Oral advisor system and recall information generation method

Abstract

To enable appropriate questioning of patients after their examination, tailored to their individual circumstances. [Solution] A server 1 according to one aspect of the present invention includes a recall AI 42 that includes a learning model that has learned the cases of dental patients; a prompt creation unit 412 that generates a recall prompt d34 for generating recall information d35, which is information prompting the patient to make an appointment to visit the clinic, based on information that includes at least the patient's attribute information and information about the examination performed on the patient, and outputs it to the recall AI 42; and a data input / output unit 311 that transmits the recall information d35 generated in the recall AI 42 based on the recall prompt d34 to a mobile terminal 2 operated by the patient.

Description

Technical Field

[0001] The present invention relates to an oral advisor system and a recall information generation method.

Background Art

[0002] Conventionally, a medical examination management system for prompting patients to undergo the next medical examination after visiting a medical institution has been known. For example, Patent Document 1 discloses a medical examination management system including a storage unit and a control device that stores in the storage unit the second data indicating the medical examination date corresponding to the patient in association with the first data for identifying the patient, and the third data indicating any one of the period until the next medical examination determined by the doctor, the scheduled date of the next medical examination, and the reservation date. The control device described in Patent Document 1 executes a process for sending a reminder for prompting a medical examination to a patient when the scheduled medical examination date calculated from the period until the next medical examination indicated by the third data approaches within a predetermined number of days. According to the technique described in Patent Document 1, even when a clearly determined reservation date has not been set in advance, it is possible to timely remind the patient.

Prior Art Documents

[0003] [[ID=...]] [[ID=...]]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, the technology described in Patent Document 1 notifies patients who wish to receive reminders of their next scheduled appointment date, etc., but does not describe how to send recall notices to patients who do not wish to receive reminders. Conventionally, it has been practiced to send patients a standardized recall message urging them to come in for their next appointment, but the content of these recall messages is generalized and does not reflect the details of the treatment performed by the dentist, etc. Therefore, patients who receive such messages often do not take the content of the message personally and tend to just read the message and leave it at that. In other words, it often does not lead to the action of making a follow-up appointment. As a result, patients only make an appointment for a follow-up visit when problems such as "pain" or "odor" occur, or they come to the clinic without an appointment if their symptoms are severe.

[0005] This invention has been made in consideration of the above circumstances, and its objective is to enable the automatic generation of recall texts according to a patient's treatment history. [Means for solving the problem]

[0006] An oral advisor system according to one aspect of the present invention comprises: a recall AI including a learning model that has learned cases of dental patients; a recall information creation instruction unit that generates a recall information creation instruction for generating recall information, which is information that prompts the patient to make an appointment to visit the clinic, based on information that includes at least the patient's attribute information and information about the examination performed on the patient, and outputs the recall information creation instruction to the recall AI; and a recall information input / output unit that transmits the recall information generated by the recall AI based on the recall information creation instruction to a patient operation terminal device operated by the patient. [Effects of the Invention]

[0007] According to at least one aspect of the present invention, recall messages can be automatically generated according to the patient's treatment history. Other issues, configurations, and effects not mentioned above will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0008] [Figure 1] This figure shows a schematic configuration example of an oral advisor system according to one embodiment of the present invention. [Figure 2] This is a block diagram showing examples of computer configurations, which are hardware components of a server, mobile terminal, tablet terminal, and terminal device, according to one embodiment of the present invention. [Figure 3] This diagram shows the flow of processing in a dental clinic according to one embodiment of the present invention, and the correspondence between this flow and the processing performed by each functional unit of the Oral Advisor System. [Figure 4] This flowchart shows an example of the procedure for processing a medical questionnaire at the time of booking by the medical questionnaire function unit at the time of booking according to one embodiment of the present invention. [Figure 5] This figure shows an example of the configuration of reservation information according to one embodiment of the present invention. [Figure 6] This figure shows an example of the configuration of the appointment-time medical interview prompt according to one embodiment of the present invention. [Figure 7] This figure shows an example of the configuration of the medical questionnaire information used when making a reservation, according to one embodiment of the present invention. [Figure 8] This figure shows an example of the configuration of a reservation screen displayed on a mobile device according to one embodiment of the present invention. [Figure 9] This figure shows an example configuration of a reservation database related to one embodiment of the present invention. [Figure 10] This flowchart shows an example of the procedure for guidance support processing by the guidance support function unit according to one embodiment of the present invention. [Figure 11] This figure shows an example of the configuration of visual inspection result information related to one embodiment of the present invention. [Figure 12] This figure shows an example of the configuration of medical record database registration information related to one embodiment of the present invention. [Figure 13] This figure shows an example configuration of a guidance support prompt related to one embodiment of the present invention. [Figure 14]It is a diagram showing a configuration example of guidance support information according to an embodiment of the present invention. [Figure 15] It is a diagram showing a configuration example of medical record information according to an embodiment of the present invention. [Figure 16] It is a diagram showing a configuration example of a business record screen according to an embodiment of the present invention. [Figure 17] It is a diagram showing a configuration example of a screen of an SNS displayed on a mobile terminal according to an embodiment of the present invention. [Figure 18] It is a flowchart showing an example of the procedure of aftercare processing by an aftercare function unit according to an embodiment of the present invention. [Figure 19] It is a diagram showing a configuration example of medical record information according to an embodiment of the present invention. [Figure 20] It is a diagram showing a configuration example of an aftercare prompt according to an embodiment of the present invention. [Figure 21] It is a diagram showing a configuration example of aftercare interview information according to an embodiment of the present invention. [Figure 22] [[ID=2))It is a diagram showing a configuration example of aftercare interview response information according to an embodiment of the present invention. [Figure 23] It is a diagram showing a configuration example of aftercare information according to an embodiment of the present invention. [Figure 24] It is a diagram showing a configuration example of an aftercare interview screen when an aftercare message according to an embodiment of the present invention is composed of an email. [Figure 25] It is a diagram showing a configuration example of an aftercare interview screen when an aftercare message according to an embodiment of the present invention is transmitted via an SNS. [Figure 26] It is a flowchart showing an example of the procedure of recall processing by a recall function unit according to an embodiment of the present invention. <000;096> [Figure 27] It is a diagram showing a configuration example of medical record information according to an embodiment of the present invention. [Figure 28] It is a diagram showing a configuration example of aftercare information according to an embodiment of the present invention. [Figure 29]This figure shows an example of the configuration of a recall prompt according to one embodiment of the present invention. [Figure 30] This figure shows an example of the structure of recall information related to one embodiment of the present invention. [Figure 31] This figure shows an example of the configuration of a recall screen when a recall message according to one embodiment of the present invention is sent via SNS. [Figure 32] This figure shows a schematic configuration example of an oral advisor system according to a modified version of the present invention. [Figure 33] This figure shows an example of the configuration of the reservation-time medical interview AI resume database according to a modified version of the present invention. [Figure 34] This figure shows an example of the configuration of the guidance support AI resume database according to a modified version of the present invention. [Figure 35] This figure shows an example configuration of the Aftercare AI Resume DB according to a modified version of the present invention. [Figure 36] This figure shows an example of the configuration of a recall AI resume database according to a modified version of the present invention. [Figure 37] This flowchart shows an example of the procedure for saving reservation-time medical interview information by the reservation-time medical interview function unit according to a modified version of the present invention. [Figure 38] This flowchart shows an example of the procedure for reading reservation-time medical interview information by the reservation-time medical interview function unit according to a modified version of the present invention. [Figure 39] This flowchart shows an example of the procedure for saving guidance support information by the guidance support function unit according to a modified version of the present invention. [Figure 40] This flowchart shows an example of the procedure for reading guidance support information by the guidance support function unit according to a modified version of the present invention. [Figure 41] This flowchart shows an example of the procedure for saving aftercare information by the aftercare function unit according to a modified version of the present invention. [Figure 42] This flowchart shows an example of the procedure for reading aftercare information by the aftercare function unit according to a modified version of the present invention. [Figure 43]This flowchart shows an example of the procedure for storing recall information by the recall function unit according to a modified version of the present invention. [Figure 44] This flowchart shows an example of the procedure for reading recall information by the recall function unit according to a modified version of the present invention. [Modes for carrying out the invention]

[0009] Hereinafter, examples of embodiments for carrying out the present invention (hereinafter referred to as "embodiments") will be described with reference to the accompanying drawings. Various numerical values ​​and other figures in the embodiments of the present invention are merely illustrative, and the present invention is not limited to the embodiments described below. Furthermore, in this specification and drawings, the same reference numerals will be used for identical components or components having substantially the same function, and redundant explanations will be omitted.

[0010] <Outline of the Oral Advisor System> First, with reference to Figure 1, the configuration of the oral advisor system 100 according to one embodiment of the present invention will be described. Figure 1 is a diagram showing a schematic example of the configuration of the oral advisor system 100.

[0011] As shown in Figure 1, the oral advisor system 100 includes a server 1, a mobile terminal 2, a tablet terminal 3, and a terminal device 4. Mobile terminal 2 (an example of a patient-operated terminal device) is a terminal device operated by patient U1 using the dental clinic, and is composed of, for example, a smartphone or mobile phone terminal. Note that the terminal device operated by patient U1 is not limited to a mobile terminal. Instead of a mobile terminal, a tablet terminal or a PC (Personal Computer) may be used.

[0012] Tablet device 3 is a tablet-type terminal device operated by dental hygienist U2 or the like. Note that the terminal device operated by dental hygienist U2 is not limited to a tablet device; it may also be a mobile device or the like. Terminal device 4 (an example of a dental operator's terminal device) is composed of, for example, a PC and is operated by a dentist U3 or the like. Server 1, mobile terminal 2, tablet terminal 3, and terminal device 4 are each connected to each other via a network (not shown) that enables communication.

[0013] [server] Server 1 is installed, for example, in a cloud environment, and has a reservation-time medical interview function unit 10, a guidance support function unit 20, an aftercare function unit 30, and a recall function unit 40. Server 1 also has a reservation database 51, a medical record database 52, and an aftercare database 53.

[0014] The appointment-time medical interview function unit 10 performs appointment-time (pre-) medical interview processing. The appointment-time medical interview processing is the process of registering the patient U1's answers to the medical interview at the time of appointment scheduling in the appointment DB 51. The medical interview with patient U1 is provided to patient U1's mobile terminal 2 as appointment-time medical interview information d3 via the website screen, email, or SNS. The answers from patient U1 are sent from patient U1's mobile terminal 2 to the server 1 as appointment-time medical interview answer information d4 via the website screen, email, or SNS. For an example of the structure of the appointment-time medical questionnaire information d3, please refer to Figure 7 and see the following explanation.

[0015] The instruction support function unit 20 performs instruction support processing. This processing generates instruction support information d13 based on the appointment-time medical interview information d3. The instruction support information d13 is information about the content of instruction that dental hygienist U2, who provides instruction to patient U1 who has come to the clinic, will refer to. The instruction support function unit 20 then provides the generated instruction support information d13 to the tablet terminal 3 operated by dental hygienist U2 via a website screen, email, or SNS. An example of the configuration of instruction support information d13 will be described later with reference to Figure 14. In addition, when the content of the treatment performed by dentist U3 is transmitted from the terminal device 4, the instruction support function unit 20 registers the instruction support information d13 and the content of the treatment in the medical record DB 52. The instruction support function unit 20 also transmits the instruction support information d13 to patient U1's mobile terminal 2.

[0016] The aftercare function unit 30 performs aftercare processing. Aftercare processing is the process of registering the answers to the post-examination interview (hereinafter also referred to as "post-examination interview") conducted based on the examination details of patient U1 stored in the medical record DB 52 into the aftercare DB 53. Specifically, "post-examination" refers to both the post-examination period when only an examination is performed and no treatment (procedure) is performed, and the post-treatment period when treatment is performed after an examination. The interview with patient U1 is provided periodically to patient U1's mobile terminal 2 as aftercare interview information d23 via a website screen, email, or SNS. The timing of the provision of aftercare interview information d23 is set by the aftercare AI 32, which will be described later. The aftercare AI 32 determines the optimal timing within the period from the end of the examination to the start of the next examination and sets that timing as the timing for providing aftercare interview information d23. The answers from patient U1 are sent from patient U1's mobile terminal 2 to the server 1 as aftercare interview response information d24 via a website screen, email, or SNS. An example of the structure of aftercare questionnaire information d23 will be described later with reference to Figure 21, and an example of the structure of aftercare questionnaire response information d24 will be described later with reference to Figure 22.

[0017] The recall function unit 40 performs a recall process. The recall process involves sending recall information d35, generated by the recall function unit 40 to prompt the patient to make an appointment for the next consultation, to the mobile terminal 2 operated by the patient U1. An example of the configuration of the recall information d35 will be described later with reference to Figure 30.

[0018] (Reservation-based medical questionnaire function) The appointment scheduling function unit 10 includes an appointment creation unit 11 and an appointment scheduling AI (Artificial Intelligence) 12. The reservation creation unit 11 includes a data input / output unit 111, a prompt creation unit 112, and a DB writing unit 113.

[0019] The data input / output unit 111 controls the operation of sending and receiving various data between it and the patient U1's mobile terminal 2. Specifically, the data input / output unit 111 receives the reservation information d1 transmitted from the mobile terminal 2 and outputs it to the prompt creation unit 112. The reservation information d1 consists of information such as the patient U1's name and date of birth, the date and time of visit, and the reason for the visit. An example of the configuration of the reservation information d1 will be described later with reference to Figure 5. The data input / output unit 111 also transmits the reservation questionnaire information d3, generated by the reservation questionnaire AI 12, to the patient U1's mobile terminal 2.

[0020] The prompt creation unit 112 (an example of a reservation questionnaire creation instruction unit) generates a reservation questionnaire prompt d2 based on the reservation information d1 transmitted from the mobile terminal 2 received by the data input / output unit 111. The prompt creation unit 112 then outputs the generated reservation questionnaire prompt d2 to the reservation questionnaire AI 12. An example of the configuration of the reservation questionnaire prompt d2 will be described later with reference to Figure 6.

[0021] The appointment scheduling AI12 is composed of, for example, a Large Language Model (LLM). An LLM is a type of text generation AI, a language model (learned model) that has learned from patient cases. LLMs have the ability to perform advanced natural language processing tasks (text generation, translation, summarization, question answering, etc.).

[0022] The appointment questionnaire AI 12 creates appointment questionnaire information d3 corresponding to patient U1 based on the appointment questionnaire prompt d2 input from the prompt creation unit 112, and outputs the created appointment questionnaire information d3 to the appointment creation unit 11.

[0023] Furthermore, the appointment scheduling AI12 may be composed of a deep learning model (hereinafter also simply referred to as the "learning model") that has learned from past consultation cases (clinical data). The learning model that has learned from past consultation cases can be composed of, for example, a neural network of a multi-class classification model, a learning model employing the random forest algorithm, or a finely tuned LLM.

[0024] The DB writing unit 113 writes reservation information based on reservation information d1, and reservation questionnaire response information d4, to the reservation DB 51. The reservation DB51 is a database that stores the reservation information d1 and the reservation questionnaire response information d4 for patient U1. The configuration of the reservation DB51 will be described later with reference to Figure 9.

[0025] (Instructional Support Department) The instruction support function unit 20 includes a medical record creation unit 21 and an instruction support AI 22. The medical record creation unit 21 includes a data input / output unit 211, a prompt creation unit 212, and a DB writing unit 213.

[0026] The data input / output unit 211 controls the transmission and reception of various data between the patient U1's mobile terminal 2 and the dental hygienist U2's tablet terminal 3. Specifically, the data input / output unit 211 outputs the visual examination result information d11 transmitted from the tablet terminal 3 to the prompt creation unit 212. The visual examination result information d11 is information indicating the content of the visual examination performed by dental hygienist U2 based on the guidance support information d13. The data input / output unit 211 also transmits the guidance support information d13, generated by the guidance support AI 22, to dental hygienist U2's tablet terminal 3. Furthermore, after dental hygienist U2 has provided guidance based on the guidance support information d13, the data input / output unit 211 transmits the guidance support information d13 to patient U1's mobile terminal 2.

[0027] The prompt generation unit 212 (an example of a guidance support information generation instruction unit) generates a guidance support prompt d12 based on the visual examination result information d11 transmitted from the dental hygienist U2's tablet terminal 3. An example of the configuration of the visual examination result information d11 will be described later with reference to Figure 11, and an example of the configuration of the guidance support prompt d12 will be described later with reference to Figure 13. The generated guidance support prompt d12 is then input to the guidance support AI 22.

[0028] The guidance support AI 22 is composed of, for example, a large-scale language model. Based on the guidance support prompts d12 input from the prompt creation unit 212, the guidance support AI 22 creates guidance support information d13 corresponding to each patient U1, and outputs the created guidance support information d13 to the medical record creation unit 21. An example of the configuration of the guidance support information d13 will be described later with reference to Figure 14.

[0029] Furthermore, the guidance support AI22 may be composed of a deep learning model (learning model) that has learned from past medical cases. The learning model that has learned from past medical cases can be composed of, for example, a neural network of a multi-class classification model, a learning model employing the Random Forest algorithm, or a finely tuned LLM. The DB writing unit 213 writes the guidance support information d13 generated by the guidance support AI 22 to the medical record DB 52. Although not shown in Figure 1, the medical record DB 52 also contains information about the examinations and procedures performed by dentist U3.

[0030] Medical record DB52 is a database where medical record information d21 is stored. Medical record information d21 includes appointment information d1, visual examination result information d11, guidance and support information d13, and the details of the examination and treatment performed by dentist U3. The medical record indicated by medical record information d21 is an electronic medical record. This electronic medical record is an insurance medical record that contains the interview conducted with patient U1, the details of the examination and treatment performed by dentist U3 and dental hygienist U2, and the insurance points related to these.

[0031] (After-sales service department) The aftercare function unit 30 includes an aftercare execution unit 31 and an aftercare AI 32. The aftercare execution unit 31 includes a data input / output unit 311, a prompt creation unit 312, and a DB writing unit 313.

[0032] The data input / output unit 311 (an example of a post-examination interview information input / output unit) controls the operation of sending and receiving various data with the patient U1's mobile terminal 2. Specifically, the data input / output unit 311 transmits the aftercare interview information d23 generated by the aftercare AI 32 to the patient U1's mobile terminal 2.

[0033] The prompt generation unit 312 (an example of a post-examination questionnaire generation instruction unit) acquires medical record information d21 from the medical record DB 52 at a predetermined timing and generates an aftercare prompt d22 (an example of a post-examination questionnaire information generation instruction) based on the acquired medical record information d21. An example of the configuration of medical record information d21 will be described later with reference to Figure 19, and an example of the configuration of aftercare prompt d22 will be described later with reference to Figure 20. The prompt generation unit 312 then outputs the generated aftercare prompt d22 to the aftercare AI 32.

[0034] The aftercare AI 32 (an example of a post-examination interview AI) is composed of, for example, a large-scale language model. Based on the aftercare prompt d22 input from the prompt creation unit 312, the aftercare AI 32 creates aftercare interview information d23 (an example of post-examination interview information) corresponding to patient U1, and outputs the created aftercare interview information d23 to the aftercare execution unit 31. An example of the configuration of the aftercare interview information d23 will be described later with reference to Figure 21.

[0035] Furthermore, the Aftercare AI32 may be composed of a deep learning model (learning model) that has learned from past consultation cases. The learning model that has learned from past consultation cases can be composed of, for example, a neural network of a multi-class classification model, a learning model employing the Random Forest algorithm, or a finely tuned LLM.

[0036] The DB writing unit 313 writes the aftercare questionnaire information d23 generated by the aftercare AI 32 and the aftercare questionnaire response information d24 transmitted from the patient U1's mobile terminal 2 to the aftercare DB 53. Aftercare DB53 is a database that stores aftercare questionnaire information d23 and aftercare questionnaire response information d24.

[0037] (Recall Function Department) The recall function unit 40 includes a recall execution unit 41 and a recall AI 42. The recall execution unit 41 includes a data input / output unit 411 and a prompt creation unit 412.

[0038] The data input / output unit 411 (an example of a recall information input / output unit) controls the operation of sending and receiving various data between the patient U1's mobile terminal 2 and the dentist U3's terminal device 4. Specifically, the data input / output unit 411 receives the recall target patient information d31 transmitted from the dentist U3's terminal device 4 and outputs it to the prompt creation unit 412. The recall target patient information d31 is information about patients to whom recall information is to be transmitted, selected by the dentist U3 via the terminal device 4. The data input / output unit 411 also transmits the recall information d35 generated by the recall AI 42 to the dentist U3's terminal device 4. Then, when confirmation information regarding the content of the recall information d35 is transmitted from the terminal device 4 operated by the dentist U3, the data input / output unit 411 transmits the recall information d35, which has been determined to be without problems in the confirmation information, to the patient U1's mobile terminal 2.

[0039] The prompt generation unit 412 (an example of a recall information creation instruction unit) generates a recall prompt d34 based on the recall target patient information d31. An example of the configuration of the recall prompt d34 will be described later with reference to Figure 29. The prompt generation unit 312 then outputs the generated recall prompt d34 to the recall AI 42.

[0040] The recall AI 42 is composed of, for example, a large-scale language model. Based on the recall prompt d34 input from the prompt creation unit 312, the recall AI 42 creates recall information d35 corresponding to each patient U1 and transmits the created recall information d35 to the recall execution unit 41. An example of the configuration of the recall information d35 will be described later with reference to Figure 30.

[0041] Furthermore, Recall AI42 may be composed of a deep learning model (learning model) that has learned from past medical cases. The learning model that has learned from past medical cases can be composed of, for example, a neural network of a multi-class classification model, a learning model employing the Random Forest algorithm, or a finely tuned LLM.

[0042] <Configuration of the control system for the oral advisor system> Next, with reference to Figure 2, the hardware configurations of the server 1, mobile terminal 2, tablet terminal 3, and terminal device 4 that make up the oral advisor system 100 will be described. Figure 2 is a block diagram showing example configurations of the computer 500, which is the hardware of the server 1, mobile terminal 2, tablet terminal 3, and terminal device 4.

[0043] As shown in Figure 2, the computer 500 includes a control unit 510, a storage unit 520, an operation input unit 530, an output unit 540, and a communication I / F (Interface) unit 550, all connected to bus B. The control unit 510 is an arithmetic unit that includes a CPU (Central Processing Unit) 511, a ROM (Read Only Memory) 512, and a RAM (Random Access Memory) 513.

[0044] The CPU 511 reads the program code of the software that implements each function of the server 1 according to this embodiment from the ROM 512, loads it into the RAM 513, and executes it. Note that the server 1 may also include a processing unit such as an MPU (Micro-Processing Unit) instead of the CPU 511. Variables and parameters generated during the calculation process by the CPU 511 are temporarily written to the RAM 513.

[0045] For the storage unit 520, for example, an HDD (Hard Disk Drive), SSD (Solid State Drive), flexible disk, optical disk, magneto-optical disk, CD-ROM, CD-R, non-volatile memory card, etc. can be used. The storage unit 520 stores the OS (Operating System), various parameters, and programs necessary for the server 1 to function.

[0046] The program required to operate server 1 may also be stored in ROM 512. The program is stored in the form of program code that can be read by a computer. The CPU 511 sequentially executes operations according to the program code. In other words, the ROM 512 or storage unit 520 is an example of a computer-readable, non-transient recording medium that stores a program executed by the computer.

[0047] The operation input unit 530 is composed of, for example, a mouse or keyboard, and generates operation signals in response to user operations and supplies them to the CPU 511. The output unit 540 is a monitor, for example, composed of an LCD (Liquid Crystal Display). The operation input unit 530 and the output unit 540 may be integrated as a single touch panel. The communication interface 550 consists of communication devices and other components that control communication with external devices.

[0048] <Example of a procedure flow in a dental clinic> Next, with reference to Figure 3, the correspondence between the processing flow in a dental clinic and the processing performed by each functional unit of the Oral Advisor System 100 according to this embodiment will be explained. Figure 3 is a diagram showing the correspondence between the processing flow in a dental clinic and the processing performed by each functional unit of the Oral Advisor System 100 according to this embodiment.

[0049] First, patient U1 becomes aware of a dental clinic based on internet research and word-of-mouth recommendations, and makes an appointment for an examination at the clinic (Step S1). After Step S1, the initial examination takes place (Step S3). If the appointment in Step S1 is made after a specified period has elapsed since the previous appointment, the examination in Step S3 will be considered a re-initial examination. Then, during the initial or follow-up visit in Step S3, a medical history is taken (Step S4).

[0050] Conventional medical interviews are templated and not suitable for identifying patient-specific problems. Furthermore, templated interviews may include questions about alcohol consumption, smoking, pregnancy, etc., that may not be necessary depending on the patient's gender and age. In such cases, patients may question whether or not they need to answer certain questions.

[0051] Furthermore, with conventional technology, the medical interview is conducted after the patient arrives at the clinic, meaning the examination does not begin while the patient is answering the interview questions. In other words, the start time of the examination is delayed by the amount of time the patient spends answering the interview questions. Therefore, for example, if a patient takes a long time to answer the interview questions, the examination times of all patients who have appointments scheduled after that time will be delayed.

[0052] Furthermore, conducting a medical interview upon arrival means that the condition of the patient coming in that day can only be understood on the day of the appointment. Therefore, depending on the patient's symptoms, the dental clinic may not have the necessary materials or equipment in stock to treat those symptoms. In such situations, it may be impossible to provide appropriate treatment to the patient, potentially resulting in only emergency measures being taken or even the inability to perform treatment at all.

[0053] To address the above-mentioned issues, in the oral advisor system 100 according to this embodiment, the appointment-time medical interview function unit 10 conducts an appointment-time medical interview (step S2) between the appointment in step S1 and the initial or follow-up consultation in step S3. Details of the appointment-time medical interview processing by the appointment-time medical interview function unit 10 will be described later with reference to Figures 4 to 9.

[0054] Following the medical interview in step S4, a dentist U3 performs an examination and diagnosis based on the information obtained from the interview (step S5). However, when the oral advisor system 100 according to this embodiment is used, the medical interview is conducted after the appointment is made in step S1, so the medical interview before the examination and diagnosis in step S4 is not performed.

[0055] Following the examination and diagnosis in Step S5, dental hygienist U2 explains the examination findings and provides guidance on future care to patient U1 (Step S6). Dental hygienist U2 then records the details of the explanation and guidance given to patient U1 in a dental hygienist work record (not shown). The quality of guidance provided by dental hygienist U2 and the speed of recording in the dental hygienist work record depend on the dental hygienist U2's experience, skills, verbal ability, memory, etc.

[0056] Furthermore, the task of dental hygienist U2 recording information in the dental hygiene work log is time-consuming. Even a skilled dental hygienist like U2 finds it difficult to always provide optimal guidance tailored to each individual patient's condition. In addition, if one attempts to record all the necessary information accurately and completely, the recording process can take more than 10 minutes per patient.

[0057] In medical record systems designed to reduce recording time, templates for dental hygienist work records are often provided. However, when templates are used, dental hygienists (U2) will select one that closely matches the content of the explanation or instruction they provided, which may result in records that do not reflect the actual situation. Furthermore, many dental clinics still use paper for dental hygienist work records. Moreover, when dental hygienist work records are recorded on paper, centralized management and utilization of the information become difficult.

[0058] In other words, regardless of the experience, skills, verbal abilities, and memory of dental hygienist U2, it is necessary to ensure that they can provide appropriate explanations and guidance according to the patient U1's condition, and that they can maintain proper records in a format that allows for easy information sharing. In the oral advisor system 100 according to this embodiment, the instruction support function unit 20 performs instruction support processing for the purpose of solving the above-mentioned problems. The instruction support processing by the instruction support function unit 20 will be described later with reference to Figures 10 to 17.

[0059] In Step S6, dental hygienist U2 provides explanation and guidance, followed by treatment by dentist U3 (Step S7) and recording of the treatment details (Step S8). Then, payment is made at the reception desk (Step S9), and if necessary, an appointment for the next visit is made (Step S10). If an appointment for the next visit is made, the follow-up visit is conducted based on that appointment (Step S11).

[0060] In the conventional system, if the follow-up examination in step S11 was completed and the series of treatments were finished at that point, the next appointment was scheduled at the patient's discretion. Alternatively, a recall was sent via paper media such as postcards, or via email or social media to prompt the patient to schedule the next appointment (step S13).

[0061] In contrast, in the oral advisor system 100 according to this embodiment, the aftercare function unit 30 performs aftercare processing between the appointment in step S10 and the follow-up visit in step S11, or between the follow-up visit in step S11 and the recall in step S13. The aftercare processing performed by the aftercare function unit 30 will be described later with reference to Figures 18 to 25.

[0062] In the recall process conducted in Step S13, the conventional system sent a standardized email or social media message prompting the patient to schedule their next appointment at predetermined intervals, such as several months after the initial consultation or follow-up visit. However, the content of these recall messages was generalized and did not reflect the details of the treatment performed in Step S7.

[0063] In the oral advisor system 100 according to this embodiment, the recall function unit 40 performs recall processing to solve the above-mentioned problems. The recall processing by the recall function unit 40 will be described later with reference to Figures 26 to 31.

[0064] <Medical questionnaire processing at the time of booking> [Procedure for pre-booking medical questionnaire] Next, with reference to Figure 4, the appointment-time medical interview processing performed by the appointment-time medical interview function unit 10 will be explained. Figure 4 is a flowchart showing an example of the procedure for the appointment-time medical interview processing performed by the appointment-time medical interview function unit 10.

[0065] First, the data input / output unit 111 (see Figure 1) of the reservation creation unit 11 in the reservation questionnaire function unit 10 receives the input of reservation information d1 from the patient U1's mobile terminal 2 (step S21). Next, the prompt creation unit 112 of the reservation creation unit 11 generates a reservation questionnaire prompt d2 based on the reservation information d1 and outputs it to the reservation questionnaire AI 12 (step S22). Next, the reservation questionnaire AI 12 creates reservation questionnaire information d3 based on the reservation questionnaire prompt d2 and outputs it to the reservation creation unit 11 (step S23).

[0066] Next, the data input / output unit 111 of the reservation creation unit 11 transmits the reservation questionnaire information d3 to the mobile terminal 2 (step S24). Then, the data input / output unit 111 receives the reservation questionnaire response information d4, which is the answer to the reservation questionnaire transmitted from the mobile terminal 2 (step S25). Next, the data input / output unit 111 confirms the appointment for the consultation managed by the medical record system (not shown) based on the reservation questionnaire response information d4 (step S26). Then, the DB writing unit 113 of the reservation creation unit 11 writes the reservation questionnaire response information d4 to the reservation DB 51 (step S27). After the processing in step S27, the reservation questionnaire processing by the reservation questionnaire function unit 10 is completed.

[0067] [Example of reservation information structure] Next, we will explain the reservation information d1 that the data input / output unit 111 of the reservation creation unit 11 receives from the patient U1's mobile terminal 2 in step S21 of the flowchart in Figure 4, with reference to Figure 5. Figure 5 is a diagram showing an example of the configuration of the reservation information d1.

[0068] As shown in Figure 5, the reservation information d1 has the following fields: "Name," "Date and Time of Visit," "Gender," "Date of Birth," "Email Address," and "Reason for Visit." The "Name" field stores the patient's name, the "Date and Time of Visit" field stores the date and time the patient wishes to make an appointment, the "Gender" field stores the patient's gender, the "Date of Birth" field stores the patient's date of birth, and the "Email Address" field stores the patient's email address. Note that the information constituting the reservation information d1 is not limited to this information, and other information may be added.

[0069] [Example of a pre-booking questionnaire prompt structure] Next, the appointment scheduling questionnaire prompt d2 will be explained with reference to Figure 6. The appointment scheduling questionnaire prompt d2 is generated by the prompt creation unit 112 of the appointment creation unit 11 in step S22 of the flowchart in Figure 4. Figure 6 shows an example of the configuration of the appointment scheduling questionnaire prompt d2.

[0070] As shown in Figure 6, the first line of the appointment-time questionnaire prompt d2 contains the sentence, "You are a top-class dentist in Japan. You will now conduct a medical interview with the patient," which assigns a role to the appointment-time questionnaire AI 12. Next to that, there is the sentence, "Consider the patient's age, gender, and reason for visit, and generate 15 questions to ensure that all of the patient's wishes are thoroughly heard," which assigns a task to the appointment-time questionnaire AI 12. Following that, there is the sentence, which specifies constraints, "The output must be in XML format and always in Japanese. In addition, it must include items that are particularly easy for humans to overlook during a medical interview." Finally, the patient's attribute information for which the appointment-time questionnaire information d3 will be created includes the patient's date of birth, gender, and reason for visit.

[0071] When such a pre-booking questionnaire prompt d2 is input, the pre-booking questionnaire AI 12 can create and output pre-booking questionnaire information d3 according to the patient attribute information specified in the prompt. Note that the pre-booking questionnaire prompt d2 shown in Figure 6 is just one example, and the pre-booking questionnaire prompt d2 may have a different structure from the text structure shown in Figure 6, and may contain different information.

[0072] [Example of the structure of the medical questionnaire information used when making a reservation] Next, with reference to Figure 7, we will explain the appointment questionnaire information d3 created by the appointment questionnaire AI12. Figure 7 is a diagram showing an example of the structure of the appointment questionnaire information d3. As shown in Figure 7, the appointment questionnaire information d3 contains multiple-choice questions and open-ended questions in XML format. The multiple-choice questions consist of the question, "When did you start experiencing toothache or sensitivity?" and the options "More than 2 months ago," "1 month ago," "About 2 weeks ago," and "A few days ago." The open-ended questions include the question, "What kind of brushing and oral care do you usually do? Do you use interdental brushes or dental floss?"

[0073] Thus, the appointment questionnaire information d3, created by the appointment questionnaire AI12, reflects the patient's attribute information and the information "treatment for dental caries" written in the "reason for visit" section of the appointment information d1.

[0074] [Example of a reservation screen configuration] Next, with reference to Figure 8, we will explain the reservation screen Sc1 on which the appointment questionnaire information d3 is displayed. Figure 8 is a diagram showing an example of the configuration of the reservation screen Sc1 displayed on the mobile device 2. The reservation screen Sc1 shown in Figure 8 is a screen that is displayed, for example, after accessing a website provided by a dental clinic (not shown), when patient information is entered.

[0075] As shown in Figure 8, the reservation screen Sc1 has a patient information display area Ar1, a medical history information display area Ar2, and a reservation confirmation button Bn1. The patient information display area Ar1 displays the patient information entered on the previously displayed screen. Of the information displayed in the patient information display area Ar1, the patient's date of birth, gender, date and time of visit, and reason for visit are transmitted as reservation information d1 to the reservation creation unit 11 of the reservation medical history function unit 10.

[0076] The medical history information display area Ar2 displays the medical history information d3 created by the medical history AI 12 during the appointment. Patients can easily answer question 1 (Q1) by selecting the radio button corresponding to the answer that best suits their situation. For question 2 (Q2), patients can communicate their symptoms to the dental clinic by writing their answers in a free-response format.

[0077] The reservation confirmation button Bn1 is used to confirm the reservation. When the reservation confirmation button Bn1 is pressed, the patient's appointment for the consultation is confirmed, and the information entered on the reservation screen Sc1 is sent to the server 1 as patient information d1. Note that the configuration of the reservation screen Sc1 is not limited to the example shown in Figure 8, and the format of the questions and other information may be different.

[0078] [Example of reservation database configuration] Next, the configuration of the reservation DB 51, where the reservation questionnaire response information d4 is stored in step S26 of the flowchart in Figure 4, will be explained with reference to Figure 9. Figure 9 is a diagram showing an example of the configuration of the reservation DB 51.

[0079] As shown in Figure 9, the reservation DB51 contains the following items: "Name," "Date and Time of Visit," "Gender," "Date of Birth," "Email Address," "Reason for Visit," and "Medical Questionnaire Results." In the example shown in Figure 9, the patient's (scheduled) visit date and time is "October 1, 2024 at 2 PM," the patient's gender is "Male," and their date of birth is "January 2, 1990." The patient's email address is taro@xxxx.com, and the reason for the visit is "Treatment for a cavity." Furthermore, the answer to question Q1 is "About two weeks ago," and the answer to question Q2 is "I brush my teeth with a toothbrush and floss three times a day after meals."

[0080] According to this embodiment, since this information stored in the reservation DB 51 can be obtained at the time a patient makes a reservation for an examination, even if there is a shortage of materials or equipment necessary for treatment, the dental clinic can replenish them before the examination. Therefore, according to this embodiment, it is possible to prevent situations in which only emergency treatment is provided or in which treatment itself cannot be performed.

[0081] Furthermore, in this embodiment, the appointment-time medical interview AI 12 creates appointment-time medical interview information d3 tailored to each patient based on the appointment information d1, so that inappropriate questions that do not match the patient's attribute information are not included. Specifically, questions about pregnancy status will not be included for male patients, and questions about smoking will not be included for pediatric patients. Therefore, patients will be able to answer the medical interview smoothly without hesitation or doubt about whether or not they need to answer the questions.

[0082] Furthermore, in this embodiment, since the appointment-time medical questionnaire function unit 10 processes the medical questionnaire between the time of booking and the first or subsequent initial consultation, patients do not need to answer the questionnaire upon arrival at the clinic. Therefore, according to this embodiment, delays in consultation time due to prolonged responses to the questionnaire can be prevented. In addition, according to this embodiment, since it is not necessary to incorporate the time spent answering the questionnaire into the consultation time for each patient, the patient turnover rate can also be improved.

[0083] In the embodiments described above, examples were given in which the appointment-time questionnaire information d3 is used to secure inventory of materials and equipment necessary for treating the patient's symptoms and for examinations, but the present invention is not limited to these examples. The appointment-time questionnaire information d3 may also be used in campaigns to improve the patient's motivation to visit the clinic. For example, suppose the appointment-time questionnaire reveals that the patient has a symptom of "sensitivity to cold." In this case, the dental clinic can plan a campaign to give the patient a sample of toothpaste effective for hypersensitivity when they visit the clinic.

[0084] In this case, the reservation creation unit 11 displays a message such as, "Receive a sample of toothpaste effective for sensitive teeth on the day of your appointment!" on the reservation screen Sc1 in Figure 8. Displaying such a message is expected to increase the patient's motivation to come to the clinic, thus preventing situations where patients cancel their appointments at the last minute. Furthermore, offering such campaigns can also be expected to improve the dental clinic's ability to attract patients.

[0085] <Instructional Support Processing> [Procedure for guidance and support processing] Next, with reference to Figure 10, the instructional support processing performed by the instructional support function unit 20 will be explained. Figure 10 is a flowchart showing an example of the procedure for instructional support processing by the instructional support function unit 20.

[0086] First, the data input / output unit 211 (see Figure 1) of the medical record creation unit 21 of the guidance support function unit 20 receives the input of visual examination result information d11 from the tablet terminal 3 (step S31). Next, the medical record creation unit 21 detects the pressing of the guidance AI button Bn2 on the work record screen Sc2 (see Figure 16) (step S32). Next, the prompt creation unit 212 of the medical record creation unit 21 generates a guidance support prompt d12 based on the reservation DB registration information d6 and the medical record DB registration information d16, and outputs it to the guidance support AI 22 (step S33). The reservation DB registration information d6 is information read from the reservation DB 51, and the medical record DB registration information d16 is information read from the medical record DB 52.

[0087] Next, the guidance support AI 22 creates guidance support information d13 based on the guidance support prompt d12 and outputs it to the medical record creation unit 21 (step S34).

[0088] Next, the data input / output unit 211 of the medical record creation unit 21 transmits the guidance support information d13 to the tablet terminal 3 (step S35). The transmission of the guidance support information d13 to the tablet terminal 3 is performed at a predetermined timing after the patient's examination is completed. The transmission process in step S35 may be performed at the same timing as step S37, or after the execution of step S37, etc. Alternatively, for example, a transmission button that instructs the timing of transmission of the guidance support information may be provided on the work record screen Sc2, and the process of step S35 may be performed when the button is pressed.

[0089] Next, the data input / output unit 211 receives the input of examination and treatment information from the dentist via the tablet terminal 3 (step S36). The data input / output unit 211 then transcribes the guidance support information d13 and the details of the examination and treatment into the medical record managed by a medical record system (not shown) (step S37).

[0090] Next, the DB writing unit 213 creates medical record information d15 based on the reservation information d1, reservation DB registration information d6, medical record DB registration information d16, and guidance support information d13, and stores it in the medical record DB 52 (step S38). An example of the configuration of medical record information d15 will be described later with reference to Figure 15. After the processing in step S38, the guidance support processing by the guidance support function unit 20 is completed.

[0091] [Example of the structure of visual examination result information] Next, we will explain the visual inspection result information d11 with reference to Figure 11. Figure 11 is a diagram showing an example of the configuration of the visual inspection result information d11. The visual examination result information d11 is information that shows the content of the visual examination performed by dental hygienist U2 based on the guidance support information d13, and is transmitted from tablet terminal 3 to server 1 in step S31 of Figure 10.

[0092] As shown in Figure 11, the visual examination result information d11 has the following items: "Examination Date," "Visual Examination," "Plaque," and "Pocket." The "Examination Date" item stores information about the date the visual examination was performed by dental hygienist U2. The "Visual Examination" item stores information about the correspondence between the position of each tooth in the oral cavity and the condition of the tooth.

[0093] The "Plaque" section stores information about the correspondence between the position of each tooth in the oral cavity and the state of plaque. The "Pocket" field stores information corresponding to the position of each tooth in the oral cavity and the depth of the pocket. Note that the visual inspection result information d11 is not limited to the example shown in Figure 11, and may include other information.

[0094] [Example of the structure of medical record database registration information] Next, we will explain the medical record database registration information d16 with reference to Figure 12. Figure 12 is a diagram showing an example of the configuration of medical record database registration information d16. The medical record database registration information d16 is the information read from the medical record database 52 in step S38 of Figure 10 so that the database writing unit 213 can generate the medical record information d15.

[0095] As shown in Figure 12, the medical record database registration information d16 has "examination history" and "treatment history" items. The examination history item stores information about the history of examinations performed on the patient to date. The treatment history item stores information about the history of examinations performed on the patient to date. In the example shown in Figure 12, the treatment history information consists of information on the treatment date, chief complaint, site, and procedure. Note that the example shown in Figure 12 shows an example in which the medical record database registration information d16 consists of the most recent examination history and treatment history, but the present invention is not limited to this. The medical record database registration information d16 may consist of a predetermined number of past examination history and treatment history entries.

[0096] [Example of a guidance support prompt configuration] Next, the instructional support prompt d12 will be explained with reference to Figure 13. Figure 13 is a diagram showing an example of the configuration of the instructional support prompt d12.

[0097] As shown in Figure 13, the first line of the instruction support prompt d12 contains the following text, which assigns a role to the instruction support AI22: "You are a top-class dentist in Japan. You will now instruct the patient on oral care." Following this, the following text assigns a task to the instruction support AI22: "Consider the patient's date of birth, gender, reason for visit, interview results, examination results, examination history, and treatment history, and if there are any changes in the patient's oral condition, point them out and devise instruction to improve their oral health."

[0098] Furthermore, although not shown in Figure 13 due to space limitations, the document includes text specifying constraints, such as, "Avoid using technical terms as much as possible and use language that patients can understand. If technical terms or instrument names must be used, include a URL to content explaining them (e.g., the dental clinic's blog or video site)." Finally, the information about the patient for whom the guidance support information d13 is created includes the patient's date of birth, gender, reason for visit, interview results, test results, test history, and treatment history. The information from the date of birth to the interview results is included in the reservation DB registration information d6, the test results are included in the visual examination results information d11, and the test history and treatment history are included in the medical record DB registration information d16.

[0099] When such a guidance support prompt d12 is input, the guidance support AI 22 can create and output guidance support information d13 that corresponds to the patient information specified in the prompt. In addition, as shown in the example in Figure 13, instructions such as "when using technical terms or names of instruments, include a URL of content that explains them (such as a dental clinic's blog or video site)" may be given to the guidance support AI 22. In such cases, the prompt creation unit 212 may add correspondence information between the term and the URL for explaining that term to the guidance support prompt d12. Furthermore, the guidance support prompt d12 shown in Figure 13 is just one example, and the guidance support prompt d12 may have a different structure from the text structure shown in Figure 12, and may contain different information.

[0100] [Example of the structure of instructional support information] Next, with reference to Figure 14, we will explain the instructional support information d13 created by the instructional support AI 22. Figure 14 is a diagram showing an example of the structure of instructional support information d13. As shown in Figure 14, the guidance and support information d13 includes guidance tailored to the patient's situation, such as "strengthening plaque control," "revising diet," and "regular dental checkups."

[0101] For example, under the section "Strengthening plaque control," it states, "I use a toothbrush three times a day and also use floss." This statement was generated based on the answer "I brush and floss three times a day after meals" included in the appointment-time questionnaire response information d4.

[0102] Furthermore, under the same section, "Strengthening Plaque Control," it states, "Attention is needed regarding tooth ┘2, which has had a large amount of plaque buildup in the past. Brushing after meals is good, but there may be areas that are missed." This statement was generated based on the plaque information from visual examination results d11.

[0103] Also, although it is omitted in Figure 14 due to space limitations, the section on "Reviewing your diet" would include text such as the following. "Since you've been experiencing toothaches for the past two weeks, it's possible that sugar intake or acidic drinks are contributing factors. Try to reduce snacking and focus on eating foods that are less stressful on your teeth." We recommend reducing the frequency of consuming sweets. Avoid acidic beverages (such as carbonated drinks and juices), and when you do drink them, use a straw to avoid direct contact with your teeth.

[0104] Also, although it is omitted in Figure 14 due to space limitations, the section for "Regular dental checkups" would include text such as the following. "To detect and prevent cavities and periodontal disease early, have a regular check-up every 3-4 months." It's especially important to manage the risk by regularly having your teeth cleaned and your plaque score checked at the dental clinic, particularly in areas where plaque tends to accumulate.

[0105] Furthermore, in the guidance and support information d13, unfamiliar terms and technical terms such as "plaque score," "root remnant," and "tact brush" are linked to explanatory URLs.

[0106] Thus, since the guidance support information d13 contains appropriate guidance content tailored to the patient's current situation, even inexperienced dental hygienists can refer to the guidance support information d13 and provide appropriate guidance to patients. Furthermore, since the guidance support information d13 is written to the medical record DB52 by the data input / output unit 211, dental hygienist U2 can avoid the trouble of recording the guidance content. In addition, since the content of the guidance and treatment performed by dental hygienist U2 is written to the medical record DB52, it becomes easy to share information with other dental hygienists U2 and dentists U3.

[0107] [Example of medical record information structure] Next, we will explain the medical record information d15 with reference to Figure 15. Figure 15 is a diagram showing an example of the configuration of medical record information d15. Medical record information d15 is the information that the DB writing unit 213 of the medical record creation unit 21 writes to the medical record DB 52 in step S38 of Figure 10. As shown in Figure 15, the medical record information d15 includes the following items: "Name," "Gender," "Date of Birth," "Email Address," "Date of Visit," "Reason for Visit," "Medical Interview Results," "Visual Examination," "Plaque," "Pocket," and "Instruction Content." The information from name to medical interview results is included in the reservation database registration information d6. The information on visual examination, plaque, and pockets is included in the visual examination results information d11, and the information on instruction content is included in the instruction support information d13.

[0108] Furthermore, the prompt creation unit 212 of the medical record creation unit 21 may include an instruction to refer to the AI's extended learning data in the guidance support prompt d12 shown in Figure 13. The AI's extended learning data includes, for example, learning data that associates the condition of the patient's oral cavity obtained by visual examination with predefined sentences in a medical record system (not shown).

[0109] For example, suppose that in the augmented learning data, a visual inspection result such as "there is a lot of plaque between the teeth" is associated with the instruction "brush the interproximal surfaces thoroughly." In this case, the instructional support AI22 can generate appropriate instructional content corresponding to the patient's oral condition as instructional support information d13. Examples of sentences that can be used to train the augmented learning data in accordance with the patient's oral condition include the following:

[0110] • We will introduce the Bass method of brushing your teeth. We will introduce the scrubbing method for brushing your teeth. We will introduce the Stillman method of brushing your teeth. We will introduce the Charters method of brushing your teeth. • Make sure to thoroughly brush the affected tooth area. • Make sure to thoroughly brush the angled parts of your teeth. • Make sure to thoroughly brush crowded teeth. • Make sure to brush your wisdom teeth thoroughly. • Make sure to brush erupting teeth thoroughly. • Thoroughly clean the area where the prosthesis is attached. • Make sure to thoroughly polish the adjacent surfaces. • Thoroughly polish the root surface. • Make sure to thoroughly clean the occlusal surface. • Make sure to brush the area around the gum line thoroughly.

[0111] [Example of a work record screen configuration] Next, the configuration of the work record screen Sc2 will be explained with reference to Figure 16. Figure 16 is a diagram showing an example of the configuration of the work record screen Sc2. The work record screen Sc2 is a screen displayed on the tablet terminal 3, and is the screen on which dental hygienist U2 records the results of visual examinations, the content of instruction, etc.

[0112] As shown in Figure 16, a guidance AI button Bn2 is provided in the upper right corner of the work record screen Sc2. When the guidance AI button Bn2 is pressed, the guidance support information display screen Sc21 is displayed on the tablet terminal 3. The guidance support information display screen Sc21 is a screen that displays guidance support information d13. In the example shown in Figure 16, the following text is displayed at the top of the guidance support information display screen Sc21: "Based on the information of "Test Taro", we have generated the content to be taught. We especially recommend that you focus on teaching the following points." By displaying such text, dental hygienist U2 can understand that information to support the teaching of a patient named "Test Taro" is displayed in the area below.

[0113] The area below displays the contents of the guidance support information d13. In Figure 16, due to space limitations, some of the information in the guidance support information d13 is not shown, but the guidance support information display screen Sc21 displays all of the contents of the guidance support information d13. By checking the contents of the guidance support information d13, dental hygienist U2 can provide appropriate guidance to the patient. Therefore, even dental hygienist U2 with little experience or knowledge can provide patient U1 with guidance at the same high level as a highly experienced dental hygienist.

[0114] Below the display area for the guidance support information d13, there is a button Bn3 labeled "Transfer to Medical Record". When the button Bn3 is pressed, the contents of the guidance support information d13 displayed on the guidance support information display screen Sc21 are transferred to the medical record. Therefore, the dental hygienist U2 no longer needs to record the contents of the guidance given to the patient by handwriting or manual input. Also, when the button Bn3 labeled "Transfer to Medical Record" is pressed, the guidance support information d13 is transmitted from the data input / output unit 211 to the mobile terminal 2 operated by the patient.

[0115] [Example of SNS screen layout] Next, with reference to Figure 17, we will explain the SNS screen Sc3 on which the instructional support information d13 is displayed. Figure 17 is a diagram showing an example of the configuration of the SNS screen Sc3 displayed on the mobile device 2. As shown in Figure 17, the SNS screen Sc3 displays a message from "Chuo Dental Clinic." This message is based on guidance and support information d13. This message includes comments tailored to the patient's current situation, predictive information on the progression of the oral condition if care is not performed appropriately, and specific care information to prevent the condition from worsening.

[0116] Specifically, the following statements will be included as comments tailored to the patient's current situation. 1. Strengthening plaque control I brush my teeth three times a day and also use floss, but I need to be careful with tooth #2, which has had a lot of plaque buildup in the past. Brushing after meals is good, but there may be some areas that are missed. Therefore, I recommend the following: • Proper brushing technique: Pay particular attention to areas where plaque tends to accumulate, such as the gum line (the area where the tooth meets the gum) and the spaces between teeth.

[0117] Furthermore, although it is omitted from Figure 17 due to space limitations, the following text is included as a point of reference relevant to the patient's current condition. "• Consider using an electric toothbrush: It can be expected to remove plaque more effectively." • Using floss and interdental brushes together: If you are already using floss, consider using interdental brushes in areas with high plaque scores. It appears you have some remaining tooth roots, so please clean them thoroughly with a Tact brush.

[0118] When patients see messages like these, they understand that the instructions are tailored specifically for them, and therefore feel more inclined to take the care outlined in the instructions seriously.

[0119] Furthermore, the instructional messages displayed on the SNS screen (Sc3) include URL links for terms such as "plaque score," "root remnant," and "tact brush," allowing patients to check the meaning of unfamiliar terms on the linked website.

[0120] <Aftercare processing> [Aftercare Procedures] Next, the aftercare processing performed by the aftercare function unit 30 will be explained with reference to Figure 18. Figure 18 is a flowchart showing an example of the procedure for aftercare processing performed by the aftercare function unit 30.

[0121] First, the data input / output unit 311 of the aftercare execution unit 31 of the aftercare function unit 30 acquires medical record information d21 for all patients from the medical record DB 52 at predetermined times such as daily or weekly (step S41). The medical record information d21 acquired by the data input / output unit 311 from the medical record DB 52 in step S41 is information to which the details of the treatment have been added to the information written to the medical record DB 52 by the DB writing unit 213 of the medical record creation unit 21 in step S38 of Figure 10. An example of the configuration of medical record information d21 will be described later with reference to Figure 19.

[0122] Next, the prompt creation unit 312 creates an aftercare prompt d22 based on the medical record information d21 acquired in step S41 and outputs it to the aftercare AI 32 (step S42). Then, the aftercare AI 32 generates aftercare questionnaire information d23 based on the aftercare prompt d22 and outputs it to the aftercare execution unit 31 (step S43).

[0123] Next, the data input / output unit 311 sends an aftercare message based on the aftercare questionnaire information d23 to the mobile terminal 2 of patient U1, for whom "no questionnaire required" has not been specified in the aftercare questionnaire information d23 (step S44). Then, the data input / output unit 311 receives input of aftercare questionnaire response information d24, which is the response to the aftercare message, from patient U1's mobile terminal 2 (step S45). Next, the DB writing unit 313 writes the aftercare questionnaire response information d24 received in step S45 to the aftercare DB 53 (step S46). After the processing in step S46, the aftercare processing by the aftercare function unit 30 is completed.

[0124] [Example of medical record information structure] Next, referring to Figure 19, we will explain the medical record information d21 that the data input / output unit 311 of the aftercare execution unit 31 acquires from the medical record DB 52. Figure 19 is a diagram showing an example of the configuration of the medical record information d21.

[0125] As shown in Figure 19, the medical record information d21 has the following items: "Name," "Gender," "Date of Birth," "Email Address," and "Medical Record Content." The "Medical Record Content" item includes the patient's visit date, reason for visit, interview results, visual examination, plaque, pockets, instructions, and treatment. Since the items other than treatment are the same as those in medical record information d15 explained with reference to Figure 15, redundant explanations are omitted. The "Treatment" item describes the treatment performed on the patient by dentist U3.

[0126] [Example of aftercare prompt configuration] Next, we will explain the aftercare prompt d22 with reference to Figure 20. Figure 20 is a diagram showing an example configuration of the aftercare prompt d22.

[0127] As shown in Figure 20, the first line of the aftercare prompt d22 contains the following text, which assigns a role to the aftercare AI32: "You are a top-class dental advisor in Japan. You will now send a questionnaire to the patient for aftercare following their last visit. The questionnaire should consist of no more than 5 questions." The following text then assigns a task to the aftercare AI32: "Consider the patient's name, date of birth, gender, date of visit, reason for visit, questionnaire results, visual examination, plaque, pockets, instructions, and treatment, and then compose a questionnaire to inquire about their condition afterward and to check if any abnormalities have occurred over time."

[0128] Next, as a statement of constraints, it says, "Also, at the end of the medical interview, be sure to include a sentence encouraging patients to 'please do not hesitate to come to the clinic immediately if you feel anything unusual.'" Following that, although it is omitted from the illustration in Figure 20 due to space limitations, as an instruction for the aftercare AI32 to select patients to whom aftercare medical interview information d23 will be sent, it says, "Furthermore, after fully considering the vast number of dental treatment trends you have learned, if you determine that today is not the optimal time to conduct a medical interview from the date of the visit, output 'No medical interview required.'"

[0129] Furthermore, although it is omitted from Figure 20 due to space limitations, the following statement is included regarding the "optimal timing for taking a medical interview" in the text that defines the above constraints. "This 'optimal timing for a consultation' refers to things like, for example, the optimal time to conduct a consultation three days after a tooth extraction, as bleeding tends to stop within three days at the latest; or, for patients whose orthodontic appliances have been removed, the optimal time to conduct a consultation one year later, as teeth tend to shift back to their original positions after that period."

[0130] Below this text, the patient's name, date of birth, gender, date of visit, reason for visit, results of medical history interview, visual examination, plaque, pockets, instructions given, and treatment performed are listed.

[0131] When such instructions are given in the aftercare prompt d22, the aftercare AI32 can set patients who have not visited the clinic for many years after their first visit, or patients who have just visited, to "no interview required." In other words, patients who have been set to "no interview required" can be excluded from receiving aftercare messages. This prevents aftercare messages from being sent to patients who are not expected to receive them. Furthermore, since dentists, dental hygienists, dental assistants, etc., do not need to judge or set whether or not to send aftercare messages, it saves them time and prevents aftercare messages from being missed.

[0132] It should be noted that even for patients who wish to receive aftercare messages, it is possible that they may remain in an "unanswered" state without providing a response. To prevent such patients from being deemed "unnecessary to have a medical interview," the prompt creation unit 312 may add an instruction to the aftercare prompt d22 to "resend to all unanswered patients." Alternatively, the data input / output unit 311 of the aftercare execution unit 31 may extract unanswered patients at predetermined intervals and send aftercare medical interview information d23 to the mobile terminals 2 of the extracted patients.

[0133] [Example of the structure of aftercare consultation information] Next, with reference to Figure 21, we will explain the aftercare questionnaire information d23 created by the aftercare AI32. Figure 21 is a diagram showing an example of the structure of the aftercare questionnaire information d23. As shown in Figure 21, the first line of the aftercare questionnaire information d23 contains the message, "Mr. Taro Test, you last visited us on 2024-10-10. How are you doing now?" This section identifies the patient's name and the date and time of their visit.

[0134] Next, the following text is included to inform the patient that an aftercare consultation will be conducted: "We would like to confirm your progress in following the 'oral self-care methods' that our dental hygienist explained to you during your last visit. We would appreciate it if you could answer the following questions." Following this, there is a detailed questionnaire tailored to each patient, based on their symptoms and the treatment they received.

[0135] The specific content of the medical interview might include, for example, the following: 1. Do you experience any pain or sensitivity after dental treatment for cavities? Yes, there are more (please tell me about the affected area and symptoms). No, nothing in particular. 2. Regarding the use of toothbrushes, floss, and interdental brushes, are you continuing to brush your teeth after meals and use floss and interdental brushes? Yes, I continue to do it every day. I sometimes forget. "I haven't been able to do it at all."

[0136] Furthermore, although it is omitted from Figure 21 due to space limitations, the following text is also included. 3. Regarding improvements to your diet, have you been able to reduce the frequency of your consumption of sweets and acidic beverages? Yes, we are able to reduce it. No, not much has changed. 4. Are you reducing snacking or making changes to how you drink beverages? (e.g., using a straw) 5. Regarding plaque and periodontal pocket care, are there any symptoms that concern you, such as swollen or bleeding gums, or bad breath? Yes, there is (please tell me specifically). No, nothing in particular. If the pain or discomfort persists, or if new symptoms appear, Please don't hesitate to come to our clinic anytime. We will provide you with our full support.

[0137] [Example of the structure of aftercare questionnaire response information] Next, we will explain the aftercare questionnaire response information d24 with reference to Figure 22. The aftercare questionnaire response information d24 is the patient's response to the aftercare message and is sent from the patient's mobile device 2 to the server 1. Figure 22 is a diagram showing an example of the configuration of the aftercare questionnaire response information d24. As shown in Figure 22, the aftercare questionnaire response information d24 contains the answer "No, not particularly" to the question "1. Do you have any pain or sensitivity symptoms after dental treatment?". Also, to the question "2. Regarding the use of toothbrushes, floss, and interdental brushes, are you continuing to brush your teeth after meals and use floss and interdental brushes?", the answer "I sometimes forget".

[0138] Furthermore, although omitted from Figure 22 due to space limitations, the aftercare questionnaire response information d24 also includes the following information. 3. Regarding improvements to your diet, have you been able to reduce the frequency of your consumption of sweets and acidic beverages? →Yes, we are able to reduce it. 4. Are you reducing snacking or making adjustments to how you drink beverages? (e.g., using a straw) →The number of snacks hasn't changed, but I've started giving them low-sugar snacks like dried squid. 5. Are you experiencing any symptoms that concern you, such as swollen or bleeding gums, or bad breath? "I still feel like it's a little swollen. My breath might also be worse than before."

[0139] [Example of aftercare information structure] Next, the aftercare information d25 will be explained with reference to Figure 23. Figure 23 is a diagram showing an example of the configuration of aftercare information d25. Aftercare information d25 is the information that the DB writing unit 313 of the aftercare execution unit 31 writes to the aftercare DB 53 in step S46 of Figure 18. As shown in Figure 23, aftercare information d25 consists of the following items: "Name", "Gender", "Date of Birth", "Recipient", "Date and Time of Sending", "Questionnaire Content", "Date and Time of Response", and "Response".

[0140] The "Recipient" field stores the email address of the patient to whom the aftercare questionnaire information d23 was sent. The "Sent Date and Time" field stores the date and time when the aftercare questionnaire information d23 was sent to the patient's mobile device 2. The "Questionnaire Content" field contains the content of the aftercare questionnaire information d23. The "Response Date and Time" field stores the date and time when the aftercare questionnaire response information d24 was sent from the patient's mobile device 2. The "Response" field stores the content of the aftercare questionnaire response information d24.

[0141] [Example of aftercare consultation screen configuration] Next, with reference to Figures 24 and 25, the aftercare questionnaire screen displayed on patient U1's mobile device 2 will be described. Figure 24 shows an example of the configuration of the aftercare questionnaire screen Sc41 when the aftercare message is sent via email. Figure 25 shows an example of the configuration of the aftercare questionnaire screen Sc42 when the aftercare message is sent via SNS.

[0142] The aftercare questionnaire screen Sc41 shown in Figure 24 displays the state in which the patient's answers have been entered for each questionnaire in the aftercare message. The aftercare questionnaire information d23, which forms the basis of the aftercare message, is created based on the aftercare prompt d22, which includes information on the patient's answers to the pre-booking questionnaire and the content of the guidance and treatment given to the patient. Therefore, the aftercare message does not contain general content that is not relevant to the patient, so the patient will perceive the message as relevant to them and feel the need to write a reply and respond.

[0143] Specifically, the aftercare questionnaire screen Sc41 contains the following text as aftercare questionnaire information d23. Subject: Re: Aftercare following your visit Text: Thank you for contacting us after your treatment. Here is my answer. 1. Do you experience any pain or sensitivity after cavity treatment? →No, nothing in particular. > 2. Regarding the use of toothbrushing, flossing, and interdental brushes, Brushing your teeth after meals and using floss / interdental brushes is important. Are you still continuing? →I sometimes forget. > 3. Regarding improving dietary habits, sweets and acidic beverages Have you been able to reduce the frequency of consumption? →Yes, we are able to reduce it."

[0144] Furthermore, although it is omitted from Figure 24 due to space limitations, the following text is also included as aftercare questionnaire information d23. 4. Are you reducing snacking or making adjustments to how you drink beverages? (e.g., using a straw) →The number of snacks hasn't changed, but I've started giving them low-sugar snacks like dried squid. 5. Are you experiencing any symptoms that concern you, such as swollen or bleeding gums, or bad breath? "I still feel like it's swollen. My breath might also be worse than before."

[0145] Furthermore, by sending aftercare messages via email and receiving responses in the form of replies, patient U1 can freely describe their symptoms and aftercare status without any restrictions. Therefore, the amount of information that patient U1 can include in the aftercare questionnaire response information d24 can be increased.

[0146] Figure 25 shows an example of an aftercare questionnaire screen Sc42 where aftercare messages are displayed in the format of an SNS chat. In the example shown in Figure 25, after the message corresponding to the aftercare questionnaire, answer options such as "Yes, there are still some" and "No, there aren't any in particular" are displayed as selectable options. Therefore, patient U1 can easily answer questions about their situation by selecting one of the answer buttons. Although Figure 25 shows an example where an answer is selected by pressing a button, the present invention is not limited to this. For example, after detecting a button press, a free text field may be displayed where the user can enter a detailed answer regarding the content of the answer indicated by the button press.

[0147] By obtaining aftercare questionnaire response information d24 through interfaces such as the aftercare questionnaire screens Sc41 and Sc42, the dental clinic can grasp information about symptoms that have occurred in the patient between visits without waiting for the next appointment. Therefore, dentist U3, upon reviewing the aftercare questionnaire response information d24, can use it as a reference for creating treatment plans for the next visit, or identify the pathology causing the symptoms and take countermeasures. Patient U1 can also gain peace of mind by communicating any concerning symptoms to the dental clinic via the aftercare questionnaire screens Sc41 and Sc42.

[0148] Furthermore, the aftercare questionnaire response information d24 may be used for gamification with the aim of improving and maintaining patient motivation for treatment. Gamification refers to the application of game elements to services that are not primarily intended as games, in order to improve user motivation and strengthen loyalty. For example, an AI for evaluating response content may be provided that evaluates the content of aftercare questionnaire response information d24 and outputs an evaluation result. The AI ​​for evaluating response content can output a better evaluation result the higher the proportion of responses indicating that positive efforts are being made by the patient among the total number of responses in the aftercare questionnaire response information d24.

[0149] Let's explain gamification in more detail. For example, if the AI ​​that evaluates responses has 5 questions in the aftercare questionnaire and 3 of them are answered positively, it will generate a message such as, "You got 3 out of 5 points! Let's try to get 2 more points before your next treatment! In particular, plaque tends to accumulate between your teeth, so don't forget to floss." By displaying such a report card-like message for the patient's efforts on the aftercare questionnaire screen Sc42, it is expected that the patient's motivation to take care of their teeth will be improved or maintained. Alternatively, by setting up achievements such as "Silver Medal Achieved! (3 / 5 points)", it is expected that patients will be able to approach their care with a game-like feeling and will be more likely to answer the aftercare questionnaire actively.

[0150] <Recall Procedure> [Recall Procedure] Next, with reference to Figure 26, the recall process performed by the recall function unit 40 will be explained. Figure 26 is a flowchart showing an example of the recall process procedure performed by the recall function unit 40.

[0151] First, terminal device 4 receives the selection of patients U1 to be recalled from dentist U3 (step S51). Dentist U3 selects, for example, patients U1 who have been absent for 3 months, 6 months, or 12 months since their last visit. Based on the selection in step S51, terminal device 4 sends recall target patient information d31 to server 1. Note that the processing in step S51 may be performed automatically by the recall execution unit 41 based on the number of days elapsed since the last visit.

[0152] Next, the data input / output unit 411 of the recall execution unit 41 obtains medical record information d32 corresponding to the selected patient U1 from the medical record DB 52 and aftercare information d33 from the aftercare DB 53 (step S52). The medical record information d32 obtained by the data input / output unit 411 in step S52 will be described in detail with reference to Figure 28, and the aftercare information d33 will be described in detail with reference to Figure 30.

[0153] Next, the prompt creation unit 412 creates a recall prompt d34 based on the medical record information d32 and aftercare information d33 and outputs it to the recall AI 42 (step S53). Then, the recall AI 42 generates recall information d35 based on the recall prompt d34 and outputs it to the recall execution unit 41 (step S54). Next, the data input / output unit 411 of the recall execution unit 41 transmits the recall information d35 to the patient's mobile terminal 2 (step S55). After processing in step S55, the recall processing by the recall function unit 40 is completed.

[0154] [Example of medical record information structure] Next, we will explain the medical record information d32 with reference to Figure 27. Figure 27 is a diagram showing an example of the structure of medical record information d32. As shown in Figure 27, medical record information d32 has the following items: "email address," "date of visit," "reason for visit," "results of medical history interview," "visual examination," "plaque," "pocket," "instruction content," and "treatment." Since each of these items has already been explained, we will omit any redundant explanations here.

[0155] [Example of aftercare information structure] Next, we will explain the aftercare information d33 with reference to Figure 28. Figure 28 is a diagram showing an example of the configuration of aftercare information d33. As shown in Figure 28, aftercare information d33 has the following items: "Name", "Gender", "Date of Birth", "Response Date and Time", and "Response". The "Response Date and Time" item stores the date and time when the aftercare questionnaire response information d24 (see Figure 22) was sent from the patient's mobile terminal 2. The "Response" item stores the aftercare questionnaire response information d24.

[0156] [Example of recall prompt configuration] Next, the recall prompt d34 will be described with reference to Figure 29. Figure 29 shows an example configuration of the recall prompt d34.

[0157] As shown in Figure 29, the first line of the recall prompt d34 contains the following text, which assigns a role to the recall AI42: "You are a top-class dentist in Japan. We will now send a direct message to encourage patients to return (become repeat patients)." The following text assigns a task to the recall AI42: "Consider the patient's name, gender, date of birth, recent patient responses, and recent medical record contents, and create a message that will encourage the patient to return, explaining that their oral condition may have changed due to the long gap between visits and that neglecting the problem could pose a health risk."

[0158] Next, there is a document outlining the constraints, which states: "The output must be in Japanese, and a greeting including a seasonal word must be included at the beginning. Dental jargon must be replaced with language that can be understood by laypeople. The main text should be as concise as possible, around 150 characters."

[0159] Next, the information about the patient for whom Recall AI42 generates Recall Information d35 is listed, including the patient's name, date of birth, and gender. Following that, information on "Most Recent Response" and "Most Recent Medical Record" is listed. The "Most Recent Response" item is the content recorded in Aftercare Information d33, and the "Most Recent Medical Record" item is the content recorded in Medical Record Information d32.

[0160] When such a recall prompt d34 is entered, the recall AI42 can generate recall information d35, which is a message appropriate for the patient encouraging them to come to the clinic, based on the patient's attributes, responses to the aftercare questionnaire, and examination information.

[0161] [Example of recall information structure] Next, we will explain recall information d35 with reference to Figure 30. Figure 30 is a diagram showing an example of the structure of recall information d35. As shown in Figure 30, recall information d35 consists of the text of the recall message. Specifically, it begins with a greeting such as, "Autumn is deepening, and the days are getting cooler," followed by a sentence that states the number of days that have passed since the last visit and inquires about the patient's condition, such as, "You came in for treatment of a cavity last time, but about three months have passed since then. Have you experienced any pain since then?"

[0162] Next, there is a sentence emphasizing the importance of regular care, based on the responses to the aftercare questionnaire: "In the aftercare questionnaire sent after treatment, you mentioned being concerned about swollen gums and bad breath, but if left untreated for a long period, it can lead to the progression of periodontal disease." Following that, there is a sentence emphasizing the importance of care, generated based on the examination results: "Mr. Test, there was some plaque buildup in your last examination, so please be sure to take good care of your teeth on a daily basis."

[0163] Finally, the text includes a message that informs patients of the benefits of visiting the clinic and encourages them to come in: "Periodontal bacteria can lead to systemic diseases, so although we know you are busy, it is important to come in as soon as possible to have your condition checked and receive appropriate care. We would be happy if you would feel free to make an appointment."

[0164] [Example of a recall screen configuration] Next, with reference to Figure 31, the recall screen Sc5 displayed on the patient's mobile device 2 will be explained. Figure 31 is a diagram showing an example of the configuration of the recall screen Sc5 when a recall message is sent via SNS. As shown in Figure 31, the recall screen Sc5 displays the recall information d35 (recall message). Due to space limitations, some of the details of the recall information d35 are not shown in Figure 31, but the recall screen Sc5 in Figure 31 displays the same content as the recall information d35 shown in Figure 30.

[0165] By checking the message displayed on the recall screen Sc5, patients can learn that three months have passed since their last visit, that neglecting concerning symptoms could lead to the progression of periodontal disease, that plaque buildup was detected during the examination, and that their current condition can be checked upon arrival. This message is not a generalized message, but rather one tailored to the patient's individual situation. Therefore, by reading such a message, patients can feel the need to make an appointment and make one.

[0166] Furthermore, recall prompt d34 may include a link to the URL of the appointment booking screen (Uniform Resource Locator) in recall information d35, for example.

[0167] <Oral advisor system with modified form> The modified oral advisor system 100A is equipped with a resume function. The resume function temporarily stores the information generated by the appointment interview AI 12, guidance support AI 22, aftercare AI 32, and recall AI 42, as well as the information necessary for generating this information by each of these AIs, in the resume DB, and reads it and displays it on the screen when work resumes.

[0168] Now, let me explain the background behind the need for a resume function. In dental clinics, work is frequently interrupted to attend to patients. For example, while dental hygienist U2 is giving instructions to a patient, an urgent patient needs to be addressed, and dental hygienist U2 may have to interrupt the instruction. In such cases, dental hygienist U2 may also have to hand over the input of the instruction content to another person while she is in the middle of entering the content into tablet device 3. This handover of input work can occur not only when dealing with emergency patients, but also in other situations.

[0169] If work is interrupted midway and the information from before the interruption is not retained anywhere, it can lead to situations such as missing necessary information or duplicate entries of already entered information. In dental treatment, accurate recording of detailed information is required, but if the above problems occur, the accuracy of the information recording will decrease.

[0170] Furthermore, if the responses generated by the appointment questionnaire AI12, guidance support AI22, aftercare AI32, and recall AI42 are lost due to work interruption, each AI will need to generate responses again. For example, if a patient interrupts the input process for the appointment questionnaire, and the responses generated by the appointment questionnaire AI12 are not retained, the appointment questionnaire AI12 will need to generate responses again. The time it takes for the appointment questionnaire AI12 to generate responses becomes waiting time for patient U1. In this case, patient U1 may even give up on answering the appointment questionnaire and aftercare questionnaire altogether.

[0171] Minimizing patient waiting times is crucial for improving the "patient experience (customer experience)." However, patient waiting times occur when tasks such as re-checking input from before the interruption when resuming work, checking input from a predecessor when taking over from another staff member, or regenerating answers using AI are performed. This increases the time from treatment to payment within the hospital, as well as the time spent preparing answers for appointment-taking and aftercare questionnaires outside the hospital. Such situations can contribute to increased patient churn.

[0172] To address these challenges, the modified oral advisor system 100A provides a resume function.

[0173] [Outline of the Oral Advisor System] First, with reference to Figure 32, the configuration of an oral advisor system 100A according to a modified version of the present invention will be described. Figure 32 is a diagram showing a schematic example of the configuration of the oral advisor system 100A.

[0174] The difference between the oral advisor system 100A shown in Figure 32 and the oral advisor system 100 shown in Figure 1 is that the oral advisor system 100A includes an appointment-time medical interview AI resume DB 61, a guidance support AI resume DB 62, an aftercare AI resume DB 63, and a recall AI resume DB 64.

[0175] Furthermore, in the oral advisor system 100A shown in Figure 32, the DB writing unit 113 of the reservation creation unit 11 saves the reservation information d1 transmitted from the mobile terminal 2 and the reservation questionnaire information d3 generated by the reservation questionnaire AI 12 to the reservation questionnaire AI resume DB 61, which is a DB that temporarily holds this information. The timing of saving to the reservation questionnaire AI resume DB 61 is as follows: reservation information d1 is saved each time character input is detected, and reservation questionnaire information d3 is saved after the reservation questionnaire AI 12 has finished generating it.

[0176] The DB writing unit 213 of the medical record creation unit 21 saves the reservation DB registration information d6, the visual examination result information d11 transmitted from the tablet terminal 3, the guidance support information d13 generated by the guidance support AI 22, and the medical record DB registration information d16 stored in the medical record DB 52 to the guidance support AI resume DB 62. The guidance support AI resume DB 62 is a DB that temporarily holds this information. The timing of saving to the guidance support AI resume DB 62 is as follows: the visual examination result information d11 is saved each time character input is detected, and the guidance support information d13 and medical record DB registration information d16 are saved after the guidance support AI 22 has finished generating the guidance support information d13.

[0177] The DB writing unit 313 of the aftercare execution unit 31 saves the medical record information d21 obtained from the medical record DB 52, the aftercare questionnaire information d23 generated by the aftercare AI 32, and the aftercare questionnaire response information d24 transmitted from the mobile terminal 2 to the aftercare AI resume DB 63. The aftercare AI resume DB 63 is a DB (an example of a post-consultation questionnaire information resume database) that temporarily holds this information. The timing of saving to the aftercare AI resume DB 63 is as follows: aftercare questionnaire response information d24 is saved each time character input is detected, and aftercare questionnaire information d23 and medical record information d21 are saved after the aftercare AI 32 has finished generating the aftercare questionnaire information d23.

[0178] The DB writing unit 413 of the recall execution unit 41 saves the medical record information d32 corresponding to patient U1 obtained from the medical record DB 52, the aftercare information d33 obtained from the aftercare DB 53, and the recall information d35 generated by the recall AI 42 to the recall AI resume DB 64. The recall AI resume DB 64 is a database that temporarily holds this information. The timing of saving each piece of information to the recall AI resume DB 64 is after the recall AI 42 has finished generating the recall information d35.

[0179] Other functions of the modified advisor system 100A are the same as those of the oral advisor system 100 shown in Figure 1, so redundant explanations will be omitted.

[0180] [Configuration of the AI ​​resume database for appointment scheduling] Next, with reference to Figure 33, the configuration of the Appointment Consultation AI Resume DB 61 will be explained. Figure 33 is a diagram showing an example of the configuration of the Appointment Consultation AI Resume DB 61. The Appointment Consultation AI Resume DB 61 consists of appointment information d1 (see Figure 5) and appointment consultation information d3 (see Figure 7).

[0181] Of the items that make up the AI ​​resume DB61 for pre-booking medical interviews shown in Figure 33, the items "Name," "Date and Time of Visit," "Gender," "Date of Birth," "Email Address," and "Reason for Visit" are items included in the pre-booking information d1. The items in "Pre-booking Medical Interview Information" are the items shown in the pre-booking medical interview information d3. The specific contents of each of these items have already been explained by referring to Figures 5 and 7, respectively, so redundant explanations will be omitted.

[0182] [Configuration of the AI-powered instructional support resume database] Next, with reference to Figure 34, the configuration of the instructional support AI resume DB62 will be explained. Figure 34 shows an example of the configuration of the guidance support AI resume DB62. The guidance support AI resume DB62 consists of reservation DB registration information d6, visual examination result information d11 (see Figure 11), medical record DB registration information d16 (see Figure 12), and guidance support information d13 (see Figure 14), all stored in the reservation DB51 (see Figure 9).

[0183] Of the items that make up the guidance support AI resume DB62 shown in Figure 34, the items "Name," "Date and Time of Visit," "Gender," "Date of Birth," "Email Address," "Reason for Visit," and "Medical Interview Results" are items included in the reservation DB registration information d6. The items "Examination Date," "Visual Examination," "Plaque," and "Pocket" are items shown in the visual examination results information d11. The items "Examination History" and "Treatment History" are items included in the medical record DB registration information d16. The item "Guidance Support Information" is an item shown in the guidance support information d13. The specific contents of each of these items have already been explained by referring to Figures 9, 11, 12, and 14, respectively, so redundant explanations will be omitted.

[0184] [Aftercare AI Resume DB Configuration] Next, the configuration of the Aftercare AI Resume DB63 will be explained with reference to Figure 35. Figure 35 is a diagram showing an example of the configuration of the Aftercare AI Resume DB63. The Aftercare AI Resume DB63 consists of medical record information d21 (see Figure 19), aftercare questionnaire information d23 (see Figure 21), and aftercare questionnaire response information d24 (see Figure 22).

[0185] Of the items that make up the Aftercare AI Resume DB63 shown in Figure 35, the items "Name," "Date and Time of Visit," "Gender," "Date of Birth," "Email Address," and "Reason for Medical Record" are items included in Medical Record Information d21. The items in "Aftercare Questionnaire Information" are items shown in Aftercare Questionnaire Information d23. The items in "Aftercare Questionnaire Response Information" are items shown in Aftercare Questionnaire Response Information d24. The specific contents of each of these items have already been explained by referring to Figures 19, 21, and 22, respectively, so redundant explanations will be omitted.

[0186] [Recall AI Resume DB Configuration] Next, with reference to Figure 36, the configuration of the Recall AI Resume DB64 will be described. Figure 36 shows an example of the configuration of the Recall AI Resume DB64. The Recall AI Resume DB64 consists of aftercare information d33 (see Figure 28), medical record information d32 (see Figure 27), and recall information d35 (see Figure 30).

[0187] Of the items that make up the Recall AI Resume DB64 shown in Figure 36, the items "Name," "Gender," "Date of Birth," "Response Date and Time," and "Response" are items included in Aftercare Information d33. The items "Email Address," "Date of Visit," "Reason for Visit," "Medical Interview Results," "Visual Examination," "Plaque," "Pocket," "Instruction Content," and "Treatment" are items included in Medical Record Information d32. The "Recall Information" item is the item shown in Recall Information d35. The specific contents of each of these items have already been explained by referring to Figures 28, 27, and 30, respectively, so redundant explanations will be omitted.

[0188] [Resume processing by the pre-booking medical questionnaire function] Next, the resume processing by the appointment-time medical interview function unit 10 will be explained with reference to Figures 37 and 38. Figure 37 is a flowchart showing an example of the procedure for saving appointment-time medical interview information by the appointment-time medical interview function unit 10, and Figure 38 is a flowchart showing an example of the procedure for reading appointment-time medical interview information by the appointment-time medical interview function unit 10.

[0189] (Saving of medical questionnaire information at the time of booking) First, with reference to Figure 37, we will explain the process of saving reservation-time medical questionnaire information by the reservation-time medical questionnaire function unit 10. First, the appointment questionnaire AI 12 of the appointment questionnaire function unit 10 creates appointment questionnaire information d3 and outputs it to the appointment creation unit 11 (step S61). This process is the same as the process in step S23 in Figure 4. Next, the DB writing unit 113 of the appointment creation unit 11 saves the appointment questionnaire information d3 and the appointment information d1 output from the appointment questionnaire AI 12 in step S61 to the appointment questionnaire AI resume DB 61 (step S62). After the process in step S62, the process of saving the appointment questionnaire information by the appointment questionnaire function unit 10 is completed. In this way, by keeping all information related to the appointment questionnaire function in the appointment questionnaire AI resume DB 61, the necessary information can be retrieved immediately when work is resumed, and the response time of processing can be increased. Furthermore, even if the process is interrupted during the generation of the appointment questionnaire information d3 and it becomes necessary to regenerate the appointment questionnaire information d3, the appointment questionnaire AI 12 can quickly and completely generate the appointment questionnaire information d3 using the information held in the appointment questionnaire AI resume DB 61. Similarly, in the process of saving each piece of information to each resume DB described below, all information related to each function is stored in the resume DB, so the same effect can be obtained.

[0190] (Processing to read medical information from the appointment booking questionnaire) Next, with reference to Figure 38, the process of reading the appointment-time medical interview information by the appointment-time medical interview function unit 10 will be explained. First, the reservation creation unit 11 of the reservation questionnaire function unit 10 determines whether the date and time of visit and email address entered on the reservation screen Sc1 (see Figure 8) have been sent from the mobile terminal 2 (step S71). Patient U1 can resume answering the reservation questionnaire, which had been interrupted, by entering the date and time of visit and email address on the reservation screen Sc1 of the mobile terminal 2.

[0191] If it is determined in step S71 that the date and time of visit and email address have not been sent (step S71 is NO), the reservation creation unit 11 repeats the determination in step S71. On the other hand, if it is determined in step S71 that the date and time of visit and email address have been sent (step S71 is YES), the data input / output unit 111 of the reservation creation unit 11 reads the reservation information d1 and the reservation questionnaire information d3 from the reservation questionnaire AI resume DB 61 and displays the reservation questionnaire information d3 on the reservation screen Sc1 (step S72). After the processing in step S72, the reservation questionnaire function unit 10 finishes reading the reservation questionnaire information.

[0192] [Resume processing by the instruction support function unit] Next, the resume processing by the instruction support function unit 20 will be explained with reference to Figures 39 and 40. Figure 39 is a flowchart showing an example of the procedure for saving instruction support information by the instruction support function unit 20, and Figure 40 is a flowchart showing an example of the procedure for reading instruction support information by the instruction support function unit 20.

[0193] (Storage of instructional support information) First, with reference to Figure 39, the process of saving instructional support information by the instructional support function unit 20 will be explained. First, the guidance support AI 22 of the guidance support function unit 20 creates guidance support information d13 and outputs it to the medical record creation unit 21 (step S81). This process is the same as the process in step S34 of Figure 10. Next, the DB writing unit 213 of the medical record creation unit 21 saves the guidance support information d13 output from the guidance support AI 22 in step S81, along with the reservation DB registration information d6, the visual examination result information d11, and the medical record DB registration information d16, to the guidance support AI resume DB 62 (step S82). After the process in step S82, the process of saving guidance support information by the guidance support function unit 20 is completed.

[0194] (Processing to retrieve instructional support information) Next, with reference to Figure 40, the process of reading instructional support information by the instructional support function unit 20 will be explained. First, the medical record creation unit 21 of the guidance support function unit 20 determines whether or not the patient's name information has been transmitted from the tablet terminal 3 (step S91). Dental hygienist U2 can resume the input work of guidance support information and treatment details that was interrupted by entering the patient U1's name on the work record screen Sc2 etc. displayed on the tablet terminal 3.

[0195] If it is determined in step S91 that the name of patient U1 has not been transmitted (step S91 is NO), the medical record creation unit 21 repeats the determination in step S91. On the other hand, if it is determined in step S91 that the name of patient U1 has been transmitted (step S91 is YES), the data input / output unit 211 of the medical record creation unit 21 reads the reservation DB registration information d6, the visual examination result information d11, the medical record DB registration information d16, and the guidance support information d13 from the guidance support AI resume DB 62, and sends the guidance support information d13 to the tablet terminal 3 to display it on the screen (step S92). After the processing in step S92, the guidance support function unit 20 finishes reading the guidance support information.

[0196] [Resume processing by the after-care function unit] Next, the resume processing by the aftercare function unit 30 will be described with reference to Figures 41 and 42. Figure 41 is a flowchart showing an example of the procedure for saving aftercare information by the aftercare function unit 30, and Figure 42 is a flowchart showing an example of the procedure for reading aftercare information by the aftercare function unit 30.

[0197] (Saving aftercare information) First, with reference to Figure 41, the aftercare information saving process by the aftercare function unit 30 will be explained. First, the aftercare AI 32 of the aftercare function unit 30 creates aftercare questionnaire information d23 and outputs it to the aftercare execution unit 31 (step S101). This process is the same as the process in step S43 in Figure 18. Next, the DB writing unit 313 of the aftercare execution unit 31 saves the aftercare questionnaire information d23 output from the aftercare AI 32 in step S101, along with the medical record information d21 and the aftercare questionnaire response information d24, to the aftercare AI resume DB 63 (step S102). After the process in step S102, the aftercare function unit 30 finishes saving the aftercare information.

[0198] (Aftercare information retrieval process) Next, with reference to Figure 42, the process of reading after-care information by the after-care function unit 30 will be explained. First, the aftercare execution unit 31 of the aftercare function unit 30 determines whether or not information has been transmitted from the mobile terminal 2 regarding patient U1's access to the aftercare questionnaire screen Sc41 (step S111). By redisplaying the aftercare questionnaire screen Sc41 on the mobile terminal 2, patient U1 can resume the interrupted aftercare questionnaire response process.

[0199] If, in step S111, it is determined that information for accessing the aftercare questionnaire screen Sc41 has not been transmitted (step S111 is NO), the aftercare execution unit 31 repeats the determination in step S111. On the other hand, if, in step S111, it is determined that information for accessing the aftercare questionnaire screen Sc41 has been transmitted (step S111 is YES), the data input / output unit 311 of the aftercare execution unit 31 reads the medical record information d21, aftercare information d23, and aftercare questionnaire response information d24 from the aftercare AI resume DB 63, and displays this aftercare information on the aftercare questionnaire screen Sc41 of the mobile terminal 2 (step S112).

[0200] Next, the aftercare execution unit 31 determines whether or not all answers to the aftercare questionnaire displayed on the aftercare questionnaire screen Sc41 have been completed (step S113). If it is determined in step S113 that there are any unfilled answers (step S113 is NO), the DB writing unit 313 of the aftercare execution unit 31 saves the medical record information d21, aftercare questionnaire information d23, and aftercare questionnaire response information d24 to the aftercare AI resume DB 63 (step S114). After processing in step S114, the aftercare execution unit 31 returns to step S113 to make a determination.

[0201] On the other hand, if it is determined in step S113 that all answers have been filled in (step S113 is YES), the DB writing unit 313 of the aftercare execution unit 31 saves the medical record information d21, aftercare questionnaire information d23, and aftercare questionnaire response information d24 as aftercare information in the aftercare DB 53 (step S115). After the processing in step S115, the aftercare function unit 30 finishes reading the aftercare information.

[0202] [Resume processing by the recall function unit] Next, the resume processing by the recall function unit 40 will be described with reference to Figures 43 and 44. Figure 43 is a flowchart showing an example of the procedure for saving recall information by the recall function unit 40, and Figure 44 is a flowchart showing an example of the procedure for reading recall information by the recall function unit 40.

[0203] (Recall information storage process) First, the recall information saving process by the recall function unit 40 will be explained with reference to Figure 43. First, the recall AI 42 of the recall function unit 40 creates recall information d35 based on the recall prompt d34 and outputs it to the recall execution unit 41 (step S121). This process is identical to the process in step S54 of Figure 26. Next, the recall execution unit 41 saves the recall information d35 output from the recall AI 42 in step S121, along with the medical record information d32 and aftercare information d33, to the recall AI resume DB 64 (step S122). After the process in step S122, the recall information saving process by the recall function unit 40 is completed.

[0204] (Recall information retrieval process) Next, with reference to Figure 44, the recall information reading process by the recall function unit 40 will be explained. First, the recall execution unit 41 of the recall function unit 40 determines whether or not the patient U1's name has been transmitted from the terminal device 4 (step S131). The dentist U3 can resume the interrupted recall information creation process by entering the name of patient U1, to whom the recall information is to be transmitted, on the screen displayed on the terminal device 4.

[0205] If it is determined in step S131 that the name of patient U1 has not been transmitted (step S131 is NO), the recall execution unit 41 repeats the determination in step S131. On the other hand, if it is determined in step S131 that the name of patient U1 has been transmitted (step S131 is YES), the data input / output unit 411 of the recall execution unit 41 reads the medical record information d32, aftercare information d33, and recall information d35 from the recall AI resume DB 64, and sends the recall information d35 to the terminal device 4 to display it on the screen (step S132). After the processing in step S132, the recall information reading process by the recall function unit 40 is completed.

[0206] In the above-described modification, the reservation-time consultation function unit 11 stores the reservation-time consultation information d3 generated by the reservation-time consultation AI 12 together with the reservation information d1 in the reservation-time consultation AI resume DB 61. Then, when the operation of answering the reservation-time consultation interrupted by the patient U1 is resumed and information regarding the patient (visiting date and time, email address) is transmitted from the mobile terminal 2, the reservation-time consultation information d3 is read from the reservation-time consultation AI resume DB 61 and transmitted to the mobile terminal 2 to be displayed on the reservation screen Sc1. Therefore, according to the modification, even when the patient U1 interrupts the reservation operation, there is no need for the reservation-time consultation AI 12 to recreate the reservation-time consultation information d3, so it is possible to prevent the occurrence of the waiting time of the patient U1 due to the recreation of the reservation-time consultation information d3.

[0207] Also, according to the resume function of the aftercare function unit 30, the aftercare consultation information d23 generated by the aftercare AI 32 is stored in the aftercare AI resume DB 63 at the time of creation. Then, when the operation of answering the aftercare consultation interrupted by the patient U1 is resumed, the aftercare consultation information d23 is read from the aftercare AI resume DB 63 and transmitted to the mobile terminal 2 to be displayed on the SNS screen Sc3. Therefore, according to the modification, even when the patient U1 interrupts the operation of answering the aftercare consultation, there is no need for the aftercare AI 32 to recreate the aftercare consultation information d23, so it is possible to prevent the occurrence of the waiting time of the patient U1 due to the recreation of the aftercare consultation information d23.

[0208] Therefore, according to the modification of the present invention, at the execution timing of reservation or aftercare outside the hospital, it is possible to shorten the time that restrains the patient U1 due to the operation of answering the consultation. If the restraint time and waiting time of the patient become long, it is predicted that the "patient experience (customer experience)" of the patient will also decrease, and such an experience is a factor that increases the dropout rate. According to the modification of the present invention, it is also possible to prevent the dropout rate of patients from the dental hospital from increasing.

[0209] Furthermore, according to the resume function of the instruction support function unit 30, the instruction support information d13 generated by the instruction support AI 22 is saved in the instruction support AI resume DB 62 at the time of creation. Then, when the recording of instruction support information to the work record screen Sc2, which had been interrupted by dental hygienist U2, is resumed, the instruction support information d13 is read from the instruction support AI resume DB 62 and sent to the tablet terminal 3, where it is displayed on the work record screen Sc2. Therefore, according to this modified example, even if dental hygienist U2 interrupts the recording of instruction support information, the instruction support AI 22 does not need to recreate the instruction support information d15, thus preventing waiting time for dental hygienist U2 due to the recreation of instruction support information d13.

[0210] Furthermore, according to the resume function of the recall function unit 40, the recall information d35 generated by the recall AI 42 is stored in the recall AI resume DB 64 at the time of its creation. Then, when the selection of patient U1 to be sent the aftercare questionnaire, which had been interrupted by dentist U3, is resumed, the recall information d35 is read from the recall AI resume DB 64 and sent to the terminal device 4, where it is displayed on the terminal device 4's screen. Therefore, according to this modification, even if dentist U3 interrupts the selection of patient U1 to be sent the aftercare questionnaire, the recall AI 42 does not need to recreate the recall information d35, thus preventing waiting time for dentist U3 due to the recreation of the recall information d35.

[0211] Dentists (U3) and dental hygienists (U2) often have to interrupt their work to attend to patients. In such cases, the resume function related to modification allows them to quickly return to the interrupted work.

[0212] Furthermore, when dentist U3 or dental hygienist U2 is handling an emergency or performing an unscheduled procedure, they may hand over the work to another dentist or dental hygienist. In this case, the modified version can prevent situations where the person taking over the work has to start over from the beginning or restart the work from the wrong point. Therefore, it can also prevent errors or omissions in recording guidance and support information, and errors in selecting patients to whom recall information is sent, due to insufficient communication or misinterpretation during the handover.

[0213] Furthermore, within the hospital, dentists U3 and dental hygienists U2 may initially enter only the "items" into the medical record or work record screen Sc2 in order to determine the billing amount, and then enter the details later. In this case, without a resume function, there is a possibility that the information entered before the work was interrupted and the information entered after the work was resumed will not be consistent. However, according to the modified version of the present invention, information such as guidance support information d13 by AI such as guidance support AI22 will not be recreated when work is interrupted, and the information from before the work was interrupted will be reliably displayed after work is resumed. As a result, dentists U3 and dental hygienists U2 can confidently and easily interrupt their work for the purpose of determining the billing amount. This can further reduce the waiting time for patient U1 to pay.

[0214] In the modified examples described above, reservation information d1, visual examination result information d11, and aftercare questionnaire response information d24 are automatically recorded in the reservation questionnaire AI resume DB61, guidance support AI resume DB62, and aftercare AI resume DB63, respectively, when character input is detected. However, the present invention is not limited to these examples. For example, a "resume button" to instruct the interruption of work may be provided on the reservation screen Sc1 (see Figure 8) where reservation information d1 is entered, the work record screen Sc2 (see Figure 16) where visual examination result information d11 is entered, the aftercare questionnaire screen Sc41 (see Figure 24), or the aftercare questionnaire screen Sc42 (see Figure 25). When the press of this resume button is detected, the reservation information d1, visual examination result information d11, or aftercare questionnaire response information d24 may be saved to the respective resume DBs.

[0215] Furthermore, while the above-described embodiment shows an example in which the appointment-time consultation AI 12, guidance support AI 22, aftercare AI 32, and recall AI 42 are provided within Server 1, the present invention is not limited to this. AIs provided by service providers, etc., may be used as each of these AIs. In this case, a single AI may be used that does not separate the functions of the appointment-time consultation AI 12, guidance support AI 22, aftercare AI 32, and recall AI 42.

[0216] Furthermore, while the above-described embodiment cited an example where the medical record transcribed by the medical record creation unit 21 is a medical record (electronic medical record) in dental practice, the present invention is not limited to this. The medical record according to the present invention may be applied to medical records for medical treatment by doctors, nurses, physical therapists, judo therapists, etc. Moreover, the oral advisor system of the present invention is applicable not only to dentistry but also to various medical fields such as medicine, pharmacy, and veterinary medicine.

[0217] Furthermore, while the above-described embodiment shows an example in which the appointment-time consultation AI12, guidance support AI22, aftercare AI32, and recall AI42 are all constructed using AI, the present invention is not limited to this. Some or all of these functional units may be constructed using methods other than AI, such as programming.

[0218] Furthermore, the oral advisor system 100 according to this embodiment is configured so that the aftercare function unit 30 can appropriately provide aftercare to patients. Therefore, the oral advisor system 100 according to this embodiment is configured to include all components: a pre-appointment consultation function unit 10, a guidance support function unit 20, and an aftercare function unit 30. However, from the viewpoint of enabling the creation of pre-appointment consultations, guidance support for dental hygienists, and recalls for patients, the oral advisor system according to the present invention may also adopt the following configuration.

[0219] (1) A medical appointment questionnaire creation instruction unit generates and outputs an instruction to create a medical appointment questionnaire, which is an instruction to create a medical appointment questionnaire, which includes at least patient attribute information and information on the reason for the patient's visit, to a learning model that has learned examples of examination content and treatment content for patient cases. It includes an input / output unit that transmits the appointment questionnaire, generated in a learning model based on instructions for creating an appointment questionnaire, to a terminal device operated by the patient. Oral advisor system.

[0220] (2) A guidance support information creation instruction unit generates and outputs guidance support information creation instructions that cause a learning model, which has learned examples of examination and treatment content for patient cases, to create guidance support information, which is information that supports guidance for patients, based on information that includes at least patient attribute information and information on the reason for the patient's visit to the hospital, It includes an input / output unit that transmits instructional support information generated in the learning model based on instructional support creation instructions to a patient operation terminal device operated by the patient. Oral advisor system.

[0221] Furthermore, the embodiments described above are intended to explain the configuration of the device (server, tablet terminal, terminal device) and system (oral advisor system) in detail and specifically in order to make the present invention easier to understand, and are not necessarily limited to those comprising all the configurations described.

[0222] Furthermore, the control lines or information lines shown as solid lines or arrows in Figures 1 and 2 are those deemed necessary for explanation and do not necessarily represent all control lines or information lines in the actual product. In reality, it can be assumed that almost all components are interconnected. [Explanation of symbols]

[0223] 1…Server, 2…Mobile terminal, 3…Tablet terminal, 4…Terminal device, 10…Reservation interview function unit, 11…Reservation creation unit, 12…Reservation interview AI, 13…DB writing unit, 20…Guidance support function unit, 21…Medical record creation unit, 22…Guidance support AI, 23…DB writing unit, 30…Aftercare function unit, 31…Aftercare execution unit, 32…Aftercare AI, 33…DB writing unit, 40…Recall function unit, 41…Recall execution unit, 42…Recall AI, 51…Reservation DB, 52…Medical record DB, 53…Aftercare DB 61... AI resume database for appointment-time medical interview, 62... AI resume database for guidance support, 63... AI resume database for aftercare, 64... AI resume database for recall, 100... Oral advisor system, 111... Data input / output unit, 112... Prompt creation unit, 113... DB writing unit, 211... Data input / output unit, 212... Prompt creation unit, 213... DB writing unit, 311... Data input / output unit, 312... Prompt creation unit, 313... DB writing unit, 411... Data input / output unit, 412... Prompt creation unit

Claims

1. A recall AI that includes a learning model trained on dental patient cases, A recall information creation instruction unit generates a recall information creation instruction for creating recall information that prompts the patient to make an appointment to visit the hospital, based on information that includes at least patient attribute information and information about the medical examination performed on the patient, and outputs the recall information creation instruction to the recall AI. The system includes a recall information input / output unit that transmits the recall information generated by the recall AI based on the recall information creation instruction to a patient operation terminal device operated by the patient. Oral advisor system.

2. The recall information creation instruction unit includes in the recall information creation instruction the patient's medical record information and an instruction to generate a document encouraging the patient to visit the hospital based on the contents of the medical record. The oral advisor system according to claim 1.

3. The recall information creation instruction unit instructs the generation of a message to encourage the patient to come to the clinic, which conveys the possibility that the patient's oral condition may have changed due to the long interval between consultations. The oral advisor system according to claim 2.

4. The recall information creation instruction unit instructs the generation of a document that encourages the patient to come to the hospital, informing the patient that leaving the symptoms untreated poses a risk to their health. The oral advisor system according to claim 2.

5. The learning model is a large-scale language model, and the recall information creation instructions are composed of prompts. The oral advisor system according to claim 2.

6. The recall information creation instruction unit includes in the recall information creation instruction information information of a post-examination interview, which is a medical interview conducted after the examination of the patient, and an instruction to generate text based on the content of the post-examination interview. The oral advisor system according to claim 2.

7. A post-examination interview AI that includes a learning model trained on dental patient cases, A post-examination questionnaire creation instruction unit generates and outputs instructions for creating a post-examination questionnaire based on the attribute information of the patient, The system further comprises a post-examination questionnaire information input / output unit that transmits the post-examination questionnaire, generated by the post-examination questionnaire AI based on the post-examination questionnaire creation instruction, to the patient operation terminal device. The oral advisor system according to claim 6.

8. The learning model is a large-scale language model, and the post-examination questionnaire creation instructions are composed of prompts. The oral advisor system according to claim 7.

9. The system further comprises a recall information resume database that temporarily stores the recall information generated by the recall AI, The recall information input / output unit reads the recall information from the recall information resume database and transmits it to the dentist's terminal device when the recall information generation process on the dentist's terminal device, which had been interrupted, is resumed. The oral advisor system according to claim 2.

10. A method for generating recall information using an oral advisor system comprising a recall AI including a learning model that has learned dental cases, a recall information creation instruction unit, and a recall information input / output unit, The recall information creation instruction unit generates a recall information creation instruction for generating recall information, which is information prompting the patient to make an appointment to visit the hospital, based on information that includes at least patient attribute information and information about the medical examination performed on the patient, and outputs the recall information creation instruction to the recall AI. The recall information input / output unit includes a procedure for transmitting the recall information generated in the recall AI based on the recall information creation instruction to a patient operation terminal device operated by the patient. Method for generating recall information.

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