Diagnosis support device, diagnosis support system, and program

Abstract

To improve diagnostic efficiency.SOLUTION: A diagnosis support device according to an embodiment comprises: an acquisition unit which acquires medical examination data including at least patient information related to a patient and medical examination information related to the medical examination of the patient; an analysis unit which analyzes the medical examination information included in the acquired medical examination data; a first calculation unit which calculates a first probability being the probability of the patient having coronary artery disease on the basis of the patient information included in the acquired medical examination data and the analysis result of the analysis unit; and a suggestion unit which suggests examinations to be performed on the patient on the basis of the medical examination data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The embodiments disclosed in this specification and the drawings relate to a diagnosis support device, a diagnosis support system, and a program. [Background technology]

[0002] Conventionally, there have been guidelines for the diagnosis of stable coronary artery disease (CAD), such as stable angina pectoris. These guidelines provide a method for calculating the probability of stable CAD. Therefore, by referring to these guidelines, doctors can calculate and evaluate the probability that a patient has stable CAD.

[0003] Although there are guidelines for the diagnosis of stable CAD, in order to calculate the probability of stable CAD, such as the pre-test probability (PTP) presented in these guidelines or the modified pre-test probability (PTP·CL), which is a PTP that takes into account clinical likelihood (CL), doctors must use various data to extract the elements necessary for calculating the probability of stable CAD from the various data and perform calculations, which is time-consuming for doctors.

[0004] In addition, to improve the diagnostic accuracy of stable CAD, doctors need to carry out several tests. However, doctors need to calculate and evaluate the probability of stable CAD and select which tests to carry out, which is time-consuming for doctors. For this reason, it is desirable to improve diagnostic efficiency by supporting the calculation of the probability of stable CAD, such as PTP and PTP·CL, while easily selecting tests to improve the diagnostic accuracy of stable CAD. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Special Publication No. 2017-533427 [Patent Document 2] International Publication No. 2013 / 175683 [Patent Document 3] JP 2019-070669 A [Non-patent literature]

[0006] [Non-Patent Document 1] "2022 JCS Guideline Focus Update: Diagnosis and Treatment of Stable Coronary Artery Disease", Japanese Circulation Society, March 11, 2022 Summary of the Invention [Problem to be solved by the invention]

[0007] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to improve diagnostic efficiency. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0008] A diagnostic support device according to an embodiment includes an acquisition unit that acquires medical data including at least patient information about a patient and medical information about the medical treatment of the patient, an analysis unit that analyzes the medical information included in the acquired medical data, a first calculation unit that calculates a first probability, which is the probability of having coronary artery disease, based on the patient information included in the acquired medical data and an analysis result by the analysis unit, and a suggestion unit that suggests tests to be performed on the patient based on the medical data. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a diagnosis support system according to an embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of a PTP table stored in a memory of a diagnosis support device according to an embodiment. [Diagram 3] 4 is a diagram showing an example of a CL table relating to elements constituting a CL stored in a memory 41 of a diagnosis support device 40 according to an embodiment. FIG. [Figure 4] FIG. 4 is a diagram showing an example of a likelihood table stored in a memory of a diagnosis support device according to an embodiment. [Diagram 5] FIG. 4 is a flowchart illustrating the contents of a suggestion process executed by the diagnosis support device according to an embodiment. [Figure 6] FIG. 4 is a diagram showing an example of medical data acquired by a diagnosis support device according to an embodiment. [Figure 7] FIG. 11 is a diagram showing an example of an analysis result of the diagnosis support apparatus according to an embodiment. [Figure 8] FIG. 4 is a diagram showing an example of an output of an output interface in the diagnosis support device according to an embodiment. [Figure 9] FIG. 11 is a diagram showing an example of a medical interview or examination suggested by a diagnosis support device according to an embodiment. [Figure 10] FIG. 4 is a diagram showing an example of a test result acquired by a diagnosis support device according to an embodiment. [Figure 11] FIG. 4 is a diagram showing an example of a likelihood table stored in a memory of a diagnosis support device according to an embodiment. [Figure 12] FIG. 4 is a diagram showing an example of an output of an output interface in the diagnosis support device according to an embodiment. [Figure 13] FIG. 11 is a diagram showing an example of a medical interview or examination suggested by a diagnosis support device according to an embodiment. [Figure 14] FIG. 4 is a diagram showing an example of an output of an output interface in the diagnosis support device according to an embodiment. [Figure 15] FIG. 11 is a diagram showing an example of a medical interview or examination suggested by a diagnosis support device according to an embodiment. [Figure 16] FIG. 4 is a diagram showing an example of an output of an output interface in the diagnosis support device according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of a diagnosis support device, a diagnosis support system, and a program will be described with reference to the drawings. In the following description, components having substantially the same functions and configurations are denoted by the same reference numerals, and duplicated descriptions will be given only when necessary.

[0011] FIG. 1 is a block diagram showing an example of the configuration of a diagnosis support system according to an embodiment. As shown in FIG. 1, the diagnosis support system 1 according to this embodiment is configured to include a hospital information system (Hospital Information System: HIS) 10, an examination device 20, a medical image diagnostic device 30, and a diagnosis support device 40. The hospital information system 10, the examination device 20, the medical image diagnostic device 30, and the diagnosis support device 40 are communicatively connected via an intra-hospital network using a dedicated line within the hospital. The hospital information system 10, the examination device 20, the medical image diagnostic device 30, and the diagnosis support device 40 may be communicatively connected to each other via a network using a public line such as the Internet. The configuration of the diagnosis support system 1 according to this embodiment is not limited to the above example. For example, the examination device 20 and the medical image diagnostic device 30 may be connected to an intra-hospital network using a dedicated line within the hospital via the hospital information system 10.

[0012] The hospital information system 10 is a system that manages information generated within a hospital. Information generated within a hospital includes, for example, medical data, hospital equipment information, electronic medical record reservation slot information, and the like. In addition, the hospital information system 10 transmits information generated within a hospital, such as medical data, to a diagnosis support device 40, and the like. Note that the information generated within a hospital is not limited to medical data, hospital equipment information, and electronic medical record reservation slot information. In other words, any information may be included in the information generated within a hospital, and may include various information other than medical data, hospital equipment information, and electronic medical record reservation slot information generated within a hospital.

[0013] The medical data includes information such as basic patient information and medical information. The basic patient information includes, for example, a patient ID, a patient name, an age, a sex, an address, a height, a weight, contraindication information, and a patient's economic situation. This basic patient information corresponds to the patient information according to the present embodiment. The medical information includes, for example, interview information related to the interview including the interview contents and the interview results, progress records such as symptoms, findings, treatment items and treatment results, and examination information related to the examination including the test order and the test results.

[0014] The examination is, for example, an examination such as taking a medical history and anamnesis conducted by a doctor on a patient, or an examination conducted on a patient using the examination device 20 or the medical image diagnostic device 30. Furthermore, the examination result may be, for example, the result of taking a medical history and anamnesis conducted by a doctor and recorded in a medical record, the examination result by the examination device 20, an examination report having findings on the examination result by the examination device 20, a medical image captured by the medical image diagnostic device 30, an image interpretation report having findings on the medical image, or other information on the examination result.

[0015] The hospital facility information includes information on the examination devices 20 and medical image diagnostic devices 30 installed in the hospital. Note that the hospital facility information is not limited to information on the examination devices 20 and medical image diagnostic devices 30 installed in the hospital, but may include information on the examination devices 20 and medical image diagnostic devices 30 installed in hospitals affiliated with the hospital or in nearby hospitals.

[0016] The electronic medical record reservation slot information is information related to the reservation slots of examinations registered in the electronic medical record. This electronic medical record reservation slot information includes examination reservation information related to the reservation status of the examination, etc.

[0017] 1, this hospital information system 10 includes an electronic medical record system 11, an examination department information management system 12, a radiology department information management system 13, a medical image storage system 14, a dose management system 15, and a medical accounting system 16. The electronic medical record system 11, the examination department information management system 12, the radiology department information management system 13, the medical image storage system 14, the dose management system 15, and the medical accounting system 16 are communicatively connected via an intra-hospital network using dedicated lines within the hospital.

[0018] The hospital information system 10 according to the present embodiment includes the electronic medical record system 11, the examination department information management system 12, the radiology department information management system 13, the medical image storage system 14, the dose management system 15, and the medical accounting system 16, but the systems included in the hospital information system 10 are not limited to these. The hospital information system 10 may include other department systems, such as a surgery department system, a rehabilitation department system, and a dialysis department system. The configuration of the hospital information system 10 is not limited to the example shown in FIG. 1. For example, the examination department information management system 12, the radiology department information management system 13, the medical image storage system 14, the dose management system 15, and the medical accounting system 16 may be connected to an intra-hospital network using a dedicated line within the hospital via the electronic medical record system 11.

[0019] The electronic medical record system 11 is a system for managing information related to electronic medical records. The information related to electronic medical records includes, for example, basic patient information, and medical interview information related to a medical interview including the contents and results of the medical interview.

[0020] The testing department information management system 12 is a system for managing information related to tests using the testing device 20. Information related to tests using the testing device 20 includes, for example, test orders for specimen tests, physiological function tests, etc. transmitted from the electronic medical record system 11, etc., and test results for specimen tests, physiological function tests, etc. and / or test reports having findings on the test results for specimen tests, physiological function tests, etc. Examples of specimen tests include blood tests, urine tests, pathological tests, microbiological tests, and immunoserological tests. Examples of physiological function tests include cardiac tests such as electrocardiograms, electroencephalograms, respiratory function tests, and fundus photography tests.

[0021] The radiology department information management system 13 is a system that manages information in the radiology department of a hospital. The radiology department information management system 13 according to this embodiment manages, for example, information related to imaging examinations using a medical image diagnostic device 30. The information related to imaging examinations using the medical image diagnostic device 30 includes, for example, information related to examination orders for imaging examinations transmitted from an electronic medical record system 11 or the like. The radiology department information management system 13 is also called a RIS (Radiology Information Systems).

[0022] The medical image archiving system 14 is a so-called PACS (Picture Archiving and Communication System) that stores various medical images transmitted from the medical image diagnostic device 30. In this medical image archiving system 14, the medical images are stored in accordance with, for example, the DICOM (Digital Imaging and Communication Medicine) standard. The medical image archiving system 14 also stores radiology reports and the like that include findings on the medical images.

[0023] The dose management system 15 is a device that manages information related to exposure of each device in the medical image diagnostic apparatus 30. The information related to exposure is, for example, information on the presence or absence of exposure of each device in the medical image diagnostic apparatus 30, the exposure dose, etc.

[0024] The medical accounting system 16 manages various information related to accounting. This information related to accounting is, for example, cost information such as insurance points for each test or medical treatment. The medical accounting system 16 also includes, for example, a terminal device used by the accounting clerk to receive patients and account for medical fees, a mobile terminal carried by the clerk, and an automatic payment machine where patients can account for medical fees, etc.

[0025] The testing device 20 is a device for performing specimen tests such as blood tests and urine tests, and physiological function tests such as electroencephalogram tests and cardiac tests. The testing device 20 performs tests based on test orders managed by the testing department information management system 12, for example. The testing device 20 also transmits test results of specimen tests and physiological function tests to the electronic medical record system 11, the testing department information management system 12, the diagnosis support device 40, and the like through the hospital network. In the example shown in FIG. 1, the number of testing devices 20 connected to the hospital network is one, but the number of testing devices 20 is not limited to this. That is, the number of testing devices 20 is arbitrary, and multiple testing devices 20 may be connected to the hospital network depending on the type of specimen test and the type of physiological function test.

[0026] The medical image diagnostic device 30 is a device for generating medical images of a patient. The medical image diagnostic device 30 is, for example, an X-ray diagnostic device, an X-ray CT (Computed Tomography) device, an ultrasound diagnostic device, an MRI (Magnetic Resonance Imaging) device, a SPECT (Single Photon Emission Computed Tomography) device, or a PET (Positron Emission Computed Tomography) device. The medical image diagnostic device 30 performs an examination based on an examination order managed by the radiology department information management system 13, for example, and generates a medical image. The medical image diagnostic device 30 also transmits the medical image to the medical image storage system 14, the diagnosis support device 40, etc., through the hospital network.

[0027] The diagnostic support device 40 is a device that calculates the probability of having stable CAD and suggests tests to improve the accuracy of stable CAD diagnosis to a doctor based on medical data managed by each system of the hospital information system 10. As shown in FIG. 1, the diagnostic support device 40 has a memory 41, an output interface 42, an input interface 43, a communication interface 44, and a processing circuit 45.

[0028] The memory 41 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc. The memory 41 stores various information such as, for example, clinical data acquired from the hospital information system 10, a PTP table for calculating PTP (pre-test probability), a CL table regarding elements constituting CL (clinical likelihood), and a likelihood table for calculating PTP·CL (corrected pre-test probability).

[0029] Here, PTP (pre-test probability) is the probability of having CAD (coronary artery disease). Specifically, PTP is a baseline pre-test probability, and is a pre-test probability of CAD calculated by evaluating three items including the characteristics of chest symptoms or dyspnea, age, and sex based on a doctor's interview with the patient before the test. This PTP corresponds to the first probability in this embodiment.

[0030] The elements constituting CL (clinical likelihood) are elements that act as correction factors for correcting PTP. The elements constituting CL are also elements included in the test results. The elements constituting CL correspond to the elements that affect the first probability and the second probability in this embodiment.

[0031] PTP·CL (modified pre-test probability) is the probability of having CAD (coronary artery disease) taking into account the test results. Specifically, PTP·CL is the probability of having CAD taking into account the results of the elements that make up CL contained in the test results, and is a PTP that has been modified according to the results of the elements that make up CL. Therefore, PTP·CL is also a PTP that takes CL into account. This PTP·CL corresponds to the second probability in this embodiment.

[0032] FIG. 2 is a diagram showing an example of a PTP table stored in the memory 41 of the diagnosis support device 40 according to this embodiment. The PTP table shown in FIG. 2 is a table used when calculating PTP (pre-test probability). In the example shown in FIG. 2, PTP values ​​according to age and sex are registered in the PTP table T1 in association with each item of the nature of the chest symptom or dyspnea. Specifically, the PTP table T1 shown in FIG. 2 associates PTP values ​​according to gender and age with each item of typical angina, atypical angina, and non-angina as the nature of the chest symptom, and dyspnea as the dyspnea. Which item of the symptoms, typical angina, atypical angina, non-angina, and dyspnea, corresponds to is determined by interview.

[0033] Specifically, the doctor interviews the patient about the nature of the chest symptoms or symptoms of dyspnea. If the doctor's interview reveals that the patient has dyspnea only or as an initial symptom, the patient will be classified as having dyspnea in PTP table T1 shown in Figure 2. In other words, if the patient has dyspnea only or as an initial symptom, the PTP is calculated from the dyspnea item in PTP table T1 shown in Figure 2 based on the patient's gender and age.

[0034] On the other hand, if the doctor's interview reveals that the patient does not have symptoms of dyspnea and that all three of the following three characteristics of the chest symptoms are met: "presence or absence of a feeling of tightness under the sternum (or neck, jaw, shoulder, or arm)", "presence or absence of aggravation due to exercise or mental stress", and "presence or absence of symptom relief within 5 minutes with rest or nitroglycerin", the patient will be classified as having typical angina in the PTP table T1 shown in FIG. 2. In other words, if all three characteristics are met, the PTP is calculated from the item for typical angina in the PTP table T1 shown in FIG. 2 based on the patient's gender and age. In addition, if the patient does not have symptoms of dyspnea and meets two of the three characteristics, the patient will be classified as having atypical angina in the PTP table T1 shown in FIG. 2. In other words, if two characteristics are met, the PTP is calculated from the item for atypical angina in the PTP table T1 shown in FIG. 2 based on the patient's gender and age. Furthermore, if the patient does not have symptoms of dyspnea and meets one or none of the three characteristics, the patient will be classified as non-anginal in PTP table T1 shown in Figure 2. In other words, if one or none of the three characteristics are met, the PTP is calculated from the non-anginal item in PTP table T1 shown in Figure 2 based on the patient's gender and age.

[0035] In the example shown in FIG. 2, the PTP table T1 is registered with a PTP value according to gender and age for each item of chest symptom characteristics or respiratory discomfort, but the PTP value is not limited to this. That is, each PTP value in the PTP table T1 is arbitrary. For example, each PTP value in the PTP table T1 may be updated based on information such as a paper on CAD.

[0036] Fig. 3 is a diagram showing an example of a CL table relating to elements constituting CL (clinical likelihood) for each test stored in memory 41 of diagnosis support device 40 according to this embodiment. CL table T2 shown in Fig. 3 is a table used when extracting elements constituting CL (clinical likelihood) from medical data, test results, etc. In the example shown in Fig. 3, tests and elements constituting CL (clinical likelihood) are registered in association with each other in CL table T2.

[0037] The examinations in the CL table T2 are items related to examinations necessary to obtain elements constituting the CL. The examinations registered in this CL table T2 are non-invasive examinations. Here, a non-invasive examination is an examination that does not involve a surgical procedure such as insertion of a catheter or a guide wire. In other words, non-invasive examinations include examinations that do not involve a surgical procedure but involve mild invasiveness such as exposure to radiation or puncturing for blood sampling, and examinations that do not involve a surgical procedure and do not involve mild invasiveness. In the following, the examinations in the CL table T2 may be referred to as non-invasive examinations. In the example shown in FIG. 3, for example, CCTA (Coronary Computed Tomography Angiography), stress myocardial blood flow imaging, blood tests, etc., which do not involve a surgical procedure and involve mild invasiveness such as exposure to radiation or puncturing for blood sampling, are registered as non-invasive examinations in the CL table T2. In addition, in the tests in CL Table T2 shown in Figure 3, medical history taking, urine tests, etc., which are tests that do not involve surgical procedures and are not slightly invasive, are registered as non-invasive tests.

[0038] As mentioned above, the elements that make up CL (clinical likelihood) are elements that act as correction factors to correct PTP. As shown in Figure 3, for example, taking a stress electrocardiogram as an example, "ischemic changes," "ST depression," and "ST elevation" are registered as elements that make up CL.

[0039] Note that the examinations registered in the CL table T2 shown in Fig. 3 and the elements constituting the CL are not limited to the example shown in Fig. 3, and other examinations and elements constituting other CLs may be added to the CL table T2. Also, if an examination registered in the CL table T2 shown in Fig. 3 cannot be performed depending on the facilities of a hospital or the like, the examination registered in the CL table T2 shown in Fig. 3 and the elements constituting the CL may be deleted. Furthermore, the examinations registered in the CL table T2 may be updated so that elements constituting the CL are added or deleted later.

[0040] FIG. 4 is a diagram showing an example of a likelihood table stored in the memory 41 of the diagnosis support device 40 according to this embodiment. This likelihood table T3 is a table used when calculating PTP·CL. In the example shown in FIG. 4, the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, equipment used, and whether or not invasiveness is present are associated and registered in the likelihood table T3 for each test. Note that the items associated and registered in the likelihood table T3 are not limited to the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, equipment used, and whether or not invasiveness is present, and other items may be associated and registered. In addition, the tests are the same as those in the CL table T2, so their description will be omitted.

[0041] Sensitivity is the proportion (probability) of people who test positive among those who actually have the disease. As shown in Figure 4, taking stress myocardial perfusion imaging as an example, the sensitivity of stress myocardial perfusion imaging is registered as "85%," and taking stress electrocardiograms as an example, the sensitivity of stress electrocardiograms is registered as "68%." This shows that the sensitivity of stress myocardial perfusion imaging is higher than that of stress electrocardiograms.

[0042] Specificity is the proportion (probability) of people who test negative among those who are not actually suffering from the disease. As shown in Figure 4, taking stress myocardial perfusion imaging as an example, the specificity of stress myocardial perfusion imaging is registered as "72%," and taking stress electrocardiograms as an example, the specificity of stress electrocardiograms is registered as "77%." This shows that the specificity of stress electrocardiograms is higher than that of stress myocardial perfusion imaging.

[0043] The positive likelihood ratio is an index that indicates how many times more likely a diseased person is to test positive than a disease-free person when focusing on people who test positive for a certain test. As shown in Figure 4, the positive likelihood ratio can be calculated as positive likelihood ratio = sensitivity / (1-specificity).

[0044] The negative likelihood ratio is an index that indicates how many times more likely a diseased person is to have a negative test result than a disease-free person when focusing on people who have a negative test result. As shown in Figure 4, the negative likelihood ratio can be calculated as negative likelihood ratio = (1 - sensitivity) / specificity.

[0045] The equipment used is information about the equipment used to perform the examination registered in the examination item. As shown in Fig. 4, taking stress myocardial perfusion imaging as an example, the equipment used in stress myocardial perfusion imaging is a SPECT device, an MRI device, an ultrasound diagnostic device, and a PET device, and taking stress electrocardiogram as an example, the equipment used in stress electrocardiogram is an electrocardiograph. Note that when multiple devices are associated and registered as the equipment used, as in stress myocardial perfusion imaging, any one of the devices may be used to perform the examination.

[0046] The "invasion" is information on the presence or absence of minor invasion that does not involve surgical procedures. In the example shown in Fig. 4, if there is a possibility of minor invasion, such as exposure to radiation in an X-ray CT scanner or puncture for blood sampling in a blood test, the "invasion" is registered as "yes," and if there is no possibility of invasion, such as an examination using an electrocardiograph or an ultrasound diagnostic device, the "invasion" is registered as "no."

[0047] In the likelihood table T3, the sensitivity value, the specificity value, the positive likelihood ratio value, and the negative likelihood ratio value are associated with each test and registered, but the values ​​associated with each test in the likelihood table T3 are not limited to this. In other words, the values ​​associated with each test in the likelihood table T3 are arbitrary. For this reason, each value in the likelihood table T3 may be updated based on a paper on CAD. In addition, in the example shown in FIG. 4, the sensitivity, specificity, etc. are associated with each test such as medical history and medical history taking and stress myocardial blood flow imaging, but the contents registered in the likelihood table T3 are not limited to this. For example, the likelihood table T3 may be associated with the sensitivity and specificity for each element constituting the CL (clinical likelihood) in the CL table T2 shown in FIG. 3, that is, the cardiovascular disease and smoking history in the medical history and medical history taking, and the abnormal Q wave in the resting electrocardiogram, and the like, and registered.

[0048] Furthermore, the tests registered in the likelihood table T3 shown in Fig. 4 are not limited to the example shown in Fig. 3, and other tests may be added to the likelihood table T3 and registered in association with the sensitivity value, specificity value, etc. Furthermore, if the tests shown in Fig. 4 cannot be performed due to the facilities of the hospital or the like, the tests, sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, facilities used, and presence or absence of invasiveness registered in the likelihood table T3 shown in Fig. 4 may be deleted. Furthermore, the likelihood table T3 may be updated so that facilities used later are added to or deleted from the tests registered in the likelihood table T3.

[0049] The output interface 42 is connected to the processing circuit 45 and outputs a signal supplied from the processing circuit 45. The output interface 42 is realized by, for example, a display circuit, a printed circuit, an audio device, and the like. The display circuit includes, for example, a CRT display, a liquid crystal display, an organic EL display, an LED display, and a plasma display. The display circuit also includes an output circuit that converts data representing a display object into a video signal and outputs the video signal to the outside. The printed circuit includes, for example, a printer, and the like. The printed circuit also includes an output circuit that outputs data representing a print object to the outside. The audio device includes, for example, a speaker, and the like. The audio device also includes an output circuit that outputs an audio signal to the outside.

[0050] The input interface 43 is a circuit that accepts various inputs from the user, and in this embodiment, for example, accepts input operations related to the decision to perform an examination from the user. In this embodiment, the input interface 43 is realized by, for example, a mouse, a keyboard, a trackball, a manual switch, a foot switch, a button, a joystick, etc.

[0051] The communication interface 44 implements various information communication protocols according to the form of the intra-hospital network. The communication interface 44 realizes communication with other devices via the intra-hospital network according to the various protocols. In this embodiment, the diagnosis support device 40 is connected to the intra-hospital network via the communication interface 44, and realizes communication with the hospital information system 10, the examination device 20, and the medical image diagnostic device 30.

[0052] The processing circuit 45 is an arithmetic circuit that performs various calculations. The processing circuit 45 according to the present embodiment acquires medical data including basic patient information and medical information, analyzes the medical information in the acquired medical data, calculates PTP, calculates PTP·CL, and suggests examinations.

[0053] For this reason, the processing circuit 45 according to this embodiment has an acquisition function 451, an analysis function 452, a PTP calculation function 453, a PTP·CL calculation function 454, and a suggestion function 455. The acquisition function 451 corresponds to the acquisition unit according to this embodiment, the analysis function 452 corresponds to the analysis unit according to this embodiment, the PTP calculation function 453 corresponds to the first calculation unit according to this embodiment, the PTP·CL calculation function 454 corresponds to the second calculation unit according to this embodiment, and the suggestion function 455 corresponds to the suggestion unit according to this embodiment.

[0054] In the embodiment shown in FIG. 1, each processing function performed by the acquisition function 451, the analysis function 452, the PTP calculation function 453, the PTP·CL calculation function 454, and the suggestion function 455 is stored in the memory 41 in the form of a program executable by a computer. The processing circuit 45 is a processor that realizes the function corresponding to each program by reading and executing the program from the memory 41. In other words, the processing circuit 45 in a state in which each program is read has each function shown in the processing circuit 45 of FIG. 1. Note that, in FIG. 1, it has been described that the acquisition function 451, the analysis function 452, the PTP calculation function 453, the PTP·CL calculation function 454, and the suggestion function 455 are realized by a single processing circuit 45, but it is also possible to configure the processing circuit 45 by combining multiple independent processors, and realize these functions by each processor executing a program.

[0055] The acquisition function 451 acquires various data and information from the electronic medical record system 11, the examination department information management system 12, the radiology department information management system 13, the medical image storage system 14, the dose management system 15, the medical accounting system 16, the examination device 20, the medical image diagnostic device 30, etc. in the hospital information system 10. In addition, the acquisition function 451 acquires various data and information from the memory 41 when the various data and information are stored in the memory 41.

[0056] The analysis function 452 analyzes various data and information acquired from the electronic medical record system 11, the examination department information management system 12, the radiology department information management system 13, the medical image storage system 14, the dose management system 15, the medical accounting system 16, the examination device 20, the medical image diagnostic device 30, etc. in the hospital information system 10. Specifically, the analysis function 452 may analyze examination reports, image interpretation reports, etc. acquired from the hospital information system 10, or may analyze images such as electrocardiogram waveforms and medical images acquired from the examination device 20, the medical image diagnostic device 30, etc.

[0057] The PTP calculation function 453 calculates the PTP (pre-test probability) based on the patient basic information and the analysis results by the analysis function 452.

[0058] The PTP·CL calculation function 454 calculates the PTP·CL (corrected pre-test probability) based on the PTP calculated by the PTP calculation function 453 and the test results performed on the patient. The test results performed on this patient are the test results included in the medical data acquired before the PTP calculation or the test results performed on the patient after the PTP calculation. In addition, when a test is performed on the patient after the PTP·CL calculation, the PTP·CL calculation function 454 recalculates the PTP·CL based on the test results of the test performed on the patient after the PTP·CL calculation and the PTP·CL.

[0059] The suggestion function 455 suggests tests to be performed on a patient from among tests that have not been performed, based on the medical data and test results acquired by the acquisition function 451. The suggestion function 455 outputs the PTP calculated by the PTP calculation function 453 and the PTP·CL calculated by the PTP·CL calculation function 454.

[0060] 5 is a flow chart for explaining the contents of the suggestion process executed by the diagnosis support device 40 according to this embodiment. In this suggestion process, medical data is acquired from the hospital information system 10, the medical information is analyzed, a PTP is calculated, and an examination is suggested. For example, this suggestion process is a process that is executed when medical data is acquired from the hospital information system 10.

[0061] As shown in FIG. 5, first, the diagnosis support device 40 acquires medical data (step S11). This process of acquiring medical data is realized by the acquisition function 451 in the processing circuit 45. Specifically, the diagnosis support device 40 acquires medical data from the hospital information system 10 via the communication interface 44. In this embodiment, the medical data acquired in step S11 includes, for example, basic patient information such as gender and age, and medical information such as information on the patient's medical interview. The acquisition function 451 in the processing circuit 45 may directly acquire the medical data via the communication interface 44, or the medical data acquired via the communication interface 44 may be temporarily stored in the memory 41, and then the acquisition function 451 in the processing circuit 45 may acquire the medical data from the memory 41.

[0062] Next, as shown in FIG. 5, the diagnosis support device 40 analyzes the medical information (step S13). This process of analyzing the medical information is realized by the analysis function 452 in the processing circuit 45. Specifically, the diagnosis support device 40 analyzes the medical information so as to extract elements for calculating the probability using the PTP table T1 from the medical information in the medical data acquired in step S11. More specifically, the analysis function 452 extracts elements related to the nature of the chest symptoms and / or symptoms of respiratory distress, such as "presence or absence of dyspnea," "presence or absence of a feeling of tightness under the sternum (or neck, jaw, shoulder, or arm)," "presence or absence of exacerbation due to exercise or mental stress," and "presence or absence of symptom relief within 5 minutes with rest or nitroglycerin," from information on the patient's interview in the medical information acquired in step S11 as elements for calculating the probability using the PTP table T1, and analyzes the medical information so as to determine which symptom corresponds to typical angina, atypical angina, non-angina, or dyspnea.

[0063] Next, as shown in Fig. 5, the diagnostic support device 40 calculates the PTP (pre-test probability) (step S15). This process of calculating the PTP is realized by the PTP calculation function 453 in the processing circuit 45. Specifically, the diagnostic support device 40 calculates the PTP based on the patient basic information acquired in step S11 and the analysis result analyzed in step S13. More specifically, the PTP calculation function 453 calculates the PTP from the PTP table T1 shown in Fig. 2 stored in the memory 41 based on the age and sex in the patient basic information and the analysis result regarding the symptoms of typical angina pectoris, atypical angina pectoris, non-angina pectoris, and dyspnea determined in the analysis in step S13.

[0064] Next, as shown in Fig. 4, the diagnosis support device 40 determines whether or not there are test results (step S17). The process of determining whether or not there are test results is realized by the analysis function 452 in the processing circuit 45. Specifically, the diagnosis support device 40 determines whether or not there are test results by determining whether or not there are elements that constitute CL (clinical likelihood) shown in Fig. 3 for the medical data acquired in step S11.

[0065] Then, in step S17, if the medical data includes test results (step S17: YES), the diagnosis support device 40 analyzes the test results (step S19). This process of analyzing the test results is realized by the analysis function 452 in the processing circuitry 45. Specifically, the diagnosis support device 40 analyzes the test results so as to extract the results of the elements that constitute the CL from the test results of the medical information in the medical data.

[0066] Next, as shown in FIG. 5, the diagnosis support device 40 calculates PTP·CL (corrected pre-test probability) (step S21). This process of calculating PTP·CL is realized by the PTP·CL calculation function 454 in the processing circuit 45. Specifically, the diagnosis support device 40 calculates PTP·CL based on the calculated PTP and the test result which is the analysis result. More specifically, the diagnosis support device 40 calculates PTP·CL (corrected pre-test probability) from a predetermined calculation formula using the sensitivity value and specificity value, positive likelihood ratio value, or negative likelihood ratio value in the test corresponding to the element constituting CL from the likelihood table T3 shown in FIG. 4 based on the calculated PTP and the result of the element constituting CL extracted from the test result in step S19. The predetermined calculation formula is, for example, a calculation formula based on Bayesian estimation. In addition, in step S21, when the diagnostic support device 40 uses the values ​​registered in association with the likelihood table T3, it may weight the values ​​of the likelihood table T3 according to the patient's age and gender based on the patient's basic information, and use the weighted values ​​of the likelihood table T3 to calculate PTP·CL from a predetermined calculation formula.

[0067] On the other hand, in step S17, if there is no test result in the medical data (step S17: NO), or after step S21, the diagnosis support device 40 outputs the calculation result (step S23) as shown in Fig. 5. The process of outputting the calculation result is realized by the suggest function 455 in the processing circuit 45. Specifically, the diagnosis support device 40 outputs the calculation result of the PTP calculated in step S15 or the PTP·CL calculated in step S21 via the output interface 42.

[0068] Next, as shown in Fig. 5, the diagnosis support device 40 judges whether or not an examination is to be performed (step S25). This process of judging whether or not an examination is to be performed is realized by the suggestion function 455. Specifically, the diagnosis support device 40 judges whether or not an examination is to be performed based on an input operation by a doctor via the input interface 43 regarding the performance of the examination. This input operation regarding the performance of the examination may be an input operation on a decision button regarding the performance of the examination displayed on the display of the output interface 42, or may be an input operation by voice input regarding the performance of the examination via a microphone or the like in the input interface 43.

[0069] Then, in step S25, when the doctor decides to perform the test, that is, when it is determined based on the input operation by the doctor that the test will be performed (step S25: YES), the diagnosis support device 40 suggests the test (step S27) as shown in Fig. 5. This process of suggesting the test is realized by the suggestion function 455 in the processing circuit 45. Specifically, the suggestion function 455 extracts unperformed tests from the CL table T2 shown in Fig. 3 or the likelihood table T3 shown in Fig. 4 based on the medical data and / or the test results, and suggests the extracted unperformed tests via the output interface 42.

[0070] The suggestion function 455 may preferentially suggest one or more unperformed tests among the extracted unperformed tests based on various information. For example, the suggestion function 455 may acquire hospital equipment information related to the hospital's equipment from the hospital information system 10, and based on the acquired hospital equipment information, may preferentially suggest tests that can be performed at this hospital or a nearby hospital among the unperformed tests.

[0071] Here, the term "preferentially suggested" refers to, for example, when unperformed examinations are displayed on the display circuit in the output interface 42, the examination suggested with priority may be displayed higher than the unperformed examinations displayed, or only the examination suggested with priority among the unperformed examinations may be displayed. Also, for example, when unperformed examinations are printed via a printing circuit in the output interface 42, the examination suggested with priority may be printed higher than the unperformed examinations displayed, or only the examination suggested with priority among the unperformed examinations may be printed. Furthermore, when unperformed examinations are output via an audio device in the output interface 42, the examination suggested with priority may be output as an audio output higher than the other unperformed examinations, or only the examination suggested with priority among the unperformed examinations may be output as an audio output.

[0072] The suggestion function 455 may preferentially suggest an examination that imposes a small burden on the patient based on invasive information on the invasiveness of the examination. The invasive information is, for example, information on the presence or absence of invasiveness registered in the likelihood table T3, or information on exposure such as the presence or absence of exposure and the amount of exposure managed by the radiology department information management system 13 or the dose management system 15. Specifically, the diagnosis support device 40 may acquire invasive information from the hospital information system 10 or the memory 41, and the suggestion function 455 may preferentially suggest a non-invasive examination as an examination that imposes a small burden on the patient among the examinations that have not been performed based on information on the presence or absence of invasiveness included in the acquired invasive information. The diagnosis support device 40 may acquire invasive information from the hospital information system 10 or the memory 41, and the suggestion function 455 may preferentially suggest an examination that does not involve exposure or an examination that involves a small amount of exposure as an examination that imposes a small burden on the patient based on information on the presence or absence of exposure and the amount of exposure included in the acquired invasive information.

[0073] In addition, the diagnostic support device 40 may obtain electronic medical record reservation slot information from the hospital information system 10, and the suggestion function 455 may preferentially suggest, among the unperformed tests, those that have a short time until the start of the test, based on the test reservation information in the electronic medical record reservation slot information.

[0074] Furthermore, the diagnosis support device 40 may obtain cost information from the medical accounting system 16, and the suggestion function 455 may preferentially suggest, among unperformed tests, tests that require less cost based on the cost information. Note that, when the patient basic information includes information on the patient's economic situation, the suggestion function 455 may preferentially suggest, among unperformed tests, tests that require less cost.

[0075] In addition, the diagnostic support device 40 may obtain the sensitivity and / or specificity of the test from the likelihood table T3, and the suggestion function 455 may preferentially suggest tests with high sensitivity and / or specificity among unperformed tests based on the sensitivity and / or specificity of the test.

[0076] Furthermore, when there are multiple tests that are preferentially suggested, the suggestion function 455 may further prioritize the tests that are preferentially suggested based on other information. For example, when the suggestion function 455 preferentially suggests multiple tests based on hospital equipment information, the suggestion function 455 may preferentially suggest, among the tests suggested based on the hospital equipment information, a test that has a short time until the start of the test based on test reservation information as other information.

[0077] Next, as shown in FIG. 5, the diagnosis support device 40 acquires the test results (step S29). This process of acquiring the test results is realized by the acquisition function 451 in the processing circuitry 45. Specifically, the diagnosis support device 40 acquires the test results for the test suggested in step S27 from the hospital information system 10, the examination device 20, or the medical image diagnostic device 30 via the communication interface 44. Note that, although the test results for the suggested test are acquired in the above-mentioned step S29, the test results acquired in step S29 are not limited to the suggested test results. That is, the test results acquired in step S29 are arbitrary, and for example, test results for a test different from the test suggested in step S27 may be acquired.

[0078] Then, when the test results are acquired in step S29, the process returns to step S19, and the test results acquired in step S29 are analyzed, and the process from step S19 is repeated to calculate PTP·CL based on the analysis results and the results calculated in step S15 or step S21.

[0079] On the other hand, in step S25, if the doctor decides not to perform the examination, that is, if it is determined based on the input operation by the doctor that the examination will not be performed (step S25: NO), the suggestion process according to this embodiment is terminated. After this, the doctor may perform an invasive examination such as an invasive coronary angiogram or a coronary artery pressure measurement to make the diagnosis more reliable, or may start treatment based on the results of the examination.

[0080] In the above-mentioned flowchart, an example of a case where a virtual patient receives diagnostic support will be described. First, a doctor performs a medical examination including a medical interview on the virtual patient and registers a medical record, so that the diagnostic support device 40 acquires, as medical data D1, information on the medical record in which the contents of the medical examination including the medical interview are described (step S11).

[0081] Fig. 6 is a diagram showing an example of medical data acquired by the diagnosis support device 40 according to this embodiment. As shown in Fig. 6, the diagnosis support device 40 acquires information such as name, address, etc., as well as "age: 43 years old" and "gender: male" as basic patient information in the medical data D1. Also, as shown in Fig. 6, the diagnosis support device 40 acquires, as information on the medical record in the medical information of the medical data D1, the patient's response to a medical interview such as "I sometimes have a tight pain around my chest. It hurts especially when I move my body. If I lie down, it gets better in about 2 or 3 minutes. I'm not having trouble breathing."

[0082] Next, the diagnosis support device 40 analyzes the patient's response to the medical interview in the medical information, such as "I sometimes feel a tight pain around my chest. It hurts especially when I move my body. It gets better after about 2-3 minutes when I lie down. I have not had any trouble breathing" (step S13). FIG. 7 is a diagram showing an example of the analysis result of the diagnosis support device 40 according to this embodiment. As shown in FIG. 7, the diagnosis support device 40 analyzes information on the chart in the medical information, and extracts, as the analysis result AR1, "a feeling of tightness under the sternum," "worsening during exercise," "symptoms relieved within 5 minutes when at rest," and "no difficulty in breathing" as elements related to the nature of the chest symptoms and / or symptoms of respiratory distress, and determines that they correspond to typical angina symptoms.

[0083] Next, the diagnostic support device 40 calculates the PTP to be 22% by referring to the PTP table T1 shown in FIG. 2 based on the acquired patient basic information such as “[Age] 43 years old” and “[Gender] Male” and the analysis result AR1 such as “Typical angina symptoms” (step S15).

[0084] Next, the diagnosis support device 40 determines whether the acquired medical data D1 includes the results of the examination (step S17), and outputs the calculated PTP of 22% (step S23) since the acquired medical data D1 does not include the results of the non-invasive examination (step S17: NO). FIG. 8 is a diagram showing an example of the output of the output interface 42 in the diagnosis support device 40 according to this embodiment. As shown in FIG. 8, the diagnosis support device 40 displays the calculated PTP of 22% on the display which is the output interface 42. In addition, the diagnosis support device 40 displays a button for allowing the doctor to decide whether or not to perform a non-invasive examination as the examination.

[0085] Next, the diagnosis support device 40 judges whether or not a non-invasive test will be performed based on the input operation by the doctor (step S25), and decides that a non-invasive test will be performed based on the input operation by the doctor (step S25: YES). Therefore, since the acquired medical data D1 does not include test results, the diagnosis support device 40 extracts all tests registered in the CL table T2 shown in Fig. 3 as unperformed tests, acquires hospital equipment information related to the hospital's equipment from the hospital information system 10, extracts tests that can be performed at the hospital from the unperformed tests based on the acquired hospital equipment information, and preferentially suggests the extracted tests (step S27).

[0086] Fig. 9 is a diagram showing an example of tests suggested by the diagnosis support device 40 according to this embodiment. As shown in Fig. 9, the diagnosis support device 40 preferentially suggests four tests including a stress electrocardiogram test via a display which is the output interface 42.

[0087] Next, since the suggested stress ECG test has been performed, the diagnosis support device 40 obtains a report containing the findings of the stress ECG shown in FIG. 10 from the testing department information management system 12 as the test results (step S29). The diagnosis support device 40 then analyzes the findings of the stress ECG shown in FIG. 10 obtained as the test results, and determines that the test result of the stress ECG is positive based on the information that there is ischemic change, which is the result of the elements that constitute CL, included in the findings of the stress ECG (step S19). Next, the diagnosis support device 40 calculates PTP·CL as 45% using a predetermined formula using the calculated PTP of 22% and the positive likelihood ratio of the stress ECG in the likelihood table T4 shown in FIG. 11 based on the analysis results, 2.96 (step S21).

[0088] Next, the diagnosis support device 40 outputs the calculated PTP·CL of 45% (step S23). FIG. 12 is an example of the output of the output interface 42 in the diagnosis support device 40 according to this embodiment, and corresponds to the above-mentioned FIG. 8. As shown in FIG. 12, the diagnosis support device 40 displays the calculated PTP·CL of 45% on the display which is the output interface 42. Also, similar to the case of FIG. 8, the diagnosis support device 40 displays a button for allowing the doctor to decide whether or not to perform a non-invasive test.

[0089] Next, the diagnosis support device 40 judges whether or not a non-invasive test will be performed based on the input operation by the doctor (step S25), and determines that a non-invasive test will be performed based on the input operation by the doctor (step S25: YES). Therefore, the diagnosis support device 40 suggests tests other than the stress electrocardiogram among the tests that can be performed at the hospital yet to be performed based on the medical data D1 and the test results, since the stress electrocardiogram has been performed (step S27). FIG. 13 is a diagram showing an example of a test suggested by the diagnosis support device 40 according to this embodiment. As shown in FIG. 13, the diagnosis support device 40 preferentially suggests three tests including the stress echocardiogram through the display, which is the output interface 42.

[0090] Next, since the suggested stress echocardiography has been performed, the diagnostic support device 40 obtains a report containing the findings of the stress echocardiography from the testing department information management system 12 as the examination result (step S29). The diagnostic support device 40 then analyzes the findings of the stress echocardiography and concludes that the stress echocardiography is positive (step S19). Next, the diagnostic support device 40 recalculates the PTP·CL to 79% using a predetermined formula based on the calculated PTP·CL of 45% and the positive likelihood ratio of the stress echocardiography of 4.53 in the likelihood table T4 shown in FIG. 11 based on the analysis result (step S21).

[0091] Next, the diagnosis support device 40 outputs the calculated PTP·CL of 79% (step S23). FIG. 14 is an example of the output of the output interface 42 in the diagnosis support device 40 according to this embodiment, and is a diagram corresponding to the above-mentioned FIG. 8. As shown in FIG. 14, the diagnosis support device 40 displays the calculated PTP·CL of 79% on the display which is the output interface 42. Also, similar to the case of FIG. 8, the diagnosis support device 40 displays a button for allowing the doctor to decide whether or not to perform a non-invasive test.

[0092] Next, the diagnosis support device 40 judges whether or not a non-invasive test is to be performed based on the input operation by the doctor (step S25), and determines that a non-invasive test is to be performed based on the input operation by the doctor (step S25: YES). Therefore, the diagnosis support device 40 suggests tests other than the stress electrocardiogram and stress echocardiogram among the tests that can be performed at the hospital yet to be performed based on the medical data D1 and the test results, since the stress electrocardiogram and stress echocardiogram have been performed (step S27). FIG. 15 is a diagram showing an example of a test suggested by the diagnosis support device 40 according to this embodiment. As shown in FIG. 15, the diagnosis support device 40 preferentially suggests two tests including a Holter electrocardiogram test via the display, which is the output interface 42.

[0093] Next, since the suggested Holter ECG test has been performed, the diagnosis support device 40 obtains a report containing the Holter ECG findings as the test results from the testing department information management system 12 (step S29). The diagnosis support device 40 then analyzes the Holter ECG test findings to determine that the Holter ECG test is positive (step S19). Next, the diagnosis support device 40 recalculates the PTP·CL to 86% using a predetermined formula based on the calculated PTP·CL of 79% and the positive likelihood ratio of the Holter ECG of 1.59 in the likelihood table T4 shown in FIG. 11 based on the analysis results (step S21).

[0094] Next, the diagnosis support device 40 outputs the calculated PTP·CL of 86% (step S23). FIG. 16 is an example of the output of the output interface 42 in the diagnosis support device 40 according to this embodiment, and is a diagram corresponding to the above-mentioned FIG. 8. As shown in FIG. 16, the diagnosis support device 40 displays the calculated PTP·CL of 86% on the display which is the output interface 42. Also, similar to the case of FIG. 8, the diagnosis support device 40 displays a button for allowing the doctor to decide whether or not to perform a non-invasive test.

[0095] Then, the diagnosis support device 40 determines whether or not a non-invasive test is to be performed based on the input operation by the doctor (step S25), and determines that a non-invasive test is not to be performed based on the input operation by the doctor (step S25: NO). Therefore, the diagnosis support device 40 ends the diagnostic support for the virtual patient. After that, the doctor decides, for example, to perform an invasive test on the virtual patient.

[0096] As described above, according to the diagnosis support system 1 of this embodiment, the diagnosis support device 40 acquires medical data including at least patient information and medical information, analyzes the medical information included in the acquired medical data, calculates the PTP (pre-test probability), which is the probability that the patient has coronary artery disease, based on the basic patient information included in the acquired medical data and the analysis results of the medical information, and suggests tests to be performed on the patient based on the medical data and / or the test results.Therefore, while assisting in the calculation of the PTP probability, tests for improving the accuracy of diagnosis of stable CAD can be easily selected, thereby improving diagnostic efficiency.

[0097] Furthermore, according to the diagnosis support system 1 of this embodiment, the diagnosis support device 40 acquires test results and calculates PTP·CL, which is the probability of PTP taking CL into account, based on the acquired test results, so that it is possible to assist in the calculation of the PTP·CL probability and improve diagnostic efficiency.

[0098] The term "processor" used in the above description means a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). The processor realizes its function by reading and executing a program stored in the memory 41. Instead of storing a program in the memory 41, the processor may be configured to directly incorporate the program in its circuit. In this case, the processor realizes its function by reading and executing the program incorporated in its circuit. The processor is not limited to being configured as a single processor circuit, and may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, the multiple components in FIG. 1 may be integrated into a single processor to realize its function.

[0099] Although several embodiments have been described above, these embodiments are presented only as examples and are not intended to limit the scope of the invention. The novel device and method described in this specification can be implemented in various other forms. In addition, various omissions, substitutions, and modifications can be made to the forms of the device and method described in this specification without departing from the spirit of the invention. The appended claims and their equivalents are intended to include such forms and modifications that fall within the scope and spirit of the invention. [Explanation of symbols]

[0100] 1...diagnosis support system, 10...hospital information system, 11...electronic medical record system, 12...examination department information management system, 13...radiology department information management system, 14...medical image storage system, 15...dose management system, 16...medical accounting system, 20...examination device, 30...medical image diagnostic device, 40...diagnosis support device, 41...memory, 42...output interface, 43...input interface, 44...communication interface, 45...processing circuit

Claims

1. An acquisition unit that acquires medical data including at least patient information related to a patient and medical information related to a medical treatment of the patient; An analysis unit that analyzes the medical information included in the acquired medical data; a first calculation unit that calculates a first probability, which is a probability of having coronary artery disease, based on patient information included in the acquired medical data and an analysis result by the analysis unit; A suggestion unit that suggests an examination to be performed on the patient based on the medical data; A diagnostic support device comprising:

2. 2. The diagnostic support device according to claim 1, further comprising a second calculation unit that calculates, based on the first probability calculated by the first calculation unit and a test result that is a result of a test performed on the patient, a second probability that the patient is affected by coronary artery disease taking into account the test result.

3. 3 . The diagnosis support device according to claim 2 , wherein the second calculation unit re-calculates the second probability based on the second probability and a test result of the test performed on the patient after calculation of the second probability. 4 .

4. The diagnosis support device according to claim 2 , wherein the suggestion unit is configured to suggest unperformed tests among the tests based on the medical data and / or the test results.

5. The diagnosis support device according to claim 4 , wherein the suggestion unit preferentially suggests, from among the unperformed tests, tests that can be performed at the hospital, based on hospital facility information relating to facilities of the hospital.

6. The diagnosis support device according to claim 4 , wherein the suggestion unit preferentially suggests, from among the unperformed tests, tests that impose a small burden on the patient, based on invasiveness information regarding the invasiveness of the test.

7. The diagnosis support device according to claim 4 , wherein the suggestion unit preferentially suggests, among the unperformed examinations, an examination that has a short time until the examination is performed, based on examination reservation information relating to a reservation status of the examination.

8. The diagnosis support device according to claim 4 , wherein the suggestion unit preferentially suggests, among the unperformed tests, tests that require less cost, based on cost information relating to costs of the tests.

9. The diagnosis support device according to claim 4 , wherein the suggestion unit preferentially suggests, among the unperformed tests, a test having high sensitivity and / or specificity based on sensitivity and / or specificity of the test.

10. The diagnosis support device according to claim 1 , wherein the analysis unit analyzes the medical information so as to extract a characteristic of a chest symptom of the patient or a symptom of respiratory distress of the patient from the medical information.

11. The diagnosis support device according to claim 2 , wherein the analysis unit analyzes the test results so as to extract factors that affect the first probability and the second probability from the test results.

12. a hospital information system that transmits medical data including at least patient information about a patient and medical information about a medical treatment of the patient; an acquisition unit that acquires the medical data from the hospital information system; An analysis unit that analyzes the medical information included in the acquired medical data; a first calculation unit that calculates a first probability, which is a probability of having coronary artery disease, based on patient information included in the acquired medical data and an analysis result by the analysis unit; a suggestion unit that suggests an examination to be performed on the patient based on the medical data; A diagnostic support system comprising:

13. obtaining clinical data including at least patient information relating to a patient and clinical information relating to a medical treatment of said patient; A step of analyzing the medical information included in the acquired medical data; calculating a first probability, which is a probability of having coronary artery disease, based on patient information and analysis results included in the acquired medical data; Suggesting a test to be performed on the patient based on the medical data; A program for causing a diagnostic support device to execute the above.

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