Medical information processing equipment

Abstract

To provide a medical information processing apparatus that can efficiently refer to necessary medical examination information.SOLUTION: In a medical information processing apparatus 100 allowing efficient reference to necessary medical examination information, a processing circuit 150 comprises an extraction function 153, a selection function 155, and a display control function 151. The extraction function 153 extracts, from first medial examination data indicating text data included in medical examination information indicating various types of data used for medical examination, character strings having a clinical meaning as topics indicating a view point for referring to the medical examination information. The selection function 155 selects, from the topics extracted by an extraction unit, one topic according to a user's input. The display control function 151 performs control of displaying, on a display, data related to the one topic elected by a selection unit, of second medical examination data including one or more pieces of data representing the state of a target analyte included in the medical examination information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The embodiments disclosed in this specification relate to a medical information processing device. [Background technology]

[0002] In recent years, various types of medical information are used in the medical field, such as specimen test data, medical image data, and electronic medical record data. Doctors will diagnose and treat subjects (e.g., patients) by comprehensively examining this information. Therefore, for example, in order to improve the efficiency of diagnosis, a technology has been proposed that displays various types of medical data required by doctors when making diagnoses on a single screen together with information to support the diagnosis.

[0003] However, when the perspective from which medical information is referred to changes (for example, when a doctor thinks, "Now that a diagnosis has been made, let's consider a treatment plan," etc.), the doctor must recollect the necessary medical information depending on the perspective from which the doctor refers to the medical information. This can lead to inefficient referencing of medical information, and can result in important medical information being overlooked. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-222478 A Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems that the embodiments disclosed in this specification are intended to solve is to enable efficient reference to necessary medical information. However, the problems solved by the embodiments disclosed in this specification are not limited to the above problems. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be considered as other problems solved by the embodiments disclosed in this specification. [Means for solving the problem]

[0006] The medical information processing device according to the first embodiment includes an extraction unit, a selection unit, and a display control unit. The extraction unit extracts a character string having a clinical meaning from first medical data indicating text data included in medical information indicating various data used in medical treatment, as a topic indicating a viewpoint for referring to the medical information. The selection unit selects one topic from the topics extracted by the extraction unit in response to a user's input. The display control unit controls displaying, on a display device, data related to the one topic selected by the selection unit from second medical data including one or more data indicating a condition of a target subject included in the medical information. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a medical image processing apparatus according to the first embodiment. [Diagram 2] FIG. 2 is a conceptual diagram showing an example of topic extraction processing according to the first embodiment. [Diagram 3] FIG. 3 is a diagram showing an example of a related topic display screen according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a process for determining medical data related to a selected topic according to the first embodiment. [Diagram 5] FIG. 5 is an image diagram showing an example of medical data classification and medical data display according to the first embodiment. [Figure 6] FIG. 6 is a diagram showing an example of a data display screen according to the first embodiment. [Figure 7] FIG. 7 is a diagram showing an example of a data display screen according to the first embodiment. [Figure 8] FIG. 8 is a conceptual diagram showing an example of the topic search process according to the first embodiment. [Figure 9] FIG. 9 is a flowchart showing an example of processing executed by the medical image processing apparatus according to the first embodiment. [Figure 10]FIG. 10 is a block diagram showing an example of the configuration of a medical image processing apparatus according to the second embodiment. [Figure 11] FIG. 11 is a conceptual diagram showing an example of the process of aggregating synonymous topics according to the second embodiment. [Figure 12] FIG. 12 is a flowchart showing an example of processing executed by the medical image processing apparatus according to the second embodiment. [Figure 13] FIG. 13 is a block diagram showing an example of the configuration of a medical image processing apparatus according to the third embodiment. [Figure 14] FIG. 14 is a conceptual diagram showing an example of the related topic aggregation process according to the third embodiment. [Figure 15] FIG. 15 is a conceptual diagram showing an example of a process for generating a related topic group according to the third embodiment. [Figure 16] FIG. 16 is an image diagram showing an example of a related topic display screen according to the third embodiment. [Figure 17] FIG. 17 is an image diagram showing an example of a related topic display screen according to the third embodiment. [Figure 18] FIG. 18 is a flowchart showing an example of processing executed by the medical image processing apparatus according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, an embodiment of a medical image processing apparatus will be described in detail with reference to the drawings.

[0009] (First embodiment) Fig. 1 is a diagram showing an example of the configuration of a medical information processing device according to the first embodiment. For example, as shown in Fig. 1, a medical information processing device 100 according to this embodiment is communicably connected to a specimen testing system 300, a radiology department system 400, an electronic medical record system 500, and the like via a network 200. For example, the medical information processing device 100 and each system are installed in a hospital or the like, and are mutually connected by the network 200 such as an in-hospital LAN.

[0010] The specimen testing system 300 generates clinical data related to specimen testing performed on a subject and stores the data in a memory circuit within the system. In response to a request from the medical information processing device 100, the specimen testing system 300 transmits the clinical data stored in the memory circuit to the medical information processing device 100.

[0011] The radiology department system 400 generates medical data related to vital signs and imaging tests performed on a subject, and stores the data in a storage circuit within the system. For example, the radiology department system 400 includes a PACS (Picture Archiving and Communication System) or the like.

[0012] In addition, imaging tests include tests using CT images taken by an X-ray CT (Computed Tomography) device, tests using MR images taken by an MRI (Magnetic Resonance Imaging) device, tests using ultrasound images taken by an ultrasound diagnostic device, and tests using X-ray images taken by an X-ray diagnostic device.

[0013] In response to a request from the medical information processing device 100, the radiology department system 400 transmits the medical data stored in the memory circuitry to the medical information processing device 100.

[0014] The electronic medical record system 500 generates medical data related to prescriptions and nursing records administered to subjects and stores the data in a memory circuit within the system. In response to a request from the medical information processing device 100, the electronic medical record system 500 transmits the medical data stored in the memory circuit to the medical information processing device 100.

[0015] The medical information processing device 100 acquires various medical data from the specimen testing system 300, the radiology department system 400, and the electronic medical record system 500 via the network 200, and performs various information processing using the acquired medical data. For example, the medical information processing device 100 is realized by a computer device such as a workstation, a personal computer, or a tablet terminal.

[0016] Specifically, the medical information processing device 100 includes a NW (network) interface 110, a memory circuitry 120, an input interface 130, a display 140, and a processing circuitry 150.

[0017] The NW interface 110 is connected to the processing circuitry 150, and controls the transmission and communication of various data between the medical information processing device 100 and each system. Specifically, the NW interface 110 receives medical data from each system, and outputs the received medical data to the processing circuitry 150. For example, the NW interface 110 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

[0018] The memory circuitry 120 is connected to the processing circuitry 150 and stores various data. Specifically, the memory circuitry 120 stores medical data received from each system. For example, the memory circuitry 120 is realized by a semiconductor memory element such as a random access memory (RAM) or a flash memory, a hard disk, an optical disk, or the like.

[0019] The input interface 130 is connected to the processing circuitry 150 and receives input operations of various instructions and various information from an operator. Specifically, the input interface 130 converts the input operations received from the operator into electrical signals and outputs the electrical signals to the processing circuitry 150.

[0020] For example, the input interface 130 is realized by a trackball, a switch button, a mouse, a keyboard, a touchpad that performs input operations by touching the operation surface, a touch screen in which a display screen and a touchpad are integrated, a non-contact input circuit using an optical sensor, a voice input circuit, etc. In this specification, the input interface 130 is not limited to only those that have physical operation parts such as a mouse and a keyboard.

[0021] For example, an example of the input interface 130 includes an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs this electrical signal to a control circuit.

[0022] The display 140 is connected to the processing circuit 150 and displays various information and images. Specifically, the display 140 converts data of various information and images sent from the processing circuit 150 into an electric signal for display and outputs it. For example, the display 140 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, or the like. The display 140 is an example of a display device.

[0023] The processing circuitry 150 controls the components of the medical information processing device 100 in response to an input operation received from an operator via the input interface 130. Specifically, the processing circuitry 150 stores medical data output from the NW interface 110 in the storage circuitry 120. The processing circuitry 150 also reads out the medical data from the storage circuitry 120 and displays it on the display 140. For example, the processing circuitry 150 is realized by a processor.

[0024] The above describes the overall configuration of the medical information processing device 100 according to this embodiment. With this configuration, the medical information processing device 100 according to this embodiment is configured to allow an operator such as a doctor to efficiently refer to necessary medical information.

[0025] Specifically, in this embodiment, the memory circuitry 120 stores an integrated medical DB (Data Base) including various medical data acquired from the specimen testing system 300, the radiology department system 400, and the electronic medical record system 500. Here, the medical data stored in the integrated medical DB includes information such as numerical values ​​(measurements), images, and medical records, and information indicating the recording date and time of these.

[0026] For example, the integrated medical DB includes specimen test data, vital sign data, medical image data, prescription data, nursing record data, etc. The specimen test data is medical data related to specimen testing obtained from the specimen testing system 300. The vital sign data is medical data related to vital signs obtained from the radiology department system 400. The medical image data is medical data related to imaging tests obtained from the radiology department system 400.

[0027] The prescription data is medical data related to the prescription obtained from the electronic medical record system 500. The nursing record data is medical data related to the nursing record obtained from the electronic medical record system 500.

[0028] The medical data stored in the integrated medical database may be the data acquired from each of the specimen testing system 300, the radiology department system 400, and the electronic medical record system 500, or it may be an integrated version of the data acquired from each system, or it may be information created for the purpose of secondary use.

[0029] The memory circuitry 120 also stores display information indicating the screen size of the display 140. The memory circuitry 120 also stores classification information indicating classification of sample test data, vital sign data, medical image data, prescription data, nursing record data, etc. The memory circuitry 120 also stores item number information indicating the maximum number of medical data (items) that can be displayed for each screen size.

[0030] In this embodiment, the processing circuit 150 has a display control function 151, a setting function 152, an extraction function 153, a first calculation function 154, a selection function 155, a second calculation function 156, a decision function 157, and a search function 158.

[0031] The display control function 151 is an example of a display control unit. The extraction function 153 is an example of an extraction unit. The first calculation function 154 is an example of a first calculation unit. The selection function 155 is an example of a selection unit. The second calculation function 156 is an example of a second calculation unit. The decision function 157 is an example of a decision unit. The search function 158 is an example of a search unit.

[0032] A display control function 151 controls the display of various information on the display 140. Details of the display process will be explained below together with the explanation of each function.

[0033] The setting function 152 sets extraction conditions indicating conditions for extracting character strings having clinical meaning according to the purpose of referring to the medical information. The setting function 152 sets the character string input by the user as the extraction condition.

[0034] For example, if "tetralogy of Fallot" is a disease related to a patient to be treated, and the user (doctor) wants to refer to information related to "tetralogy of Fallot," the user inputs "tetralogy of Fallot" as an extraction condition. In this case, the setting function 152 sets "tetralogy of Fallot" as an extraction condition.

[0035] In this example, the disease name is used as the extraction condition, but the extraction condition may be a patient ID for identifying a patient, a doctor ID for identifying a doctor in charge of the medical treatment, a department name indicating a medical department, etc. A combination of these may also be used as the extraction condition. The setting function 152 may also specify a doctor in charge, a department, etc. from a user ID for identifying a user of the medical information processing device 100, and automatically set them as the extraction conditions.

[0036] The extraction function 153 extracts character strings having clinical meaning from the first medical data indicating text data included in the medical information indicating various data used in medical treatment, as topics indicating a viewpoint for referring to the medical information.

[0037] Examples of the first medical data include text data included in medical data (an example of medical information) such as sample test data, vital data, prescription data, nursing record data, etc. Other examples of the first medical data include metadata (such as DICOM (Digital Imaging and Communications in Medicine) tags) that indicate attributes of medical image data (an example of medical information).

[0038] Specifically, the extraction function 153 extracts character strings having clinical meaning as topics from the first medical data in accordance with extraction conditions indicating conditions for extracting character strings having clinical meaning according to the purpose of referring to the medical information.

[0039] More specifically, the extraction function 153 extracts character strings having clinical meaning from the first medical data by using known natural language processing techniques (such as named entity extraction) using language resources such as dictionaries, corpora, and ontologies in accordance with the extraction conditions set by the setting function 152.

[0040] In addition, when the extraction condition is set as a character string indicating a disease name or the like, the extraction function 153 also extracts character strings related to synonyms, similar words, and abbreviations of the character string indicating the disease name or the like as topics.

[0041] Hereinafter, topic extraction will be described with reference to Fig. 2. Fig. 2 is a conceptual diagram showing an example of topic extraction processing.

[0042] In this example, a case will be described in which "tetralogy of Fallot" is one of the one or more diseases D related to a target patient P, and a doctor inputs "tetralogy of Fallot" as a topic extraction condition. In this case, first, the setting function 152 sets "tetralogy of Fallot" as an extraction condition C.

[0043] The extraction function 153 refers to the integrated medical DB and uses existing natural language processing technology to extract character strings W having clinical meanings such as edema, chest pain, shortness of breath, etc., related to "Tetralogy of Fallot," "Tetralogy of Fallot," a synonym of "Tetralogy of Fallot," and the abbreviation "TOF" of "Tetralogy of Fallot," as topics from text data included in medical data such as specimen test data.

[0044] Returning to Fig. 1, the explanation will be continued. The first calculation function 154 calculates the importance indicating the degree of importance of a topic. Specifically, the first calculation function 154 calculates the importance for each topic extracted by the extraction function 153 based on the occurrence probability and reference probability of the topic.

[0045] The importance calculation process will be described below. In this example, the calculation of the importance of the topic "edema" will be described. In this case, first, the first calculation function 154 calculates the appearance probability of "edema". For example, the first calculation function 154 calculates the appearance probability of "edema" from the ratio of the total number (total number) of "edema" extracted by the extraction function 153 to the total number (total number) of topics extracted by the extraction function 153.

[0046] In addition, from the perspective of the probability that the topic “edema” appears for the target patient, the first calculation function 154 may calculate the occurrence probability of “edema” from the ratio of the total number of “edema” extracted by the extraction function 153 from the first medical data of the target patient to the total number of “edema” extracted by the extraction function 153.

[0047] Also, from the viewpoint of the probability of the topic "edema" appearing in a certain period, the first calculation function 154 may calculate the appearance probability of "edema" from the ratio of the total number of "edema" extracted by the extraction function 153 in a certain period (e.g., the most recent month) to the total number of "edema" extracted by the extraction function 153. Furthermore, depending on the situation, the above-mentioned multiple calculation methods may be used separately, or multiple calculation methods may be combined.

[0048] Next, the first calculation function 154 calculates the reference probability of “edema”. For example, the first calculation function 154 calculates the reference probability of “edema” from the ratio of the total number of references (total number) of “edema” by the user to the total number of references (total number) of the topic by the user.

[0049] In addition, from the perspective of the probability that the topic "edema" is referenced by the user in the medical treatment of the target patient, the first calculation function 154 may calculate the reference probability of "edema" from the ratio of the total number of references to "edema" in the medical treatment of the target patient to the total number of references to "edema" by users.

[0050] In addition, from the viewpoint of the probability of the topic "edema" being referenced in a certain period, the first calculation function 154 may calculate the reference probability of "edema" from the ratio of the total number of references to "edema" by users in a certain period (e.g., the most recent month) to the total number of references to "edema". Furthermore, depending on the situation, the above-mentioned multiple calculation methods may be used separately, or multiple calculation methods may be combined.

[0051] Then, the first calculation function 154 calculates the importance of "edema" from the sum of the occurrence probability of "edema" and the reference probability of "edema." Note that weighting may be performed on either the occurrence probability or the reference probability depending on which of them is considered more important.

[0052] Thereafter, the display control function 151 performs control to rearrange the topics and display them on the display 140 according to the importance of the topics calculated by the first calculation function 154.

[0053] Hereinafter, the topic display process will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of a topic display screen.

[0054] When a topic is extracted by the extraction function 153, the display control function 151 displays the patient data PD, a topic display panel TD, a topic log panel TL, and a medical data list L on the data display screen DD displayed on the display 140, as shown in FIG.

[0055] The patient data field PD is a display field showing basic information about the target patient, such as the name of the target patient. In this example, the display control function 151 displays basic information about "Name: XX XX" identified by "Patient ID: P001" in the patient data field PD.

[0056] The topic panel TD is a display area for items related to topics. The display control function 151 displays a search box SC, a search button SB, a topic display area TE, and a cursor CS on the topic panel TD. The search box SC, the search button SB, and the cursor CS will be described later.

[0057] In this example, the display control function 151 displays the topics T, “edema,” “shortness of breath,” “surgery,” “convulsions,” and “heart failure,” in the topic display area TE in order of importance calculated by the first calculation function 154.

[0058] The topic log panel TL is a display area for displaying a topic history showing topics that have been referenced in the past (past topics). The topic log panel TL will be described later. The medical data list L is a list of the medical data of the target patient (in the example of FIG. 3, the patient identified by "Patient ID: P001"). The user can display any medical data on the data display screen DD by selecting and clicking an icon in the medical data list L.

[0059] Continuing the explanation, returning to Fig. 1, the selection function 155 selects one topic from the topics extracted by the extraction function 153 in response to a user input.

[0060] Specifically, the selection function 155 selects a topic T displayed in the topic display area TE in accordance with a user operation. In the example of Fig. 7, when the user places the cursor CS on "Surgery", which is one of the topics T, and left-clicks with the mouse, the selection function 155 selects "Topic: Surgery". Also, for example, when the user left-clicks with the mouse on a past topic displayed in the topic log panel TL, the selection function 155 selects the past topic.

[0061] The second calculation function 156 calculates a degree of association indicating the degree of relationship between a plurality of topics. Specifically, the second calculation function 156 calculates a degree of association between the topic selected by the selection function 155 and another topic.

[0062] More specifically, the second calculation function 156 analyzes the associations between the topics extracted by the extraction function 153 using known analysis methods such as association analysis, co-occurrence networks, causal inference (IPTW method, DR method), causal discovery (LinGAM, Bayesian network), knowledge graph, principal component analysis (PCA), topic model (LDA), latent semantic analysis (LSA), and distributed representations (Word2Vec), and calculates the degree of association between the topics based on the analysis results.

[0063] When the selection function 155 selects one topic, the display control function 151 displays topics (hereinafter also referred to as related topics) whose relevance to the selected topic exceeds a threshold value, below the selected topic, in descending order of relevance.

[0064] The determination function 157 determines a display layout for displaying data related to one topic selected by the selection function 155 from the second medical data including one or more data representing the condition of the target subject contained in the medical information.

[0065] Specifically, first, the determination function 157 cooperates with the second calculation function 156 to use a publicly known analysis method similar to that used for calculating the relevance between topics to calculate the relevance between the topic selected by the selection function 155 (selected topic) and text data contained in specimen test data, vital data, prescription data, nursing record data, etc., or metadata indicating attributes of medical image data.

[0066] Then, the decision function 157 decides that medical data (examples of second medical data) such as specimen test data, vital data, medical image data, prescription data, and nursing record data, which contain text data (or metadata) whose relevance to the selected topic exceeds a threshold value, are display candidates to be displayed on the data display screen DD.

[0067] Next, the determination function 157 refers to the display information stored in the memory circuitry 120 and checks the screen size of the display 140 on which the data display screen DD is to be displayed. The determination function 157 also checks the classification information of each medical data item determined as a display candidate. Then, the determination function 157 determines the display size and display position of the medical data item based on the relevance to the selected topic, the classification information of the medical data item, and the screen size of the display 140.

[0068] The process of determining the display layout and displaying medical data will be described below with reference to Fig. 4 to Fig. 7. Fig. 4 is an image diagram showing an example of the process of calculating the degree of association between a topic and medical data.

[0069] In this example, we will explain the case where the user places the cursor CS on "Topic: Surgery" in Figure 3 and left-clicks the mouse. In this case, the selection function 155 selects "Topic: Surgery". Next, the decision function 157 calculates the degree of association between "Topic: Surgery" and the medical data, such as specimen test data, of the target patient identified by the patient ID "P001".

[0070] For example, the decision function 157 cooperates with the second calculation function 156 to calculate the degree of association between "topic: surgery" T and the character string "Na" included in "specimen testing data: Na" MD1. This numerical value becomes the degree of association between "topic: surgery" T and "specimen testing data: Na" MD1. If the degree of association between "topic: surgery" T and "specimen testing data: Na" MD1 exceeds a threshold, the decision function 157 sets "specimen testing data: Na" MD1 as a display candidate.

[0071] The decision function 157 performs similar processing for "Specimen test data: NTproBNP" MD2, "Prescription data: Lasix" MD3, "Vital data: SpO2" MD4, "Nursing record data: 20XX-05-20" MD5, "Medical image data: US" MD6, and "Medical image data: CR" MD7.

[0072] Next, the determination function 157 refers to the classification information stored in the memory circuitry 120 and confirms the classification information for each of the medical data items that are candidates for display.

[0073] Here, Fig. 5 is an image diagram showing an example of classification of medical data and display of medical data. In this example, a case will be described in which the medical data are "specimen test data: Na" MD1, "specimen test data: NTproBNP" MD2, "prescription data: Lasix" MD3, "vital data: SpO2" MD4, "nursing record data: 20XX-05-20" MD5, "medical image data: US" MD6, and "medical image data: CR" MD7.

[0074] For example, the decision function 157 refers to the classification information and confirms that the "specimen test data: Na" MD1 and the "specimen test data: NTproBNP" MD2 belong to the "classification: specimen test" C1. Similarly, the decision function 157 confirms that the "prescription data: Lasix" MD3 belongs to the "classification: medication" C2.

[0075] Similarly, the decision function 157 confirms that "Vital Data: SpO2" MD4 belongs to the category "Category: Vitals" C3. Similarly, the decision function 157 confirms that "Nursing Record Data: 20XX-05-20" MD5 belongs to the category "Category: Chart Description" C4. Similarly, the decision function 157 confirms that "Medical Image Data: US" MD6 and "Medical Image Data: CR" MD7 belong to the category "Category: Imaging Test" C5.

[0076] Then, the decision function 157 decides the display layout of each medical data so that the medical data of "Classification: Specimen Test" C1 is displayed in the "Specimen Test Panel" SP, the medical data of "Classification: Medication" C2 is displayed in the "Medication Panel" MP, the medical data of "Classification: Vitals" C3 is displayed in the "Vitals Panel" BP, the medical data of "Classification: Medical Chart Recording" C4 is displayed in the "Medical Chart Recording Panel" KP, and the medical data of "Classification: Imaging Test" C5 is displayed in the "Imaging Test Panel" IP.

[0077] The display size of each panel, the arrangement of each panel, the display size of each piece of medical data, and the arrangement of each piece of medical data are determined by the determination function 157 based on the relevance between the topic and the medical data and the screen size of the display 140. Here, the determination of the layout of the data display screen by the determination function 157 will be described in detail.

[0078] When the medical data to be displayed is determined, the determination function 157 refers to the display information and the item number information stored in the memory circuit 120, checks how many medical data (items) can be displayed at most on the display 140 used for display, and determines the display items to be displayed on the data display screen. When the number of medical data to be displayed as candidates is within the number of medical data that can be displayed, the determination function 157 sets all the medical data selected as display candidates as display items.

[0079] On the other hand, if the number of medical data candidates for display exceeds the number of medical data that can be displayed, the decision function 157 arranges the medical data candidates for display in order of their relevance to the selected topic, and sets the medical data up to the "maximum number of medical data that can be displayed" as display items.

[0080] In this way, by defining the "maximum number of medical data that can be displayed" for each screen size of the display device, it is possible to prevent a situation in which the display size of each medical data becomes small because there is too much medical data related to the selected topic, making it difficult for the user to understand the contents of the medical data.

[0081] In this embodiment, the maximum number of medical data items that can be displayed on the data display screen is determined according to the screen size, but the number of medical data items to be displayed on the data display screen may be manually set by the user.

[0082] When the display items are determined, the determination function 157 determines the layout and size of the data display panel (such as a "specimen test panel") based on the number of medical data for each category and the relevance to the selected topic. For example, the determination function 157 increases the size of the data display panel as the number of medical data for each category increases.

[0083] Also, for example, the decision function 157 increases the size of the data display panel for a classification to which medical data with a high relevance to the selected topic belongs. Furthermore, the decision function 157 calculates, for example, an average value of the relevance between the selected topic and medical data for each classification, and arranges the data display panels from the left in descending order of the average relevance.

[0084] In this way, by changing the layout and display size of each piece of medical data depending on factors such as the degree of relevance between the selected topic and the medical data, important information becomes easier to see, enabling users to refer to medical information efficiently.

[0085] When the layout of the data display panel is determined, the determination function 157 determines the layout and size of each piece of medical data. For example, the more relevant the medical data is to the selected topic, the larger the display size of the medical data is. Also, for example, the determination function 157 arranges the medical data so that the more relevant the medical data is to the selected topic, the higher it is displayed in the data display panel.

[0086] The display layout determination process and the medical care data display process will be specifically described below with reference to Figures 6 and 7. Figures 6 and 7 are diagrams showing an example of a data display screen.

[0087] For example, in the example of FIG. 5, when the selection function 155 selects "Topic: Surgery", the display control function 151 first displays the selected topic ST (in this example, "Topic: Surgery") at the top of the topic display area TE.

[0088] In addition, the display control function 151 displays topics whose relevance to "topic: surgery" exceeds a threshold value as related topics SR of the selected topic ST (in this example, "topic: Rastelli surgery," "topic: heart failure," and "topic: catheter") below the selected topic ST.

[0089] As a result, when a user wants to refer to a topic that is displayed as a related topic SR of the selected topic ST, the user does not have to collect the medical data themselves, and can refer to the necessary medical information efficiently. In addition, by automatically displaying the related topic SR of the selected topic ST, the user can be informed that another perspective exists, which can reduce the probability of overlooking important medical data.

[0090] Next, the determination function 157 cooperates with the second calculation function 156 to calculate the degree of association between "Topic: Surgery" and each medical data, and determines the medical data whose degree of association is equal to or greater than a threshold as display candidates. In this example, the determination function 157 determines two items of medical data in "Classification: Imaging Examination" and two items of medical data in "Classification: Report" (a total of four items) as display candidates.

[0091] Next, the determination function 157 refers to the display information and the item number information stored in the memory circuitry 120, and checks the screen size of the display 140 and the maximum number of medical data that can be displayed. For example, if the maximum number of medical data that can be displayed is "10", there are four display candidates, so the determination function 157 determines all display candidates as display items.

[0092] Next, the decision function 157 decides the placement and placement size of the "Imaging Examination Panel" IP and the "Report Panel" RP based on the degree of relevance between "Topic: Surgery" and each medical data, the number of medical data in "Category: Imaging Examination", and the number of medical data in "Category: Report".

[0093] The determination function 157 also determines the layout and display size of each piece of medical image data in the "Image Examination Panel" IP based on the degree of association between the "Topic: Surgery" and each piece of medical image data. Furthermore, the determination function 157 determines the layout and display size of each piece of report data in the "Report Panel" RP based on the degree of association between the "Topic: Surgery" and each piece of report data.

[0094] When the decision function 157 decides the layout of the data display screen, the display control function 151 performs control to display the data display screen DD on the display 140 in accordance with the layout decided by the decision function 157 .

[0095] For example, as shown in FIG. 6, the display control function 151 displays patient data PD, a topic display panel TD, a topic log panel TL, a medical data list L, an “imaging examination panel” IP, and a “report panel” RP on a data display screen DD displayed on the display 140.

[0096] The patient data PD, topic display panel TD, and medical data list L are as described above, so their explanation will be omitted. The “imaging examination panel” IP is a panel for displaying medical data classified as “classification: imaging examination”.

[0097] The "report panel" RP is a panel for displaying medical data classified under "classification: report." The left side of the panel shows a list of reports, and the user can select any one of the reports. The right side of the panel is an enlarged display area, and the display control function 151 enlarges and displays one report that the user selects from the list of reports on the right side.

[0098] Here, when the user places the cursor CS on another topic displayed on the topic display panel TD and left-clicks the mouse, the selection function 155 selects that topic, the decision function 157 decides the layout again, and the display control function 151 displays the data display screen DD in accordance with the screen layout redetermined by the decision function 157.

[0099] For example, when the selection function 155 selects "Topic: Heart Failure", which is one of the topics T, the display control function 151 displays medical data related to "Topic: Heart Failure" on the data display screen DD in accordance with the screen layout determined by the determination function 157, as shown in FIG. 7.

[0100] In the example of Figure 7, the display control function 151 displays medical data belonging to "Category: Specimen Testing" on a "Specimen Testing Panel" SP, medical data belonging to "Category: Imaging Testing" on an "Imaging Testing Panel" IP, medical data belonging to "Category: Vitals" on a "Vitals Panel" BP, and medical data belonging to "Category: Medical Chart Recording" on a "Medical Chart Recording Panel" KP, in accordance with the screen layout determined by the determination function 157.

[0101] In addition, the display control function 151 not only switches the display of medical data to that related to the selected topic, but also controls changing the display of the topic log panel TL.

[0102] For example, before referring to the current selected topic ST, the display control function 151 displays the past topic (in the example of FIG. 7, "Topic: Surgery") that it referred to previously in the topic log panel TL. Then, the display control function 151 displays in the topic log panel TL a selection button LB for selecting the past topic and a reduced display PV of the data display screen that is displayed when the past topic is selected.

[0103] Note that in this example, the display control function 151 displays only one past topic, but if there are multiple topics that were referred to in the past, multiple past topics may be displayed. In this way, by displaying the past topics so that they can be selected, the user can efficiently refer to the medical information when they want to return to the original display to check the information.

[0104] Returning to FIG. 1 and continuing the explanation. The search function 158 searches for topics among the topics extracted by the extraction function 153 that at least partially match the character string specified by the user. Also, the search function 158 searches for topics among the topics extracted by the extraction function 153 that are synonyms or similar in meaning to the character string specified by the user.

[0105] Here, the topic search process will be described with reference to FIG. 8. FIG. 8 is an image diagram showing an example of the topic search process.

[0106] In this example, the case where the user enters "heart" in the search box SC using a keyboard or the like and presses the search start button SB will be described. In this case, the search function 158 searches for topics among the topics extracted by the extraction function 153 that contain "heart". Also, the search function 158 searches for topics that contain "Heart", which is a synonym for "heart".

[0107] The display control function 151 displays in the topic display area TE the topics RE found in the search, "topic: heart failure" and "topic: echocardiogram," in order of importance calculated by the first calculation function 154. The user can select a topic by placing the cursor CS on a topic RE found in the search and left-clicking the mouse.

[0108] Providing the search function 158 in this manner allows the user to efficiently find a topic that he or she wishes to refer to when the number of topics extracted by the extraction function 153 is too large.

[0109] Next, a description will be given of processing executed by the medical information processing apparatus 100 according to this embodiment. Fig. 9 is a flowchart showing an example of processing executed by the medical information processing apparatus 100 according to the first embodiment.

[0110] First, the setting function 152 sets topic extraction conditions according to a user's instruction (step S1).

[0111] Next, the extraction function 153 extracts character strings having clinical meaning as topics from the text data included in the medical data in accordance with the topic extraction conditions set by the setting function 152 (step S2).

[0112] Next, first calculation function 154 calculates the importance of the topic extracted by extraction function 153 (step S3).

[0113] Next, the display control function 151 performs control to display the topics extracted by the extraction function 153 on the display 140 in the order of decreasing importance calculated by the first calculation function 154 (step S4).

[0114] Next, the selection function 155 selects one topic from among the topics extracted by the extraction function 153 in response to the user's input (step S5).

[0115] Next, the second calculation function 156 calculates the degree of association between the topic selected by the selection function 155 (selected topic) and other topics (step S6).

[0116] Next, the display control function 151 performs control to display the topics whose relevance to the selected topic exceeds a threshold value, as calculated by the second calculation function 156, as related topics below the selected topic (step S7).

[0117] Next, the determination function 157 cooperates with the second calculation function 156 to calculate the degree of association between the selected topic and the medical data of the target patient (step S8).

[0118] Next, the determination function 157 refers to the display information stored in the memory circuitry 120 and checks the screen size of the display 140. Then, the determination function 157 determines the layout of the data display screen (the arrangement and display size of the medical data, etc.) based on the screen size of the display 140 and the relevance to the selected topic (step S9).

[0119] Next, the display control function 151 displays the medical data related to the selected topic on the data display screen in accordance with the decision made by the decision function 157 (step S10).

[0120] Next, the selection function 155 checks whether or not a selection input of a topic other than the currently selected topic has been received from the user (step S11). If a selection input of a different topic has been received (step S11: Yes), the selection function 155 selects the different topic selected by the user and proceeds to the process of step S6. On the other hand, if a selection input of a different topic has not been received (step S11: No), this process ends.

[0121] The medical information processing device 100 according to the first embodiment described above includes an extraction function 153 that extracts character strings having clinical meaning from first medical data indicating text data included in medical information indicating various data used in medical treatment, as topics indicating a viewpoint for referring to the medical information, a selection function 155 that selects one topic from the topics extracted by the extraction function 153, and a display control function 151 that controls the display of data related to the one topic selected by the selection function 155 on a display device from second medical data including one or more data indicating the condition of the target subject included in the medical information.

[0122] As a result, character strings having clinical meaning are automatically extracted as topics, and the user can simply select a topic to check medical information related to that topic on the screen. If there is a topic that matches the purpose of the medical information reference, the user does not need to collect medical information according to the purpose of the reference. Therefore, according to the medical information processing device 100 of this embodiment, the user can efficiently refer to the necessary medical information.

[0123] Furthermore, if users can efficiently refer to necessary medical information, it is believed that they will be able to smoothly make decisions related to medical care, such as determining diagnoses and treatment plans.

[0124] Second embodiment The second embodiment is based on the first embodiment, and differs from the first embodiment in that in the second embodiment, the medical information processing device 100 has an aggregation function 159. Below, the differences between the second embodiment and the first embodiment will be mainly described, and repeated description will be appropriately omitted.

[0125] 10 is a block diagram showing an example of the configuration of a medical information processing apparatus 100 according to the second embodiment. The processing circuitry 150 of the medical information processing apparatus 100 according to this embodiment further includes an aggregation function 159.

[0126] The aggregation function 159 analyzes character strings having clinical meanings extracted by the extraction function 153, and aggregates synonyms, similar words, and abbreviations into one topic. Specifically, the aggregation function 159 uses a known medical ontology, thesaurus, dictionary, etc., and aggregates synonyms, similar words, hypernyms / hypernyms, and words in an abbreviation-formal name relationship into one topic based on the clinical meaning of the topic.

[0127] The topic aggregation process will be described below with reference to Fig. 11. Fig. 11 is a conceptual diagram showing an example of the topic aggregation process.

[0128] In this example, a process will be described that is performed after a character string W having clinical meanings such as edema, chest pain, and shortness of breath is extracted as a topic in Fig. 2. First, the aggregation function 159 recognizes that "edema", "edema", "swelling", and "edema" are mutually related to each other as synonyms, for example, by using a known medical ontology, thesaurus, dictionary, and the like.

[0129] Next, the aggregation function 159 checks the importance of "edema," "edema," "swelling," and "edema" calculated by the first calculation function 154. Then, for example, if "edema" has the highest importance among these, the aggregation function 159 aggregates "edema," "edema," "swelling," and "edema" into one "topic: edema" T1, with "edema" as the topic name.

[0130] Next, a description will be given of processing executed by the medical information processing apparatus 100 according to this embodiment. Fig. 12 is a flowchart showing an example of processing executed by the medical information processing apparatus 100 according to the second embodiment.

[0131] First, steps S31 to S33 are similar to steps S1 to S3 in FIG. 9, so their description will be omitted.

[0132] After the process of step S33, the aggregation function 159 aggregates into one topic the topics that have the same meaning, similar word, higher / lower concept word, and abbreviation-formal name relationship based on the clinical meaning of the topic extracted by the extraction function 153 (step S34). At this time, the aggregation function 159 sets the name of the topic with the highest importance among the topics aggregated into one as the topic name.

[0133] Moreover, the processes from step S35 onwards are similar to those from step S4 to step S11 in FIG. 9, and therefore the description thereof will be omitted.

[0134] The medical image processing device 100 according to the second embodiment described above has an aggregation function 159 that analyzes character strings having clinical meanings extracted by the extraction function 153, and aggregates synonyms, similar words, and abbreviations into a single topic.

[0135] As a result, topics that are related to each other, such as synonyms or similar words, are aggregated into one topic, making it easier for the user to find a desired topic when there are many synonymous or similar topics among the topics extracted by the extraction function 153. Therefore, according to the medical information processing device 100 of this embodiment, the user can efficiently refer to the necessary medical information.

[0136] Third embodiment The third embodiment is based on the second embodiment, and differs from the second embodiment in that in the second embodiment, the medical information processing device 100 has a generating function 160. Below, the differences between the third embodiment and the second embodiment will be mainly described, and repeated description will be appropriately omitted.

[0137] 13 is a block diagram showing an example of the configuration of a medical information processing apparatus 100 according to the third embodiment. The processing circuitry 150 of the medical information processing apparatus 100 according to this embodiment further includes a generating function 160.

[0138] In this embodiment, the second calculation function 156 calculates the degree of association between each of the topics aggregated by the aggregation function 159 and other topics. Note that the second calculation function 156 may calculate the degree of association between the topics before aggregation.

[0139] The generating function 160 aggregates one or more topics according to the relevance calculated by the second calculating function 156, and generates a topic group. Specifically, the generating function 160 first aggregates topics whose relevance calculated by the second calculating function 156 is equal to or greater than a threshold. Next, the generating function 160 checks the importance calculated by the first calculating function 154 for each aggregated topic.

[0140] Then, the generation function 160 sets the name of the most important topic among the aggregated topics as the name of the topic group, and generates a topic group to which the aggregated topic belongs. Note that the topic group may contain only one topic. The generation function 160 may only generate a topic group without aggregating topics that are in a synonymous relationship or the like.

[0141] The topic group generation process will be described below with reference to Fig. 14 and Fig. 15. Fig. 14 is a conceptual diagram showing an example of the process of aggregating related topics. Fig. 15 is a conceptual diagram showing an example of the process of generating a topic group.

[0142] In this example, a process is described that is performed after aggregation of topics having synonymous or other relationships in Fig. 11. First, the second calculation function 156 calculates the degree of association between topics such as "topic: edema" T1-"topic: pleural effusion" T2 and "topic: edema" T1-"topic: chest pain" T3, for example, using a known analysis method such as association analysis.

[0143] For example, if the degree of relevance between the topics "Topic: Edema" T1-"Topic: Pleural effusion" T2 and "Topic: Edema" T1-"Topic: Chest pain" T3 is equal to or greater than a threshold, the generation function 160 aggregates "Topic: Edema" T1, "Topic: Pleural effusion" T2, and "Topic: Chest pain" T3, as shown in FIG. 14.

[0144] Next, the generating function 160 checks the importance of "edema," "pleural effusion," and "chest pain" calculated by the first calculating function 154. Then, for example, if "edema" has the highest importance among these, the generating function 160 generates a "topic group: edema" TG, with "edema" as the topic group name, to which "topic: edema" T1, "topic: pleural effusion" T2, and "topic: chest pain" T3 belong, as shown in FIG.

[0145] Here, "Topic: Edema" T1, which is the topic group name, is called the head topic, and "Topic: Pleural effusion" T2 and "Topic: Chest pain" T3 are called related topics of the head topic.

[0146] When the generation function 160 generates a topic group, the display control function 151 controls the display of the topics on the display 140. Hereinafter, the topic display process will be described with reference to Figures 16 and 17. Figures 16 and 17 are image diagrams showing an example of a topic display screen.

[0147] When the generation function 160 generates a topic group, the display control function 151 displays a topic display panel TD as shown in FIG.

[0148] In this example, the display control function 151 displays, in the topic display area TE, as headline topics TT, "edema," "shortness of breath," "surgery," "convulsions," and "diuretics," in order of increasing importance calculated by the first calculation function 154. In addition, the display control function 151 displays an expansion button EB at the right end of each headline topic TT.

[0149] Here, for example, when the user places the cursor CS on the expand button EB and left-clicks the mouse, the display control function 151 displays related topics RT of the headline topic in the topic display area TE as shown in Fig. 17. In the example of Fig. 17, the display control function 151 displays "chest pain" and "pleural effusion" in order of increasing importance calculated by the first calculation function 154 as related topics RT of "topic: edema", which is the headline topic TT.

[0150] Next, a description will be given of processing executed by the medical information processing apparatus 100 according to this embodiment. Fig. 18 is a flowchart showing an example of processing executed by the medical information processing apparatus 100 according to the third embodiment.

[0151] First, steps S51 to S54 are similar to steps S31 to S34 in FIG. 12, so their description will be omitted.

[0152] After the process of step S54, the second calculation function 156 calculates the degree of association between the topics extracted by the extraction function 153 and aggregated by the aggregation function 159 (step S55).

[0153] Next, the generating function 160 aggregates the topics whose relevance calculated by the second calculating function 156 is equal to or greater than a threshold value, and generates one or more topic groups (step S56). At this time, the generating function 160 sets the name of the topic with the highest importance in the generated topic group as the topic group name.

[0154] Next, display control function 151 controls display of one or more topic group names generated by generation function 160 on display 140 (step S57). At this time, display control function 151 controls display of one or more topic names belonging to the topic groups on display 140.

[0155] Next, the selection function 155 selects one topic from among the topics extracted by the extraction function 153 in accordance with an instruction from the user (step S58).

[0156] Next, the display control function 151 performs control to display the topics whose relevance to the selected topic exceeds a threshold value, as calculated by the second calculation function 156, as related topics below the selected topic (step S59).

[0157] Steps S60 to S62 are similar to steps S39 to S42 in FIG. 12, and therefore description thereof will be omitted.

[0158] The medical image processing apparatus 100 according to the third embodiment described above includes a generating function 160 that aggregates one or more topics according to the relevance calculated by the second calculating function 156 to generate a topic group.

[0159] This generates a topic group that aggregates related topics, making it easier for users to find related topics and enabling them to efficiently refer to required medical information.

[0160] The above-described first to third embodiments can be modified as appropriate by changing a part of the configuration or function of each device. Therefore, some modified examples of the above-described embodiments will be described below as other embodiments. Note that the following mainly describes the differences from the above-described embodiments, and detailed descriptions of the commonalities with the contents already described will be omitted. The modified examples described below may be implemented individually or in appropriate combination.

[0161] (Variation 1) In the above-described first to third embodiments, the determination function 157 calculates the degree of association between the selected topic and medical data (items) using a known analysis method, and determines the medical data (items) whose degree of association is equal to or greater than a threshold as display candidates to be displayed on the data display screen. In contrast, the determination function 157 may determine display candidates based on correspondence information that associates a topic with one or more pieces of medical data (items).

[0162] The correspondence information is determined based on medical treatment guidelines, etc. According to this modification, the process of calculating the relevance between the selected topic and the medical data (item) is not required, so that the load on the medical information processing device 100 can be reduced.

[0163] (Variation 2) In the above-mentioned first to third embodiments, the determination function 157 determines the layout of the display screen. In contrast, after the determination function 157 determines the layout of the display screen, the user may be allowed to replace the medical data (items) or change the display size of the medical data (items). Furthermore, the layout changed by the user may be given an arbitrary name and stored in the storage circuitry 120 as a custom topic.

[0164] According to this modification, it becomes possible to efficiently display medical data (items) that correspond to a user's unique viewpoint.

[0165] According to at least one of the embodiments described above, necessary medical information can be efficiently referred to.

[0166] Although several embodiments (variations) have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the gist of the invention. These embodiments and their variations are included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and gist of the invention. [Explanation of symbols]

[0167] 100 Medical information processing device 150 Processing circuit 151 Display control function 152 Setting Function 153 Extraction Function 154 First calculation function 155 Selection Function 156 Second calculation function 157 Decision Function 158 Search function 159 Aggregation Function 160 Generation function

Claims

1. an extracting unit that extracts a character string having a clinical meaning from first medical data indicating text data included in medical information indicating various data used in medical treatment, as a topic indicating a viewpoint for referring to the medical information; a selection unit that selects one of the topics from the topics extracted by the extraction unit in response to an input from a user; a display control unit that controls displaying, on a display device, the data related to the one topic selected by the selection unit among second medical data including one or more data representing a condition of a target subject included in the medical information; and Equipped with The extraction unit extracts the character string as the topic from the first medical data in accordance with an extraction condition indicating a condition for extracting the character string according to a reference purpose of the medical information. Medical information processing equipment.

2. The extraction conditions include at least one of a disease name, a medical department name, subject identification information for identifying a subject, and doctor identification information for identifying a doctor. The medical information processing device according to claim 1 .

3. The method further includes the steps of: The medical information processing device according to claim 1 .

4. The display control unit performs control to rearrange and display the topics according to the importance of the topics calculated by the first calculation unit. The medical information processing device according to claim 3 .

5. The apparatus further includes an aggregation unit that analyzes the character strings extracted by the extraction unit and aggregates synonyms, similar words, and abbreviations into one topic. The medical information processing device according to claim 1 .

6. A second calculation unit that calculates a degree of association between the plurality of topics; a generation unit that generates a topic group by aggregating one or more of the topics according to the relevance calculated by the second calculation unit, The medical information processing device according to claim 5 .

7. The display control unit controls the display device to arrange and display the second medical data according to classification information indicating a type of the second medical data. The medical information processing device according to claim 1 .

8. The display control unit performs control to change a display size and a layout of the second medical data in accordance with a size of the display device. The medical information processing device according to claim 1 .

9. The display control unit displays a topic history indicating topics that the user has referenced before a topic that the user is currently referenced; The selection unit selects one of the topics from the topic history. The medical information processing device according to claim 1 .

10. a search unit that searches for a topic that at least partially matches a character string specified by a user from among the topics extracted by the extraction unit, The medical image processing device according to claim 1 .

11. The search unit searches for topics that are synonymous or similar to a character string specified by a user. The medical information processing device according to claim 10.

12. The display control unit controls the display of one or more pieces of data corresponding to the one topic selected by the selection unit on a display device based on correspondence information that associates the topic with one or more pieces of second medical data. The medical image processing device according to claim 1 .

Images