Information processing device, information processing method, and program

Abstract

Using AI to facilitate communication among families of patients battling illness. [Solution] The information processing device communicates with terminal devices used by multiple members, including a patient requiring treatment. The information processing device acquires conversation data from each member's terminal device, showing the conversation between the AI ​​model and each member. Based on the conversation data, the information processing device creates analysis data evaluating each member's feelings towards treatment. Based on the analysis data, the information processing device creates advice to promote communication among family members and presents it to the terminal device.

Description

Technical Field

[0001] This disclosure relates to a technology for promoting communication among family members.

Background Art

[0002] In the life of fighting a disease, not only the patient himself / herself but also the family often don't know about the treatment. Also, due to the differences in age and daily busyness of each family member, there may be a gap in awareness of treatment, and there is a risk that the relationship within the family will deteriorate. Patent Document 1 describes a system that can suppress the dilution of communication in a family group by using a virtual space.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, the technology of AI (Artificial Intelligence) has evolved rapidly and is being used in various fields.

[0005] One of the objectives of this disclosure is to promote communication among family members with a disease-stricken patient by using AI.

Means for Solving the Problems

[0006] To solve the above problems, from one aspect of this disclosure, an information processing apparatus includes communication means for communicating with terminal devices respectively used by a plurality of members including a patient who needs treatment, conversation data acquisition means for acquiring conversation data showing conversations between an AI model and each member from the terminal devices respectively used by each member, Based on the aforementioned conversation data, a means for creating analytical data is provided to create analytical data that evaluates each member's feelings towards treatment. Based on the aforementioned analysis data, a means for creating advice to promote communication among family members, A presentation means for presenting the aforementioned advice to the terminal device, It is equipped with.

[0007] From another perspective of this disclosure, the information processing method performed by the information processing device is: It communicates with terminal devices used by multiple members, including patients who require treatment. Conversation data showing the conversation between the AI ​​model and each member is acquired from the terminal device used by each member. Based on the aforementioned conversation data, we created analytical data to evaluate each member's feelings towards treatment. Based on the aforementioned analysis data, we created advice to promote communication among family members. The aforementioned advice is presented to the terminal device.

[0008] In yet another aspect of this disclosure, the program is It communicates with terminal devices used by multiple members, including patients who require treatment. Conversation data showing the conversation between the AI ​​model and each member is acquired from the terminal device used by each member. Based on the aforementioned conversation data, we created analytical data to evaluate each member's feelings towards treatment. Based on the aforementioned analysis data, we created advice to promote communication among family members. The computer is made to perform the process of presenting the aforementioned advice to the terminal device. [Effects of the Invention]

[0009] According to this disclosure, AI can be used to facilitate communication among families of patients battling illness. [Brief explanation of the drawing]

[0010] [Figure 1] Shows an example of the schematic configuration of a communication promotion system. [Figure 2] It is a schematic diagram showing an example of the interaction between an AI model and each member. [Figure 3] Shows an example of the hardware configuration of a server and a family terminal. [Figure 4] It is a block diagram showing an example of the functional configuration of a server. [Figure 5] It is a diagram for explaining a log acquisition application. [Figure 6] It is a table for explaining three indicators. [Figure 7] It is an example of a problem related to treatment. [Figure 8] It is an example of analysis data. [Figure 9] It is an example of advice. [[ID=***]] [Figure 10] It is an example of a plan. [Figure 11] It is a flowchart of communication promotion processing. [Figure 12] It is an example of feedback. [Figure 13] It is a block diagram showing the functional configuration of the information processing apparatus according to the second embodiment. [Figure 14] It is a flowchart of the processing by the information processing apparatus according to the second embodiment.

Mode for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. [First Embodiment] (Overall Configuration) FIG. 1 is an example of the schematic configuration of a communication promotion system 100 to which the information processing apparatus of the present disclosure is applied. The communication promotion system 100 is a system that promotes communication among a plurality of members including a family member with a disease requiring treatment, using an AI model. (Overall Configuration)

[0012] ## In the communication facilitation system 100 shown in Figure 1, Server 1, Family Terminal 2a, Family Terminal 2b, Family Terminal 2c, and Family Terminal 2d are connected to each other via a network 5 such as the Internet. Family Terminals 2a to 2d are collectively referred to as Family Terminal 2.

[0013] In this embodiment, as an example, the family consists of four members A to D, with member A using family terminal 2a, member B using family terminal 2b, member C using family terminal 2c, and member D using family terminal 2d. Member B is the patient requiring treatment. Family terminals 2 are smartphones, tablets, PCs, etc., used by each member, and receive text or voice messages from server 1 for the AI ​​model to converse with the member, and send text or voice messages from the member to server 1 for the member to converse with the AI ​​model. Family terminals 2a to 2d are examples of terminal devices in this disclosure.

[0014] Server 1 is an information processing device that processes, stores, and transmits various types of data and has an AI model. Server 1 transmits text or audio of the AI ​​model conversing with members to family terminal 2, and receives text or audio of members conversing with the AI ​​model from family terminal 2. Server 1 also creates analysis data based on the conversations between the AI ​​model and members, and presents advice to the members via family terminal 2 to promote communication among family members based on the analysis data. Server 1 is connected to a registration database (hereinafter referred to as "DB") 31, a conversation storage DB 32, and an analysis DB 33, which will be described later. Server 1 may be a virtual server located in a cloud environment. Server 1 is an example of an information processing device in this disclosure.

[0015] (Overview of operation) Figure 2 is a schematic diagram showing an example of the interaction between the AI ​​model on Server 1 and each member in the communication facilitating system 100. The AI ​​model is a Large Language Model (LLM) capable of understanding multimodal information and converses with each member via Family Terminal 2. While conventional systems involve "one-to-one interaction between AI and human," this disclosure is characterized by "one-to-many interaction between AI and human (all family members)" and by its focus on facilitating communication "among multiple (family) members."

[0016] First, the AI ​​model converses with each member, including the patient, via family terminal 2. Specifically, as shown in Figure 2(a), if member A asks the AI ​​model, "What are the effects of the XX I'm currently taking?", the AI ​​model will provide an answer explaining the effects of XX based on the information stored in various databases. Also, if member C asks the AI ​​model, "Are there any side effects?", the AI ​​model will provide an answer explaining the side effects of the XX currently being taken, based on the information stored in various databases.

[0017] Next, the AI ​​model creates analytical data that evaluates each member's awareness and feelings about treatment based on the conversation, and then creates and presents advice to promote communication among family members based on this analytical data. Specifically, as shown in Figure 2(b), the AI ​​model creates analytical data that evaluates each member's level of knowledge, interest, and concern regarding treatment. Based on this analytical data, the AI ​​model might, for example, advise member D, who has the highest level of knowledge, on how to talk to member A, who has the lowest level of knowledge.

[0018] With the guidance of the AI ​​model, as shown in Figure 2(c), member D begins to speak to member A, thereby promoting communication within the family. Increased communication within the family can help eliminate disparities in awareness regarding treatment within the family.

[0019] (Hardware configuration) Figure 3(a) is a block diagram showing an example of the hardware configuration of Server 1. As shown in the figure, Server 1 comprises an interface 11, a processor 12, memory 13, a recording medium 14, a display unit 15, and an input unit 16. These components, along with the registration DB 31, conversation storage DB 32, and analysis DB 33, are interconnected via a bus.

[0020] Interface 11 exchanges data with family terminal 2. Interface 11 is used to receive text or voice messages from family terminal 2 for members to converse with the AI ​​model, and to send text or voice messages from the AI ​​model to family terminal 2 for members to converse with.

[0021] Processor 12 is a computer such as a CPU (Central Processing Unit) that controls the entire server 1 by executing pre-prepared programs. Processor 12 can be a CPU, GPU (Graphics Processing Unit), DSP (Digital Signal Processor), MPU (Micro Processing Unit), FPU (Floating Point Number Processing Unit), PPU (Physics Processing Unit), TPU (Tensor Processing Unit), quantum processor, microcontroller, or a combination of these.

[0022] Memory 13 consists of ROM (Read Only Memory), RAM (Random Access Memory), and other components. Memory 13 stores programs executed by the processor 12. Memory 13 is also used as working memory while the processor 12 is executing various processes.

[0023] The recording medium 14 is a non-volatile, non-temporary recording medium such as a disk-shaped recording medium or semiconductor memory, and is configured to be detachable from the server 1. The recording medium 14 stores various programs that the processor 12 executes. When the server 1 performs communication acceleration processing, the programs stored in the recording medium 14 are loaded into the memory 13 and executed by the processor 12.

[0024] The display unit 15 displays a predetermined image, for example, using an LCD (Liquid Crystal Display). The input unit 16 is used by the operator managing server 1, and can be a keyboard, mouse, touch panel, etc.

[0025] Figure 3(b) is a block diagram showing an example of the hardware configuration of family terminal 2. As shown in the figure, family terminal 2 includes an interface 21, a processor 22, memory 23, recording medium 24, display unit 25, and input unit 26.

[0026] Interface 21 exchanges data with Server 1 via Network 5. Interface 21 is used when members send text or voice messages to Server 1 for conversation with the AI ​​model, and when the AI ​​model receives text or voice messages from Server 1 for conversation with the members.

[0027] The processor 22 is a computer such as a CPU, and controls the entire family terminal 2 by executing a pre-prepared program. The processor 22 can be a CPU, GPU, DSP, MPU, FPU, PPU, TPU, quantum processor, microcontroller, or a combination thereof.

[0028] Memory 23 is composed of ROM, RAM, etc. Memory 23 stores programs executed by the processor 22. Memory 23 is also used as working memory while the processor 22 is executing various processes.

[0029] The recording medium 24 is a non-volatile, non-temporary recording medium such as a disk-shaped recording medium or semiconductor memory, and is configured to be detachable from the family terminal 2. The recording medium 24 stores various programs executed by the processor 22. The display unit 25 is, for example, an LCD, which displays a predetermined image. The input unit 26 is a touch panel or the like, which is used when the user performs a predetermined operation.

[0030] The registration database 31 stores, either in advance or as needed, the following as registration data: basic information for each member, browser search log information for each member, patient claims data, adverse event statistics, open claims data, medical terminology data, welfare system information, and insurance information.

[0031] The conversation storage DB 32 stores, for each member, the text or audio that the AI ​​model presents to family terminals 2a to 2d, and the text or audio that is obtained from family terminals 2a to 2d, as conversation data between the AI ​​model and each member. For example, the conversation storage DB has separate databases for members A, B, C, and D, and stores text or audio data showing the interaction between the AI ​​model and each member in the database corresponding to each member.

[0032] Analysis DB33 stores the analysis data. Furthermore, the analysis data is updated in Analysis DB33 whenever it is updated.

[0033] (Functional Configuration) Figure 4 is a block diagram showing an example of the functional configuration of Server 1. Server 1 includes a registration DB 31, a conversation storage DB 32, and an analysis DB 33. Functionally, Server 1 also includes a family data registration unit 41, a search log extraction unit 42, a search log registration unit 43, a claims data registration unit 44, an adverse event statistics data registration unit 45, a claims open data registration unit 46, a medical terminology data registration unit 47, a family data acquisition unit 48, a search log acquisition unit 49, a claims data acquisition unit 50, an adverse event statistics data acquisition unit 51, a claims open data acquisition unit 52, a medical terminology data acquisition unit 53, a conversation data registration unit 54, a conversation data acquisition unit 55, an analysis data registration unit 56, an analysis data acquisition unit 57, an AI model, a text-to-speech presentation unit 61, and a text-to-speech acquisition unit 62. The AI ​​model functions as an analysis data creation unit 71, a problem creation unit 72, an advice creation unit 73, and a plan creation unit 74.

[0034] The family data registration unit 41, search log extraction unit 42, search log registration unit 43, claims data registration unit 44, adverse event statistics data registration unit 45, claims open data registration unit 46, medical terminology data registration unit 47, family data acquisition unit 48, search log acquisition unit 49, claims data acquisition unit 50, adverse event statistics data acquisition unit 51, claims open data acquisition unit 52, medical terminology data acquisition unit 53, conversation data registration unit 54, conversation data acquisition unit 55, analysis data registration unit 56, analysis data acquisition unit 57, AI model, text-to-speech presentation unit 61, and text-to-speech acquisition unit 62 are realized by the processor 12 executing a program.

[0035] The family data registration unit 41 registers the four basic pieces of information for each family member as registration data in the registration DB 31, via a predetermined operation using the My Number Card of each family member and a family terminal 2. The four basic pieces of information are name, address, date of birth, and gender.

[0036] The search log extraction unit 42 reads the search logs of each member from the log acquisition application 40 installed on each of the family terminals 2a to 2d, and extracts the search logs related to each member's treatment.

[0037] Figure 5 illustrates the log acquisition application 40. The log acquisition application 40 is an application that extracts search logs related to treatment from browser search logs on smartphones and other devices used by individual members of a family, and loads them into an AI model as real-time registration data. The procedure for using the log acquisition application 40 is as follows: First, each member installs the log acquisition application 40 on their respective family terminals 2a to 2d. Next, each member operates their respective family terminals 2a to 2d to read the patient's (in this embodiment, member B's) My Number Card, thereby registering the patient's medical claim data in the log acquisition application 40. Here, medical claim data refers to the medical fee statement submitted by a medical institution to the insurer, and information about the patient's treatment can be obtained from this medical claim data.

[0038] Next, each member operates their respective family terminal 2a to 2d to enable log acquisition for the log acquisition application 40. As a result, the log acquisition application 40 extracts and acquires logs related to the registered medical claim from the logs searched by each member, such as disease name, medications being taken, and logs regarding assistance and care, as shown in Figure 5.

[0039] The search log registration unit 43 acquires search logs for treatment-related information extracted by the search log extraction unit 42 and registers them as registration data in the registration DB 31 for each member as needed.

[0040] The claims data registration unit 44 registers claims data as registered data in the registration DB 31 via a predetermined operation using the patient's My Number Card and a family terminal 2. Alternatively, claims data may be registered in the registration DB from the log acquisition application 40.

[0041] The adverse event statistics data registration unit 45 obtains adverse event statistics data from the adverse event database of the Pharmaceuticals and Medical Devices Agency and registers it as registration data in the registration database 31.

[0042] The claims open data registration unit 46 retrieves claims open data from the Ministry of Health, Labour and Welfare's NDB (National Database) and registers it as registration data in the registration database 31. The NDB is a claims information and specific health checkup information database, and is a medical database provided by the Ministry of Health, Labour and Welfare.

[0043] The medical terminology data registration unit 47 retrieves medical terminology data from the medical terminology database of a medical terminology website and registers it as registration data in the registration database 31. The medical terminology data registration unit 47 may also retrieve welfare system information, such as the high-cost medical care reimbursement system and medical expense deductions, and insurance information from the Ministry of Health, Labour and Welfare website, and register it as registration data in the registration database 31.

[0044] The family data acquisition unit 48 acquires four basic pieces of information about the family members from the registration DB 31 and feeds them into the AI ​​model.

[0045] The search log acquisition unit 49 acquires search logs from the registration DB 31 for treatment-related information made by each member and provides them to the AI ​​model.

[0046] The claims data acquisition unit 50 acquires patient claims data from the registration DB 31 and provides it to the AI ​​model.

[0047] The adverse event statistics data acquisition unit 51 acquires adverse event statistics data from the registered DB 31 and provides it to the AI ​​model.

[0048] The claims open data acquisition unit 52 acquires claims open data from the registration DB 31 and provides it to the AI ​​model.

[0049] The medical terminology data acquisition unit 53 acquires medical terminology data from the registration DB 31 and provides it to the AI ​​model. The medical terminology data acquisition unit 53 may also acquire welfare system information and insurance information from the registration DB 31 and provide them to the AI ​​model.

[0050] The AI ​​model engages in conversations with each individual member of the family. The topics of these conversations include "anxiety about battling illness" and "the situation of other family members." The conversation data registration unit 54 registers the frequency and content of conversations between the AI ​​model and each member as conversation data in the conversation storage DB 32. Specifically, the conversation data registration unit 54 acquires conversation data, along with time information, the text or audio that the AI ​​model presents to family terminals 2a-2d for conversations with each member, and the text or audio acquired from family terminals 2a-2d. The conversation data registration unit 54 registers the conversation data for each member in the conversation storage DB 32 as it becomes available.

[0051] The conversation data acquisition unit 55 acquires conversation data from the conversation storage DB 32 and provides it to the AI ​​model.

[0052] The analysis data registration unit 56 stores the analysis data generated by the AI ​​model in the analysis DB 33. The analysis data acquisition unit 57 reads the analysis data from the analysis data DB 33 as needed and provides it to the AI ​​model.

[0053] The AI ​​model functions as an analysis data creation unit 71, a problem creation unit 72, an advice creation unit 73, and a plan creation unit 74.

[0054] The analysis data creation unit 71 creates analysis data that evaluates each member's feelings towards treatment based on registered data and conversation data. Specifically, the analysis data creation unit 71 creates analysis data that evaluates each member's feelings towards treatment based on registered data registered in the registration DB 31 and conversation data registered in the conversation storage DB 32. In this embodiment, as an example, the analysis data creation unit 71 calculates a numerical value optimized for evaluating each member's feelings towards treatment based on search logs and conversation data.

[0055] Figure 6 is a table illustrating three indicators for evaluating feelings towards treatment. As shown in Figure 6, the evaluation of feelings consists of three indicators: knowledge level, which represents the degree of understanding about the treatment; interest level, which represents the degree of interest in the treatment; and worry level, which represents the degree of anxiety about the treatment.

[0056] Knowledge level is assessed using conversational data as judgment information. Knowledge level is evaluated by having an AI model generate questions related to treatment, and then assigning scores to members based on their responses to these questions during conversations. Figure 7 shows an example of a treatment-related question. As shown in Figure 7, knowledge level assessment questions include those asking about the efficacy and side effects of medications being taken. The more accurately a member answers these knowledge level assessment questions during their conversation with the AI ​​model, the higher their knowledge level assessment becomes.

[0057] Figure 8 shows an example of analysis data. In the analysis data shown in Figure 8, the evaluation index is expressed as a relative value within the family, represented by an integer from 1 to 4. 1 is the lowest evaluation index, and 4 is the highest. A lower knowledge level index indicates less knowledge, while a higher index indicates more knowledge. Specifically, the analysis data creation unit 71 calculates one of the values ​​from 1 to 4 as the knowledge level evaluation index for each member based on the conversation data. Note that the evaluation index is not limited to these values ​​and can be set arbitrarily.

[0058] The level of interest is determined using registered data as judgment information. The level of interest is evaluated by assigning a score based on the search frequency in the search log. Specifically, the analysis data creation unit 71 calculates the search frequency for treatment-related information for each member from each member's search log, and based on the search frequency, calculates one of the values ​​from 1 to 4 as an evaluation index for each member's level of interest. A lower value on the evaluation index of the level of interest indicates less interest, and a higher value indicates higher interest.

[0059] The level of worry is assessed using conversational data as judgment information. The level of worry is evaluated by having an AI model generate questions to assess the degree of worry regarding treatment, and then addressing the content of these questions during conversations with members and assigning scores. Examples of questions used to assess the level of worry include those asking whether anxiety about treatment is the reason why members are not getting enough sleep or food, as shown in Figure 7. The more negative a member's answers are to the questions assessing the level of worry during conversations with the AI ​​model, the lower their level of worry will be. A lower level of the worry level index indicates more worry, while a higher level indicates less worry. Specifically, the analysis data creation unit 71 calculates one of four numerical values ​​(1 to 4) as the worry level index for each member based on the conversational data.

[0060] The question creation unit 72 creates knowledge level assessment questions and worry level assessment questions, as shown in Figure 7. Specifically, the question creation unit 72 identifies the treatment the patient is receiving based on the medical claims data and creates knowledge level assessment questions. The question creation unit 72 also creates worry level assessment questions to investigate the degree of worry regarding the treatment. The created questions are presented to the family terminal 2 during a conversation with the member by the text-to-speech presentation unit 61, which will be described later.

[0061] The advice creation unit 73 creates advice to promote communication among family members based on registered data, conversation data, and analysis data. For example, the advice may include having members with higher levels of knowledge, interest, and concern reach out to members with lower levels.

[0062] Figure 9 shows an example of advice. According to the analysis data shown in Figure 8, member D has the highest knowledge level, "4," while member A has the lowest level, "1." Therefore, as shown in Figure 9, the advice generation unit 73 creates advice for member D such as, "Mr. A may not fully understand the medication XXX he is taking. We recommend that you have a conversation with him." The created advice is presented to the family terminal 2d during the conversation with the member by the text-to-speech presentation unit 61, which will be described later.

[0063] Furthermore, according to the analysis data shown in Figure 8, member B has the highest level of interest, "4," while member C has the lowest level, "1." Therefore, as shown in Figure 9, the advice generation unit 73 generates advice for member B such as, "Recently, C has been searching less frequently for information about treatment. We recommend that you have a conversation about treatment." The generated advice is then presented to the family terminal 2b during the conversation with the member by the text-to-speech presentation unit 61, which will be described later.

[0064] Furthermore, according to the analysis data shown in Figure 8, member A has the highest level of worry, "4," and member B has the lowest level, "1." Therefore, as shown in Figure 9, the advice generation unit 73 creates advice for member B such as, "Ms. A may be excessively worried about the treatment. We recommend that you have a conversation to reduce stress." The created advice is then presented to the family terminal 2b by the text-to-speech presentation unit 61, which will be described later.

[0065] The planning unit 74 creates a plan for the systems that the family can use based on the registered data. Specifically, the planning unit 74 checks the registered data to see if there are any systems that the family can use, and if there are, it creates a plan for using those systems.

[0066] Figure 10 shows an example of a plan. Specifically, Figure 10(a) is an example of a plan that suggests to a family the use of the high-cost medical expense reimbursement system. As shown in Figure 10(a), the AI ​​model creates a plan based on medical claim data, welfare system information, and insurance information, such as, "Your out-of-pocket medical expenses this month exceed the self-pay limit. You can receive a refund of XX yen by applying at the XX counter." The created plan may be presented to all family terminals 2a to 2d by the text-to-speech presentation unit 61 described later, or it may be presented to one or more of the pre-configured family terminals 2a to 2d.

[0067] Figure 10(b) shows an example of a plan to propose medical expense deductions to a family. As shown in Figure 10(b), the AI ​​model creates a plan based on medical claim data, welfare system information, and insurance information, stating, "Your medical expenses paid last year exceeded 100,000 yen, so you are eligible for a medical expense deduction. By filing a tax return with the tax office, you can receive an income deduction of XX yen." The created plan may be presented to all family terminals 2a-2d by the text-to-speech display unit 61 described later, or it may be presented to one or more of the pre-configured family terminals 2a-2d.

[0068] The text-to-voice presentation unit 61 transmits and presents text or voice data for the AI ​​model to converse with the member to the family terminal 2. The text-to-voice acquisition unit 62 acquires text or voice data from the member to converse with the AI ​​model from the family terminal 2.

[0069] The text-to-speech presentation unit 61 engages in conversations in response to questions from members, and also presents problems created by the problem creation unit 72 to the family terminal 2 within the conversation. In addition, the text-to-speech presentation unit 61 presents advice created by the advice creation unit 73 and plans created by the plan creation unit 74 to one or more of the family terminals 2a to 2d used by the member to whom the advice is presented.

[0070] In the above configuration, the search log acquisition unit 49, the claims data acquisition unit 50, the conversation data acquisition unit 55, the analysis data creation unit 71, the problem creation unit 72, the advice creation unit 73, the plan creation unit 74, and the text-to-speech presentation unit 61 of Server 1 are examples of the search log acquisition means, claims data acquisition means, conversation data acquisition means, analysis data creation means, problem creation means, advice creation means, plan creation means, and presentation means, respectively, according to the present disclosure.

[0071] (Communication Facilitation Process) Next, we will explain the communication acceleration process performed by Server 1. Figure 11 is a flowchart of the communication acceleration process performed by Server 1. This process is achieved by the processor 12 shown in Figure 2 executing a pre-prepared program.

[0072] First, Server 1 retrieves registration data and conversation data from the conversation storage DB 32 (Step S101). Next, Server 1 uses an AI model to create analysis data that evaluates each member's feelings towards treatment based on the registration data and conversation data (Step S102). Next, Server 1 uses an AI model to create advice to promote communication among family members based on the registration data, conversation data, and analysis data (Step S103). Next, Server 1 presents the advice to one of the family terminals 2a to 2d used by the designated member (Step S104). Thus, the communication promotion process is completed.

[0073] Furthermore, the AI ​​models used in the analysis data creation unit 71, the problem creation unit 72, the advice creation unit 73, the plan creation unit 74, and the text-to-speech presentation unit 61 may be the same AI model, or different AI models may be used depending on the specifications and cost, provided that data can be obtained from various databases.

[0074] According to this communication-facilitating system 100, Server 1 can use an AI model to provide advice and facilitate communication among families of patients battling illness. Furthermore, by utilizing analytical data that evaluates the feelings of each family member regarding treatment when creating advice, disparities in awareness regarding treatment can be resolved through communication within the family.

[0075] Furthermore, Server 1 can use an AI model based on registered data to plan and present welfare programs available to the family. This allows the family to easily learn about welfare programs such as the high-cost medical care reimbursement system and medical expense deductions. The family can also easily understand the amount of reimbursement or income tax deductions they will receive by utilizing these welfare programs.

[0076] [First variation] After Server 1 provides advice to facilitate communication among family members, if the analysis data is updated, it may create feedback data based on the updated analysis data and present it to one of the family terminals 2a to 2d used by the designated member.

[0077] Figure 12 shows an example of feedback. As shown in Figure 12, Server 1 first presents advice to Family Terminal 2d, such as "Please teach A about XX," based on the analysis data before communication, as a suggestion for Member D, who has the highest knowledge level. Member D responds to the advice by speaking to Member A and having a conversation about XX using a communication tool of their choice. Subsequently, when the analysis data is updated, Server 1 creates feedback data on the change in Member A's knowledge level based on the updated analysis data and presents it to Family Terminal 2d. Specifically, as shown in Figure 12, Server 1 creates feedback data such as "A's knowledge level has increased" and presents it to Family Terminal 2d, informing Member D that Member A's knowledge level has increased as a result of the conversation with Member D.

[0078] In this way, by presenting feedback data, each member of the family can realize the importance of communication and maintain their motivation to converse. Note that Server 1 in this modified example is just one example of the presentation method described in this disclosure.

[0079] [Second variation] Server 1 may, at any time, register information about subscription services such as music and movies used by the family in the registration database DB 31 as registration data. This allows the AI ​​model to inform a designated member during a conversation about other members who are using similar content. Thus, it can stimulate communication among family members.

[0080] Furthermore, by having families or groups participate in support services such as health points and linking with Server 1, the AI ​​model can encourage motivation and competition among the members.

[0081] [Third variation] In the first embodiment described above, the communication promotion system 100 is applied to promoting communication among family members, but it is not limited to this and may also be applied to promoting communication among students. In addition to the conventional use of the AI ​​model to teach each student, the AI ​​model, which is familiar with the characteristics of each student (personality, academic performance), can, for example, encourage a student who is good at math to teach a student who is not good at math. Thus, communication among students can be made more active, and new connections that transcend grade levels and genders can be expected.

[0082] [Second Embodiment] Figure 13 is a block diagram showing the functional configuration of the information processing device of the second embodiment. The information processing device 90 includes a communication means 91, a conversation data acquisition means 92, an analysis data creation means 93, an advice creation means 94, and a presentation means 95.

[0083] Figure 14 is a flowchart of the processing performed by the information processing device 90. The communication means 91 communicates with terminal devices used by multiple members, including a patient requiring treatment (step S201). The conversation data acquisition means 92 acquires conversation data showing the conversation between the AI ​​model and each member from the terminal device used by each member (step S202). The analysis data creation means 93 creates analysis data evaluating each member's feelings towards treatment based on the conversation data (step S203). The advice creation means 94 creates advice to promote communication among family members based on the analysis data (step S204). The presentation means 95 presents the advice to the terminal device (step S205).

[0084] According to the information processing device 90 of the second embodiment, AI can be used to facilitate communication among families of patients battling illness.

[0085] In addition, some or all of the above embodiments (including modifications, the same applies hereinafter) may also be described as follows, but are not limited to the following.

[0086] (Note 1) A communication means for communicating with terminal devices used by multiple members, including patients requiring treatment, A means for acquiring conversation data that shows conversations between the AI ​​model and each member, by obtaining conversation data from the terminal device used by each member. Based on the aforementioned conversation data, a means for creating analytical data is provided to create analytical data that evaluates each member's feelings towards treatment. Based on the aforementioned analysis data, a means for creating advice to promote communication among family members, A presentation means for presenting the aforementioned advice to the terminal device, An information processing device equipped with the following features.

[0087] (Note 2) The aforementioned data analysis means is an information processing device as described in Appendix 1, which generates data based on the conversation data, evaluating the knowledge level representing each member's understanding of the treatment and the worry level representing each member's level of worry about the treatment.

[0088] (Note 3) The system includes a search log acquisition means that acquires search logs for information related to the treatment from the terminal device used by each member, for each member. The aforementioned data analysis means is an information processing device as described in Appendix 2, which calculates the frequency of searches for information related to the treatment for each member from each member's search log, and uses the search frequency to create data that evaluates the level of interest of each member in relation to the treatment.

[0089] (Note 4) The system includes a question creation means for creating questions to evaluate the aforementioned knowledge level and the aforementioned worry level, The presenting means presents the problem to the terminal device during the conversation, The aforementioned analysis data creation means is an information processing device as described in Appendix 2, which creates analysis data evaluating each member's knowledge level and concern level based on conversation data corresponding to each member's answers to the aforementioned questions.

[0090] (Note 5) The advice generation means generates advice from high-level members to low-level members based on the analysis data, in terms of knowledge level, interest level, and concern level. The presentation means is an information processing device according to Appendix 3, which presents the advice to a terminal device used by the high-level member.

[0091] (Note 6) The information processing device described in Appendix 5, wherein, after presenting the advice, when the analysis data is updated, the presenting means presents feedback data indicating the level change of the lower-level member to the terminal device used by the higher-level member, based on the updated analysis data.

[0092] (Note 7) A means for acquiring medical claim data related to treatment, The system includes a planning tool that creates a plan for the systems that families can utilize, based on information about welfare systems and the aforementioned claims data. The presentation means is an information processing device as described in Appendix 6, which presents the plan to the terminal device.

[0093] (Note 8) The information processing device described in Appendix 1 generates the analysis data by using the AI ​​model to calculate optimized numerical values ​​for evaluating each member's feelings towards treatment based on the search logs and conversation data.

[0094] (Note 9) An information processing method performed by an information processing device, It communicates with terminal devices used by multiple members, including patients who require treatment. Conversation data showing the conversation between the AI ​​model and each member is acquired from the terminal device used by each member. Based on the aforementioned conversation data, we created analytical data to evaluate each member's feelings towards treatment. Based on the aforementioned analysis data, we created advice to promote communication among family members. An information processing method for presenting the aforementioned advice to a terminal device.

[0095] (Note 10) It communicates with terminal devices used by multiple members, including patients who require treatment. Conversation data showing the conversation between the AI ​​model and each member is acquired from the terminal device used by each member. Based on the aforementioned conversation data, we created analytical data to evaluate each member's feelings towards treatment. Based on the aforementioned analysis data, we created advice to promote communication among family members. A program that causes a computer to perform the process of presenting the aforementioned advice to a terminal device.

[0096] While the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure may be understood by those skilled in the art within the scope of the present disclosure. That is, the present disclosure includes the entire disclosure, including the claims, and of course, various modifications and alterations that those skilled in the art may make in accordance with the technical idea. [Explanation of symbols]

[0097] 1 server 2, 2a, 2b, 2c, 2d Family terminals 11, 21 Interfaces 12, 22 processors 13, 23 memory 14, 24 Recording media 15, 25 Display section 16, 26 Input section 31 Registered Database 32 Conversation Storage Database 33 Analysis DB 40. Log acquisition app 42 Search Log Extraction Section 43 Search Log Registration Section 49 Search log acquisition section 50. Claim Data Acquisition Unit 54 Conversation Data Registration Section 55 Conversation Data Acquisition Unit 56 Analysis Data Registration Department 57 Analysis Data Acquisition Department 61 Text-to-Speech Presentation Unit 62 Text-to-Speech Acquisition Unit 71 Analysis Data Creation Department 72 Question Creation Department 73. Advisory Preparation Department 74 Planning Department 100 Communication Facilitation Systems

Claims

1. A communication means for communicating with terminal devices used by multiple members, including patients requiring treatment, A conversation data acquisition means that obtains conversation data showing the conversation between the AI ​​model and each member from the terminal device used by each member, Based on the aforementioned conversation data, a means for creating analytical data is provided to create analytical data that evaluates each member's feelings towards treatment. Based on the aforementioned analysis data, a means for creating advice to promote communication among family members, A presentation means for presenting the aforementioned advice to the terminal device, An information processing device equipped with the following features.

2. The information processing device according to claim 1, wherein the analysis data creation means creates analysis data based on the conversation data, evaluating the knowledge level representing each member's understanding of the treatment and the worry level representing each member's level of worry about the treatment.

3. The system includes a search log acquisition means that acquires search logs for information related to the treatment from the terminal device used by each member, for each member. The information processing device according to claim 2, wherein the analytical data creation means calculates the frequency of searches for information related to the treatment for each member from the search logs of each member, and creates analytical data that evaluates the level of interest of each member in relation to the treatment based on the search frequency.

4. The system includes a question creation means for creating questions to evaluate the aforementioned knowledge level and the aforementioned worry level, The presenting means presents the problem to the terminal device during the conversation, The information processing device according to claim 2, wherein the analysis data creation means creates analysis data that evaluates each member's knowledge level and concern level, based on conversation data corresponding to each member's answers to the problem.

5. The advice generation means generates advice from high-level members to low-level members based on the analysis data, in terms of knowledge level, interest level, and concern level. The information processing apparatus according to claim 3, wherein the presentation means presents the advice to a terminal device used by the high-level member.

6. The information processing apparatus according to claim 5, wherein, after the presentation means has presented the advice, when the analysis data is updated, it presents feedback data indicating the level change of the lower-level member to a terminal device used by the higher-level member, based on the updated analysis data.

7. A means for acquiring medical claim data related to treatment, The system includes a planning tool that creates a plan for the systems that families can utilize, based on information about welfare systems and the aforementioned claims data. The information processing device according to claim 6, wherein the presentation means presents the plan to the terminal device.

8. The information processing device according to claim 3, wherein the analysis data creation means uses the AI ​​model to calculate optimized numerical values ​​for evaluating each member's feelings toward treatment based on the search log and the conversation data, thereby creating the analysis data.

9. An information processing method performed by an information processing device, It communicates with terminal devices used by multiple members, including patients who require treatment. Conversation data showing the conversation between the AI ​​model and each member is obtained from the terminal device used by each member. Based on the aforementioned conversation data, we created analytical data to evaluate each member's feelings towards treatment. Based on the aforementioned analysis data, we created advice to promote communication among family members. An information processing method for presenting the aforementioned advice to a terminal device.

10. It communicates with terminal devices used by multiple members, including patients who require treatment. Conversation data showing the conversation between the AI ​​model and each member is obtained from the terminal device used by each member. Based on the aforementioned conversation data, we created analytical data to evaluate each member's feelings towards treatment. Based on the aforementioned analysis data, we created advice to promote communication among family members. A program that causes a computer to perform the process of presenting the aforementioned advice to a terminal device.

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