JP2020144861A - Cerebral apoplexy examination support system - Google Patents

Abstract

To provide a cerebral apoplexy examination support system capable of promptly responding to a patient with the cerebral apoplexy or suspected to have the cerebral apoplexy.SOLUTION: In a system 2, one type of a cerebral apoplexy examination support system, a question provision section 9 provides a terminal 1 with questions relating to the cerebral apoplexy of a patient via an application. A data acquisition section 3 acquires data relating to the cerebral apoplexy of the patient based on answers to the questions from the terminal 1. An estimation section 6 estimates an optimal therapy method for the patient on the basis of the acquired data. A data provision section 7 provides the terminal 1 with the estimated optimal treatment method.SELECTED DRAWING: Figure 1

Description

The present invention relates to a stroke medical care support system.

Stroke is not only one of the three leading causes of death in Japan, but also the number one cause of "bedridden" and the need for long-term care. In Japan, which is facing a super-aging society in the future, it is easy to expect an increase in the number of patients, and countermeasures are important and urgently needed.

There are two types of hyperacute treatment for cerebral infarction, which is one of strokes, tissue plasminogen activator (tPA) intravenous therapy and intravascular recanalization therapy, both of which contribute to the reduction of sequelae of cerebral infarction. Has been proven. Intravascular recanalization therapy is a specific treatment by a specialist, but intravenous tPA therapy does not require a specific procedure as long as the indication is judged, so it can be performed even by a non-stroke specialist. Therefore, it is necessary to establish a system in which as many patients with cerebral infarction as possible can benefit from at least intravenous tPA therapy.

However, as a result of a national survey conducted four years after the approval of intravenous tPA therapy, there are 44 medical areas (13%) that have never received this therapy, and there is a significant regional disparity. It became clear that there was. In Europe and the United States, attempts to overcome this regional disparity in tPA medical care by providing remote medical support began in the 1990s, and now, according to the European guidelines and the American Stroke Association policy statement, 24 hours 365 days of intravenous tPA therapy It is clearly positioned as medical care that must be developed in areas where it cannot be handled, and is proceeding with the commercialization of practical equipment and the development of regional medical networks.

In Japan as well, the necessity is described in the "Stroke Guideline 2015", and it is considered that there is an urgent need to build a telestroke system specialized for stroke in order to enter a super-aging society unlike any other in the world. Currently, remote image support is being provided, but the TeleStroke System, which uses a real-time interactive high-definition video conferencing system similar to that in Europe and the United States, is not yet in place. The TeleStroke System is generally a Hub and Spoke model of hospitals that support medical care (Hub) and hospitals that support remote areas (Spoke), especially in remote areas where stroke specialists cannot be present 24 hours a day. In some hospitals, a stroke-specific remote medical system (Telestroke) is a useful tool.

Imai T et al: Specific needs for telestroke networks for thrombolytic therapy in Japan. J Stroke Cerebrovasc Dis 23: 811-816,2013 Schwamm LH et al: Recommendations for the implementation of telemedicine within stroke systems of care: apolicy statement from the American Heart Association. Stroke 40: 2635-2660, 2009 Japan Stroke Society: Stroke Guidelines 2015

However, the Hub and Spoke model remote medical system (Telestroke) has a high introduction cost, and in order to deal with strokes that require an immediate response system, a specialist on the Hub side and a non-specialist on the Spoke side are resident. It is necessary to accept a 24-hour system by exchanging information with each other, and the spread is not progressing due to concerns about cost effectiveness related to labor costs and introduction costs.

The present invention has been made in view of such a problem, and an object of the present invention is to reduce the introduction cost, and even a non-specialist in a remote place can immediately respond to a patient suspected of having a stroke. It is to provide a support system.

The present inventors are conducting diligent research to solve the above problems, and by using a system that can support face-to-face medical examinations by non-specialists and present treatment guidelines, even non-specialists can be suspected of having a stroke. The present invention was completed by finding that a ready-to-use system can be constructed.

That is, the present invention relates to the following.

[1] Medical support to support medical treatment of patients based on data obtained by sequentially using applications for executing information processing necessary for medical treatment of patients with stroke or suspected stroke. It ’s a system
Question Providing Department, which provides questions related to a patient's stroke through an application,
Data acquisition department, which acquires data related to the patient's stroke obtained by answering the question,
The medical care support system including an estimation unit that estimates an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing unit that provides an optimum treatment method estimated by the estimation unit.
[2] The medical care support system according to [1], wherein the estimation unit estimates the applicability of intravenous tPA therapy based on data related to the onset time of a patient.
[3] The medical care support system according to [2], wherein the estimation unit estimates the applicability of intravenous tPA therapy based on data related to the patient's medical history.

[4] The medical care support system according to any one of [1] to [3], wherein the estimation unit estimates the applicability of intravenous tPA therapy based on the data related to the patient's NIHSS score. ..
[5] The description in any one of [1] to [4], wherein when the estimation unit estimates that intravenous tPA therapy is applicable, data related to tPA administration is provided to the data provider. Medical support system.
[6] The medical care support according to any one of [1] to [4], which provides an appropriate instruction plan to the data providing department when the estimation department estimates that tPA intravenous therapy is not applicable. system.
[7] A time calculation unit that calculates the difference between the patient's onset time and the tPA applicable time is further included, and the estimation unit calculates the applicable time of tPA intravenous therapy based on the calculated data of the time calculation unit. The medical treatment support system according to any one of [1] to [6] provided in.
[8] The medical care support system according to any one of [1] to [7], which identifies the type of stroke selected from the group consisting of the presence or absence of cerebral infarction, hemorrhagic lesions, and lesions.
[9] The medical care support system according to any one of [1] to [8], wherein the estimation by the estimation unit includes an estimation by AI.
[10] The medical care support system according to any one of [1] to [9], wherein the data includes image data, and the processing by the estimation unit includes image interpretation processing.
[11] A network system can be constructed by connecting a plurality of medical care support systems to each other, and the processing by the estimation unit is a process based on the data shared among the plurality of medical care support systems, [1] to The medical care support system according to any one of [10].
[12] An application that cooperates with the medical care support system according to any one of [1] to [11] and that functions as an input / output unit of the medical care support system.

[13] Medical support for supporting the medical treatment of patients based on the data obtained by sequentially using the application for executing the information processing necessary for the medical treatment of the patient who has or is suspected of having a stroke. It ’s a program
Question-providing means, which provides questions related to a patient's stroke through an application,
A data acquisition method for acquiring data related to a patient's stroke obtained by answering a question,
The medical care support program including an estimation means for estimating an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing means for providing an optimum treatment method estimated by the estimation unit.
[14] The medical care support program according to [13], wherein the estimation unit estimates the applicability of intravenous tPA therapy based on data related to the time of onset of a patient.
[15] Medical support for supporting patient medical care based on data obtained by sequentially using an application for executing information processing necessary for patient medical care in the hyperacute stage of cerebral infarction. It ’s a system
Question Providing Department, which provides questions related to a patient's stroke through an application,
Data acquisition department that acquires data related to cerebral infarction of patients obtained by answering questions,
The medical care support system including an estimation unit that estimates an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing unit that provides an optimum treatment method estimated by the estimation unit.
[16] The application that cooperates with the medical care support system according to [15] and that functions as an input / output unit of the medical care support system.
[17] Medical support for supporting patient medical care based on data obtained by sequentially using an application for executing information processing necessary for patient medical care in the hyperacute stage of cerebral infarction. It ’s a program
Question-providing means, which provides questions related to a patient's stroke through an application,
Data acquisition means for acquiring data related to cerebral infarction of patients obtained by answering questions,
The medical care support program including an estimation means for estimating an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing means for providing an optimum treatment method estimated by the estimation unit.

By using the system of the present invention, the introduction cost can be reduced by constructing an application or the like on the information terminal used by the user without constructing a remote medical system (Telestroke) of the Hub and Spoke model, which has a high introduction cost. It is suppressed, and it is possible for non-specialists to respond immediately to patients with suspected stroke. In addition, in areas where medical resources are scarce, the need for in-hospital non-specialists who provided initial medical care to consult with out-of-hospital specialists will be reduced, and the burden on specialists who have been on-call will be reduced. ..

Furthermore, by rapidly identifying the type of stroke, for example, based on the data obtained by the user sequentially using an application for performing information processing necessary for medical treatment of a patient in the hyperacute stage of cerebral infarction. It is possible to support the medical treatment of patients in the hospital, and in areas where medical resources are scarce, non-specialists who provided initial medical treatment can decide treatment policies without consulting with specialists outside the hospital. In addition, it is possible to reduce the sequelae of cerebral infarction patients by rapidly estimating the possibility of administration of tPA, which generally needs to be administered within 4.5 hours.
In addition, if necessary, the medical treatment support system used in the hospital can be connected to another medical treatment support system in the hospital, an out-of-hospital medical treatment support system, an information terminal of a specialist, AI, a database, etc. It is possible to estimate the optimal treatment method based on the above and provide it to non-specialists.

FIG. 1 is a block diagram showing a functional configuration example of the system according to the first embodiment. FIG. 2 is a flowchart showing an operation example of the system according to the first embodiment. FIG. 3 is a diagram showing question items of question 1 (checklist 1). FIG. 4 is a diagram showing a modified example of the system of FIG. FIG. 5 is a flowchart showing an operation example after the operation example of FIG. 6A to 6D are diagrams showing question items of Question 2 (NIH Stroke Scale). 6A to 6D are diagrams showing question items of Question 2 (NIH Stroke Scale). 6A to 6D are diagrams showing question items of Question 2 (NIH Stroke Scale). 6A to 6D are diagrams showing question items of Question 2 (NIH Stroke Scale). 7A to 7B are diagrams showing the question items of Question 3 (checklist 2). 7A to 7B are diagrams showing the question items of Question 3 (checklist 2). FIG. 8 is a diagram showing question items of questions 4 to 6 (checklists 3 to 5). FIG. 9A is a diagram showing the display contents of the instruction plan A. FIG. 9B is a diagram showing the display contents of the instruction plan B. FIG. 9C is a diagram showing the display contents of the instruction plan C. FIG. 9D is a diagram showing the display contents of the instruction plan Z. FIG. 10A is a diagram showing display contents of data related to tPA administration. FIG. 10B is a diagram showing the display contents of the instruction plan T. FIG. 11 is a block diagram showing an overall configuration example of the network system according to the second embodiment. FIG. 12 is a flowchart showing an operation example of the system according to the second embodiment. FIG. 13 is a flowchart showing an operation example of the system according to the second embodiment. FIG. 14 is a flowchart showing an operation example of the system according to the second embodiment. FIG. 15 is a flowchart showing an operation example of the system according to the second embodiment.

<First Embodiment>
Hereinafter, the first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing an overall configuration example of the system according to the present embodiment. The system 2 shown in FIG. 1 is an information terminal 1 used by a patient suspected of having a stroke (in the case of the present embodiment, cerebral infarction as an example) or a doctor (hereinafter referred to as a user) who treats such a patient. Communication is possible. The system 2 includes a data acquisition unit 3, a storage unit 4, an estimation unit 6, a data providing unit 7, a question processing unit 8, and a question providing unit 9. The system 2 can also be incorporated into the information terminal 1.

Each functional block 3 to 9 of the system 2 can be configured by any of hardware, DSP, and software. For example, when configured by software, each functional block 3 to 9 is actually configured to include a computer CPU, RAM, ROM, etc., and a program stored in a recording medium such as RAM, ROM, hard disk, or semiconductor memory. It is realized by working. The functional blocks 3 to 9 may be separately arranged at different locations on the network so that they can communicate with the information terminal 1 used by the user (network connection is possible).

The user can sequentially execute various information processing necessary for treatment by using an application installed on the information terminal 1. For example, the user can input an answer to a cerebral infarction-related inquiry (question) provided from the system 2 to the application of the information terminal 1. The question processing unit 8 can extract the question content stored in advance in the storage unit 4 and provide it to the application via the question providing unit 9. That is, the application can function as the software of the medical care support system of the present invention and also as an input / output unit.

The data acquisition unit 3 can acquire various data obtained by the user sequentially using the application from the information terminal 1. Specifically, the data acquisition unit 3 acquires the data of the answers to the questions provided to the application of the information terminal 1 from the system 2, and the storage unit 4 acquires the question contents to be provided to the application and the data acquisition unit 3. The data acquired by can be stored.

The estimation unit 6 estimates the optimum treatment method according to the answer contents of the questions stored in the storage unit 4, and the data providing unit 7 provides the application with the optimum treatment method estimated by the estimation unit 6. be able to. Further, when the estimation unit 6 estimates that a further question is necessary according to the answer content of the question, the question processing unit 8 extracts the further question and provides it to the application via the question providing unit 9. You can also do it. For example, the estimation unit 6 uses a mathematical model 61 (algorithm, etc.) to perform algorithm analysis (information processing) on the answer contents of the question by the processing unit 62 (CPU, etc.), thereby performing the optimum treatment method and the optimum. Further questions can be inferred. Therefore, when the system 2 is incorporated in the information terminal 1, even if the communication with the outside of the hospital is interrupted due to a disaster or the like, the system 2 can be used to continue the medical treatment.

In this way, the application transmits the execution result (answer to the question) of the information processing by the user to the system 2, and receives and displays the notifications regarding various treatment advices from the system 2, so that the action is effective for the treatment. Can be prompted to the user. By acting according to the content of this advice, the user can deal with the cerebral infarction of the patient in a medical field where there is no specialist in cerebral infarction. This is particularly advantageous in areas where medical resources are scarce, because non-specialists who have undergone initial medical care can decide treatment policies without consulting with specialists outside the hospital.

FIG. 2 is a flowchart showing an operation example of the system according to the present embodiment configured as described above.

First, the question processing unit 8 can extract a question related to cerebral infarction stored in the storage unit 4 and provide it to the application via the question providing unit 9. Examples of the question include a question related to cerebral infarction (checklist 1) as shown in FIG. Checklist 1 is a selection-type checklist as shown in FIG. 3, and the user answers seven questions by selecting "Yes" or "No" for each question. be able to.

As shown in FIG. 3, the checklist 1 indicates, for example, whether the question regarding the time of onset exceeds 4.5 hours from the time of onset, and whether or not there is non-traumatic intracranial hemorrhage as a question regarding the history. Presence or absence of cerebral infarction (not including transient ischemic attack) within 3 months, presence or absence of severe head and spinal cord trauma or surgery within 3 months, presence or absence of gastrointestinal or urinary tract bleeding within 21 days It can include questions such as major bleeding within 14 days or serious trauma other than the head, and the presence or absence of therapeutic drug hypersensitivity.

The system 2 can acquire the content of the user's reply via the application via the data acquisition unit 3 and store the response content in the storage unit 4. The estimation unit 6 analyzes the contents of the answers stored in the storage unit 4, and if there are no “yes” in the checklist 1, it is estimated that tPA may be administered, and the tPA is likely to be administered via the data providing unit 7. , Can provide data that causes the application to display "tPA may be administered". In addition, the estimation unit 6 estimates that there is no possibility of tPA administration when there is one or more "yes" in the checklist 1, and tells the application "no possibility of tPA administration" via the data providing unit 7. Data to be displayed can be provided.

In addition, the system 2 provides data for displaying "tPA may be administered", and then provides data for displaying the next treatment such as blood test (including coagulation system), head MRI or CT electrocardiogram, and X-ray. You can also do it. Furthermore, the system 2 provides data for displaying "no tPA administration possibility" and then data for displaying the next treatment such as blood test (including coagulation system), head MRI + MRA or CT electrocardiogram, and X-ray. You can also do it.

In this way, the system 2 sends the user a question related to the patient's cerebral infarction and obtains an answer from the user to quickly estimate the possibility of tPA administration and provide it to the application. Can be done.

FIG. 4 shows a modified example of the system 2 of FIG. In the case of this modification, the system 2 further includes a time calculation unit 5, and the checklist 1 is configured to input the onset time numerically as a question regarding the onset time. Then, for example, when the system 2 is programmed that the administration of tPA needs to be performed within 4.5 hours from the onset time of the cerebral infarction, the time calculation unit 5 determines the onset time and the tPA applicable time. The difference from (from the onset time to 4.5 hours) can be calculated and provided to the estimation unit 6.
In the present invention, the "data related to the onset time" includes the time when the cerebral infarction occurs, and when the onset time is unknown, the final non-onset time can be used as the onset time.

The estimation unit 6 is based on the data calculated by the time calculation unit 5 and the current time, and the tPA static such as the remaining time (countdown) at which tPA can be applied and the time (time limit) at which tPA cannot be applied. Data regarding the applicable time of injection therapy can be transmitted to the data providing unit 7. Further, when the current time exceeds the tPA applicable time, the estimation unit 6 can transmit the data to be displayed as "no tPA administration possibility" to the data providing unit 7.

As described above, the system 2 of this modified example can provide the applicable time of the intravenous tPA therapy in addition to estimating the presence or absence of the possibility of tPA administration by having the time calculation unit 5. This is particularly advantageous in intravenous tPA therapy, which should be administered within 4.5 hours of the onset of cerebral infarction.

FIG. 5 is a flowchart showing an operation example after the operation example of the flowchart of FIG.

The system 2 can provide the application with the next question after displaying the possibility of tPA administration to the application via the data providing unit 7. Specifically, the estimation unit 6 estimates an appropriate next question based on the above estimation result and provides it to the question processing unit 8. The question processing unit 8 can extract data related to the next question estimated by the estimation unit 6 from the storage unit 4 and provide the data to the application via the question providing unit 9. The next question includes, for example, Question 2 (NIH Stroke Scale) related to cerebral infarction as shown in FIGS. 6A to 6D.

As shown in FIGS. 6A-D, the NIH Stroke Scale (NIHSS measurement) is, for example, consciousness level, dysarthria, best gaze, visual field, facial paralysis, upper limb movement, lower limb movement, ataxia, sensation, best. Can include questions such as language, dysarthria, and erase / ignore. Then, the answer to each question can be selected from a plurality of answer candidates by a selection formula. In addition, the commentary portion shows specific actions that the user takes with respect to the patient in order to obtain an answer to each question.

The system 2 can provide a question about the NIH Stroke Scale to the application of the information terminal 1 via the question providing unit 9. In addition to providing the question, the system 2 can also provide a specific action that the user takes on the patient in order to obtain an answer to the question. Then, the system 2 can acquire the answer contents via the data acquisition unit 3 and store them in the storage unit 4. The NIHSS measurement quantifies the severity of cerebral infarction patients and can be used to measure the severity of cerebral infarction on a regular basis from the first medical examination (on the day of admission) and to confirm the progress of the severity of cerebral infarction. By analyzing the content of each response, the estimation unit 6 can determine the careful administration of patients with the possibility of tPA indication as described below and provide appropriate medical treatment content after hospitalization. Further, for example, as shown in FIGS. 6A to 6C, by weighting each answer with a score of 1 to N and continuously measuring from the day of admission, the estimation unit 6 can obtain the total score of the NIH Stroke Scale. Based on this, the degree of progression of cerebral infarction can be estimated and the estimation result can be provided.

As shown in FIG. 5, the system 2 can further ask the application the next question after storing the data related to the NIH Stroke Scale. Specifically, the estimation unit 6 estimates an appropriate next question based on the data related to the above NIH Stroke Scale and provides it to the question processing unit 8. The question processing unit 8 can extract data related to the next question estimated by the estimation unit 6 from the storage unit 4 and provide the data to the application via the question providing unit 9. The next question includes, for example, question 3 (checklist 2) related to cerebral infarction as shown in FIGS. 7A-B.

As shown in FIGS. 7A-B, Checklist 2 may include, for example, questions related to non-tPA indications such as clinical findings, blood tests, blood findings, CT / MR findings (FIG. 7A). 7A). In addition, Checklist 2 shows, for example, questions related to careful administration, such as age (81 years or older), history, biopsy / trauma within 10 days, delivery / premature delivery within 10 days, and 1 month or more. Cerebral infarction (especially cases with diabetes), myocardial infarction within 3 months, protein allergy, neurological signs, NIHSS score 26 or higher, mild, rapid mildening of symptoms, convulsions (presence of epilepsy, etc.) (Not indicated), clinical symptoms, cerebral aneurysm / intracranial tumor / cerebral arteriovenous malformation / haze disease, thoracic aortic aneurysm, gastrointestinal ulcer / diverticulitis, colitis, active tuberculosis, diabetic hemorrhagic retinopathy / bleeding Includes questions such as sexual ophthalmopathy, thrombolytics, antiplatelet drugs (especially oral anticoagulants), menstrual periods, severe nephropathy, uncontrolled diabetes, infectious endocarditis, etc. Can be done (Fig. 7B).

The system 2 can acquire answers to questions related to non-tPA indication and answers to questions related to careful administration via the data acquisition unit 3, and store the answer contents in the storage unit 4. The estimation unit 6 analyzes the contents of the answers stored in the storage unit 4, and for example, there is no "yes" in the answers related to non-tPA indication, and there is a slight "yes" in the answers related to careful administration. If there are (for example, two or less), data instructing tPA administration is transmitted to the data providing unit 7. The estimation unit 6 transmits data related to tPA administration (including total amount, dose, rapid intravenous injection amount, continuous intravenous injection amount, items related to final confirmation before tPA administration, etc.) to the data providing unit 7. , The question processing unit 8 can be extracted and provided to the question providing unit 9.

Items related to the final confirmation before tPA administration include explanation and consent to the family, urinary tract catheter placement (do not overdo it), arterial dissection excluded, blood pressure measurement (systolic blood pressure) within 4 hours and 30 minutes from the time of onset. When 180 mmHg or more or diastolic blood pressure 105 mmHg or more, Nikaldipine (10) 5A 2 ml started 2 ml / h after intravenous injection, then increased or decreased by 1 ml / h according to blood pressure (systolic blood pressure 140 mmHg or less, 1 ml / h weight loss), NIHSS score Measurements can be included.

In addition, the estimation unit 6 analyzes the contents of the answers stored in the storage unit 4, and for example, there is "yes" in the answers related to non-tPA indication, and there are many "yes" in the answers related to careful administration. If there are (for example, three or more), the next question 4 (checklist 3) can be extracted by the question processing unit 8 and provided to the question providing unit 9. Similarly, the system 2 provides the next question 5 (checklist 4) according to the answer contents of the checklist 3, and further, the next question 6 (checklist 5) according to the answer contents of the checklist 4. Can also be provided.

As shown in FIG. 8, the checklist 3 can include, for example, question items such as within 6 hours from the onset time, under 40 years old, headache, neck pain, chest pain, etc. If there is one or more, the estimation unit 6 transmits the instruction plan A to the data providing unit 7. Then, the estimation unit 6 causes the question processing unit 8 to extract the next question 5 (checklist 4) when “yes” does not exist. Checklist 4 can include, for example, question items such as atrial fibrillation, 10 or more D-dimers, and frequent occurrences in multivascular areas. If there is one or more "yes", the estimation unit 6 transmits the instruction plan B to the data providing unit 7. Then, the estimation unit 6 causes the question processing unit 8 to extract the next question 6 (checklist 5) when “yes” does not exist.

The checklist 5 can include, for example, a question item such as whether it is within 48 hours after the onset, and the estimation unit 6 transmits the instruction plan C to the data providing unit 7 within 48 hours, and 48 If the time is exceeded, the instruction plan Z is transmitted to the data providing unit 7. In one aspect, the checklist 5 can be omitted, and in this case, it is determined whether or not it is within 48 hours after the onset based on the data calculated by the time calculation unit 5 and the current time. However, it can also be configured to transmit the instruction plan C or the instruction plan Z. The instruction plans A to Z transmitted to the data providing unit 7 include the presentation of treatment methods and post-hospital instructions as shown in FIGS. 9A to 9D. When tPA administration is performed as described above, data is provided as Plan T, including data related to tPA administration (FIG. 10A) and post-administration instructions (FIG. 10B), as shown in FIGS. 10A and 10B. It can also be transmitted to unit 7.

As described above, the system according to the present embodiment is based on the data obtained by the user sequentially using the application for executing the information processing necessary for the medical treatment of the patient in the hyperacute stage of cerebral infarction. In areas where medical resources are scarce, non-specialists who provided initial medical care can decide treatment policies without consulting with specialists outside the hospital. In addition, it is possible to reduce the sequelae of cerebral infarction patients by rapidly estimating the possibility of administration of tPA, which generally needs to be administered within 4.5 hours. Furthermore, by providing the instruction plans A to Z as described above, it is possible to flexibly and widely respond to the symptoms of cerebral infarction.

<Second Embodiment>
Hereinafter, a second embodiment of the present invention will be described. FIG. 11 is a block diagram showing an overall configuration example of the network system according to the present embodiment, and FIGS. 12 to 15 are flowcharts showing an operation example of the system according to the present embodiment. In the present embodiment, the patient is a patient suspected of having a stroke, a plurality of information terminals 1 exist on the network and can communicate with each other, and the user is a doctor (non-specialist) who treats the patient, such a doctor. Includes specialists (neurologists, brain surgeons, radiological technologists, etc.) to support.

As shown in FIG. 11, in the network system according to the present embodiment, a plurality of information terminals 1 (desktop PC, laptop PC, smartphone, tablet PC, etc.) exist on the network, and these can communicate with each other. In addition, each information terminal 1 can communicate with each other with an artificial intelligence AI, a database server, and cloud computing arranged on the network.

As described in the first embodiment, each information terminal 1 can communicate with the system 2, and the system 2 also includes the functional blocks 3 to 9. The functional blocks 3 to 9 can also be arranged separately at different locations on the network. That is, for example, the storage unit 4 can be realized by using a database server, and the processing unit 62 can be realized by using an artificial intelligence (AI) system. The storage unit 4 can be realized by using a plurality of different resources on the network, such as storing the data that can be shared on the network in the database server and the data that cannot be shared in the memory of the information terminal 1.

Further, as in the case of constructing a general smartphone application (smartphone application), the system 2 is constructed on cloud computing (for example, AWS), and the application installed on the information terminal 1 is input / output (interface). It is also possible to send and receive data to and from the system 2. In ultra-high-speed communication (4G, 5G), all information processing is performed on the cloud, and the information terminal 1 only needs to realize the minimum functions as an input / output unit such as input and display, and resources (CPU speed). , Memory capacity, etc.) Even the information terminal 1 can use the functions of the system 2 (that is, the functions of the medical care support system).

As shown, non-specialist A working at hospital A can also install and interconnect applications on both smartphones and desktop PCs, for example. Then, when dealing with a patient suspected of having a stroke, it is possible to conduct a medical inquiry using a smartphone application as described above and perform work related to the patient's brain image using a desktop PC application. That is, the system 2 of the present invention can be configured to further process image data in addition to information (data) such as the above-mentioned questions, answers to questions, and treatment methods.

Specifically, the data acquisition unit 3 acquires image (for example, brain image) data about the patient sent from an imaging device (MRI, CT, etc.) connected to the desktop PC, and the storage unit 4 acquires the image. The data is stored, the estimation unit 6 can perform AI analysis (image interpretation) of the image data stored in the storage unit 4, and the data providing unit 7 can provide the analysis result by the estimation unit 6 to the application. Further, when the estimation unit 6 determines that further analysis is necessary, the question processing unit 8 is provided with another user on the network (for example, specialist D who is a brain surgeon) who can handle further image analysis on call. It is also possible to automatically extract and transmit the image data to the information terminal 1 of the specialist D via the question providing unit 9.

Then, the specialist D further analyzes the received image data and transmits the further analysis result via the information terminal 1, and the data acquisition unit 3 on the non-specialist A side receives the further analysis result and is an estimation unit. Upon transmission to 6, the estimation unit 6 can provide the application with a more accurate analysis result based on the original analysis result and the further analysis result. In addition, each information terminal 1 on the network uses a data acquisition unit 3, an estimation unit 6, a question providing unit 9, a data providing unit 7, and the like to create a database of data sets including the above image data and its analysis results. Sending daily to the server, the database server can store these datasets as big data.

Then, the artificial intelligence system can also be configured to analyze the image by the processing unit 62 (AI) by using the mathematical model 61 (deep learning model). That is, by having an artificial intelligence system machine-learn the above big data as patterning of image data and its analysis results, and further deep learning (deep learning), the mathematical model 61 is developed into a machine learning model and a deep learning model. You can also let it. Big data may include data such as the above-mentioned questions, answers to questions, and treatment methods, and by deep learning these, the contents of questions and estimation of treatment methods can be evolved. The system 2 of the present invention including such an artificial intelligence system (estimation unit 6) can provide the above-mentioned big data, AI, and deep learning model to the non-specialist A as collective intelligence. Since the non-specialist A can always access the collective intelligence via the information terminal 1, it is possible to construct an immediate response system for a patient suspected of having a stroke without relying on a specialist.

Needless to say, as described above, as in the case where the image data for further image analysis is transmitted to the information terminal 1 of the specialist D, the answer data to the question is used as the answer data for further estimation, for example, a hospital. It can also be sent to B's specialist B. That is, in the items of the above checklist, it is possible to provide an item that is neither a non-specialist nor an estimation unit 6 and always requires the judgment (estimation) of a specialist. Then, when the estimation unit 6 receives the checklist (answer data) in which such items are selected, another user on the network (for example, specialist B) who can respond to the question processing unit 8 on-call further judgment (estimation). Can be automatically extracted and the answer data and the image data can be transmitted together to the information terminal 1 of the specialist B via the question providing unit 9.

Non-specialist A can also receive consultation from specialist B by using the SNS messenger, voice communication, Web conferencing system, etc. incorporated in the application, if necessary. Further, the specialist B can transfer the response data and the image data to the information terminal 1 of another specialist C in the same hospital B as necessary, and can receive the consultation of the specialist C. Then, when the non-specialist A works at a clinic in a developing country, he / she can receive consultation from a specialist in another country, for example, a developed country by using an automatic translation function or the like.

It is also possible to take an image (MRI image, CT image, etc.) obtained by the above-mentioned imaging device with a smartphone and transmit it to the information terminal 1 of a specialist. Furthermore, by incorporating an API that enables direct communication between the information terminal 1 (application) and the imaging device, the system of the present invention can be achieved by simply installing the application on the smartphone (information terminal 1) even in a clinic with limited equipment. 2 can be used freely anywhere. As a result, in a country like Japan where the birthrate is declining and the population is aging, it is possible to connect local clinics with hospitals in cities, and by connecting hospitals in developing countries with poor medical environments and hospitals in developed countries. , Can support the medical treatment of non-specialists. In addition, for example, by connecting a clinic in a rural area of Japan with a hospital in another city with a time difference, a 24-hour support system for non-specialists can be constructed.

As described above, the system 2 of the present invention can further include various functions such as an SNS messenger, a voice communication, a Web conferencing system, an automatic translation function, an image capturing function, and an imaging device API function. Modules that realize these functions are provided by general cloud computing, and such modules are added to the functional blocks 3 to 9 of the system 2 as new functional blocks 10 to 14 (not shown). You can also. Those skilled in the art can further strengthen the medical care support system by adding necessary functions related to stroke medical care as new functional blocks as appropriate.

An operation example of the system according to the present embodiment will be briefly described with reference to the flowcharts shown in FIGS. 12 to 15. As shown in FIG. 12, first, the question providing unit 9 displays a message requesting a brain image of a stroke or a patient suspected of having a stroke on the information terminal 1 of the non-specialist A through an application. Non-specialist A sends the image data through the application, and System 2 interprets the image to identify the type of stroke selected from the group consisting of cerebral infarction, hemorrhagic lesions, and the presence or absence of lesions, and obtains the identification result. Provide to non-specialist A. In the case of cerebral infarction, according to the cerebral infarction flow in the figure, by transmitting the data instructing tPA administration to the data providing unit 7 as described above, the treatment of the cerebral infarction of non-specialist A in the hyperacute stage is supported. be able to.

If it is a hemorrhagic lesion rather than a cerebral infarction, the information terminal 1 displays a question for estimating whether it is an intracerebral hemorrhage or a subarachnoid hemorrhage or a request for further imaging. In case of intracerebral hemorrhage, F. Proceed to cerebral hemorrhage logic and if you have subarachnoid hemorrhage, seek neurosurgery consultation. Furthermore, if it is neither a cerebral infarction nor a hemorrhagic lesion, the presence or absence of a lesion is analyzed, and if there is no lesion, G. Proceed to Stroke Mimic Logic and consult a specialist if there is a lesion. Details of the logics A to G in FIG. 12 are as shown in FIGS. 13 to 15. In each step in the flow shown in FIGS. 13 to 15, if there is a step that needs to be consulted by a specialist, a step that needs to be judged from collective intelligence, a step that needs AI analysis, etc., those steps are automatically performed. The flow can also be configured to proceed in a targeted manner. Those skilled in the art can combine the steps necessary to treat a stroke or suspected stroke patient to build an optimal flow.

As described above, by constructing a network system by interconnecting a plurality of information terminals 1 on which the system (medical care support system) 2 of the present invention is installed, a network system can be constructed between the plurality of systems 2, a database server, and cloud computing. , Information can be shared by artificial intelligence systems. And by fusing new knowledge created by information sharing, new knowledge created by comparison processing with a huge amount of past data by deep learning, ultra-high-speed processing by cloud computing, etc., it did not exist until now. It is possible to realize an advanced medical care support system. Therefore, the stroke medical care support system of the present invention can be used not only as medical care support for non-specialists, but also as a medical care support system for specialists and radiological technologists, as well as medical personnel, university institutions, international institutions, etc. It can also be used as a stroke information database to share new findings among others.

1 Information terminal 2 System 3 Data acquisition unit 4 Storage unit 5 Time calculation unit 6 Estimating unit 61 Mathematical model 62 Processing unit 7 Data providing unit 8 Question processing unit 9 Question providing unit

Claims (17)

It is a medical care support system to support the medical care of patients based on the data obtained by sequentially using the application for executing the information processing necessary for the medical care of patients with stroke or suspected stroke. hand,
Question Providing Department, which provides questions related to a patient's stroke through an application,
Data acquisition department, which acquires data related to the patient's stroke obtained by answering the question,
The medical care support system including an estimation unit that estimates an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing unit that provides an optimum treatment method estimated by the estimation unit. The medical care support system according to claim 1, wherein the estimation unit estimates the applicability of intravenous tPA therapy based on data related to the time of onset of the patient. The medical care support system according to claim 2, wherein the estimation unit estimates the applicability of intravenous tPA therapy based on data related to the patient's medical history. The medical care support system according to any one of claims 1 to 3, wherein the estimation unit estimates the applicability of intravenous tPA therapy based on the data related to the patient's NIHSS score. The medical care support system according to any one of claims 1 to 4, wherein the estimation unit provides the data provider with data related to tPA administration when the estimation unit estimates that intravenous tPA therapy is applicable. The medical care support system according to any one of claims 1 to 4, wherein an appropriate instruction plan is provided to the data providing unit when the estimation unit estimates that tPA intravenous therapy is not applicable. It further includes a time calculation unit that calculates the difference between the patient's onset time and the tPA applicable time, and the estimation unit provides the data provider with the applicable time of tPA intravenous therapy based on the calculated data of the time calculation unit. , The medical treatment support system according to any one of claims 1 to 6. The medical care support system according to any one of claims 1 to 7, which identifies the type of stroke selected from the group consisting of cerebral infarction, hemorrhagic lesions, and the presence or absence of lesions. The medical care support system according to any one of claims 1 to 8, wherein the estimation by the estimation unit includes an estimation by AI. The medical care support system according to any one of claims 1 to 9, wherein the data includes image data, and the processing by the estimation unit includes image interpretation processing. Any of claims 1 to 10, wherein a network system can be constructed by interconnecting a plurality of medical care support systems, and the process by the estimation unit is a process based on data shared among the plurality of medical care support systems. The medical care support system described in item 1. The application that cooperates with the medical care support system according to any one of claims 1 to 11 and functions as an input / output unit of the medical care support system. It is a medical care support program to support the medical care of patients based on the data obtained by sequentially using the application for executing the information processing necessary for the medical care of patients with stroke or suspected stroke. hand,
Question-providing means, which provides questions related to a patient's stroke through an application,
A data acquisition method for acquiring data related to a patient's stroke obtained by answering a question,
The medical care support program including an estimation means for estimating an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing means for providing an optimum treatment method estimated by the estimation unit. The medical care support program according to claim 13, wherein the estimation unit estimates the applicability of intravenous tPA therapy based on data related to the time of onset of the patient. It is a medical care support system to support the medical care of patients based on the data obtained by sequentially using the application for executing the information processing necessary for the medical care of patients in the hyperacute stage of cerebral infarction. hand,
Question Providing Department, which provides questions related to a patient's stroke through an application,
Data acquisition department that acquires data related to cerebral infarction of patients obtained by answering questions,
The medical care support system including an estimation unit that estimates an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing unit that provides an optimum treatment method estimated by the estimation unit. The application that cooperates with the medical care support system according to claim 15 and functions as an input / output unit of the medical care support system. It is a medical care support program to support the medical care of patients based on the data obtained by sequentially using the application for executing the information processing necessary for the medical care of patients in the hyperacute stage of cerebral infarction. hand,
Question-providing means, which provides questions related to a patient's stroke through an application,
Data acquisition means for acquiring data related to cerebral infarction of patients obtained by answering questions,
The medical care support program including an estimation means for estimating an optimal treatment method for a patient based on data acquired by a data acquisition unit, and a data providing means for providing an optimum treatment method estimated by the estimation unit.