requested from a departing patient or an absent patient, and the reason for departure / absence is a legitimate reason as specified, A system for automatically updating a patient treatment order, characterized in that the treatment waiting line is not updated if the expected return time is within the expected waiting time.

5. In paragraph 3, The above treatment waiting line generation unit is, If the above absence detection unit receives information requested from a departing patient or an absent patient, and the reason for departure / absence is a legitimate reason as specified, A system for automatically updating the patient treatment order, characterized in that when the treatment order of the departed patient or the absent patient returns within the expected return time, the treatment order of the departed patient or the absent patient is changed to the next order.

6. In paragraph 3, The above treatment waiting line generation unit is, If the above absence detection unit receives information requested from a departing patient or an absent patient, and the reason for departure / absence is a legitimate reason as specified, A system for automatically updating the patient treatment order, characterized in that when the patient who has left or the absent patient has not returned beyond the expected return time, but the treatment order of the patient who has left or the absent patient returns within a preset maximum return time, the treatment order of the patient who has left or the absent patient is changed to the next order.

7. In paragraph 3, The above treatment waiting line generation unit is, If the above absence detection unit receives information requested from a departing patient or an absent patient, and the reason for departure / absence is a legitimate reason as specified, A system for automatically updating a patient treatment order, characterized in that if the patient who has left or the absent patient does not return within a preset maximum return time, the treatment order of the patient who has left or the absent patient is changed to the last.

8. In paragraph 3, The above treatment waiting line generation unit is, If the above absence detection unit does not receive the information requested from the patient who has left or is absent, or if the reason for the departure / absence is not a legitimate reason as specified above, A system for automatically updating a patient treatment order, characterized in that when the treatment order of the departed patient or the absent patient returns within a preset maximum return time, the treatment order of the departed patient or the absent patient is changed to the next order.

9. In paragraph 3, The above treatment waiting line generation unit is, If the above absence detection unit does not receive the information requested from the patient who has left or is absent, or if the reason for the departure / absence is not a legitimate reason as specified above, A system for automatically updating a patient treatment order, characterized in that if the patient who has left or the absent patient does not return within a preset maximum return time, the treatment order of the patient who has left or the absent patient is changed to the last.

10. In paragraph 1, An identity verification unit that outputs a specific identity to a patient who approaches within a certain distance and receives an input as to whether the specific identity is correct for the patient who approaches; A system that automatically updates the patient care order including more.

11. A step of recording images using one or more cameras installed at a certain location in the patient waiting room; A step of detecting the patient's movement within the image; A step of recognizing the patient's face in the above image to identify the patient; A step of automatically updating the patient's treatment queue by comparing the patient's identity and treatment appointment details accessed through the above camera; and A step of detecting a patient who has left or is absent from the patient waiting room and reflecting it in the treatment waiting line; A method for automatically updating a patient care sequence including:

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