Disease information presentation device and program

Abstract

This disease information presentation device comprises: an objective data acquisition unit that acquires objective data objectively indicating the medical condition of a specific patient suffering a chronic and progressive disease; an explanatory variable imparting unit that imparts, as an explanatory variable, the acquired objective data to a trained model trained by using, as an explanatory variable, medical condition data objectively indicating the medical conditions of a plurality of patients suffering diseases, and by using, as response variables, medical examination results of the medical conditions when the plurality of patients are respectively examined by medical specialists of the diseases; a response variable acquisition unit that acquires, as medical examination result information, a medical examination result that is a response variable outputted by the trained model to which the objective data has been imparted; a disease information generation unit that generates disease information relating to the degree of progression of the disease on the basis of the acquired medical examination result information; and a presentation unit that presents the generated disease information.

Description

Disease information display device and program

[0001] This invention relates to a disease information display device and program. This application claims priority under Japanese Patent Application No. 2024-180256, filed in Japan on October 15, 2024, the contents of which are incorporated herein by reference.

[0002] Pulmonary hypertension (PH) is a chronic and progressive disease, and right heart failure is one of the prognostic factors. Therefore, it is crucial to be able to live a normal life without worsening right heart failure. To accurately assess the state of PH, hemodynamic measurement by right heart catheterization is necessary. However, this is a highly invasive test that involves inserting a catheter into a central vein to measure pressure in the heart and lungs, so in routine clinical practice, assessment is done using blood tests, X-rays, and findings of internal jugular vein distension. Since patients only visit the doctor about once a month, it is difficult for them to notice that their condition is gradually worsening during the approximately one month they spend at home, until right heart failure has progressed. Patients experience "rejoicing or despairing over test results each month, being shocked if the condition has worsened, and feeling despairing that it is hopeless" with each visit. Previous studies have reported that this "threat of progression and worsening" is one of the components of the mental distress of PH patients (see, for example, Non-Patent Literature 1). It would be desirable to have a computer system that can monitor the worsening condition of PH patients and present this information to the PH patients themselves and their healthcare providers.

[0003] Takita Y, Takeda Y, Fujisawa D, Kataoka M, Kawakami T,Doorenbos AZ. Depression, anxiety and psychological distress in patients with pulmonary hypertension: a mixed-methods study. BMJ Open Respir Res. 2021 Apr;8(1):e000876. doi: 10.1136 / bmjresp-2021-000876

[0004] However, PH is also a rare disease, and conventionally, no computer system has been proposed that can grasp the deterioration of the disease state specific to PH and present it to the PH patient himself / herself or medical staff.

[0005] An object of the present invention is to provide a disease information presentation device and a program that can grasp the deterioration of the disease state of a PH patient and present it to the PH patient himself / herself or medical staff.

[0006] One aspect of the present invention includes an objective data acquisition unit that acquires objective data objectively indicating the disease state of a specific patient suffering from a chronic and progressive disease, and disease state data objectively indicating the disease states of a plurality of patients suffering from the disease as explanatory variables, and gives the acquired objective data as an explanatory variable to a learned model learned with the diagnosis results of the disease states when each of the plurality of patients is examined by a specialist in the disease as an objective variable, an objective variable acquisition unit that acquires, as diagnosis result information, the diagnosis result that is the objective variable output by the learned model to which the objective data is given, a disease information generation unit that generates disease information, which is information regarding the degree of progression of the disease, based on the acquired diagnosis result information, and a presentation unit that presents the generated disease information.

[0007] One aspect of the present invention is a program for causing a computer to acquire objective data objectively indicating the disease state of a specific patient suffering from a chronic and progressive disease, give the acquired objective data as an explanatory variable to a learned model learned with disease state data objectively indicating the disease states of a plurality of patients suffering from the disease as explanatory variables and the diagnosis results of the disease states when each of the plurality of patients is examined by a specialist in the disease as objective variables, acquire, as diagnosis result information, the diagnosis result that is the objective variable output by the learned model to which the objective data is given, generate disease information, which is information regarding the degree of progression of the disease, based on the acquired diagnosis result information, and present the generated disease information. <老实说,我不太确定你提供的“

[0008] ”是否有特定含义,如果没有特殊要求,我就直接保留它。如果你能告诉我它的具体要求,我会按照要求进行翻译。>According to the present invention, it is possible to grasp the deterioration of the disease state of a PH patient and present it to the PH patient himself / herself or medical staff.

[0009] This figure shows an example of the functional configuration of the disease information management system of the first embodiment. This figure shows an example of the operation flow of the disease information management system of this embodiment. This figure shows an example of self-acquired data of this embodiment. This figure shows the correspondence between walking speed and activity intensity by age for men. This figure shows the correspondence between walking speed and activity intensity by age for women. This figure shows an example of the data input screen of this embodiment. This figure shows an example of the physical condition selection screen of this embodiment. This figure shows an example of medical institution acquired data of this embodiment. This figure shows an example of the disease information display screen of this embodiment. This figure shows an example of the physical condition selection screen of this embodiment. This figure shows an example of the functional configuration of the disease information management system of the second embodiment. This figure shows an example of the electronic medical record screen of this embodiment.

[0010] The disease information management system 1 of this embodiment will be described with reference to the drawings. The embodiments described below are merely examples, and the embodiments to which the present invention is applied are not limited to the embodiments described below. In all the figures used to describe the embodiments, components having the same function will be given the same reference numerals, and repeated explanations will be omitted. Furthermore, in this application, "based on XX" means "based on at least XX," and includes cases where it is based on another element in addition to XX. Furthermore, "based on XX" is not limited to cases where XX is used directly, but also includes cases where it is based on XX after calculations or processing have been performed on it. "XX" is any element (for example, any information).

[0011] [First Embodiment] Figure 1 is a diagram showing an example of the functional configuration of the disease information management system 1 of the first embodiment. The disease information management system 1 is configured by connecting a disease information presentation device 10, a patient terminal 20, a medical institution terminal 21, an objective data storage unit 30, and a trained model storage unit 40 to each other via a wired or wireless communication network.

[0012] The disease information display device 10 is a computer device comprising a calculation unit 100 and a storage unit 190. The calculation unit 100 includes, for example, a central processing unit (CPU), and operates based on programs and data stored in the storage unit 190, providing various functions.

[0013] The storage unit 190 is composed of, for example, a hard disk drive or semiconductor memory (flash memory, RAM, ROM), and stores various types of information, such as programs and data read by the arithmetic unit 100. The storage unit 190 may also be implemented by a virtual storage device, such as a cloud server, located outside the disease information presentation device 10.

[0014] The calculation unit 100 of the disease information presentation device 10 includes, as its functional units, an objective data acquisition unit 110, an explanatory variable assignment unit 120, a target variable acquisition unit 130, a disease information generation unit 140, and a presentation unit 150.

[0015] The patient terminal 20 and the medical institution terminal 21 are both computer devices such as smartphones, tablets, and personal computers. The patient terminal 20 is a terminal device used by patient P and includes a display unit 201 and an operation detection unit 202. The display unit 201 is equipped with a display device such as a liquid crystal display and displays various images based on the control of the calculation unit (not shown) of the patient terminal 20. The operation detection unit 202 is equipped with an input operation device such as a touch panel, keyboard, or mouse and detects operations by the user (for example, patient P).

[0016] The patient terminal 20 may be a wristwatch-type computer device (a so-called smartwatch), as shown in the figure, patient terminal 20a. The patient terminal 20a may be capable of periodically acquiring information indicating the degree of exercise load of patient P (for example, steps taken, heart rate, blood oxygen saturation (SpO2), etc.) from patient P using contact-type or non-contact-type sensors. The patient terminal 20a may also be capable of acquiring patient P's location information and walking speed using GPS (Global Positioning System), etc.

[0017] The medical institution terminal 21 is a terminal device used by medical professionals (e.g., doctors, nurses, laboratory technicians, and staff who perform administrative tasks based on their instructions) in hospitals, clinics, and other medical facilities, and comprises a display unit 211 and an operation detection unit 212. The display unit 211 is equipped with a display device such as a liquid crystal display and displays various images based on the control of the calculation unit (not shown) of the medical institution terminal 21. The operation detection unit 212 is equipped with an input operation device such as a touch panel, keyboard, or mouse and detects operations performed by a user (e.g., patient P).

[0018] The objective data storage unit 30 is composed of, for example, a physical server or a virtual server such as a cloud server, and stores objective data D11. The trained model storage unit 40 is composed of, for example, a physical server or a virtual server such as a cloud server, and stores trained models M.

[0019] [Operation Flow of Disease Information Management System 1] Figure 2 is a diagram showing an example of the operation flow of the disease information management system 1 of this embodiment. The details of the functions and operation flow of the disease information management system 1 will be described below with reference to Figures 1 and 2.

[0020] (Step S110) The objective data acquisition unit 110 acquires objective data D11 from the objective data storage unit 30. Here, the objective data D11 will be explained.

[0021] [Objective Data] Objective data D11 is data that objectively shows the medical condition of a specific patient P suffering from a chronic and progressive disease. Objective data D11 includes, for example, self-obtained data D111 and medical institution-obtained data D112. Self-obtained data D111 is objective data D11 obtained by the patient P themselves. Medical institution-obtained data D112 is objective data D11 obtained by medical professionals when patient P visits a medical institution.

[0022] The chronic and progressive disease referred to here is pulmonary hypertension (PH).

[0023] Figure 3 shows an example of self-acquired data D111 in this embodiment. As described above, patient P may be wearing a patient terminal 20a (a so-called smartwatch, etc.). The patient terminal 20a periodically acquires information indicating the degree of exercise load of patient P (for example, steps taken, heart rate, blood oxygen saturation (SpO2), etc.). Here, periodically means, for example, every minute.

[0024] The patient terminal 20a transmits the acquired self-acquired data D111 to the objective data storage unit 30. The objective data storage unit 30 stores the time-series self-acquired data D111 for each patient P.

[0025] [Calculation of Estimated Activity Intensity (METs)] Objective data D11 also includes data calculated by performing calculations on self-acquired data D111 (for example, estimated activity intensity (METs)). Activity intensity (METs) is an index that indicates the intensity of activity by how many times more energy is consumed compared to rest (for example, sitting quietly), with resting energy set at 1.

[0026] As described above, the patient terminal 20a may be able to acquire data indicating the walking speed of patient P (for example, the location information of patient P at each time). In this case, the patient terminal 20a transmits the data indicating the walking speed of patient P to the objective data storage unit 30 as self-acquired data D111. As a result, the walking speed of each patient P is stored in the objective data storage unit 30 as self-acquired data D111. The disease information presentation device 10 calculates an estimated activity intensity (METs) value based on the walking speed of each patient P stored in the objective data storage unit 30.

[0027] Figure 4 shows the relationship between walking speed and activity intensity by age for men. Figure 5 shows the relationship between walking speed and activity intensity by age for women. The disease information display device 10 calculates an estimated activity intensity (METs) value for each patient P based on the relationship shown in Figures 4 and 5.

[0028] [Manual Input of Self-Acquired Data D111] Returning to Figure 3, the self-acquired data D111 may include objective data D11 such as weight, which the patient terminal 20a cannot automatically acquire. For objective data D11 that the patient terminal 20a cannot automatically acquire (for example, weight), patient P operates the patient terminal 20 (or patient terminal 20a; the same applies in the following description) to input a numerical value. The patient terminal 20 transmits the numerical value entered by patient P to the objective data storage unit 30 as self-acquired data D111. In this way, the objective data storage unit 30 stores time-series self-acquired data D111 (i.e., objective data D11) for each patient P.

[0029] The disease information management system 1 of this embodiment provides a function to acquire subjective symptoms from patient P. For example, the disease information management system 1 displays a data input screen P1 on the display unit 201 of the patient terminal 20.

[0030] Figure 6 shows an example of the data input screen P1 of this embodiment. The data input screen P1 is a screen for patient P to input their daily subjective symptoms and living situation.

[0031] The data entry screen P1 has a date field P11 and a health condition input button P12. The date field P11 is a field that displays the current date in a calendar format and also functions as an operation image for selecting the date on which to input subjective symptoms and living conditions. The health condition input button P12 is an operation image for inputting the patient P's health condition (subjective symptoms). When the health condition input button P12 is pressed, the health condition selection screen P2 is displayed on the display unit 201.

[0032] Figure 7 shows an example of the physical condition selection screen P2 of this embodiment. The physical condition selection screen P2 displays the subjective symptoms of patient P that can be objectively obtained as described above (shortness of breath, palpitations, malaise, chest pain, fatigue, loss of appetite, nausea, headache, edema, etc.) as selection candidates. Patient P inputs their physical condition for the day by selecting from the selection candidates on the physical condition selection screen P2.

[0033] The patient terminal 20 transmits the selected subjective symptoms to the objective data storage unit 30 as self-acquired data D111. In this way, the objective data storage unit 30 stores time-series self-acquired data D111 (i.e., objective data D11) for each patient P.

[0034] [Acquisition of Medical Institution Data D112] As described above, objective data D11 may include medical institution data D112. An example of medical institution data D112 is shown in Figure 8.

[0035] Figure 8 shows an example of medical institution acquired data D112 in this embodiment. When patient P visits a medical institution and undergoes an examination, the medical staff inputs the information into the medical institution terminal 21. The medical institution terminal 21 transmits the input information (i.e., patient P's examination results) to the objective data storage unit 30 as medical institution acquired data D112. As a result, the objective data storage unit 30 stores time-series medical institution acquired data D112 (i.e., objective data D11) for each patient P. Note that the medical institution acquired data D112 may include not only the data of the examination results themselves, but also the doctor's findings and diagnosis results based on patient P's examination results and consultation results. Figure 8 shows, but is not limited to, examples of items in medical institution data D112, including right heart catheterization values, echocardiogram findings, electrocardiogram findings, chest X-ray findings, physical examination findings, exercise tolerance, pulmonary function test findings, CPX (cardiopulmonary exercise test) test findings, blood test findings, and sepsis scintigraphy findings.

[0036] Returning to Figure 2, the objective data acquisition unit 110 acquires the time-series objective data D11 for each patient P that has been accumulated in this manner.

[0037] In other words, the objective data acquisition unit 110 acquires objective data D11 that objectively shows the medical condition of a specific patient P suffering from a chronic and progressive disease. The objective data acquisition unit 110 outputs the acquired objective data D11 to the explanatory variable assignment unit 120.

[0038] (Step S120) The explanatory variable assignment unit 120 provides the objective data D11 acquired in step S110 to the trained model M as an explanatory variable. This objective data D11 can be said to be data that shows the progression of the disease (for example, a chronic and progressive disease such as PH). In other words, the objective data D11 can be said to be disease condition data D13 that shows the disease condition of patient P suffering from a chronic and progressive disease such as PH. In other words, the explanatory variable assignment unit 120 provides the objective data D11 as disease condition data D13 to the trained model M. The trained model M will now be explained.

[0039] [Pre-trained model] The pre-trained model M is a model that has been pre-trained using disease condition data D13, which objectively shows the disease condition of multiple patients P suffering from a disease (e.g., PH), as the explanatory variable, and the results of the examination of each of the multiple patients P by a disease specialist as the dependent variable.

[0040] In the training process of the trained model M, it is desirable to collect data (received data) that combines the disease condition data D13 of as many patients P as possible with the examination results for those patients P, in order to improve the training accuracy. On the other hand, in the case of rare diseases such as PH, it is generally difficult to collect such cases. The disease information management system 1 of this embodiment may have a function to collect examination data of PH patients P by linking multiple specialized hospitals. The disease information management system 1 may also have a function to retrain the trained model M based on the collected received data. The disease information management system 1 configured in this way can collect received data from patients P and retrain the trained model M while operating to support patients P and medical professionals. Therefore, according to the disease information management system 1 of this embodiment, the training accuracy of the trained model M can be improved even for rare diseases such as PH.

[0041] The explanatory variable assignment unit 120 provides the trained model M, which has been trained in this manner, with objective data D11 (i.e., disease condition data D13) as explanatory variables.

[0042] That is, the explanatory variable assignment unit 120 uses the disease state data D13, objectively indicating the conditions of a plurality of patients P suffering from a disease, as an explanatory variable, and gives the acquired objective data D11 as an explanatory variable to the learned model M that has been learned with the examination results of the conditions when each of the plurality of patients P is examined by a specialist in the disease as an objective variable.

[0043] (Step S130) When the learned model M is given the objective data D11, the learned model M outputs an examination result corresponding to the objective data D11. The objective variable acquisition unit 130 acquires the examination result output from the learned model M as examination result information D2.

[0044] That is, the objective variable acquisition unit 130 acquires, as examination result information D2, the examination result that is the objective variable output by the learned model M to which the objective data D11 is given. The objective variable acquisition unit 130 outputs the acquired examination result information D2 to the disease information generation unit 1,40.

[0045] (Step S14) The disease information generation unit 140 generates disease information D3 based on the examination result information D2 acquired in Step S130. The disease information D3 is an alert to the patient P about a sign of the deterioration of the disease state and information provided to medical staff about the disease state of the patient P.

[0046] That is, the disease information generation unit 140 generates disease information D3, which is information about the degree of progression of the disease, based on the acquired examination result information D2. The disease information generation unit 140 outputs the generated disease information D3 to the presentation unit 150.

[0047] [Prediction of Future Progression of Disease State] Note that the learned model M may be learned so as to be able to predict the degree of future progression of a disease of a specific patient P.

[0048] For example, the learned model M learns by associating the time series of the progression of the medical conditions of a plurality of patients P suffering from a disease indicated by the medical condition data D13 with the time series of the examination results obtained by a specialist in the disease observing the progress of each of the plurality of patients P. As a result, when given the objective data D11 from the past to the present for a specific patient P, the learned model M can estimate the future progress of the medical condition of this specific patient P.

[0049] In this case, the target variable acquisition unit 130 acquires the time series of examination results output by the learned model M given the objective data D11 as examination result information D2 respectively. The disease information generation unit 140 generates information regarding the degree of progression of the future disease of a specific patient P as disease information D3 based on the examination result information D2.

[0050] [Presentation of Disease Information to Patient P and Medical Staff] (Step S150) The presentation unit 150 presents the generated disease information D3 to the patient P and medical staff. As an example of the case where the disease information D3 is presented to the patient P, a disease information display screen P3 indicating an alert to the patient P will be described.

[0051] FIG. 9 is a diagram showing an example of the disease information display screen P3 of the present embodiment. The presentation unit 150 causes the disease information display screen P3 shown in the figure to be displayed on the display unit 201 of the patient terminal 20 as the disease information D3. As an example, the disease information display screen P3 includes a sentence expressing concern for the physical condition of the patient P, such as "Attention! How is your recent physical condition? Let's take it easy for a while", when the estimated value of the activity intensity (Mets) of the patient P becomes a predetermined value or more.

[0052] The disease information generation unit 140 described above may generate disease information D3 divided into multiple levels, such as "Level 1: No alert," "Level 2: Rest required alert," and "Level 3: Medical consultation required alert," depending on the medical condition indicated by the examination result information D2. In this example, at "Level 1: No alert," the presentation unit 150 does not present disease information D3 to the patient terminal 20. At "Level 2: Rest required alert," the disease information display screen P3 is presented to the patient terminal 20 as disease information D3. At "Level 3: Medical consultation required alert," a screen (not shown) prompting the patient terminal 20 to immediately visit a medical institution (for example, their primary care physician) is presented as disease information D3.

[0053] In other words, disease information D3 is information indicating that the disease has worsened. The presentation unit 150 presents to a specific patient P that the disease has worsened.

[0054] [Interactive Presentation of Examination Result Information] The disease information presentation device 10 may also present examination result information D2 based on the results of the patient P's operation of the patient terminal 20. In other words, the disease information presentation device 10 may present the examination result information D2 interactively with the patient P. An example of an interactive examination result information D2 presentation screen will be described using the physical condition selection screen P31.

[0055] Figure 10 shows an example of the health condition selection screen P31 of this embodiment. The health condition selection screen P31 includes a question P310 that inquires about the health condition of patient P, in addition to the text expressing concern for patient P's health condition displayed on the disease information display screen P3 described above. The question P310 includes multiple options (three options in the example shown in the figure) regarding patient P's health condition. Patient P operates the patient terminal 20 to select one of the options in the question P310. The disease information presentation device 10 displays one of the following screens on the display unit 201 of the patient terminal 20: the first advice screen P311, the second advice screen P312, or the third advice screen P313, depending on the selection result.

[0056] According to the disease information management system 1 configured in this way, it is possible to reduce the anxiety that patient P feels during the period until their next medical visit, and to advise patient P to reduce physical strain if there is a risk of their condition worsening.

[0057] [Second Embodiment] Figure 11 shows an example of the functional configuration of the disease information management system 1a of the second embodiment. The disease information management system 1a differs from the disease information management system 1 described above in that the disease information presentation device 10 comprises a subjective data acquisition unit 160 and a medical examination support information generation unit 170.

[0058] In step S110 described above, the subjective data acquisition unit 160 acquires subjective data D12 from the subjective data acquisition device 50. An example of the subjective data acquisition device 50 will be described below.

[0059] [Subjective Data Acquisition Device] Subjective data D12 refers to subjective data D12 that shows situations other than the objective data D11 described above, among the situations that patient P is aware of. As described above, the symptoms shown in objective data D11 are objectively obtainable symptoms of patient P, and refer to symptoms that are given simple names that patient P can understand, rather than specialized terms that only medical professionals can understand. On the other hand, the symptoms shown in subjective data D12 broadly include the symptoms that patient P feels among patient P's symptoms. For example, the symptoms shown in subjective data D12 may include symptoms that patient P is aware of (subjective symptoms). As an example, subjective symptoms of patient P may include shortness of breath, palpitations, malaise, chest pain, fatigue, loss of appetite, nausea, headache, edema, etc. Furthermore, the symptoms indicated by subjective data D12 include symptoms that patient P subjectively describes, regardless of whether they are related to a specific disease, such as "a feeling that is different than usual" or "feeling unwell," which patient P may find difficult to express. Patient P may communicate these various symptoms to healthcare professionals during examinations and tests.

[0060] In this situation, if the healthcare professional who hears about patient P's mental state is a specialist in a specific disease (for example, PH), they may be able to grasp the degree of progression of patient P's condition. On the other hand, if the healthcare professional is not a specialist in the specific disease, they may mistakenly judge that the situation described by patient P is unrelated to the progression of the disease and is merely a mental issue. If the situation described by patient P is related to the progression of the disease, but is mistakenly judged as unrelated, patient P may subsequently come to believe that their own perception was wrong and may avoid telling their doctor about even minor changes in their physical condition, which could lead to adverse effects.

[0061] In this embodiment, the disease information management system 1 acquires subjective information about the patient P's subjective condition as conveyed by the patient P to the medical professional, using a subjective data acquisition device 50 as subjective data D12. For example, the subjective data acquisition device 50 is equipped with a sound-collecting unit such as a microphone and records conversations between the patient P and the medical professional. The subjective data acquisition device 50 extracts conversations corresponding to subjective data D12 from the recorded conversations and outputs them to the disease information presentation device 10a.

[0062] As another example, the subjective data acquisition device 50 may be equipped with an imaging unit such as a video camera. In this case, the subjective data acquisition device 50 captures the situation of the conversation between the patient P and the medical professional. The subjective data acquisition device 50 extracts the situation corresponding to subjective data D12 from the captured conversation situation and outputs it to the disease information presentation device 10a.

[0063] As another example, the subjective data acquisition device 50 may display a question on the patient terminal 20 inquiring about the patient P's subjective condition. The subjective data acquisition device 50 acquires the patient P's answer to the question as subjective data D12 and outputs it to the disease information presentation device 10a.

[0064] The subjective data acquisition unit 160 acquires subjective data D12 that shows the subjective complaints of patient P regarding their physical condition.

[0065] When the subjective data acquisition unit 160 acquires subjective data D12 from the subjective data acquisition device 50, it outputs the acquired subjective data D12 to the explanatory variable assignment unit 120. The explanatory variable assignment unit 120 outputs the subjective data D12 acquired by the subjective data acquisition unit 160 as explanatory variable data D1, in addition to (or instead of) the objective data D11 acquired by the objective data acquisition unit 110 described above, to the trained model M.

[0066] In this embodiment, the trained model M is trained using disease condition data D13 and subjective data D12, which represents the subjective complaints of patient P regarding their physical condition, as explanatory variables. When subjective data D12 is given as an explanatory variable, the trained model M outputs the examination result information D2 corresponding to the subjective data D12 as the target variable.

[0067] The target variable acquisition unit 130 acquires the examination result information D2 output by the trained model M. As described above, this examination result information D2 is information output by the trained model M based on subjective data D12. The target variable acquisition unit 130 outputs the acquired examination result information D2 to the examination support information generation unit 170 in addition to (or instead of) the disease information generation unit 140.

[0068] The examination support information generation unit 170 generates examination support information D4, which indicates the content of what the doctor examining patient P says to patient P, based on the examination result information D2 acquired by the target variable acquisition unit 130.

[0069] [Prediction of future disease progression] Similar to the first embodiment described above, the trained model M may be trained to predict the future degree of disease progression for a specific patient P.

[0070] In other words, the trained model M learns by associating the time series of disease progression of multiple patients P suffering from a disease, as shown by the disease condition data D13, with the time series of examination results from follow-up observations by disease specialists for each of the multiple patients P. The target variable acquisition unit 130 acquires the time series of examination results output by the trained model M, which is given objective data D11, as examination result information D2. The examination support information generation unit 170 generates examination support information D4 based on the examination result information D2, which includes the content of verbal communication corresponding to the future progression of the disease of a particular patient P. The examination support information D4 includes the content of verbal communication from medical professionals to patient P, corresponding to the subjective situation of patient P as revealed in conversations between patient P and medical professionals during examinations and tests. For example, if patient P's physical burden is increasing, the examination support information D4 may include phrases such as, "How have you been feeling lately? Let's take it easy for a while."

[0071] [Presentation of Examination Support Information] The presentation unit 150 presents examination support information D4 to the physician. Figure 12 shows an example of when the presentation unit 150 presents examination support information D4 on the electronic medical record screen P4 displayed on the display device 60.

[0072] Figure 12 shows an example of the electronic medical record screen P4 of this embodiment. The electronic medical record screen P4 includes an objective data display area P41 and an advice display area P42. The objective data display area P41 is a section that presents the objective data D11 shown in Figure 3 to healthcare professionals. The objective data display area P41 shows the objective data D11 for each patient P. The advice display area P42 is a section that presents the medical support information D4 generated by the medical support information generation unit 170 to healthcare professionals. As an example of the content of the message, the advice display area P42 displays text such as, "How have you been feeling lately? Let's take it easy for a while."

[0073] According to the disease information management system 1a configured in this way, it is possible to take into account even minor subjective changes in the patient's physical condition, reduce the anxiety the patient feels during the period until their next medical visit, and advise the patient to reduce physical strain if there is a risk of the patient's condition worsening.

[0074] [Summary of Embodiments] To date, numerous support systems have been developed for patients with specific diseases such as hypertension and diabetes. On the other hand, there have been few support systems for patients with pulmonary hypertension (PH), and all of them have been for the patient's self-management.

[0075] The disease information management system 1 of this embodiment is unprecedented in that it compares data not only from the patient's side but also from the healthcare provider's side, and uses a trained model M to support patients and healthcare professionals.

[0076] Traditionally, a patient's current medical condition could only be determined through invasive tests such as blood tests or right heart catheterization during a medical visit. However, the disease information management system 1 now evaluates this condition in real time, allowing it to detect early signs of worsening symptoms and issue alerts from the patient's home.

[0077] This encourages patients to reduce their activity levels, rest, and seek medical attention early, which can prevent the progression of PH and the worsening of right heart failure, thus contributing to a reduction in readmission rates and prevention of worsening prognosis. In addition, alerts can be issued in cases of excessive rest, encouraging low-stress activities and potentially improving activity tolerance.

[0078] Because PH is a chronic disease, patients live with symptoms on a daily basis. In the early stages of exacerbation of right heart failure symptoms, it is not uncommon for patients to feel something is different than usual, even if they cannot put it into words, such as "I don't feel as well as usual today," "I feel tired easily," "I feel sluggish," "My heart is racing more than usual," or "I feel somehow more uncomfortable than usual." These "unusual feelings" are suspected to be signs of worsening, but if they are faint signs that are not yet reflected in test data, there is a risk that even if the patient reports them to a healthcare provider, they will be dismissed as a psychological problem. The disease information management system 1 accumulates and learns from the patient's subjective data, measurement data, and hospital test data, so it has a high probability of determining that these signs are signs of worsening, and by informing the patient before the condition worsens, it is possible that the patient will take preventive actions and thus prevent readmission.

[0079] Because PH is a rare and intractable disease, there are still aspects that remain unclear, making generalization difficult. However, according to the disease information management system 1 of this embodiment, since it is a system that accumulates and learns from individual patient data, it can provide personalized medical care for each patient.

[0080] Furthermore, with the disease information management system 1 of this embodiment, healthcare professionals can also grasp the trends in the patient's subjective data, weight, and activity levels from the management screen, making it possible to utilize this information in daily medical practice.

[0081] While embodiments of the present invention have been described in detail above with reference to the drawings, the specific configuration is not limited to these embodiments, and design changes and the like are also included within the scope of the gist of the present invention. For example, a computer program for realizing the functions of each of the above-described devices may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read by a computer system and executed. The term "computer system" as used herein may include hardware such as an operating system and peripheral devices.

[0082] Furthermore, "computer-readable recording media" refers to writable non-volatile memory such as flexible disks, magneto-optical disks, ROMs, and flash memory, portable media such as DVDs (Digital Versatile Discs), and storage devices such as hard disks built into computer systems. In addition, "computer-readable recording media" also includes volatile memory (such as DRAM (Dynamic Random Access Memory)) within computer systems that act as servers or clients when programs are transmitted via networks such as the Internet or communication lines such as telephone lines, which retains programs for a certain period of time.

[0083] Furthermore, the above program may be transmitted from a computer system that stores the program in a memory device or the like to another computer system via a transmission medium or by transmission waves within the transmission medium. Here, the "transmission medium" for transmitting the program refers to a medium that has the function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. Also, the above program may be for the purpose of realizing a part of the functions described above. Furthermore, it may be a so-called differential file (differential program) that can realize the above functions in combination with a program already recorded in the computer system.

[0084] 1... Disease information management system, 10... Disease information display device, 20... Patient terminal, 30... Objective data storage unit, 40... Trained model storage unit, 50... Subjective data acquisition device

Claims

1. A disease information presentation device comprising: an objective data acquisition unit that acquires objective data that objectively shows the medical condition of a specific patient suffering from a chronic and progressive disease; an explanatory variable assignment unit that assigns the acquired objective data as explanatory variables to a trained model that has been trained with medical condition data that objectively shows the medical condition of multiple patients suffering from the disease as explanatory variables and the results of medical examinations of each of the multiple patients when examined by a specialist in the disease as the objective variable; an objective variable acquisition unit that acquires the medical examination results, which are the objective variable output by the trained model to which the objective data has been assigned, as medical examination result information; a disease information generation unit that generates disease information which is information relating to the degree of progression of the disease based on the acquired medical examination result information; and a presentation unit that presents the generated disease information.

2. The disease information display device according to claim 1, wherein the disease is pulmonary hypertension.

3. The disease information display device according to claim 1, wherein the disease information is information indicating that the disease has worsened, and the display unit displays to the specific patient that the disease has worsened.

4. The disease information presentation device according to claim 3, wherein the trained model has learned by associating the time series of disease progression of multiple patients suffering from the disease, as indicated by the disease condition data, with the time series of examination results obtained when a specialist in the disease observed each of the multiple patients; the target variable acquisition unit acquires the time series of examination results output by the trained model given the objective data, as examination result information; and the disease information generation unit generates information regarding the future degree of disease progression of a particular patient, based on the examination result information.

5. A disease information presentation device according to claim 1, further comprising: a subjective data acquisition unit that acquires subjective data indicating subjective complaints about the patient's physical condition; and a medical support information generation unit that generates medical support information indicating the content of what a physician examining the patient says to the patient, based on the medical result information acquired by the objective variable acquisition unit, wherein the trained model is trained with the disease condition data and subjective data indicating subjective complaints about the patient's physical condition as explanatory variables, and the presentation unit presents the medical support information to the physician.

6. The disease information presentation device according to claim 5, wherein the trained model has learned by associating the time series of the progression of the disease in multiple patients suffering from the disease, as indicated by the disease condition data, with the time series of examination results obtained when a specialist in the disease observed each of the multiple patients; the target variable acquisition unit acquires the time series of examination results output by the trained model given the objective data, as examination result information; and the examination support information generation unit generates, based on the examination result information, the content of verbal encouragement corresponding to the future progression of the disease in the specific patient, as examination support information.

7. A program for causing a computer to perform the following actions: acquire objective data that objectively shows the medical condition of a specific patient suffering from a chronic and progressive disease; provide the acquired objective data as an explanatory variable to a trained model that has been trained with the medical condition data objectively showing the medical condition of multiple patients suffering from the disease as explanatory variables and the examination results of the medical condition when each of the multiple patients is examined by a specialist in the disease as the dependent variable; acquire the examination results, which are the dependent variable output by the trained model to which the objective data has been provided, as examination result information; generate disease information, which is information regarding the degree of progression of the disease, based on the acquired examination result information; and present the generated disease information.

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