Medical information processing device and medical information processing system

Abstract

To prevent overlook of medical examination information that needs to be checked.SOLUTION: A medical information processing apparatus according to the present embodiment comprises an acquisition unit, a calculation unit, and a display control unit. The acquisition unit acquires operation information on a medical worker for medical examination information on a target patient or medical examination information on a similar patient similar to the target patient. The calculation unit calculates, based on the operation information, the matching ratio between a period during which the medical examination information on the target patient or the medical examination information on the similar patient is referred to and a period during which the medical examination information on the target patient is displayed. The display control unit displays information on the matching ratio.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] In a hospital, for example, when a doctor checks the medical information of a target patient, the period for which the medical information of the target patient is displayed varies depending on the disease of the target patient, the purpose for viewing the medical information, etc. For example, if the doctor wants to check the effectiveness of the treatment of the target patient, the doctor sets the display period so that past medical information can be compared with current medical information, and in the case of an emergency, the doctor sets the display period so that the most recent medical information can be viewed. In this way, when checking each piece of medical information of a target patient, the doctor needs to set a display period for each piece of medical information. However, it is time-consuming for the doctor to set the display period. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2007-328678 [Patent Document 2] Japanese Patent Application Laid-Open No. 2009-157812 Summary of the Invention [Problem to be solved by the invention]

[0004] One of the problems that the embodiments disclosed in this specification and drawings aim to solve is to prevent overlooking of medical information that requires confirmation. However, the problems solved by the embodiments disclosed in this specification and drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0005] The medical information processing device according to this embodiment includes an acquisition unit, a calculation unit, and a display control unit. The acquisition unit acquires operation information of a medical professional with respect to the medical information of a target patient or the medical information of a similar patient similar to the target patient. The calculation unit calculates, based on the operation information, a match rate between a period during which the medical information of the target patient or the medical information of the similar patient is referenced and a period during which the medical information of the target patient is displayed. The display control unit displays information related to the match rate. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a medical information processing system including an electronic medical record server according to the first embodiment. [Figure 2] FIG. 2 is a flowchart showing the procedure of processing by the electronic medical record server according to the first embodiment. [Figure 3A] FIG. 3A is a flowchart showing the procedure of processing by the electronic medical record server according to the first embodiment. [Figure 3B] FIG. 3B is a flowchart showing the procedure of processing by the electronic medical record server according to the first embodiment. [Figure 4] FIG. 4 is a diagram for explaining the processing by the electronic medical record server according to the first embodiment. [Figure 5] FIG. 5 is a diagram for explaining the processing by the electronic medical record server according to the first embodiment. [Figure 6] FIG. 6 is a diagram for explaining the processing by the electronic medical record server according to the first embodiment. [Figure 7] FIG. 7 is a diagram for explaining the processing by the electronic medical record server according to the first embodiment. [Figure 8] FIG. 8 is a diagram for explaining the processing by the electronic medical record server according to the first embodiment. [Figure 9] FIG. 9 is a diagram for explaining the processing by the electronic medical record server according to the first embodiment. [Figure 10]FIG. 10 is a diagram for explaining the processing by the electronic medical record server according to the first modified example of the first embodiment. [Figure 11] FIG. 11 is a diagram for explaining the processing by the electronic medical record server according to the second modified example of the first embodiment. [Figure 12] FIG. 12 is a diagram for explaining the processing by the electronic medical record server according to the third modified example of the first embodiment. [Figure 13] FIG. 13 is a diagram for explaining the processing by the electronic medical record server according to the fourth modified example of the first embodiment. [Figure 14] FIG. 14 is a diagram for explaining the processing by the electronic medical record server according to the fifth modified example of the first embodiment. [Figure 15A] FIG. 15A is a diagram for explaining processing by the electronic medical record server according to the sixth modified example of the first embodiment. [Figure 15B] FIG. 15B is a diagram for explaining the processing by the electronic medical record server according to the sixth modified example of the first embodiment. [Figure 16] FIG. 16 is a flowchart showing the procedure of processing by the electronic medical record server according to the second embodiment. [Figure 17A] FIG. 17A is a flowchart showing the procedure of processing by the electronic medical record server according to the third embodiment. [Figure 17B] FIG. 17B is a flowchart showing the procedure of processing by the electronic medical record server according to the third embodiment. [Figure 18] FIG. 18 is a diagram for explaining the processing of the calculation function by the electronic medical record server according to the third embodiment. [Figure 19] FIG. 19 is a flowchart showing the procedure of processing by the electronic medical record server according to the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0007] Hereinafter, an embodiment of a medical information processing device will be described in detail with reference to the accompanying drawings. The following description will be given taking as an example a medical information processing system 1 including an electronic medical record server incorporating the functions of the medical information processing device. While the medical information processing system 1 shown in FIG. 1 shows one of each device, in reality, it may include multiple devices.

[0008] (First embodiment) Fig. 1 is a diagram showing an example of the configuration of a medical information processing system 1 including an electronic medical record server 100 according to the first embodiment. The medical information processing system 1 shown in Fig. 1 is a system including, for example, an electronic medical record system 2, a radiology information system (RIS), and a medical image management system (PACS: Picture Archiving and Communication System). The electronic medical record system 2 includes, for example, a hospital information system (HIS).

[0009] 1 includes an electronic medical record server 100, terminals 10 to 30, an HIS server, a RIS server, a medical image diagnostic device, and a PACS server (not shown). The electronic medical record server 100 has the functions of a medical information processing device.

[0010] The HIS server manages information generated within the hospital. Information generated within the hospital includes patient information, test order information, etc. When test order information is input from, for example, a terminal 10, the HIS server transmits the input test order information and patient information identified by the test order information to the RIS server. The RIS server manages test reservation information related to radiological testing services. A medical imaging diagnostic device is a device that performs tests based on test reservation information transmitted from, for example, the RIS server. For example, a clinical laboratory technician uses a medical imaging diagnostic device to perform tests by photographing a patient, and the medical imaging diagnostic device generates medical images during the test.

[0011] Examples of medical images include X-ray CT (Computed Tomography) images, X-ray images, MRI (Magnetic Resonance Imaging) images, nuclear medicine images, and ultrasound images. A medical image diagnostic apparatus converts generated medical images into a format that complies with, for example, the Digital Imaging and Communication in Medicine (DICOM) standard. That is, the medical image diagnostic apparatus generates medical images to which DICOM tags are added as incidental information. The incidental information includes, for example, a patient ID, an examination ID, an apparatus ID, an image series ID, and the like, and is standardized according to the DICOM standard. The medical image diagnostic apparatus transmits the generated medical images to a PACS server. The PACS server receives, for example, patient information transmitted from an HIS server and manages the received patient information. For example, the PACS server includes a memory circuit for managing patient information, receives medical images transmitted from the medical image diagnostic apparatus, and stores the received medical images in its own memory circuit in association with the patient information.

[0012] The terminals 10 to 30 are used by medical professionals involved in the medical treatment of patients. For example, the terminals 10 to 30 are used by doctors. The terminals 10 to 30 include, for example, PCs (Personal Computers), tablet PCs, PDAs (Personal Digital Assistants), mobile terminals, etc. A viewer (software) for displaying medical images on the terminals 10 to 30's own display is installed on the terminals 10 to 30.

[0013] As described above, the electronic medical record server 100 is incorporated into the electronic medical record system 2 together with the HIS server. The electronic medical record server 100 is communicably connected to terminals 10-30 via a network. The electronic medical record server 100 and terminals 10-30 are connected to an in-hospital LAN (Local Area Network) installed in a hospital, for example, and transmit information to predetermined devices and receive information transmitted from the predetermined devices. For example, the electronic medical record server 100 is realized by computer equipment such as a workstation or personal computer.

[0014] The electronic medical record server 100 has a processing circuit 110 and a memory circuit 120. The electronic medical record server 100 is not limited to the above-described configuration, and for example, the memory circuit 120 does not have to be built into the electronic medical record server 100 as long as the electronic medical record server 100 is accessible over a network.

[0015] The memory circuitry 120 is connected to the processing circuitry 110 and stores various types of information. Specifically, the memory circuitry 120 stores patient information received from each system. For example, the memory circuitry 120 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like.

[0016] The processing circuitry 110 controls the components of the electronic medical record server 100. For example, the processing circuitry 110 executes a processing function 111, a monitoring function 112, an acquisition function 113, a calculation function 114, and a control function 115. Here, for example, each function executed by the processing function 111, the monitoring function 112, the acquisition function 113, the calculation function 114, and the control function 115, which are components of the processing circuitry 110, is recorded in the storage circuitry 120 in the form of a program executable by a computer. The processing circuitry 110 is a processor that realizes the function corresponding to each program by reading and executing each program from the storage circuitry 120. In other words, the processing circuitry 110 in a state in which each program has been read will have each function shown in the processing circuitry 110 of FIG. 1.

[0017] The processing function 111 executes the functions of the electronic medical record system. Specifically, the processing function 111 stores in the memory circuitry 120 an electronic medical record that records patient information such as prescriptions, nursing records, and specimen tests administered to the patient.

[0018] Patient information includes basic information and medical information about the patient. Basic information includes the patient ID, name, date of birth, sex, blood type, height, weight, etc. Identification information that uniquely identifies the patient is set in the patient ID. Patient medical information includes information such as numerical values ​​(measurements) and medical records, as well as information indicating the date and time of recording. For example, patient medical information includes information such as medication prescriptions by doctors, nursing records by nurses, specimen tests sent to the testing department, and meal arrangements during hospitalization. For example, prescriptions are recorded in electronic medical records by doctors, and nursing records are recorded in electronic medical records by nurses.

[0019] The monitoring function 112, acquisition function 113, calculation function 114, and control function 115 execute the functions of the medical information processing device possessed by the electronic medical record server 100. A display application (program) is installed in the medical information processing device, and the display application can be read by the terminals 10 to 30. The processing of the monitoring function 112, acquisition function 113, calculation function 114, and control function 115 will be described later.

[0020] The storage circuitry 120 has, as databases (hereinafter simply referred to as DB), a medical information DB 121 and an operation information DB 122. The medical information DB 121 corresponds to, for example, the storage circuitry of an HIS server, and stores patient medical information or electronic medical records that record the patient medical information. The information stored in the operation information DB 122 will be described later.

[0021] The term "processor" used in the above description refers to a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). If the processor is a CPU, for example, the processor realizes its function by reading and executing a program stored in the memory circuit 120. On the other hand, if the processor is an ASIC, for example, the program is directly embedded in the processor circuit instead of storing the program in the memory circuit 120. Note that each processor in this embodiment is not limited to being configured as a single circuit, but may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, multiple components in FIG. 1 may be integrated into a single processor to realize its function.

[0022] The above has described the overall configuration of the medical information processing system 1 including the electronic medical record server 100 according to this embodiment. With this configuration, the electronic medical record server 100 prevents overlooking of medical information that requires confirmation.

[0023] In a hospital, for example, when a doctor checks the medical information of a target patient, the period for which the medical information of the target patient is displayed varies depending on the disease of the target patient, the purpose for viewing the medical information, etc. For example, when the doctor wants to check the effectiveness of treatment for the target patient, the doctor searches for each piece of medical information for the target patient and sets the display period from the date and time of the treatment to be compared to the current date and time in order to compare the target patient's past medical information with its current medical information. In addition, in the case of an emergency, the doctor sets the most recent period as the display period in order to check the target patient's most recent medical information. In addition, when the doctor is young or inexperienced, the display period may be set to a longer period.

[0024] The period for which the medical information of the target patient is displayed varies depending on the type of medical information. For example, when a doctor wants to check the medical information of specimen tests such as vital data or blood test results of the target patient, the doctor sets the display period to the period from the last medical examination date and time to the current date and time in order to compare the previous medical information of the target patient with the current medical information. Also, when a doctor checks information such as tumors of the target patient, the doctor may set the display period to a longer period.

[0025] In this way, when a doctor checks each piece of medical information of a target patient, the doctor needs to set a display period for each piece of medical information. However, it is time-consuming for the doctor to set a display period.

[0026] Therefore, the electronic medical record server 100 according to this embodiment performs the following process to prevent overlooking medical information that requires confirmation. First, in the electronic medical record server 100 according to this embodiment, the acquisition function 113 acquires operation information of the medical staff regarding the medical information of the target patient. Based on the acquired operation information, the calculation function 114 calculates the match rate between the period during which the medical information of the target patient was referenced and the period during which the medical information of the target patient is displayed, and the control function 115 displays information regarding the match rate.

[0027] Here, for example, if the acquisition function 113 cannot acquire operation information of a medical professional regarding the medical information of a similar patient whose illness, etc. is similar to that of the target patient, the acquisition function 113 acquires operation information of a medical professional regarding the medical information of a similar patient. In this case, the calculation function 114 calculates the match rate between the period during which the medical information of the similar patient was referenced and the period during which the medical information of the target patient is displayed based on the acquired operation information, and the control function 115 displays information regarding the match rate. Below, an example will be described in which operation information of a medical professional regarding the medical information of the target patient is acquired.

[0028] FIG. 2 is a flowchart showing the procedure of processing by the electronic medical record server 100 according to the first embodiment.

[0029] Step S101 in FIG. 2 is a step in which the processing circuitry 110 calls up a program corresponding to the monitoring function 112 from the storage circuitry 120 and executes the program. In step S101, the monitoring function 112 executes a storage process. For example, the monitoring function 112 monitors the operations of the terminals 10 to 30 of doctors who are medical professionals, and stores a log of the operations on the patient's medical information as operation information in the operation information DB 122. Specifically, the monitoring function 112 monitors the operations of multiple doctors in each department, and stores the contents of the operations by the doctors on the patient's medical information and the date and time when the operations were performed as operation information in the operation information DB 122. Because the monitoring function 112 monitors the operations (behaviors) of the doctors, the operation information collected by the monitoring function 112 is also referred to as behavior data representing the doctors' behavior.

[0030] Here, for example, the operation information includes, as the details of the doctor's operations, the time the doctor referred to the medical information and the history of when the doctor accessed the medical information. The time the doctor referred to the medical information can be a click operation or a gaze time measured by eye tracking. For example, each of the terminals 10 to 30 is provided with a camera that captures an image of the doctor operating the terminal, and in step S101, the monitoring function 112 analyzes the image captured by the camera to measure the doctor's line of sight (eye tracking) and collects the gaze time measured by eye tracking.

[0031] 2 is a step in which the processing circuitry 110 calls and executes programs corresponding to the acquisition function 113, the calculation function 114, and the control function 115 from the memory circuitry 120. In step S102, the acquisition function 113, the calculation function 114, and the control function 115 execute the display process shown below.

[0032] First, the processing of the electronic medical record server 100 according to the first embodiment will be described with reference to Figures 3 to 15. Figures 3A and 3B are flowcharts showing the procedure of processing by the electronic medical record server 100 according to the first embodiment.

[0033] In step S110 of Fig. 3A, the acquisition function 113 of the electronic medical record server 100 acquires the medical information of the target patient registered in the medical information DB 121. For example, when a doctor operating the terminal 10 checks the medical information of the target patient, the doctor uses the terminal 10 to perform a search using a patient ID or the like, and the acquisition function 113 acquires the medical information of the target patient up to the current date and time for each item from the medical information DB 121. Here, examples of the items include specimen testing, medication using various drugs, and tests using medical images.

[0034] In step S111 of Figure 3A, the acquisition function 113 of the electronic medical record server 100 acquires operation information of the doctor for the medical information of the target patient acquired for each item. The operation information acquired by the acquisition function 113 is information operated by multiple doctors in each medical department. The acquisition function 113 is an example of an "acquisition unit."

[0035] In step S112 of FIG. 3A, the calculation function 114 of the electronic medical record server 100 calculates, for each item, based on the operation information, the agreement rate between the period during which the medical information of the target patient was referenced and the period during which the medical information of the target patient is displayed. For example, the calculation function 114 determines the display period as a period beginning with the date and time at which the agreement rate is greatest and ending with the current date and time. The method for calculating the agreement rate and the method for determining the display period will be described later. The calculation function 114 is an example of a "calculation unit."

[0036] In step S113 of Figure 3A, the control function 115 of the electronic medical record server 100 selects one or more items to be displayed on the doctor's terminal 10. The method for selecting items will be described later. The control function 115 is an example of a "selection unit."

[0037] In step S114 of Figure 3A, the control function 115 of the electronic medical record server 100 causes information relating to the match rate for each item to be displayed on the doctor's terminal 10. Specifically, the control function 115 causes the doctor's terminal 10 to display medical information for the determined display period as information relating to the match rate for each selected item. The control function 115 is an example of a "display control unit."

[0038] 3B, step S112 may be executed after step S113 is executed. In this case, the control function 115 selects one or more items to be displayed on the doctor's terminal 10, and then the calculation function 114 calculates the matching rate for each selected item based on the operation information and determines the display period.

[0039] Next, the processing by the electronic medical record server 100 according to the first embodiment will be explained using a specific example.

[0040] FIG. 4 shows an example of a physician's operation information for the medical information of a target patient acquired by the acquisition function 113 for each item. The operation information includes the physician's operation details, such as the time the physician referenced the medical information. In FIG. 4, the operation information includes, for example, a click operation and gaze time measured by eye tracking. In the example shown in FIG. 4, the operation information includes the medical information items "CT image," "CT image," "specimen test," and "CT image," the occurrence dates of each item (2020 / 5 / 1," "2020 / 4 / 15," "2020 / 4 / 20," and "2020 / 3 / 19"), and the gaze times for each item (5.2 seconds," "3.2 seconds," "0.8 seconds," and "0.2 seconds"). Here, the occurrence dates refer to the date and time when each item ("CT image," "CT image," "specimen test," and "CT image") was registered in the medical information DB 121. The gaze time refers to the time the physician referenced each item ("CT image," "CT image," "specimen test," and "CT image") as medical information. The calculation function 114 performs a reference determination of the operation information for the gaze times of "5.2 seconds," "3.2 seconds," "0.8 seconds," and "0.2 seconds" for each item. For example, if the threshold is "2 seconds" and the time the doctor referred to the medical information is "2 seconds" or longer, the calculation function 114 generates a reference determination of the operation information of "○" as information indicating that the doctor referred to the medical information. On the other hand, if the time the doctor referred to the medical information is less than "2 seconds," the calculation function 114 generates a reference determination of the operation information of "×" as information indicating that the doctor did not refer to the medical information. In the example shown in FIG. 4, the calculation function 114 generates a reference determination of the operation information of "○," "○," "×," and "×" for the gaze times of "5.2 seconds," "3.2 seconds," "0.8 seconds," and "0.2 seconds," respectively.

[0041] FIG. 5 shows an example of operation information of a doctor for the medical information of a target patient acquired by the acquisition function 113 for each item. The operation information includes a history of when the doctor accessed the medical information as the content of the doctor's operations. In FIG. 5, the operation information is an access history. In the example shown in FIG. 5, the operation information includes the medical information items "electrocardiogram," "MRI image," "MRI report," and "specimen test," the occurrence dates of each item "2020 / 5 / 1," "2020 / 4 / 15," "2020 / 4 / 20," and "2020 / 3 / 10," and the accesses of each item "yes," "yes," "no," and "no." Here, the occurrence dates refer to the dates and times when each item "electrocardiogram," "MRI image," "MRI report," and "specimen test" was registered in the medical information DB 121. The accesses refer to the history of when the doctor accessed each item "electrocardiogram," "MRI image," "MRI report," and "specimen test" as medical information. The calculation function 114 performs a reference determination of the operation information for each item's access "yes," "yes," "no," and "no." For example, when a doctor is accessing the medical information, the calculation function 114 generates a reference judgment of "o" for the operation information as information indicating that the doctor has referenced the medical information. On the other hand, when the doctor is not accessing the medical information, the calculation function 114 generates a reference judgment of "x" for the operation information as information indicating that the doctor has not referenced the medical information. In the example shown in FIG. 5, the calculation function 114 generates "o", "o", "x", and "x" as reference judgments for the operation information for the accesses of each item "o", "o", "x", and "x", respectively.

[0042] In the example shown in Fig. 4, the acquisition function 113 can strictly determine whether or not the doctor has referred to the medical information by using click operations and eye tracking. Also, in the example shown in Fig. 5, the acquisition function 113 can determine whether or not the doctor has referred to the medical information by using an existing log collection function such as a click operation.

[0043] Fig. 6 is another example of the medical information of a target patient acquired for the item "specimen testing" by the acquisition function 113. The example shown in Fig. 6 shows the medical information acquired when the acquisition function 113 acquired the medical information of the target patient for the item "specimen testing", from the date and time "2020 / 5 / 8" to the current date and time "2020 / 7 / 10". Here, the period from the date and time "2020 / 5 / 8" to the current date and time "2020 / 7 / 10" is the display candidate period. Then, the calculation function 114 generates "x", "x", "o", "o", "o", "o", "o", "o", "o", "o", "o", "o", and "o" as the reference judgment of the operation information for the occurrence dates of the item "specimen test" of "2020 / 5 / 8", "2020 / 5 / 15", "2020 / 5 / 22", "2020 / 5 / 29", "2020 / 6 / 5", "2020 / 6 / 12", "2020 / 6 / 19", "2020 / 6 / 26", "2020 / 7 / 3", and "2020 / 7 / 10", respectively. In this case, of the display candidate period "2020 / 5 / 8 to 2020 / 7 / 10", the period for which the reference judgment of the operation information is "o" is "2020 / 5 / 22" to "2020 / 7 / 10". Here, when the calculation function 114 calculates the match rate between the period during which the medical information of the target patient was referenced and the period during which the medical information of the target patient is displayed for the item "specimen testing" based on the operation information, the date and time at which the match rate is highest is "2020 / 5 / 22." For example, the calculation function 114 determines, as the display period, the display candidate period of "2020 / 5 / 22-2020 / 7 / 10," with "2020 / 5 / 22" as the start date and "2020 / 7 / 10" as the end date, with "2020 / 5 / 22" as the end date and the current date and time. That is, the calculation function 114 adjusts the display period from "2020 / 6 / 19" to "2020 / 5 / 22" to "2020 / 7 / 10" so that the start date and time of the display period becomes "2020 / 5 / 22" as the date and time at which the match rate is highest.

[0044] 7 is a diagram for explaining a method for calculating the matching rate. The calculation function 114 calculates the matching rate by calculating the precision rate and the recall rate from past reference decisions.

[0045] The precision, for example, represents an index of how much of the medical information referred to by a doctor is included in the acquired medical information of a patient. For example, the precision (Precision) is the ratio of the value "R", which is the number of pieces of medical information referred to among the medical information included in the display candidate period, to the value "N", which is the number of pieces of medical information included in the display candidate period among the acquired medical information, and is calculated as Precision = R / N. For example, the value "R" represents the number of pieces of medical information referred to by the doctor among the value "N" that have a reference judgment of "○". Note that the value "N" is an example of a "first value", and the value "R" is an example of a "second value".

[0046] The recall rate represents, for example, an index of how comprehensively the medical information referred to by a doctor is displayed. For example, the recall rate is the ratio of the value "R" to the value "C," which is the number of pieces of medical information referred to among the acquired medical information, and is calculated as Recall = R / C. For example, the value "C" represents the number of pieces of acquired medical information for which the reference judgment is "○." The value "R" is an example of a "third value."

[0047] To increase recall (R / C), the display candidate period can be lengthened to increase R, i.e., N can be increased, but in this case precision (R / N) will decrease. As recall and precision are in a trade-off relationship, the calculation function 114 calculates the F value, which is the harmonic mean of precision and recall, as the match rate. The F value is calculated as F = (2 × precision × Recall) / (precision + Recall) = 2R / (N + C).

[0048] Here, the calculation function 114 calculates the F-number for multiple display candidate periods and determines the display period based on the display candidate period with the largest F-number. In the example shown in Fig. 6, the calculation function 114 determines the display candidate period with the largest F-number, "2020 / 5 / 22 to 2020 / 7 / 10", as the display period.

[0049] For example, the calculation function 114 calculates the F value for each item based on the operation information. In the example shown in Fig. 8, the calculation function 114 determines the display candidate period "2020 / 6 / 10 to 2020 / 7 / 10", which has the highest F value, for the medical information "Ca (Calcium)" and "White Blood Cells" of the item "Specimen Test", as the display period. In this example, the date and time from immediately after discharge from the hospital to the present is determined as the display period.

[0050] Furthermore, the calculation function 114 determines, as the display period, the display candidate period "2020 / 4 / 10 to 2020 / 7 / 10" that includes the date and time with the maximum F value in the medical information "Drug A" to "Drug D" of the item "Drug Administration Date and Time." In this example, the date and time from post-surgery through discharge from hospital to the present is determined as the display period.

[0051] The calculation function 114 is also applicable to examinations using medical images, and determines the two dates and times "2020 / 3 / 18" and "2020 / 6 / 20" when the F-value reaches its maximum (peak) in the item "CT image" as the display period. In this example, the date and time before surgery and the date and time after discharge are determined as the display period.

[0052] In this way, the calculation function 114 determines an appropriate display period that a doctor is likely to want to check for each different type of medical information.

[0053] Here, the control function 115 of the electronic medical record server 100 selects one or more items to be displayed on the doctor's terminal 10. For example, the doctor operating the terminal 10 may select the items, or items frequently referenced by the doctor may be selected with priority. Alternatively, the selected items may be obtained by inputting information such as the disease of the target patient into a trained model obtained by machine learning. For example, based on performance data from which the doctor selected items, the items frequently referenced by the doctor are identified, and a trained model is generated by learning using the performance data. The control function 115 identifies the items by inputting information such as the disease of the target patient into the trained model.

[0054] Then, the control function 115 causes the doctor's terminal 10 to display the medical information for the display period determined by the calculation function 114 for each selected item. In the example shown in Fig. 9, the control function 115 causes the terminal 10 to display the medical information for the display period "2020 / 6 / 19 to 2020 / 7 / 10" determined by the calculation function 114 as the medical information "Ca" and "white blood cells" for the item "specimen testing". The control function 115 also causes the terminal 10 to display the medical information for the display period "2020 / 6 / 10 to 2020 / 7 / 10" determined by the calculation function 114 as the medical information "γ-GTP (γ-Glutamyl TransPeptidase)" and "CEA (carcinoembryonic antigen)" for the item "specimen testing". Furthermore, the control function 115 causes the terminal 10 to display, as medical information "Drug A" to "Drug D" for the item "Drug administration date and time", medical information for the display period "2020 / 4 / 10 to 2020 / 7 / 10" determined by the calculation function 114. Furthermore, in an examination using medical images, the control function 115 causes the terminal 10 to display, as the item "CT image", CT images for the dates and times "2020 / 3 / 18" and "2020 / 6 / 20" determined by the calculation function 114.

[0055] As a first modified example, the calculation function 114 may determine a period with a high number of references within the determined display period as the important period, and the control function 115 may display the granularity of the important period within the display period determined by the calculation function 114 at a larger value. For example, the calculation function 114 may determine, as the display period, the candidate display period "June 10, 2020 to July 10, 2020" that resulted in the highest F-value for the medical information "Ca" and "white blood cells" of the item "specimen testing." Here, the calculation function 114 determines, as the important period, a period during which the medical information "Ca" and "white blood cells" were frequently referenced by doctors within the display period "June 10, 2020 to July 10, 2020" determined by itself. For example, within the display period "June 10, 2020 to July 10, 2020," the number of references exceeds a set number during the period "June 30, 2020 to July 10, 2020." In this case, the calculation function 114 determines the period "2020 / 6 / 30 to 2020 / 7 / 10" as the important period, and the control function 115 displays the details of the important period "2020 / 6 / 30 to 2020 / 7 / 10" on the doctor's terminal 10 so that the doctor can understand them, for example, by increasing the granularity of the important period "2020 / 6 / 30 to 2020 / 7 / 10" within the display period "2020 / 6 / 10 to 2020 / 7 / 10," as shown in Figure 10. For example, the control function 115 displays the details of the important period on the doctor's terminal 10 so that the doctor can understand them, by increasing the size per day of the horizontal axis showing the display period "2020 / 6 / 10 to 2020 / 7 / 10" by the amount of the important period "2020 / 6 / 30 to 2020 / 7 / 10."

[0056] Furthermore, in the above-described embodiment, the calculation function 114 determines the display candidate period with the largest F-value as the display period. However, in a second modified example, the calculation function 114 may determine the display candidate period including the date and time when the F-value is largest as the display period. In the example shown in FIG. 11 , for the item "specimen testing," the calculation function 114 determines the display candidate period "2020 / 6 / 19 to 2020 / 7 / 10" as the display period, starting from the date and time when the F-value is largest, "2020 / 6 / 19," and ending at the current date and time, "2020 / 7 / 10." Here, since the period "2020 / 6 / 19 to 2020 / 7 / 10" is information after the target patient is discharged from the hospital, in order to include information after surgery of the target patient, the display candidate period "2020 / 5 / 15 to 2020 / 7 / 10," which includes the date and time when the F-value is largest, is determined as the display period. That is, the calculation function 114 adjusts the start point so that it includes the date and time "2020 / 6 / 19" when the F value is maximum, and determines the display period to be "2020 / 5 / 15" to "2020 / 7 / 10". In this case, the control function 115 causes the medical information for the display period "2020 / 5 / 15 to 2020 / 7 / 10" determined by the calculation function 114 to be displayed on the doctor's terminal 10.

[0057] Furthermore, in the second modified example, the calculation function 114 adjusts the starting point, but in the third modified example, the calculation function 114 may adjust both the starting point and the ending point. In the example shown in FIG. 12, if the medical information "Drug E" in the item "Drug Administration Date and Time" has a history of administration of "Drug E," the calculation function 114 includes the date and time when the F value is maximum during the period when "Drug E" was administered. In this case, the calculation function 114 adjusts both the starting point and the ending point to calculate the F value for multiple periods from the starting point to the ending point, and determines the period among the multiple periods with the maximum F value as the display period. In this way, the calculation function 114 determines the past period including the date and time when the F value is maximum as the display period. In this case, the control function 115 displays the medical information for the display period determined by the calculation function 114 on the doctor's terminal 10.

[0058] In addition, in the third modified example, the calculation function 114 determines, as the display period, a past period including the date and time when the F value is maximum, but in the fourth modified example, the calculation function 114 may determine, as the display period, a past period including the date and time when the F value is maximum (peak), or a period including the date and time when the F value is maximum and the current date and time. In the example shown in Fig. 13, the calculation function 114 determines, as the display period, multiple display candidate periods "2020 / 3 / 10 to 2020 / 4 / 10" and "2020 / 6 / 10 to 2020 / 7 / 10" that include the date and time when the F value is maximum for the medical information "Ca" and "white blood cells" of the item "specimen testing". In this case, the control function 115 causes the doctor's terminal 10 to display the medical information "Ca" and "white blood cells" for the display period "2020 / 3 / 10 to 2020 / 4 / 10" and the medical information "Ca" and "white blood cells" for the display period "2020 / 6 / 10 to 2020 / 7 / 10".

[0059] 14, the calculation function 114 determines the display period based on the relevance of the subitems. For example, as shown in the left side of Fig. 14, the calculation function 114 determines the display period as the clinical information for the item "specimen test" for the subitems "Ca" and "white blood cells", starting from the date and time "2020 / 6 / 19" when the F value is maximum and ending at the current date and time "2020 / 7 / 10", and determines the display period as the clinical information for the subitems "γ-GTP" and "CEA", starting from the date and time "2020 / 6 / 5" when the F value is maximum and ending at the current date and time "2020 / 7 / 10". Here, for example, if the correlation between the sub-items is high because the temporal fluctuations of the sub-items "Ca" and "white blood cells" are similar to the temporal fluctuations of the sub-items "γ-GTP" and "CEA" as medical information, the calculation function 114 selects "2020 / 6 / 5 to 2020 / 7 / 10", which is the longest display period. In this case, the control function 115 displays the medical information "Ca", "white blood cells", "γ-GTP", and "CEA" for the display period "2020 / 6 / 5 to 2020 / 7 / 10" on the doctor's terminal 10.

[0060] On the other hand, if the correlation between the subitems is low, for example, because the temporal fluctuations of the subitems "Ca" and "white blood cells" are not similar to the temporal fluctuations of the subitems "γ-GTP" and "CEA" as medical information, the calculation function 114 does not select a display period. In this case, as shown on the right side of Figure 14, the control function 115 divides the medical information into the medical information "Ca" and "white blood cells" for the display period "2020 / 6 / 19 to 2020 / 7 / 10" and the medical information "γ-GTP" and "CEA" for the display period "2020 / 6 / 5 to 2020 / 7 / 10", and displays the medical information on the doctor's terminal 10.

[0061] As a sixth modified example, the calculation function 114 may determine the display period using not only the period but also the number of references (views). For example, as shown in FIG. 15A, if the number of references at which the F-value is maximized is 1.5 for the medical information of the item "specimen test," the calculation function 114 determines, as the display period, a candidate display period that includes the date and time at which the F-value is maximized and the number of references is 1.5 or more. The calculation function 114 may determine the display period using machine learning. For example, as shown in FIG. 15B, machine learning is used to determine a ranking of each item in descending order of the frequency with which the medical information of the target patient is displayed. For example, if the item "specimen test" is ranked fourth with the largest F-value, the calculation function 114 determines, as the display period, a candidate display period that includes the date and time at which the F-value is maximized for the item "CT scan," ranked fifth.

[0062] As described above, in the electronic medical record server 100 according to the first embodiment, the acquisition function 113 acquires operation information of a doctor regarding the medical information of a target patient or the medical information of a similar patient. Based on the operation information, the calculation function 114 calculates an F value, which is the rate of agreement between the target patient's medical information or the period during which the target patient's medical information was referenced and the period during which the target patient's medical information is displayed, and the control function 115 displays information regarding the F value. Specifically, the calculation function 114 determines a period beginning with the date and time at which the F value is maximized and ending with the current date and time as the display period, and the control function 115 displays the medical information for the display period determined by the calculation function 114. Alternatively, the calculation function 114 determines a period including the date and time at which the F value is maximized as the display period, and the control function 115 displays the medical information for the display period determined by the calculation function 114. This prevents the electronic medical record server 100 according to the first embodiment from overlooking medical information that requires confirmation.

[0063] (Second embodiment) In the second embodiment, the acquisition function 113 identifies a medical scene of the target patient and acquires operation information of the doctor regarding the medical information of the target patient according to the identified medical scene. For example, the medical scene includes information about the disease of the target patient. The information about the disease includes the name of the disease, the disease location, the treatment method, etc. For example, the medical scene includes medical phases, which are periods separated by events. For example, the medical phases include the period from the first consultation to hospitalization, the period from hospitalization to surgery, the period from surgery to discharge, etc.

[0064] FIG. 16 is a flowchart showing the processing procedure of the electronic medical record server according to the second embodiment. In the second embodiment, in step S200 of FIG. 16, the acquisition function 113 identifies the medical scene of the target patient by referring to the patient's medical information registered in the medical information DB 121. Then, steps S110 to S114 in the first embodiment are executed. In this case, in steps S110 and S111, the acquisition function 113 acquires the patient's medical information for each item from the medical information DB 121 according to the identified medical scene, and acquires operation information of the doctor regarding the patient's medical information. In step S112, the calculation function 114 calculates an F value for the medical information of the target patient based on the operation information, and determines a display period using the calculated F value. In steps S113 and S114, the control function 115 selects items to be displayed on the doctor's terminal 10 and displays the medical information for the determined display period for each selected item on the terminal 10.

[0065] In the second embodiment, the acquisition function 113 can acquire operation information (behavioral data) of a doctor according to a medical situation. For example, in step S110, the acquisition function 113 acquires medical information of a target patient. Furthermore, in step S110, the acquisition function 113 acquires medical information of a similar patient who was in a medical situation similar to the medical situation identified in step S200 and was treated by the doctor in charge of the target patient. Then, in step S111, the acquisition function 113 acquires operation information performed on the similar patient by the doctor in charge of the target patient. Note that there may be one or more similar patients. Then, in step S112, the calculation function 114 determines a display period for the target patient based on the operation information performed on the similar patient. For example, the calculation function 114 determines a display period for the target patient by applying the period determined for the similar patient to the target patient. This allows the calculation function 114 to determine a display period according to the preference of the doctor in charge of the target patient.

[0066] Alternatively, the target similar patients in the above example may be similar patients who have been in a medical situation similar to the medical situation identified in step S200, and may be similar patients who have been treated by the doctor in charge of the target patient or by doctors with the same attributes as the doctor in charge. This allows the calculation function 114 to determine the display period according to the preferences of the group to which the doctor in charge of the target patient belongs.

[0067] Alternatively, the target similar patient in the above example may be a similar patient who encountered a similar medical situation to the medical situation identified in step S200 and who was treated by a doctor with any attribute. Here, attributes include junior, experienced, and specialist. For example, the calculation function 114 determines the display period of the experienced doctor, and the control function 115 can provide the junior doctor with educational information about the period the experienced doctor refers to when making a diagnosis. In other words, by comparing the display period of the junior doctor with that of the experienced doctor, the junior doctor can identify areas for improvement. Furthermore, the calculation function 114 determines the display period of the specialist, and the control function 115 can provide the specialist with a unique perspective.

[0068] Furthermore, in the second embodiment, a medical department may be used as an attribute. For example, if the target patient has a highly urgent disease, the acquisition function 113 acquires medical information and operation information of similar patients with the highly urgent disease in step S111, and the calculation function 114 can determine a display period suitable for the patient with the highly urgent disease in step S112. For example, a display period for displaying the most recent medical information is determined for the target patient with the highly urgent disease. On the other hand, if the target patient has a chronic disease, the acquisition function 113 acquires medical information and operation information of similar patients with the chronic disease in step S111, and the calculation function 114 can determine a display period suitable for the patient with the chronic disease in step S112. For example, a display period for displaying long-term medical information is determined for the target patient with the chronic disease.

[0069] Furthermore, in the second embodiment, depending on the medical situation, it is possible to acquire operation information according to the patient's condition. For example, if the target patient has a sudden symptom, the acquisition function 113 acquires the medical information and operation information of a similar patient who had a sudden symptom in step S111, and the calculation function 114 can determine a display period suitable for the patient with the sudden symptom in step S112. For example, for a target patient with a sudden symptom, a display period for displaying the most recent medical information is determined.

[0070] Furthermore, in the second embodiment, depending on the medical situation, operation information according to the patient's location can be acquired. For example, when the target patient is an outpatient, the acquisition function 113 acquires medical information and operation information of similar patients performed during outpatient treatment in step S111, and the calculation function 114 can determine a display period suitable for the outpatient patient in step S112. For example, for outpatient patients, a display period for displaying long-term medical information is determined. On the other hand, when the target patient is hospitalized, the acquisition function 113 acquires medical information and operation information of similar patients performed during medical treatment during hospitalization in step S111, and the calculation function 114 can determine a display period suitable for the hospitalized patient in step S112. For example, for hospitalized patients, a display period for displaying the most recent medical information is determined.

[0071] In this way, the electronic medical record server 100 according to the second embodiment can determine the display period according to the medical treatment scene.

[0072] (Third embodiment) A doctor may refer to a combination of various pieces of medical information. For example, the doctor may administer a drug to a patient while taking into consideration the patient's symptoms, and check the effectiveness and side effects of the drug. Therefore, in the third embodiment, the calculation function 114 calculates an F value by combining the medical information of the patient acquired for each item, and determines the display period using the calculated F value.

[0073] FIG. 17A is a flowchart showing the processing steps performed by the electronic medical record server according to the third embodiment. In the third embodiment, after steps S110 to S111 in the first embodiment are executed, in step S300 in FIG. 17A, the calculation function 114 determines a combination of the clinical information of the target patient acquired for each item. In the example shown in FIG. 18, in step S300, the calculation function 114 determines a combination of the clinical information "Ca" and "white blood cell count" in the item "specimen testing" and the clinical information "drug C" and "drug D" in the item "drug administration date and time" based on the start of chemotherapy. In step S112, the calculation function 114 determines the display candidate period "2020 / 5 / 25 to 2020 / 7 / 10," which includes the date and time when chemotherapy started, "2020 / 6 / 10," as the display period. Thereafter, steps S112 to S114 in the first embodiment are executed.

[0074] Here, as shown in FIG. 17B, after steps S110, S111, and S113 in the first embodiment are executed, step S300 may be executed, and then steps S112 and S114 in the first embodiment may be executed.

[0075] In this way, the electronic medical record server 100 according to the third embodiment can determine the display period taking into consideration the combination of medical information.

[0076] (Fourth embodiment) A doctor may want to check the past symptoms and treatment history of a target patient or a similar patient whose disease, etc., is similar to that of the target patient. Therefore, in the fourth embodiment, a display target period is determined using a past behavior pattern, and the calculation function 114 determines the display period from the determined display target period. In this case, the display target period may be determined by the doctor, or the acquisition function 113 may determine the display target period. For example, the display target period is a period in which medical information was frequently referenced in the past by click operations, eye tracking, access history, etc.

[0077] FIG. 19 is a flowchart showing the processing steps performed by the electronic medical record server according to the fourth embodiment. In the fourth embodiment, in step S400 of FIG. 19, for example, the acquisition function 113 determines the display target period based on click operations, eye tracking, access history, etc. Then, steps S110 to S114 in the first embodiment are executed. In this case, in steps S110 and S111, the acquisition function 113 acquires the medical information of the target patient for each item during the determined display target period from the medical information DB 121 and acquires operation information of the doctor regarding the medical information of the target patient. In step S112, the calculation function 114 calculates an F value for the medical information of the target patient based on the operation information and determines the display period using the calculated F value. In steps S113 and S114, the control function 115 selects items to be displayed on the doctor's terminal 10 and displays the medical information for the determined display period for each selected item on the terminal 10.

[0078] In this way, the electronic medical record server 100 according to the fourth embodiment can determine the display period taking into consideration the past symptoms and treatment history of the target patient or similar patients.

[0079] Note that the components of each device illustrated in the first to fourth embodiments are conceptual functional units and do not necessarily have to be physically configured as illustrated. That is, the specific form of distribution and integration of each device is not limited to that illustrated, and all or part of the devices can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Furthermore, all or any part of the processing functions performed by each device can be realized by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0080] The methods described in the first to fourth embodiments can be realized by executing a prepared program on a computer such as a personal computer or a workstation. This program can be distributed via a network such as the Internet. This program can also be recorded on a non-transitory computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and executed by being read from the recording medium by a computer.

[0081] According to at least one of the embodiments described above, it is possible to prevent overlooking medical information that requires confirmation.

[0082] Although several embodiments 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 spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0083] 100 Electronic Medical Record Server 113 Acquisition Function 114 Calculation Function 115 Control Functions

Claims

1. an acquisition unit that acquires operation information of a medical professional with respect to medical information of a target patient or medical information of a similar patient similar to the target patient; a calculation unit that calculates a coincidence rate between a period during which the medical information of the target patient or the medical information of the similar patient is referenced and a period during which the medical information of the target patient is displayed, based on the operation information; a display control unit that displays medical information for a period determined based on the match rate; A medical information processing device comprising:

2. the calculation unit determines a period starting from the date and time at which the match rate is greatest and ending at the current date and time as a display period; The display control unit displays medical information for the display period. The medical information processing device according to claim 1 .

3. the calculation unit determines a period including a date and time when the matching rate is greatest as a display period; The display control unit displays medical information for the display period. The medical information processing device according to claim 1 .

4. the calculation unit calculates the matching rate for a plurality of periods by adjusting both the starting point and the ending point, and determines, from among the plurality of periods, a period with the highest matching rate as a display period; The display control unit displays medical information for the display period. The medical information processing device according to claim 1 .

5. the calculation unit determines, as a display period, a plurality of periods including a date and time when the matching rate is at a maximum; The display control unit displays medical information for the display period. The medical information processing device according to claim 1 .

6. The calculation unit determines, within the determined display period, a period in which the medical information of the target patient or the medical information of the target patient is frequently referenced as an important period; the display control unit displays the important period with a larger granularity within the display period; The medical information processing device according to any one of claims 2 to 5.

7. The calculation unit calculates, as the matching rate, a harmonic mean of a ratio of a second value, which is the number of pieces of medical information referenced in the medical information included in the display candidate period, to a first value, which is the number of pieces of medical information included in the acquired medical information, and a ratio of the second value to a third value, which is the number of pieces of medical information referenced in the acquired medical information. The medical information processing device according to any one of claims 1 to 6.

8. the calculation unit determines the display period based on the display candidate period with the highest matching rate among the matching rates calculated for the plurality of display candidate periods; The display control unit displays medical information for the display period. The medical information processing device according to claim 7 .

9. the acquisition unit acquires the operation information for the medical information of the target patient acquired for each item or the medical information of the similar patient acquired for each item, the calculation unit calculates the match rate for each of the items based on the operation information; the display control unit displays, for each of the items, medical information for a period determined based on the matching rate; The medical information processing device according to any one of claims 1 to 8.

10. a selection unit for selecting an item for displaying medical information for a period determined based on the match rate; The medical information processing apparatus according to claim 9 , further comprising:

11. the calculation unit calculates the match rate by combining the medical information of the target patient acquired for each item. The medical information processing device according to claim 9 or 10.

12. the acquisition unit acquires the operation information according to a medical scene. The medical information processing device according to any one of claims 1 to 11.

13. The medical scene includes information about the disease of the target patient, The medical information processing device according to claim 12 .

14. The medical scene includes a medical phase separated by an event, The medical information processing device according to claim 12 or 13.

15. The operation information includes, as the content of the operation by the medical worker, a time when the medical worker referred to the medical information. The medical information processing device according to any one of claims 1 to 14.

16. The operation information includes, as the content of the operation by the medical worker, a history of when the medical worker accessed the medical information. The medical information processing device according to any one of claims 1 to 14.

17. The operation information is information operated by a plurality of medical professionals of each medical department. The medical information processing device according to any one of claims 1 to 16.

18. Multiple devices used by multiple medical professionals; a medical information processing device connected to the plurality of terminals via a network; Equipped with The medical information processing device includes: an acquisition unit that acquires operation information of the medical staff regarding medical information of a target patient or medical information of a similar patient similar to the target patient; a calculation unit that calculates a coincidence rate between a period during which the medical information of the target patient or the medical information of the similar patient is referenced and a period during which the medical information of the target patient is displayed, based on the operation information; a display control unit that displays medical information for a period determined based on the match rate; A medical information processing system comprising:

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