Medical scheduling system, medical information display device, medical scheduling method, medical information display method, medical information acquisition display method, and medical scheduling program

Abstract

This medical scheduling system includes: a patient information input unit for inputting information related to a patient; a diagnosis information input unit for inputting first physician information for a first medical institution at which a first diagnosis is performed on the patient, and also inputting the result of a first diagnosis; and a display control unit for retrieving treatment information related to a treatment corresponding to the first diagnosis result from a medical information database and displaying, in accordance with the treatment information, background information pertaining to a plurality of medical institutions capable of performing the treatment.

Description

Medical scheduling system, medical information display device, medical scheduling method, medical information display method, medical information acquisition and display method, and medical scheduling program

[0001] The present invention relates to a medical scheduling system, a medical information display device, a medical scheduling method, a medical information display method, a medical information acquisition and display method, and a medical scheduling program.

[0002] Conventionally, appointments for medical procedures are determined on a first-come, first-served basis depending on the availability of specific medical institutions, medical personnel, medical equipment, etc. For example, Japanese Patent Application Laid-Open Publication No. 2022-160794 discloses a medical appointment system that enables an appropriate number of appointments to be accepted for the medical personnel's human resources. This medical appointment system determines whether a medical institution can accept an appointment for a medical procedure based on a schedule that manages the attendance of each of multiple medical personnel working at the medical institution, the attributes of each of the multiple medical personnel, the attributes and appointment slots of appointments for medical procedures made at the medical institution, and the attributes and appointment slots of appointments for medical procedures already accepted by the medical institution.

[0003] This type of reservation method places an excessive burden on medical staff and medical equipment at each individual medical institution. Furthermore, if many patients suffer from the same symptoms, patients who make later reservations may not be able to receive medical treatment for a long period of time. Delaying medical treatment may lead to a worsening of symptoms. Furthermore, patients may need to adjust their schedules for future appointments that are currently unknown, which is likely to affect their daily lives and makes it difficult to schedule hospital appointments that meet the patient's needs.

[0004] The present invention has been made in consideration of the above-mentioned circumstances, and aims to provide a medical scheduling system, a medical information display device, a medical scheduling method, a medical information display method, a medical information acquisition and display method, and a medical scheduling program that are capable of making hospital appointments that meet the needs of patients without placing an excessive burden on medical staff or medical equipment at a single medical institution.

[0005] A medical scheduling system according to one aspect of the present invention includes a patient information input unit that inputs information about a patient, first doctor information of a first medical institution that performed a first diagnosis on the patient, and a diagnosis information input unit that inputs the results of the first diagnosis, and a display control unit that searches a medical information database for treatment information related to a treatment corresponding to the first diagnosis result and displays background information for each of a plurality of medical institutions that can perform the treatment according to the treatment information.

[0006] Another aspect of the medical scheduling system of the present invention includes a patient information input unit that inputs information about a patient, first doctor information of a first medical institution that performed a first diagnosis on the patient, and a diagnosis information input unit that inputs the results of the first diagnosis, a judgment unit that determines the content of the next treatment based on the results of the first diagnosis, a search unit that searches for doctor information and equipment information of multiple medical institutions based on the judgment result of the judgment unit, and searches for multiple medical institutions that can perform the next treatment, and a creation unit that creates an appointment screen that recommends the multiple medical institutions according to specified conditions based on the search results of the search unit.

[0007] Another aspect of the medical scheduling system of the present invention includes a user information input unit that inputs information about a user; a medical procedure candidate output unit that outputs, from the information about the user, candidates for medical procedures that the user is likely to receive treatment for in the future; a medical institution search unit that searches for information on medical institutions with medical departments that can handle the candidate medical procedures in accordance with the outputted candidates; and an assignment unit that assigns information indicating the relationship with the user's family doctor to the information of the searched medical institution.

[0008] A medical information display device according to one embodiment of the present invention includes an input unit for inputting the results of a first diagnosis of a patient, a transceiver unit for transmitting the first diagnosis result, doctor information of the first medical institution that performed the first diagnosis, and information about the patient to a medical information database in accordance with the input results, and receiving the results of a search for treatment information related to the treatment corresponding to the transmission results, multiple medical institutions that can perform the treatment, and related information about the doctors, and a display control unit for displaying the reception results.

[0009] Furthermore, a medical scheduling method according to one aspect of the present invention inputs information about a patient, inputs information about a first doctor at a first medical institution that performed a first diagnosis on the patient and the results of the first diagnosis, searches a medical information database for treatment information related to the treatment corresponding to the first diagnosis result, and displays background information about multiple medical institutions that can perform the treatment according to the treatment information.

[0010] Another aspect of the medical scheduling method of the present invention inputs information about a user, outputs candidate medical procedures for which the user is likely to receive treatment in the future from the information about the user, searches for information about medical institutions with medical departments that can handle the candidate medical procedures based on the outputted candidate medical procedures, and adds information indicating the relationship with the user's family doctor to the information about the searched medical institutions.

[0011] In addition, a medical information display method according to one aspect of the present invention includes inputting the results of a first diagnosis performed on a patient, transmitting the first diagnosis results, doctor information of the first medical institution that performed the first diagnosis, and information about the patient to a medical information database according to the input results, searching for treatment information related to the treatment corresponding to the transmission results, receiving related information about multiple medical institutions that can perform the searched treatment and the doctors, and displaying the received results.

[0012] Another aspect of the medical information display method of the present invention involves inputting the results of a first diagnosis of a patient, transmitting the first diagnosis result and information about the patient to a medical information database in accordance with the input results, searching for treatment information regarding the treatment corresponding to the transmission results, receiving relationship information between multiple medical institutions that can perform the searched treatment and the patient's primary care physician, and displaying the received results.

[0013] Another aspect of the medical information display method of the present invention acquires behavioral history information about which hospitals a user visited and when, and determines medical institutions that the user visited repeatedly within a specific period of time and with a long period of time as the user's regular doctor.When searching and displaying information about medical institutions not included in the behavioral history information, medical institutions related to the user's regular doctor are displayed in an identifiable manner.

[0014] In addition, a medical information acquisition and display method according to one aspect of the present invention displays user information in a first area of ​​a terminal screen, displays the results of a search on the terminal for schedule information of multiple medical institutions that correspond to the user information in a second area of ​​the terminal screen, and also displays information on the results of a search for relationships between the multiple medical institutions and the user's family doctor in the second area of ​​the terminal screen.

[0015] In addition, a medical scheduling program according to one aspect of the present invention causes a computer to execute the following processes: inputting information about a patient; inputting first doctor information of a first medical institution that performed a first diagnosis on the patient and the results of the first diagnosis; searching a medical information database for treatment information related to the treatment corresponding to the first diagnosis result; and displaying background information about multiple medical institutions that can perform the treatment according to the treatment information.

[0016] 1 is a block diagram showing an example of the configuration of a medical scheduling system according to a first embodiment of the present invention. FIG. 1 is a configuration diagram showing an example of a medical knowledge database 80 in FIG. 1. FIG. 2 is a diagram showing an example of an association DB 87. FIG. 3 is a diagram showing an example of a hospital association analysis unit 84 and a case-specific medical institution DB. FIG. 4 is an explanatory diagram for explaining medical-related transition data for each patient input to the hospital association analysis unit 84. FIG. 5 is a flowchart for explaining an example of the flow of a creation process of the association DB 87. FIG. 6 is an explanatory diagram for explaining an example of a scene in which a reservation clerk displays a reservation screen. FIG. 7 is an explanatory diagram for explaining an example of a conventional reservation screen. FIG. 8 is an explanatory diagram for explaining an example of a reservation screen of the present embodiment. FIG. 9 is an explanatory diagram for explaining another example of the reservation screen of the present embodiment. FIG. 10 is a flowchart for explaining the operation of the embodiment. FIG. 11 is an explanatory diagram for explaining a scene in which a patient makes a reservation at a medical institution. FIG. 12 is a diagram showing an example of a display screen displayed on a display unit when a patient makes a reservation at a medical institution. FIG. 13 is an explanatory diagram for explaining an example of a reservation screen displayed on a mobile terminal. FIG. 14 is an explanatory diagram for explaining an inference model created by the inference model creation unit 50.

[0017] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0018] (First embodiment) Fig. 1 is a block diagram showing an example of the configuration of a medical scheduling system according to a first embodiment of the present invention. Fig. 2 is a configuration diagram showing an example of a medical knowledge database 80 in Fig. 1.

[0019] The medical scheduling system 1 shown in Figure 1 is an example that includes a medical treatment information input unit 10, a schedule creation unit 20, a display unit 30, a device control (setting) unit 40, an inference model creation unit 50, an in-hospital system 60, an other facility collaboration unit 70, and a medical knowledge database 80. For ease of understanding, these are separated into their respective functions, and it is assumed that they are linked by control units such as computers consisting of hardware and software that control them, but of course, the entire system may also be controlled by a single large computer, and cases where each function is appropriately included as part of the same system are also assumed.

[0020] The medical treatment information input unit 10 includes a text input unit 11 such as a keyboard or touch panel. The text input unit 11 inputs to the schedule creation unit 20 diagnosis result information 12 including information about the diagnosis result and the doctor who performed the diagnosis, patient card information 13 including patient information such as the patient's name written on the patient card, and linkage information 14 including information about affiliated hospitals. In other words, the medical treatment information input unit 10 comprises a patient information input unit for inputting information about the patient, and a diagnosis information input unit for inputting information about the doctor who performed the diagnosis on the patient and information about the diagnosis result.

[0021] The schedule creation unit 20 includes a schedule search unit 21 , a next procedure determination unit 22 , a device selection unit 23 , an inference linking unit 24 , and a display control unit 25 .

[0022] The next treatment determination unit 22 determines the content of the next treatment to be performed based on the diagnosis result information 12 input from the medical treatment information input unit 10. The content may be determined by a doctor or medical professional based on the results of their judgment, or the next treatment may be determined uniformly depending on the symptoms and diagnosis results, and the content of such treatment may be determined based on the search results of a database or the output results of an inference model as described below.

[0023] The equipment selection unit 23 selects the equipment to be used in the next treatment based on the content of the next treatment determined by the next treatment determination unit 22. Again, the content may be determined based on the judgment of a doctor or medical professional, or the equipment for the next treatment may be uniformly determined depending on the symptoms and diagnosis results, and in such cases the content may be determined based on the search results of a database or the output results of an inference model, as described below.

[0024] The inference linking unit 24, which links with the inference model creation unit 50 and other units, can create, customize, and improve inference models as needed, and can also link with the inference models created there. With the recent spread of artificial intelligence, inference models have been created to improve efficiency in various business and service scenarios. This function allows for the creation of inference models by preparing training data tailored to the medical institution, its patients, and its business operations. For example, if a specific symptom such as a fever appears, training data can be created based on past patient symptoms and their diagnostic results, and by inputting the symptoms, potential diagnostic results can be inferred. If there are regional differences, a model can be created that is tailored to the region, resulting in customization. Using a similar approach, inference models can be created that infer, based on symptoms, the medical institution where a diagnosis should be made, the testing equipment, and the medication that should be taken. Naturally, it is also possible to infer the medical facility where the equipment and medication are located. Furthermore, as long as the factors involved are not complexly intertwined, a database can be used, and the inference linking unit 24 can link to the database. In this way, the linkage information 24 input from the medical treatment information input unit 10 and the inference model created by the inference model creation unit 50 are used to infer the affiliated hospital where the next treatment can be performed.

[0025] The schedule search unit 21 searches for schedule information including doctor schedule information (described later) and the scheduled date and time of equipment use, and searches for the schedule of the doctor who can perform the next treatment and the schedule of the equipment to be used in the next treatment selected by the equipment selection unit 23. The schedule search unit 21 also searches for the locations of the hospitals 90 and pharmacies 91, doctor information and equipment availability at the other hospitals 90 via the other facility collaboration unit 70 for other multiple hospitals 90.

[0026] With the spread of the in-hospital system 60 and various business management systems described below, such schedule information is being digitized and organized, and information is recorded automatically by manually acquiring information or by linking with devices, making it easier to check availability information and operating status (along with information on the location of use and users) remotely, for example online.

[0027] Based on the information searched by the schedule search unit 21, the schedule creation unit 20 creates a next appointment screen (see Figure 8B or Figure 8C described below) that includes multiple hospital candidates, such as the hospital where an appointment can be made earliest (priority given to date and time), the hospital closest to the patient's home or the nearest station (priority given to location), and the hospital with the largest number of cases of the patient's illness (other information).

[0028] With the recent development of ICT (Information and Communication Technology), it has become common to obtain location information on mobile devices and search maps, or to search routes on map information, so it would be good to use such technology.With this system, it is possible to predict the medical treatments that a user is likely to receive in the future from user information (symptoms, etc.), and by searching for medical institutions that can provide that treatment, the user can check, using maps and other tools, whether the relevant medical institution is nearby.

[0029] The display control unit 25 outputs the created appointment screen to the display unit 30. This is intended to be the display of an information and communication device terminal such as a personal computer, tablet, or smartphone, and the display unit 30 displays the next appointment screen created by the schedule creation unit 20 under the control of the display control unit 25. By viewing this, the schedule can be easily confirmed. Depending on the system configuration, the results of input to a specific terminal operated by a doctor at a specific medical institution (such as the doctor's schedule, potential dates for the next appointment, and the facilities and equipment to be used) can be almost simultaneously checked on a separate screen by, for example, the receptionist and accounting staff of the medical institution, and the patient can also check them on their own terminal.

[0030] The device control (setting) unit 40 sets the medical device to be used for the next treatment, as determined by the next treatment determination unit 22. This is because there are cases where it is desired to set the conditions under which the treatment will be performed on the device, and information such as doctor handover information and observation information under the same conditions may be important. If the settings are set in advance, there is no need to set the device hastily on the day of the treatment when there is little time. Increasing the rotation efficiency in this area also helps to alleviate congestion in the hospital.

[0031] The in-hospital system 60, also known as a medical information system, is a system for managing various information handled in hospitals, controlled by a computer, and manages information (data) such as medical records, tests, prescriptions, and accounting for each department of the hospital. The in-hospital system 60 is popular because it digitizes information such as medical records and reservation management, making it easy to manage and share and improving work efficiency.

[0032] For example, this in-hospital system 60 includes information 61 on multiple doctors in the hospital (which can also be used for attendance management, etc.), information 62 on patients (medical record information, etc.), and equipment information 63 that is entered each time an equipment is purchased and is used for crisis management and to understand usage status.

[0033] The information 61 about the doctor includes a doctor ID that identifies the doctor (this can be used for salary calculations and employee benefits, as employees of various occupations work here, and card verification allows for systematic understanding of entry management, relationships with patients, and relationships with other medical professionals), background information about the doctor, and doctor schedule information. The background information includes the doctor's skill information, personal connection information, and patient evaluation information that indicates patient evaluations. The doctor schedule information may be linked to a reservation system or may be entered manually based on the doctor's arrival and departure times.

[0034] The patient-related information 62 includes a patient ID for identifying the patient, the patient's hospital visit history, prescription history, doctor in charge, profile information, and reservation information. The equipment information 63 includes equipment list information including surgical equipment, and schedule information including the scheduled date and time of equipment use. Data related to collaboration with other facilities, which will be described later, may be organized and recorded in a recording unit (not shown) within the hospital system 60. Since personal information about each doctor is available within the illustrated range, this information may be used to organize and use it as information related to collaboration with other facilities.

[0035] The inter-facility linking unit 70 serves as an interface between various systems. While it may link with the in-hospital system 60, this example illustrates the possibility of linking with medical institutions other than the hospital itself through this interface. Each system is configured with its own unique specifications, and simply enabling data exchange is impossible without properly configuring communication protocols and other settings. Furthermore, simply enabling communication does not reveal what data is stored in which storage area. While this example assumes that each medical institution has a system similar to the in-hospital system 60, security and contractual restrictions mean that some information may or may not be shared. For these reasons, the schedule creation unit 20 may not be able to connect directly. In such cases, the inter-facility linking unit 70 performs processing to enable connection while overcoming such restrictions through rules established within a special framework.

[0036] The other facility collaboration unit 70 collaborates with the medical knowledge database 80 by exchanging data with it. Furthermore, the other facility collaboration unit 70 collaborates with other facilities, such as hospitals 90 and pharmacies 91, by exchanging data with them in addition to the medical knowledge database 80. This allows the schedule creation unit 20 to grasp the locations of the hospitals 90 and pharmacies 91, doctor information and facility availability at other hospitals 90, etc. As a result, the schedule creation unit 20 can create an appointment screen 8B or 8C (described later) and display it on the display unit 30.

[0037] As shown in FIG. 2, the medical knowledge database 80 is a database that holds medical knowledge, and digitally organizes medical papers, doctors' knowledge, and the latest health and medical knowledge.

[0038] In business settings, computers known as knowledge management tools are often used to build systems that enable the smooth sharing of know-how and knowledge accumulated by personnel and departments throughout the company. Known systems include those specialized in knowledge accumulation and sharing, those capable of creating FAQs (a service that uses highly accurate AI specialized in language processing to answer ambiguous free-text questions and provide support with recommendation functions. For example, AI specialized in language processing can address linguistic inconsistencies and provide answers), those capable of creating knowledge sharing tools, those supporting help desks, and those with excellent information search capabilities. A medical version of such a system could be established by public institutions such as governments and universities to reduce the burden on future medical fields and patients and enable the development of high-quality medical services. The information stored in the medical knowledge database 80 is, for example, medical diagnosis information that can be used for medical diagnoses. The medical knowledge database 80 includes a control unit 81, a communication unit 82, multiple case-specific databases (DBs) 83, a hospital linkage analysis unit 84, and a medical facility background information recording unit 85. 2 shows one of a plurality of case-specific DBs 83. The control unit 81 may be configured by a processor using a CPU (Central Processing Unit) or FPGA (Field Programmable Gate Array), may operate according to a program stored in a memory (not shown) to control each unit, or may realize some or all of its functions using a hardware electronic circuit. In some cases, this function is realized by several systems working together.

[0039] The control unit 81 is responsible for overall control of the medical knowledge database 80, and may control cooperation with external devices by controlling the communication unit 82, storing and searching information in the database, and managing the case-specific DB 83. The communication unit 82 communicates with external devices via a predetermined transmission path to exchange data. The control unit 81 receives various information to be recorded in the case-specific DB 83 via the communication unit 82 and builds the case-specific DB 83. This mainly records the contents of medical textbooks according to rules, but it is also possible to incorporate the contents of new papers and the like as appropriate.

[0040] The case-specific DB 83 stores information for each case, including the disease name, affected area, onset symptoms, subjective symptoms, causal information, treatment information, progress information, and representative patient information for that case. This organized data allows for searching the information organized in a database, and for an inference model trained by using the organized data as training data to output disease name candidates based on onset symptoms and subjective symptoms. Such inference and search may be performed by the control unit of the knowledge database 80, or by the inference linking unit 24 or display control unit 25 of the schedule creation unit 20. Given the disease name, the DB 83 also contains the associated tests, procedures, and treatment methods. Therefore, by inputting information about the user through the medical procedure information input unit 10, it is possible to output medical procedures that the user is likely to undergo in the future. The part responsible for these functions may be referred to as a medical procedure candidate output unit. This function may be primarily performed by the next procedure determination unit 22 of the schedule determination unit 20. Furthermore, if the disease requires an examination that requires specific equipment, the equipment selection unit 23 searches for this in the knowledge database 80 and outputs it.

[0041] Videos in which doctors or other medical professionals explain various types of medical technology, such as the medical instruments used in the treatment of each case, how to use them, and the state of the procedure, may be stored on a specified server in a state accessible to users as medical knowledge. Such videos may be used as examples of representative patients. In this case, examples of information about the representative patient include patient attributes obtained from the medical record, such as age, gender, and medical history; a video ID that identifies the video related to the case; instruments used in the video to treat the case; the timing at which the video portion in which the procedure is performed (the procedure video) begins; and memo information, which is various reference information such as the difficulty and benefits of the surgery, the characteristics of the equipment, and the burden on the patient.

[0042] The causal information includes genetic information, constitution, living environment, lifestyle, environmental climate, and other information. The progress information includes records of the period leading up to the onset of the disease, such as the period until onset, and records of the period required for recovery, such as the period required for recovery.

[0043] That is, the medical knowledge database 80 stores knowledge information on the incubation period, infection route, main symptoms, testing methods, treatment methods, etc. for each type of disease. For example, knowledge information about COVID-19 indicates that the incubation period is 1-14 days, infection routes include droplets, contact, and aerosols, main symptoms include fever, muscle pain, fatigue, cough, phlegm, and impaired taste and smell, testing methods include PCR testing, and treatment methods include symptomatic treatment. Furthermore, knowledge information about influenza indicates that the incubation period is 2-5 days, infection routes include droplets and contact, main symptoms include high fever, joint pain, muscle pain, cough, sore throat, and runny nose, testing methods include antigen testing, and treatment methods include anti-influenza drugs. Data also exists about the average incubation period for each strain of COVID-19.

[0044] The medical knowledge database 80 also stores various other types of knowledge information, such as knowledge information for each disease covering a wide range of symptoms including fever, cough, phlegm, shortness of breath, sore throat, runny nose, muscle pain / joint pain, chills / shivering, fatigue / lethargy, headache, diarrhea, taste / smell disorders, etc. The medical knowledge database 80 stores this knowledge information and can provide medical diagnosis information based on the stored knowledge information.

[0045] Each medical facility background information recording unit 85 records clinic / hospital collaboration record information 86. The clinic / hospital collaboration record information 86 includes a collaboration DB 87, a collaboration inference unit 88, and a case-specific medical institution DB 89.

[0046] The link DB 87 stores, for example, a database of link information between clinics and hospitals. Through such linkages or by writing information to the database, it is possible to determine which medical facilities can treat a specific disease. It is also possible to determine the testing equipment, treatment tools, therapeutic instruments, and medications (such as diagnostic drugs) available at each facility. This allows for the provision of a medical scheduling system that includes a user information input unit for inputting information about a user, a medical procedure candidate output unit for outputting, based on the user information, medical procedure candidates that the user is likely to receive in the future, a medical institution search unit for searching for information about medical institutions with medical departments that can treat the candidate medical procedures according to the medical procedure candidates, and an assignment unit for assigning information indicating the relationship between the medical institution and the user's primary care physician to the information about the searched medical institution. Figure 3 is a diagram showing an example of the link DB 87.

[0047] The collaboration DB 87 is created based on the information in the case-specific medical institution DB 89 analyzed by the hospital collaboration analysis unit 84. Collaboration information with hospitals for each clinic is recorded in the collaboration DB 87, in this case, collaboration information 87a between Clinic X and a hospital, collaboration information 87b between Clinic Y and a hospital, etc. For example, the collaboration information 87a between Clinic X and a hospital records information such as that Clinic X collaborates with Hospital A (○), the average number of collaborative treatments is 2, that Clinic X collaborates very well with Hospital B (◎), the average number of collaborative treatments is 3, that Clinic X collaborates less well with Hospital C (△), and the average number of collaborative treatments is 1. The collaboration DB 87 also indicates patient ratings for each hospital using a number of stars.

[0048] Such information can be obtained by analyzing medical record information and the like in the in-hospital system 60, and may be obtained through cooperation with the inter-facility collaboration unit 70 and schedule creation unit 20, as shown in Figure 1. In the current environment, each facility manages its own data using its own system. While the inter-facility collaboration unit 70 and schedule creation unit 20 address these system differences and exchange information in the example shown, systems with common specifications can be connected without the inter-facility collaboration unit 70. However, due to security and contract issues, some kind of gate-like mechanism is necessary, and it is assumed that the schedule creation unit 20 will play this role. In this way, the inter-facility collaboration unit 70 understands the differences between systems, adjusts consistency, enables communication, and controls procedures such as data sharing conditions, contracts, and security protection.

[0049] In addition to the medical records mentioned above, information such as which doctor wrote which patient a referral letter to which hospital is centrally managed within each hospital's in-house system. This information may be recorded so that a non-physician, such as the reception department, can understand the rules for coordinating with a certain technician or doctor at a certain hospital for a certain test. This information may be recorded, for example, in a "schedule information" section. Each medical institution maintains a database of information about its affiliated institutions. While each medical institution maintains affiliated information to facilitate the smooth execution of its own operations, this application aims to further facilitate access to medical institutions by using this information. Such individual information may be integrated and recorded in a knowledge database. Using this data has the advantage that patients can understand the status of hospitals without visiting them, and medical institutions can also check which hospitals have similar facilities. However, maintaining a relationship diagram for each medical institution for each individual hospital is cumbersome and unrealistic. Of course, even without linking to the in-house system, each medical institution may create a relationship diagram and record it in the knowledge database.

[0050] In addition to linking with hospital systems and compiling reports from each medical institution into a database, analysis is also possible based on patient behavioral history, etc. For example, if a patient has a common habit of requesting a certain hospital when a certain test cannot be performed, this may be satisfied by simply having the phone number of the requested hospital posted on the desk of a doctor or administrative staff member. However, it is difficult to determine the collaboration relationship between a clinic or other hospitals that operates in this manner based solely on the exchange of data. The present invention is effective even in such situations, and a collaboration inference unit 88 may be provided to infer collaboration information between a clinic and a hospital, for example.

[0051] The case-specific medical institution DB 89 is a database of the analysis results of the hospital linkage analysis unit 84. Fig. 4 is a diagram showing an example of the hospital linkage analysis unit 84 and the case-specific medical institution DB.

[0052] As mentioned above, individual medical institutions may manage their operations using in-house systems with different specifications, so in order to understand the medical-related transition data 101 for each patient, the necessary items can be organized as shown in the hospital collaboration analysis unit 84 in the figure, and the method of organization can be standardized and made public as necessary, thereby organizing the contents of the case-specific medical institution DB 89.

[0053] 5 is an explanatory diagram illustrating an example of medical-related transition data for each patient input to the hospital collaboration analysis unit 84. This shows that even in cases where a hospital does not have collaboration in its in-house system, where a patient visits a different clinic at their own discretion rather than through the doctor's referral, where collaboration information is not digitized, or where the in-house system cannot grasp the information, collaboration relationships can be inferred from the patient's behavioral history and fragmentary information (when collaboration is possible with certain in-house systems but not with others, or when the in-house system simply indicates the time a specific patient visited the hospital).

[0054] Other medical history data for each patient may also be used. It may be managed systematically without the need for analysis. Furthermore, connections between individual doctors may be inferred from this linkage and used as personal network information. This is because information is kept on not only the medical institutions the patient visited, but also which doctors they were examined by.

[0055] Under the control of the control unit 81 , medical-related transition data 101 for each patient is input to the hospital link analysis unit 84 via the network 100 .

[0056] The medical-related transition data 101 is generated from the medical-related information for each patient shown in Fig. 5. For example, after a patient A is examined at Clinic X where he has a family doctor, he goes to Hospital A where there is a specialist and where appointments can be made quickly, and recovers.

[0057] Patient B is examined at Clinic X where his family doctor is located, then visits Hospital B twice, and then returns to Clinic X for further treatment until he is cured. In this case, Clinic X and Hospital B collaborate on two treatments, with a collaboration span of approximately one month.

[0058] After being examined at Clinic X where Patient C has a family doctor, he visits Hospital C three times and then returns to Clinic X for treatment. In this case, Clinic X and Hospital C have collaborated on treatment three times, with the collaboration span being approximately three and a half months.

[0059] After being examined at Clinic X where his family doctor is located, Patient D has been undergoing treatment at Hospital C, visiting the hospital five times. Such medical-related information for each of Patients A, B, C, and D is input to the hospital linkage analysis unit 84 as medical-related transition data 101.

[0060] The hospital collaboration analysis unit 84 analyzes the medical-related transition data 101 for disease classification, affected area classification, patient attributes, family doctor information, affiliated hospital information, collaboration span, and effectiveness assessment (cured or currently being treated), and generates a case-specific medical institution DB 89. The hospital collaboration analysis unit 84 generates organized data 89a and 89b for each disease name and records them in the case-specific medical institution DB 89. The organized data 89a and 89b associate information such as the affected area, symptoms, patient attributes, family doctor, affiliated hospital, collaboration span, collaboration information, and whether cured or currently being treated with each disease name. The collaboration information includes background information about the medical institution (skills of the medical institution, collaboration information between medical institutions, and personal connections between doctors at the medical institution). When the schedule creation unit 20 determines the next treatment, it references the information in the case-specific medical institution DB 89 in each medical facility background information recording unit 85, obtains background information about multiple medical institutions that can provide the next treatment, and displays the information on the display unit 30.

[0061] The Japan Medical Association defines a "family doctor" as "a nearby, reliable doctor who can provide consultation on any health-related issue and, if necessary, referrals to specialized medical institutions." The association encourages individuals to designate a doctor for their local clinic or hospital, where they can receive appropriate health guidance when experiencing symptoms such as fever, fatigue, or loss of appetite. This, in turn, can help to level the strain on the national healthcare system. Depending on a patient's health concerns, they can choose from a wide range of specialties, including internal medicine, surgery, pediatrics, gynecology, ophthalmology, otolaryngology, dermatology, orthopedics, and urology. For example, a patient with allergies and back pain could choose two family doctors: an internal medicine doctor and an orthopedic surgeon. From health consultations in daily life to consultations and hospital visits for injuries and illnesses, a "family doctor" is expected to support health. Patients can choose which of multiple family doctors to visit based on their past experience and their health condition. Since patients regularly visit these doctors for health consultations, it is possible to infer their primary care physician from the behavioral history in the database, information on whether the in-hospital patient card or My Number card was used, or to allow each patient to enter the name of their primary care physician and the name of the medical institution where they work in a specific recording area. Patients often visit their primary care physician when receiving a periodic influenza vaccine, and it is possible to infer their primary care physician from these medical records. On such occasions, the patient's overall health status is often ascertained, and medical institutions that have such medical records may have records of the patient's health status, making it easier to consult with them after the vaccination.

[0062] The skills of medical institutions, the skills of their physicians (specialties, years of experience), the medical departments at the medical institution, the number of medical professionals, the number of hospital beds, and the types and number of testing equipment may be recorded in the in-hospital system 60 (and such physician information may also be made public on the website). In recent years, physicians who are highly conscious of collaboration may post some of this information on social media or other Internet medical services as their own background information. This information may be recorded in a medical knowledge database or on a server that provides the relevant service. The present application enables collaboration with such systems via the other-facility collaboration unit 70, etc. Of course, the schedule creation unit 20 may record such information, but since centralized management would make updating difficult, the latest information may be collected and analyzed from various computers connected to the Internet.

[0063] Regarding information on collaboration between medical institutions, medical information collaboration networks are being established in each region, with a trend toward sharing information through common systems and the Internet. These networks are overseen by the Ministry of Health, Labor, and Welfare and local governments. Organizations developing and marketing these systems and applications monitor their implementation status and compile collaboration information into databases. Specific affiliated hospitals may also be connected through social networking services (SNS), and collaboration can be determined from SNS information. Systems for sharing medical record information are also in place, and hospitals that have implemented these systems are considered to be collaborating with each other. Furthermore, many medical institutions already have established collaborations, and this information is made public by each institution, or collaboration between medical institutions can be confirmed by collecting patient consultation history data. Local governments may also have policies promoting collaboration between medical institutions. In such circumstances, collaboration is likely occurring within the same region.

[0064] Regarding information on the connections between doctors at medical institutions, as medical information networks are being built in each region and information is increasingly being linked via common systems and the Internet, organizations developing and marketing these systems and applications are tracking their implementation status and compiling information on doctor networks and other collaborations into databases. Specific doctors may also be connected through social networking services (SNS), and this information can reveal collaborations. Furthermore, since systems for sharing medical record information are in place and hospitals that have implemented these systems are likely to collaborate with each other, it is possible to infer or confirm connections between doctors based on the viewing history of individual doctors in that information. Furthermore, many medical institutions already have established collaborations between doctors, and this information is made public by each institution, or by collecting patient consultation history data, doctor collaborations can be confirmed. Furthermore, local governments sometimes have policies promoting collaboration between medical institutions. In such situations, doctors in the same region are likely to collaborate.

[0065] Networks between doctors at medical institutions can be formed through medical journals, academic societies, doctor-oriented information websites, research groups, study groups, etc., and the organizations that set up these venues may compile information. This type of collaboration between doctors will become even more important in the future in an age of advanced remote communication technology, allowing medical institutions in areas with few doctors to respond immediately to cases outside the specialty of their on-staff doctors, enabling early treatment before the patient's condition worsens.

[0066] In other words, the system of the present application not only searches for information on medical institutions with medical departments that can handle the medical procedures the user wants or should receive from this information, but also adds information indicating the relationship with the user's family doctor from the personal connection information. This function may be provided by the display control unit 25, or by the linkage information unit 14. In this way, the relationship between the user's family doctor and other doctors, or the medical institutions to which those doctors belong, can be determined by searching a database or analyzing information on the patient's behavioral history.

[0067] Currently, the development of services to support this kind of collaboration among doctors is also underway, and doctor networks are becoming increasingly digitalized. (Examples: MediGuru: "Service to strengthen regional medical collaboration"; Join: "Family doctors can consult with specialists via chat.")

[0068] Furthermore, even if there is no information that Clinic X in Figure 5 is a family doctor, it is possible to analyze whether this is a family doctor from the user's behavioral history. Since Patients B and C ultimately return to Clinic X for consultation, even if they visit multiple doctors or other hospitals within a specific period, it is possible to determine that Clinic X, where they ultimately return for consultation, is a family doctor. In other words, by obtaining behavioral history information on which hospitals the user visited and when, it is possible to determine medical institutions that the user visited repeatedly within a specific period and with a long period of time as their family doctor. This result can be used to display the information shown in Figure 8C (described below). For example, a medical information display method can be provided that, when searching and displaying information about medical institutions not included in the behavioral history, identifiable medical institutions related to the family doctor can be displayed.

[0069] Here, a description will be given of the creation process of the linkage DB 87. Fig. 6 is a flowchart for explaining an example of the flow of the creation process of the linkage DB 87.

[0070] First, medical institution transition data 101 for each patient is input to the hospital collaboration analysis unit 84 (S1). The hospital collaboration analysis unit 84 determines whether there are any candidate clinics in the collaboration DB 87 (S2). If the hospital collaboration analysis unit 84 determines that there are no candidate clinics in the collaboration DB 87 (S2: NO), it terminates the processing. On the other hand, if the hospital collaboration analysis unit 84 determines that there are candidate clinics in the collaboration DB 87, it classifies the disease name and the affected area and organizes them by disease name and affected area (S3).

[0071] Next, the hospital collaboration analysis unit 84 determines whether there is a collaboration hospital for the disease name and affected area (S4). If the hospital collaboration analysis unit 84 determines that there is no collaboration hospital for the disease name and affected area (S4: NO), it determines the collaboration level to be 1 (low collaboration level) (S5). Thereafter, the hospital collaboration analysis unit 84 determines whether the patient has recovered or is undergoing treatment (S6) and proceeds to the processing of S12.

[0072] On the other hand, if the hospital collaboration analysis unit 84 determines that there is a collaboration hospital for the disease name and affected area (F4: YES), it determines whether any patients have returned from the collaboration hospital (S7). If the hospital collaboration analysis unit 84 determines that no patients have returned from the collaboration hospital (S7: NO), it determines that the collaboration level is 2 (medium collaboration level) (S8). Thereafter, the hospital collaboration analysis unit 84 determines whether the patient has recovered or is undergoing treatment (S9) and proceeds to the processing of S12.

[0073] On the other hand, if the hospital collaboration analysis unit 84 determines that a patient has returned from a collaborating hospital (S7: YES), it determines the collaboration level to be 3 (high collaboration level) (S10). Thereafter, the hospital collaboration analysis unit 84 determines whether the patient has recovered or is undergoing treatment (S11), and proceeds to the processing of S12.

[0074] Next, the hospital collaboration analysis unit 84 determines whether or not the aggregation for the candidate clinic has been completed (S12). If the hospital collaboration analysis unit 84 determines that the aggregation for the candidate clinic has not been completed (S12: NO), it returns to the processing of S2 and repeats the same processing. On the other hand, if the hospital collaboration analysis unit 84 determines that the aggregation for the candidate clinic has been completed (S12: YES), it creates a database in the inference DB 87 (S13) and returns to the processing of S2.

[0075] When the data for all candidate clinics has been compiled and put into a database, it is determined in the process of S2 that there are no candidate clinics, and the process ends.

[0076] Next, the reservation screen created by the schedule creation unit 20 will be described. FIG. 7 is an explanatory diagram illustrating an example of a scene in which a reservation clerk displays the reservation screen. As shown in FIG. 7, for example, a receptionist (reservation clerk 110) at a family doctor's clinic displays the reservation screen on a display unit 30, which is a computer display. This reservation reception does not have to be performed by a family doctor's receptionist; for example, it may be performed when a patient goes to an emergency hospital to receive first aid and makes a next reservation at the same time. This reservation method is also effective in applications in situations where, after receiving a consultation at a hospital with a medical department that the patient has not previously visited, the patient makes a reservation at another hospital for a second opinion.

[0077] In this embodiment, various information is collected in the in-hospital system (60 in FIG. 1), so in many cases, it is possible to display information such as that shown in FIG. 8 using only the information held by the in-hospital system. In particular, there are many cases where other affiliated medical institutions are systematically connected, and such information can be easily added, as indicated by reference numeral 132 in FIG. 8C. However, there are cases where a patient prefers a medical institution with which they have not previously affiliated, based on ease of access, availability of parking, or reputation. In such cases, the other-facility linking unit 70 in FIG. 1 establishes communication, acquires information, checks the schedule, and the display control unit 25 organizes and displays the information as shown in FIG. 8B.

[0078] Fig. 8A is an explanatory diagram illustrating an example of a conventional reservation screen, Fig. 8B is an explanatory diagram illustrating an example of the reservation screen of this embodiment, and Fig. 8C is an explanatory diagram illustrating another example of the reservation screen of this embodiment.

[0079] The conventional appointment screen 120 only displayed the appointment status of, for example, Hospital B, which is affiliated with the clinic where the patient's family doctor is located. This was relatively easy to do if there was already a system connection.

[0080] In contrast to this, in this embodiment, as shown in Figure 1, an effort has been made to enable collaboration with medical institutions with which there has been no collaboration until now, because the schedule creation unit 20 can search for schedules (availability of doctors who can perform treatment and availability of equipment required for treatment), location information of hospitals 90, etc. of other multiple other hospitals 90 via the other facility collaboration unit 70 (which understands the differences between the systems, adjusts consistency, enables communication, and controls procedures such as conditions for data sharing and contracts). Based on this information, the schedule creation unit 20 creates an appointment screen 130 or 131 and displays it on the display unit 30.

[0081] The appointment screen 130 of this embodiment includes patient information, which includes information on the patient ID and diagnosis results, and next schedule information. The next schedule information indicates that an appointment can be made at Hospital A on February 6th, with priority given to date and time, at Hospital C on February 14th, with priority given to location, and at Hospital D on February 20th, with other information. The other information indicates hospitals with a large number of cases of the patient's illness.

[0082] The other information may, for example, display hospitals affiliated with the patient's family doctor. The appointment screen 131 shown in FIG. 8C indicates that an appointment can be made on February 22nd at Hospital B, which is affiliated with the patient's family doctor, in the other information of the next schedule information. Here, three hospitals are searched, but more than three medical institutions may be searched and displayed. Since it is difficult to choose if there are too many, the number of medical institutions displayed is limited to a few, at most about 10, based on the patient's accessibility and the ability to receive treatment quickly.

[0083] Patients want to receive treatment quickly at a large hospital, fearing that their symptoms will worsen (priority is given to date and time). Patients also want to receive treatment at a hospital close to their home or the nearest station, considering that they will have to make long visits to the hospital (priority is given to location). Patients also want to receive treatment with peace of mind at a hospital that is affiliated with their family doctor (priority is given to other information).

[0084] In cases where a patient needs to go to another hospital after first aid, or when a patient needs a second opinion after a consultation at a hospital for the first time due to an unfamiliar illness, the date and location are important factors. However, displaying the relationship with the patient's primary care physician and including it as a selection option provides a sense of security for the patient. This is because the patient can easily consult with the primary care physician even if they are not an expert. In other words, when a patient inputs the results of their first diagnosis and searches for the next treatment information (including second opinions) based on the results, and then selects multiple medical institutions that can provide the treatment, displaying the relationship information with the patient's primary care physician is sufficient. In cases such as second opinions, it would be meaningless to select the same doctor, so when searching, a clinic other than the one at reception should be selected.

[0085] In this way, by displaying user information in the first area 130a of the terminal screen (appointment screen 130), displaying the results of a search on the terminal for schedule information of multiple medical institutions that can accommodate the user information in the second area 130b of the terminal screen, and displaying the results of a search for relationships between multiple medical institutions and the user's family doctor in the second area, it is possible to easily select a medical institution that suits the user's schedule or that gives the user peace of mind depending on the situation. In other words, by obtaining behavioral history information on which hospital the user visited and when, a medical institution that the user visited repeatedly within a specific period and has a long cycle of visits is determined to be the family doctor, or if a family doctor is determined based on information written in an in-hospital system or information recorded on the user's mobile terminal, when searching and displaying information on a new hospital (a medical institution not in the behavioral history), medical institutions related to the family doctor are displayed in an identifiable manner.

[0086] In this embodiment, the schedule creation unit 20 creates the appointment screen 130 or 131, allowing the patient to select a hospital from among multiple hospitals that best meets the patient's needs as described above.

[0087] Next, the operation of the embodiment configured as described above will be described with reference to Fig. 9. Fig. 9 is a flowchart for explaining the operation of the embodiment. Control of such a flow may be mainly performed by the display control unit 25 of a device called the schedule creation unit 20. Alternatively, it may be performed in cooperation with a device called the medical treatment information input unit 10.

[0088] First, patient information is input from the medical treatment information input unit 10 (S21), and then a diagnosis result is input (S22). The patient information is input based on the patient card information 13, and the diagnosis result is input based on the diagnosis result information 12.

[0089] Next, the next treatment determination unit 22 determines the content of the next treatment based on the input diagnosis results (S23). Subsequently, the schedule search unit 21 determines the equipment and skills required for the next treatment and searches for a medical institution (doctor) that can perform the treatment (S24). The equipment required for the next treatment is selected by the equipment selection unit 23. For example, in the case of abdominal pain, if it is mild, it may be possible to diagnose it by palpation, etc., but if it is not mild, it is more reassuring to have CT, MRI, or endoscopic examination equipment in the equipment from the beginning and to have a doctor or technician who can operate it, so that these examinations can be performed immediately.

[0090] Next, the schedule creation unit 20 recommends candidate medical institutions based on the amount of available time (S25). Subsequently, the schedule creation unit 20 recommends candidate medical institutions based on accessibility (distance) (S26). The schedule creation unit 20 then recommends candidate medical institutions based on their track record of collaboration with the patient's primary care physician (S27). The track record of collaboration with the patient's primary care physician may be inferred by the inference collaboration unit 24 based on the collaboration information 14 input from the medical treatment information input unit 10, or the collaboration information may be acquired by accessing the collaboration DB 87 of the medical knowledge database 80 via the other facility collaboration unit 70.

[0091] It should be noted that steps S25, S26, and S27 are merely examples for easy understanding, and are applicable in various ways, such as restricting accessibility and selecting the earliest available results. Of course, the search results may be displayed after listening to the patient's requests from the beginning and restricting which items are prioritized. The extent of collaboration with the patient's primary care physician may be quantified and color-coded, or the size of the icon may be made easy to see, allowing the degree of collaboration to be confirmed.

[0092] Next, the schedule creation unit 20 displays the appointment screen 130 (131) including information about the medical institution recommended in the processes of S25 to S27 on the display unit 30 (S28). Subsequently, the schedule creation unit 20 determines whether or not a medical institution has been selected on the appointment screen 130 (131) (S29). If the schedule creation unit 20 determines that a medical institution has not been selected on the appointment screen 130 (131) (S29: NO), it returns to the process of S21 and searches for other candidate medical institutions.

[0093] On the other hand, if the schedule creation unit 20 determines that a medical institution has been selected on the reservation screen 130 (131) (S29: YES), it makes a reservation with the medical institution (doctor), reserves equipment, and prepares facilities (setting up medical equipment to be used in the next treatment) (S30).

[0094] Finally, the schedule creation unit 20 determines whether all processing has been completed (S31). If the schedule creation unit 20 determines that all processing has not been completed (S31: NO), the schedule creation unit 20 returns to the processing of S21 and repeats the same processing. On the other hand, if the schedule creation unit 20 determines that all processing has been completed (S31: YES), the schedule creation unit 20 ends the processing.

[0095] As described above, the schedule creation unit 20, by linking with the medical knowledge database 80 and multiple other hospitals 90 via the other facility linkage unit 70, displays on the display unit 30 the reservation screen 130 (131) that allows a patient to make a reservation with a medical institution that prioritizes date and time, a medical institution that prioritizes location, or a medical institution that prioritizes collaboration with a family doctor. As a result, a patient can make a reservation with a medical institution that meets their needs from the multiple medical institutions displayed.

[0096] A medical information device can be provided that has: a transceiver unit that receives, in accordance with the results of a first diagnosis of a patient, the first diagnosis result, doctor information of the first medical institution that performed the diagnosis, and information about the patient to a medical information database and searches for treatment information related to the treatment corresponding to the transmission result, and relationship information between multiple medical institutions that can perform the treatment and the doctors; and a display control unit that displays the reception result.

[0097] Second Embodiment Next, a second embodiment will be described. In the second embodiment, a situation where a patient himself / herself makes a reservation at a medical institution will be described. Fig. 10 is an explanatory diagram for explaining a situation where a patient makes a reservation at a medical institution.

[0098] A patient P makes a reservation at a medical institution using a mobile terminal 200 such as a smartphone or tablet terminal. The mobile terminal 200 is made up of a medical treatment information input unit 10 and a display unit 30 shown in FIG.

[0099] FIG. 11 is a diagram showing an example of a display screen displayed on the display unit when a patient makes a reservation at a medical institution.

[0100] The display screen 30A displayed on the display unit 30 has a patient information display area 140 in which a patient profile is displayed, and a symptom input area 141 for inputting symptoms. The patient information display area 140 has a patient profile field. The patient profile field displays the profile of the user who owns the mobile terminal 200.

[0101] The symptom input area 141 has a symptom input field 142 for inputting the main symptom, and a message display field 143. A symptom such as "lower back pain" is input in the symptom input field 142. A message such as "touch the area where the symptom is present" is displayed in the message display field 143. By touching the area where the symptom is present in response to this message, the patient P can display the area where the symptom is present 144 in the symptom input area 141.

[0102] The information entered on the display screen 30A is input to the schedule creation unit 20. As in the first embodiment, the schedule creation unit 20 searches for the availability of doctors and equipment at multiple other hospitals 90 via the other facility collaboration unit 70, creates a reservation screen, and transmits it to the mobile terminal 200.

[0103] 12 is an explanatory diagram illustrating an example of an appointment screen displayed on a mobile terminal. An appointment screen 150 created by the schedule creation unit 20 is displayed on the display unit 30 of the mobile terminal 200. The appointment screen has a patient information display area 151 including a patient profile and diagnosis results, and a schedule information area 152 for making an appointment at a medical institution.

[0104] The schedule information area 152 displays a schedule display 153 showing the schedules of a plurality of medical institutions for which reservations can be made, and a map display 154 showing the locations of the plurality of medical institutions.

[0105] The schedule display 153 displays the date at the top and the priority order at the left, with "Clinic A" displayed as a candidate if priority is given to date and time, "Clinic C" displayed if priority is given to location, and "Clinic B" displayed if priority is given to a family doctor as other information. The map display 154 displays a map showing the locations of "Clinic A," "Clinic B," and "Clinic C."

[0106] Patient P can easily make a reservation at a medical institution prioritizing date and time, location, or family doctor by referring to the display in the schedule display field 153 and touching the medical institution that meets his / her preference.

[0107] When the patient P inputs symptoms using the mobile terminal 200 and transmits them to the schedule creation unit 20, the schedule creation unit 20 may transmit information on hospitals and clinics that are suitable for the symptoms to the mobile terminal 200. The information on hospitals and clinics that are suitable for the symptoms is inferred by the inference linking unit 24. The inference model of the inference linking unit 24 is created by the inference model creation unit 50.

[0108] FIG. 13 is an explanatory diagram for explaining the inference model created by the inference model creation unit 50.

[0109] The example in Figure 13 shows the use of two inference models, a hospital inference model and a clinic inference model. A first group of teacher data is provided to network N1 for learning, and a second group of teacher data is provided to network N2 for learning. Networks N1 and N2 are trained using large amounts of teacher data, for example, deep learning, to determine the network designs of networks N1 and N2 so that outputs corresponding to the respective inputs are obtained. By performing this type of training, networks N1 and N2 are constructed as a hospital inference model and a clinic inference model, respectively.

[0110] 13, the first training data group uses information on hospital names and treated symptoms. When the symptoms of patient P are input, the hospital inference model obtained as a result of learning network N1 using the first training data group outputs information on hospitals with a track record of treating those symptoms as inference results.

[0111] The second training data group also uses information on hospital names and clinics that have a history of collaboration with the hospitals. The information on hospital names and clinics that have a history of collaboration with the hospitals can be information stored in the collaboration DB 87 of the medical knowledge database 80. The clinic inference model obtained as a result of learning the network N2 using the second training data group can obtain information on clinics that are affiliated with the disease name as an inference result by inputting a hospital (hospital name) as input.

[0112] Therefore, when patient P inputs symptoms using the mobile terminal 200 and transmits them to the schedule creation unit 20, the inference linking unit 24 can infer hospitals and clinics that are suitable for the symptoms (that have a track record of treating those symptoms) and transmit them to the mobile terminal 200. Patient P can receive treatment at a hospital or clinic that is suitable for his or her symptoms based on the information about hospitals and clinics inferred by the inference linking unit 24. For example, if the inferred hospital is a large hospital that requires a referral letter, patient P can first visit the inferred clinic and receive a referral letter from the inferred hospital that has a track record of collaboration, thereby being able to receive treatment at the inferred hospital.

[0113] Deep learning is a multilayered version of the machine learning process using neural networks. A typical example is a forward propagation neural network, which sends information from front to back and makes a judgment. In its simplest form, it requires three layers: an input layer consisting of m1 neurons, a hidden layer consisting of m2 neurons determined by parameters, and an output layer consisting of m3 neurons corresponding to the number of classes to be discriminated. The neurons in the input and hidden layers, and those in the hidden and output layers, are connected by connection weights, and a bias value is added between the hidden and output layers, making it easy to form logic gates. While three layers are sufficient for simple discrimination, increasing the number of hidden layers makes it possible to learn how to combine multiple features during the machine learning process. In recent years, neural networks with 9 to 152 layers have become practical due to their training time, judgment accuracy, and energy consumption.

[0114] Various known networks may be used for machine learning. For example, R-CNN (Regions with CNN features) or FCN (Fully Convolutional Networks) using CNN (Convolution Neural Network) may be used. This involves a process called "convolution" that compresses image features, operates with minimal processing, and is strong in pattern recognition. In addition, "recurrent neural networks" (fully connected recurrent neural networks) that can handle more complex information and flow information bidirectionally may be used to handle information analysis in which the meaning changes depending on the order or sequence of information.

[0115] To realize these technologies, conventional general-purpose arithmetic processing circuits such as CPUs and FPGAs can be used, but because much of the processing in neural networks involves matrix multiplication, GPUs and Tensor Processing Units (TPUs), which are specialized for matrix calculations, may also be used.In recent years, such dedicated artificial intelligence (AI) hardware, called "neural network processing units (NPUs)," have been designed to be integrated and embeddable with CPUs and other circuits, and may even become part of the processing circuit.

[0116] It should be noted that the steps in the flowcharts in this specification may be executed in a different order, may be executed multiple times simultaneously, or may be executed in a different order each time, as long as this does not contradict the nature of the steps.

[0117] The present invention is not limited to the above-described embodiments, and it goes without saying that various modifications, combinations, and applications are possible within the scope of the invention without departing from the spirit of the invention.

[0118] Furthermore, among the technologies described herein, many of the controls and functions, primarily those illustrated in flowcharts, can be set by a program, and the above-described controls and functions can be realized by a computer reading and executing the program. The program can be recorded or stored, in whole or in part, as a computer program product on portable media such as nonvolatile memory, including flexible disks and CD-ROMs, or on storage media such as hard disks and volatile memory, and can be distributed or provided at the time of product shipment, via portable media, or via communication lines. A user can easily realize the medical scheduling program of this embodiment by downloading the program via a communication network and installing it on a computer, or by installing it on a computer from a recording medium.

Claims

1. A medical scheduling system having: a patient information input unit for inputting information about a patient; a diagnosis information input unit for inputting first doctor information of a first medical institution that performed a first diagnosis on the patient and the results of the first diagnosis; and a display control unit for searching a medical information database for treatment information related to a treatment corresponding to the first diagnosis result, and displaying background information for each of a plurality of medical institutions that can perform the treatment according to the treatment information.

2. A medical scheduling system according to claim 1, wherein each of the background information of the plurality of medical institutions includes the skills of the medical institution, information on collaboration with other medical institutions, and information on the personal connections of the doctors at the medical institution.

3. The medical scheduling system according to claim 2, wherein the medical institution's doctor's personal network information includes information on the patient's primary care physician.

4. A medical scheduling system having: a patient information input unit for inputting information about a patient; a diagnosis information input unit for inputting first doctor information of a first medical institution that performed a first diagnosis on the patient and the results of the first diagnosis; a judgment unit for determining the content of the next treatment based on the results of the first diagnosis; a search unit for searching doctor information and equipment information of multiple medical institutions based on the judgment results of the judgment unit, and for searching for multiple medical institutions that can perform the next treatment; and a creation unit for creating an appointment screen that recommends the multiple medical institutions according to predetermined conditions based on the search results of the search unit.

5. The medical scheduling system of claim 4, wherein the appointment screen recommended based on the specified conditions includes information on medical institutions that prioritize consultation dates and times, medical institutions that prioritize access conditions, and medical institutions that prioritize collaboration with a patient's primary care physician.

6. A medical scheduling system having a user information input unit that inputs information about a user; a medical procedure candidate output unit that outputs, from the information about the user, candidates for medical procedures that the user is likely to receive treatment for in the future; a medical institution search unit that searches for information on medical institutions with medical departments that can handle the candidates for medical procedures in accordance with the output medical procedure candidates; and an assignment unit that assigns information indicating the relationship with the user's family doctor to the information about the searched medical institutions.

7. A medical scheduling system according to claim 6, further comprising a linkage information unit that establishes a relationship between the searched medical institution and the user's family doctor by searching a database or analyzing information on the user's behavioral history.

8. The medical scheduling system of claim 7, wherein the information about the user includes information about the user's current symptoms and the user's behavioral history.

9. The medical scheduling system according to claim 7, wherein the user's behavioral history is a record of the user's past visits to medical institutions.

10. A medical information display device having an input unit for inputting the results of a first diagnosis made to a patient; a transceiver unit for transmitting the first diagnosis result, doctor information of the first medical institution that made the first diagnosis, and information about the patient to a medical information database in accordance with the input results, and receiving the results of a search for treatment information related to the treatment corresponding to the transmission results, multiple medical institutions that can perform the treatment, and related information about the doctors; and a display control unit for displaying the reception results.

11. A medical scheduling method comprising: inputting information about a patient; inputting information about a first doctor at a first medical institution that performed a first diagnosis on the patient and the first diagnosis result; searching a medical information database for treatment information related to the treatment corresponding to the first diagnosis result; and displaying background information about multiple medical institutions that can perform the treatment according to the treatment information.

12. The medical scheduling method according to claim 11, wherein each of the background information of the plurality of medical institutions includes the skills of the medical institution, information on collaboration with other medical institutions, and information on the personal connections of the doctors of the medical institution.

13. The medical scheduling method according to claim 12, wherein the personal network information of the doctors at the medical institution includes information on the patient's primary care doctor.

14. A medical scheduling method that inputs information about a user, outputs candidates for medical procedures that the user is likely to receive treatment for in the future from the information about the user, searches for information on medical institutions with medical departments that can handle the candidates for medical procedures based on the output, and adds information indicating the relationship with the user's family doctor to the information about the searched medical institutions.

15. The medical scheduling method according to claim 14, wherein the relationship between the searched medical institution and the user's family doctor is determined by searching a database or analyzing information on the user's behavior history.

16. A medical information display method comprising: inputting the results of a first diagnosis made to a patient; transmitting the first diagnosis result, doctor information of the first medical institution that made the first diagnosis, and information about the patient to a medical information database in accordance with the input results; searching for treatment information relating to treatment corresponding to the transmitted results; receiving relevant information on a plurality of medical institutions that can perform the retrieved treatment and the doctors; and displaying the received results.

17. A medical information display method comprising: inputting the results of a first diagnosis of a patient; transmitting the first diagnosis result and information about the patient to a medical information database in accordance with the input results; searching for treatment information related to the treatment corresponding to the transmitted results; receiving relationship information between a plurality of medical institutions capable of the retrieved treatment and the patient's primary care physician; and displaying the received results.

18. A medical information display method that acquires behavioral history information about which hospitals a user visited and when, determines medical institutions that the user visited repeatedly within a specific period of time and with a long period of time as the user's regular doctor, and when searching and displaying information about medical institutions not included in the behavioral history information, displays medical institutions related to the user's regular doctor in an identifiable manner.

19. A method for acquiring and displaying medical information, which displays user information in a first area of ​​a terminal screen, displays the results of a search on the terminal for schedule information of multiple medical institutions that can accommodate the user information in a second area of ​​the terminal screen, and also displays information on the results of a search for relationships between the multiple medical institutions and the user's family doctor in the second area of ​​the terminal screen.

20. A medical scheduling program that causes a computer to execute the following processes: inputting patient information; inputting first doctor information of a first medical institution that performed a first diagnosis on the patient and the results of the first diagnosis; searching a medical information database for treatment information related to the treatment corresponding to the first diagnosis result, and displaying background information of multiple medical institutions that can perform the treatment according to the treatment information.

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