Medical information processing device, medical information processing method, and program

Abstract

To provide support by supplying cultured organs to subjects at the time they need them. [Solution] The medical information processing device according to this embodiment acquires medical information, performs organ simulation to predict changes in the state of the patient's organs related to the disease, including at least one of changes in an indicator related to organ size and changes in an indicator related to organ function, calculates the time required for transplantation, acquires culture information related to the patient's organ culture, including at least one of the proliferation characteristics of cells related to organ culture and the progress of organ culture, calculates an organ culture schedule based on the organ simulation and the culture information, including a start time to begin organ culture, a predicted completion time when organ culture is completed, and a storage period during which the cultured organs can be stored in a state suitable for transplantation, and presents the results of the organ simulation, information representing the time required for transplantation, and the culture schedule together.

Description

Technical Field

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

Background Art

[0002] In recent years, there has been an increasing interest in regenerative medicine (cell therapy). For example, there have been numerous studies on the use of stem cells such as ES cells and iPS cells related to regenerative medicine, cloning, organ culture, etc. It is also said that in the future, a service will be provided to create nerve cells and organs by culturing iPS cells created from the patient's own cells and providing them to the patient at the necessary time.

[0003] However, it takes time until nerve cells and organs can be cultured and used for treatment. Therefore, in order to provide an organ cultured at the time required by the patient, a technology that can plan for organ provision according to the situation of each patient is demanded.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to assist in providing an organ cultured at the time required by the subject. However, the problems solved by the embodiments disclosed in this specification and the drawings are not limited to the above problems. The problems corresponding to the respective effects of each configuration shown in the embodiments described later can also be regarded as other problems.

Means for Solving the Problems

[0006] The medical information processing device according to this embodiment comprises a first acquisition unit, a first calculation unit, a second acquisition unit, a second calculation unit, and a presentation unit. The first acquisition unit acquires patient medical information related to a disease. Based on the medical information, the first calculation unit performs an organ simulation that predicts changes in the state of the patient's organs related to the disease, including at least one of changes in an index related to organ size and changes in an index related to organ function, and calculates the predicted transplantation time when the patient will need an organ transplant. The second acquisition unit acquires culture information related to the patient's organ culture, including at least one of the proliferation characteristics of cells involved in organ culture and the progress of organ culture. Based on the organ simulation and the culture information, the second calculation unit calculates an organ culture schedule that includes a start time to begin organ culture, a predicted completion time when organ culture is expected to be completed, and a storage period during which the cultured organ can be stored in a transplantable state. The presentation unit presents the results of the organ simulation, information representing the transplantation time, and the culture schedule together. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 shows an example of the configuration of a medical information processing system including a medical information processing device according to an embodiment. [Figure 2] Figure 2 shows an example of the configuration of a medical information processing device according to the embodiment. [Figure 3] Figure 3 illustrates an example of the results of an organ simulation according to the embodiment. [Figure 4] Figure 4 illustrates an example of a culture schedule according to the embodiment. [Figure 5] Figure 5 illustrates an example of the recalculation process for the culture schedule according to the embodiment. [Figure 6] Figure 6 illustrates an example of the recalculation process for the culture schedule according to the embodiment. [Figure 7] Figure 7 illustrates another example related to Figures 5 and 6 of the culture schedule recalculation process according to the embodiment. [Figure 8]Figure 8 illustrates another example related to Figures 5 and 6 of the culture schedule recalculation process according to the embodiment. [Figure 9] Figure 9 illustrates another example of the recalculation process for the culture schedule according to the embodiment. [Figure 10] Figure 10 illustrates another example of the culture schedule recalculation process according to the embodiment. [Figure 11] Figure 11 illustrates another example related to Figures 9 and 10 of the culture schedule recalculation process according to the embodiment. [Figure 12] Figure 12 illustrates another example related to Figures 9 and 10 of the culture schedule recalculation process according to the embodiment. [Figure 13] Figure 13 is a flowchart showing an example of a process performed by the medical information processing device according to this embodiment. [Modes for carrying out the invention]

[0008] The embodiments of the medical information processing device will be described in detail below with reference to the attached drawings. The following description will use a medical information processing system including the medical information processing device as an example. In the medical information processing system shown in Figure 1, one of each device is shown, but in reality, multiple devices may be included.

[0009] The medical information processing system shown in Figure 1 includes a Hospital Information System (HIS), a Radiology Information System (RIS), a Picture Archiving and Communication System (PACS), and a Laboratory Information System (LIS).

[0010] The medical information processing system includes a HIS server 10, a RIS server 20, a medical image diagnostic device 30, a PACS server 40, a LIS server 50, inspection equipment 60, a terminal 70, and a medical information processing device 100.

[0011] The HIS server 10, the RIS server 20, the medical image diagnostic device 30, the PACS server 40, the terminal 70, the LIS server 50, the inspection equipment 60, and the terminal 70, the medical information processing device 100 are connected to, for example, an in-hospital LAN (Local Area Network) installed in the hospital, transmit information to a predetermined device, and receive information transmitted from a predetermined device. Note that the HIS server 10 may be connected to an external network in addition to the in-hospital LAN.

[0012] For example, the terminal 70 is used by a user involved in patient treatment. For example, the user is a medical worker such as a doctor or a nurse. For example, the terminal 70 includes a PC (Personal Computer), a tablet PC, a PDA (Personal Digital Assistant), a mobile terminal, and the like.

[0013] In the HIS, the HIS server 10 shown in FIG. 1 manages information generated in the hospital. Information generated in the hospital includes patient information and inspection order information, etc.

[0014] The patient information includes the patient's basic information, medical treatment information, and inspection execution information (image inspection execution information, specimen inspection execution information). The basic information includes a patient ID, name, date of birth, gender, blood type, height, weight, etc. The patient ID is set with identification information that uniquely identifies the patient. The patient's medical treatment information includes information such as numerical values (measurement values) and medical treatment records, and information indicating the recording date and time thereof.

[0015] For example, the patient's medical information includes information such as prescriptions by doctors, nursing records by nurses, examinations by the examination department, and arrangements for meals at the time of 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. The examination execution information includes information such as past examinations and examination results by the examinations, and information indicating the execution date of the examinations.

[0016] Examination order information is issued to generate examination execution information. The examination order information includes an examination ID, patient ID, examination code, medical department, examination type, examination site, and scheduled examination date and time, etc. The examination ID is an identifier for uniquely identifying the examination order information. The examination code is an identifier for uniquely identifying the examination.

[0017] The medical department indicates the specialized field classification of the medical treatment. The examination type indicates examination items such as image examinations using medical images and specimen examinations in which specimens such as blood obtained from patients are analyzed by clinical laboratory technicians.

[0018] For example, the examination types of image examinations include X-ray examinations, CT (Computed Tomography) examinations, and MRI (Magnetic Resonance Imaging) examinations, etc. Also, for example, the examination types of specimen examinations include general examinations, biochemical examinations, immunological examinations, blood examinations, microbiological examinations, pathological examinations, and genetic examinations, etc. The examination sites include the brain, kidneys, lungs, liver, and bones, etc.

[0019] For example, when examination order information for an examination using a medical image is input from the requesting doctor of the examination to the HIS server 10, the HIS server 10 transmits the input examination order information and the patient information specified by the examination order information to the RIS. Also, in this case, the HIS server 10 transmits the patient information to the PACS. [[ID=IS=17]]

[0020] Furthermore, for example, when the HIS server 10 receives a test order information for a specimen test from the requesting physician, it transmits the entered test order information and the patient information identified by that test order information to the LIS.

[0021] Furthermore, the HIS server 10 shown in Figure 1 manages culture information related to organ culture based on iPS cells. Culture information includes information representing the proliferation characteristics of iPS cells, the start date of organ culture, the progress of organ culture, the state of the cultured organ, and the expected completion date of organ culture. Culture information is used for calculating the culture schedule, which will be described later.

[0022] In the RIS, the RIS server 20 shown in Figure 1 manages information related to radiological inspection work. For example, the RIS server 20 receives inspection order information transmitted from the HIS server 10, adds various setting information to the received inspection order information and stores it, and manages the stored information as image inspection reservation information.

[0023] Specifically, when the RIS server 20 receives patient information and examination order information transmitted from the HIS server 10, it generates image examination reservation information necessary to operate the medical imaging diagnostic device 30 based on the received patient information and examination order information. The image examination reservation information includes, for example, information necessary for performing the examination, such as examination ID, patient ID, examination type, and examination site. The RIS server 20 transmits the generated image examination reservation information to the medical imaging diagnostic device 30.

[0024] The medical imaging diagnostic device 30 shown in Figure 1 is a device used by radiologic technologists to perform examinations by taking images of patients.

[0025] Examples of medical imaging diagnostic equipment 30 include ultrasound diagnostic equipment, X-ray CT (Computed Tomography) equipment, MRI (Magnetic Resonance Imaging) equipment, SPECT (Single Photon Emission Computed Tomography) equipment, PET (Positron Emission Computed Tomography) equipment, SPECT-CT equipment which integrates a SPECT equipment and an X-ray CT equipment, and PET-CT equipment which integrates a PET equipment and an X-ray CT equipment. Medical imaging diagnostic equipment 30 is also called modality equipment.

[0026] For example, the medical imaging diagnostic device 30 performs an examination based on the image examination reservation information transmitted from the RIS server 20. The medical imaging diagnostic device 30 then generates image examination execution information indicating that the image examination has been performed and transmits it to the RIS server 20.

[0027] In this case, the RIS server 20 receives image examination information from the medical imaging diagnostic device 30 and outputs the received image examination information to the HIS server 10 as the latest image examination information. For example, the HIS server 10 receives the latest image examination information and manages the received image examination information. The image examination information includes image examination reservation information (examination ID, patient ID, examination type, examination site, etc.) and the date and time the examination was performed.

[0028] Furthermore, the medical imaging diagnostic device 30 generates medical image data when a clinical laboratory technician photographs the subject (patient) during the examination. Medical image data includes, for example, X-ray CT image data, X-ray image data, MRI image data, nuclear medicine image data, and ultrasound image data.

[0029] The medical imaging diagnostic device 30 converts the generated medical image data into a format compliant with, for example, the DICOM (Digital Imaging and Communication in Medicine) standard. That is, the medical imaging diagnostic device 30 generates medical image data to which a DICOM tag is attached as supplementary information. The medical imaging diagnostic device 30 transmits the generated medical image data to the PACS.

[0030] The supplementary information includes, for example, patient ID, examination ID, device ID, image series ID, and imaging conditions, and is standardized according to the DICOM standard. The device ID is information used to identify the medical imaging diagnostic device 30.

[0031] The image series ID is information used to identify a single image taken by the medical imaging diagnostic device 30, and includes, for example, the part of the subject (patient) being photographed, the image generation time, slice thickness, slice position, etc. For example, by performing a CT scan or MRI scan, tomographic images at each of multiple slice positions are obtained as medical image data.

[0032] In a PACS system, the PACS server 40 shown in Figure 1 receives, for example, patient information transmitted from the HIS server 10 and manages the received patient information. The PACS server 40 is equipped with a memory circuit for managing patient information.

[0033] For example, the PACS server 40 receives medical image data transmitted from the medical imaging diagnostic device 30, associates the received medical image data with patient information, and stores it in its own memory circuit. Alternatively, for example, the PACS server 40 reads medical image data from its own memory circuit in response to an acquisition request from the medical information processing device 100 and transmits it to the medical information processing device 100.

[0034] Furthermore, the medical image data stored in the PACS server 40 is accompanied by supplementary information such as patient ID, examination ID, device ID, and image series ID. Therefore, users can obtain the necessary patient information from the PACS server 40 by performing a search using the patient ID, etc. Users can obtain the necessary medical image data from the PACS server 40 by performing a search using the patient ID, examination ID, device ID, image series ID, etc.

[0035] The LIS server 50 is a system that manages specimen testing reservation information related to clinical laboratory testing operations. For example, the LIS server 50 receives specimen testing order information transmitted from the HIS server 10, adds various setting information to the received test order information and stores it, and manages the stored information as specimen testing reservation information.

[0036] Specifically, when the LIS server 50 receives patient information and test order information transmitted from the HIS server 10, it generates specimen test reservation information necessary to operate the testing equipment 60 based on the received patient information and test order information. The specimen test reservation information includes, for example, information necessary for performing the test, such as the test ID, patient ID, and test type. The LIS server 50 transmits the generated specimen test reservation information to the testing equipment 60.

[0037] The testing device 60 is a device that analyzes biological samples such as saliva, urine, and blood collected from a subject and generates test result data. Suitable testing devices 60 include automated biochemical analyzers, automated immunoassay analyzers, automated blood smear analyzers, automated blood coagulation analyzers, etc. Multiple testing devices 60 may be installed depending on the type of specimen test.

[0038] Furthermore, specimen testing may be performed without using the testing equipment 60, such as microscopic testing. In this case, the LIS server 50 receives and stores the test result data related to specimen testing from clinical laboratory technicians, etc. Also, at least a portion of the specimen testing may be performed by an external testing laboratory. In this case, the LIS server 50 receives and stores the test result data related to specimen testing from the external testing laboratory.

[0039] For example, the testing device 60 performs a test based on the sample test reservation information transmitted from the LIS server 50. After the test is performed, the testing device 60 generates sample test execution information indicating that the sample test has been performed, associates it with the test result data, and sends it to the LIS server 50. In this case, the LIS server 50 receives the sample test execution information from the testing device 60 and outputs the received sample test execution information as the latest sample test execution information, along with the associated test result data, to the HIS server 10 or the like.

[0040] For example, the HIS server 10 receives the latest specimen test implementation information and manages the received specimen test implementation information. The specimen test implementation information includes specimen test reservation information such as the test ID, patient ID, and test type, as well as the date and time the test was performed.

[0041] Here, the HIS server 10 receives, for example, an electronic medical record created by a clinician who is the physician requesting the test, and the specimen test implementation information corresponding to that electronic medical record. The received electronic medical record and specimen test implementation information are then associated and stored in its own memory circuit.

[0042] As mentioned above, the specimen test implementation information includes the test ID, patient ID, test type, and the date and time the test was performed. Therefore, the operator can retrieve the necessary electronic medical record from the HIS server 10 by searching using the patient ID, test ID, etc. In this embodiment, the electronic medical record is stored in the memory circuit of the HIS server 10, but it may also be stored in the memory circuit of another device within the medical information system, as long as it is searchable by ID.

[0043] The medical information processing device 100 shown in Figure 1 is a device that provides support for providing organs cultured from the patient's own cells at the time the patient needs them. For example, the medical information processing device 100 is a workstation.

[0044] The details of the medical information processing device 100 according to this embodiment will be described below. Figure 2 is a diagram showing an example of the configuration of the medical information processing device 100 according to this embodiment. As shown in Figure 2, the medical information processing device 100 has a processing circuit 110, a storage circuit 120, and a communication interface 130.

[0045] The memory circuit 120 is connected to the processing circuit 110 and stores various types of information. Specifically, the memory circuit 120 stores patient information received from each system. For example, the memory circuit 120 can be implemented using semiconductor memory elements such as RAM (Random Access Memory) or flash memory, or by using a hard disk or optical disc.

[0046] Here, the memory circuit 120 is an example of a memory unit. The communication interface 130 is, for example, a NIC (Network Interface Card) and communicates with other devices.

[0047] The processing circuit 110 controls the components of the medical information processing device 100. For example, as shown in Figure 2, the processing circuit 110 performs a first acquisition function 111, a first calculation function 112, a second acquisition function 113, a second calculation function 114, an adjustment function 115, and a display control function 116.

[0048] Here, for example, each processing function performed by the components of the processing circuit 110—the first acquisition function 111, the first calculation function 112, the second acquisition function 113, the second calculation function 114, the adjustment function 115, and the display control function 116—is recorded in the memory circuit 120 in the form of a program that can be executed by a computer. The processing circuit 110 is a processor that reads each program from the memory circuit 120 and executes it to realize the function corresponding to each program.

[0049] In other words, the processing circuit 110 in the state where each program has been read will have the functions shown in the processing circuit 110 in Figure 2. The first acquisition function 111, the first calculation function 112, the second acquisition function 113, the second calculation function 114, the adjustment function 115, and the display control function 116 are examples of the first acquisition unit, the first calculation unit, the second acquisition unit, the second calculation unit, the adjustment unit, and the display unit, respectively.

[0050] In the above explanation, the term "processor" refers to circuits such as CPUs (Central Processing Units), GPUs (Graphics Processing Units), and Application Specific Integrated Circuits (ASICs).

[0051] Furthermore, the term "processor" 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).

[0052] Another example of a programmable logic device is a Field Programmable Gate Array (FPGA). When the processor is a CPU, for example, it performs its functions by reading and executing a program stored in the memory circuit 120. On the other hand, when the processor is an ASIC, for example, instead of storing the program in the memory circuit 120, the program is directly incorporated into the processor's circuitry.

[0053] In this embodiment, each processor 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 its functions.

[0054] The first acquisition function 111 acquires medical data related to the patient's disease from the HIS server 10, RIS server 20, PACS server 40, and LIS server 50 via the communication interface 130. Medical data is an example of medical information.

[0055] Medical data related to a patient's illness includes, for example, the patient's medical history, the patient's family medical history, the patient's medication status, the patient's lifestyle, and various test results. The first acquisition function 111 may also acquire input results received from the operator as medical data.

[0056] The method for acquiring data related to the patient's disease is not limited to the above. For example, the first acquisition function 111 may directly acquire examination result data from the medical imaging diagnostic device 30 or the examination equipment 60 as medical data related to the patient's disease via the communication interface 130.

[0057] Furthermore, for example, the first acquisition function 111 monitors designated folders in the HIS server 10, RIS server 20, PACS server 40, and LIS server 50, and acquires new patient disease-related medical data when it is added. This ensures that the first acquisition function 111 always acquires the latest patient disease-related medical data.

[0058] The first calculation function 112 performs organ simulations based on medical information to predict changes in the state of organs related to the patient's disease, including changes in indicators related to organ size and changes in indicators related to organ function, and calculates the predicted time of need for organ transplantation for the patient.

[0059] For example, the first calculation function 112 uses the patient's disease-related medical data acquired by the first acquisition function 111 to perform a patient condition simulation that predicts how the patient's condition will change. The first calculation function 112 then calculates the disease risk from the results of this simulation. The disease risk is, for example, a quantitative representation of the likelihood of developing a disease.

[0060] Specifically, the first calculation function 112 uses patient medical data related to the disease to predict the disease based on genetic information, the progression of the disease based on the results of imaging tests, the progression of the disease based on specimen tests, the disease based on lifestyle habits, the disease based on medication status, and the disease based on chromosomal state (especially the state of telomere shortening).

[0061] Furthermore, the first calculation function 112 calculates disease risk based on the respective prediction results, according to a predetermined calculation method for each disease. The method for calculating disease risk can be determined, for example, based on clinical practice guidelines.

[0062] Furthermore, the first calculation function 112 calculates the organ risk associated with diseases where the disease risk exceeds a threshold. Organ risk quantitatively represents, for example, the risk of suffering damage from a disease that necessitates organ transplantation. The method for calculating organ risk can be determined based on clinical guidelines, etc., similar to disease risk.

[0063] Furthermore, the first calculation function 112 performs organ simulations to predict changes in the state of each organ whose organ risk exceeds a threshold.

[0064] Specifically, the first calculation function 112 predicts changes in organ status based on a combination of the patient's imaging test results, the patient's specimen test results, and the patient's genetic information obtained from genetic testing. As an example, the first calculation function 112 predicts changes in indicators related to organ size and changes in indicators related to organ function.

[0065] The above is merely one example of a method for predicting changes in organ condition, and the method for organ simulation is not limited to that described above. For example, the first calculation function 112 may perform organ simulations based on information obtained by tracking the lifetime medical data of multiple patients who have developed a disease.

[0066] In this case, the first calculation function 112 may predict changes in organ condition based on information such as genetic information, what diseases people with that gene developed, how the organ condition of people with similar findings in imaging tests changed over time (throughout their lives), and what diseases people with similar results in specimen tests developed. Alternatively, a combination of the above methods may be used to predict changes in indicators related to organ size and changes in indicators related to organ function.

[0067] Furthermore, for example, the first calculation function 112 calculates the predicted time of need for transplantation, which is when the patient is expected to need an organ transplant, based on the results of the organ simulation. Specifically, the first calculation function 112 calculates the time of need for transplantation as the point in time when both an indicator related to organ size and an indicator related to organ function are predicted to fall below a predetermined threshold.

[0068] Here, Figure 3 illustrates an example of the results of an organ simulation. In the example in Figure 3, the changes in indicators related to organ size and organ function are predicted as the state of the organ (organ condition). The thinner line graph represents the change in the indicator related to organ size, and the thicker line graph represents the change in the indicator related to organ function.

[0069] Furthermore, the vertical axis of the graph in Figure 3 represents the organ condition, with the further away from the origin of the vertical axis, the better the organ condition. The horizontal axis of the graph in Figure 3 represents time, with the origin (0) of the horizontal axis representing the present time.

[0070] Furthermore, the dotted lines on the graph drawn parallel to the horizontal axis in Figure 3 represent predetermined thresholds (transplant thresholds) for changes in indicators related to organ size and indicators related to organ function, respectively. In Figure 3, the indicators related to organ size are predicted to fall below the transplant threshold at time X. Similarly, the indicators related to organ function are predicted to fall below the transplant threshold at time Y.

[0071] In the example shown in Figure 3, the first calculation function 112 calculates the time at which transplantation is needed as time Y, when both the organ size indicator and the organ function indicator are predicted to be below the transplant threshold.

[0072] The above is merely one example of a method for calculating the timing of transplantation, and the method for calculating the timing of transplantation is not limited to the above. For example, the first calculation function 112 may calculate the timing of transplantation as an intermediate point between the time when one of the indicators related to organ size and the indicator related to organ function is predicted to fall below the transplant threshold, and the time when both the indicator related to organ size and the indicator related to organ function are predicted to fall below the transplant threshold.

[0073] Furthermore, the time when transplantation is needed may be expressed as a period between two specific points in time. For example, the first calculation function 112 may calculate the time when transplantation is needed as the period from a point midway between the point in time when one of the indicators related to organ size and the indicator related to organ function is predicted to fall below the transplant threshold, and the point in time when both the indicator related to organ size and the indicator related to organ function are predicted to fall below the transplant threshold, to the point in time when both are predicted to fall below the transplant threshold.

[0074] Returning to Figure 2, let's continue the explanation. The second acquisition function 113 acquires culture information related to organ culture, including at least one of the following: the proliferation characteristics of cells involved in organ culture and the progress of organ culture.

[0075] For example, if the patient's culture schedule has not been calculated, the second acquisition function 113 acquires information regarding the proliferation characteristics of iPS cells included in the culture information from the HIS server 10 via the communication interface 130. Note that the cells used as the basis for organ culture are not limited to iPS cells. For example, the cells used as the basis for organ culture may be ES cells or the like.

[0076] Furthermore, for example, if a patient's culture schedule has been calculated, the second acquisition function 113 acquires information from the HIS server 10 via the communication interface 130, which includes information such as the start date of culture, the progress of organ culture, the state of the cultured organ, and the expected completion date of culture.

[0077] The second calculation function 114 calculates the culture schedule for a patient's organ culture, including the start date of culture, the expected completion date of culture when organ culture is complete, and the storage period during which the cultured organ can be stored in a transplantable state, based on organ simulation and culture information.

[0078] For example, if a patient's culture schedule has not been calculated, the second calculation function 114 determines the target size of the organ to be cultured (hereinafter also referred to as the cultured organ). As an example, the second calculation function 114 determines the target size of the cultured organ based on the patient's height, weight, predicted patient condition, etc.

[0079] Furthermore, the second calculation function 114 calculates the storage period for the cultured organ. For example, the second calculation function 114 calculates the storage period for the cultured organ based on the type of cultured organ, the target size of the cultured organ, etc.

[0080] Furthermore, the second calculation function 114 calculates the culture period, which represents the predicted period required to culture the patient's iPS cells and produce an organ of the target size, based on the proliferation characteristics of the patient's iPS cells acquired by the second acquisition function 113.

[0081] Furthermore, the second acquisition function 113 calculates the culture start time and the planned culture completion time based on the calculated culture period, so that organ culture is completed by the transplantation requirement time calculated by the first calculation function 112. The second calculation function 114 may also calculate the culture start time and the planned culture completion time before the transplantation requirement time, taking into account the calculated storage period.

[0082] Here, Figure 4 illustrates an example of a culture schedule. The culture schedule in Figure 4 was calculated based on the results of the organ simulation in Figure 3.

[0083] In Figure 4, the vertical axis of the graph represents the predicted size of the cultured organ, with larger sizes occurring further from the origin of the vertical axis. The horizontal axis of the graph in Figure 4 represents time, with the origin (0) representing the current time. The graph also shows the change in the predicted size of the cultured organ, with the width along the horizontal axis representing the culture period. The period between the expected completion date of culture and the storage deadline represents the storage period calculated by the second calculation function 114.

[0084] In the example in Figure 4, the second acquisition function 113 calculates the start time of culture and the planned completion time of culture so that the predicted size of the cultured organ reaches the target size at time Y, which was calculated as the transplantation required time by the first calculation function 112 in the example in Figure 3.

[0085] Returning to Figure 2, the explanation continues. The adjustment function 115 adjusts at least one of the required transplant timing and culture schedule based on the latest patient disease-related clinical data obtained by the first acquisition function 111 and the latest culture information obtained by the second acquisition function 113.

[0086] For example, if the culture initiation time has not yet arrived, the adjustment function 115 performs a process to adjust the culture initiation time based on the latest patient disease treatment data obtained by the first acquisition function 111 and the current culture schedule.

[0087] Specifically, the adjustment function 115 works in cooperation with the first calculation function 112 to recalculate the transplantation timing using the latest patient disease-related medical data. If the recalculated transplantation timing is earlier than the previous timing, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the culture schedule with an earlier start to culture.

[0088] Figures 5 and 6 illustrate an example of the recalculation process for the culture schedule. Figures 5 and 6 show an example where the predicted rate of deterioration of the organ state in the current study is higher than the predicted rate of deterioration in the previous study.

[0089] Figure 5 compares the results of the previous organ simulation with those of the current organ simulation. The solid line graph in Figure 5 represents the results of the previous organ simulation. The dashed line graph in Figure 5 represents the results of the current organ simulation.

[0090] In the example shown in Figure 5, compared to the results of the previous organ simulation, the predicted time when both the organ size indicator and the organ function indicator will fall below the transplant threshold has been brought forward. In this case, the adjustment function 115 works in cooperation with the first calculation function 112 to recalculate the transplant requirement time as time point B, when both the organ size indicator and the organ function indicator are predicted to fall below the transplant threshold.

[0091] Figure 6 compares the culture schedule before and after adjustment. The solid line graph in Figure 6 represents the culture schedule before adjustment, while the dashed line graph in Figure 6 represents the culture schedule after adjustment.

[0092] In the example in Figure 5, as described above, the time required for transplantation has been brought forward compared to the results of the previous organ simulation. Therefore, as shown in Figure 6, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the start time of culture so that the predicted size of the cultured organ reaches the target size at time B, which is earlier than the time at which the cultured organ is predicted to reach the target size under the current culture schedule.

[0093] On the other hand, if the recalculated transplantation time is later than the transplantation time before recalculation, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the culture schedule with a delayed start to culture.

[0094] Here, Figures 7 and 8 illustrate another example related to Figures 5 and 6 of the recalculation process for the culture schedule. Figures 7 and 8 show an example where the predicted rate of deterioration of the organ state in the current case is lower than the predicted rate of deterioration of the organ state in the previous case.

[0095] Figure 7 compares the results of the previous organ simulation with those of the current organ simulation. The solid line graph in Figure 7 represents the results of the previous organ simulation. The dashed line graph in Figure 7 represents the results of the current organ simulation.

[0096] In the example shown in Figure 7, compared to the results of the previous organ simulation, the predicted time when both the organ size indicator and the organ function indicator will fall below the transplant threshold has been delayed. In this case, the adjustment function 115 works in cooperation with the first calculation function 112 to recalculate the transplant requirement time as time point B', when both the organ size indicator and the organ function indicator are predicted to fall below the transplant threshold.

[0097] Figure 8 compares the culture schedule before and after adjustment. The solid line graph in Figure 8 represents the culture schedule before adjustment, while the dashed line graph in Figure 8 represents the culture schedule after adjustment.

[0098] In the example in Figure 7, as described above, the required transplantation time is later compared to the results of the previous organ simulation. Therefore, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the start time of culture so that the predicted size of the cultured organ reaches the target size at time B', which is later than the time at which the cultured organ is predicted to reach the target size under the current culture schedule.

[0099] Furthermore, for example, if organ culture has been initiated, the adjustment function 115 performs a process to adjust at least one of the required transplant timing and culture schedule based on the latest patient disease-related medical data obtained by the first acquisition function 111 and the latest culture information obtained by the second acquisition function 113.

[0100] Specifically, the adjustment function 115 works in cooperation with the first calculation function 112 to recalculate the required transplant timing using the latest patient disease-related medical data. Furthermore, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the culture period based on information representing the progress of the culture included in the latest culture information obtained by the second acquisition function 113.

[0101] The adjustment function 115 then determines, based on the recalculated transplantation time and the expected completion time of culture calculated from the recalculated culture period, whether the culture will be completed in time for the transplantation time or too early.

[0102] Furthermore, the adjustment function 115 calculates the probability that the cultured organ will not reach the target size even if culture continues, based on the state of the cultured organ included in the latest culture information obtained by the second acquisition function 113 (for example, whether some of the cells of the cultured organ have undergone necrosis, etc.). Here, the probability that the cultured organ will not reach the target size can also be rephrased as the probability that the organ culture will fail.

[0103] If the probability of organ culture failure exceeds a predetermined threshold, the adjustment function 115 will promptly suggest starting a new organ culture and taking measures to slow the progression of the deterioration of the patient's organ condition. Since slowing the progression of the deterioration of the patient's organ condition can delay the time when transplantation is needed, suggesting measures to slow the progression of the deterioration of the patient's organ condition can be considered an example of a process to adjust the time when transplantation is needed.

[0104] Furthermore, the adjustment function 115 may determine whether the culture will be completed in time for the transplantation or too early, by considering the patient's condition and the current state of the patient's organs, derived from the latest clinical data on the patient's disease, as well as the latest progress of organ culture.

[0105] In this case, the adjustment function 115 may take into account indicators such as the patient's age, height, weight, physical condition, current organ size, changes in organ condition, and risks associated with the patient's condition.

[0106] The physical condition represents the load on the patient's body, such as the load level. For example, in the case of a diabetic patient, the extent to which the patient can withstand surgery varies depending on their condition, such as renal failure or myocardial infarction. Therefore, for example, if organ culture is progressing smoothly, but it is predicted that the patient will not be able to withstand the transplant surgery when transplantation is needed, the adjustment function 115 may determine that the expected completion date of culture is early.

[0107] Changes in organ status indicate how the condition of the organ has changed as a result of treatment. For example, if organ culture is progressing smoothly, but the organ status does not improve as much as expected after starting a new treatment, the regulatory function 115 may determine that the culture will not be completed in time for transplantation.

[0108] The risk associated with the patient's condition indicates the probability of various risks occurring based on the patient's condition. For example, if organ culture is progressing smoothly, but the risk of worsening the organ's condition is increasing, such as when the patient's condition can no longer be controlled by the medication being administered, when inflammation occurs in the organ, when cells constituting the organ are dying, or when cancer metastasis is observed, the regulatory function 115 may determine that the culture will not be completed in time for the transplantation period.

[0109] Furthermore, the adjustment function 115 may compare the structure of the patient's organs with the structure of the cultured organs based on medical images obtained from imaging examinations, and, taking the comparison results into consideration, determine whether the culture will be completed in time for the transplantation period or whether the culture will be completed too early.

[0110] Furthermore, the adjustment function 115 may determine whether the completion of culture will not be in time for the transplantation period, or whether the culture will be completed too early, taking into consideration the treatment plan for other diseases. For example, if organ culture is progressing smoothly, but it is considered better to transplant the organ earlier due to the treatment plan for other diseases, the adjustment function 115 may determine that the completion of culture will not be in time for the transplantation period.

[0111] Furthermore, for example, if organ culture is progressing smoothly and it is considered better to perform organ transplantation after the condition of other diseases has improved, the regulatory function 115 may determine that the expected completion date of culture is early.

[0112] Here, Figures 9 and 10 illustrate another example of the recalculation process for the culture schedule. Figures 9 and 10 show an example where the predicted rate of deterioration of the organ state in the current study is lower than the predicted rate of deterioration in the previous study.

[0113] Figure 9 compares the results of the previous organ simulation with the results of the current organ simulation. The solid line in Figure 9 represents the results of the previous organ simulation. The dashed line in Figure 9 represents the results of the current organ simulation. The origin on the horizontal axis of the graph in Figure 9 represents the start time of culture. The value of 0 on the horizontal axis of the graph in Figure 9 represents the current time.

[0114] In the example shown in Figure 9, compared to the results of the previous organ simulation, the predicted time when both the organ size indicator and the organ function indicator will fall below the transplant threshold has been delayed. In this case, the adjustment function 115 works in cooperation with the first calculation function 112 to recalculate the time when both the organ size indicator and the organ function indicator are predicted to fall below the transplant threshold, as the time when transplantation is needed.

[0115] Figure 10 compares the culture schedule before and after adjustment. The solid line graph in Figure 8 represents the culture schedule before adjustment. The dashed line graph in Figure 8 represents the culture schedule after adjustment. In Figure 10, 0 on the horizontal axis represents the current time.

[0116] In the example in Figure 10, as described above, the time required for transplantation is later compared to the results of the previous organ simulation. Therefore, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the culture schedule so that the predicted size of the cultured organ reaches the target size at time E, which is later than the time at which the cultured organ is predicted to reach the target size under the current culture schedule.

[0117] Specifically, the adjustment function 115 performs a process that delays the time when the cultured organ is expected to reach its target size, such as by lowering the culture temperature in the organ culture environment below the optimal temperature.

[0118] Figures 11 and 12 illustrate another example related to Figures 9 and 10 of the recalculation process for the culture schedule. Figures 11 and 12 show an example where the predicted rate of deterioration of the organ state in the current study was higher than the predicted rate of deterioration in the previous study.

[0119] Figure 11 compares the results of the previous organ simulation with the results of the current organ simulation. The solid line in Figure 11 represents the results of the previous organ simulation. The dashed line in Figure 11 represents the results of the current organ simulation. The origin on the horizontal axis of the graph in Figure 9 represents the start time of culture. The value of 0 on the horizontal axis of the graph in Figure 9 represents the current time.

[0120] In the example shown in Figure 11, compared to the results of the previous organ simulation, the predicted time at which both the organ size indicator and the organ function indicator will fall below the transplant threshold has been brought forward. In this case, the adjustment function 115 works in cooperation with the first calculation function 112 to recalculate the time at which both the organ size indicator and the organ function indicator are predicted to fall below the transplant threshold, E', as the time when transplantation is needed.

[0121] In this case, the adjustment function 115 proposes taking measures to improve the condition of the patient's organs. Specifically, the adjustment function 115 proposes improving the patient's lifestyle, adding or changing medications administered to the patient, implementing new treatments, or changing the treatment plan. Here, a change in the treatment plan might be, for example, increasing the frequency of hemodialysis if the organ to be transplanted is a kidney (e.g., increasing the number of hemodialysis sessions from twice a week to three times a week).

[0122] Furthermore, if it is decided that a procedure will be performed to improve the condition of the patient's organs, the adjustment function 115 performs an organ simulation that predicts the changes in the patient's organ condition if the procedure is performed.

[0123] Furthermore, if the time required for transplantation is brought forward, and the culture temperature in the organ culture environment is lowered below the optimal temperature, the adjustment function 115 may bring the culture temperature closer to the optimal temperature, thereby accelerating the time when the cultured organ is expected to reach the target size.

[0124] Here, Figure 12 compares the culture schedule before adjustment with the culture schedule after adjustment, corresponding to Figure 11. As a premise, in the example in Figure 12, it is assumed that organ culture is performed with the culture temperature lower than the optimal temperature.

[0125] The solid line graph in Figure 12 represents the culture schedule before adjustment. The dashed line graph in Figure 12 represents the culture schedule after adjustment. Furthermore, 0 on the horizontal axis of the graph in Figure 12 represents the current time.

[0126] In the example shown in Figure 12, the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the culture period when the culture temperature is set to the optimal temperature. The adjustment function 115 then determines whether the cultured organ size is predicted to reach the target size before the recalculated E' time point, which is the required time for transplantation, based on the recalculated culture period.

[0127] Then, if it is predicted that the cultured organ size will reach the target size before time E', the adjustment function 115 works in cooperation with the second calculation function 114 to recalculate the culture schedule so that the cultured organ size reaches the target size at time E'.

[0128] On the other hand, if it is predicted that the cultured organ size will not reach the target size before time E', the adjustment function 115 also suggests setting the culture temperature to the optimal temperature and taking measures to improve the condition of the patient's organ.

[0129] Returning to Figure 2, let's continue the explanation. The display control function 116 controls the display of various information on the display device. For example, the display control function 116 controls the display of the organ simulation results calculated by the first calculation function 112 and the culture schedule calculated by the second calculation function 114 together on the display of the terminal 70 used by the user.

[0130] Furthermore, for example, if the adjustment function 115 performs a process to adjust the transplantation timing, the display control function 116 controls the display of the terminal 70 to show the results of the organ simulation together with the latest culture schedule in a manner that allows comparison between the transplantation timing before adjustment and the transplantation timing after adjustment.

[0131] Furthermore, for example, if the adjustment function 115 performs a process to adjust the culture schedule, the display control function 116 controls the display of the terminal 70 to show the culture schedule on the terminal 70's display in a manner that allows comparison between the culture schedule before adjustment and the culture schedule after adjustment, together with the results of the latest organ simulation.

[0132] Next, the processing performed by the medical information processing device 100 according to this embodiment will be described. Figure 13 is a flowchart showing an example of the processing performed by the medical information processing device 100 according to this embodiment.

[0133] First, the first acquisition function 111 acquires medical data related to the patient's disease (step S101). For example, the first acquisition function 111 monitors the HIS server 10, RIS server 20, PACS server 40, and LIS server 50 via the communication interface 130 and acquires the latest medical data related to the patient's disease from these servers.

[0134] Next, the first calculation function 112 determines whether a culture schedule has been calculated (step S102). If a culture schedule has been calculated (step S102: Yes), the process proceeds to step S105, which will be described later.

[0135] On the other hand, if a culture schedule has not been calculated (Step S102: No), the first calculation function 112 calculates the disease risk and determines whether the calculated disease risk exceeds a threshold (Step S103). For example, the first calculation function 112 calculates the disease risk for various diseases based on the clinical data obtained in Step S101. If there are no diseases for which the disease risk exceeds a threshold (Step S103: No), the process returns to Step S101.

[0136] On the other hand, if the disease risk exceeds the threshold for at least one disease (step S103: Yes), the first calculation function 112 calculates the organ risk for that disease (step S104). For example, the first calculation function 112 calculates the organ risk for various organs based on the medical data obtained in step S101. If there are no organs whose organ risk exceeds the threshold (step S104: No), the process returns to step S101.

[0137] On the other hand, if the organ risk exceeds a threshold for at least one organ (Step S104: Yes), the first calculation function 112 performs an organ simulation and calculates the timing of the transplant based on the results of the organ simulation (Step S105).

[0138] For example, the first calculation function 112 performs organ simulations for each organ whose organ risk exceeds a threshold, based on the medical data acquired in step S101. Based on the results of the organ simulations, the first calculation function 112 calculates the timing of the transplant.

[0139] If the timing of the transplant has been calculated before step S105, the first calculation function 112 will recalculate the timing of the transplant based on the latest medical data obtained in step S101.

[0140] Next, the second acquisition function 113 determines whether a culture schedule has been calculated, similar to step S102 (step S106). If a culture schedule has not been calculated (step S106: No), the second acquisition function 113 acquires information representing the proliferation characteristics of the patient's cells (step S107).

[0141] For example, the second acquisition function 113 acquires information regarding the proliferation characteristics of patient iPS cells included in the culture information from the HIS server 10 via the communication interface 130.

[0142] Next, the second calculation function 114 calculates the culture schedule (step S108). For example, the second calculation function 114 calculates the culture period for organ culture based on the medical data obtained in step S101 and the information representing the proliferation characteristics of the patient's cells obtained in step S107.

[0143] Furthermore, the second calculation function 114 calculates the start time of culture and the planned completion time of culture based on the target size of the cultured organ derived from the medical data acquired in step S101, the calculated culture period, and the required transplantation time calculated in step S105. The second calculation function 114 also calculates the storage period of the cultured organ based on the type of cultured organ.

[0144] Furthermore, if a culture schedule has been calculated in step S106 (step S106: Yes), the second calculation function 114 recalculates the start time of organ culture (step S109). For example, the second calculation function 114 performs an organ simulation based on the latest clinical data obtained in step S101, and recalculates the start time of culture based on the transplantation requirement recalculated from the results of the organ simulation.

[0145] After step S108 or step S109, the second acquisition function 113 determines whether organ culture has started (step S110). For example, if the second acquisition function 113 can acquire information representing the progress of the culture included in the culture information via the communication interface 130, it determines that organ culture has started. If organ culture has not started (step S110: No), the process returns to step S101.

[0146] On the other hand, if organ culture has been started (step S110: Yes), the second acquisition function 113 acquires information representing the latest culture progress (step S111). For example, the second acquisition function 113 acquires information representing the latest culture progress from the HIS server 10 via the communication interface 130.

[0147] Next, the second calculation function 114 recalculates the expected completion time of the culture (step S112). For example, the second calculation function 114 recalculates the culture period based on the latest information representing the progress of the culture obtained in step S111. The second calculation function 114 then recalculates the expected completion time of the culture based on the recalculated culture period.

[0148] Next, the first acquisition function 111 acquires the latest medical data, similar to step S101 (step S113). Then, the first calculation function 112 recalculates the timing of the transplant, similar to step S105 (step S114).

[0149] Next, the adjustment function 115 determines whether the culture is expected to be completed before the required transplant time (step S115). For example, the adjustment function 115 compares the expected completion time of the culture, recalculated based on the latest information representing the progress of the culture obtained in step S111, with the required transplant time, recalculated in step S114, to determine whether the culture is expected to be completed before the required transplant time.

[0150] If the culture is scheduled to be completed before the time when transplantation is required (Step S115: Yes), determine whether the time when transplantation is required is after the storage period of the cultured organ (Step S116).

[0151] For example, the adjustment function 115 works in cooperation with the second calculation function 114 to compare the end date of the storage period included in the culture schedule, which has been recalculated based on the latest information representing the progress of the culture obtained in step S111, with the transplantation requirement time, which has been recalculated in step S114, to determine whether the transplantation requirement time is later than the storage period of the cultured organ.

[0152] If the time required for transplantation is not later than the storage period of the cultured organ (Step S116: No), the process proceeds to Step S119 described below. On the other hand, if the time required for transplantation is later than the storage period of the cultured organ (Step S116: Yes), the adjustment function 115 performs a process to adjust the culture environment so that it is later than the expected completion time of culture calculated based on the latest information representing the progress of culture (Step S117).

[0153] For example, the adjustment function 115 adjusts the culture temperature of the organ culture to a temperature lower than the optimal temperature so that the size of the cultured organ reaches the target size by the recalculated transplantation time.

[0154] Furthermore, if the culture is not scheduled to be completed before the time required for transplantation in step S115 (step S115: No), the adjustment function 115 proposes countermeasures to improve the patient's organ condition (step S118). For example, the adjustment function 115 may suggest improving the patient's lifestyle, adding medications to the patient's regimen, or implementing new treatment methods.

[0155] After step S117 or step S118, the first acquisition function 111 determines whether the time for transplantation has arrived (step S119). If the time for transplantation has not arrived (step S119: No), the process returns to step S111. On the other hand, if the time for transplantation has arrived (step S119: Yes), this process ends. After this, the patient will undergo a transplant surgery with the cultured organ.

[0156] As described above, the medical information processing device 100 according to this embodiment acquires patient medical data relating to a disease, performs organ simulations based on the medical data to predict changes in the state of the patient's disease-related organs, including at least one of changes in an indicator relating to organ size and changes in an indicator relating to organ function, calculates the time when the patient is expected to need organ transplantation, acquires culture information relating to the patient's organ culture, including at least the proliferation characteristics of cells related to organ culture, calculates an organ culture schedule based on the organ simulation and the culture information, including a culture start time to begin organ culture, a culture completion time when organ culture is expected to be completed, and a storage period during which the cultured organ can be stored in a transplantable state, and presents the results of the organ simulation, information representing the time when transplantation is needed, and the culture schedule together.

[0157] As a result, the medical information processing device 100 according to this embodiment can calculate the timing of transplantation required according to the patient's organ condition. Furthermore, for example, users such as doctors are presented with the results of the organ simulation, information indicating the timing of transplantation, and the culture schedule together, making it easier to understand the relationship between the prediction of changes in the patient's organ condition and the planned progress of organ culture. Also, for example, by understanding the relationship between the prediction of changes in the patient's organ condition and the planned progress of organ culture in advance, it is thought that even after organ culture has actually started, it will be easier to understand whether the progress of culture is commensurate with the changes in the patient's organ condition. Furthermore, for example, by understanding whether the progress of culture is commensurate with the changes in the patient's organ condition, it will be easier for users to improve the patient's organ condition or adjust the culture environment of the organ culture so that the culture is completed when transplantation is needed. In other words, the medical information processing device 100 according to this embodiment can provide support for providing cultured organs to the subject at the time they need them.

[0158] Furthermore, the medical information processing device 100 according to this embodiment acquires the most recent medical data, recalculates the required transplant timing based on said medical data, and, if organ culture has not yet begun, recalculates the culture start time and the planned culture completion time based on the recalculated required transplant timing.

[0159] As a result, the medical information processing device 100 according to this embodiment can adjust the planned completion time of culture by advancing or delaying the start time of culture according to the current organ condition of the patient, and can provide support for providing cultured organs at the time the patient needs them.

[0160] Furthermore, the medical information processing device 100 according to this embodiment acquires the most recent medical data, recalculates the required transplant timing based on said medical data, and, if organ culture has already started, adjusts at least one of the required transplant timing and the culture schedule based on the most recent medical data and the most recent culture information.

[0161] As a result, the medical information processing device 100 according to this embodiment can adjust the timing of transplantation or the planned completion of culture by taking measures to improve the patient's organ condition or reviewing the culture environment for organ culture, in accordance with the patient's current organ condition, and can provide support for providing cultured organs at the time the patient needs them.

[0162] Furthermore, the medical information processing device 100 according to this embodiment adjusts the culture schedule by adjusting the culture environment for organ culture so that the transplantation time recalculated based on the most recent medical data falls within the storage period calculated based on the most recent culture information.

[0163] As a result, the medical information processing device 100 according to this embodiment can adjust the culture environment for organ culture according to the current organ condition of the patient, thereby adjusting the expected completion time of the culture and providing the cultured organ at the time the patient needs it.

[0164] Furthermore, if the recalculated transplantation time is earlier than the start of the storage period calculated based on the most recent culture information, the medical information processing device 100 in this embodiment adjusts the culture schedule by lowering the culture temperature below the optimal temperature.

[0165] As a result, the medical information processing device 100 according to this embodiment can adjust the planned completion time of culture by lowering the culture temperature below the optimal temperature when the planned completion time of culture is earlier than the time required for transplantation, thereby supporting the provision of cultured organs at the time needed by the patient.

[0166] Furthermore, if the recalculated transplantation time is later than the storage period calculated based on the most recent culture information, and the organ culture is not being performed at the optimal temperature, the medical information processing device 100 according to this embodiment adjusts the culture schedule by bringing the culture temperature closer to the optimal temperature.

[0167] As a result, the medical information processing device 100 according to this embodiment can adjust the planned completion date of culture by bringing the culture temperature closer to the optimal temperature when the storage period of the cultured organ is later than the time required for transplantation, and can provide support for providing the cultured organ at the time the patient needs it.

[0168] Furthermore, the medical information processing device 100 according to this embodiment adjusts the timing of transplantation so that the timing of transplantation when such measures are taken to improve the condition of the patient's organs related to organ transplantation, including at least one of the following: improving the patient's lifestyle, adding or changing drugs administered to the patient, implementing new treatments for the patient, or changing existing treatments, falls within the storage period calculated based on the most recent culture information.

[0169] As a result, the medical information processing device 100 according to this embodiment can, when the storage period of cultured organs is later than the time required for transplantation, take measures to improve the condition of the patient's organs related to organ transplantation, thereby delaying the time required for transplantation and providing support for providing cultured organs at the time the patient needs them.

[0170] 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.

[0171] 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.

[0172] According to at least one embodiment described above, it is possible to provide assistance in delivering cultured organs to a subject at the time they require them.

[0173] 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]

[0174] 100 Medical Information Processing Devices 111 First Acquisition Function 112 First Calculation Function 113 Second acquisition function 114 Second Calculation Function 115 Adjustment function 116 Display control function 120 Memory circuit

Claims

1. The first acquisition unit acquires patient medical information related to diseases, Based on the aforementioned medical information, a first calculation unit performs an organ simulation to predict changes in the state of the patient's organs related to the disease, including at least one of changes in an indicator related to organ size and changes in an indicator related to organ function, and calculates the predicted time of transplantation when the patient will need to transplant the organs. A second acquisition unit that acquires culture information relating to the organ culture of the patient, including at least one of the proliferation characteristics of cells involved in organ culture and the progress of the organ culture, A second calculation unit calculates a culture schedule for organ culture, which includes, based on the required transplantation time and the culture information, a start time for initiating the organ culture, a predicted completion time for when the organ culture is completed, and a storage period during which the cultured organ can be stored in a transplantable state. A display unit that presents the results of the organ simulation and information indicating the timing of transplantation, along with the culture schedule, A medical information processing device equipped with [a specific feature].

2. The first acquisition unit acquires the most recent clinical information after the culture schedule has been calculated. The first calculation unit recalculates the required transplant timing based on the most recent medical information, When the medical information is acquired, the second acquisition unit acquires the most recent culture information, If the organ culture has not yet been started, the second calculation unit recalculates the start time and the completion time based on the recalculated transplantation requirement time and the most recent culture information. The medical information processing device according to claim 1.

3. If the organ culture has already been started, the second acquisition unit acquires the culture information, including information representing the progress of the organ culture. The system further includes an adjustment unit that adjusts at least one of the required transplantation time and the culture schedule based on the most recent clinical information and the most recent culture information. The medical information processing device according to claim 2.

4. The adjustment unit adjusts the culture schedule by adjusting the culture environment of the organ culture so that the transplantation time, recalculated based on the most recent clinical information, falls within the storage period calculated based on the most recent culture information. The medical information processing device according to claim 3.

5. If the recalculated transplantation time is earlier than the start of the storage period calculated based on the most recent culture information, the adjustment unit adjusts the culture schedule by lowering the culture temperature in the culture environment to below the optimal temperature. The medical information processing device according to claim 4.

6. The adjustment unit adjusts the culture schedule by bringing the culture temperature closer to the optimal temperature if the recalculated transplantation time is later than the end of the storage period calculated based on the most recent culture information, and the culture temperature for organ culture is not the optimal temperature. The medical information processing device according to claim 5.

7. The adjustment unit adjusts the required transplant timing so that, by implementing measures to improve the condition of the organs of the patient involved in organ transplantation, the required transplant timing after such measures are implemented falls within the storage period calculated based on the most recent culture information. The medical information processing device according to claim 3.

8. The adjustment unit adjusts the timing of the transplant by performing at least one of the following: improving the patient's lifestyle, adding or changing the medication administered to the patient, or implementing a new treatment for the patient or changing the treatment method being implemented. The medical information processing device according to claim 6.

9. A medical information processing method using a medical information processing device, The first acquisition step is to obtain patient medical information regarding the disease, Based on the aforementioned medical information, an organ simulation is performed to predict changes in the state of the patient's organs related to the disease, including at least one of changes in an indicator related to organ size and changes in an indicator related to organ function, and a first calculation step is performed to calculate the predicted time of transplantation when the patient will need to transplant the organs. A second acquisition step of acquiring culture information relating to the organ culture of the patient, including at least one of the proliferation characteristics of cells involved in organ culture and the progress of the organ culture, A second calculation step involves calculating a culture schedule for the organ culture, which includes, based on the required transplantation time and the culture information, a start time for initiating the organ culture, a predicted completion time for when the organ culture is completed, and a storage period during which the cultured organ can be stored in a transplantable state. A presentation step that presents the results of the organ simulation and information indicating the timing of transplantation, along with the culture schedule, A medical information processing method including [the specified term].

10. On the computer, The first acquisition step is to obtain patient medical information regarding the disease, Based on the aforementioned medical information, an organ simulation is performed to predict changes in the state of the patient's organs related to the disease, including at least one of changes in an indicator related to organ size and changes in an indicator related to organ function, and a first calculation step is performed to calculate the predicted time of transplantation when the patient will need to transplant the organs. A second acquisition step of acquiring culture information relating to the organ culture of the patient, including at least one of the proliferation characteristics of cells involved in organ culture and the progress of the organ culture, A second calculation step involves calculating a culture schedule for the organ culture, which includes, based on the required transplantation time and the culture information, a start time for initiating the organ culture, a predicted completion time for when the organ culture is completed, and a storage period during which the cultured organ can be stored in a transplantable state. A presentation step that presents the results of the organ simulation and information indicating the timing of transplantation, along with the culture schedule, A program that executes the command.

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