Information processing method, program, and information processing device

Abstract

This information processing method acquires, by a computer, a life record including text information in which the life of a subject is recorded, determines, on the basis of the life record, whether or not a psychological symptom and / or a behavioral symptom related to dementia is occurring in the subject, and if the result of the determination indicates that the symptom is occurring, determines, on the basis of the life record, whether or not the subject has occurred a psychological symptom and / or a behavioral symptom. One or more candidate causes for symptom occurrence are identified, and symptom information indicating a determination result and candidate cause information indicating each of the one or more candidate causes are output to the user device in accordance with a user's request.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based on Japanese patent application No. 2022-126487 filed on August 8, 2022, and the contents thereof are cited herein. Technical Field

[0003] The present disclosure relates to an information processing method, a program, and an information processing apparatus. Background Art

[0004] Conventionally, there is a technique for determining the occurrence of behavioral symptoms and psychological symptoms of a subject using sensor data obtained by sensing the subject's body and the subject's surrounding environment. Patent document 1 below discloses a method for determining the subject's sleep conditions, such as the frequency of waking, taking naps, or sleeping at night, based on sensor data related to the subject, and determining the occurrence of peripheral symptoms of dementia in the subject based on the determined sleep conditions.

[0005] Prior art documents

[0006] Patent Literature

[0007] Patent Document 1: Japanese Patent Application Publication No. 2019-076689 Summary of the invention

[0008] In the technology described in Patent Document 1, when using sensor data to determine the occurrence of behavioral symptoms or psychological symptoms of a subject, a unified judgment can only be made based on quantitative data. However, for example, when a sleep sensor is used, even when the sensor data indicates that subject A and subject B have the same sleep condition, the restful sleep conditions of subject A and subject B may be different from each other. Subject A may feel safe about his current sleep condition, while subject B may feel unsafe about his current sleep condition. In this way, it is difficult to determine the occurrence of behavioral symptoms or psychological symptoms corresponding to each subject. Furthermore, in the case of a unified judgment result, when determining what the main cause is based on the result of the judgment, a unified response method will be adopted.

[0009] Therefore, some aspects of the present disclosure aim to provide an information processing method, a program, and an information processing device that can determine the occurrence of behavioral symptoms and psychological symptoms for each subject and identify candidate causes of the occurrence.

[0010] In an information processing method involved in one embodiment of the present invention, a computer obtains a life record containing text information recording the life of a subject, and based on the life record, determines whether the subject is experiencing psychological symptoms and / or behavioral symptoms related to dementia, and when the result of the determination indicates that the symptoms are occurring, determines one or more candidate causes of the occurrence of the symptoms based on the life record.

[0011] In a program involved in one embodiment of the present invention, a computer is caused to implement: an acquisition function, which acquires a life record containing text information recording the life of a subject; and a judgment function, which judges whether the subject is experiencing psychological symptoms and / or behavioral symptoms related to dementia based on the life record; and a computer is caused to implement: a determination function, which determines one or more candidate causes of the occurrence of the symptoms based on the life record when the result of the determination indicates that the symptoms are occurring.

[0012] An information processing device involved in one embodiment of the present invention includes: an acquisition unit that acquires a life record containing text information recording the life of a subject; and a determination unit that determines whether the subject is experiencing psychological symptoms and / or behavioral symptoms related to dementia based on the life record; and includes a determination unit that determines one or more candidate causes of the occurrence of the symptoms based on the life record when the result of the determination indicates that the symptoms are occurring.

[0013] According to some aspects of the present disclosure, it is possible to determine the occurrence of behavioral symptoms and psychological symptoms for each subject and to identify candidate causes of the occurrence. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a diagram showing an example of the system configuration of the care support system according to the present embodiment.

[0015] Figure 2 This is a diagram showing an example of an overview of the care support system according to the present embodiment.

[0016] Figure 3 This is a diagram showing an example of the functional configuration of the server device according to the present embodiment.

[0017] Figure 4 It is a diagram showing an example of a screen of the care support system according to the present embodiment.

[0018] Figure 5 It is a diagram showing an example of a screen of the care support system according to the present embodiment.

[0019] Figure 6 It is a diagram showing an example of a screen of the care support system according to the present embodiment.

[0020] Figure 7 It is a diagram showing an example of a screen of the care support system according to the present embodiment.

[0021] Figure 8 It is a diagram showing an operation example of the care support system according to the present embodiment.

[0022] Fig. 9 This is a diagram for explaining an example of the hardware configuration of the care support system according to the present embodiment. DETAILED DESCRIPTION

[0023] One embodiment of the present invention (hereinafter referred to as "this embodiment") will be described with reference to the drawings. In the drawings, components denoted by the same reference numerals have the same or similar configurations.

[0024] <1. System Configuration>

[0025] use Figure 1 An example of the system configuration of the nursing support system 1 involved in the present embodiment is described. The nursing support system 1 involved in the present embodiment is a system for supporting a caregiver as a caregiver when providing nursing services to a care recipient (a case of a subject). A care recipient is a person who uses the nursing support system 1 and receives life-related nursing care (hereinafter also referred to as "nursing") from a caregiver.

[0026] In the care support system 1, a life record including text information of the life of the care receiver recorded by a recorder or a computer and data obtained by sensing the body of the care receiver and / or the surrounding environment of the care receiver (hereinafter also referred to as "sensor data") are used for the care of the care receiver. The recorder may be, for example, a caregiver or a family member of the care receiver.

[0027] The care support system supports caregivers in coping with psychological symptoms and / or behavioral symptoms related to dementia of the care receiver, so-called BPSD (Behavioral and Psychological Symptom of Dementia). Hereinafter, psychological symptoms and / or behavioral symptoms related to dementia of the care receiver are also referred to as "BPSD".

[0028] like Figure 1 As shown, the nursing support system 1 includes: a server device 100 and a staff terminal 200 used by a nursing staff. The server device 100 and the staff terminal 200 are connected via a communication network N. Users of the nursing support system 1 may be, for example, nursing staff, providers of nursing services other than nursing staff, and / or persons related to the person being cared for (e.g., family members of the person being cared for, etc.).

[0029] The communication network N is composed of a wireless network or a wired network. Examples of the communication network N include a mobile phone network, a PHS (Personal Handy-phone System) network, a wireless LAN (Local Area Network), 3G (3rd Generation), LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation), WiMax (registered trademark), infrared communication, Bluetooth (registered trademark), a wired LAN, a telephone line, a power line communication network, and a network based on IEEE1394 or the like.

[0030] [Server device]

[0031] The server device 100 is an information processing device capable of communicating with the staff terminal 200. The server device 100 provides a function for supporting the nursing staff when providing nursing services to the care receiver. In the present embodiment, an example is described in which the server device 100 generates a website for providing nursing services (hereinafter also referred to as a "nursing support website") and transmits the generated web page of the nursing support website to the staff terminal 200. The server device 100 enables the nursing staff to specify the URL of the nursing support website and log in through the staff terminal 200, thereby enabling access to the web page of the permitted nursing support website. The login is performed through the account (user ID and password) pre-registered by each user in the nursing support system 1.

[0032] [Staff terminal]

[0033] The staff terminal 200 is composed of a general or dedicated information processing device such as a smart phone, a tablet terminal, a PDA, a notebook computer, etc. The staff terminal 200 is one form of a user device. In this embodiment, an example of using a web browser provided as a standard in the staff terminal 200 is described. The staff terminal 200 is configured to receive provision of a learning tool from the server device 100 by browsing a web page transmitted from the server device 100 through the web browser.

[0034] <2. System Overview>

[0035] use Figure 2 , the overview of the nursing support system 1 involved in this embodiment is described. Figure 2As shown, in the nursing support system 1, it is possible to enable the staff terminal 200 to output a control panel (hereinafter also referred to as a "nursing support control panel") at the nursing support site, which summarizes the information associated with (1) to (4), such as (1) evaluation, (2) life records caused by DAR (Data Action Response), accidents (falls, wrong entry, etc.), (3) sensors / physical condition records / medicines, and (4) nursing improvement tips, for each care recipient.

[0036] (1) Assessment (basic information of the care recipient)

[0037] The care support control panel, for example, outputs the evaluation records of the care recipient (the latest record and the records within a specified period before the latest record) as the basic information of the care recipient. The evaluation includes, for example, the care need level of the care recipient, the stage of dementia, the presence or absence of orientation disorder, the degree of independence in each life scene (for example, the degree of independence in daily life, etc.).

[0038] (2)DAR accident (for care recipients)

[0039] The care support control panel may output, for example, the change in the number of BPSD cases per unit time as the situation of the care receiver based on the life record. In addition, the care support control panel may output, for example, the text information itself contained in the life record as detailed information related to the output. In addition, the life record may be a record obtained by tracking the life of the care receiver using the Focused Care Record (DAR) method as a recording method.

[0040] The care support control panel may output the number of each facial feature based on the result of recording the care receiver's expression using the facial features, for example.

[0041] The nursing support control panel, for example, outputs the accident situation (for example, the change in the number of accidents per unit time, etc.) as the situation of the care receiver based on the accident record containing text information recording the accident of the care receiver. In addition, the nursing support control panel may also output the text information itself contained in the accident record as detailed information related to the output, for example.

[0042] The nursing support dashboard, for example, includes the number of accidents, the number of BPSD, and the number of facial features, in addition to the number of units of time (in Figure 2 In addition to outputting the information by time period (marked as “time period”), it is also possible to output the information by the type of care provided when these events occurred.

[0043] (3) Sensors / physical condition records / medicines (cause of the care receiver's condition)

[0044] The care support control panel, for example, outputs sensor data of the care receiver, records of physical conditions, prescription contents of medicines, current care contents, etc. as the cause of the above situation (2).

[0045] (4) Tips for improving nursing care (responses to the causes)

[0046] The care support control panel, for example, outputs a prompt for improving care as a response to the cause (3) above. The care support control panel, for example, can output a prompt such as "The sleep time seems to be short. Is the sleeping posture correct?" when the sensor data of the sleep sensor indicates that the sleep time of the care receiver is shorter than the standard value.

[0047] When caring for a care recipient, the caregiver has several points to consider: what kind of person the care recipient is, whether the care recipient's condition is good or bad, what are the causes of the good / bad condition, how to deal with those causes, etc. According to the above configuration, in the care support system 1, information that can serve as answers or prompts can be summarized in the care support control panel and output according to the caregiver's thinking process.

[0048] According to the above configuration, the nursing support system 1 can output the change in the number of BPSD cases per unit time based on the text information of the subject's life record and accident record. Therefore, it is possible to output the occurrence status of BPSD that matches the subject by recording the detailed characteristics, interests, etc. of each subject that cannot be expressed in the quantitative record or the selective record.

[0049] <3. Functional structure>

[0050] Reference Figure 3 , the functional structure of the server device 100 involved in this embodiment is described. Figure 3 As shown, the server device 100 includes a control unit 110 , a communication unit 120 , and a storage unit 130 .

[0051] [Control Department]

[0052] The control unit 110 includes an acquisition unit 111, a determination unit 112, a determination unit 113, and an output unit 115. In addition, the control unit 110 may include a classification unit 114, for example.

[0053] [Acquisition Department]

[0054] Acquisition unit 111 acquires the life record of the care receiver from staff terminal 200 or storage unit 130 .

[0055] The acquisition unit 111 can, for example, acquire sensor data at the time point at which the life record is recorded (hereinafter also referred to as the "recording time point") from a sensor device (not shown) or a storage unit 130. The sensor device can be, for example, a body motion sensor, a sleep sensor, a pulse sensor, a breathing sensor, a temperature sensor, an excretion detection sensor, a blood pressure sensor (sphygmomanometer), a weight scale, a hygrometer, a barometer and / or an image sensor, etc. In addition, the recording time point can, for example, also represent a time within a certain range (i.e., a period). For example, if the date and time at which the life record is recorded is "10:15 am on June 30, 2022", the recording time point of the record can be 10 am on June 30, 2022, or it can be the morning of June 30, 2022.

[0056] Sensor data, for example, may include data obtained by sensing the body of the care receiver (hereinafter, also referred to as "body data"). Body data, for example, may be the measurement results of the care receiver's sleeping condition, excretion condition, pulse condition, breathing condition, blood pressure condition, weight condition and / or body temperature condition. In addition, sensor data may include data obtained by sensing the surrounding environment of the care receiver (hereinafter, also referred to as "environmental data"). Environmental data, for example, may be the measurement results of the temperature condition, humidity condition and / or air pressure condition of the surrounding environment of the care receiver.

[0057] The acquisition unit 111 may also acquire, for example, a healthy life record and healthy sensor data from the storage unit 130. The healthy life record is a life record including text information, which records the life of the care receiver when the care receiver is healthy. In addition, the healthy sensor data is data obtained by sensing the body of the care receiver and / or the surrounding environment of the care receiver when the care receiver is healthy.

[0058] The acquisition unit 111 may acquire the evaluation information from, for example, the storage unit 130. The evaluation information is information indicating the result of the evaluation of the care receiver.

[0059] [Judgment Department]

[0060] The determination unit 112 determines the occurrence of psychological symptoms and / or behavioral symptoms related to dementia (in other words, BPSD) of the care receiver based on the life record. Specifically, the determination unit 112 can determine whether the care receiver is experiencing BPSD (in other words, whether it is occurring), and can also determine what kind of symptoms the BPSD that is occurring is. The determination unit 112 can also store symptom information indicating the determination result in the storage unit 130.

[0061] The life record, for example, may also be a text recorded in free text by a recorder (e.g., a caregiver, etc.) using a focused care record as a recording method. Specifically, the life record may contain text information that records the care receiver's experience focusing on things that the care receiver is worried about or concerned about, the care receiver's behavior, or events that occurred to the care receiver. In addition, the life record, for example, may also be a free text of a recorder who conducts a follow-up survey of the care receiver using the focused care record (DAR) method. According to such a structure, a survey focusing on events that occurred to each care receiver is conducted on each care receiver, and the occurrence of BPSD can be determined based on the survey record obtained by the caregiver's free record. Therefore, the occurrence of BPSD that matches each care receiver can be determined, and the determination can be made in the form of experience and insights through a survey record based on effective use of the care receiver's experience and insights.

[0062] Symptom information is information related to BPSD of each care receiver, and may include, for example, whether BPSD has occurred, (if BPSD has occurred), the BPSD type, occurrence date and time, and / or occurrence location of each BPSD that is occurring.

[0063] The determination unit 112 may determine the occurrence of BPSD using, for example, natural language processing technology, machine learning, and deep learning technology. The determination unit 112 may make a determination using, for example, a determination model for determining which symptom of BPSD is occurring.

[0064] The determination model may be, for example, a model learned using machine learning and deep learning techniques based on the training data. In addition, the training data may be, for example, text information to which a label indicating the presence or absence of BPSD, the type, and the presence or absence of active POS behavior is assigned. In addition, the label may be assigned based on the designation of the text information displayed on the staff terminal 200 by the nursing staff (in other words, the operation input to the screen displaying the text information).

[0065] For example, as a preprocessing, the judgment model performs morphological analysis on the text information contained in the life record, and divides the sentences contained in the text information into word units. The judgment model, for example, may include BERT (Bidirectional Encoder Representations from Transformers). The judgment model uses BERT to convert the above-mentioned segmented word groups into their vector sequences, and inputs the converted vector sequence, and outputs a vector sequence equivalent to the response sentence. Then, the judgment model generates a feature vector based on the output vector sequence. Next, the judgment model includes a neural network (classifier), and after inputting the feature vector into the neural network, it outputs a classification of which type of symptom of BPSD is occurring or not occurring, thereby determining whether it occurs, and then classifying the type of BPSD. In addition, the judgment model, for example, can be used to determine whether there is active behavior and / or positive behavior (hereinafter also referred to as "active POS behavior"), just like determining whether BPSD occurs.

[0066] According to the above configuration, the determination unit 112 can determine the occurrence of BPSD based on text information recorded on each subject, such as personality and interests, which cannot be expressed in quantitative records or selective records. Therefore, the occurrence of BPSD corresponding to each subject can be determined.

[0067] [Judgment Department]

[0068] The determination unit 112 determines the active POS behavior of the care receiver based on the life record. Specifically, the determination unit 112 can determine whether the care receiver is performing active POS behavior (in other words, whether there is behavior) or what kind of active POS behavior is being performed. The determination unit 112 can store behavior information indicating the determination result in the storage unit 130.

[0069] [Determination Department]

[0070] When the determination result of the determination unit 112 indicates that BPSD has occurred, the determination unit 113 determines one or more candidate causes of BPSD based on the life record. The determination unit 113 may store candidate cause information in the storage unit 130, the candidate cause information indicating each of the one or more determined candidate causes.

[0071] The determination unit 113, for example, may refer to dictionary information in which character strings representing each of a plurality of causes of the occurrence of BPSD (hereinafter also referred to as "cause strings") are registered, and when it is possible to extract at least a portion of a character string that is consistent with the cause string from a character string containing text information that is determined by the determination unit 112 to be causing BPSD, the cause corresponding to the cause string is determined as a candidate cause.

[0072] The determination unit 113 may also use, for example, natural language processing technology, machine learning, and deep learning technology to determine one or more candidate causes of BPSD. The determination unit 113 may also use, for example, a determination model for determining one or more candidate causes of BPSD to perform the determination. In addition, the determination model and the determination model of the determination unit 112 may be the same model.

[0073] The determination model may be, for example, a model obtained by learning using machine learning and deep learning techniques based on training data. In addition, the training data may also be, for example, text information to which labels indicating the presence, type, and cause of BPSD are assigned. In addition, the cause label may also be assigned based on the nurse's designation of the text information displayed on the staff terminal 200 (in other words, the operation input to the screen displaying the text information).

[0074] The determination unit 113 may also determine one or more candidate causes of BPSD based on the sensor data and / or nursing records at the recording time of the life record, for example. Specifically, the determination unit 113 may determine insufficient sleep time as a candidate cause when the sensor data of the sleep sensor at the time of BPSD indicates that the care receiver has insufficient sleep time. According to such a configuration, it is possible to quantitatively represent changes in the care receiver's body or environment that cannot be represented in the text information record, and it is possible to determine the candidate cause based on the sensor data or nursing records that include a large amount of information without increasing the burden on the caregiver.

[0075] For example, the determination unit 113 may determine one or more causes of BPSD from one or more candidate causes based on the contribution degree (hereinafter also referred to as “contribution degree”) of each of the one or more candidate causes calculated by the contribution degree calculation unit 113 b described later.

[0076] The determination unit 113 may, for example, determine the type of the care receiver being cared for (hereinafter, also referred to as "care receiver type") based on the evaluation information and / or the symptom information. The care receiver type may, for example, be a type indicating the type of care the care receiver is experiencing, a type indicating the care receiver's behavior, a type indicating a physical condition including a dementia condition of the care receiver, and / or a type indicating the care receiver's interests (including a combination of two or more of these types).

[0077] For example, the identification unit 113 may identify the content of the care performed on the date and time when the BPSD occurred by referring to the storage unit 130 storing the care history information. The care history information is information indicating the care history for the care receiver within a predetermined period.

[0078] The determination unit 113 may, for example, also refer to the storage unit 130 and determine, based on the improvement plan information, a nursing improvement plan (hereinafter also referred to as a "corresponding improvement plan") corresponding to at least one of the one or more candidate causes from a plurality of improvement plans, wherein the storage unit 130 stores improvement plan information representing each of a plurality of improvement plans for the care of the subject. In addition, the determination unit 113 may, for example, further determine the corresponding improvement plan based on the similarity calculated by the similarity calculation unit 113c. The determination unit 113 may, for example, determine the improvement plan with the highest similarity among the plurality of improvement plans as the corresponding improvement plan.

[0079] The determination unit 113 may include, for example, a comparison unit 113a. For example, when the determination result of the determination unit 112 indicates that BPSD has occurred, the comparison unit 113a compares the life record in which the BPSD has occurred (hereinafter, also referred to as “life record during BPSD”) with the life record in a healthy state (hereinafter, also referred to as “first comparison”). In addition, when the determination result of the determination unit 112 indicates that BPSD has occurred, the comparison unit 113a compares the sensor data at the recording time point of the life record during BPSD (hereinafter, also referred to as “sensor data during BPSD”) with the sensor data during a healthy state (hereinafter, also referred to as “second comparison”).

[0080] The BPSD life record and the healthy life record may also include a case where the recording is performed by tracing back the first period from the respective recording time points as the starting time points. For example, when the recording time point of the life record is "June 30, 2022", and the first period is "3 months", the life record may include the life record recorded from June 30, 2022, tracing back 3 months until March 30, 2022. In this case, the comparison unit 113a, for example, may also extract the difference between the multiple BPSD life records and the healthy life records along the time series based on the result of the first comparison in which the time series in the first period are merged (hereinafter also referred to as "first difference").

[0081] The comparison unit 113a, for example, can weight each of the extracted multiple first differences according to the length of time from the start time point to the extraction of each of the multiple first differences. For example, the comparison unit 113a can make the weight proportional to the length of the time, and the shorter the length, that is, the closer the extraction time point is to the start time point, the greater the weight can be.

[0082] The sensor data during BPSD and the sensor data during health may also include data obtained by tracing back to a second period from the start time point corresponding to each of the recording time points. For example, when the recording time point corresponding to the sensor data is set to "June 30, 2022" and the second period is set to "3 months", the sensor data during BPSD may also include data measured from June 30, 2022, tracing back 3 months to March 30, 2022. In this case, the comparison unit 113a may also extract the difference between the multiple sensor data and the sensor data during health along the time series (hereinafter also referred to as "second difference") based on the result of the second comparison by merging the time series within the second period. In addition, the first period and the second period may be the same period or different periods.

[0083] The comparison unit 113a, for example, can weight each of the plurality of second differences extracted according to the time length from the start time point to the extraction of each of the plurality of second differences. The comparison unit 113a, for example, can make the weight proportional to the time length, and the shorter the length, the greater the weight, as with the first difference.

[0084] The determination unit 113 may include, for example, a contribution calculation unit 113b. The contribution calculation unit 113b may calculate, for example, the contribution of each of the one or more candidate factors to the BPSD based on the results of the first comparison and / or the second comparison.

[0085] The contribution calculation unit 113b may, for example, use a variable importance analysis method to calculate the contribution of each of the one or more candidate causes. The contribution calculation unit 113b may, for example, evaluate the importance of the feature quantity (so-called FeatureImportance) of the one or more candidate causes as the contribution based on the date and time of BPSD occurrence and sensor data and / or nursing records. In addition, the contribution calculation unit 113b may, for example, use the ICE (Individual Conditional Expectation) method in evaluating the importance of the feature quantity.

[0086] The contribution calculation unit 113b may further calculate the contribution based on the weighting of each of the plurality of first differences, for example. According to such a configuration, the degree to which the difference from the healthy state contributes to the occurrence of BPSD can be changed according to the temporal distance from the time point of occurrence of BPSD. Therefore, for example, by increasing the weight of the difference closer to the time point of occurrence, the contribution value can be increased, and a candidate cause with a stronger correlation with BPSD can be determined.

[0087] The contribution calculation unit 113b may further calculate the contribution based on the weighting of each of the plurality of second differences, for example. According to such a configuration, the degree to which the difference from the healthy state contributes to the occurrence of BPSD can be changed according to the temporal distance from the time point of occurrence of BPSD. Therefore, for example, by increasing the weight of the difference closer to the time point of occurrence, the contribution value can be increased, and a candidate cause with a stronger correlation with BPSD can be determined.

[0088] The determination unit 113 may include, for example, a similarity calculation unit 113c. The similarity calculation unit 113c calculates, for each of a plurality of candidate improvement plans for the care receiver, a similarity to the type of the care receiver determined by the determination unit 113. The similarity calculation unit 113c may, for example, calculate a degree of consistency showing to what extent the improvement plan information representing each of the plurality of improvement plans is consistent with the type information representing the type of the care receiver, and calculates the similarity based on the calculated degree of consistency.

[0089] [Classification Department]

[0090] When the determination result of the determination unit 112 indicates that BPSD has occurred, the classification unit 114 classifies the occurred BPSD into a plurality of types (hereinafter also referred to as “BPSD types”).

[0091] The classification unit 114 includes an evaluation unit 114a. The evaluation unit 114a evaluates the status of the symptoms in each of the plurality of BPSD types (for example, the occurrence amount of the symptoms of each type, etc.).

[0092] [Output section]

[0093] The output unit 115 enables the staff terminal 200 to output various information through the screen, sound, etc. of the nursing support system 1. The output unit 115 can, for example, generate a video for displaying the following based on life records, sensor data, symptom information, behavior information, evaluation information, improvement plan information, and / or nursing history information. Figures 4 to 7 The output unit 115 may transmit the generated display information to the staff terminal 200. The staff terminal 200 displays each screen based on the received display information.

[0094] The output unit 115 causes the staff terminal 200 to output symptom information in response to a user's request. Symptom information is information indicating the result of the determination of the occurrence of BPSD by the determination unit 112. With such a configuration, the output unit 115 can prompt the nursing staff with the occurrence of BPSD determined based on the life record, and can support the nursing staff in caring for the care receiver.

[0095] The output unit 115, for example, can also cause the staff terminal 200 to output candidate cause information according to the request of the nursing staff, and the candidate cause information indicates each of the one or more candidate causes determined by the determination unit 113. According to such a configuration, the candidate causes of BPSD occurrence can be prompted to the nursing staff. Therefore, the nursing staff can determine the cause of BPSD occurrence with reference to the prompted candidate causes, and the nursing staff can support the care of the care receiver.

[0096] For example, the output unit 115 may cause the staff terminal 200 to output cause information indicating each of the one or more causes specified by the specifying unit 113 in response to a request from the nursing staff. With such a configuration, the cause of occurrence of BPSD can be presented to the nursing staff.

[0097] The output unit 115 can also cause the staff terminal 200 to output the occurrence of the symptoms evaluated by the evaluation unit 114a in each of the plurality of BPSD types according to the request of the nursing staff, for example. According to such a configuration, it is possible to confirm which type of BPSD type is stronger. Therefore, the nursing staff can give a higher priority to the type with stronger symptoms than other types to deal with it.

[0098] The output unit 115 can also cause the staff terminal 200 to output improvement plan information indicating the improvement plan determined by the determination unit 113 according to the request of the nursing staff. According to such a configuration, it is possible to provide the nursing staff with a suggestion on how to improve the care for the output candidate cause or causes. Thus, the nursing staff does not need to consider the improvement of care from the beginning, and even if the nursing staff has little skills or experience, it is possible to make improvements to cope with BPSD so as to provide more appropriate care for each care recipient.

[0099] For example, when the determination result of the determination unit 112 indicates the occurrence of BPSD, the output unit 115 may correspond the symptom information, the content of the care determined by the determination unit 113, and the improvement plan information indicating the improvement plan determined by the determination unit 113 according to the request of the nursing staff, and output them to the staff terminal 200. According to such a configuration, the nursing staff can uniformly confirm the occurrence of the corresponding BPSD, the content of the care when it occurs, and the improvement plan. Therefore, a nursing support system that is easy to use for the nursing staff can be provided.

[0100] [Ministry of Communications]

[0101] The communication unit 120 transmits and receives various information such as a web page of a care support website to and from the staff terminal 200 via the communication network N.

[0102] [Storage Department]

[0103] The storage unit 130 stores various information related to nursing, including life records, sensor data, symptom information, behavior information, evaluation information, improvement plan information, and nursing history information. The storage unit 130, for example, can also store these information in association with each other. The storage unit 130 can use a database management system (DBMS) to store various information, or it can use a file system to store various information. In the case of using a DBMS, a table can also be set for each information, and the tables can be associated with each other to manage various information.

[0104] <4. Screen example>

[0105] Reference Figures 4 to 7 , an example of a screen of the nursing support control panel of the nursing support system 1 is described. Figures 4 to 7 Each screen described in the description may also include Figures 4 to 7 Elements other than the components of the screen described above may be omitted as appropriate. Figures 4 to 7 A part of the components of the screen being explained.

[0106] exist Figures 4 to 7In the figure, examples of the BPSD status and candidate causes screen A2, BPSD occurrence cause details A3, and life record (DAR) screen A4 displayed on the nursing support control panel A1 are described. The nursing support control panel A1 can specify a tab corresponding to each screen located in the switching tab area a11, and switch to display the screen corresponding to the specified tab.

[0107] Figures 4-5 1 is a schematic diagram showing an example of a BPSD status and candidate cause screen A2 for displaying the occurrence status of BPSD and its candidate causes. In this example, the BPSD status and candidate cause screen A2 is displayed by scrolling the screen. Figure 4 After Figure 5 show.

[0108] like Figure 4 As shown, the BPSD status and candidate cause screen A2 includes a BPSD number display area a22, an active record display area a23, a facial feature display area a24, and an accident number display area a25. The BPSD status and candidate cause screen A2 specifies the tab displayed as "BPSD status and candidate cause" in the switching tab area a11 to be displayed.

[0109] The BPSD number display area a22 displays the number of BPSD occurrences per unit time in a vertical bar graph. The number of BPSD occurrences is, for example, the number of BPSD symptoms that have occurred when the determination unit 112 determines that BPSD is occurring. In addition, in each chart displayed on the BPSD status and candidate cause screen A2, the unit time can be switched between the daily unit, the weekly unit, the quarterly unit, and the annual unit. After the unit time is switched, the display of each chart is also changed according to the switched unit.

[0110] The active record display area a23 displays the number of active POS actions per unit time in a bar graph. The number of active POS actions is, for example, a statistical number of each active POS action when the determination unit 112 determines that an active POS action exists.

[0111] The facial feature display area a24 displays the number of facial features of each type in which the care receiver's expression is recorded per unit time in the form of a vertical bar graph.

[0112] The accident number display area a25 displays the number of accidents per unit time in a vertical bar graph. The accident number display area a25 may not be displayed, for example, when the number of accidents is 0. The number of accidents is a number counted based on nursing records or life records. Nursing records, for example, may be records that quantitatively and / or selectively record the conditions of the care recipient. Specifically, nursing records refer to records that quantitatively record the sleep, excretion, eating, water intake, weight, blood pressure, breathing, arterial oxygen saturation (hereinafter also referred to as "SpO2"), etc. of the care recipient, and / or records that are recorded in a selective manner.

[0113] like Figure 5 As shown, when the determination unit 112 determines that BPSD is occurring, the BPSD status and candidate cause screen A2 may include a BPSD classification display area a26, a BPSD case count display area a27 by nursing classification, a BPSD display area a28 by time period classification, and a BPSD candidate cause display area a29. In other words, when the determination unit 112 determines that BPSD is occurring, the BPSD status and candidate cause screen A2 may not display these areas.

[0114] The upper part of the BPSD classification display area a26 classifies the occurred BPSD into multiple types (9 types in this example), and then calculates the occurrence amount of each type (in this example, the above-mentioned number of BPSD occurrences is summed up for each type), that is, evaluates the occurrence of the symptoms, and displays it in a radar chart. In addition, the lower part of the BPSD classification display area a26 displays a link for displaying the nursing reminder screen A2-1 for each of the multiple types of BPSD (hereinafter also referred to as a "nursing reminder link"). In addition, the type displayed in the upper part and the type displayed in the lower part may be the same as or different from each other. In the latter case, the type displayed in the upper part, for example, may be a higher-level conceptualized type of the type displayed in the lower part, in other words, it may be a type that further roughly classifies the type displayed in the lower part.

[0115] When a care prompt link is specified, a care prompt screen A2-1 is displayed on the care support control panel A1. In this example, a care prompt link corresponding to the type "No. 3 violent refusal of care" among the multiple types of BPSD is specified. The care prompt screen A2-1 displays the care improvement plan corresponding to the specified BPSD type as a prompt to the care staff during care.

[0116] The BPSD number display area a27 by nursing care category displays the number of BPSD occurrences in a horizontal bar graph according to the type of nursing care performed when BPSD occurred.

[0117] The BPSD display area a28 classified by time period displays the number of BPSD occurrences in a horizontal bar graph for each time period when BPSD occurred.

[0118] The BPSD candidate cause display area a29 displays the contribution of each of the more than one candidate cause of BPSD in a horizontal bar graph. In the horizontal bar graph, the more than one candidate cause is sorted and displayed in descending order according to the contribution (in Figure 5 In the example, it is recorded as “the horizontal bars with strong correlation are arranged in order from the top”).

[0119] like Figure 6 As shown, the BPSD occurrence cause detailed screen A3 displays the sleep time and activity time per unit time and the like related to the candidate causes of BPSD occurrence for the care receiver in a bar graph or time chart based on the sensor data. In addition, the BPSD occurrence cause detailed screen A3 displays the defecation volume, defecation characteristics, urine volume, food intake, water content, weight, body temperature, blood pressure (high or low), pulse, and / or breathing related to the candidate causes of BPSD occurrence for the care receiver in a bar graph or other chart based on the nursing record. The BPSD occurrence cause detailed screen A3 specifies the tab displayed as "BPSD occurrence details (sensor·record)" in the switching tab area a11 to be displayed.

[0120] like Figure 7 As shown, the life record (DAR) screen A4 displays a table summarizing multiple life records. In this table, for each record, for the event of interest, the data (Data) related to the event, the care or treatment (Action) performed on the event, and the response (Response) of the care recipient to the performed care or treatment are displayed through the recorded free text. In addition, in this table, multiple life records can be classified and displayed using their corresponding facial features. In addition, in this table, multiple life records can be classified and displayed based on whether or not BPSD occurs in each of them. In addition, in this table, multiple life records can be classified and displayed based on whether or not their respective active POS behaviors occur.

[0121] <5. Action example>

[0122] Reference Figure 8 , an example of the operation of the server device 100 is described. In addition, the processing sequence shown below is only an example and can be changed appropriately.

[0123] like Figure 8As shown, the acquisition unit 111 of the server device 100 acquires a life record in which a recorder records the life of a subject (S10). The acquisition unit 111 acquires sensor data at the recording time point of the life record (S11). The determination unit 112 of the server device 100 determines whether psychological symptoms and / or behavioral symptoms related to dementia are occurring for the subject based on the life record (S12).

[0124] When the result of the above determination indicates that the above symptom is occurring ("Yes" in S13), the determination unit 113 of the server device 100 determines one or more candidate causes of the occurrence of the above symptom based on the sensor data and the life record (S14). The contribution calculation unit 113b of the server device 100 calculates the respective contribution of the one or more candidate causes to the above symptom (S15). The determination unit 113 determines one or more causes of the occurrence of the above symptom from the one or more candidate causes based on the respective contribution of the one or more candidate causes (S16). The output unit 115 of the server device 100 causes the user device to output symptom information indicating that the above symptom is occurring and cause information indicating each of the one or more causes according to the user's request (S17).

[0125] When the result of the determination indicates that the symptom is not occurring (No in S13), the output unit 115 of the server device 100 causes the user device to output symptom information indicating that the symptom is not occurring in response to a user's request (S18).

[0126] <5. Hardware Configuration>

[0127] Reference Fig. 9 , an example of the hardware configuration when the server device 100 is implemented by a computer 800 is described. In addition, the functions of each device may be implemented by dividing into a plurality of devices.

[0128] like Fig. 9 As shown, the computer 800 includes a processor 801 , a memory 803 , a storage device 805 , an input I / F unit 807 , a data I / F unit 809 , a communication I / F unit 811 , and a display device 813 .

[0129] The processor 801 controls various processes in the computer 800 by executing the program stored in the memory 803. For example, each functional unit included in the control unit 110 of the server device 100 can be realized by the processor 801 executing the program temporarily stored in the memory 803.

[0130] The memory 803 is a storage medium such as a RAM (Random Access Memory) and temporarily stores program codes executed by the processor 801 and data required when the program is executed.

[0131] The storage device 805 is a non-volatile storage medium such as a hard disk drive (HDD) or a flash memory. The storage device 805 stores an operating system and various programs for implementing the above-mentioned components. In addition, the storage device 805 may also store a table for registering various information such as life records, sensor data, symptom information, evaluation information, improvement plan information, and nursing history information, and a DB for managing the table. Such programs and data are loaded into the memory 803 as needed and referenced by the processor 801.

[0132] The input I / F unit 807 is a device for receiving input from the user. Specific examples of the input I / F unit 807 include a keyboard, a mouse, a touch panel, various sensors, a wearable device, etc. The input I / F unit 807 may be connected to the computer 800 via an interface such as a USB (Universal Serial Bus).

[0133] The data I / F unit 809 is a device for inputting data from outside the computer 800. As a specific example of the data I / F unit 809, there is a drive device for reading data stored in various storage media. The data I / F unit 809 may also be provided outside the computer 800. In this case, the data I / F unit 809 is connected to the computer 800 via an interface such as a USB.

[0134] The communication I / F unit 811 is a device for performing data communication with an external device of the computer 800 via the Internet N in a wired or wireless manner. The communication I / F unit 811 may also be provided outside the computer 800. In this case, the communication I / F unit 811 is connected to the computer 800 via an interface such as a USB.

[0135] The display device 813 is a device for displaying various information. Specific examples of the display device 813 include a liquid crystal display, an organic EL (Electro-Luminescence) display, and a display of a wearable device. The display device 813 may also be provided outside the computer 800. In this case, the display device 813 is connected to the computer 800, for example, via a display cable. In addition, when a touch panel is used as the input I / F unit 807, the display device 813 may be integrated with the input I / F unit 807.

[0136] In addition, this embodiment is an illustration for illustrating the present invention, and its purport is not to limit the present invention only to this embodiment. In addition, the present invention can be variously modified as long as it does not depart from its purport. And then, if it is a person skilled in the art, it is possible to adopt the embodiment in which each element described below is replaced by an equal element, and this embodiment is also included in the scope of the present invention.

[0137] [Modifications]

[0138] Furthermore, although the present invention has been described based on the above-mentioned embodiment, the present invention also includes the following cases.

[0139] [Modification 1]

[0140] At least a part of each configuration included in the server device 100 of the above-mentioned embodiment may be included in the staff terminal 200. The staff terminal 200, for example, may also implement these configurations by installing an application (native application) dedicated to the nursing support system 1 (hereinafter, also referred to as a "nursing support application") and executing the nursing support application. In other words, in the nursing support system 1, both the nursing support site transmitted by the server device 100 and the nursing support application may be utilized. In the nursing support system, when the nursing support application is utilized, the nursing staff can utilize at least a part of the functions even if the staff terminal 200 is offline.

[0141] Description of Reference Numerals

[0142] 1…nursing support system, 100…server device, 110…control unit, 111…acquisition unit, 112…judgment unit, 113…determination unit, 114…classification unit, 115…output unit, 200…staff terminal, 800…computer, 801…processor, 803…memory, 805…storage device, 807…input I / F unit, 809…data I / F unit, 811…communication I / F unit, 813…display device.

Claims

1. An information processing method, characterized in that: The user obtains a life record including text information recording the life of the subject through a computer; Based on the life record, determining whether the subject is experiencing psychological symptoms and / or behavioral symptoms associated with dementia; When the result of the determination indicates that the symptom is occurring, one or more candidate causes of the occurrence of the symptom are determined based on the life record.

2. The information processing method according to claim 1, wherein: The method obtains sensor data obtained by sensing the subject's body and / or the subject's surrounding environment, i.e., sensor data recording the recording time point of the life record, and / or a nursing record quantitatively and / or selectively recording the subject's condition at the recording time point, When the result of the determination indicates that the symptom is occurring, one or more candidate causes of the occurrence of the symptom are determined based on the sensor data and / or the care record.

3. The information processing method according to claim 2, wherein: the computer, When the subject is healthy, a healthy life record and healthy sensor data are obtained, wherein the healthy life record includes text information recording the life of the subject, and the healthy sensor data is obtained by sensing the body of the subject and / or the surrounding environment of the subject, When the result of the determination indicates that the symptom is occurring, a first comparison between the life record and the life record when healthy, and / or a second comparison between the sensor data and the sensor data when healthy are performed, Based on the results of the first comparison and / or the second comparison, calculating the contribution of each of the one or more candidate causes to the symptom, Based on the contribution degree of each of the one or more candidate causes, one or more causes of the occurrence of the symptom are determined from the one or more candidate causes.

4. The information processing method according to claim 3, wherein: the computer, The BPSD life record and the healthy life record determined as the life record in which the symptom is occurring include contents recorded in a first period traced back from the start time point with the respective record time points as the start time points, extracting a plurality of first differences between the BPSD life records and the healthy life records along the time series based on the result of the first comparison performed by combining the time series of the first period, weighting each of the extracted first differences according to a time length from the start time point to a time point at which each of the first differences is extracted, The contribution is further calculated based on the weighting.

5. The information processing method according to claim 3, wherein: the computer, The BPSD sensor data and the healthy sensor data of the sensor data of the recording time point of the life record determined to be the time point at which the symptom is occurring include data sensed by tracing back the second period from the starting time point with the corresponding recording time point as the starting time point, extracting a plurality of second differences between the BPSD sensor data and the healthy sensor data along the time series based on the result of the second comparison performed by combining the time series within the second period, weighting each of the extracted second differences according to a time length from the start time point to a time point at which each of the second differences is extracted, The contribution is further calculated based on the weighting.

6. The information processing method according to claim 1 or 2, wherein: the computer, The text information is information recorded in a free text form by a recorder using focused care recording as a recording method.

7. The information processing method according to claim 1 or 2, wherein: the computer, When the determination result indicates that the symptom is occurring, the symptom is classified into a plurality of types, The occurrence of the symptoms is evaluated in each of the plurality of types.

8. The information processing method according to claim 1 or 2, wherein: the computer, An improvement plan corresponding to at least one of the one or more candidate causes is determined from a plurality of improvement plans for nursing care of the subject.

9. The information processing method according to claim 8, wherein: the computer, obtaining evaluation information indicating a result of an evaluation performed on the subject person, determining the type of the subject based on the symptom information indicating the evaluation information and / or indicating the determination result, For each of the improvement solutions, calculate the similarity to the type, Based on the approximation, an improvement solution corresponding to at least one of the one or more candidate factors is determined from the plurality of improvement solutions.

10. The information processing method according to claim 1 or 2, wherein: When the result of the determination indicates that the symptom is occurring, the symptom information indicating the result of the determination includes a date and time of occurrence of the symptom, the computer, The content of the care performed at the occurrence date and time is specified by referring to a storage unit storing care history information indicating a history of the care provided to the subject within a predetermined period.

11. A program, characterized in that Make the computer realize: An acquisition function for acquiring a life record including text information recording the life of the subject; a determination function for determining whether the subject is experiencing psychological symptoms and / or behavioral symptoms associated with dementia based on the life record; And make the computer realize: A determination function that determines one or more candidate causes of occurrence of the symptom based on the life record when the result of the determination indicates that the symptom is occurring.

12. An information processing device, characterized in that: The information processing device comprises: an acquisition unit that acquires a life record including text information recording the life of the subject; a determination unit that determines whether the subject is experiencing psychological symptoms and / or behavioral symptoms related to dementia based on the life record; The method further includes a determination unit that determines, when the result of the determination indicates that the symptom is occurring, one or more candidate causes of the occurrence of the symptom based on the life record.

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