Blood purification device

Abstract

To provide a blood purification device capable of selecting, in real time, staff members who can appropriately respond when an abnormality occurs in a patient or in the blood purification device, and promptly notifying the selected staff members of the abnormality.SOLUTION: A blood purification device comprises: a required skill acquisition unit 3; a staff information acquisition unit 4; a staff determination processing unit 5 that generates and stores a learning model obtained by performing machine learning of determining a staff member for an abnormality in a specific patient or an abnormality in the blood purification device 1 using accumulated data including multiple pieces of staff information acquired when an abnormality occurred as teacher data; a selection unit 6 that inputs the staff information to the learning model of the staff determination processing unit 5 to select a staff member to respond; and an abnormality notification unit 7 that notifies a portable terminal 2 carried by the selected staff member of the abnormality.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a blood purification device for purifying a patient's blood and performing blood purification treatment.

Background Art

[0002] As a dialysis device as a blood purification device used in dialysis treatment or the like, a plurality of dialysis devices are installed in a dialysis room provided in a medical facility such as a hospital, and dialysis treatment (blood purification treatment) for a large number of patients is performed in the dialysis room. For example, in the blood purification device disclosed in Patent Document 1, by displaying information about a patient on a display unit (monitor or the like) of the blood purification device, staff such as medical workers can grasp the state of the patient, and can quickly and appropriately take measures when an abnormality occurs.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above conventional blood purification device, although information about a patient can be displayed on the display unit of the blood purification device, the staff who can appropriately and quickly take measures during treatment based on the information is not always near the blood purification device that requires response, and it is necessary to search for appropriate staff within the medical facility. Further, such a problem can similarly occur not only for patient abnormalities but also for responses to abnormalities of the blood purification device.

[0005] On the one hand, it is conceivable to preset staff members who can handle abnormalities for each patient or blood purification device in advance, and when an abnormality occurs in the patient or blood purification device, call the preset staff members within the medical facility. However, it is difficult to preset appropriate staff members for each abnormality, and even if they are preset, due to the location and schedule of the staff members when an abnormality occurs, there may be cases where the abnormality cannot be dealt with promptly.

[0006] The present invention has been made in view of such circumstances, and an object thereof is to provide a blood purification device capable of selecting, in real time, staff members who can appropriately respond when an abnormality occurs in a patient or a blood purification device, and quickly notifying the selected staff members of the abnormality.

Means for Solving the Problems

[0007] A blood purification device according to an embodiment of the present invention is a blood purification device for purifying a patient's blood and performing blood purification treatment. When an abnormality of a patient being treated by the blood purification device or an abnormality of the blood purification device occurs, a necessary skill acquisition unit that acquires skill information necessary for resolving the abnormality, a staff information acquisition unit that acquires staff information including staff position information, schedule information, and skill information based on the necessary skill information acquired by the necessary skill acquisition unit, a staff determination processing unit that generates and stores a learning model obtained by performing machine learning to determine staff members who should respond to an abnormality of a specific patient or an abnormality of the blood purification device, using accumulated data in which a plurality of the staff information acquired by the staff information acquisition unit is accumulated as teacher data when an abnormality of a patient being treated by the blood purification device or an abnormality of the blood purification device occurs, a selection unit that acquires the staff information by the staff information acquisition unit and inputs the staff information into the learning model of the staff determination processing unit to select staff members who should respond when an abnormality of a patient being treated by the blood purification device or an abnormality of the blood purification device occurs, and an abnormality notification unit that notifies the portable terminal carried by the selected staff members of the abnormality of the patient or the abnormality of the blood purification device.

Advantages of the Invention

[0008] According to the present invention, by using a learning model obtained through machine learning, a staff member to be dealt with when an abnormality occurs in a patient or a blood purification device is determined. Therefore, when an abnormality occurs in a patient or a blood purification device, a staff member who can appropriately respond can be selected in real time, and the selected staff member can be quickly notified of the abnormality.

Brief Description of Drawings

[0009]

Figure 1

Figure 2

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Figure 8

Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present invention will be specifically described with reference to the drawings. The blood purification device according to this embodiment is for purifying the blood of a patient. As shown in FIGS. 1 and 2, it includes a blood purification device 1 for purifying the patient's blood and performing blood purification treatment, and a mobile terminal 2 carried by staff including medical personnel and capable of communicating with the blood purification device 1. The staff refers to all workers related to medical facilities, including doctors and medical personnel who can handle patient treatment, as well as technical staff who can handle malfunctions and maintenance of the blood purification device 1.

[0011] As shown in FIG. 3, the blood purification device 1 is provided with a dialysate introduction line L1 for introducing dialysate and a dialysate discharge line L2 for discharging dialysate. A duplex pump 16 is arranged across these dialysate introduction line L1 and dialysate discharge line L2. Further, a dialyzer 15 (blood purifier) is connected to the dialysate introduction line L1 and the dialysate discharge line L2, and a blood circuit 13 for extracorporeal circulation of the patient's blood is connected to the dialyzer 15. By driving the blood pump 14, blood purification treatment can be performed on the patient's blood undergoing extracorporeal circulation in the blood circuit 13 by the dialyzer 15.

[0012] The pump chamber of the duplex pump 16 is partitioned by a single plunger (not shown) into a liquid delivery side pump chamber connected to the dialysate introduction line L1 and a discharge side pump chamber connected to the dialysate discharge line L2. By the reciprocating movement of the plunger, the dialysate or cleaning liquid sent to the liquid delivery side pump chamber is supplied to the dialyzer 15, and the drainage in the dialyzer 15 is inhaled into the discharge side pump chamber.

[0013] Furthermore, a bypass line L3 is formed in the dialysate discharge line L2, bypassing the duplex pump 16, and a water removal pump 17 is arranged in the middle of this bypass line L3. By driving such a water removal pump 17, it is possible to perform water removal on the patient's blood flowing through the dialyzer 15. Note that instead of the duplex pump 16, a so-called chamber type may be used.

[0014] Further, as shown in FIG. 2, the blood purification device 1 includes a display unit 1a, and various treatment means (for example, a blood pump, a replenishing liquid pump, a syringe pump, etc.) related to blood purification treatment (hemodialysis treatment) are arranged. Such treatment means include not only actuators such as pumps but also various general-purpose means used in blood purification treatment, such as clamp means such as solenoid valves and monitoring means such as hydraulic pressure.

[0015] Here, as shown in FIG. 1, the blood purification device 1 according to the present embodiment includes, in addition to the display unit 1a, a required skill acquisition unit 3, a staff information acquisition unit 4, a staff determination processing unit 5, a selection unit 6, an abnormality notification unit 7, a prediction processing unit 8, and a display control unit 9. The display unit 1a is composed of a monitor such as a touch panel, and is configured to be able to perform various displays controlled by the display control unit 9 in addition to treatment information related to blood purification treatment.

[0016] The required skill acquisition unit 3 is composed of a microcomputer or the like, and when an abnormality of a patient during treatment with the blood purification device 1 or an abnormality of the blood purification device 1 occurs, it acquires necessary skill information for resolving the abnormality from information previously input to the blood purification device. Thereby, it is possible to preliminarily select which skills related to patient treatment or skills related to the blood purification device 1 are required, and the subsequent selection of staff can be smoothly performed.

[0017] The staff information acquisition unit 4 is composed of a microcomputer or the like, and acquires staff information including staff position information, schedule information, and skill information based on the necessary skill information acquired by the required skill acquisition unit 3. The staff position information is composed of information input in real time by radio waves from the portable terminal 2 carried by the staff, and the position information is detected by the position detection unit 11 provided in the portable terminal 2.

[0018] That is, the mobile terminal 2 detects in real time, using GPS (Global Positioning System) or other position measurement systems, the position information indicating its current location with a position detector 11, and since this position information is transmitted to the blood purification device 1 via a wireless communication system such as Wi-Fi, the staff information acquisition unit 4 of the blood purification device 1 can acquire the staff's position information.

[0019] The staff schedule information is input to the blood purification device 1 based on a schedule management unit 12 that manages the staff's work information (attendance information), and consists of, for example, vacation schedules, business trip schedules, information on the schedules and time slots of events such as meetings and surgeries. The schedule management unit 12 may be, for example, a specific department of a medical facility (the department for managing attendance) or a server arranged in a cloud system, and it is preferably one that can sequentially update the schedule information.

[0020] The staff skill information is input to the blood purification device 1 based on the staff's expertise, skills, or proficiency (period of experience or number of experiences), and includes, for example, information on doctors who can determine changes in treatment conditions, specialist doctors who can perform specific treatments professionally, medical staff who can handle patients other than determining changes in treatment conditions (including changes in settings based on the judgment of doctors), technicians who can inspect and maintain the blood purification device 1 (including peripheral devices), etc. Also included is the time that can be dedicated to the same task.

[0021] When an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 (including peripheral devices) occurs, the staff determination processing unit 5 generates and stores a learning model obtained by performing machine learning to determine the staff who should respond to the abnormality of a specific patient or the abnormality of the blood purification device 1, using the accumulated data in which a plurality of pieces of staff information acquired by the staff information acquisition unit 4 are accumulated as teacher data.

[0022] That is, the staff determination processing unit 5 is capable of generating a learning model using artificial intelligence (AI). As shown in FIG. 4, when an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, a plurality (a large number) of staff information acquired by the staff information acquisition unit 4 are accumulated, and the huge accumulated data is input in advance as teacher data. Then, based on the input teacher data, machine learning for determining a staff member who should respond (suitable for responding) to an abnormality of a specific patient or an abnormality of the blood purification device 1 can be performed to generate and store a learning model.

[0023] Here, machine learning refers to a technology in which a computer automatically constructs an algorithm or model for learning a large amount of data and performing tasks such as classification and prediction. As a technology or algorithm for enabling machine learning, known machine learning algorithms such as neural networks can be used.

[0024] When an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, the selection unit 6 acquires staff information by the staff information acquisition unit 4, and as shown in FIG. 4, inputs the staff information into the learning model of the staff determination processing unit 5 to select the staff member who should respond. That is, actually, when an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, after the selection unit 6 acquires the staff information at that time by the staff information acquisition unit 4, if the staff information is input into the learning model of the artificial intelligence that the staff determination processing unit 5 has, staff information suitable for responding and a priority order (staff member capable of responding with the highest priority, staff member capable of responding second, etc.) will be output.

[0025] For example, when an abnormality occurs in the blood purification device 1, if the necessary skill information acquired from the necessary skill acquisition unit 3 for the abnormality is skill information that enables inspection and maintenance of the blood purification device 1, among the pre-input staff information, there are two staff members who have the skill information enabling inspection and maintenance of the blood purification device and can respond in combination with the current work status and location information. The staff member who is currently performing another inspection task but is the closest to the blood purification device 1 in terms of distance is the staff member who can be given the highest priority for response (the staff member to be responded to), and the staff member who is currently on standby but is slightly farther from the blood purification device 1 in terms of distance is the staff member who can be given the second priority for response, which are output from the learning model. Also, not only distance but also factors such as means of transportation and traffic congestion information may be considered for judgment. Further, if the time required to respond to the abnormality including the travel time to the blood purification device 1 is within the allowable time range for responding to the abnormality, a staff member on standby at a location away from the current blood purification device 1 may be regarded as the staff member who can be given the highest priority for response, and a staff member who is close to the current blood purification device 1 but is performing another inspection task may be regarded as the staff member who can be given the second priority for response for judgment.

[0026] The abnormality notification unit 7 notifies the mobile terminal 2 carried by the staff member to be responded to selected by the selection unit 6 of the abnormality of the patient or the blood purification device 1. That is, when the selection unit 6 selects the staff member to be responded to, the abnormality notification unit 7 can display and notify that an abnormality has occurred on the display unit 10 etc. of the mobile terminal 2 of the selected staff member via a wireless communication system such as Wi-Fi.

[0027] In addition, when the staff responds that they are unable to handle the notified information (or fails to respond within a certain period of time), the information may subsequently be notified to the mobile terminal 2 carried by the second staff member who is able to handle it. When the second staff member who is able to handle it responds that they are unable to handle it (or fails to respond within a certain period of time), the information may subsequently be notified to other staff members who are able to handle it in order of priority. Furthermore, the abnormality notification unit 7 may provide information on the staff member to be dealt with selected by the selection unit 6, the information on the staff members who are able to handle it, and the priority order information to other medical staff via a notification means such as a screen display of the blood purification device 1 or a mobile terminal, and may make a proposal for determining the staff member to be dealt with. In addition, the abnormality notification unit 7 may notify the abnormality of the patient or the blood purification device 1 to the mobile terminals 2 carried by all the staff members who are able to handle it selected by the selection unit 6, and provide the response content and response time from each staff member to other medical staff via a notification means such as a screen display of the blood purification device 1 or a mobile terminal, and may make a proposal for determining the staff member to be dealt with.

[0028] On the other hand, the mobile terminal 2 is composed of a smartphone or tablet that can be carried by the staff, and is capable of continuous wireless communication with the blood purification device 1. The mobile terminal 2 includes a display unit 10 composed of a touch panel or the like and the aforementioned position detection unit 11. When an abnormality of the patient or the blood purification device 1 is wirelessly transmitted from the abnormality notification unit 7 of the blood purification device 1, the occurrence of the abnormality is displayed on the display unit 10, and it is possible to give an instruction to respond to the patient or the blood purification device 1 in which the abnormality has occurred.

[0029] The prediction processing unit 8 is composed of a microcomputer or the like. Using accumulated data in which a plurality of pieces of past information of the patient being treated by the blood purification device 1 or past information of the blood purification device 1 (including past information of peripheral devices) are accumulated as teacher data, the prediction processing unit 8 generates and stores a learning model obtained by performing machine learning for predicting the occurrence of an abnormality of a specific patient or the blood purification device 1 and proposing an appropriate countermeasure method.

[0030] That is, the prediction processing unit 8 is capable of generating a learning model using artificial intelligence (AI). As shown in FIG. 5, it accumulates a plurality (a large number) of past information of the patient being treated by the blood purification device 1 (for example, the patient's blood pressure, etc. during the treatment process) or past information of the blood purification device 1 (such as sensor failures or pump malfunctions), and that huge amount of accumulated data is input in advance as teacher data. Then, based on the input teacher data, it is possible to generate and store a learning model obtained by performing machine learning to predict the occurrence of an abnormality in a specific patient or an abnormality in the blood purification device 1 and propose an appropriate countermeasure method therefor.

[0031] For example, when blood purification treatment is started, the treatment information at that time is transmitted to the prediction processing unit 8, and when the received treatment information is input into the learning model of artificial intelligence, it is possible to output a prediction of the occurrence of an abnormality in the patient or the blood purification device 1 that is assumed to occur in the future when the treatment is continued, and a proposal for a countermeasure method for the predicted abnormality. The prediction of the occurrence of an abnormality in the patient or the blood purification device 1 output in this way, and the proposal for a countermeasure method for the predicted abnormality may be single or plural.

[0032] The display control unit 9 causes the display unit 1a of the blood purification device 1 to display the occurrence of an abnormality in a specific patient or the blood purification device 1 predicted by the prediction processing unit 8 and the proposal of an appropriate countermeasure method therefor. Further, the prediction processing unit 8 may propose a plurality of countermeasure methods for the predicted abnormality in a specific patient or the blood purification device 1, and the display control unit 9 may cause the display unit 1a to display the plurality of countermeasure methods proposed by the prediction processing unit 8.

[0033] In addition to being displayed on the display unit 1a by the display control unit 9, the prediction of the occurrence of an abnormality in a specific patient or the blood purification device 1 predicted by the prediction processing unit 8 and the proposal of an appropriate countermeasure method therefor may be transmitted as data to the mobile terminal 2 and displayed on the display unit 10 of the mobile terminal 2 to notify the staff.

[0034] Next, a method for generating and storing a learning model by the staff determination processing unit 5 according to the present embodiment will be described based on the flowchart of FIG. 6. First, after acquiring the skills of the staff and the skills required for treatment at S1, the position information of the staff is acquired at S2. Then, after acquiring the schedule information of the staff at S3, the time when the treatment actually starts is acquired at S4, and then the process proceeds to S5. In S5, the information acquired in S1 to S4 is accumulated as teacher data, and machine learning for determining the staff to be responsible for the abnormality of a specific patient or the abnormality of the blood purification device 1 is performed to generate and store a learning model.

[0035] Next, a method for selecting and notifying a staff when an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 actually occurs will be described based on the flowchart of FIG. 7. First, when an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, the skills required for treatment (elimination of the abnormality) for the abnormality are acquired by the required skill acquisition unit 3 at S1, and the skill information of the staff is acquired by the staff information acquisition unit 4 at S2.

[0036] Thereafter, the position of the blood purification device 1 that requires countermeasures for the abnormality is acquired at S3 (since the position of each blood purification device 1 is set in advance, the position of the blood purification device 1 where the abnormality has occurred is specified). The position information of the staff is acquired by the staff information acquisition unit 4 at S4, and the schedule information of the staff is acquired by the staff information acquisition unit 4 at S5. The information obtained in the series of information acquisition steps Sa (S1 to S5) is input to the learning model at S6.

[0037] In this way, by inputting the information obtained in the series of information acquisition steps Sa into the learning model at S6, it is possible to output the staff members who should respond to the abnormalities of a specific patient or the blood purification device 1. Then, at S7, the selection unit 6 selects the output staff members and notifies the abnormalities to the mobile terminal 2 carried by the staff members. This notification of the abnormalities includes the position information of the blood purification device 1 acquired at S3, enabling the staff members who receive the notification to quickly head towards the blood purification device 1.

[0038] After selecting the staff members and notifying the abnormalities at S7, at S8, each data after the occurrence of the abnormalities is acquired, and the acquired data is input into the learning model of the staff determination processing unit 5 to update the learning model, thus ending the series of steps. In this manner, each time an abnormality occurs, the related data is input into the learning model for updating, so that the learning model can be continuously updated.

[0039] Next, a method for predicting the occurrence of abnormalities in a specific patient or the blood purification device 1 by the prediction processing unit 8 and proposing an appropriate countermeasure will be described based on the flowchart of FIG. 8. First, when the blood purification treatment starts, various information related to the treatment is input into the prediction processing unit 8. At S1, the learning model is used to predict the occurrence of abnormalities in a specific patient (e.g., a decrease in the patient's blood) or the blood purification device 1 (e.g., a sensor abnormality). At S2, the predicted abnormalities and the proposed appropriate countermeasures are displayed on the display unit 1a.

[0040] Thereafter, staff information is acquired at S3. Such staff information can be acquired, for example, through the same steps as the information acquisition step Sa shown in FIG. 7. Then, the information obtained at S3 is input into the learning model of the staff determination processing unit 5 at S4. At S5, the selection unit 6 selects the staff members who should respond to the predicted abnormalities of the patient or the blood purification device 1, and notifies the prediction of the abnormalities to the mobile terminal 2 carried by the staff members.

[0041] Thus, after selecting the staff at S5 and notifying the abnormality, at S6, each data after the abnormality is predicted is acquired, and the acquired data is input into the learning model of the prediction processing unit 8 to update the learning model, and a series of processes are terminated. In this way, each time an abnormality is predicted, the related data is input into the learning model and updated, so that the learning model can be continuously updated.

[0042] As described above, although the present embodiment has been described, the present invention is not limited thereto. For example, it may be configured not to include the prediction processing unit 8 and not to predict the occurrence of an abnormality in a specific patient or an abnormality in the blood purification device 1 and not to propose an appropriate countermeasure method. Further, the method for acquiring staff information and the communication means can be various forms different from the above embodiment. In the present embodiment, a dialysis device for dialysis treatment is applied, but other devices (for example, a blood purification device used in hemodiafiltration, hemofiltration, AFBF, a plasma adsorption device, etc.) that can purify while extracorporeally circulating the patient's blood may be applied.

[0043] A first embodiment of the present invention is a blood purification device 1 for purifying a patient's blood and performing blood purification treatment. When an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, a necessary skill acquisition unit 3 that acquires necessary skill information required to eliminate the abnormality, and based on the necessary skill information acquired by the necessary skill acquisition unit 3, a staff information acquisition unit 4 that acquires staff information including the position information, schedule information, and skill information of the staff, and when an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, the accumulated data in which a plurality of staff information acquired by the staff information acquisition unit 4 is accumulated is used as teacher data, and a staff determination processing unit 5 that generates and stores a learning model obtained by performing machine learning to determine a staff to be dealt with for an abnormality of a specific patient or the blood purification device 1, and when an abnormality of a patient being treated by the blood purification device 1 or an abnormality of the blood purification device 1 occurs, the staff information acquisition unit 4 acquires the staff information, and inputs the staff information into the learning model of the staff determination processing unit 5 to select a staff to be dealt with, and an abnormality notification unit 7 that notifies the mobile terminal 2 carried by the staff selected by the selection unit 6 of the abnormality of the patient or the blood purification device 1.

[0044] Accordingly, by using the learning model obtained by performing machine learning, when an abnormality occurs in the patient or the blood purification device 1, the staff to be dealt with is determined. Therefore, when an abnormality occurs in the patient or the blood purification device 1, an appropriate staff can be selected in real time, and the selected staff can be notified of the abnormality quickly.

[0045] A second embodiment of the present invention is, in the first embodiment, the position information of the staff acquired by the staff information acquisition unit 4 is detected by the position detection unit 11 provided in the mobile terminal 2 and input in real time. Thereby, the position information of the staff can be acquired accurately and in real time.

[0046] In the third embodiment of the present invention, in the first embodiment, the schedule information of the staff acquired by the staff information acquisition unit 4 is input based on the schedule management unit 12 that manages the work information of the staff. Thereby, the schedule information of the staff can be acquired in detail and accurately.

[0047] In the fourth embodiment of the present invention, in the first embodiment, the selection unit 6 determines the staff who can be corresponded including the staff to be corresponded by the learning model and the priority order of the staff who can be corresponded, and the abnormality notification unit 7 notifies the mobile terminal 2 carried by the staff to be corresponded of the abnormality of the patient or the abnormality of the blood purification device 1, and then notifies other correspondable staff according to the priority order according to the response status of the staff to the notification. Thereby, it is possible to notify other correspondable staff according to the priority order according to the response status of the staff.

[0048] In the fifth embodiment of the present invention, in the first embodiment, the skill information of the staff acquired by the staff information acquisition unit 4 is input based on the specialty, skill, or experience period or number of experiences of the staff. Thereby, the skill information of the staff can be acquired in detail and accurately.

[0049] The sixth embodiment of the present invention includes a prediction processing unit 8 that generates and stores a learning model obtained by performing machine learning for predicting the occurrence of an abnormality of a specific patient or an abnormality of the blood purification device and proposing an appropriate countermeasure method using accumulated data in which a plurality of past information of the patient during treatment by the blood purification device 1 or past information of the blood purification device 1 is accumulated as teacher data, and a display control unit 9 that causes the display unit 1a of the blood purification device 1 to display the occurrence of an abnormality of a specific patient or an abnormality of the blood purification device 1 predicted by the prediction processing unit 8 and the proposal of an appropriate countermeasure method. Thereby, using the learning model obtained by performing machine learning, it is possible to predict the occurrence of an abnormality of a specific patient or an abnormality of the blood purification device 1 and propose an appropriate countermeasure method.

[0050] In the seventh embodiment of the present invention, in the sixth embodiment, the prediction processing unit 8 proposes a plurality of coping methods for the predicted abnormality of a specific patient or the abnormality of the blood purification device 1, and the display control unit 9 causes the display unit 1a to display the plurality of coping methods proposed by the prediction processing unit 8. As a result, the staff can select and cope with the optimal one among the plurality of proposed coping methods.

Industrial Applicability

[0051] As long as it has the same gist as the present invention, it can also be applied to those with different external shapes or those with additional other functions.

Explanation of Reference Numerals

[0052] 1 Blood purification device 1a Display unit 2 Mobile terminal 3 Necessary skill acquisition unit 4 Staff information acquisition unit 5 Staff determination processing unit 6 Selection unit 7 Abnormality notification unit 8 Prediction processing unit 9 Display control unit 10 Display unit 11 Position detection unit 12 Schedule management unit 13 Blood circuit 14 Blood pump 15 Dialyzer 16 Compound pump 17 Dewatering pump

Claims

1. A blood purification device for purifying a patient's blood and performing blood purification treatment, when an abnormality of a patient being treated with the blood purification device or an abnormality of the blood purification device occurs, a necessary skill acquisition unit that acquires necessary skill information required to eliminate the abnormality; a staff information acquisition unit that acquires staff information including staff position information, schedule information, and skill information based on the necessary skill information acquired by the necessary skill acquisition unit; a staff determination processing unit that generates and stores a learning model obtained by performing machine learning to determine a staff member to be dealt with in response to an abnormality of a specific patient or an abnormality of the blood purification device, using, as teacher data, accumulated data in which a plurality of pieces of the staff information acquired by the staff information acquisition unit when an abnormality of a patient being treated with the blood purification device or an abnormality of the blood purification device occurs; when an abnormality of a patient being treated with the blood purification device or an abnormality of the blood purification device occurs, a selection unit that acquires the staff information by the staff information acquisition unit and inputs the staff information into the learning model of the staff determination processing unit to select a staff member to be dealt with; an abnormality notification unit that notifies an abnormality of the patient or the blood purification device to a mobile terminal carried by the staff member selected by the selection unit; A blood purification device having the above.

2. The blood purification device according to claim 1, wherein the position information of the staff acquired by the staff information acquisition unit is detected by a position detection unit provided in the mobile terminal and input in real time.

3. The blood purification device according to claim 1, wherein the schedule information of the staff acquired by the staff information acquisition unit is input based on a schedule management unit that manages the work information of the staff.

4. The selection unit determines staff members who can be dealt with including the staff member to be dealt with in the learning model and the priority order of the staff members who can be dealt with, and after the abnormality notification unit notifies the abnormality of the patient or the blood purification device to the mobile terminal carried by the staff member to be dealt with, according to the response status of the staff member to the notification, notifies other staff members who can be dealt with in accordance with the priority order. The blood purification device according to claim 1.

5. The blood purification device according to claim 1, wherein the skill information of the staff acquired by the staff information acquisition unit is input based on the specialty, skill level, or experience period or number of experiences of the staff.

6. A prediction processing unit that generates and stores a learning model obtained by performing machine learning that predicts the occurrence of an abnormality in a specific patient or an abnormality in the blood purification device using accumulated data in which a plurality of past information of a patient being treated with the blood purification device or past information of the blood purification device is accumulated as teacher data, and proposes an appropriate countermeasure method; A display control unit that causes a display unit included in the blood purification device to display the occurrence of an abnormality in a specific patient or an abnormality in the blood purification device predicted by the prediction processing unit and the proposal of an appropriate countermeasure method; The blood purification device according to claim 1, comprising:

7. The prediction processing unit proposes a plurality of countermeasure methods for the predicted abnormality in a specific patient or the abnormality in the blood purification device, and the display control unit causes the display unit to display the plurality of countermeasure methods proposed by the prediction processing unit. The blood purification device according to claim 6.

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