Information processing device, information processing method, and program

Abstract

To improve the efficiency of identification. [Solution] The information processing device according to this embodiment comprises an acquisition unit, a calculation unit, and a display control unit. The acquisition unit acquires information about the patient's condition. The calculation unit calculates indicators related to the occurrence of multiple diseases based on the acquired information. The display control unit causes the indicators related to the occurrence of each of the multiple diseases to be displayed on the display unit. As a result, the information processing device according to this embodiment can improve the efficiency of diagnosis.

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] At the emergency scene, quick judgment and treatment are important for saving the patient's life. For example, when a patient has a life-threatening injury, the probability of survival decreases with time, so it is important to narrow down the diseases from the patient's vital signs and physical findings.

[0003] In recent years, while the demand for emergency medical services has been increasing, there has been a shortage of emergency physicians. As a result, due to the inability to deploy sufficient personnel at the emergency scene, inexperienced physicians (e.g., interns or physicians from other fields) may perform the differential diagnosis. In addition, in recent years, due to the adjustment of physicians' working hours due to the work style reform, there may also be a possibility that physicians cannot be sufficiently deployed. However, at present, there is no means to support the differential diagnosis. Therefore, shortening the time for differential diagnosis is desired along with the support for differential diagnosis.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0005] One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to improve the efficiency of identification. However, the problems solved by the embodiments disclosed herein and in 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]

[0006] The information processing device according to this embodiment comprises an acquisition unit, a calculation unit, and a display control unit. The acquisition unit acquires information about the patient's condition. The calculation unit calculates indicators related to the occurrence of multiple diseases based on the acquired information. The display control unit causes the indicators related to the occurrence of each of the multiple diseases to be displayed on the display unit. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 shows an example of the configuration of an information processing system including an information processing device according to this embodiment. [Figure 2] Figure 2 shows an example of the configuration of the information processing device according to this embodiment. [Figure 3] Figure 3 is an explanatory diagram illustrating an example of a workflow in the emergency department. [Figure 4] Figure 4 is a flowchart showing the processing procedure by the information processing device according to this embodiment. [Figure 5] Figure 5 shows an example of a screen display shown on the display of the information processing device according to this embodiment. [Figure 6] Figure 6 is a diagram showing the probability of occurrence for each of the multiple diseases displayed in the screen display area of ​​Figure 5. [Figure 7] Figure 7 shows an example of how the criteria for each disease are displayed in the display area of ​​the screen shown in Figure 5. [Figure 8] Figure 8 shows an example of how the scoring criteria items are displayed in a graph format within the display area of ​​the screen shown in Figure 5. [Figure 9]Figure 9 shows an example of how the scoring criteria items are displayed in a graph format within the display area of ​​the screen shown in Figure 5. [Figure 10] Figure 10 is a diagram showing the probability of occurrence for each of the multiple diseases displayed in the display area of ​​the screen in Figure 5, and is an example of how it is displayed when there are many diseases to be shown in the probability graph. [Figure 11] Figure 11 is a diagram showing the probability of occurrence for each of the multiple diseases displayed in the display area of ​​the screen in Figure 5, and is an example of how it is displayed when there are many diseases to be shown in the probability graph. [Figure 12] Figure 12 is an explanatory diagram showing an example of a workflow in an emergency department as the first modified example, and is a diagram showing an example of display when images are used. [Figure 13] Figure 13 is a first modified example, showing the probability of occurrence of each of the multiple diseases displayed in the display area of ​​the screen in Figure 5, and is a diagram illustrating an example of display when using images. [Figure 14] Figure 14 is a first modified example showing an example of displaying disease-specific judgment criteria in the display area of ​​the screen in Figure 5, and is a diagram showing an example of display using images. [Figure 15] Figure 15 is a second modified example illustrating the case where the probability of occurrence is the same. [Figure 16] Figure 16 is a flowchart showing the procedure for handling the case where the probability of occurrence is the same, as a second modified example. [Figure 17] Figure 17 is a diagram illustrating the processing in the second modified example when the conditions of the judgment criteria are met and the difference between the threshold and the measured value is large. [Figure 18] Figure 18 is a diagram illustrating the process in the second modified example where the conditions of the judgment criteria are not met, but the difference between the threshold and the measured value is small. [Figure 19] Figure 19 is a third modified example illustrating the preferred display of disease-based parameters. [Figure 20] Figure 20 is a diagram illustrating an example of the display in the fourth modified example. [Figure 21]FIG. 21 is a diagram for explaining a display example in the fifth modification. [Figure 22] FIG. 22 is a diagram for explaining another display example in the fifth modification. [Figure 23] FIG. 23 is a diagram showing an example of the configuration of an information processing system including a biological information collection device. [Figure 24] FIG. 24 is a diagram showing an example of the configuration of a biological information collection device.

Embodiments for Carrying Out the Invention

[0008] Hereinafter, embodiments of an information processing apparatus, an information processing method, and a program will be described in detail with reference to the drawings. In the following, an information processing system including the information processing apparatus will be described as an example.

[0009] (First Embodiment) FIG. 1 is a diagram showing an example of the configuration of an information processing system 1 including an information processing apparatus 100 according to the present embodiment. The information processing system 1 shown in FIG. 1 includes an information processing apparatus 100, a medical image diagnostic apparatus 2, an image storage apparatus 3, and a HIS (Hospital Information System) server 10. The information processing apparatus 100 is connected to the medical image diagnostic apparatus 2, the image storage apparatus 3, and the HIS server 10 via a network 4 such as an in-hospital LAN (Local Area Network) installed in a hospital, for example. Here, each apparatus is in a state where it can communicate with each other directly or indirectly. For example, when a PACS (Picture Archiving and Communication System) is introduced into the information processing system 1, each apparatus transmits and receives medical images and the like to and from each other in accordance with the DICOM (Digital Imaging and Communications in Medicine) standard.

[0010] The HIS server 10 manages information generated within the hospital. This information includes patient information and test order information. Patient information includes basic patient information, medical information, and test execution information. Basic information includes patient ID, name, date of birth, gender, blood type, height, weight, etc. The patient ID is set to unique identification information that identifies the patient. Patient medical information includes information such as numerical values ​​(measured values) and medical records, as well as information indicating the date and time of these records. For example, patient medical information includes information such as prescriptions by doctors, nursing records by nurses, tests ordered by the laboratory, and arrangements for meals during hospitalization. For example, prescriptions are recorded in the electronic medical record by doctors, and nursing records are recorded in the electronic medical record by nurses. Test execution information includes information such as tests performed in the past and the results of those tests, as well as information indicating the date the tests were performed.

[0011] Medical imaging diagnostic equipment 2 includes X-ray diagnostic equipment, X-ray CT (Computed Tomography) equipment, MRI (Magnetic Resonance Imaging) equipment, ultrasound diagnostic equipment, SPECT (Single Photon Emission Computed Tomography) equipment. Medical imaging diagnostic equipment 2 also includes PET (Positron Emission Computed Tomography) equipment, SPECT-CT equipment (integrating SPECT and X-ray CT equipment), PET-CT equipment (integrating PET and X-ray CT equipment), or groups of these equipment. Medical imaging diagnostic equipment 2 can generate 2D medical images, 3D medical images (volume data), 2D medical images along time series, and 3D medical images along time series.

[0012] Here, the medical imaging diagnostic device 2 collects medical images by photographing the subject based on patient information and examination order information from the HIS server 10. For example, the X-ray CT scanner, which is the medical imaging diagnostic device 2, rotates the X-ray tube and X-ray detector over the subject to which a contrast agent has been administered, and detects the X-rays that have passed through the subject to collect projection data. Then, based on the collected projection data, the X-ray CT scanner generates a two-dimensional CT image, a three-dimensional CT image (volume data), a two-dimensional CT image along a time series, or a three-dimensional CT image along a time series. Alternatively, the X-ray CT scanner generates multiple two-dimensional CT images along a predetermined direction based on the collected projection data. For example, the X-ray CT scanner generates multiple two-dimensional CT images of axial sections along the body axis.

[0013] The medical imaging diagnostic device 2 transmits the generated medical images to the image storage device 3. When transmitting the medical images to the image storage device 3, the medical imaging diagnostic device 2 also transmits supplementary information such as a patient ID to identify the patient, an examination ID to identify the examination, a device ID to identify the medical imaging diagnostic device 2, and a series ID to identify a single image taken by the medical imaging diagnostic device 2.

[0014] Image storage device 3 is a database for storing medical images. Specifically, image storage device 3 is equipped with a memory circuit and stores medical images transmitted from medical image diagnostic device 2 in the memory circuit. The memory circuit of image storage device 3 is, for example, a semiconductor memory element such as RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or optical disk. Medical images stored in image storage device 3 are stored in association with patient ID, examination ID, device ID, series ID, etc. Therefore, information processing device 100 can retrieve the necessary medical images from image storage device 3 by performing a search using patient ID, examination ID, device ID, series ID, etc.

[0015] The information processing device 100 is a device that processes various types of medical information, such as workstations, personal computers (PCs), tablet PCs, PDAs (Personal Digital Assistants, Personal Data Assistants), and mobile phones such as smartphones. The information processing device 100 is capable of performing various processes on medical information acquired from the HIS server 10, medical image diagnostic device 2, image storage device 3, etc. In this embodiment, the information processing device 100 is located in a treatment room where emergency transport patients are treated, and it mainly processes information about patients obtained in that treatment room.

[0016] Figure 2 shows an example of the configuration of the information processing device 100 according to this embodiment. As shown in Figure 2, the information processing device 100 includes an input interface 110, a communication interface 130, a display 120, a storage circuit 140, and a processing circuit 150.

[0017] The input interface 110 is implemented by a trackball, switch buttons, mouse, keyboard, touchpad for input operations by touching the operating surface, touchscreen with integrated display screen and touchpad, non-contact input interface using optical sensors, and voice input interface. The input interface 110 receives various operation inputs for the information processing device 100 from the user, a physician, and transfers the instructions and setting information received from the user to the processing circuit 150.

[0018] The display 120 is a monitor referenced by the user. Under the control of the processing circuit 150, the display 120 displays images to the user and a GUI (Graphical User Interface) to receive various instructions and settings from the user via the input interface 110. The communication interface 130 is a NIC (Network Interface Card) or the like, and communicates with other devices. The display 120 is an example of a display unit.

[0019] The memory circuit 140 is, for example, a semiconductor memory element such as RAM or flash memory, or a storage device such as a hard disk or optical disc. The memory circuit 140 stores various medical information of the patient used in the processing, as well as information on guidelines for calculating the probability of occurrence, which will be described later.

[0020] The processing circuit 150 controls the components of the information processing device 100. For example, as shown in Figure 2, the processing circuit 150 executes an acquisition function 151, a calculation function 152, and a display control function 153. Here, for example, each processing function executed by the acquisition function 151, calculation function 152, and display control function 153, which are components of the processing circuit 150, is recorded in the storage circuit 140 in the form of a program that can be executed by a computer. The processing circuit 150 is a processor that realizes the function corresponding to each program by reading each program from the storage circuit 140 and executing it. In other words, the processing circuit 150 in the state in which each program has been read has the functions shown in the processing circuit 150 in Figure 2. Note that the acquisition function 151, calculation function 152, and display control function 153 are examples of an "acquisition unit," a "calculation unit," and a "display control unit," respectively.

[0021] In the above description, the term "processor" refers to circuits such as CPUs (Central Processing Units), GPUs (Graphics Processing Units), and Application Specific Integrated Circuits (ASICs). It also refers to circuits such as programmable logic devices. Examples of programmable logic devices include Simple Programmable Logic Devices (SPLDs) and Complex Programmable Logic Devices (CPLDs). Another example of a programmable logic device is a Field Programmable Gate Array (FPGA). When the processor is a CPU, it functions by reading and executing a program stored in the memory circuit 140. On the other hand, when the processor is an ASIC, instead of storing the program in the memory circuit 140, the program is directly incorporated into the processor's circuit. Note that each processor in this embodiment is not limited to being configured as a single circuit; multiple independent circuits may be combined to form a single processor and realize its functions. Furthermore, the multiple components shown in Figure 2 may be integrated into a single processor to realize their functions.

[0022] In emergency situations, rapid judgment and treatment are crucial for saving patients' lives. For example, if a patient has life-threatening injuries, the chances of survival decrease with time, making differential diagnosis based on the patient's condition (vitals and physical findings) essential. In recent years, while the demand for emergency care has increased, there has been a shortage of emergency physicians. As a result, insufficient personnel can be deployed to emergency scenes, potentially leading to inexperienced physicians (e.g., residents or physicians from other specialties) performing differential diagnoses. Furthermore, recent work-style reforms have also led to adjustments in physicians' working hours, potentially resulting in insufficient physician deployment. However, currently, there are no means to support differential diagnosis. Therefore, support for differential diagnosis and reduction of the time required for diagnosis are desired.

[0023] Therefore, in order to improve the efficiency of differentiation, the information processing device 100 according to this embodiment performs the following processing. First, in the information processing device 100 according to this embodiment, the acquisition function 151 acquires information about the patient's condition. The calculation function 152 calculates indicators related to the occurrence of multiple diseases based on the acquired information. The display control function 153 displays the indicators related to the occurrence of each of the multiple diseases on the display 120.

[0024] In this context, indicators related to the occurrence of a disease are important for physicians in narrowing down the possible causes of a disease. Indicators related to the occurrence of a disease, for example, are used as criteria or guidelines to make it easier to understand the likelihood of a disease occurring, by representing the probability of the disease occurring with numbers or symbols.

[0025] For example, when expressing the likelihood of a disease occurring numerically as an indicator of its occurrence, probability of occurrence or a five-point scale are used. For instance, probability of occurrence is expressed on a scale from "0%" to "100%", with "100%" indicating the highest probability of the disease occurring. For example, a five-point scale is expressed on a scale from "1" to "5", with "5" indicating the highest probability of the disease occurring.

[0026] For example, when using symbols to represent the likelihood of a disease occurring, indicators such as "○", "△", and "×", or a five-point scale may be used. For instance, in the "○", "△", and "×" scale, "×" represents the highest likelihood of the disease occurring, and "○" represents the lowest likelihood. In the five-point scale, for example, "A", "B", "C", "D", and "E" represent the highest likelihood of the disease occurring, and "A" represents the lowest likelihood.

[0027] The following explanation will use the example of a case where the probability of occurrence is used as an indicator of occurrence.

[0028] Figure 3 is an explanatory diagram illustrating an example of a workflow in the emergency department. As mentioned above, rapid judgment and treatment are crucial for saving patients' lives in emergency situations. Therefore, the emergency department typically follows the steps shown in Figure 3.

[0029] As shown in Figure 3, the patient is first brought in (Step S1). Upon arrival, the ABC approach is used to avoid life-threatening situations and stabilize vital signs, and the ABC stabilization is confirmed (Step S2). The ABC approach is a method used to prevent sudden deterioration, and prioritizes observation and resuscitation along the flow of oxygen in the body (Airway, Breathing, Circulation). Simultaneously with Step S2, an important workflow is performed to identify (differentially identify) the disease causing the symptoms (Step S3). After the ABC is stabilized, treatment is administered as an approach to the disease (Step S4). Steps S2 and S3 are repeated until the ABC is stabilized.

[0030] In the information processing device 100 according to this embodiment, diagnostic support is provided in step S2. Figure 4 is a flowchart showing the processing procedure by the information processing device 100 according to this embodiment. Figure 5 is a diagram showing an example of the display of the screen 200 shown on the display 120 of the information processing device 100 according to this embodiment. Figure 6 is a diagram showing the probability of occurrence of each of the multiple diseases displayed in the display area 212 of the screen 200 in Figure 5.

[0031] Step S101 in Figure 4 is a step in which the processing circuit 150 reads and executes a program corresponding to the acquisition function 151 from the memory circuit 140. In step S101, the acquisition function 151 acquires information about the patient's condition. For example, the HIS server 10 manages patient information transmitted from the emergency medical personnel's terminal when the patient is transported by ambulance, and patient information generated within the hospital after the ambulance transport. The acquisition function 151 acquires patient information and information about the patient's condition (consciousness, vital signs, etc.) from the HIS server 10. The acquisition function 151 also sequentially acquires information about the patient obtained in the treatment room where the patient was brought.

[0032] Step S102 in Figure 4 is a step in which the processing circuit 150 reads and executes a program corresponding to the calculation function 152 from the memory circuit 140. In step S102, the calculation function 152 calculates the probability of occurrence of multiple diseases based on the information acquired by the acquisition function 151. For example, the calculation function 152 calculates the probability of occurrence [%] of multiple diseases as possible diseases based on the information acquired by the acquisition function 151 and the diagnostic items of the guidelines. The guidelines used for calculating the probability of occurrence may be those established by public institutions such as academic societies, or those agreed upon within the hospital.

[0033] For example, let's take sepsis as an example of a possible disease. Diagnostic criteria for "sepsis" include, for example, altered consciousness, respiratory rate, and systolic blood pressure, as shown in the upper part of Figure 6.

[0034] In diagnosing altered consciousness, the patient's impaired consciousness is assessed by whether their GCS (Glasgow Coma Scale) score is less than 15. For example, if the GCS score is 15 or higher, the patient may have sepsis.

[0035] The respiratory rate diagnostic criterion determines whether the patient's respiratory rate is 22 breaths per minute or more. For example, if the respiratory rate is 22 breaths per minute or more, there is a possibility of the disease being "sepsis".

[0036] The diagnostic criterion for systolic blood pressure is whether the patient's systolic blood pressure is 100 mmHg or less. For example, if the systolic blood pressure is less than 100 mmHg, the disease "sepsis" may be a possibility.

[0037] Here, as shown in the upper part of Figure 6, if two out of three diagnostic criteria for "sepsis" apply, the calculation function 152 calculates (2 / 3) × 100 = 67, resulting in a probability of sepsis occurring of 67%.

[0038] Step S103 in Figure 4 is a step in which the processing circuit 150 reads and executes a program corresponding to the display control function 153 from the memory circuit 140. In step S103, the display control function 153 displays the probability of occurrence of each of the multiple diseases calculated by the calculation function 152 on the display 120.

[0039] For example, the display control function 153 causes the screen 200 shown in Figure 5 to be displayed on the display 120. In the example shown in Figure 5, display areas 210, 220, 230, 240, and 250 are displayed on the screen 200.

[0040] For example, display areas 220, 230, 240, and 250 display patient information, including the patient's basic information (patient ID, name, date of birth, gender, blood type, height, weight), patient's medical information (numerical values, measured values, medical records, etc., and information indicating the date and time of recording), patient's examination information (information on examinations and the results of those examinations, and information indicating the date the examinations were performed), and medical images obtained from the examinations.

[0041] For example, display area 210 is an area that displays data in chronological order and includes display areas 211 and 212. Display area 211 displays vital signs such as heart rate in chronological order as information about the patient's condition. Note that there may be multiple vital signs displayed in display area 211, such as heart rate and blood pressure. The vital signs displayed in display area 211 can be changed by input from a physician. Display area 212 displays the probability of occurrence of multiple diseases in chronological order as information about the patient's condition.

[0042] Furthermore, the data displayed in the display area 212 is updated sequentially. Specifically, the acquisition function 151 sequentially acquires information about the patient's condition (consciousness and vital signs), and the calculation function 152 updates the probability of occurrence of multiple diseases based on the sequentially acquired information. At this time, the display control function 153 sequentially updates the vital signs to be displayed on the display 120, and also sequentially updates the probability of occurrence of each of the multiple diseases to be displayed on the display 120. For example, in the example shown in Figure 5, the display control function 153 displays the sequentially updated vital signs on the display 120 in chronological order, and also displays the probability of occurrence of each of the sequentially updated diseases on the display 120 in chronological order.

[0043] Figure 6 shows the probability of occurrence for each of the multiple diseases displayed in the display area 212 of screen 200 in Figure 5. As shown in the lower part of Figure 6, for example, the multiple diseases displayed in the display area 212 are "pneumonia," "sepsis," "hypertension," "subarachnoid hemorrhage," and "septic shock." In the display area 212, the horizontal axis is the time axis [seconds], and the vertical axis is the probability of occurrence [%].

[0044] For example, as shown in Figure 6, in the display area 212, the probability of the latest disease occurring is highest for "pneumonia," "sepsis," "hypertension," and "subarachnoid hemorrhage," followed by "septic shock." The higher the probability of occurrence, the greater the urgency. Note that "hypertension" and "subarachnoid hemorrhage" have the same probability of occurrence.

[0045] In the information processing device 100 according to this embodiment, the display control function 153 displays the occurrence probability of each of the multiple diseases, which are updated sequentially, on the display 120 in chronological order, and the diseases are displayed in descending order of occurrence probability, thereby supporting differential diagnosis. This is expected to shorten the time required for diagnosis. Furthermore, with the information processing device 100 according to this embodiment, the user can also check the chronological display of vital signs, so they can check the changes in occurrence probability in relation to the changes in vital signs. In this way, the information processing device 100 according to this embodiment can improve the efficiency of diagnosis.

[0046] Figure 7 shows an example of how disease-specific judgment criteria are displayed in the display area 212 of screen 200 in Figure 5.

[0047] The display control function 153 displays on the display 120 information regarding the judgment criteria used to calculate the probability of occurrence of a disease specified by the user from among several diseases. The information regarding the judgment criteria includes, for example, the diagnostic items of the guidelines used to determine the disease.

[0048] For example, suppose that the user gives an instruction to display the criteria for diagnosing sepsis when the probability of occurrence of several diseases is displayed in the display area 212 of screen 200 in Figure 5.

[0049] In this case, the display control function 153 displays the criteria for diagnosing sepsis in the display area 212. Here, when the user issues the instruction "Show criteria for diagnosing sepsis," the display control function 153 displays the criteria for diagnosing sepsis in the display area 212 via voice input. Alternatively, when the user inputs the text "Show criteria for diagnosing sepsis" using the input interface 110, the display control function 153 displays the criteria for diagnosing sepsis in the display area 212 via text input.

[0050] For example, the display control function 153 displays the criteria for diagnosing sepsis in a table format in the display area 212. Specifically, the display control function 153 displays the disease name, the criteria for diagnosing the diagnostic item, the acquisition time of the diagnostic item, and the latest value of the diagnostic item in the display area 212, associating them with each other.

[0051] In the example shown in Figure 7, if two out of three diagnostic criteria for "sepsis" are met, a probability of sepsis occurring of 67% is displayed in display area 212. For example, the diagnostic criteria for altered consciousness might be that the patient's latest GCS score is 15 points, the diagnostic criteria for respiratory rate might be that the patient's latest respiratory rate is 25 breaths per minute, and the diagnostic criteria for systolic blood pressure might be that the patient's latest systolic blood pressure is 100 mmHg or higher. Two out of three diagnostic criteria for "sepsis" are met: the diagnostic criteria for altered consciousness and the diagnostic criteria for respiratory rate.

[0052] At this time, it is assumed that the user has given the instruction "Show sepsis diagnostic criteria" to display the sepsis diagnostic criteria. In this case, as shown in the example in Figure 7, the display area 212 displays the disease name "Sepsis", the diagnostic criteria "Change in consciousness <15", acquisition time "10 minutes ago", and latest value "GCS 15 points", as well as the diagnostic criteria "Respiratory rate ≥ 22 breaths / min", acquisition time "0 seconds ago", and latest value "Respiratory rate 25 breaths".

[0053] In the example shown in Figure 7, the diagnostic items for "sepsis," specifically the altered consciousness and respiratory rate, which are likely to indicate sepsis, are displayed in the display area 212. However, the diagnostic item for systolic blood pressure, which is not likely to indicate sepsis, may also be displayed in the display area 212. Alternatively, all diagnostic items—alternated consciousness, respiratory rate, and systolic blood pressure—may be displayed in the display area 212 regardless of whether sepsis is likely or not.

[0054] Figures 8 and 9 show examples of how the scoring criteria items are displayed in a graph format in the display area 212 of screen 200 in Figure 5.

[0055] The display control function 153 displays the occurrence probability of each of the multiple diseases, which are updated sequentially, on the display 120 in a time-series graph format. The legend of the graph, "Correspondence between line type and symptoms (solid line for pneumonia, etc.)", may also reflect the ranking of the occurrence probabilities. In other words, the legend may display the diseases in descending order of occurrence probability.

[0056] In the example shown in Figure 8, when the criteria for diagnosing sepsis are displayed in display area 212, the user gives the command "Show changes in consciousness" via voice input to display the diagnostic items for changes in the patient's consciousness as a symptom of impaired consciousness. Alternatively, when the probability of occurrence of multiple diseases is displayed in display area 212 of screen 200 in Figure 5, if the user determines that "sepsis" is a possible disease for the patient, the user gives the command "Show changes in consciousness" via voice input to display the diagnostic items for changes in the patient's consciousness.

[0057] In this case, the display control function 153 displays the diagnostic items for altered consciousness in sepsis in the display area 212. For example, the display control function 153 displays the score items of the judgment criteria as diagnostic items for altered consciousness in sepsis in graph format in the display area 212. Specifically, in the example shown in Figure 8, the display control function 153 displays the score items of the judgment criteria as diagnostic items for altered consciousness in sepsis in graph format such as a radar chart in the display area 212.

[0058] In Figure 8, the display area 212 shows the disease name "Sepsis," the judgment criterion "Change in consciousness <15," the acquisition time "10 minutes ago," and the latest value "GCS 15 points." In addition, the score items for change in consciousness in sepsis, such as eye opening "5 points," best motor response "5 points," and best speech function "5 points," are displayed in graph format. For example, the GCS score includes information transmitted from the emergency medical personnel's terminal as patient information when the patient is transported to the emergency room, and patient information generated within the hospital after the emergency transport.

[0059] Furthermore, in the example shown in Figure 9, when the criteria for diagnosing sepsis are displayed in the display area 212, the user gives the command "Show SOFA (Sequential Organ Failure Assessment) score" to display diagnostic items for changes in the patient's consciousness as a sign of impaired consciousness. Alternatively, when the probability of occurrence of multiple diseases is displayed in the display area 212 of screen 200 in Figure 5, if the user determines that "sepsis" is a possible disease for the patient, the user gives the command "Show SOFA score" to display diagnostic items for changes in the patient's consciousness. The SOFA score is determined by the calculation function 152 based on information acquired by the acquisition function 151 and the SOFA score guidelines, for example.

[0060] In this case, the display control function 153 displays the diagnostic items for altered consciousness in sepsis in the display area 212. For example, the display control function 153 displays the score items of the judgment criteria as the SOFA score, which is an indicator of organ damage, in the display area 212 in graph format. Specifically, in the example shown in Figure 9, the display control function 153 displays the score items of the judgment criteria as the SOFA score, which is an indicator of organ damage, in the display area 212 in graph format such as a radar chart.

[0061] In Figure 9, the display area 212 shows the disease name "Sepsis," the judgment criteria "Change in consciousness <15," the acquisition time "5 minutes ago," and the latest value "GCS 14 points." In addition, the SOFA score items are displayed in graph format as follows: Respiratory "1 point," Kidney "3 points," Central function "4 points," Cardiovascular "3 points," Liver "1 point," and Coagulation ability "2 points."

[0062] Figures 10 and 11 show the probability of occurrence for each of the multiple diseases displayed in the display area 212 of screen 200 in Figure 5, and are examples of displays when there are many diseases to be shown in the probability of occurrence graph.

[0063] The display control function 153 displays the probability of occurrence of a disease that meets predetermined conditions from among several diseases. Here, the predetermined conditions are those in the order of probability from 1st to Nth. The predetermined conditions may be, for example, that diseases with a probability of occurrence of 10% or more are to be displayed, or they may be the number of diseases that can be displayed on the display 120 (in this embodiment, the display area 212). The predetermined conditions can be arbitrarily changed by the emergency physician.

[0064] In the example shown in Figure 10, N=5. That is, in the example shown in Figure 10, the probability of occurrence of the most recently ranked diseases from 1st to 5th is displayed in display area 212. In the example shown in Figure 5, the time-series changes in the probability of occurrence of the following diseases are displayed in graph format in display area 212: "Pneumonia" (1st), "Sepsis" (2nd), "Hypertension" and "Subarachnoid Hemorrhage" (tied for 3rd), and "Septic Shock" (5th).

[0065] Here, diseases with an incidence probability of 6th place or lower are displayed together as a single thick line at the bottom of the graph in display area 212. In the example shown in Figure 10, these are displayed together as a single thick line at the bottom of the graph in display area 212, and diseases other than "pneumonia," "sepsis," "hypertension," "subarachnoid hemorrhage," and "septic shock" that cannot be displayed are shown as, for example, "Other (5 items)."

[0066] For example, the display control function 153 displays information about diseases that are not shown on the display 120, in response to a user request.

[0067] For example, in Figure 5, the display area 212 of screen 200 shows the probability of occurrence for multiple diseases, "pneumonia," "sepsis," "hypertension," "subarachnoid hemorrhage," and "septic shock," and also displays "other (5 items)." The user then gives an instruction to display the other diseases.

[0068] In the example shown in Figure 11, when the criteria for diagnosing sepsis are displayed in display area 212, the user gives the instruction "Show other tables" to display other diseases via voice input. Alternatively, when the probability of occurrence of multiple diseases is displayed in display area 212 of screen 200 in Figure 5, the user gives the instruction "Show other tables" to display other diseases via voice input.

[0069] In this case, the display control function 153 displays other diseases in a table format in the display area 212. Specifically, the display control function 153 displays diseases with a probability of occurrence of 6th place or lower in the display area 212, associating the disease probability ranking with the diseases ranked 6th or lower.

[0070] In the example shown in Figure 11, the display area 212 shows the disease names "cerebral infarction," "hypertensive kidney disease," "cerebral artery atherosclerosis," "renal vascular hypertension," and "hypertensive cardiorenal disease" for disease probability ranks "6," "7," "8," "9," and "10," respectively.

[0071] As described above, in the information processing device 100 according to this embodiment, the display control function 153 displays the occurrence probability of each of the multiple diseases that are updated sequentially on the display 120 in chronological order, and the diseases are displayed in descending order of occurrence probability, thereby supporting differential diagnosis. This is expected to shorten the time required for diagnosis. Furthermore, with the information processing device 100 according to this embodiment, the user can also check the chronological display of vital signs, so they can check the changes in occurrence probability in relation to the changes in vital signs.

[0072] Furthermore, in the information processing device 100 according to this embodiment, the display control function 153 can prevent overlooking diseases and assist in differential diagnosis by displaying information about diseases not shown on the display 120 in response to a user's request.

[0073] Thus, the information processing device 100 according to this embodiment can improve the efficiency of identification.

[0074] Furthermore, the time-series information, such as the probability of occurrence of each of the multiple diseases acquired in this embodiment, may be stored in the HIS server 10 in association with the patient's patient information. This allows for the management of information that forms the basis of differential diagnosis performed at the time of emergency admission within the hospital.

[0075] Furthermore, in this embodiment, the information processing device 100 is located in the treatment room where emergency transport patients are processed. However, in the information processing device 100, the input interface 110 and the display 120 may be located in the treatment room, while the other components such as the storage circuit 140 and processing circuit 150 may be distributed to other servers.

[0076] Furthermore, in this embodiment, the information processing device 100 displays the occurrence probability of each of the multiple diseases, which are updated sequentially, on the display 120 in a time-series graph format. However, it is not limited to this, and the latest occurrence probability may be displayed on the display 120 in a tabular format.

[0077] (Other embodiments) While embodiments have been described above, various other forms may also be used.

[0078] (First variation) Figure 12 is an explanatory diagram showing an example of a workflow in the emergency department as the first modified example, and is a diagram showing an example of display when images are used. In Figure 12, first the patient is brought in (step S1), then the stabilization of ABC is confirmed (step S2), and then images are taken (step S10). In step S10, if images are used, the presence or absence of findings such as stroke is determined. Also, as an important workflow performed simultaneously with steps S2 and S10, the disease causing the symptoms is identified (differential diagnosis) (step S3). Then, after ABC is stable, treatment is performed as an approach to the disease (step S4). Steps S2, S10 and S3 are repeated until ABC is stable.

[0079] In the first modified example, the display control function 153 causes the display 120 to display a message indicating that there are findings using images for at least one of the multiple diseases.

[0080] Figure 13 is a first modified example, showing the probability of occurrence of each of the multiple diseases displayed in the display area 212 of screen 200 in Figure 5, and is a diagram illustrating an example of display when using images.

[0081] In the example shown in Figure 13, when images are used, they are not used in the calculation of disease probability, but the display control function 153 displays the presence of findings next to the disease name. For example, as shown in the upper part of Figure 13, if the display control function 153 determines that there are findings in the acute phase of cerebral infarction based on the presence or absence of physical findings (numbness in the limbs or face, slurred speech) or impaired consciousness (GCS score) in the diagnostic item "stroke", it displays the disease "stroke" in the display area 212, and also displays "Image findings present" next to the disease "stroke" in the display area 212.

[0082] Figure 14 is a diagram showing an example of a first modified example in which the judgment criteria for each disease are displayed in the display area 212 of screen 200 in Figure 5, and is a diagram showing an example of a display using images.

[0083] In the example shown in Figure 14, when the disease "stroke" and "imaging findings present" are displayed in the display area 212, the user gives the instruction "Show stroke criteria" to display the criteria for diagnosing stroke via voice input.

[0084] In this case, the display control function 153 displays the stroke diagnosis criteria along with the image in the display area 212. In the example shown in Figure 14, the display area 212 displays the diagnosis criteria "physical findings" and the latest value "present, slurred speech" for the disease name "stroke," as well as the diagnosis criteria "altered consciousness <15" and the latest value "GCS 15 points." Furthermore, the display area 212 displays the image used for the disease "stroke." For example, the image is acquired from the medical image diagnostic device 2 or the image storage device 3.

[0085] Thus, in this first modified example, the display control function 153 displays on the display 120 that there are findings using images related to the disease, thereby preventing the disease from being overlooked.

[0086] (Second variation) Figure 15 is a second modified example illustrating the case where the probability of occurrence is the same.

[0087] The display control function 153, when ranking multiple diseases based on their probability of occurrence, adjusts the ranking based on the difference between the threshold value and the actual value related to the judgment criteria used to calculate the probability of occurrence. For example, for multiple diseases with the same probability of occurrence, the display control function 153 adjusts the ranking based on the difference between the threshold value and the actual value related to the judgment criteria used to calculate the probability of occurrence of the disease. Specifically, if multiple diseases have the same probability of occurrence, the display control function 153 displays the diseases considering the discrepancy (difference between the threshold value and the actual value) between the threshold value and the actual value related to the judgment criteria used to calculate the probability of occurrence.

[0088] As shown in Figure 15, the patterns of deviation can be categorized into two types: one where the probability of occurrence is met and the difference between the threshold and the measured value is large, and another where the probability of occurrence is not met but the difference between the threshold and the measured value is small. Here, we will explain how to handle the case where the probability of occurrence is the same using Figure 16.

[0089] Figure 16 is a flowchart showing the procedure for handling the case where the probability of occurrence is the same in the second modified example.

[0090] First, the calculation function 152 calculates the probability of occurrence for each of the multiple diseases (step S200). At this time, the display control function 153 checks whether there are multiple diseases with the same probability of occurrence (step S201).

[0091] If there are no multiple diseases with the same probability of occurrence (step S201; No), then, as described above, the display control function 153 displays the probability of occurrence of the disease with the highest probability of occurrence among the multiple diseases in the display area 212 of the screen 200 (step S204).

[0092] On the other hand, if there are multiple diseases with the same probability of occurrence (step S201; Yes), the display control function 153 checks the user's settings information.

[0093] For example, suppose the user has pre-configured an instruction to prioritize the criterion "large deviation from threshold" as part of the settings. In this case, the display control function 153 performs the "large deviation from threshold" process described below (step S202), and then the process in step S204 is performed.

[0094] For example, suppose the user has pre-configured a setting that prioritizes the criterion "the difference between the threshold and the measured value is small." In this case, the display control function 153 performs the process described below, "the difference between the threshold and the measured value is small" (step S203), and then the process in step S204 is performed.

[0095] The process for steps S202 and S203, specifically the case where the probability of occurrence is the same, will be explained in detail using Figures 17 and 18.

[0096] Figure 17 is a diagram illustrating the process in step S202 of Figure 16, which is the case when the conditions of the judgment criteria are met and the difference between the threshold and the measured value is large.

[0097] In the example shown in Figure 17, the multiple diseases with the same probability of occurrence are assumed to be "sepsis" and "pneumonia."

[0098] For example, diagnostic criteria for "sepsis" include altered consciousness, respiratory rate, and systolic blood pressure. The diagnostic criterion for altered consciousness is whether the patient's GCS score is less than 15 points, the diagnostic criterion for respiratory rate is whether the patient's respiratory rate is 22 breaths per minute or more, and the diagnostic criterion for systolic blood pressure is whether the patient's systolic blood pressure is 100 mmHg or less. For example, suppose the latest GCS score for altered consciousness is 14 points, the latest respiratory rate is 25 breaths per minute, and the latest systolic blood pressure is 120 mmHg. In this case, the diagnostic criteria for altered consciousness and respiratory rate are met, and the probability of sepsis occurring is 67%.

[0099] For example, the diagnostic criteria for "pneumonia" include body temperature, respiratory rate, and pulse rate. The diagnostic criterion for body temperature is whether the patient's body temperature is 38.6 degrees Celsius or higher, the diagnostic criterion for respiratory rate is whether the patient's respiratory rate is 130 breaths per minute or higher, and the diagnostic criterion for pulse rate is whether the patient's pulse rate is 30 beats per minute or higher. For example, suppose the latest reading of the patient's body temperature is 37 degrees Celsius, the latest reading of the patient's respiratory rate is 150 breaths per minute, and the latest reading of the patient's pulse rate is 45 beats per minute. In this case, the diagnostic criteria for "pneumonia" are met for both respiratory rate and pulse rate, and the probability of developing pneumonia is 67%.

[0100] Here, in the diagnostic items for "sepsis," the diagnostic items that meet the criteria are the diagnostic items for altered consciousness and respiratory rate, and the display control function 153 checks the discrepancy between the threshold and the measured value for the diagnostic items for altered consciousness and respiratory rate. For example, in the diagnostic item for altered consciousness, the degree of discrepancy is (|15-14| / 15)×100=7%, and in the diagnostic item for respiratory rate, the degree of discrepancy is (|22-25| / 22)×100=14%.

[0101] Furthermore, in the diagnostic items for "pneumonia," the diagnostic items that meet the criteria are respiratory rate and pulse rate, and the display control function 153 checks the discrepancy between the threshold and the measured value for the respiratory rate and pulse rate diagnostic items. For example, in the respiratory rate diagnostic item, the degree of discrepancy is (|130-150| / 130)×100=15%, and in the pulse rate diagnostic item, the degree of discrepancy is (|30-45| / 30)×100=50%.

[0102] In this case, the display control function 153 displays "pneumonia" above "sepsis" in the display area 212 because, among multiple diseases with the same probability of occurrence, "sepsis" and "pneumonia," the deviation from the threshold is greater for "pneumonia." Here, when the display control function 153 displays "pneumonia" and "sepsis" in the display area 212, since the probability of occurrence of "pneumonia" and "sepsis" is the same, in the graph format shown in Figures 6, 10, and 13, the graphs for "pneumonia" and "sepsis" overlap in the latest probability of occurrence. Therefore, in this modified example, as described above, when displaying diseases in order of the latest probability of occurrence in the graph legend, "pneumonia" is displayed above "sepsis." Alternatively, if there are diseases with the same probability of occurrence, the multiple diseases may be displayed in a table format in order of deviation, along with the message "Ranking based on deviation."

[0103] Figure 18 is a diagram illustrating the process in step S203 of Figure 16, which describes the case where the conditions of the judgment criteria are not met, but the difference between the threshold and the measured value is small.

[0104] In the example shown in Figure 18, as in the example shown in Figure 17, the multiple diseases with the same probability of occurrence are assumed to be "sepsis" and "pneumonia." The difference between the example shown in Figure 18 and the example shown in Figure 17 is that, in the diagnostic item for "sepsis," the latest value of the patient's systolic blood pressure is 110 mmHg.

[0105] In this case, among the diagnostic items for "sepsis," the diagnostic item that does not meet the criteria is the systolic blood pressure diagnostic item, and the display control function 153 checks the discrepancy between the threshold and the measured value for the systolic blood pressure diagnostic item. For example, in the diagnostic item for systolic blood pressure, the degree of discrepancy is (|100-110| / 100)×100=10%.

[0106] Furthermore, in the diagnostic items for "pneumonia," the item that does not meet the criteria is the body temperature diagnostic item, and the display control function 153 checks the discrepancy between the threshold and the measured value for the body temperature diagnostic item. For example, in the diagnostic item for body temperature, the degree of discrepancy is (|38.6-37| / 38.6)×100=4%.

[0107] In this case, the display control function 153 displays "pneumonia" above "sepsis" in the display area 212 because, among several diseases with the same probability of occurrence, "sepsis" and "pneumonia," the deviation from the threshold is smaller for "pneumonia." In this modified example, as described above, when displaying diseases in the graph legend in order of the most recent probability of occurrence, "pneumonia" is displayed above "sepsis." Alternatively, if there are diseases with the same probability of occurrence, the multiple diseases may be displayed in a table format in order of deviation, along with the message "Ranking based on deviation."

[0108] Thus, in this second modified example, the display control function 153 can accurately rank multiple diseases by considering the discrepancy between the threshold value and the actual value (the difference between the threshold value and the actual value) related to the judgment criteria used to calculate the probability of occurrence.

[0109] In the second modified example, it is possible that the degree of deviation may be the same for multiple diseases with the same probability of occurrence. For example, the degree of deviation for the diagnostic items of "sepsis" may be the same as the degree of deviation for the diagnostic items of "pneumonia." In this case, in the second modified example, accurate ranking can be achieved by pre-setting weights for each diagnostic item. For example, in Figure 18, if the degree of deviation for the diagnostic items of "sepsis" and the degree of deviation for the diagnostic items of "pneumonia" are the same, and the weight of systolic blood pressure is set to "0.8" for the diagnostic items of "sepsis" and the weight of body temperature is set to "0.9" for the diagnostic items of "pneumonia," the display control function 153 will display "pneumonia" higher than "sepsis" in the display area 212 because, although the degree of deviation for both diseases is the same among the multiple diseases "sepsis" and "pneumonia" with the same probability of occurrence, the weight of disease "pneumonia" is greater.

[0110] Thus, in this second modified example, the display control function 153 takes into account the discrepancy between the threshold value and the actual value (the difference between the threshold value and the actual value) related to the judgment criteria used to calculate the probability of occurrence, and sets weights for each diagnostic item, thereby enabling accurate ranking of multiple diseases.

[0111] (Third variation) Figure 19 is a third modified example illustrating the preferred display of disease-based parameters.

[0112] For example, if a disease is determined by a doctor's judgment, the parameters based on that disease will be displayed preferentially. In the example shown in Figure 19, when the probability of occurrence of multiple diseases is displayed in the display area 212 of screen 200 in Figure 5, if the user (doctor) decides to prioritize the treatment of "septic shock" as an approach to the disease, the instruction to determine the disease, "Prioritize displaying septic shock," is given by the user via voice input.

[0113] In this case, the display control function 153 switches the display to prioritize displaying information for the treatment of the disease "septic shock" on the display 120, instead of the normal information display. For example, if the normal display shows the hydrogen ion index "pH", oxygen saturation "sO2", and lactate "Lac" in that order, then in the case of the disease "septic shock", lactate "Lac" is important for treatment, so lactate "Lac" is moved to the top as a priority display.

[0114] Thus, in this third modified example, when a disease is determined by a physician, the display control function 153 can support treatment by prioritizing the display of information for the treatment of that disease on the display 120.

[0115] (Fourth variation) Figure 20 is a diagram illustrating the fourth modified example. Figure 20 shows an example of a display in which, as the fourth modified example, information regarding trend change points (points where the indicator changes) is displayed in the display area 212 of screen 200 in Figure 5 while the probability of occurrence of each of the multiple diseases is displayed.

[0116] In the fourth modified example, the display control function 153 displays on the display 120 information before and after the change in the information regarding the judgment criteria used to calculate the probability of occurrence of a disease whose probability of occurrence [%] has changed over time.

[0117] Here, "information before the change" refers to, for example, the information immediately before the change. "Information after the change" refers to, for example, the information immediately after the change, or the most recent information. The following explains the cases where "information immediately before the change" and "the most recent information" are displayed as information before and after the change in the judgment criteria.

[0118] In Figure 20, the horizontal axis represents time [seconds], and the vertical axis represents the probability of occurrence [%]. In the example shown in the upper part of Figure 20, similar to Figure 13, the disease "stroke" and "imaging findings present" are displayed in the display area 212, and the probability of occurrence of the disease "stroke" changes from 40% to 50% after 100 seconds. In this case, the display control function 153 displays the information immediately before the change and the latest information regarding the criteria for judging stroke on the display 120, as shown in the lower part of Figure 20. Note that in the example shown in the lower part of Figure 20, the image is also displayed in the display area 212.

[0119] In the example shown in the lower part of Figure 20, the display area 212 shows the value "GCS 13 points" as information immediately before the change, and also displays the value "GCS 15 points" as the latest information. In addition, in the example shown in the lower part of Figure 20, the display area 212 displays information regarding the physical findings immediately before the change and information regarding the latest physical findings, such as "Yes, slurred speech."

[0120] The above describes a case where information before and after a change is automatically displayed when an indicator related to occurrence (probability of occurrence) changes. However, the fourth variation is a case where information before and after a change is displayed only when specified by the user.

[0121] In other words, when the user specifies a disease whose probability of occurrence [%] has changed over time, the display control function 153 may display on the display 120 both the indicator before the change and the indicator after the change or the latest indicator for the judgment criteria used to calculate the probability of occurrence.

[0122] For example, suppose that in Figure 20, 100 seconds after the probability of the disease "stroke" is displayed, the user specifies a change point 300 in the stroke graph using the mouse, which is an example of the input interface 110. In this case, the display control function 153 displays the image in the display area 212 and also displays the information immediately before the change and the latest information regarding the stroke judgment criteria on the display 120.

[0123] By displaying this fourth variant, physicians can identify the factors that caused the change in the probability of occurrence.

[0124] (Fifth variation) Figure 21 is a diagram illustrating an example of display in the fifth modified example, and Figure 22 is a diagram illustrating another example of display in the fifth modified example.

[0125] The display control function 153 displays information on the display 120 regarding the probability of occurrence of each of the multiple diseases, along with information regarding the priority of treatment.

[0126] For example, as shown in Figure 21, in the display area 212, the probability of the latest disease occurring is highest for "pneumonia," "sepsis," "hypertension," and then for "subarachnoid hemorrhage" and "septic shock." However, depending on the factors causing the disease, the order of highest probability of occurrence does not necessarily correspond to the order in which treatment should be performed. The order of treatment is predetermined, for example, within the hospital.

[0127] For example, suppose it is agreed that the disease requiring the highest priority treatment is "hypertension," and the disease requiring the second highest priority treatment is "subarachnoid hemorrhage." In this case, the display control function 153 displays information 400 (an exclamation mark in Figure 21) indicating that the disease requiring the highest priority treatment is associated with the disease "hypertension" on the display 120.

[0128] Alternatively, as shown in Figure 22, the display control function 153 displays a mark indicating the "1st" priority of treatment (in Figure 22, "(1)") on the display 120 as information 401 regarding the priority of treatment, corresponding to the disease "hypertension," and displays a mark indicating the "2nd" priority of treatment (in Figure 22, "(2)") on the display 120 as information 402 regarding the priority of treatment, corresponding to the disease "subarachnoid hemorrhage."

[0129] In addition, in the fifth variation, the predetermined order within the hospital may be changed depending on the patient's information (e.g., medical history). For example, if the patient has previously suffered a subarachnoid hemorrhage, "subarachnoid hemorrhage" may be ranked "1st" and "hypertension" "2nd".

[0130] Thus, in this fifth modification, the display control function 153 can support efficient emergency treatment by displaying information regarding the priority of treatment on the display 120.

[0131] Furthermore, each function of the information processing device 100 in the information processing system 1 described above may be provided, for example, in a biological information collection device.

[0132] Figure 23 shows an example of the configuration of an information processing system including a biological information collection device 500. For example, each function of the information processing device 100 is performed by the biological information collection device 500 as shown in Figure 24.

[0133] For example, the biometric information collection device 500 is a device that collects a patient's biometric information from various biometric information measurement devices. The biometric information collection device 500 is located in a treatment room where emergency patients are processed, and mainly performs processing using patient information obtained in that treatment room. In addition, the biometric information collection device 500 is capable of performing various processes on medical information acquired from the HIS server 10, medical image diagnostic device 2, image storage device 3, etc.

[0134] Figure 24 shows an example of the configuration of the biological information collection device 500. As shown in Figure 24, the biological information collection device 500 has an input interface 510, a communication interface 530, a display 520, a memory circuit 540, and a processing circuit 550. The input interface 510, communication interface 530, display 520, and memory circuit 540 correspond to the input interface 110, communication interface 130, display 120, and memory circuit 140 of the information processing device 100 in Figure 2, respectively.

[0135] The processing circuit 550 controls the components of the biological information collection device 500. For example, the processing circuit 550 performs the acquisition function 551, the calculation function 552, the display control function 553, and the biological information collection function 600.

[0136] The biometric information collection function 600 collects the patient's biometric information and displays it on the display 520. The biometric information that can be collected by the biometric information collection function 600 includes, for example, heart rate, respiratory rate, blood pressure, electroencephalogram, electrocardiogram, electromyogram, and pulse wave. The acquisition function 551, calculation function 552, and display control function 553 correspond to the acquisition function 151, calculation function 152, and display control function 153 of the information processing device 100 in Figure 2, respectively.

[0137] It should be noted that the components of each device illustrated in this embodiment are functional concepts and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions. Furthermore, all or any part of the processing functions performed by each device can be realized by a CPU and a program that is analyzed and executed by the CPU, or by hardware using wired logic.

[0138] Furthermore, the method described in this embodiment can be implemented by executing a pre-prepared program on a computer such as a personal computer or workstation. This program can be distributed via a network such as the Internet. Alternatively, this program can be recorded on a computer-readable non-temporary recording medium such as a hard disk, flexible disk (FD), CD-ROM, MO, or DVD, and executed by reading it from the recording medium by a computer.

[0139] According to at least one embodiment described above, the efficiency of identification can be improved.

[0140] While several embodiments have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These embodiments can be implemented in a variety of other forms, and various omissions, substitutions, modifications, and combinations of embodiments are possible without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of Symbols]

[0141] 100 Information Processing Devices 120 displays 151 Acquisition function 152 Calculation Function 153 Display control function

Claims

1. An acquisition unit that acquires information about the patient's condition, Based on the information obtained, a calculation unit calculates indicators related to the occurrence of multiple diseases, A display control unit that displays indicators related to the occurrence of each of the aforementioned multiple diseases on the display unit, An information processing device equipped with the following features.

2. The acquisition unit sequentially acquires information regarding the patient's condition. The calculation unit updates the indicators related to the occurrence of the multiple diseases based on the sequentially acquired information. The display control unit sequentially updates the indicators related to the occurrence of each of the multiple diseases to be displayed on the display unit. The information processing apparatus according to claim 1.

3. The display control unit causes the display unit to display information regarding the priority of treatment, along with an indicator related to the occurrence of each of the multiple diseases. The information processing apparatus according to claim 1.

4. The display control unit causes the indicators relating to the occurrence of each of the multiple diseases, which are updated sequentially, to be displayed on the display unit in chronological order. The information processing apparatus according to claim 2.

5. The display control unit causes the display unit to display information on the information before and after the change in the judgment criteria used to calculate the indicators for a disease whose occurrence has changed over time. The information processing apparatus according to claim 4.

6. When the user specifies a disease whose indicators for occurrence have changed over time, the display control unit displays information on the display unit before and after the change in the information regarding the judgment criteria used to calculate the indicators for occurrence. The information processing apparatus according to claim 4.

7. The display control unit causes the display unit to display the indicators related to the occurrence of each of the multiple diseases, which are updated sequentially, in a time-series graph format. The information processing apparatus according to claim 2.

8. The display control unit causes the display unit to display information on the judgment criteria used to calculate an indicator for the occurrence of a disease specified by the user among the multiple diseases. The information processing apparatus according to claim 1.

9. The display control unit displays an indicator related to the occurrence of a disease among the plurality of diseases that meets predetermined conditions. The information processing apparatus according to claim 1.

10. The display control unit, in response to a user's request, causes the display unit to display information about diseases not currently shown. The information processing apparatus according to claim 9.

11. The display control unit, if there are findings using images in at least one of the multiple diseases, causes the display unit to display a statement indicating that there are findings using images in that disease. The information processing apparatus according to claim 1.

12. The display control unit, when ranking the multiple diseases based on an indicator of occurrence, adjusts the ranking based on the difference between the threshold value and the measured value related to the judgment criteria used to calculate the indicator of occurrence. The information processing apparatus according to claim 1.

13. Obtain information about the patient's condition, Based on the information obtained, indicators related to the occurrence of multiple diseases are calculated. The display unit displays indicators related to the occurrence of each of the aforementioned multiple diseases. Information processing methods that include the following.

14. Obtain information about the patient's condition, Based on the information obtained, indicators related to the occurrence of multiple diseases are calculated. The display unit displays indicators related to the occurrence of each of the aforementioned multiple diseases. A program that instructs a computer to perform a process.

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