A system for matching patients with medical institutions.

Abstract

By specifically identifying patients' needs and having them register their needs as medical institutions, we collect and match patient needs with medical institution needs. [Solution] The server 20 receives patient information entered into the patient terminal 30. Meanwhile, medical institution information from medical institutions is entered into the medical institution terminal 10, and the server 20 receives it. Basically, medical institution information is pre-registered in the server 20, and based on this registered information, the server matches it with patient information (symptom information and symptom-related information) from the patient. The matching results are displayed on the patient terminal 30, and a suitable medical institution is recommended for the patient. The recommended medical institution terminal 10 is also notified of the recommendation. The patient can start contacting the recommended medical institution and receive treatment, and the medical institution can determine whether it is possible to treat the recommended patient by knowing the patient's symptoms and illness before starting contact with the patient.

Description

Technical Field

[0001] The present invention relates to a computer tool (system, program, method) for matching a patient with a medical institution and presenting a medical institution suitable for the patient.

Background Art

[0002] The injured and sick people, including patients considering visiting a medical institution, used to rely on the guidance information published in the telephone directory, map, or town information magazine to reserve and visit a medical institution when searching for a medical institution. Recently, they use information communication terminals such as computers and smartphones to search and reserve medical institutions through Internet information.

[0003] The medical institution selection server / method disclosed in Patent Document 1 predicts the time until treatment starts in order to select a medical institution that can treat a patient earlier. Therefore, it predicts patient classification from the patient's condition (symptoms, past history, information obtained by an emergency team member, etc.), refers to the availability of each patient classification in each hospital and the status of resources (blood test, electrocardiogram, echocardiogram, CT, contrast CT, t-PA treatment, catheter treatment) required by the patient, and selects an acceptable medical institution. It is mainly used for selecting an accepting medical institution during emergency transportation.

[0004] The hospital reservation method disclosed in Patent Document 2 can select a hospital to visit by conducting a consultation remotely. At the time of making a reservation for a first visit, online questions and answers are conducted to estimate the injury or illness, and the name of the injury or illness is estimated. If the name of the illness cannot be estimated, further questions are asked. When the name of the injury or illness and the department in charge can be estimated, the department in charge corresponding to the disease name is introduced. For each hospital, the departments it handles, its specialty departments, and the departments it does not handle are shown. After the hospital is specified, a screen for determining the reservation date and time is displayed.

[0005] The hospital appointment support device disclosed in Patent Document 3 estimates the disease name, medical specialty, and severity of the disease based on the patient's health information, and searches for hospitals that can provide treatment to determine the appointment date and time. If it is difficult to determine the disease name, etc., from the patient information alone, additional questions will be asked. Furthermore, after specifying the hospital to be treated and making an appointment for the date and time, the patient can receive instructions from the hospital via email or other means regarding what preparations should be made before the appointment.

[0006] The medical institution review information provision system disclosed in Patent Document 4 allows medical institutions to set it so that negative reviews from patients are not displayed.

[0007] Furthermore, Non-Patent Document 1 discloses a study of patients who visited our clinic after consulting multiple medical institutions, focusing on those who experienced persistent or worsening symptoms and resulting anxiety. It states that a high proportion of patients in their "40s" and "50s" consulted multiple medical institutions, and that many of their complaints were generally considered nonspecific, such as "loss of appetite," "weight loss," "chest discomfort," and "pain and numbness in the limbs."

[0008] Furthermore, Non-Patent Document 2, the Medical Information Network (Navi), operated by the Ministry of Health, Labour and Welfare and prefectural governments, allows users to search for hospitals, clinics, dental clinics, midwifery centers, and pharmacies nationwide by medical specialty, consultation days, prefecture, city / ward / town / village, and train line. In addition to general information such as consultation days and medical specialties, users can search for medical institutions nationwide based on various information such as the diseases and treatments they can handle and the services they provide. Examples of diseases and treatments include treatment for pediatric diseases, treatment for women's specific diseases, treatment for rare diseases, treatment for cardiovascular diseases, and treatment for mental illnesses. Users can select from a broad category of medical specialty and a subcategory of specific symptoms or diseases to display medical institutions. [Prior art documents] [Patent Documents]

[0009] [Patent Document 1] Patent No. 7122279 (

[0006] etc.) [Patent Document 2] JP-A-10-149391 (

[0020]

[0021]

[0030]

[0031] etc.) [Patent Document 3] Japanese Patent Publication No. 2002-99615 (e.g.,

[0013] ,

[0019] ,

[0020] ,

[0036] -

[0040] ) [Patent Document 4] Japanese Patent Publication No. 2014-119932 [Patent Document 5] Japanese Patent Publication No. 2002-236760 [Patent Document 6] Japanese Patent Application Publication No. 11-353324 [Patent Document 7] Japanese Patent Publication No. 2017-194791

[0010] [Non-Patent Document 1] Journal of the Japan Society for Pre-disease Systems, 8(2), pp. 170-172, 2002. [Non-Patent Document 2] Medical Information Network (Navi) https: / / www.iryou.teikyouseido.mhlw.go.jp / znk-web / juminkanja / S2300 / initialize

[0011] The technologies disclosed in the above patent documents involve a computer predicting the medical department, disease name, etc., based on the input patient information, and then searching for hospitals that can accept the patient and displaying the results to the patient. The computer's predictions may not match the patient's wishes or the medical institution may not be able to accommodate them, so the patient's input and the medical institution's registered information are crucial factors. In particular, as seen in the chief complaint of a patient who came to the hospital after visiting multiple medical institutions, as disclosed in Non-Patent Document 1, there are cases where suspicion arises that the medical institution's response is a mismatch for patients with vague symptoms. Furthermore, the input method disclosed in Non-Patent Document 2, in which the patient selects from a group of broad and minor categories, has the drawback that the meanings described in the selection options are medical jargon that is incomprehensible or unfamiliar to the patient.

[0012] Furthermore, Patent Document 5 discloses a technology that automatically estimates the relevant medical department when symptoms and body part information are entered, and searches for medical institutions based on that department. This technology includes logic for deriving medical departments according to body part information, gender, age, etc., but it does not disclose that medical institutions can actively register "desired treatment targets (symptoms or disease names)". Patent Document 6 discloses a technology that automatically selects the relevant medical department from symptom information entered by the user and displays medical institutions that match those conditions. In this technology as well, medical institution information is mainly registered on a medical department basis, and it is not configured so that individual medical institutions can set detailed symptoms and diseases they treat themselves. Patent Document 7 discloses a medical institution search system that associates symptoms, disease names, and test contents, and users can perform searches by selecting body part, symptoms, and disease names step by step. However, the content of the registered medical institution information is fixed, and it is not designed so that the displayed content changes dynamically based on information updated in real time, nor is it configured to match based on the treatment contents that medical institutions explicitly register as "desired" treatments.

[0013] In other words, none of the prior art discloses a configuration in which a medical institution can actively register and update the symptoms it wishes to be examined for and the attributes related to those symptoms (e.g., elapsed time), and use this information to dynamically control the matching conditions and priorities. In contrast, the present invention is configured to allow a medical institution to register and update the subjects of treatment it wishes to treat (symptom categories and their corresponding acceptable elapsed times), and based on this, it performs matching with the patient's symptom information (especially including elapsed time). Furthermore, it recalculates and redisplays the priority of the matching results in real time, triggered by an update of the medical institution information.

[0014] In addition, as a related technology outside the medical field, on-demand ride-hailing systems are known. For example, US2014 / 0063957A1 (Goggin et al.) discloses a configuration that matches user requests (ride-hailing requests) with vehicle availability information to select and present a driver. However, in this technology, the vehicle conditions are mainly based on a single threshold information such as "acceptable pickup time," and it does not maintain pairs of information of multiple categories and time ranges and perform matching for each condition. On the other hand, the present invention has a clear difference from the above technology in that it responds in real time to multiple treatment requests accepted by medical institutions based on pairs of patient symptom categories and elapsed time information.

[0015] Matching medical institutions with patients requires that both the registered symptom information from the medical institution that matches the patient's needs and the patient's symptom information and related symptom information that matches the medical services provided by the medical institution are displayed using the same terminology. Only when these match can the system display medical institutions that are suitable for the patient, thus preventing mismatches between patients and medical institutions.

[0016] Currently, patients' requests are vague and subjective, so pre-determining symptom information and related symptom information will prevent mismatches and eliminate the hassle for both patients and medical institutions of having to ask and answer additional questions. Furthermore, medical institutions' information registration is often vague and subjective, and simply registering the medical department does not guarantee that they can handle all symptoms and diseases in that department. Registering the specific symptoms and diseases they can handle / are skilled at will help match patients' requests and prevent mismatches. To give a concrete example, a physician who specializes in gastroenterology may also specialize in the liver, and in that case, their experience in treating diarrhea symptoms is often less than that of a physician specializing in the intestines. Similarly, emergency medicine departments are often excellent at handling acute cases, but have less experience in handling chronic cases. Furthermore, while it is often correct for women to first consult an obstetrician / gynecologist for lower abdominal pain, many patients with abdominal pain can be adequately treated by a gastroenterologist. Patients with sudden onset abdominal pain require a visit to an emergency medicine or cardiology department. Therefore, after asking about abdominal pain, it is only after asking about the time of onset and location of the pain that the correct medical department to consult can be determined. A mismatch between a patient's condition and the medical institution's expertise often leads to medical malpractice lawsuits and has been a source of concern for healthcare professionals. In one recent case, a patient who presented with abdominal pain was diagnosed with superior enteroartery syndrome, a vascular disease, but the diagnosis was delayed, leading to death and a medical malpractice lawsuit.

[0017] Furthermore, unlike simple search sites for restaurants that display a list of establishments that match customer A's search criteria, medical institution searches require the disclosure of specific information that identifies both A and B. To be satisfied with the matching suitability, A often has to carefully research B before making a self-assessment of the compatibility with A. For example, although many medical institution portal sites exist, patients select medical institutions based on each institution's website and reputation (reviews), which places a significant burden on patients as it requires time for research. In particular, information obtained through internet searches and reviews is often ambiguous, and the selection of reviews is up to the patient; therefore, patients need to make their own research efforts to expect a good match. Moreover, reviews of medical institutions often do not disclose whether they are evaluations of treatments outside the institution's area of ​​expertise or evaluations of treatments within the area of ​​expertise, making them often unreliable.

[0018] Furthermore, unlike search sites for restaurants that aim to attract a large number of customers, clinics that are actually run by a single doctor do not want the majority of patients to show up unexpectedly. In reality, they only want patients that they can treat to come to their clinic.

[0019] This invention was made in view of these challenges and aims to provide a tool (system, program, method) that collects and matches the needs of patients and medical institutions by specifically grasping the needs of patients and having medical institutions register their needs in advance. In other words, unlike simple searching, medical institutions also proactively present information, defining the patients they can treat and registering them on the site. At that time, it is desirable for medical institutions to present information based on the symptoms described by the patients themselves. Here, the difference between matching and searching is considered as follows: In matching, the collective brain of the information providers is proactive, whereas in searching, only one party is proactive. Because matching is proactive, it means real-time information management. In a broad sense, searching is a part of matching.

[0020] In addition, the present invention enables a medical institution to actively set the symptom categories for which it desires to conduct examinations and the acceptable elapsed time (time period after the onset) therefor. As a result, according to the medical resource situation, expertise, and response policy regarding urgency on the medical institution side, the system can reflect the distinction between the symptoms that the medical institution currently wishes to examine or the symptoms that are currently difficult to examine. Furthermore, these setting information are immediately reflected on the server side, and the matching logic is recalculated in real time. The recalculated priority information is held in the server, and the latest guidance result is immediately provided for the matching request from the patient terminal that accesses next. As a result, different from merely static filtering based on medical departments, a real-time triage function is realized in which the intention and situation changes of whether a medical institution can conduct an examination are dynamically reflected, and it is possible to provide support for selecting a medical institution that is clearly differentiated from the prior art.

Summary of the Invention

Problems to be Solved by the Invention

[0021] The present invention has the following eight features and corresponds to the purpose of utilizing limited medical resources in the region and maintaining the medical experience in the region, which are currently faced by medical institutions and Japanese medicine. Medicine has a high degree of sociality. Therefore, it is not suitable for medicine to introduce a competition principle such as that in the food service industry, where restaurants present information on a search site, customers search and select the site, and restaurants that do not receive enough customers go out of business. In order to maintain regional medicine and manage better patient experiences and resources, as in this matching system, it is necessary for medical institutions to be able to present information in real time, design appropriate matching, and for organizations such as medical associations to utilize that search experience for each department.

[0022] The first feature of the present invention is a system that takes the patient's words as "patient information" and inputs them as multiple-choice questions, and matches medical institutions based on the input content. Based on the "symptom information" and "symptom-related information" input by the patient through an electronic medical questionnaire or web form, an appropriate medical department is automatically selected. This system can clarify the symptoms by asking the patient to answer them as multiple-choice questions and derive an accurate medical department. If sufficient information cannot be obtained in the multiple-choice format, it is also possible to receive information from the patient in text format. In that case, functions such as autosuggest are used to guide the patient to standard terms as much as possible, and it is necessary to use a large language model or the like to understand the intention and convert it into search terms for more precise matching. (Unification of patient-term vocabulary, conversion of patient input to multiple-choice selection)

[0023] The second feature is a mechanism that presents additional questions related to the patient's symptoms to the patient according to the symptoms and collects detailed information about the symptoms. As an implementation method, the program presents questions related to the symptoms as multiple-choice questions, and more detailed information can be obtained by the patient answering them. Before the introduction of the matching system, medical staff confirmed detailed information such as the time course of symptoms and the location of symptoms with the patient after the examination during the examination in the examination room, and when it was different from their own specialty, they wrote a referral letter and referred the patient to another doctor. With the introduction of this system, it is possible to perform the additional information confirmation, which was previously only carried out after the examination, as a mechanism before the examination. This mechanism reduces the patient's wasted actions. As a result, it is possible to optimize the resources of medical institutions, improve patient satisfaction, and collect positive feedback content. (Promote the input of symptom-related information regarding symptoms)

[0024] The third feature is that the terminology used in symptom information and symptom-related information entered by patients is standardized across multiple medical institutions. For example, in this system, the symptoms of a patient visiting a dermatology clinic can be standardized to the question, "Are you currently experiencing any skin abnormalities?" Patients can also describe dermatological symptoms such as "my skin is itchy" or "my skin is red," but when deciding which department to visit, it is sufficient to determine whether there is a skin abnormality or not, without asking for detailed information about the specific skin symptoms. Therefore, simply asking "Are you currently experiencing any skin abnormalities?" is enough to decide whether to visit a dermatology clinic. On the other hand, for a patient with a stomach ache, more detailed questions are needed to select a department. Ideally, for a patient with a stomach ache, additional questions should be asked about gender and the location of the abdominal pain, suggesting a visit to an obstetrician / gynecologist if the pain is in the lower abdomen for a woman, and to an internal medicine specialist otherwise. In this way, the necessary symptom-related information differs depending on the symptoms, and this system is innovative in that it standardizes the terminology used for these symptoms across the entire region, allowing for consistent interpretation by medical institutions in that region and enabling subsequent feedback. For example, if a patient answers "headache" as a symptom and, in response to additional questions about the timeline, answers "it started suddenly," they often need to see an emergency specialist. Standardizing questioning about symptoms and timelines, as well as terminology, allows multiple medical institutions to consistently review which institution is best suited to provide treatment. Before the introduction of this system, patients had to search the web, select a medical institution based on the listed specialties, call the institution to confirm things like whether a CT scan was possible, and then determine the appropriateness of their visit. Furthermore, at each medical institution, the reception staff would have to verify the information received over the phone with a doctor to determine whether or not they could see the patient—a rather tedious process. After the introduction of this system, it will be possible for the entire region to discuss, using standardized terminology, which medical institutions different patients should visit and in what order, thereby improving resource plans through a PDCA cycle.The expected effects include establishing a consistent healthcare system throughout the region, enabling patients to efficiently access appropriate medical facilities. (This includes standardizing terminology for patient input within the region and designing patient flow paths.)

[0025] The fourth feature is that by actively involving medical institutions in the matching site, it becomes possible to adjust appointments based on the medical institution's availability and resource status in real time in response to patient input. For example, if a medical institution's CT scanner malfunctions and it becomes impossible to take CT scans, it becomes difficult to properly treat a patient with a "sudden onset headache." On the other hand, patients with "chronic headaches" or "headaches that have been ongoing for a year" can continue to be treated appropriately. With this system, a medical institution can present information in real time, tailored to the patient's words, such as "We cannot treat a 'sudden onset headache,' but we can treat a 'headache that has persisted for many years.'" As a result, patients can avoid unnecessary visits. The effect is that a consultation flow that is free from misunderstandings is realized for both patients and medical institutions. In addition, by placing cameras and sensors in each medical institution and using the information collected from a system that measures how long patients are waiting in the waiting room and how crowded it is in real time, patients with mild symptoms such as a cold who simply want to be tested for influenza or COVID-19 can select a medical institution with short waiting times and low crowds. In another example, by linking with map information, it's possible to predict the travel time from the current location to a medical facility, calculate and display the time it takes to visit the medical facility, wait there, finish the consultation, pick up medication at a pharmacy, and return home. Naturally, if prescriptions are filled online, it can also display the time it would take to return home without visiting a pharmacy, thus assisting users in choosing to visit a medical facility. (Improving the utilization of local medical resources through real-time information provision from medical institutions)

[0026] The fifth feature is the consistent terminology used to maintain patient data within the system. To avoid patients having to re-enter the same information each time they visit a medical institution, the system can be linked to personal healthcare records or the My Number Portal, maintain its own database, or store information in the browser. If information is stored in the cloud, patient information must be stored on a server in accordance with the three ministries' two guidelines. (Reducing the effort of duplicate data entry by maintaining personal information, and visualizing continuous medical visit information)

[0027] The sixth feature is the continuous improvement of the matching system based on collected data. By regularly reviewing patient consultation logs with local medical associations and performing process mining, the system settings can be continuously updated. To perform such process mining, a system is implemented to anonymize patient information and extract statistical data. The goal is to visualize patient flow and simultaneously improve efficiency through statistical analysis. This makes it possible to eliminate bottlenecks in regional healthcare and optimize medical resources. The resulting effects include improved speed of consultation and continuous improvement in the quality of medical care. (Patient flow design through automatic anonymization, statistical transformation, and process mining)

[0028] The seventh feature is the design of pathways across the entire region to specialists who can diagnose specific diseases or doctors who can prepare specific documents, starting with standardized patient terminology. The implementation method involves determining questionnaire responses that evoke particularly rare diseases, and then connecting patients who match these responses to specialists who can diagnose specific diseases or doctors who can prepare specific documents. By presenting the reasons and messages from the medical institutions, regional medical resources become more efficient, and appropriate responses to patient needs are made more smoothly. For example, a patient with recurrent abdominal pain would be prompted to inquire about their family history. Clinically, a patient with recurrent abdominal pain and a parent with symptoms of lip swelling should be considered for hereditary angioedema. This matching system uses an electronic questionnaire to confirm the chief complaint. For patients who report "abdominal pain," it is configured to also ask for symptom-related information such as "recurrent abdominal pain" and "family history of lip swelling." For patients who report both "recurrent abdominal pain" and "parental lip swelling," the system can recommend medical institutions that can measure "C1 inhibitor activity" and "complement C4 concentration." It would be even better to use the messaging function to instruct patients to "ask their doctor to consider testing for hereditary angioedema." (Guiding patients to doctors with appropriate qualifications and experience)

[0029] The eighth and final feature is the integration of the search system and matching system into the user experience. This matching site is designed to appear like a typical medical institution search site from the patient's perspective, allowing searches by criteria such as appointment date, desired department, parking availability, and required tests. The search screen includes buttons such as "Start department selection with electronic questionnaire" and "Select department with AI questionnaire," enabling users to review patient symptom information using the electronic questionnaire and match it with information provided by medical institutions. This integration of search and matching experiences makes it possible to design a system that will redefine the way healthcare is provided in the region. (Integration with existing search sites) [Means for solving the problem]

[0030] To solve the above problems, the present invention is based on a system that matches patients with medical institutions. This system includes symptom information entered by the patient, and symptom-related information related to that symptom, including information on the number of days since the onset of the symptom, whether it is acute, chronic, recurrent, first onset, or the location of the symptom. Medical institution information entered by the medical institution includes information on the medical departments that the medical institution can handle, or information on the symptoms and symptom-related information that the medical institution wishes to treat, and the diseases that it can treat. The system standardizes terminology for symptom information and symptom-related information related to that symptom in the region, matches this information with medical institutions while confirming their needs, and displays a medical institution suitable for the patient based on the matching results.

[0031] More specifically, the following will be provided. In the following, "patient" in the narrow sense refers to someone who has visited a medical institution, but in a broader sense, it also includes system users who have not yet visited a medical institution. "Medical institution" includes hospitals, clinics, dental offices, pharmacies, public health centers, etc.

[0032] (1A) The patient information entered by the patient includes the symptom information and symptom-related information relating to the symptom, and the symptom-related information is one or more of the following information about the symptom: the number of days since onset, acute, chronic, recurrent, first onset, and location of the symptom. Symptoms and illnesses are sometimes referred to as "chief complaints." A "chief complaint" is considered the primary symptom reported by the patient to the doctor. Since information such as pain or discomfort, carefully considered and selected by the patient, tends to be vague and subjective, doctors often need chronological information to understand the patient's symptoms. Therefore, the number of days since onset is medically converted, and the patient is asked to input their chief complaint, including information on whether it is acute / chronic, worsening / improving, or recurrence / initial onset. This chronological information is particularly important when searching for a medical institution, as it affects whether tests are performed and what equipment is used. Other information, such as the reason for the visit and desired tests, is also obtained through the electronic questionnaire. Here, symptom information, including chronological information related to the chief complaint, should be entered in the patient's own words and later converted to standardized terminology so that the system can accurately grasp the content of the chief complaint. The terminology provided by the medical institution may be specialized and difficult to understand. When the AI ​​suggests a diagnosis or other information in response to the patient's chief complaint, an index can be attached that expresses the disease and test results in simple and easy-to-understand language.

[0033] (1B) The medical institution information registered by the medical institution includes information on the medical department, the symptom information and symptom-related information that the medical institution wishes to treat. The purpose of this system is to encourage medical institutions (doctors) to provide information not only about their stated medical specialties but also about the symptoms they treat and the diseases they can treat, as the medical specialties they advertise may differ from those they actually treat. For example, even among "otolaryngologists" or "ear, nose, and throat" specialists, some may specialize in one of these areas (ear, nose, or throat) and be less proficient in treating other organs (such as the ear). Similarly, even within "gastroenterology," there are usually subspecialties such as "esophagus," "stomach," "colon," "gallbladder," and "pancreas." In such cases, a patient visiting a gastroenterologist specializing in the liver may have less experience treating diarrhea than a gastroenterologist specializing in the colon. Therefore, the system aims to create a search based on symptoms and diseases rather than just the stated medical specialty.

[0034] Claim 1 of the present invention is a matching process rather than a search process, and includes dynamic and proactive processing such as recalculating and updating the priority order based on changes in conditions on the medical institution side, thus clearly differentiating it from a search in a technical sense. Matching: Condition matching based on "symptom category" and "acceptable elapsed time" → Matching process based on mutual conditions, not keyword matching. Prioritization: "Display matching medical institutions with priority" → Display control based on the degree of match, rather than just a simple list of search results. Real-time updates: "Detects updates to medical institution information → recalculates priority" → Dynamic information updates from medical institutions affect the display results. Active participation of both parties: Medical institutions also register and update "desired consultation category + acceptable time" → while searching is passive, medical institutions are actively involved.

[0035] If an update to the medical institution information is detected, the server re-executes the extraction and prioritization process based on the update, and stores the results on the server. This makes it possible to immediately present the updated priority results to matching requests received from patient terminals thereafter, ensuring that the latest medical institution acceptance status is shared with patients in real time.

[0036] The processor stores symptom information and elapsed time information obtained from the patient terminal, as well as medical institution information including symptom categories and acceptable elapsed times updated from the medical institution terminal, in memory. Based on this information, the processor extracts medical institutions that meet the criteria, assigns a priority to them, and displays them on the patient terminal. If an update to the medical institution information is detected, the extraction and prioritization are re-executed on the server side based on the updated content, and the results are stored on the server. This makes it possible to immediately present the updated priority results to matching requests received from the patient terminal thereafter, and the latest medical institution acceptance status is shared with the patient in real time. Furthermore, by enabling medical institutions to actively register or update the symptom categories they can treat and the acceptable elapsed times for them, the intentions of the medical institution regarding acceptance or priority are directly reflected in the matching logic. This enables flexible triage guidance in response to changes in the treatment policies and resources of individual medical institutions, and realizes appropriate guidance control for multiple patients.

[0037] In this regard, the configurations in Patent Documents 1-4 are all, Enter the "Patient Information (Symptoms, etc.)" and This system searches, extracts, and displays information such as medical departments and facility conditions from the registered information of medical institutions. In all cases, there is no description or suggestion of proactive information presentation or control based on the medical institution's "desired response" or "acceptable conditions," nor is there any mention of matching, ranking, or display update processing based on dynamic conditions of both parties.

[0038] The present invention achieves matching accuracy and real-time responsiveness that cannot be realized by search-based processing. Specifically, firstly, regarding the structure of condition matching, the patent document describes a one-way search process that "searches for registered information of medical institutions based on conditions entered by the patient and displays it in a list," whereas the present invention has a significant difference in that it performs a bidirectional matching process that compares "pre-registered consultation request conditions (symptom categories and their acceptable elapsed time)" and "symptom and elapsed time information entered by the patient." Secondly, regarding the difference in matching content, the patent document uses a simple search based on keyword and category matching, whereas the present invention uses a logical matching configuration that combines multiple conditions such as "symptom category" and "their elapsed time," resulting in a more precise matching process. Furthermore, regarding display control, the patent document merely presents matching medical institutions as a list, whereas the present invention displays them with priority based on the matching results, and also has a dynamic feedback mechanism that recalculates the priority and redisplays them according to the content when the medical institution information is updated. Finally, there is a clear difference in how medical institutions are involved. In the patent document, the registration information of medical institutions is static and not intended to be updated, whereas in the present invention, medical institutions can actively update their desired treatment conditions and available time conditions in real time, ensuring that the information provided to patients is always up-to-date. In other words, the present invention is not merely an information retrieval system, but a system that enables the selection of highly suitable medical institutions based on bidirectional condition matching and the control of their display.

[0039] In one aspect of the present invention, when information from a medical institution is updated, the system detects the change in its content, recalculates the priority within a predetermined time, and updates the display content of the matching results.

[0040] For example, the processor recalculates and redisplays the priority of candidate medical institutions presented on the patient terminal within Δ seconds, more preferably within 3,600 seconds (1 hour), after detecting that the medical institution information has been updated. This allows for rapid reflection of changes in the medical institution's treatment preferences in the matching results, thus enabling the patient to always receive the latest and most appropriate medical institution information. This configuration allows medical institutions to flexibly and at any time update their desired treatment conditions regarding symptom categories and elapsed time, and the updates are reflected on the patient terminal in real time, improving the accuracy and reliability of the matching. Unlike conventional methods that statically match based solely on medical department information, this system achieves dynamic matching control that responds immediately to the needs of both patients and medical institutions.

[0041] (2) If the medical institution information consists only of department information, the department will be determined and matched based on the patient's symptom information and symptom-related information. However, if the medical institution information includes either department information or both symptom information and symptom-related information, the patient's symptom information and symptom-related information will be given priority over the department information when matching. According to this invention, the matching algorithm differs depending on the content of the registered medical institution information, and the degree of matching is influenced by prioritizing specific symptoms and disease conditions over information on medical departments. Patients matched solely based on medical department may result in medical institutions receiving patients outside their area of ​​expertise, leading to a high likelihood of mismatches. However, patients matched based on the symptoms and disease conditions desired by medical institutions are preferred by medical institutions, and the possibility of mismatches is low.

[0042] (3) After a medical visit, feedback from the patient regarding the medical institution is received and recorded in conjunction with the patient's medical information (contents entered in the electronic medical questionnaire at the time of the visit). According to the present invention, by linking patient feedback with the input content of the medical institution's electronic medical questionnaire, the chief complaint entered in the electronic medical questionnaire and the feedback are linked and recorded, which helps to understand the degree and circumstances of the mismatch.

[0043] (4) The system will automatically remind patients to provide feedback on whether they have recovered or not. According to this invention, by automatically reminding patients to input information about their recovery from illness, it is possible to obtain information about the patient's recovery. This also helps the medical institution receiving the treatment to assess the possibility of follow-up visits, provide advice, and determine whether treatment has ended once the patient has recovered. Patients will stop coming to the clinic once they have recovered, but this invention can help infer the patient's intentions if they do not come to the clinic when they have not recovered.

[0044] (5) Feedback can be set to be public or private, and furthermore, the feedback is linked to the contents entered in the electronic medical questionnaire, and regardless of whether it is public or private, the display is changed based on the content of the feedback linked to the electronic medical questionnaire from previous visits. According to this invention, the setting for making feedback public or private is important for protecting patient privacy, and referring to past feedback received by a medical institution can serve as an indicator for determining the favorability of that medical institution. Medical institutions with high favorability ratings will be displayed preferentially.

[0045] (6) Limit the visibility or privacy settings of the above feedback to a desired group, such as your acquaintances. According to the present invention, by limiting the scope of disclosure of feedback (whether public or private) to the patient's desired scope, it is possible to disclose it only to acquaintances and others without making it publicly accessible on websites. In particular, people often do not want to disclose their chief complaint or medical information to others as it is personal information, but they would be willing to share it with acquaintances so that it can be used to evaluate the quality of medical institutions.

[0046] (A system that matches patients with medical institutions based on their disease name.) (7) A system characterized by receiving patient information from a patient, including disease information and disease-related information related to the disease, wherein the patient inputs the patient information, which includes the disease information and the disease-related information, and the disease-related information includes one or more of the following information about the disease: the number of days since onset, acute, chronic, recurrent, initial onset, severity of the disease, and symptoms of the disease, and the medical institution inputs the medical institution information, which includes one or more of the medical departments that the medical institution can handle, or the disease information and disease-related information that the medical institution wishes to handle, and the processor converts the patient information into a terminology standardized in the region of each medical institution, matches one or more of the medical departments that the medical institution can handle, or the disease information and disease-related information that the medical institution wishes to handle, and displays the medical institution. The present invention is a system related to diseases, similar to (1). Furthermore, since medical institutions send messages to patients and accept appointments only after the patient has reviewed the messages, patients can choose a medical institution based on the messages they receive before making an appointment, even if multiple institutions are listed. For medical institutions, this system allows them to explain the approach to the patient's chief complaint in advance, accept appointments only after the patient understands and agrees, coordinate appointment dates and times considering factors such as congestion, and provide information on pre-arrival procedures and appropriate attire. This reduces the likelihood of mismatches between patients and medical institutions. For example, informing patients of the expected duration and examination content in advance reduces patient dissatisfaction and encourages positive feedback. Messages from medical institutions are sent using existing tools such as email and chat.

[0047] (8) The reservation management means is linked to a reservation system operated by a medical institution, and before a patient makes a reservation through the reservation system, the patient confirms a message provided by the medical institution before making the reservation. According to the present invention, this system, which is linked to a reservation system operated by a medical institution, contributes to the efficiency of administrative work.

[0048] (9) The system has a history tracking means, which tracks the history of a patient visiting multiple different medical institutions for the same chief complaint. According to the present invention, the history of a single patient visiting multiple different medical institutions for the same chief complaint is useful as part of evaluating patient satisfaction with medical institutions and collecting hidden feedback. The history of visiting different hospitals or different departments for the same chief complaint helps determine whether the medical institution's response was poor or whether the matching performance for the chief complaint was poor, leading to improvements in the medical institution's response and improvements in the system (AI retraining).

[0049] (10) The system has a search result modification unit, which dynamically changes the search results according to the time of day and the congestion status of medical institutions. According to the present invention, by displaying search results according to the consultation hours and congestion status of medical institutions, it is possible to dynamically (in real time) present only the medical institutions that are necessary for the patient.

[0050] (11) The patient inputs symptom information of the chief complaint, including symptoms, and symptom-related information related to the symptoms, based on the patient's voice input. The matching means includes a voice search unit, which combines vector search technology and voice recognition technology to search for medical institutions based on the patient's voice input. According to this invention, by changing the input of the chief complaint from text input to voice input, the patient input interface can be diversified, and it can also accommodate patients who are unable to input text due to hand diseases. Furthermore, voice input can save time for patients who are in a hurry to find a medical institution.

[0051] (12) The matching means includes a user interface, which facilitates the selection of a medical institution suitable for the patient according to the patient's movement or treatment process. According to the present invention, matching is performed according to the patient's movement or treatment process, and for example, medical institutions located along the patient's travel route (within the range of commuting to and from home) are displayed preferentially to encourage selection. Furthermore, by providing a system that also considers the coordination of medical institutions according to the treatment process, such as coordinating from a medical institution that handles diseases requiring surgical intervention to a medical institution that handles diseases that can be treated with internal medicine, the convenience of the patient can be improved.

[0052] (13) The system includes a medical record means for recording past medical visits and a feedback record means for recording patient feedback based on the medical visits, wherein the matching means performs matching of past medical visits in the medical record means with the feedback content recorded in the feedback record means and changes the display of the matching result. According to the present invention, since matching is performed based on feedback content for past medical visits, medical institutions with negative feedback content are excluded from the matching target and not displayed, or the display of the matching results is changed to highlight the negative feedback. Alternatively, medical institutions with positive feedback content are displayed preferentially.

[0053] (14) The medical institution has means for collecting feedback and means for deleting or invalidating feedback received by the medical institution. According to the present invention, by deleting or invalidating the received feedback, the medical institution can avoid leaving records of unfavorable feedback in the electronic medical record.

[0054] (15) If patient feedback is to be made public, an evaluation method will be provided that uses AI to evaluate whether the content of the feedback is negative, and if the feedback is positive, it will be made public automatically, and if the feedback is negative, it will be made public after approval from the medical institution. According to this invention, the content of feedback is disclosed automatically for positive feedback and only after approval by the medical institution for negative feedback, thereby leaving the decision of whether or not to disclose negative feedback to the medical institution.

[0055] Furthermore, the information regarding "symptoms" above may be replaced with information regarding "diseases." Specifically, a system like the following, which is involved in matching "diseases," may be created. In this case, the disease name may be inferred by AI, and the medical institution may be displayed without explicitly showing it to the patient. [Effects of the Invention]

[0056] This invention provides a system that matches patients with medical institutions and displays medical institutions suitable for the patient based on the matching results. By presenting matching results that align with both the patient's needs and the medical institution's needs, it offers a convenient system for both parties. [Brief explanation of the drawing]

[0057] [Figure 1] A diagram showing the overall configuration of a system according to an embodiment of the present invention. [Figure 2] A block diagram showing an example of the functional configuration of a server. [Figure 3] A diagram showing the external appearance and functional configuration of the patient terminal. [Figure 4] A diagram illustrating the system outline according to this embodiment. [Figure 5] A diagram showing an example of a dating app screen display. [Figure 6] A diagram showing an example of the registration screen for a medical institution. [Figure 7] A flowchart showing the procedure for processing patient input information. [Figure 8] A flowchart illustrating the registration process for medical institutions. [Figure 9] A flowchart illustrating the matching process. [Best Mode for Carrying Out the Invention]

[0058] The mismatch between patients' symptoms and available medical institutions, and consequently the mismatch between the tests and treatments they receive, is a social issue. Disclosing their current capabilities and resources as much as possible can help resolve this social issue. However, medical institutions have been restricted from advertising consultations and treatments, which has hindered effective matching based on sufficient information disclosure. These advertising regulations have now been relaxed. In one embodiment of this patent, based on information entered by the patient, it is possible to evaluate the resources necessary for treatment using AI rule-based or machine learning and match the patient with a medical institution that can provide those resources. The resources to be evaluated as medical institution information entered by the medical institution include whether or not emergency services are available, hospital beds, surgeries, surgical procedures, specialist consultation hours, tests, qualifications for preparing documents, and consultation hours of designated intractable disease physicians. In particular, designated intractable disease physicians are required to prepare special documents, and this makes it possible to match patients with such physicians.

[0059] One embodiment of this patent describes a system that uses a large-scale language model to suggest the optimal medical department to visit based on a lengthy description of symptoms provided by a patient. The system receives the patient's symptoms as text or voice, converts the content to text if received via voice recognition, and inputs it into a large-scale language model. The system can then receive the medical department the patient should visit from the large-scale language model or other generating AI. This large-scale language model is trained through prompt engineering or fine-tuning to take the patient's symptom text as input and output the medical department the doctor should choose based on their judgment. This allows patients to input their complex symptoms and medical history, and the AI ​​analyzes this information to recommend the appropriate medical department.

[0060] <Integrated system of electronic medical questionnaires and conversational AI> One embodiment of this patent provides a system that integrates input from an electronic medical questionnaire with a conversational large-scale language model to conduct a detailed medical interview through interactive dialogue with the patient. Electronic medical questionnaires are useful for ensuring that patients input all necessary and accurate information. However, they tend to be formal and lack flexibility. On the other hand, large-scale language models allow for flexible responses to patients. By utilizing the large-scale language model, additional questions are automatically generated as needed based on the information the patient provides, and more detailed information is collected. This enables healthcare professionals to make diagnoses based on more comprehensive information and propose the most suitable treatment plan for the patient. Furthermore, for example, in the case of a patient with recurrent abdominal pain and a first-degree relative exhibiting symptoms of lip edema, hereditary angioedema should be considered. It is possible to set up an electronic questionnaire to ask about family history for patients with edema, and for patients with a family history, the system recommends a medical institution that can measure "C1 inhibitor activity" and "complement C4 concentration," while simultaneously using the messaging function to inform the patient that they should "ask their doctor to consider the possibility of hereditary angioedema and have them perform tests."

[0061] In one embodiment of this patent, a system is provided that, as a matching tool, not only suggests an appropriate medical department based on the patient's symptoms, but also presents the optimal medical institution by considering the congestion level and access information of the medical institution. This system grasps the current congestion level and resources of medical institutions in real time through video images installed at each medical institution, and supports the selection of a medical institution that is convenient for the patient and takes into account waiting times and ease of access. This improves the patient's experience of visiting a medical institution and enables the efficient use of medical resources.

[0062] <Currently, it is recommended to consult multiple medical departments consecutively if a diagnosis cannot be made, rather than relying on just one department.> In one embodiment of this patent, a system is provided that proposes a sequential consultation plan across multiple medical departments when a clear diagnosis cannot be made in a single medical department. For example, in the case of a patient with a headache, the differential diagnoses (candidate diseases) in order of frequency include tension headache, migraine, herpes zoster, sinusitis, and depression, and the appropriate medical departments for each are internal medicine, internal medicine, internal medicine, otolaryngology, and psychiatry, respectively. Therefore, if the patient does not improve with treatment at an internal medicine department, it is possible to recommend that they consult an otolaryngologist or psychiatrist. It should be noted that there are headache specialists, and it is especially desirable for chronic headaches that are difficult to treat to be treated by a headache specialist. This system recommends consultation with a headache specialist when the patient has consulted multiple medical institutions for the same symptoms. Furthermore, during the matching process, it is possible to convert patient terminology into medical terms, search case reports and electronic textbooks to list differential diagnoses, obtain a list of recommended departments for each differential diagnose to determine which department is appropriate for treatment, and determine which department to visit and in what order based on statistical data such as the most frequent value of each department included in the recommended department information. In this process, it is also possible to display the department with the most frequent differential diagnoses at the top of the results.

[0063] <When you are particular about something or when you visit a medical institution multiple times> In one embodiment of this patent, if a patient repeatedly visits a medical institution for the same symptoms, they are encouraged to visit a medical institution that specializes in a more specific subspecialty. For example, internal medicine has subspecialties such as cardiology, respiratory medicine, neurology, and infectious diseases. If the patient is asked whether they have repeatedly visited a medical institution for the same symptoms, or if this is confirmed through medical records, they are encouraged to visit a medical institution that matches their subspecialty. This helps avoid unnecessary repeat visits and allows patients to receive more appropriate medical care.

[0064] <Check for emergency symptoms> In one embodiment of this patent, a system is provided that incorporates a mechanism for quickly checking symptoms during emergencies and determines whether urgent response is necessary. When a patient enters the symptoms of themselves or others, if findings indicating a high degree of urgency are recognized, it immediately prompts the calling of an ambulance or the patient to visit a medical institution specialized in emergency life-saving treatment. This enables a prompt response to life-threatening situations.

[0065] <Listed in the distance rank - matching rank map of medical institutions> In one embodiment of this patent, a system is provided that ranks the nearest medical institutions based on distance and congestion level based on the patient's location information and displays them in map form.

[0066] <Maternal and child health handbook growth curve OCR> In one embodiment of this patent, a system is provided that takes a photo of the growth curve data recorded in the maternal and child health handbook and automatically digitizes it using optical character recognition (OCR) technology. This system extracts the handwritten growth curve from the growth curves, extracts numbers from it to grasp the weight gain. With these mechanisms, abnormalities and delays in the patient's growth pattern are quickly detected, and if an abnormality is found, a warning is issued to the doctor. Also, with this system, data sharing between medical institutions is simplified, and it becomes possible to manage the patient's growth data centrally.

[0067] <Digitization of examination findings by OCR and diagnostic support system by AI> In one embodiment of this patent, using OCR technology, it is also possible to convert the examination findings submitted from a medical institution into digital data, detect abnormalities in the examination values, convert them into medical words, and use that data for clinic search. For example, when "platelet 10,000" is described in the examination findings, it is changed to the word "low platelet count", combined with the input of the electronic consultation form at that time (for example, headache), and appropriate advice is proposed for patients who are found to have headache and low platelet count. This can improve the diagnostic accuracy in the medical field.

[0068] <Digitalization of Inspection Findings by OCR and Diagnostic Support System by AI> In one embodiment of this patent, multiple medical visits are linked using the information on the My Number insurance card.

[0069] <Overall Configuration of the System> FIG. 1 is a diagram showing the overall configuration of a system 1 according to an embodiment of the present invention. This system 1 has a terminal 10 on the hospital side, which is a medical institution, an external server 20, and a terminal 30 such as a patient's portable device connected via a wired / wireless network 80 such as the Internet. The server 20 is a server having a function as a web server (including a cloud server), and exchanges information with the terminals 10 and 30 via web pages. Also, although a web browser for browsing web pages is installed on the terminals 10 and 30, a dedicated application for enjoying the services of the server 20 may be installed so that web pages can be browsed by the dedicated application.

[0070] The terminal 10 is a device operated by medical staff (doctors, nurses, medical technicians, clerks, assistants, etc.) in a medical institution and is communicably connected to the server 20 via the network 80. The terminal 10 is connected to the network 80 by communicating with communication devices such as a wireless base station 81 compatible with various communication standards such as LTE and other wireless LAN routers compatible with IEEE and wireless LAN standards. The terminal 10 includes a communication IF 12, an input device 13, an output device 14, a memory 15, a storage unit 16, and a processor 19. The terminal 10 is a desktop or laptop PC, a portable terminal such as a tablet or a smartphone.

[0071] The communication interface 12 is an interface for the terminal 10 to communicate with an external device and input / output signals. The input device 13 is an input device (such as a keyboard, touch panel, touchpad, mouse, or other pointing device) for receiving input operations from the user. The output device 14 is an output device (such as a display or speaker) for presenting information to the user. The memory 15 is for temporarily storing programs, data processed by programs, etc., and is a volatile memory such as DRAM. The storage unit 16 is a storage device for saving data, such as flash memory or an HDD. The processor 19 is hardware for executing the instruction set written in the program, and is composed of an arithmetic unit, registers, peripheral circuits, etc. The program may be stored on a computer-readable recording medium on which the program is recorded.

[0072] Server 20 is managed by the administrator of System 1 according to the embodiment of the present invention (administrator of the matching site, administrator of the portal site), and the stored contents, such as modification / addition / deletion of information, can be modified as appropriate by healthcare professionals who are users of Terminal 10. Server 20 may also have the functionality of an electronic medical record device, allowing healthcare professionals in medical facilities to view input items and contents of the electronic medical record via a terminal device (not shown) and modify / add to the input contents. Furthermore, the server accepts editing operations of electronic medical record templates and electronic questionnaires performed by healthcare professionals via Terminal 10, and the stored contents are modified / added / deleted based on these editing operations.

[0073] Server 20 is a computer connected to a network 80 such as the Internet, and is equipped with a communication interface 22, an input / output interface 23, memory 25, storage 26, and a processor 29.

[0074] The communication interface is an interface for inputting and outputting signals so that the server 20 can communicate with external devices. The input / output interface 23 functions as an interface to an input device for receiving input operations from the user and an output device for presenting information to the user. The memory 25 is for temporarily storing programs and data processed by programs, etc., and is a volatile memory such as DRAM. The storage 26 is a storage device for saving data, such as flash memory or an HDD. The processor 29 is hardware for executing the instruction set written in the program, and is composed of an arithmetic unit, registers, peripheral circuits, etc.

[0075] Since the patient's portable device (tablet, smartphone, etc.) terminal 30 is a known device, details will be omitted. The patient's terminal 30 can communicate with the server 20 via the internet and communicate with the hospital's terminal 10.

[0076] <Functional configuration of Server 20> Figure 2 is a block diagram showing an example of the functional configuration of server 20. Server 20 comprises communication means 220, input device 230, output device 240, storage means 280, and control means 290, with each block being electrically connected by a bus or the like.

[0077] The communication means 220 performs modulation and demodulation processing for the server 20 to communicate with other terminals 10 and 30, processes the signal calculated by the control means 290 for transmission, and transmits it to external devices and equipment. The communication means 220 processes the signal received from the outside and outputs it to the control means 290. In this way, the communication means 220 interprets commands or input content and provides them to each means, and also functions as an interface that interprets various display commands issued from the storage means 280 and performs output control.

[0078] The input device 230 is a device used by a user operating the server 20 to input instructions or information, and may be a keyboard, mouse, reader, or touch-sensitive device. The input device 230 also converts the instructions input by the user into electrical signals and outputs the electrical signals to the control means 290. The input device 230 also includes a receiving port that accepts electrical signals input from an external input device.

[0079] The output device 240 is a display device 241 such as an LCD or organic EL for presenting information to the user operating the server 20. The display 241 can display data corresponding to the control content of the control means 290 and can confirm the communication status between the server 20 and other external devices 10, 30.

[0080] The storage means 280 is implemented by memory (RAM) 25 and storage 26 such as a disk device (floppy disk, hard disk, or magneto-optical disk, etc.) and stores data, programs, etc. used by the server 20. The storage means 280 stores the application program 282 of this system, as well as data for the work area 281, data storage area 283, and screen definition storage area 284.

[0081] The work area 281 is allocated upon startup of this system and is an area where various data input and output by this system are temporarily stored. The data storage area 283 is an area where data temporarily stored in the work area 281 is semi-permanently stored through write control when a save request is made. The screen definition area 284 is an area where screen definition information for various screens to be output and displayed to terminals 10 and 30 is stored in advance, and includes format information for the screen settings to be displayed.

[0082] Medical data 283A is structured to allow users to search for appropriate medical departments, treatments, coping mechanisms, examination methods, and disease names based on their symptoms. For example, for cold symptoms, it associates runny nose, cough, and sore throat, and stores information that while these symptoms often improve naturally, there is no medication to speed up the recovery, and nutrition, hydration, and rest are necessary. While sore throats usually resolve naturally within a week, abnormalities in voice or breathing recommend a hospital visit, and if it persists for more than three days, a doctor's visit is strongly recommended. In the case of unique disease and symptom examples, it also links with data from medical research.

[0083] Medical institution data 283B stores data registered by medical institutions via terminal 10. Specifically, on a registration screen as shown in Figure 6, the medical institution registers the medical department, consultation hours, equipment, symptom / disease information for the symptoms / diseases it wishes to treat, and symptom-related information such as chronic / peripheral symptoms, and the registered information is stored. For example, for acute conditions, equipment such as CT scans is necessary, so a recommendation of such a medical institution is required, but for chronic / peripheral conditions, a visit can be recommended as part of a continuous set of symptoms.

[0084] Patient data 283C stores the patient's personal information (name, address, contact information, etc.) entered by the patient through terminal 30, as well as the patient's symptoms, disease information, and symptom-related and disease-related information. It also stores the patient's past medical history, prescription drug history, and purchase history.

[0085] Feedback data 283D stores the feedback content entered by the patient through terminal 30. The feedback data may be categorized by the content of the feedback, such as positive or negative.

[0086] The electronic medical questionnaire data 283E stores the medical questionnaire content presented to the patient via terminal 30 and the patient's responses to the questionnaire. For example, as shown in Figure 5(A), the questionnaire begins with the question, "What brings you here today?", and prompts the patient to input their chief complaint and a timeline related to the chief complaint as their answers to the questionnaire, as shown in Figures 5(B) and (B2). In (B), in response to the question, "Do you experience any of the following symptoms?", there are options such as "None of the above," "Sudden change in symptoms," "Symptoms started suddenly," "Pain unlike anything I've ever experienced before," "Convulsions," "Feeling of being disoriented," "Shortness of breath," "Wheezing," "Increased respiratory rate," "Turning of lips to purple," and "Feeling of a lump in the throat," and the patient selects one or more of these. Next, the screen transitions to (B2), where in response to the question, "When did you first experience these symptoms?", the patient selects the time, days, years, or number of days, or selects "I don't know." In this way, the medical questionnaire screens (B) and (B2) prompt the patient to input patient information. The chronological information prompts patients to input the severity of their symptoms (acute / chronic), their condition from onset to the present (worsening / improving trend), and the frequency of their symptoms (recurrence / initial onset). The electronic questionnaire may be provided as a questionnaire function within the app, or it may be provided as a web-based form on a website where users are asked to input information. Patient responses to the questionnaire may be accepted in free text format, or it may proceed in a question-and-answer chat format. Chronological information may be entered using radio buttons as selection options, but multiple-choice answers are preferable to ensure consistency in terminology.

[0087] Furthermore, patient data 283C, feedback data 283D, and electronic medical questionnaire data 283E are linked and stored for each patient. Alternatively, by linking medical institution data 283B and feedback data 283D, the evaluation of medical institutions can be assessed based on the feedback content, and by linking medical institution data 283B and electronic medical questionnaire data 283E, the feasibility of responding to the questionnaire content can be evaluated for each medical institution. By performing these evaluations of medical institutions based on the feedback content of feedback data 283D, an objective evaluation can be made.

[0088] Figure 3 shows the hardware configuration of the patient's terminal 30, which includes a camera 31, a PC unit 32, a display unit 33, a touchscreen 34, a speaker 35, and a microphone 36. The patient answers the electronic medical questionnaire displayed on the display unit 33 by text input on the touchscreen 34 or by selecting from radio buttons. Patient input is accepted in the form of multiple-choice options for the questionnaire, ensuring consistency in terminology. The patient can also confirm the displayed medical institution based on the matching results, check messages, make reservations, and provide feedback. This system, which supports voice input, has a voice processing function in the PC unit 32, which performs digital-to-analog conversion processing of the voice signal. It converts the signal provided from the microphone 36 into a digital signal and provides the converted signal to the PC unit 32. The voice processing function also provides the voice signal to the speaker 35. The voice processing function is implemented by a voice processing processor, and the microphone 36 receives voice input and provides the corresponding voice signal to the PC unit 32. The speaker 35 converts the voice signal provided by the voice processing function into voice. Furthermore, the PC unit 32 handles the transmission and reception of audio signals from the server 20, and functions as an audio output via the speaker 35 and an audio input via the microphone 36. The control means 290 is realized when the processor 29 reads the application program 282 stored in the storage means 280 and executes the instructions contained in the application program 282. The control means 290 also controls the operation of the server 20 and terminals 10, 30, and by operating according to the application program 282, it performs functions as an input means 291, a reservation management means 293, a display means 294, a matching means 295, a user interface 296, a consultation history recording means 297, and a feedback control means 298.

[0089] The input means 291 receives input information about the patient's chief complaint (symptom information and symptom-related information) entered into terminal 30, which is then entered into patient input unit 291A. The medical department of the medical institution and the conditions for symptoms / diseases that the medical institution wishes to treat, entered into terminal 10, are then entered into condition input unit 291B. Alternatively, input may be received from an input device 230 connected to server 20 to assist in inputting into patient input unit 291A or condition input unit 291B. Information entered into patient input unit 291A is stored in patient data 283C, and information entered into condition input unit 291B is stored in medical institution data 283B.

[0090] The reservation management means 293 includes a message transmission / reception unit 293A and a reservation acceptance unit 293B. The message transmission / reception unit 293A performs processing to enable the server 20 to send and receive data according to a communication protocol. Specifically, for example, the transmission / reception unit sends the message content from the medical institution to the patient, and conversely, if it is possible to receive a message from the patient, the server 20 receives it and sends a reply to the medical institution. In addition, it sends a message from the medical institution to the patient and confirms receipt by automatically obtaining an ACK (Acknowledge) signal from the patient within a certain period of time. When an ACK signal is obtained from the patient, the function of the reservation acceptance unit 293B is activated, and a reservation operation screen is displayed to the patient to accept the reservation. The reservation management means 293 may also be linked with a reservation system operated by the medical institution, and it is possible for patients to make reservations via the server 20 or for the reservation system to accept reservations directly from patients without going through the server 20.

[0091] The display means 294 changes the content displayed on terminals 10 and 30 according to the processing status of the application program 282, or processes and edits the display content for displaying matching results to patients. When displaying matching results, the display of medical institutions suitable for the patient is given priority, but if the patient has a medical institution they are familiar with, that can be given priority display, and if there is a medical institution that has received negative feedback in the past, it will be excluded from the display. The display algorithm of the display means 294 is determined according to the application program 282.

[0092] The matching means 295 includes a processing unit 295A, a search result modification unit 295B, and a voice search unit 295C. The processing unit 295A performs calculations on the data received by the server 20 according to the application program and outputs the calculation results to the memory 25, etc. The processing unit 295A performs matching processing between the input information entered by the patient (chief complaint including symptoms, etc.) and the medical institution information registered by the medical institution (medical department, symptoms that the medical institution wishes to treat or diseases that can be treated), and searches for a medical institution suitable for the patient's symptoms and illness. Depending on the content of the patient's chief complaint, the medical department of the medical institution and the symptoms / diseases that it wishes to treat will differ, and the availability of testing equipment when tests are necessary will also differ from medical institution to medical institution, so it searches for a medical institution suitable for the patient. Search terms are created from the patient's chief complaint obtained from the electronic medical questionnaire and a search is performed in the medical database to find a suitable medical institution. Alternatively, depending on the patient's symptoms and illness, there may be two or more medical departments, a general medical institution may be better, or a family doctor may be better, so the search result modification unit 295B modifies the results. The voice search unit 295C performs language processing and searches when the input is in the form of speech. The voice search unit 295C searches for medical institutions by combining vector search technology and speech recognition technology.

[0093] User IF296 acquires the patient's movement and treatment progress and processes it in the matching processing unit 295A, and may be configured as a function of the matching means 295. The patient's movement can be acquired by obtaining location information using the GPS function of a communication terminal 30 or the like held by the patient, which is useful for understanding the patient's range of activity. The matching means 295 can attempt to match the patient with medical institutions located between the patient's home and workplace, or with medical institutions located near the home or workplace. The treatment progress can be acquired by obtaining the treatment status stored in the patient data 283C, allowing the matching means 295 to re-search for medical institutions corresponding to the treatment progress.

[0094] The medical consultation history recording means 297 works in conjunction with patient data 283C to record past medical consultation history, or to record feedback content along with the medical consultation history, and has a function to change the display of matching results. Medical institutions with a lot of negative feedback content are reduced in the degree of matching or excluded, which is helpful for well-meaning third parties who are considering visiting a medical institution. Conversely, medical institutions with a lot of positive feedback content are given an advantage in matching.

[0095] The feedback processing means 298 includes a feedback recording unit 298A for recording feedback, a feedback collection unit 298B for collecting feedback, and a public / private setting unit 298C for setting whether the feedback content should be made public or private. The feedback collection unit 298B receives and collects feedback regarding medical treatment after a patient has visited a medical institution. As part of the patient's feedback, it automatically reminds the patient to input whether they have recovered or not at a later date. The public / private setting unit 298C allows the patient to set the feedback to be made public or private. If the patient's feedback is set to be made public, it uses AI to evaluate whether the feedback content is negative. If the feedback content is positive, it is automatically made public; if the feedback content is negative, it is made public subject to approval by the medical institution, or the negative feedback content is deleted or invalidated. The public / private setting unit 298C can also limit the scope of the number of people to whom private feedback content can be made public or the setting of private content to a desired range, such as acquaintances. This is effective for patients who do not want their medical personal information to be made public, and for patients who think it is fine to make it public only to acquaintances.

[0096] In this embodiment, the processor stores symptom information and elapsed time information obtained from the patient terminal, as well as medical institution information including symptom categories and acceptable elapsed times updated from the medical institution terminal, in memory. Based on this information, the processor extracts medical institutions that meet the criteria, assigns a priority to them, and displays them on the patient terminal. If an update to the medical institution information is detected, the extraction and prioritization are re-executed on the server side based on the updated content, and the results are stored on the server. This makes it possible to immediately present the updated priority results to matching requests received from the patient terminal thereafter, and the latest medical institution acceptance status is shared with the patient in real time. Furthermore, by enabling medical institutions to actively register or update the symptom categories they can treat and the acceptable elapsed times for those categories, the intentions of the medical institution regarding acceptance or priority are directly reflected in the matching logic. This enables flexible triage guidance in response to changes in the treatment policies and resources of individual medical institutions, and realizes appropriate guidance control for multiple patients. Furthermore, by providing these processes as a real-time triage function, the matching logic is immediately recalculated when a medical institution updates information on "symptoms that can be treated now / cannot be treated now," ensuring that the latest guidance results are always presented to other patients who access the system next. The updated priority (score) is maintained on the server side, and the latest version is always used for new matching requests, thus enabling accurate guidance that always reflects the current situation. Unlike conventional department-based searches or medical institution selection based solely on waiting times, this system is significantly differentiated by allowing medical institutions to proactively present conditions and control guidance according to their ability to accept patients.

[0097] Figure 4 is an overview diagram of the system according to this embodiment, in which a medical device terminal 10 and a patient terminal 30 are connected to the server 20 to support the matching of patients with medical institutions.

[0098] Patient input information is entered into the patient terminal 30, and the server 20 receives it. Meanwhile, prior to or after the patient input information, medical institution information is entered into the medical institution terminal 10, and the server 20 receives it. Basically, medical institution information is pre-registered in the server 20, and matching is performed with the patient input information based on that registered information.

[0099] The matching results are displayed on the patient terminal 30, and a suitable medical institution is recommended for the patient. The recommended medical institution terminal 10 is also notified of the recommendation. The patient can initiate contact with the recommended medical institution and schedule an appointment, and the medical institution can determine whether it can treat the recommended patient after learning about their symptoms and illness before initiating contact. The patient selects a medical institution from the display screen shown in Figure 5(C) and proceeds to the input screen shown in Figure 5(D). If the patient already has contact with a medical institution, the request is registered as an appointment; otherwise, it is registered as a request for an appointment.

[0100] If multiple medical institutions are displayed on the patient terminal 30, the medical institutions can contact the patient (message) to help them select the most suitable medical institution, and the displayed institutions can be sorted based on criteria such as proximity to home, proximity to work, or proximity to the current location.

[0101] Figures 7 to 9 are flowcharts showing the processing procedures of the system according to this embodiment. Figure 7 shows the processing procedure for patient input information, Figure 8 shows the processing procedure for medical institution registration, and Figure 9 shows the processing procedure for matching. In this system, the control means 290 performs the processing of each processing unit via a server 20 connected to a communication line such as the Internet.

[0102] In Figure 7, when a patient browses the system's website or launches the application, the display screen shown in Figure 5(A) is displayed on the patient terminal 30, and the medical interview using the electronic questionnaire begins when the patient initiates the interview start operation (step S701). The patient input unit 291 constantly monitors for the presence or absence of input information and determines whether or not input information is present (step S702).

[0103] If it is determined in step S702 that there is input information and no further questions are needed, the chief complaint and time series analysis of the input information (symptom information and symptom-related information) is performed (step S703). That is, the input means 291 refers to the medical data 283A (step S704) to analyze what symptoms or diseases are present and to identify the symptoms or diseases. The time series in which multiple symptoms appear is also analyzed and compared, and further questions are asked. On the other hand, if it is determined in step S702 that there is no input information, the system waits for the input information to be entered.

[0104] Based on the analysis and comparison results, it is determined whether the symptoms or disease can be identified (step S705). If identified (OK), the symptoms or disease are linked to patient data 283C and saved (step S706), and this subroutine is terminated. On the other hand, if it cannot be identified in step S705 (NG), the process returns to step S701 and the interview is repeated.

[0105] Even if a patient's personal information (name, address, date of birth, etc.) is not registered in patient data 283C, it can still be saved in patient data 283C by issuing and linking a patient ID (for example, a phone number or email address).

[0106] Figure 8 shows the flow for registering a medical institution in the medical institution data 283B using the condition input unit 291, and the operation details of the hospital terminal 10 are transmitted by command from the server 20. When a registration request is received from the hospital terminal 10, the server 20 retrieves the medical institution data 283B into the work area 281 (step S801) and determines whether the requested medical institution is already registered (step S802).

[0107] In step S802, if there is an existing registration and no additional request from the hospital terminal 10, this subroutine terminates. On the other hand, if there is no existing registration and a new registration is requested, or if there is an existing registration and an update request is made, the user is prompted to enter / update basic information (hospital name, address, telephone number, etc.), and the basic information is registered (step S803). After the basic information is registered, the medical department is registered (step S804). After the medical department is registered, the hospital's facilities and the symptoms / diseases it can treat or specializes in are registered as optional information (step S805), and this subroutine terminates upon completion of registration. The presence or absence of medical departments and facilities may be made mandatory information, while symptoms / diseases may be made optional information. During the registration in steps S803 to S805, the display screen shown in Figure 6 is displayed on the hospital terminal 10.

[0108] Figure 9 is a flowchart showing the matching process performed by the matching means 295, which is basically carried out by the processing unit 295B. During matching, patient data is retrieved (step S901) and medical institution data is retrieved (step S902) in parallel, and a matching process is performed to determine the compatibility between the patient's input information and the medical institution's medical institution information (step S903). Based on the results of the matching process, it is determined whether a match is possible or not (step S904), and if a match is possible, the matching medical institution is displayed as shown in Figure 5(C) (step S905). If a match is not possible, the various conditions used for matching are changed (step S906), and the process returns to step S902 to perform matching with a medical institution again.

[0109] The various conditions used for matching are basically the patient input information and medical institution information processed by the processing unit 295A. However, in order to unify the terminology between the two, the patient input information is converted to a unified terminology used by both sides before matching. In addition, if matching is performed using additional functions (search result modification unit 295B, voice search unit 295C, user IF 296, medical consultation history recording means 297, feedback processing means 298), the medical institutions may be narrowed down, so this narrowing is removed by the patient's instruction or by automatic modification by the AI.

[0110] The matching process can improve the accuracy of the matching by using a machine learning algorithm based on patient data 283C, feedback data 283D, medical history, user interface, etc. To improve the accuracy of the matching, it is preferable that the medical institution data 283B is up-to-date, and medical institutions should be regularly requested to input / update the latest data. [Industrial applicability]

[0111] This invention is useful as a convenient system that matches patients with medical institutions suitable for their symptoms and diseases, making it user-friendly for patients and allowing medical institutions to avoid unexpected patient visits.

[0112] (See Appendix P1) A program for matching patients with medical institutions, which is executed on a server having a processor and memory, The system stores patient information, including symptom information and elapsed time information for those symptoms, obtained from the patient's terminal, and medical institution information, including the symptom categories for which the patient wishes to be examined and the acceptable elapsed time for those categories, updated from the medical institution's terminal. A program characterized by causing a processor to match patient information with medical institution information to extract medical institutions that meet the conditions, assign priorities to the extracted medical institutions and display them on the patient terminal, and when an update to the medical institution information is detected, to recalculate the priorities to reflect the update and update the display. (See page 2 for details) A program for matching patients with medical institutions, which is executed on a server having a processor and memory, The system stores patient information, including symptom information and elapsed time information for those symptoms, obtained from the patient's terminal, and medical institution information, including the symptom categories for which the patient wishes to be examined and the acceptable elapsed time for those categories, updated from the medical institution's terminal. A program characterized by having the processor match patient information with medical institution information to extract medical institutions that meet the conditions, assign priorities to the extracted medical institutions and display them on the patient terminal, and when an update to the medical institution information is detected, having the server re-execute the extraction and prioritization based on the updated medical institution information, storing the recalculation results in the server, and then using the recalculation results to present matching requests received from the patient terminal thereafter. (See Appendix P3) A program for matching patients with medical institutions, which is executed on a server having a processor and memory, The memory stores patient information, including symptom information, symptom-related information, and elapsed time information for the symptoms, obtained from the patient's terminal, and medical institution information, which includes departmental information and, if necessary, symptom-related information and the allowed elapsed time for that information, updated from the medical institution's terminal. A program characterized in that it causes the processor to perform the following processes: if the medical institution information contains only medical department information, it determines the medical department based on the patient's symptom information and symptom-related information and performs matching; if the medical institution information contains either medical department information or both symptom information and symptom-related information, it prioritizes the patient's symptom information and symptom-related information over the medical department information when performing matching; and it also performs prioritization and display update processes. (See Appendix P4) A program for matching patients with medical institutions, which is executed on a server having a processor and memory, A program characterized by storing patient information and medical institution information in memory, causing the processor to perform processing for extracting, prioritizing, and updating the display of medical institutions by matching the information, and receiving feedback from patients after their visit to a medical institution and recording such feedback in association with the patient's information. (See page 5 for details) A program for matching patients with medical institutions, which is executed on a server, A program characterized by, in addition to processing patient feedback, automatically sending reminders to patients from medical institutions regarding whether or not the patient's symptoms have been cured. (See Appendix P6) A program for matching patients with medical institutions, which is executed on a server, A program characterized by allowing patients to set their feedback to be public or private, linking that feedback to symptom information, and executing a process that applies an algorithm to change the display of matching results based on past feedback content, regardless of whether it is public or private. (See page 7 for details) A program for matching patients with medical institutions, which is executed on a server, A program characterized by performing a process that limits the visibility or privacy settings of patient feedback to a range of people designated by the patient, such as acquaintances. (See page 8 for details) A program for matching patients with medical institutions, which is executed on a server having a processor and memory, The system stores patient information, including disease information and elapsed time information for the disease obtained from the patient's terminal as responses to a medical questionnaire, and medical institution information, including the disease category for which the patient wishes to be examined and the acceptable elapsed time for that category, which is updated from the medical institution's terminal. A program characterized in that it causes the processor to prioritize medical institutions whose patient information matches the medical institution information and display them on the patient terminal, and when it detects an update to the medical institution information, it executes a process to recalculate based on the priority associated with the update and update the display. (See page 9 for details) A program for matching patients with medical institutions, which is executed on a server having a processor and memory, The system stores patient information, including disease information and elapsed time information for the disease obtained from the patient's terminal as responses to a medical questionnaire, and medical institution information, including the disease category for which the patient wishes to be examined and the acceptable elapsed time for that category, which is updated from the medical institution's terminal. A program characterized in that the processor is instructed to prioritize and display on the patient terminal medical institutions whose patient information matches the medical institution information, and when an update to the medical institution information is detected, the server is instructed to re-execute the extraction and prioritization based on the updated medical institution information, the recalculation results are stored on the server, and the recalculation results are used to present matching requests received from the patient terminal thereafter. (See Appendix P10) A program for matching patients with medical institutions, which is executed on a server, The system stores symptom information or disease information obtained from the patient's terminal, patient information including the elapsed time of the symptoms or disease, and medical institution information updated from the medical institution's terminal, including the symptom category or disease category for which the patient wishes to be examined and the acceptable elapsed time for each. The system performs at least one of the following: matching the patient information with the medical institution information, prioritizing it, recalculating when an update to the medical institution information is detected, and (displaying the update or recalculating result on the server and presenting it thereafter based on that result). Furthermore, the program features a reservation management function that integrates with the reservation system operated by the medical institution, sends a message from the medical institution to the patient, obtains confirmation information from the patient regarding the message content, and then executes a process to enable the reservation after obtaining the confirmation information. (See page 11 for details) A program for matching patients with medical institutions, which is executed on a server, The system performs matching processing based on patient information and medical institution information (extraction, prioritization, recalculation and display update upon update detection, or at least one of retaining the recalculation results and presenting them thereafter). A program characterized by performing a process to track the history of a single patient visiting multiple different medical institutions for the same chief complaint. (See page 12 for details) A program for matching patients with medical institutions, which is executed on a server, The system performs matching processing based on patient information and medical institution information (extraction, prioritization, recalculation and display update upon update detection, or at least one of retaining the recalculation results and presenting them thereafter). A program characterized by executing a process that dynamically changes search results according to the time of day and the congestion status of medical facilities. (See Appendix P13) A program for matching patients with medical institutions, which is executed on a server, A program characterized by obtaining information on the patient's chief complaint and related symptom information based on the patient's voice input, searching for medical institutions using a combination of vector search technology and speech recognition technology as a voice search function, and executing a process that prioritizes and updates the display or recalculates the results and presents them thereafter based on the search results. (See page 14 for details) A program for matching patients with medical institutions, which is executed on a server, A program characterized by performing display and guidance processing via a user interface to prompt the patient to select a suitable medical institution according to the patient's movement or treatment process, and performing processing to present matching results in accordance with said guidance (including at least one of prioritizing, updating the display, or holding and subsequently presenting the results). (See page 15 for details) A program for matching patients with medical institutions, which is executed on a server, A program characterized by recording past medical history as a medical record processing, recording patient feedback content as a feedback record processing, and executing a process (including prioritizing, updating the display, or retaining and subsequently presenting the recalculation results) that modifies the display of the matching results based on the medical history and feedback content. (See page 16 for details) A program for matching patients with medical institutions, which is executed on a server, A program characterized by causing a feedback collection process to be executed, and causing a medical institution to execute a process to delete or invalidate the feedback it has received. (See page 17 for details) A program for matching patients with medical institutions, which is executed on a server, A program characterized by using artificial intelligence to evaluate whether patient feedback that has been set to be made public is positive or negative, automatically publishing it if it is positive, and publishing it after approval from the medical institution if it is negative.

[0113] (Note M1) A patient-healthcare matching method executed by a server having a processor and memory, A process of storing patient information including symptom information and elapsed time information of the symptoms obtained from the patient terminal, and medical institution information including the symptom category for which the patient wishes to be examined and the acceptable elapsed time for that category, updated from the medical institution terminal. A step of matching the patient information with the medical institution information to extract medical institutions that meet the conditions, The process involves assigning priority to the extracted medical institutions and displaying them on the patient's terminal, When an update to the medical institution information is detected, the priority is recalculated to reflect the update, and the display is updated. A method that includes this. (Note M2) A patient-healthcare matching method executed by a server having a processor and memory, A process of storing patient information including symptom information and elapsed time information of the symptoms obtained from the patient terminal, and medical institution information including the symptom category for which the patient wishes to be examined and the acceptable elapsed time for that category, updated from the medical institution terminal. A step of matching the patient information with the medical institution information to extract medical institutions that meet the conditions, The process involves assigning priority to the extracted medical institutions and displaying them on the patient's terminal, When an update to medical institution information is detected, the extraction and prioritization process is re-executed based on the updated medical institution information, the recalculation results are stored in the server, and the recalculation results are used to present matching requests received from patient terminals thereafter. A method that includes this. (Note M3) A method that includes the step of determining and matching the medical department based on the patient's symptom information and symptom-related information if the medical institution information consists only of medical department information, or both symptom information and symptom-related information, while prioritizing the matching of the patient's symptom information and symptom-related information over the medical department information if the medical institution information consists of either medical department information or both symptom information and symptom-related information. (Note M4) A method that includes the process of receiving feedback from patients after they have visited a medical institution and recording that feedback in conjunction with patient information. (Note M5) A method that includes a process of automatically sending reminders to patients from medical institutions to input the status of their symptom recovery as a form of patient feedback. (Note M6) A method comprising the steps of setting the aforementioned feedback to be public or private, linking the feedback to symptom information, and further applying an algorithm that changes the display based on past feedback content regardless of whether it is public or private. (Note M7) A method that includes the step of limiting the scope of public or private settings of the aforementioned feedback to a desired group of acquaintances, etc. (Note M8) A patient-healthcare matching method executed by a server having a processor and memory, A process of storing patient information, including disease information and its elapsed time, obtained from the patient's terminal as responses to a medical questionnaire, and medical institution information, including the disease category for which the patient wishes to be examined and the acceptable elapsed time for that category, updated from the medical institution's terminal. A step of assigning priority to medical institutions whose patient information matches the medical institution information and displaying them on the patient terminal, When an update to medical institution information is detected, the process involves recalculating and updating the display based on the priority given to the update. A method that includes this. (Note M9) A patient-healthcare matching method executed by a server having a processor and memory, A process of storing patient information, including disease information and elapsed time information for the disease obtained from the patient terminal as answers to a medical questionnaire, and medical institution information, including the disease category for which the patient wishes to be examined and the acceptable elapsed time for that category, updated from the medical institution terminal, in memory. A step of assigning priority to medical institutions whose patient information matches the medical institution information and displaying them on the patient terminal, When an update to medical institution information is detected, the process involves recalculating based on the priority order in response to the update and updating the display on the patient's terminal. When an update to medical institution information is detected, the extraction and prioritization processes are re-executed on the server side based on the updated medical institution information, the recalculation results are stored on the server, and the recalculation results are used to present matching requests received from patient terminals thereafter. A method that includes this. (Note M10) A method that involves linking with a medical institution's reservation system using a reservation management means, including sending a message from the medical institution to the patient and obtaining confirmation information from the patient, and enabling the reservation after obtaining the confirmation information. (Note M11) A method that includes the step of tracking the history of a single patient visiting multiple different medical institutions for the same chief complaint. (Note M12) A method that includes a process for dynamically changing search results according to the time of day and the congestion level of medical facilities. (Note M13) A method that includes the process of obtaining symptom information and symptom-related information based on the patient's voice input, and searching for a medical institution by combining vector search and speech recognition using a voice search unit. (Note M14) A method that includes a step of prompting the patient to select a suitable medical institution in accordance with their movement or treatment process via a user interface. (Note M15) A method comprising the steps of recording past medical history using a medical record means, recording feedback content using a feedback record means, and applying an algorithm to modify the matching result based on these. (Note M16) A method that includes the step of deleting or invalidating feedback received by a healthcare institution. (Note M17) A method that includes a process of using AI to evaluate whether publicly available feedback is positive or negative, automatically publishing positive feedback, and publishing negative feedback after approval from the medical institution. [Explanation of symbols]

[0114] 10: Hospital terminal (13: Input device, 14: Output device, 15: Memory, 16: Storage unit, 19: Processor) 20: Server (25: Memory, 26: Storage, 29: Processor) 30: Patient terminal (31: Camera, 32: PC unit, 33: Display unit, 34: Touchscreen, 35: Speaker, 36: Microphone) 80: Internet network, 81: Wireless base station

Claims

1. A system for matching patients and healthcare institutions, operated on a server having a processor and memory, The aforementioned memory is Patient information including symptom information and elapsed time information of the symptoms obtained from the patient's terminal, The system stores medical institution information, including the symptom category for which the patient wishes to be examined and the acceptable elapsed time for that category, which is updated from the medical institution's terminal. The aforementioned processor, A) By matching the patient information with the medical institution information, medical institutions that meet the conditions are extracted. B) The extracted medical institutions are given priority and displayed on the patient's terminal. C) When an update to the medical institution information is detected, the priority order is recalculated to reflect the update, and the display is updated. A system characterized by the following features.

2. A patient-healthcare matching system operated on a server having a processor and memory, The aforementioned memory is Patient information including symptom information and elapsed time information of the symptoms obtained from the patient's terminal, The system stores medical institution information, including the symptom category for which the patient wishes to be examined and the acceptable elapsed time for that category, which is updated from the medical institution's terminal. The aforementioned processor, A) By matching the patient information with the medical institution information, medical institutions that meet the conditions are extracted. B) The extracted medical institutions are given priority and displayed on the patient's terminal. C) A system characterized in that, when an update to medical institution information is detected, the server re-executes the extraction and prioritization based on the updated medical institution information, stores the recalculation results on the server, and uses the recalculation results to present matching requests received from patient terminals thereafter.

3. The system according to claim 1 or 2 is If the aforementioned medical institution information only contains information on the medical department, the medical department will be determined and matched based on the patient's symptom information and symptom-related information. If the medical institution information includes both departmental information and symptom-related information, the patient's symptom information and symptom-related information will be matched with priority over the departmental information. A system characterized by the following features.

4. The system according to claim 1 or 2 is A system characterized by receiving feedback from the patient regarding the medical institution after the patient has visited the medical institution, and recording the feedback in conjunction with the patient's patient information.

5. In the system described in claim 4, This system features an automated reminder system that sends patients feedback from medical institutions regarding whether or not their symptoms have been cured.

6. In the system described in claim 4, The aforementioned feedback can be set to be public or private. Furthermore, the feedback is linked to the symptom information, A system characterized by having an algorithm that changes the display based on the content of past feedback, regardless of whether it is public or private.

7. The system according to claim 4, wherein the setting of the public or private scope of the aforementioned feedback can be limited to a desired range of people, such as acquaintances.

8. Patient-healthcare matching operated on a server with a processor and memory. It is a system for that purpose, The aforementioned memory is Patient information, including disease information and time elapsed since the onset of the disease, obtained from the patient's terminal as responses to a medical questionnaire, The system stores medical institution information, including the disease category for which the patient wishes to be examined and the acceptable elapsed time for that category, which is updated from the medical institution's terminal. The aforementioned processor, Medical institutions whose patient information matches the medical institution information are given priority and displayed on the patient terminal. When an update to the medical institution information is detected, the priority is recalculated based on the update and the display is updated. A system characterized by the following features.

9. Patient-healthcare matching operated on a server with a processor and memory. It is a system for that purpose, The aforementioned memory is Patient information, including disease information and time elapsed since the onset of the disease, obtained from the patient's terminal as responses to a medical questionnaire, The system stores medical institution information, including the disease category for which the patient wishes to be examined and the acceptable elapsed time for that category, which is updated from the medical institution's terminal. The aforementioned processor, The system prioritizes and displays medical institutions on the patient terminal that match the patient information and medical institution information, and when it detects an update to the medical institution information, it recalculates the priority based on the update and updates the display accordingly. A system characterized by detecting updates to medical institution information, re-executing the extraction and prioritization processes on the server side based on the updated medical institution information, storing the recalculation results on the server, and using those recalculation results to present matching requests received from patient terminals thereafter.

10. In the system according to any one of claims 1, 2, 8, or 9, The reservation management means of the aforementioned processor is linked to a reservation system operated by a medical institution, and has the function of sending messages from the medical institution to the patient and obtaining confirmation information of the message content by the patient. The aforementioned reservation management means is When a patient makes a reservation through the reservation system, the reservation is made possible after obtaining the confirmation information. A system characterized by the following features.

11. The system according to any one of claims 1, 2, 8, or 9 further comprises a history tracking means for the processor, The aforementioned history tracking means is a system characterized by tracking the history of a single patient visiting multiple different medical institutions for the same chief complaint.

12. The system according to any one of claims 1, 2, 8, or 9 has a search result modification unit as a matching means of the processor, The aforementioned search result modification unit is a system characterized by dynamically changing search results according to the time of day and the congestion status of medical institutions.

13. The system according to any one of claims 1, 2, 8, or 9, wherein the processor is The patient's voice input is used to generate information about the chief complaint, including symptoms, and related symptom information. The matching means of the aforementioned processor includes a voice search unit. The aforementioned voice search unit is characterized by combining vector search technology and speech recognition technology to search for medical institutions based on the patient's voice input.

14. The system according to any one of claims 1, 2, 8, or 9, wherein the processor has a user interface as a matching means, The user interface is a system characterized by prompting the patient to select a medical institution suitable for them, depending on the patient's movement or treatment process.

15. The system according to any one of claims 1, 2, 8, or 9 further comprises the processor, A means of recording past medical history, The system includes a feedback recording means for recording patient feedback based on the aforementioned medical history, The matching means of the processor performs matching based on the feedback content recorded in the feedback recording means against the past medical history in the medical record means. A system characterized by having an algorithm for changing the display of matching results.

16. The system according to claim 4 further comprises a feedback collection means, A system characterized by its ability to delete or invalidate feedback received by medical institutions.

17. In the system described in claim 16, If patient feedback is made public, the system includes an evaluation method that uses AI to assess whether the feedback is negative. Positive feedback will be automatically published. If the feedback is negative, it will be published after approval from the medical institution. A system characterized by the following features.

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