WO2025169373A1 - Recommendation method, recommendation device, program, and recommendation system - Google Patents

Abstract

Provided are a recommendation method, a recommendation device, a program, and a recommendation system which make it possible to propose a proper response to a symptom of an individual. The present invention is a recommendation method performed by a recommendation device comprising a processor, said recommendation method comprising: a symptom reception step for receiving, with the processor, input of a symptom of a user; an output step for searching a database in which information including a treatment method for each symptom is classified and outputting related information for alleviating the symptom; and a physical condition reception step for requesting input of a physical condition of the user after an estimated time has elapsed since the related information has been output, according to estimated time information, which indicates a time until an effect takes place and which has been obtained by searching the database per treatment method for efficacy information including the estimated time information.

Description

Recommendation method, recommendation device, program, and recommendation system

This disclosure relates to a recommendation method, a recommendation device, a program, and a recommendation system.

In recent years, with growing health awareness and the need to reduce medical costs and improve patients' quality of life (QOL), self-medication is being promoted, in addition to traditional medical care where people only go to the hospital once they realize they have an illness, and where people take responsibility for their own health from the pre-illness stage onwards, treating minor physical ailments themselves. This is the idea of managing your health with an awareness of your health by eating a balanced diet, getting enough sleep and rest, and being mindful of your physical condition on a daily basis. This leads to maintaining health, preventing, improving, and preventing lifestyle-related diseases from becoming more severe, and ultimately extending healthy lifespans. It also saves on medical costs and has social benefits such as reducing the excessive burden on medical institutions and medical professionals.

Furthermore, given the current social climate, it is recommended that people use supplements and over-the-counter medications to treat even mild physical ailments. It is also important for patients to visit a medical institution early, while symptoms are still mild.

For example, Patent Document 1 discloses a vending machine for supplying supplements that, in order to maintain health through daily self-help efforts, involves a step of asking about health status and a step of building a database of ingredient combinations in advance based on the results of each interview.

Japanese Patent Application Laid-Open No. 2005-276148

Incidentally, self-medication involves individuals living a health-conscious lifestyle, but when they feel unwell due to subjective symptoms, they take supplements or over-the-counter medicines, and if the symptoms improve as a result of taking these medicines, they then try to improve their condition by taking care of themselves.

However, if symptoms do not improve with supplements or over-the-counter medications, it is advisable for individuals to visit a medical institution, but in such cases, it is unclear what to do.

This disclosure has been made in light of the above, and aims to provide a recommendation method, recommendation device, program, and recommendation system that can suggest appropriate responses to individual symptoms.

In order to solve the above-mentioned problems and achieve the objectives, the recommendation method disclosed herein is a recommendation method executed by a recommendation device equipped with a processor, and includes: a symptom reception step in which the processor receives input of a user's symptoms; an output step in which the processor searches a database in which information including countermeasures for each symptom is categorized and outputs related information for alleviating the symptoms; and a health condition reception step in which the processor searches the database for effectiveness information including information on the estimated time until an effect appears for each countermeasure, and, in accordance with the obtained estimated time information, requests the user to input their health condition after the estimated time has elapsed after outputting the related information.

Furthermore, the recommendation method according to the present disclosure, in the above disclosure, further includes a first generation step in which, if the remedy is included as one of the remedy methods, the processor generates a first QR code indicating the remedy as part of the related information, and a second generation step in which, if a health condition reception result for the user's health condition is obtained, the processor generates a second QR code indicating the remedy and its effect.

Furthermore, the recommendation method according to the present disclosure, in the above disclosure, further includes a recommendation step in which the processor recommends the next possible action related to the user's physical condition and the symptoms in accordance with the physical condition reception result of the user's physical condition.

Furthermore, the recommendation method according to the present disclosure, in the above disclosure, further includes a behavioral history acquisition step in which the processor acquires the behavioral history of the user after outputting the related information.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the estimated time information includes a plurality of estimated times, and the physical condition reception step switches the content of the request for input of the user's physical condition for each of the plurality of estimated times.

Furthermore, the recommendation method according to the present disclosure is implemented by the processor as described above, including a symptom reception step for receiving input of the user's symptoms, an output step for outputting related information for alleviating the symptoms, a health condition reception step for receiving input of the user's health condition after outputting the related information, and a recommendation step for recommending medical institutions related to the health condition and the symptoms.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the recommendation device is capable of accessing a knowledge database composed of at least multiple pieces of over-the-counter drug information relating to multiple over-the-counter drugs that can be purchased externally, efficacy information and ingredient information for each of the multiple pieces of over-the-counter drug information, and medical department information and medical procedure information for each of multiple medical institutions; the output step searches the knowledge database for the over-the-counter drug information related to the symptoms and outputs it; and the recommendation step searches the knowledge database and recommends the medical institution.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the output step searches for over-the-counter drug information related to the symptom from among the plurality of over-the-counter drug information and outputs it.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the processor further executes a behavioral history acquisition step of acquiring the user's behavioral history after outputting the over-the-counter drug information.

Furthermore, in the recommendation method according to the present disclosure, in the above disclosure, the behavioral history is a purchase history or medication history of over-the-counter drugs corresponding to the over-the-counter drug information, and the physical condition reception step displays information on a display unit prompting the user to input their physical condition after a predetermined time has elapsed since the over-the-counter drug was purchased, and receives the input of their physical condition.

Furthermore, in the recommendation method according to the present disclosure, in the above disclosure, the recommendation step classifies the physical condition into multiple categories, and searches the knowledge database for medical institutions related to the classification results, the symptoms, the over-the-counter drug information, and the behavioral history, and recommends them.

In addition, the recommendation method according to the present disclosure, in the above disclosure, further includes a transmission control step in which the processor, after making the recommendation, accepts input of a degree of satisfaction with the over-the-counter drug information and transmits the degree of satisfaction to the knowledge database, and the knowledge database updates the over-the-counter drug information recommended according to symptoms based on the degree of satisfaction with the effectiveness of the over-the-counter drug information.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the recommendation step searches the knowledge database to recommend medical institutions that have testing equipment and facilities related to the symptoms.

Furthermore, in the recommendation method according to the present disclosure, in the above disclosure, the processor further executes a creation step in which it creates a first medical interview code including at least the symptoms and the related information, and the output step outputs the related information and the first medical interview code to a display unit. This medical interview code may be information indicating the remedial drug selected as a result of the interview, or the drug itself in that category, and may be displayed as a QR code. By presenting this QR code at a pharmacy, it can be used to purchase the drug from the pharmacy's inventory. In the recommendation method according to the present application, when a remedial drug is included as a remedial method, a first QR code indicating the remedial drug is generated as part of the remedial related information.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the behavioral history acquisition step further acquires vital sign information of the user at predetermined intervals, the creation step creates a second medical interview code including at least the symptoms, the physical condition, the behavioral history, and the vital sign information, and the recommendation step displays the second medical interview code on a display unit.

Furthermore, in the recommendation method disclosed herein, in the above disclosure, the recommendation step searches the knowledge database and makes an appointment for a consultation at the medical institution.

Furthermore, in the recommendation method according to the present disclosure, in the above disclosure, the output step requests and outputs the over-the-counter drug information related to the symptoms from a generation AI that lists the over-the-counter drug information or medical institution that is best suited to the symptoms from at least multiple over-the-counter drug information related to each of multiple over-the-counter drugs that can be purchased externally, efficacy information and ingredient information for each of the multiple over-the-counter drug information, and medical department information and medical procedure information for each of multiple medical institutions, and the recommendation step requests and recommends the medical institution related to the physical condition and the symptoms from the generation AI.

Furthermore, the recommendation device according to the present disclosure includes a symptom receiving unit that receives input of the user's symptoms; an output control unit that searches a database in which information including countermeasures for each symptom is categorized and outputs related information for alleviating the symptoms; and a physical condition receiving unit that requests input of the user's physical condition after the elapse of the estimated time following output of the related information, in accordance with estimated time information obtained by searching the database for effectiveness information including information on the estimated time until an effect appears for each countermeasure.

Furthermore, the program disclosed herein causes a recommendation device equipped with a processor to execute the following steps: a symptom reception step of receiving input of a user's symptoms; an output step of searching a database in which information including countermeasures for each symptom is categorized and outputting related information for alleviating the symptoms; and a health condition reception step of requesting input of the user's health condition after the elapse of the estimated time following output of the related information, in accordance with estimated time information obtained by searching the database for effectiveness information including information on the estimated time until an effect appears for each countermeasure.

Furthermore, the recommendation system according to the present disclosure is a recommendation system comprising a recommendation device and a medical system capable of communicating with the recommendation device via a network, wherein the medical system comprises a database in which related information for alleviating symptoms, including countermeasures, is classified for each symptom, and the recommendation device comprises a symptom reception unit that receives input of the user's symptoms, an output control unit that searches the database for and outputs the related information, and a physical condition reception unit that requests input of the user's physical condition after the elapse of the estimated time following output of the related information, in accordance with estimated time information obtained by searching the database for effectiveness information including information on the estimated time until an effect appears for each of the countermeasures.

The present invention has the effect of being able to suggest appropriate responses to individual symptoms.

FIG. 1 is a schematic configuration diagram of a recommendation system according to an embodiment. FIG. 2 is a block diagram showing the functional configuration of the mobile terminal according to one embodiment. FIG. 3 is a diagram illustrating an example of time-based information recorded by a time-based information recording unit of the mobile terminal according to an embodiment. FIG. 4 is a block diagram illustrating a functional configuration of a medical system according to an embodiment. FIG. 5 is a diagram showing an example of knowledge data registered in a knowledge DB of a medical system according to an embodiment. FIG. 6 is a block diagram showing the configuration functions of a pharmacy system according to one embodiment. FIG. 7 is a timing chart showing an outline of the process executed by the mobile terminal according to the embodiment. FIG. 8 is a diagram illustrating an example of an image displayed on the display unit of the mobile terminal according to the embodiment. FIG. 9D is a diagram showing an outline of the screen transition displayed on the mobile terminal after a predetermined time has elapsed. FIG. 9B is a diagram showing an outline of the screen transition displayed on the mobile terminal after a predetermined time has elapsed. FIG. 9C is a diagram showing an outline of the screen transition displayed on the mobile terminal after a predetermined time has elapsed. FIG. 9D is a diagram showing an outline of the screen transition displayed on the mobile terminal after a predetermined time has elapsed. FIG. 10 is a diagram showing an outline of an image displayed on a doctor terminal owned by a doctor. FIG. 11 is a flowchart showing an outline of a process executed by a mobile terminal according to an embodiment. FIG. 12 is a flowchart showing an outline of processing executed by a medical system according to an embodiment. FIG. 13 is a flowchart showing an outline of the processing executed by the pharmacy system according to one embodiment.

Below, modes for implementing the present disclosure are described in detail with reference to the drawings. Note that the present disclosure is not limited to the following modes. Furthermore, the figures referenced in the following description merely show a rough outline of the shape, size, and positional relationship to the extent that the contents of the present disclosure can be understood. In other words, the present disclosure is not limited to the shape, size, and positional relationship illustrated in each figure. Furthermore, in the following description, a mobile phone is used as an example of a recommendation device, but the present disclosure can also be applied to devices other than mobile phones, such as tablet terminal devices and personal computers.

[Recommendation system overview]
FIG. 1 is a schematic diagram of a recommendation system according to one embodiment. The recommendation system 1 shown in FIG. 1 includes a mobile terminal 10 that functions as a recommendation device, a medical system 20, a pharmacy system 30, and a payment server 40. The mobile terminal 10, the medical system 20, the pharmacy system 30, and the payment server 40 are connected to each other via a network N100 so that they can communicate bidirectionally. This network N100 is configured, for example, by an internet network or a mobile phone network. A user U1 uses the mobile terminal 10 to access the medical system 20, the pharmacy system 30, and the payment server 40.

[Functional configuration of mobile terminal]
2 is a block diagram showing the functional configuration of the mobile terminal 10. The mobile terminal 10 shown in FIG. 2 accepts input of a user's symptoms, outputs related information for alleviating the symptoms, and after outputting the related information, accepts input of the user's physical condition and recommends medical institutions related to the physical condition and the user's symptoms. The mobile terminal 10 shown in FIG. 2 includes a communication unit 11, a sensor group 12, an input unit 13, a display unit 14, a recording unit 15, and a control unit 16.

Under the control of the control unit 16, the communication unit 11 transmits various information to the medical system 20, the pharmacy system 30, and the payment server 40 via the network N100, and receives various information from the medical system 20, the pharmacy system 30, and the payment server 40. The communication unit 11 also receives vital information and health information related to the health condition of the user of the mobile terminal 10 from external sensors, such as a smart tray or a weighing scale, that are connected to the mobile terminal 10 in advance via Bluetooth (registered trademark) or Wi-Fi (registered trademark) communication, and outputs this information to the control unit 16. Here, vital information refers to blood pressure, electrocardiogram, blood oxygen, heart rate, pulse, body temperature, etc. Health information refers to uric acid levels, weight, blood glucose levels, etc. Under the control of the control unit 16, the communication unit 11 also receives environmental information about the mobile terminal 10 from an external weather server (not shown) and outputs this information to the control unit 16. Here, environmental information includes weather information (sunny, cloudy, etc.), temperature, humidity, warnings (e.g., dry weather warnings, migraine warnings), alerts, etc. The communication unit 11 is configured using a communication module.

The sensor group 12 acquires various information related to the user of the mobile terminal 10, such as vital signs, step count, and sleep information, and outputs this information to the control unit 16. The sensor group 12 is composed of, for example, a GPS (Global Positioning System) sensor, an acceleration sensor, a blood glucose sensor such as a pulse oximeter, a humidity sensor, a direction sensor, and a gyro sensor.

The input unit 13 accepts various inputs in response to external operations and outputs them to the control unit 16. The input unit 13 is configured using buttons, switches, a touch panel, etc.

Under the control of the control unit 16, the display unit 14 displays various information related to the mobile terminal 10. The display unit 14 is configured using a liquid crystal display, an organic electroluminescent display (OLED), or the like.

The recording unit 15 records various information related to the mobile terminal 10. The recording unit 15 includes a program recording unit 151 that records various programs executed by the mobile terminal 10, a time information recording unit 152 that records time information related to the user of the mobile terminal 10, a payment information recording unit 153 that manages the payment server 40 for electronic payments such as two-dimensional codes, the type of electronic payment, the balance, etc., and a mobile terminal identification information recording unit 154 that records identification information for identifying the mobile terminal 10. The recording unit 15 is configured using volatile memory, non-volatile memory, a memory card, an SSD (Solid State Drive), etc.

Figure 3 is a diagram showing an example of temporal information recorded by the temporal information recording unit 152. As shown in Figure 3, temporal information K1 records temporal information about the user of the mobile terminal 10. Specifically, temporal information K1 includes the user's lifestyle habits, preferences, whether they drink alcohol, whether they smoke, behavioral history, body temperature, whether they take medication, purchase history, sensor detection results, environmental information, and search history. For example, temporal information K1 stores November 1st, the number of steps of 10,021, body temperature of 36°, and weather as rain, all of which are associated with each other.

Returning to FIG. 2, the description of the configuration of the mobile terminal 10 will continue.
The control unit 16 is realized using a processor having hardware such as an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), or a CPU (Central Processing Unit), and a memory that is a temporary storage area used by the processor. The control unit 16 includes an acquisition unit 161, a symptom reception unit 162, an output control unit 163, a behavioral history acquisition unit 164, a physical condition reception unit 165, a recommendation unit 166, a transmission control unit 167, a creation unit 168, and a settlement unit 169.

The acquisition unit 161 acquires the detection results detected by the sensor group 12. Furthermore, the acquisition unit 161 acquires payment information when the user pays for a product via the payment server 40, and records this information in the payment information recording unit 153.

The symptom reception unit 162 receives input of the user's symptoms by the user inputting the symptoms via the input unit 13.

The output control unit 163 searches the knowledge database 242 of the medical system 20 (described below) based on the user's symptoms input by the symptom reception unit 162, searches for relevant information for recovering from or improving the user's symptoms, and outputs the information to the display unit 14. The output control unit 163 also searches a database in which information including coping methods is categorized by symptom for relevant information for recovering from the user's symptoms input by the symptom reception unit 162, and outputs the information.

The behavioral history acquisition unit 164 acquires behavioral history indicating whether the user purchased any of the multiple over-the-counter drugs displayed as related information by the output control unit 163 based on the mobile device identification information linked to the mobile device 10 from the medical system 20 or pharmacy system 30 via the network N100. Furthermore, the behavioral history acquisition unit 164 acquires the user's behavioral history after the output control unit 163 outputs the related information based on the mobile device identification information linked to the mobile device 10 from the medical system 20 or pharmacy system 30 via the network N100.

The physical condition reception unit 165 determines whether a predetermined time, for example, three days, has passed since the display unit 14 displayed multiple pieces of over-the-counter drug information as related information. The physical condition reception unit 165 also requests the user to input their physical condition after the estimated time has passed since the output control unit 163 output the related information, in accordance with the estimated time information obtained by searching the knowledge database 242 of the medical system 20 (described below) for effectiveness information including information on the estimated time until the effect of each method is apparent.

The recommendation unit 166 displays on the display unit 14 the results of medical institutions corresponding to the symptoms, physical condition, and related information obtained by searching the knowledge database 242. The recommendation unit 166 also recommends the next potential treatment related to the user's physical condition and the user's symptoms, in accordance with the physical condition reception result of the user's physical condition received by the physical condition reception unit 165.

The transmission control unit 167 initiates a reservation with the medical institution selected by the user via the input unit 13 to the medical system 20 via the network N100.

The creation unit 168 creates a medical interview code for a medical institution that includes the user's symptoms, etc. The medical interview code includes the user's name, contact information (phone number of the mobile terminal 10), the user's date of birth, the user's gender, and other information such as the user's hourly body temperature for a specified number of days that a doctor can use as a reference when examining the patient, as well as information such as the user's subjective symptoms, whether the user has purchased and taken a nasal allergy medication, and whether the symptoms have not improved with the nasal allergy medication. Here, the medical interview code is constructed using a two-dimensional code or a three-dimensional code, such as a QR code (registered trademark). When a remedy selected by the user includes a remedy, the creation unit 168 creates (generates) a second QR code that is different from the first QR code (medical interview code) indicating the remedy and the effect of taking the remedy (obtained according to information obtained when further medical interview information and health reception results are acquired). As a result, if a pharmacy or medical institution has a system that can present and read this second QR code, the pharmacy can recommend a further remedy. As a result, doctors can obtain more information than patients can provide verbally or in writing, enabling them to make diagnoses and provide treatment that takes into account the effectiveness of medication.

The payment unit 169 connects to the payment server 40 via the network N100, and makes payments for the over-the-counter medications desired by the user using two-dimensional or three-dimensional codes or electronic money.

[Structure of the medical system]
Next, a description will be given of the functional configuration of the medical system 20. Fig. 4 is a block diagram showing the functional configuration of the medical system 20. The medical system 20 shown in Fig. 4 includes a communication unit 21, an input unit 22, an output unit 23, a recording unit 24, and a server control unit 25.

Under the control of the server control unit 25, the communication unit 21 receives various information from the mobile terminal 10, medical terminals used by external doctors, pharmacist terminals used by external pharmacists, dispensing pharmacy terminals used at dispensing pharmacies, pharmacy terminals used at pharmacies and drug stores, etc., via the network N100, and transmits various information to the mobile terminal 10. The communication unit 21 is configured using a communication module, etc.

The recording unit 24 records various information executed by the medical system 20. The recording unit 24 has a program recording unit 241 that records various programs executed by the medical system 20, and a knowledge database 242 (hereinafter simply referred to as "knowledge DB 242").

Knowledge DB242 registers and stores various types of knowledge corresponding to the patient's symptoms and condition in a systemized and organized manner. Specifically, knowledge DB242 stores symptoms, which are registered or accumulated elements, in association with related information indicating the relevance of these symptoms. Here, related information refers to information regarding causes according to the patient's symptoms and condition, related medical institutions, treatment methods, testing equipment, testing facilities, medical devices, ingredient information, effectiveness information, specialists, medical departments, side effects, dosage and administration, doctors at related medical institutions, over-the-counter drugs, supplements, traditional remedies, and the patient's medical history.

FIG. 5 is a diagram showing an example of knowledge data registered in knowledge DB 242. As shown in FIG. 5, in knowledge DB 242, for the symptom: nasal congestion, multiple pieces of related information indicating a relationship to this nasal congestion are stored in association with each other. For example, in related information Q1, candidate disease 1 "cold" is stored with "resistance" and "infection" as causes, "internal medicine" as related medical institution, "cold medicine A", "cold medicine B", and "cold medicine C" as treatments, ingredient information, and effect information associated with each other. Similarly, candidate disease 2 "hay fever" is stored with "pollen" as cause, "allergy" as related medical institution, and "rhinitis medicine A", "rhinitis medicine B", and "rhinitis medicine C" as treatments, ingredient information, and effect information associated with each other.

Here, each of rhinitis medications A to C contains ingredients such as antihistamines that work on sneezing, runny nose, and nasal congestion, and the fact that the same ingredients are also included in cold medicines is stored (registered) in related information Q1 to Qn (n = 2 or more). Each of cold medicines A to C always contains antipyretic and analgesic ingredients that work on fever, chills (chills), headache, muscle pain, joint pain, etc., and also contains ingredients that work on nasal symptoms and allergic symptoms, as well as other ingredients that work on coughs and phlegm. In other words, the difference is that each of rhinitis medications A to C contains ingredients that are specialized for nasal symptoms, while cold medicines contain ingredients that address a variety of symptoms, including nasal symptoms and systemic cold symptoms.

Furthermore, patients and those taking medicines typically experience cold symptoms for about one week to ten days, and related information Q1 stores the length of time it takes for a cold to fully recover, depending on the severity of the individual symptoms, such as the causative virus or pollen. Specifically, related information Q1 stores the average duration of common cold symptoms, which is seven to ten days. Furthermore, this varies depending on the symptoms; in the case of a cough, related information Q1 stores (registers) as knowledge data that these symptoms last for two to three weeks after the onset of the cold. Cold symptoms peak on the second or third day (48 to 72 hours) after the onset of the cold, and in most cases, they subside within one week to ten days. However, if symptoms do not improve after one week, there may be another underlying illness. Therefore, related information Q1 registers relevant medical institutions (hospital name and address, specialty, whether or not they have a specialist), etc., as it is necessary to consult a doctor. Note that the related information Q is merely an example, and for each symptom, associated information is registered regarding related medical institutions, treatment methods, ingredient information, effect information, specialists, medical departments, side effects, dosage and administration, doctors at related medical institutions, over-the-counter drugs, supplements, traditional remedies, and the patient's medical history. Here, medical history information includes the patient's medical history and current underlying diseases, such as diabetes, anemia, and high blood pressure.

Furthermore, as effectiveness information, information on the improvement effect of the countermeasures for symptoms or illnesses, as well as success information including the symptoms and the estimated time until the effects of each presented countermeasure are observed, are recorded as one of the items. This can be searched in knowledge DB242, and information on the estimated time until a specific countermeasure is performed, such as whether it was effective or whether side effects will occur, can be obtained. After outputting relevant information to help the user recover their health based on this, next guidance can be provided based on how the user's health condition changes after the estimated time has passed when the countermeasure is performed. Furthermore, if side effects occur, this can be used as a clue to immediately discontinue that countermeasure. In addition to manually entering health information, when effectiveness is determined by referencing data from a mobile device or other device, information on which device and what information is required to determine whether the countermeasure is effective or not can be recorded in the "Effective Information" item in knowledge DB242.

Returning to FIG. 4, the configuration of the medical system 20 will be described.
The server control unit 25 includes an acquisition unit 251 , a search unit 252 , a determination unit 253 , and a communication control unit 254 .

The acquisition unit 251 acquires various information for updating the knowledge DB 242 via the communication unit 21 and the network N100, and updates the systematized and organized state of various knowledge in the knowledge DB 242 according to the patient's symptoms and condition.

The search unit 252 searches the knowledge DB 242 for relevant information related to the user's symptoms based on the user's symptoms received from the mobile terminal 10.

The determination unit 253 determines whether or not there has been input communication of the user's symptoms from the mobile terminal 10 via the network N100 and the communication unit 21.

The communication control unit 254 transmits the search results of the related information related to the user's symptoms searched from the knowledge DB 242 by the search unit 252 to the mobile terminal 10.

[Pharmacy system configuration]
Next, a description will be given of the functional configuration of pharmacy system 30. Fig. 6 is a block diagram showing the functional configuration of pharmacy system 30. Pharmacy system 30 shown in Fig. 6 includes a communication unit 31, an input unit 32, an output unit 33, a reading unit 34, a recording unit 35, and a pharmacy control unit 36.

Under the control of the pharmacy control unit 36, the communications unit 31 transmits various information to the mobile terminal 10, medical system 20, and payment server 40 via the network N100, and receives various information from the mobile terminal 10, medical system 20, and payment server 40.

The input unit 32 accepts various inputs in response to external operations and outputs them to the pharmacy control unit 36. The input unit 32 is configured using buttons, switches, a touch panel, etc.

Under the control of the pharmacy control unit 36, the output unit 33 displays information such as a two-dimensional code, such as a QR code (registered trademark), read by the reading unit 34 (described below). The output unit 33 is configured using a liquid crystal display or the like.

The reading unit 34 is configured using a reader or the like that can read two-dimensional codes, and outputs the information read from the two-dimensional code to the pharmacy control unit 36.

The recording unit 35 records various information related to the pharmacy system 30. The recording unit 35 has a program recording unit 351 that records various programs executed by the pharmacy system 30, and a purchase recording unit 352 that records purchase information that associates the purchase and inventory of each product with purchaser information (gender, age, etc.).

The pharmacy control unit 36 is implemented using a processor with hardware such as an FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit), or CPU (Central Processing Unit), and memory, which is a temporary storage area used by the processor. The pharmacy control unit 36 also has an acquisition unit 361, a settlement unit 362, and a communication control unit 363.

The acquisition unit 361 acquires the QR code (first QR code) of the medical interview code displayed on the display unit 14 of the mobile terminal 10, read using the reading unit 34, and determines whether or not the QR code of the acquired medical interview code is for the purchase of an over-the-counter drug. This QR code may be a summary of the medical interview results, or it may be information indicating the corrective drug searched for or selected by the user as a result of the medical interview results.

The payment unit 362 determines whether the user's mobile terminal 10 has paid for the over-the-counter drug via electronic payment, and if it determines that the user's mobile terminal 10 has paid for the over-the-counter drug via electronic payment, it provides the over-the-counter drug. Such information can be behavioral information.

The communications control unit 363 transmits to the medical system 20 the patient information (i.e., the user of the mobile terminal 10) contained in the QR code of the medical interview code acquired by the acquisition unit 361, the provided medication (over-the-counter medication), and the date and time. In this case, if a remedial medication is included as a remedial measure selected by the user, a second QR code is generated that indicates the remedial medication and the effect of taking the remedial medication (obtained according to information obtained when further medical interview information and health status reception results are acquired), rather than the first QR code indicating the remedial medication. As a result, if a pharmacy or medical institution has a system that can present and read this second QR code, the pharmacy can recommend yet another remedial medication. As a result, doctors can obtain more information than the patient would verbally or in writing, enabling them to diagnose and treat patients based on the effects of the remedial medication.

[Overview of mobile terminal processing]
Next, an overview of the processing executed by the mobile terminal 10 will be described. FIG. 7 is a timing chart showing an overview of the processing executed by the mobile terminal 10. FIG. 8 is a diagram showing an example of an image displayed on the display unit 14 of the mobile terminal 10. In FIG. 7, from the top, (a) shows the timing of body temperature (thermometer) detection by the sensor group 12, (b) shows the timing of input information, (c) shows the timing of search to the knowledge DB 242, (d) shows the timing of purchase at the pharmacy, and (e) shows the timing of payment by the mobile terminal 10. Note that FIG. 7 describes a case where the user of the mobile terminal 10 experienced discomfort in the nose on November 2nd.

As shown in FIG. 7, the mobile terminal 10 measures body temperature using the sensor group 12 at predetermined times, for example, at fixed times every 24 hours. In this case, as shown in FIG. 7(b), if the user experiences nasal discomfort due to a stuffy or runny nose or a runny nose that won't stop on November 2nd, the user inputs their symptoms via the input unit 13 on November 3rd, for example. In this case, the symptom receiving unit 162 receives the user's symptoms input via the input unit 13. As shown in FIG. 8, the symptom receiving unit 162 receives "My nose won't stop running" input into input cell R1 via the input unit 13 as the user's symptoms.

Then, based on the user's symptoms input by the symptom receiving unit 162, the output control unit 163 searches the knowledge DB 242 of the medical system 20 via the network N100 to find relevant information for recovering from or improving the user's symptoms, and outputs the information to the display unit 14. Specifically, as shown in FIG. 8, the output control unit 163 searches the knowledge DB 242 for multiple pieces of over-the-counter drug information related to each of multiple over-the-counter drugs related to the user's symptoms as relevant information, and outputs the information to the display unit 14. In this case, as shown in image P1 in FIG. 8, the output control unit 163 searches and extracts rhinitis medication A and rhinitis medication B from the knowledge DB 242 as relevant information optimal for recovering from the symptoms input by the user, and displays them on the display unit 14 as relevant information for improving the symptoms. Furthermore, the output control unit 163 displays the cause according to the symptom on the display unit 14. The user then goes to a pharmacy to purchase rhinitis medication A or rhinitis medication B, which is displayed in the related information on the mobile device 10, and makes the purchase using electronic money or the like on the mobile device 10.

The user purchases the over-the-counter drug displayed on the display unit 14 at a pharmacy or the like based on the related information displayed on the display unit 14 (see Figure 7(d)). In this case, the payment unit 169 connects to the payment server 40 via the network N100 and makes payment for the over-the-counter drug desired by the user using a two-dimensional code, a three-dimensional code, or electronic money. The transmission control unit 167 transmits the payment information paid by the payment unit 169 to the payment server 40, the pharmacy system 30, and the medical system 20 (see Figure 7(e)).

[Screen transitions on mobile devices]
Next, we will explain the details of the screen transitions displayed by the mobile terminal 10. Figures 9A to 9D are diagrams showing an overview of the screen transitions displayed by the mobile terminal 10 after a predetermined time has elapsed. Figure 10 is a diagram showing an overview of the images displayed on the doctor terminal owned by the doctor.

As shown in FIG. 9A, the creation unit 168 creates a medical questionnaire code D1 to be presented at a drugstore or pharmacy for the recommended over-the-counter drug H1 (rhinitis medication B) corresponding to the symptoms, taking into account the user U1's date of birth and gender information, and displays this on the display unit 14. Here, if a remedy is included as a remedy, the creation unit 168 creates a two-dimensional code, three-dimensional code, etc. (first QR code) indicating the remedy as part of the related information and displays it on the display unit 14. Note that instead of a two-dimensional code or three-dimensional code, the creation unit 168 may create information such as a product name of rhinitis medication B associated with the user U1's symptoms and display it on the display unit 14. In this case, the payment unit 169 connects to the payment server 40 via the network N100, and makes payment for the over-the-counter drug desired by the user using the two-dimensional code, three-dimensional code, or electronic money.

9B, if user U1 purchases an over-the-counter drug at a pharmacy and takes it, after a predetermined time, for example, three days, the physical condition reception unit 165 displays an image P11 on the display unit 14 asking the user whether their symptoms have improved. Specifically, the physical condition reception unit 165 displays an image P11 on the display unit 14 that includes a message and an input cell H2 to prompt the user to input whether their symptoms have improved. In this case, before three days have passed (for example, two days have passed), if the symptoms should not have improved yet based on the efficacy of the remedy (which works after three days) (this can be determined because the knowledge DB 242 contains estimated time information), the recommendation unit 166 recommends inputting "Has it worsened?" rather than "Has it improved?" By the fourth day, the symptoms should have improved, so it is made easier to input if they have not improved (for example, by making it a one-touch button), and in that case, the recommendation unit 166 emphasizes a recommendation to stop taking the medication. The type of recommendation to be made is assumed to be organized and recorded as "effect information" in the knowledge DB 242. Of course, the physical condition receiving unit 165 may switch the content of the request for input of the physical condition of user U1 for each of the multiple estimated times searched in the knowledge DB 242.

Therefore, in the recommendation method of the present application, the estimated time information includes multiple estimated times (2 days, 3 days, and 4 days in the above example), and the above-mentioned request for input of physical condition or the recommendation content changes for each of the multiple estimated times.

Next, as shown in FIG. 9C, if user U1 enters "symptoms not improving" in input cell H2, the recommendation unit 166 accesses the knowledge DB 242 via the network N100, searches for related information related to physical condition, symptoms, and over-the-counter medications, and displays the information on the display unit 14. Specifically, as shown in FIG. 9C, the recommendation unit 166 displays an image P12 on the display unit 14 recommending multiple clinics that can treat the symptoms. In this case, the recommendation unit 166 may make a recommendation that prompts user U1 to enter their current symptoms every predetermined period, for example, every third day or every fourth day. At this time, the recommendation unit 166 may search the knowledge DB 242 via the network N100 for the content of a question to be posed to user U1 and display it on the display unit 14. As a result, the recommendation unit 166 recommends the next potential treatment related to user U1's physical condition and symptoms according to the result of the health condition reception for the user U1.

After that, when user U1 selects a desired clinic from the multiple clinics displayed by display unit 14 (FIG. 9C), as shown in FIG. 9D, transmission control unit 167 initiates a reservation at the medical institution selected by the user via input unit 13. Furthermore, as shown in FIG. 9D, creation unit 168 creates a medical interview code D2 (second QR code) including the user's symptoms, etc., for the medical institution, and displays image P13 on display unit 14, including medical interview code D2 and cell R10 indicating that the reservation has been initiated. Medical interview code D2 includes user U1's name, contact information (phone number of mobile terminal 10), date of birth, gender information of user U1, and other information such as hourly body temperature for a specified number of days that a doctor may use as a reference when examining the patient, as well as user U1's subjective symptoms, such as a runny nose on November 3rd, the fact that nasal decongestant B was purchased and taken, and the fact that nasal decongestant B has not improved the symptoms. That is, when the creation unit 168 acquires the result of the user's physical condition reception, it generates an interview code (second QR code) indicating at least the corrective medication included in the interview code D1 (first QR code) and its effects. Of course, the interview code D2 may also include user U1's hospital visit history, underlying illnesses, and vital information other than weight and body temperature, such as blood pressure, blood sugar level, and heart rate.

Next, as shown in FIG. 10, the doctor uses the doctor terminal 100 to read the medical interview code D2 displayed on user U1's mobile terminal 10 using a camera or other device provided on the doctor terminal 100. As a result, as shown in image P20 displayed on the doctor terminal 100, the doctor or other device can grasp the patient information H10 and symptoms H20 of user U1, who is the patient, and can provide smooth treatment.

[Processing performed by the mobile terminal]
Next, a description will be given of the processing executed by the mobile terminal 10. Fig. 11 is a flowchart showing an outline of the processing executed by the mobile terminal 10.

As shown in FIG. 11, if the user has made an input to the input unit 13 (step S101: Yes), the control unit 16 displays the Top screen on the display unit 14 (step S102). After step S102, the mobile terminal 10 proceeds to step S103. On the other hand, if the control unit 16 determines that the user has not made an input to the input unit 13 (step S101: No), the mobile terminal 10 continues this determination.

In step S103, if the symptom reception unit 162 receives the user's symptom input by inputting the user's symptoms via the input unit 13 (step S103: Yes), the output control unit 163 communicates with the knowledge DB 242 via the network N100 (step S104). Here, the user's symptom input may be automatically input based on the results of sensors (smartwatches, smart glasses, or other dedicated medical/health (peripheral) devices) built into or connected to the user's mobile terminal 10 or user operation, or, once input, the processing of step S103 may be repeated until the results become invalid or unnecessary. After step S104, the mobile terminal 10 proceeds to step S105, which will be described later. On the other hand, if the symptom reception unit 162 does not receive the user's symptom input via the input unit 13 (step S103: No), the symptom reception unit 162 proceeds to step S111, which will be described later.

In step S105, the output control unit 163 searches the knowledge DB 242 of the medical system 20 based on the user's symptoms input by the symptom reception unit 162, and determines whether there are any candidate diseases or recommended medical actions as related information for recovering from or improving the user's symptoms. For example, the output control unit 163 searches the knowledge DB 242 of the medical system 20 and determines whether any candidate diseases have been extracted as related information for recovering from or improving the user's symptoms. Furthermore, recommended medical actions include presenting information on multiple over-the-counter drugs for purchasing and taking over-the-counter drugs related to the symptoms, visiting a medical institution related to the symptoms, practicing folk remedies related to the symptoms, taking supplements related to the symptoms, etc. The output control unit 163 searches the knowledge DB 242 of the medical system 20 based on the user's symptoms input by the symptom receiving unit 162, and if it determines that there is a disease candidate or recommended medical action as related information for recovering from or improving the user's symptoms (step S105: Yes), the output control unit 163 displays the search results from the knowledge DB 242 on the display unit 14 (step S106). Specifically, the output control unit 163 searches the knowledge DB 242 for multiple pieces of over-the-counter drug information related to each of multiple over-the-counter drugs related to the user's symptoms as related information, and outputs this information to the display unit 14.

Next, the output control unit 163 displays options for purchasing over-the-counter medications, making medical appointments, etc., when the user performs a selection operation on the input unit 13 based on the related information displayed by the display unit 14 (step S107). Specifically, when the user performs an operation to purchase an over-the-counter medication via the input unit 13, the output control unit 163 causes the display unit 14 to display the medical interview code (first QR code) created by the creation unit 168 (see, for example, Figure 9A). Specifically, the creation unit 168 creates a medical interview code (first QR code) containing information including the user's date of birth, the user's gender information, the subjective symptoms entered by the user, and the selected over-the-counter medication "rhinitis medication B," and which includes related information for alleviating the user's symptoms according to the search results of a search of the knowledge DB 242, which classifies information including coping methods for each symptom. Furthermore, when a user makes an appointment at a medical institution via the input unit 13, the output control unit 163 causes the display unit 14 to display a medical interview code created by the creation unit 168, which includes information such as the name of user U1, contact information (phone number of the mobile terminal 10), date of birth of user U1, gender information of user U1, and other information such as hourly body temperature for a specified number of days that a doctor will use as a reference when examining the patient, as well as user U1's subjective symptoms, for example, a runny nose on November 3rd and rhinitis medication B as a search result from the knowledge DB 242.

Then, the behavioral history acquisition unit 164 acquires the user's behavioral history (step S108). Specifically, the behavioral history acquisition unit 164 acquires behavioral history indicating whether the user has purchased any of the multiple over-the-counter drugs displayed as related information by the output control unit 163 from the medical system 20 or the pharmacy system 30 via the network N100, based on the mobile device identification information linked to the mobile device 10. Of course, the behavioral history acquisition unit 164 may also acquire behavioral history indicating whether the user has purchased any of the multiple over-the-counter drugs displayed as related information by the output control unit 163 from the payment information recorded by the payment information recording unit 153. The behavioral history acquisition unit 164 may also acquire, as behavioral history, from the sensor group 12, whether the user has taken any of the multiple over-the-counter drugs displayed as related information by the output control unit 163. In this case, the behavioral history acquisition unit 164 acquires behavioral history in which, if the user's body temperature detected by the sensor group 12 changes over time or if the heart rate is increasing, it is considered that the user has taken any of the multiple over-the-counter drugs. Here, the behavioral history acquisition unit 164 determines whether the presented countermeasure was followed based on the user's behavioral history (step S108). This determines whether the user followed the instructions, allowing the next piece of advice to be given correctly. This behavioral history may also be used to determine changes in physical condition after the countermeasure was taken.

Next, if the user ends the operation of the mobile terminal 10 (step S109: Yes), the mobile terminal 10 returns to step S101. On the other hand, if the user does not end the operation of the mobile terminal 10 (step S109: No), the mobile terminal 10 returns to step S103.

In step S105, if the symptom reception unit 162 is unable to search the knowledge DB 242 for disease candidates or recommended medical procedures based on the symptoms received (step S105: No), the output control unit 163 causes the display unit 14 to display a result indicating that there is no information related to the symptoms entered by the user in the knowledge DB 242 (step S110). After step S110, the mobile terminal 10 proceeds to step S109.

In step S111, the physical condition reception unit 165 determines whether a predetermined time, for example, three days, has passed since the related information was displayed on the display unit 14. If the physical condition reception unit 165 determines that the predetermined time has passed since the related information was displayed on the display unit 14 (step S111: Yes), the mobile device 10 proceeds to step S112. This predetermined time is determined based on the symptoms and effectiveness information, including information on the estimated time until the effects of each presented countermeasure are observed. This information is recorded as one of the "effectiveness information" items in the knowledge DB 242 (see Figure 5), and the estimated time information can be obtained by searching this information. After outputting related information to improve the user's physical condition in accordance with this information, the next guide can be provided based on how the user's physical condition changes after the estimated time has passed when the countermeasure is taken. On the other hand, if the physical condition reception unit 165 determines that the predetermined time has not passed since the related information was displayed on the display unit 14 (step S111: No), the mobile device 10 proceeds to step S119, which will be described later.

In step S112, the physical condition receiving unit 165 determines whether it is time to check the effects of the actions taken by the user in response to the related information. If the physical condition receiving unit 165 determines that it is time to check the effects of the actions taken by the user in response to the related information (step S112: Yes), the mobile device 10 proceeds to step S113, which will be described later. On the other hand, if the physical condition receiving unit 165 determines that it is not time to check the effects of the actions taken by the user in response to the related information (step S112: No), the mobile device 10 proceeds to step S109.

In step S113, the physical condition reception unit 165 displays a confirmation display on the display unit 14 to prompt the user to confirm the details of the effect of the action taken in response to the related information. Specifically, as shown in FIG. 9B above, the physical condition reception unit 165 displays a confirmation display on the display unit 14 to prompt the user to confirm the details of the effect of the action taken in response to the related information. In this way, the physical condition reception unit 165 accepts the user's input of symptoms, searches the knowledge DB 242, which classifies related information including countermeasures for each symptom, and outputs related information for alleviating the symptoms. For each countermeasure, the physical condition reception unit 165 searches for success information including information on the estimated time until the effect appears, and performs physical condition reception that requests the user to input their physical condition after the estimated time has passed since the output of the related information. This makes it possible to determine whether the presented countermeasure was effective and to provide the user with various advice. In addition to manually entering physical condition information, the physical condition reception unit 165 may also determine effectiveness by referring to data from the mobile terminal 10 or other devices. In such cases, information on which device and which information is deemed effective or ineffective can be recorded in the "Effective Information" section of knowledge DB242.

Next, if the physical condition receiving unit 165 determines that the input unit 13 has received input indicating that the action taken by the user in response to the related information is effective (step S114: Yes), the recommendation unit 166 communicates with the knowledge DB 242 via the network N100 (step S115).

The recommendation unit 166 then displays the search results from the knowledge DB 242 on the display unit 14 (step S116). Specifically, even if the user's symptoms have improved, the recommendation unit 166 searches the knowledge DB 242 for information on symptoms requiring caution and displays the information obtained on the display unit 14. For example, even if the symptoms have improved, the recommendation unit 166 displays on the display unit 14 a message to the user that they should visit a medical institution if they experience a cough related to the symptoms. Furthermore, the recommendation unit 166 may classify symptoms into multiple categories and search the knowledge DB 242 for medical institutions related to the classification results, physical condition, over-the-counter drug information, and behavioral history, and recommend them. Specifically, the recommendation unit 166 may classify symptoms into categories such as nasal congestion or fever, and may search the knowledge DB 242 for medical institutions related to the classification results, physical condition, over-the-counter drug information, and behavioral history, and recommend them. At this time, the transmission control unit 167 accepts input of the user's level of satisfaction with the over-the-counter drug information in the related information, and transmits this satisfaction level to the knowledge DB 242. After step S116, the mobile terminal 10 proceeds to step S109.

In step S114, if the physical condition receiving unit 165 determines that the input unit 13 has received input indicating that the action taken by the user in response to the related information was ineffective (step S114: No), the recommendation unit 166 communicates with the knowledge DB 242 via the network N100 (step S117).

Next, the recommendation unit 166 searches the knowledge DB 242 for medical institutions related to the symptoms, physical condition, and behavioral history, and displays the acquired results on the display unit 14 (step S118). Specifically, if the user's symptoms have not improved, the recommendation unit 166 searches the knowledge DB 242 for information on the most appropriate medical institution (or other medical treatment) for the symptoms, since the medical history and medication history (which may include other treatments such as massage, exercise, diet, water intake, and living environment) and their effects have already been systematically acquired (either from the mobile terminal 10 or the primary care physician's hospital system), and displays the acquired results on the display unit 14. Therefore, the recommendation method of the present application allows the recommendation unit 166 to recommend the next treatment candidate related to the physical condition and original symptoms according to the physical condition reception result (such as changes in physical condition after the treatment). For example, as shown in FIG. 9C, the recommendation unit 166 recommends multiple clinics that can treat the symptoms and physical condition. In this case, the recommendation unit 166 may search the knowledge DB 242, further taking into account the location information of the mobile device 10, and recommend multiple medical institutions in order of proximity to the location of the mobile device 10. This allows the user to intuitively understand the clinic that is best suited to their symptoms, allowing them to receive treatment at an appropriate clinic before their symptoms worsen. Thereafter, the transmission control unit 167 initiates a reservation at the medical institution selected by the user via the input unit 13, as shown in FIG. 9D above. Furthermore, as shown in FIG. 9D above, the creation unit 168 creates an inquiry code D2 (second QR code) for the medical institution that includes the user's symptoms, etc., and indicates the corrective medication and its effects, and displays it on the display unit 14. After step S118, the mobile device 10 proceeds to step S109.

In step S119, the mobile terminal 10 executes processing in another mode, for example, a mode corresponding to an app stored on the mobile terminal 10. After step S118, the mobile terminal 10 proceeds to step S108.

[Medical system processing]
Next, a description will be given of the processing executed by the medical system 20. Fig. 12 is a flowchart showing an outline of the processing executed by the medical system 20.

As shown in FIG. 12, the determination unit 253 determines whether or not there has been an input communication of the user's symptoms from the mobile terminal 10 via the network N100 and the communication unit 21 (step S201). If the determination unit 253 determines that there has been an input communication of the user's symptoms from the mobile terminal 10 (step S201: Yes), the medical system 20 proceeds to step S202, which will be described later. On the other hand, if the determination unit 253 determines that there has not been an input communication of the user's symptoms from the mobile terminal 10 (step S201: No), the medical system 20 proceeds to step S206, which will be described later.

In step S202, the search unit 252 searches the knowledge DB 242 for relevant information related to the user's symptoms based on the user's symptoms received from the mobile terminal 10.

Next, the search unit 252 determines whether it is possible to search the knowledge DB 242 for related information relating to the symptoms, including disease candidates or recommended medical procedures, based on the symptoms (step S203). If the search unit 252 determines that it is possible to search the knowledge DB 242 (step S203: Yes), the medical system 20 proceeds to step S204, which will be described later. On the other hand, if the search unit 252 determines that it is not possible to search the knowledge DB 242 (step S203: No), the medical system 20 proceeds to step S205, which will be described later.

In step S204, the communication control unit 254 transmits the search results of the relevant information related to the user's symptoms searched from the knowledge DB 242 by the search unit 252 to the mobile terminal 10. After step S204, the medical system 20 returns to step S201 described above.

In step S205, the communication control unit 254 transmits to the mobile terminal 10 a message indicating that there is no related information related to the user's symptoms searched for in the knowledge DB 242 by the search unit 252. After step S205, the medical system 20 returns to step S201 described above.

In step S206, the determination unit 253 determines whether or not the user's behavior information transmitted from the mobile terminal 10 via the network N100 and the communication unit 21 includes medication information communication. If the determination unit 253 determines that the user's behavior information transmitted from the mobile terminal 10 via the network N100 and the communication unit 21 includes medication information communication (step S206: Yes), the medical system 20 proceeds to step S207, which will be described later. On the other hand, if the determination unit 253 determines that the user's behavior information transmitted from the mobile terminal 10 via the network N100 and the communication unit 21 does not include medication information communication (step S206: No), the medical system 20 proceeds to step S208, which will be described later.

In step S207, the communication control unit 254 transmits an effectiveness confirmation to the mobile terminal 10 at a specific timing to confirm the effectiveness of the related information searched in the knowledge DB 242 and transmitted to the mobile terminal 10. After step S207, the medical system 20 returns to step S201 described above.

In step S208, the determination unit 253 determines whether a result response for related information has been received from the mobile terminal 10 via the network N100 and the communication unit 21. If the determination unit 253 determines that a result response for related information has been received from the mobile terminal 10 via the network N100 and the communication unit 21 (step S208: Yes), the medical system 20 proceeds to step S209, which will be described later. On the other hand, if the determination unit 253 determines that a result response for related information has not been received from the mobile terminal 10 via the network N100 and the communication unit 21 (step S208: No), the medical system 20 proceeds to step S212, which will be described later.

In step S209, the search unit 252 searches the knowledge DB 242 for medical institutions as relevant information related to the user's symptoms and physical condition, based on the user's physical condition in response to the over-the-counter medication taken in accordance with the symptoms received from the mobile terminal 10.

Next, the communication control unit 254 transmits the search results of medical institutions as related information related to the user's symptoms and physical condition searched for by the search unit 252 from the knowledge DB 242 to the mobile terminal 10 (step S210).

Then, the communication control unit 254 transmits various information about medical institutions to display information such as medical institution appointments in response to a selection operation on the mobile terminal 10 (step S211). After step S211, the medical system 20 returns to step S201.

In step S212, the medical system 20 executes processing according to the other mode. For example, the medical system 20 executes an update process that updates the information in the knowledge DB 242 according to the satisfaction level according to the related information transmitted from the mobile terminal 10. After step S212, the medical system 20 returns to step S201.

[Processing executed by the pharmacy system]
Next, a description will be given of the processing executed by the pharmacy system 30. FIG.

As shown in FIG. 13, the acquisition unit 361 acquires the QR code of the medical interview code displayed on the display unit 14 of the mobile terminal 10 read by the reading unit 34, and determines whether or not the acquired QR code of the medical interview code indicates the purchase of an over-the-counter drug (step S301). If the acquisition unit 361 determines that the QR code of the medical interview code indicates the purchase of an over-the-counter drug (step S301: Yes), the pharmacy system 30 proceeds to step S302, which will be described later. On the other hand, if the acquisition unit 361 determines that the QR code of the medical interview code does not indicate the purchase of an over-the-counter drug (step S301: No), the pharmacy system 30 proceeds to step S306, which will be described later.

In step S302, the pharmacy control unit 36 checks the inventory of the over-the-counter drug corresponding to the QR code of the medical interview code based on the inventory information recorded in the recording unit 35.

Next, the payment unit 362 determines whether the user's mobile terminal 10 has paid for the over-the-counter drug by electronic payment (step S303). If the payment unit 362 determines that the user's mobile terminal 10 has paid for the over-the-counter drug by electronic payment (step S303: Yes), the payment unit 362 provides the over-the-counter drug (step S304). In this case, the payment unit 362 communicates with the payment server 40 via network N100 and accepts payment of the amount corresponding to the over-the-counter drug. On the other hand, if the payment unit 362 determines that the user's mobile terminal 10 has paid for the over-the-counter drug by electronic payment (step S303: No), the pharmacy system 30 proceeds to step S306, which will be described later.

In step S305, the communication control unit 363 transmits to the medical system 20 the patient information of the user of the mobile terminal 10 contained in the QR code of the medical interview code acquired by the acquisition unit 361, the provided medicine (over-the-counter medicine), and the date and time. Furthermore, the communication control unit 363 records in the purchase recording unit 352 of the recording unit 35 the patient information of the user of the mobile terminal 10 contained in the QR code of the medical interview code acquired by the acquisition unit 361, the provided medicine (over-the-counter medicine), and the date and time, in association with each other. After step S305, the pharmacy system 30 returns to step S301.

In step S306, the pharmacy control unit 36 executes the other mode. After step S306, the pharmacy system 30 returns to step S301.

According to the embodiment described above, the mobile device 10 accepts input of the user's symptoms, outputs related information for alleviating the symptoms, and after outputting the related information, accepts input of the user's physical condition and recommends medical institutions related to the physical condition and symptoms, thereby making it possible to propose appropriate responses to each individual's symptoms.

In one embodiment, the mobile terminal 10 searches the knowledge DB 242 for over-the-counter drug information related to the symptoms and outputs it, searches the knowledge DB 242 to accept input of the user's physical condition, and recommends medical institutions related to the physical condition and symptoms, thereby suggesting the medical institution best suited to the user's current physical condition.

Furthermore, in one embodiment, after the user purchases an over-the-counter drug, the mobile device 10 displays information on the display unit 14 prompting the user to input their physical condition after a predetermined time has elapsed, and accepts the user's input of their physical condition, thereby making it possible to suggest the most appropriate medical institution taking the user's behavior into consideration.

Furthermore, in one embodiment, the mobile terminal 10 displays related information and the medical interview code D1 (first medical interview code) on the display unit 14, so even if the user has no knowledge of over-the-counter drugs, they can easily purchase over-the-counter drugs that correspond to their symptoms by simply presenting the drug at the pharmacy.

Furthermore, in one embodiment, the mobile terminal 10 creates a medical interview code D2 (second medical interview code) that includes at least the user's symptoms, the user's physical condition, the user's behavioral history, such as the purchase or administration of over-the-counter medications, and the user's vital signs, and displays this medical interview code D2 on the display unit 14. This allows the user to easily present the details of the medical interview form to a doctor, and the doctor can provide medical care to the user based on the details obtained from the second medical interview code D2.

In one embodiment, the mobile terminal 10 searches the knowledge DB 242, but this is not limited to this. For example, the mobile terminal 10 may request and output over-the-counter drug information related to symptoms from a generation AI that lists the over-the-counter drug information or medical institution that is best suited to the symptoms from at least multiple over-the-counter drug information related to multiple over-the-counter drugs that can be purchased externally, the efficacy and ingredient information for each of the multiple over-the-counter drug information, and the medical department information and medical procedure information for each of multiple medical institutions, and then request and have the generation AI recommend a medical institution related to the physical condition and symptoms.

Various inventions can be created by appropriately combining multiple components disclosed in the recommendation system according to the embodiment of the present disclosure described above. For example, some components may be deleted from all of the components described in the recommendation system according to the embodiment of the present disclosure described above. Furthermore, the components described in the recommendation system according to the embodiment of the present disclosure described above may be appropriately combined.

Furthermore, in a recommendation system according to one embodiment of the present disclosure, the above-mentioned "unit" can be read as "means" or "circuit." For example, a control unit can be read as a control means or a control circuit.

In addition, the program executed by the recommendation system according to one embodiment of the present disclosure is provided as file data in an installable or executable format recorded on a computer-readable recording medium such as a CD-ROM, flexible disk (FD), CD-R, DVD (Digital Versatile Disk), USB medium, or flash memory.

Furthermore, the program executed by the recommendation system according to one embodiment of the present disclosure may be stored on a computer connected to a network such as the Internet, and may be configured to be provided by being downloaded via the network.

Note that in the explanations of the flowcharts in this specification, expressions such as "first," "then," and "continue" are used to clearly indicate the order of processing between steps, but the order of processing required to implement the present invention is not uniquely determined by these expressions. In other words, the order of processing in the flowcharts described in this specification can be changed as long as there are no contradictions. Furthermore, programs are not limited to these simple branching processes; branching may be achieved by comprehensively determining more judgment items. In this case, artificial intelligence technology such as machine learning, which involves prompting the user to perform manual operations and repeating learning, may also be used in combination. Furthermore, the operating patterns used by many experts may be learned, and deep learning may be used to incorporate more complex conditions.

The above describes in detail some of the embodiments of the present application based on the drawings, but these are merely examples, and the present invention can be implemented in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the disclosure of the present invention.

1 Recommendation system 10 Mobile terminal 11, 21, 31 Communication unit 12 Sensor group 13, 22, 32 Input unit 14 Display unit 15, 24, 35 Recording unit 16 Control unit 20 Medical system 23, 33 Output unit 25 Server control unit 30 Pharmacy system 34 Reading unit 36 Pharmacy control unit 40 Payment server 100 Doctor terminal 151, 241, 351 Program recording unit 152 Time information recording unit 153 Payment information recording unit 154 Mobile terminal identification information recording unit 161, 251, 361 Acquisition unit 162 Symptom reception unit 163 Output control unit 164 Action history acquisition unit 165 Physical condition reception unit 166 Recommendation unit 167 Transmission control unit 168 Creation unit 169, 362 Payment unit 242 Knowledge database 252 Search unit 253 Determination unit 254, 363 Communication control unit 352 Purchase record unit N100 Network

Claims (20)

A recommendation method executed by a recommendation device having a processor,
the processor:
a symptom receiving step of receiving an input of a symptom of a user;
an output step of searching a database in which information including a treatment method for each symptom is classified and outputting information related to relieving the symptom;
a physical condition receiving step of requesting the user to input their physical condition after the elapse of the estimated time period following the output of the related information, in accordance with estimated time period information obtained by searching the database for effectiveness information including estimated time period information until an effect is observed for each of the countermeasures;
Including,
Recommendation method. The recommendation method according to claim 1,
the processor:
a first generation step of generating a first QR code indicating a remedy as part of the related information when the remedy is included in the remedy;
a second generation step of generating a second QR code indicating the remedy and its effect when a health condition reception result of the user is obtained;
further comprising:
Recommendation method. The recommendation method according to claim 1,
the processor:
The method further includes a recommendation step of recommending a next action candidate related to the physical condition and the symptom according to a result of receiving the physical condition information of the user.
Recommendation method. The recommendation method according to claim 1,
the processor:
further comprising a behavior history acquisition step of acquiring a behavior history of the user after outputting the related information.
Recommendation method. The recommendation method according to claim 1,
the estimated time information includes a plurality of estimated times,
The physical condition reception step includes:
The content of the request for inputting the user's physical condition is changed for each of the plurality of estimated times.
Recommendation method. Please continue below.
A recommendation method executed by a recommendation device having a processor,
the processor:
a symptom receiving step of receiving an input of a symptom of a user;
an output step of outputting information related to relieving the symptom;
a physical condition receiving step of receiving input of the user's physical condition after outputting the related information;
a recommendation step of recommending a medical institution related to the physical condition and the symptom;
Implementing the following:
Recommendation method. The recommendation method according to claim 6,
The recommendation device
The system is capable of accessing a knowledge database that includes at least a plurality of pieces of over-the-counter drug information relating to each of a plurality of over-the-counter drugs that can be purchased externally, efficacy information and ingredient information for each of the plurality of pieces of over-the-counter drug information, and medical department information and medical procedure information for each of a plurality of medical institutions;
The output step includes:
searching the knowledge database for over-the-counter drug information related to the symptom and outputting the information;
The recommendation step includes:
searching the knowledge database and recommending the medical institution;
Recommendation method. The recommendation method according to claim 7,
The output step includes:
searching for and outputting the over-the-counter drug information related to the symptom from among the plurality of over-the-counter drug information;
Recommendation method. The recommendation method according to claim 8,
the processor:
After outputting the over-the-counter drug information, a behavior history acquisition step of acquiring a behavior history of the user is further performed.
Recommendation method. The recommendation method according to claim 9,
The behavioral history includes:
a purchase history or medication history of an over-the-counter drug according to the over-the-counter drug information;
The physical condition reception step includes:
After a predetermined time has elapsed since the over-the-counter drug was purchased, information prompting the user to input the physical condition is displayed on a display unit;
Accepting input of the physical condition;
Recommendation method. The recommendation method according to claim 10,
The recommendation step includes:
classifying the symptoms into a plurality of categories, and searching the knowledge database for the medical institution related to the classification result, the physical condition, the over-the-counter drug information, and the behavioral history, and recommending the medical institution;
Recommendation method. The recommendation method according to claim 11,
the processor:
a transmission control step of accepting an input of a degree of satisfaction with the over-the-counter drug information after the recommendation and transmitting the degree of satisfaction to the knowledge database;
Further execute
The knowledge database includes:
updating information on over-the-counter drugs recommended according to symptoms based on the degree of satisfaction with the effects of the over-the-counter drug information;
Recommendation method. The recommendation method according to claim 12,
The recommendation step includes:
searching the knowledge database to recommend medical institutions that have testing equipment and facilities related to the symptoms;
Recommendation method. The recommendation method according to claim 13,
the processor:
further performing a creating step of creating a first interview code including at least the symptom and the related information;
The output step includes:
outputting the related information and the first medical interview code to a display unit;
Recommendation method. The recommendation method according to claim 14,
The behavioral history acquisition step includes:
Further acquiring vital information of the user at predetermined intervals;
The creating step includes:
creating a second medical interview code including at least the symptoms, the physical condition, the behavioral history, and the vital sign information;
The recommendation step includes:
displaying the second medical interview code on a display unit;
Recommendation method. The recommendation method according to claim 15,
The recommendation step includes:
searching the knowledge database to make an appointment at the medical institution;
Recommendation method. The recommendation method according to claim 6,
The output step includes:
a generating AI that lists the over-the-counter drug information or medical institution that is most suitable for the symptom from at least a plurality of over-the-counter drug information related to the symptom and outputs the over-the-counter drug information related to the symptom, the efficacy and effect information and ingredient information of each of the plurality of over-the-counter drug information, and the medical department information and medical procedure information of each of a plurality of medical institutions;
The recommendation step includes:
The generating AI is requested to recommend the medical institution related to the physical condition and the symptoms.
Recommendation method. a symptom receiving unit that receives input of a user's symptoms;
an output control unit that searches a database in which information including a countermeasure for each symptom is classified and outputs information related to relieving the symptom;
a physical condition receiving unit that requests the user to input their physical condition after the estimated time has elapsed since the output of the related information, in accordance with estimated time information obtained by searching the database for effectiveness information including estimated time information until an effect is observed for each of the countermeasures;
Equipped with
Recommendation device. A recommendation device including a processor,
a symptom receiving step of receiving an input of a symptom of a user;
an output step of searching a database in which information including a treatment method for each symptom is classified and outputting information related to relieving the symptom;
a physical condition receiving step of requesting the user to input their physical condition after the elapse of the estimated time period following the output of the related information, in accordance with estimated time period information obtained by searching the database for effectiveness information including estimated time period information until an effect is observed for each of the countermeasures;
Execute
program. A recommendation device;
a medical system capable of communicating with the recommendation device via a network;
Equipped with
A recommendation system,
The medical system includes:
It has a database that categorizes information related to symptom recovery, including how to deal with each symptom,
The recommendation device
a symptom receiving unit that receives input of a user's symptoms;
an output control unit that searches the database for the related information and outputs it;
a physical condition receiving unit that requests the user to input their physical condition after the estimated time has elapsed since the output of the related information, in accordance with estimated time information obtained by searching the database for effectiveness information including estimated time information until an effect is observed for each of the countermeasures;
Equipped with
Recommendation system.