Apparatus for determining whether an examination is necessary, method for determining whether an examination is necessary, and program for determining whether an examination is necessary

Abstract

The present invention provides a device for determining whether or not an assessment is necessary, which makes it possible to omit the assessment process when renewing long-term care certification. [Solution] The examination necessity determination device 30 of the present invention includes an acquisition unit that acquires information regarding the condition of the subject 50, and a determination unit that determines whether or not a care needs assessment is necessary for the subject 50 based on information regarding the condition of the subject 50 at a first time point and information regarding the condition of the subject 50 at a second time point later than the first time point.

Description

Technical Field

[0001] The present invention relates to a review necessity determination device, a review necessity determination method, and a review necessity determination program.

Background Art

[0002] With the increase in the elderly population, the number of certified care recipients is also increasing. In the certification of care needs, a certification survey by a certification examiner and a diagnosis by a primary care physician are conducted, and based on these results, the degree of care needs of the subject is determined by a care certification review committee.

[0003] In recent years, from the perspective of shortening the period of care needs certification and reducing the workload, the use of AI (Artificial Intelligence) technologies such as image analysis in care needs certification has been studied (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In order to maintain the care needs certification, regular updates are necessary. For the update of the care needs certification, the same procedures as the first care needs certification are performed.

[0006] However, when updating the care needs certification, in many cases, the degree of care needs of the subject is determined to be the same as the degree of care needs at the first care needs certification. Even though the degree of care needs has not changed, it is not preferable to perform the same procedures as the first time at the time of update from the perspective of shortening the period and reducing the workload. Therefore, at the time of updating the care needs certification, it is desirable to be able to omit the care needs certification review for subjects with little change in their condition since the first care needs certification.

[0007] The present invention has been made in view of the above-mentioned problems. Accordingly, the object of the present invention is to provide a device for determining whether or not an assessment is necessary, a method for determining whether or not an assessment is necessary, and a program for determining whether or not an assessment is necessary, which enable the omission of the assessment for long-term care needs when renewing long-term care needs assessment. [Means for solving the problem]

[0008] The above objectives of the present invention are achieved by the following means.

[0009] (1) A device for determining whether a care needs assessment is necessary for a subject, comprising: an acquisition unit for acquiring information on the subject's condition; and a determination unit for determining whether a care needs assessment is necessary for the subject based on the information on the subject's condition at a first time point and the information on the subject's condition at a second time point later than the first time point.

[0010] (2) The assessment necessity determination device described in (1) above, wherein the first time point is the time when the subject enters the facility, and the second time point is the time when the long-term care certification for the subject is renewed.

[0011] (3) The examination necessity determination device according to (1) or (2) above, further comprising a quantification processing unit that quantifies the physical and cognitive functions of the subject based on the information on the state acquired by the acquisition unit, wherein the determination unit determines whether or not an examination for long-term care needs assessment is necessary based on numerical values ​​indicating the physical and cognitive functions of the subject at a first time point and numerical values ​​indicating the physical and cognitive functions of the subject at a second time point.

[0012] (4) The assessment necessity determination device described in (3) above, wherein if the difference between the numerical value at the first time point and the numerical value at the second time point exceeds a predetermined amount, the determination unit determines that an assessment for long-term care needs is necessary.

[0013] (5) The assessment necessity determination device described in (4) above, wherein if the numerical values ​​indicating the physical and cognitive functions of the subject at a third time between the first time and the second time fall outside the numerical range determined by the numerical values ​​at the first time and the numerical values ​​at the second time, the determination unit determines that an assessment for long-term care needs is necessary.

[0014] (6) The examination necessity determination device described in (3) above, wherein the information relating to the subject's condition includes imaging data, motion data, and audio data of the subject, and the digitization processing unit digitizes the subject's physical and cognitive functions based on the imaging data, motion data, and audio data.

[0015] (7) The examination necessity determination device according to (3) above, wherein the information relating to the subject's condition includes imaging data of the subject, and the examination necessity determination device further comprises: a captioning unit that adds captions to images based on the imaging data of the subject; and an analysis unit that analyzes the captions added to the images to quantify the subject's physical and cognitive functions.

[0016] (8) The examination requirement determination device according to (1) or (2) above, further comprising an output unit that outputs the determination result from the determination unit.

[0017] (9) A method for determining whether an assessment is necessary, comprising the steps of: (a) obtaining information about the subject's condition at a first point in time; (b) obtaining information about the subject's condition at a second point in time that is later than the first point in time; and (c) determining whether an assessment for long-term care needs assessment is necessary for the subject based on the information about the subject's condition at the first point in time and the information about the subject's condition at the second point in time.

[0018] A review necessity determination program for causing a computer to execute: a procedure (a) for acquiring information on the state of a subject at a first point in time, a procedure (b) for acquiring information on the state of the subject at a second point in time after the first point in time, and a procedure (c) for determining the necessity of a care needs certification review for the subject based on the information on the state of the subject at the first point in time and the information on the state of the subject at the second point in time.

Advantages of the Invention

[0019] According to the present invention, it becomes possible to omit the care needs certification review at the time of updating the care needs certification.

Brief Description of the Drawings

[0020] The advantages and features provided by one or more embodiments of the present invention will be more fully understood from the following detailed description and the accompanying drawings, which are for illustrative purposes only and are not intended to define the limitations of the present invention. [Figure 1] It is a diagram showing a schematic configuration of a review necessity determination system. [Figure 2] It is a block diagram showing a schematic configuration of a detection device. [Figure 3] It is a block diagram showing a schematic configuration of a terminal device. [Figure 4] It is a block diagram showing a schematic configuration of a server device. [Figure 5] It is a diagram showing the stored content of the storage unit of the server device according to the first embodiment. [Figure 6] It is a flowchart showing a procedure of digitization processing. [Figure 7] It is a flowchart showing a procedure of review necessity determination processing. [Figure 8] It is a diagram for explaining review necessity determination processing. [Figure 9] It is a diagram for explaining review necessity determination processing according to a modification example. [Figure 10] It is a diagram showing the stored content of the storage unit of the server device according to the second embodiment. [Modes for carrying out the invention]

[0021] Embodiments of the present invention will be described below with reference to the drawings. However, the scope of the present invention is not limited to the disclosed embodiments.

[0022] (First Embodiment) Figure 1 is a diagram showing the schematic configuration of the examination necessity determination system 1 to which the examination necessity determination device according to the first embodiment of the present invention is applied.

[0023] As shown in Figure 1, the examination necessity determination system 1 comprises a detection device 10, a terminal device 20, and a server device 30. The detection device 10, the terminal device 20, and the server device 30 are configured to communicate with each other via a network 40.

[0024] The detection device 10 is installed in the rooms of 50 target individuals within various facilities such as nursing homes and hospitals. The terminal device 20 is used, for example, by local government officials who hold care certification review meetings. The server device 30 is an on-premise server located on the premises of the various facilities, or a cloud server using a commercial cloud service. The network 40 consists of the internet and an intranet.

[0025] <Detection device 10> Figure 2 is a block diagram showing the schematic configuration of the detection device 10. The detection device 10 is installed as a sensor box on the ceiling or upper part of the wall of the room where the subject 50 lives.

[0026] As shown in Figure 2, the detection device 10 comprises a control unit 11, a communication unit 12, a camera 13, a Doppler sensor 14, and a microphone 15, which are interconnected by a bus.

[0027] The control unit 11 is composed of a CPU (Central Processing Unit) and memory such as RAM (Random Access Memory) and ROM (Read Only Memory), and controls each of the above parts and performs various calculation processes according to the program.

[0028] The communication unit 12 is an interface for communicating with other devices, and various wired or wireless communication interfaces are used.

[0029] Camera 13 captures images of the subject 50 from the ceiling or upper part of the wall of the living room and outputs the image data of the subject 50.

[0030] The Doppler sensor 14 transmits and receives microwaves to the subject 50 to detect the subject 50's body movements (for example, breathing) and outputs the subject 50's body movement data.

[0031] The microphone 15 captures the sound from inside the room of the subject 50 and outputs the voice data of the subject 50.

[0032] <Terminal device 20> Figure 3 is a block diagram showing the schematic configuration of the terminal device 20. The terminal device 20 is, for example, a PC (Personal Computer).

[0033] As shown in Figure 3, the terminal device 20 comprises a control unit 21, a storage unit 22, a communication unit 23, a display unit 24, and an input unit 25, which are interconnected by a bus. Note that, to avoid repetition in the explanation, the parts of the terminal device 20 that have the same functions as those of the detection device 10 will not be described.

[0034] The storage unit 22 consists of an HDD (Hard Disk Drive) or SSD (Solid State Drive) and stores various programs and data.

[0035] The display unit 24 is, for example, a liquid crystal display, which displays various information.

[0036] The input unit 25 is equipped with a keyboard, numeric keypad, mouse, etc., and accepts input of various instructions and information.

[0037] <Server device 30> Figure 4 is a block diagram showing the schematic configuration of the server device 30. The server device 30 corresponds to the examination requirement determination device of the present invention.

[0038] As shown in Figure 4, the server device 30 comprises a control unit 31, a storage unit 32, and a communication unit 33, which are interconnected by a bus. Note that the above-mentioned parts of the server device 30 have the same functions as the above-mentioned parts of the detection device 10 and the terminal device 20, so their descriptions are omitted.

[0039] Figure 5 shows the contents of the storage unit 32 of the server device 30. As shown in Figure 5, numerical data 100 is stored in the storage unit 32 of the server device 30. The numerical data 100 is numerical data representing the monthly physical and cognitive functions of the subject 50.

[0040] Furthermore, the storage unit 32 of the server device 30 stores programs corresponding to the acquisition unit 110, the digitization processing unit 120, the determination unit 130, and the output unit 140. The acquisition unit 110 acquires information regarding the status of the subject 50. The digitization processing unit 120 digitizes the physical and cognitive functions of the subject 50 based on the information regarding the status of the subject 50. The determination unit 130 determines whether a care needs assessment is necessary at the time of care needs assessment renewal, based on the numerical values ​​indicating the physical and cognitive functions of the subject 50 at the time of facility admission and the numerical values ​​indicating the physical and cognitive functions of the subject 50 at the time of care needs assessment renewal. The output unit 140 outputs the determination result from the determination unit 130 to the terminal device 20. The functions of each of the above units are performed by the control unit 31 executing the corresponding programs.

[0041] Furthermore, the detection device 10, terminal device 20, and server device 30 may have components other than those described above, and may not have some of the components described above.

[0042] In the assessment necessity determination system 1 configured as described above, information regarding the condition of a person 50 who has received long-term care certification and entered a facility is continuously collected by the detection device 10. Then, when the long-term care certification is renewed after a predetermined period (for example, 2 years) has elapsed since the person 50 entered the facility, the necessity of a long-term care certification assessment at the time of renewal is determined based on the information regarding the person 50's condition at the time of entering the facility and the information regarding the person 50's current condition. The operation of the assessment necessity determination system 1 will be explained below with reference to Figures 6 to 8.

[0043] First, referring to Figure 6, we will explain the operation of the server device 30 that quantifies the physical and cognitive functions of the subjects 50.

[0044] Figure 6 is a flowchart showing the procedure for the digitization process performed by the server device 30. The process shown in the flowchart in Figure 6 is executed by the control unit 31 according to the program stored in the storage unit 32 of the server device 30.

[0045] (Step S101) First, the server device 30 acquires information regarding the status of the subject 50. More specifically, the server device 30 acquires a day's worth of imaging data, motion data, and audio data of the subject 50 collected by the detection device 10.

[0046] (Step S102) Next, the server device 30 quantifies the physical functions of the subject 50. More specifically, based on the data acquired in step S101, the server device 30 quantifies the state of the subject 50 with respect to several indicators of physical function.

[0047] In this embodiment, the server device 30 estimates the joint points (joint positions) of the subject 50 from the imaging data of the subject 50 using known machine learning techniques such as OpenPose. The server device 30 then calculates the subject 50's movement speed (walking speed) as an indicator of the subject 50's physical function, for example, from the movement trajectory of the subject 50's head position. The server device 30 then quantifies the subject 50's movement speed on a scale of 0 to 5, with higher values ​​indicating faster movement speed. It should be noted that the higher the subject 50's physical function, the faster their movement speed tends to be.

[0048] Furthermore, the server device 30 calculates the subject 50's daily range of movement (activity range) from the movement trajectory of the subject 50's head position, as another indicator of the subject 50's physical function. The server device 30 then quantifies the subject 50's range of movement on a scale of 0 to 5, with higher values ​​indicating a wider range of movement. It should be noted that the higher the subject 50's physical function, the wider their range of movement tends to be.

[0049] Furthermore, the server device 30 calculates the rotational speed of the subject 50 as another indicator of the subject 50's physical function, for example, from the movement trajectories of the subject 50's head position and shoulder position. The server device 30 then quantifies the rotational speed of the subject 50 on a scale of 0 to 5, with higher values ​​indicating faster rotational speed. It should be noted that the higher the subject 50's physical function, the faster their rotational speed tends to be.

[0050] (Step S103) Next, the server device 30 quantifies the cognitive function of the subject 50. More specifically, based on the data obtained in step S101, the server device 30 quantifies the state of the subject 50 with respect to several indicators of cognitive function.

[0051] In this embodiment, the server device 30 calculates the amount of time the subject 50 is continuously asleep from the subject 50's body movement data. The server device 30 then calculates, for example, the subject 50's continuous nighttime sleep duration as an indicator of the subject 50's cognitive function. The server device 30 then quantifies the subject 50's continuous nighttime sleep duration on a scale of 0 to 5, with higher values ​​indicating longer continuous nighttime sleep duration. It should be noted that the higher the subject 50's cognitive function, the longer their continuous nighttime sleep duration tends to be.

[0052] Furthermore, the server device 30 calculates the speech rate of the subject 50 from the subject 50's voice data as another indicator of the subject 50's cognitive function. The server device 30 then quantifies the subject 50's speech rate on a scale of 0 to 5, with higher values ​​indicating faster speech rate. It should be noted that the higher the subject 50's cognitive function, the faster their speech rate tends to be.

[0053] Furthermore, the server device 30 transcribes the speech content of the subject 50 from the subject 50's audio data. The server device 30 then counts the number of specific words (such as negative words) included in the subject 50's speech content as another indicator of the subject 50's cognitive function. The server device 30 then quantifies the subject 50's speech content on a scale of 0 to 5, with a higher value indicating a smaller number of specific words. It should be noted that the higher the subject 50's cognitive function, the fewer specific words tend to be included in the subject 50's speech content.

[0054] (Step S104) The server device 30 then stores numerical values ​​representing the physical and cognitive functions of the subject 50 and terminates the process. More specifically, the server device 30 calculates the average value of the numerical values ​​of the multiple indicators calculated in the process of step S102 as numerical values ​​representing the physical functions of the subject 50 and stores this average value in the storage unit 32. The server device 30 also calculates the average value of the numerical values ​​of the multiple indicators calculated in the process of step S103 as numerical values ​​representing the cognitive functions of the subject 50 and stores this average value in the storage unit 32, then terminates the process.

[0055] As described above, according to the flowchart shown in Figure 6, the physical and cognitive functions of the subject 50 are quantified from the daily data collected by the detection device 10 and stored in the memory unit 32. In this embodiment, the physical and cognitive functions of the subject 50 are quantified in the range of 0 to 5 and stored in the memory unit 32.

[0056] In addition, in the examination necessity determination system 1 of this embodiment, the server device 30 calculates numerical values ​​indicating the physical and cognitive functions of the subject 50 on a daily basis. Then, once 30 days' worth of data has been accumulated in the storage unit 32, the 30 days' worth of data is averaged to calculate numerical values ​​indicating the physical and cognitive functions of the subject 50 for one month. In this embodiment, from the time the subject 50 enters the facility, numerical values ​​indicating the physical and cognitive functions of the subject 50 are calculated every month and stored in the storage unit 32 as numerical data 100.

[0057] Furthermore, the indicators for the physical and cognitive functions of subject 50 are not limited to those described above, and various indicators may be used. For example, the degree of head sway during walking of subject 50, calculated from subject 50's imaging data, may be used as an indicator of physical function. Alternatively, the walking area of ​​subject 50 (near the wall / center of the room), calculated from subject 50's imaging data, may be used as an indicator of physical function. Or, as an indicator of subject 50's cognitive function, the time subject 50 stands still, calculated from subject 50's imaging data, may be used, or the time period during which subject 50 is walking may be used. Alternatively, as an indicator of subject 50's cognitive function, the intonation of subject 50's speech, the frequency of subject 50's self-talk, or sudden sounds occurring in subject 50's room, calculated from subject 50's voice data, may be used.

[0058] Furthermore, the numerical values ​​representing the physical and cognitive functions of the subjects 50 are not limited to the above embodiment. For example, instead of the average value of multiple indicators, the sum or weighted average of multiple indicators may be used as the numerical values ​​representing the physical and cognitive functions of the subjects 50. Also, the numerical range for each indicator is not limited to 0 to 5; for example, different numerical ranges may be set for each indicator.

[0059] The operation of the server device 30, which determines whether or not a care needs assessment is necessary when renewing the care needs assessment for the subject 50, will be explained below with reference to Figures 7 and 8.

[0060] Figure 7 is a flowchart showing the procedure for determining whether or not an examination is necessary, which is performed by the server device 30. The process shown in the flowchart in Figure 7 is executed by the control unit 31 according to the program stored in the storage unit 32 of the server device 30.

[0061] (Step S201) First, the server device 30 reads numerical data of the subject 50 at the time of admission to the facility. More specifically, the server device 30 reads numerical values ​​from the memory unit 32 indicating the subject 50's physical function and cognitive function one month after admission to the facility. The time of the subject 50's admission to the facility corresponds to the time when the subject 50 received their initial long-term care needs assessment.

[0062] (Step S202) Next, the server device 30 reads the current numerical data of the subject 50. More specifically, the server device 30 reads from the storage unit 32 the numerical values ​​representing the physical function and cognitive function of the subject 50 for the most recent month, as numerical data for the subject 50 when the long-term care certification is renewed.

[0063] (Step S203) Next, the server device 30 compares the numerical data at the time of facility admission with the current numerical data. More specifically, the server device 30 compares the numerical data indicating physical function for one month after facility admission, which was read in step S201, with the numerical data indicating physical function for the most recent month, which was read in step S202. In addition, the server device 30 compares the numerical data indicating cognitive function for one month after facility admission, which was read in step S201, with the numerical data indicating cognitive function for the most recent month, which was read in step S202.

[0064] (Step S204) Next, the server device 30 determines whether the difference between the numerical data at the time of facility admission and the current numerical data is greater than a predetermined amount. More specifically, the server device 30 determines whether the difference between the numerical value indicating physical function one month after facility admission and the numerical value indicating physical function in the most recent month, which were compared in the processing of step S203, is greater than a predetermined amount. The server device 30 also determines whether the difference between the numerical value indicating cognitive function one month after facility admission and the numerical value indicating cognitive function in the most recent month, which were compared in the processing of step S203, is greater than a predetermined amount. If the difference in numerical values ​​for at least one of the physical function and cognitive function is greater than a predetermined amount, the server device 30 determines that the difference between the numerical data at the time of facility admission and the current numerical data is greater than a predetermined amount. The predetermined amount may be set to the same value for both physical function and cognitive function, or different values ​​may be set.

[0065] If the server device 30 determines that the difference between the numerical data at the time of facility entry and the current numerical data is greater than a predetermined amount (step S204: YES), the server device 30 proceeds to the process in step S206. On the other hand, if the server device 30 does not determine that the difference between the numerical data at the time of facility entry and the current numerical data is greater than a predetermined amount (step S204: NO), the server device 30 proceeds to the process in step S205.

[0066] (Step S205) If the difference between the numerical data at the time of facility admission and the current numerical data is not determined to be greater than a predetermined amount (step S204: NO), the server device 30 determines that a care needs assessment is unnecessary and proceeds to step S207. More specifically, the server device 30 determines that there has been no significant change in the physical and cognitive functions of the subject 50 since admission to the facility, and therefore a care needs assessment at the time of renewal is unnecessary, and proceeds to step S207.

[0067] (Step S206) On the other hand, if the server device 30 determines that the difference between the numerical data at the time of admission to the facility and the current numerical data is greater than a predetermined amount (step S204: YES), the server device 30 determines that a care needs assessment is necessary and proceeds to step S207. More specifically, the server device 30 determines that there has been a significant change in at least one of the physical and cognitive functions of the subject 50 after admission to the facility, and therefore a care needs assessment is necessary at the time of renewal, and proceeds to step S207.

[0068] (Step S207) The server device 30 then outputs the result of the determination of whether or not a care needs assessment is necessary and terminates processing. More specifically, the server device 30 sends information indicating whether or not a care needs assessment is necessary at the time of update to the terminal device 20 and terminates processing. As a result, the display unit 24 of the terminal device 20 displays information indicating, for example, that there has been no significant change in the physical and cognitive functions of the subject 50, and therefore the care needs assessment of the subject 50 can remain unchanged and a care needs assessment is not necessary.

[0069] As described above, according to the flowchart shown in Figure 7, when renewing the long-term care certification for subject 50, the physical and cognitive functions of subject 50 at the time of admission to the facility are compared with the physical and cognitive functions of subject 50 at the present time. If there is no significant change between the physical and cognitive functions at the time of admission to the facility and the current physical and cognitive functions, it is determined that a long-term care certification review is unnecessary, and the result is output to the terminal device 20.

[0070] Figure 8 is a diagram illustrating the process for determining whether or not an assessment is necessary. As shown in Figure 8, in this embodiment, the physical and cognitive functions of subject 50 at the time of facility admission (January 2022) and the physical and cognitive functions of subject 50 at the time of renewal of long-term care certification (January 2024) are quantified and compared.

[0071] Furthermore, if the difference between the physical function at the time of facility admission and the physical function at the time of care needs assessment renewal is less than a predetermined amount, and the difference between the cognitive function at the time of facility admission and the cognitive function at the time of care needs assessment renewal is also less than a predetermined amount, it will be determined that holding a care needs assessment review committee meeting is unnecessary.

[0072] This configuration eliminates the need for long-term care certification assessments during renewal, thereby reducing the workload. More specifically, the assessment by certification investigators, the diagnosis and opinion preparation by the attending physician, and the long-term care certification review committee are all eliminated, significantly reducing the workload. In addition, the time it takes to obtain renewal results is shortened.

[0073] The graph shown in Figure 8 may be displayed on the display unit 24 of the terminal device 20, along with the determination result regarding the necessity of the long-term care certification assessment.

[0074] (modified version) In the embodiment described above, only numerical data from the month after admission to the facility and numerical data from the month before the renewal of the long-term care certification were compared to determine whether a long-term care certification assessment was necessary for the subject 50. However, numerical data from the period between the month after admission to the facility and the month before the renewal of the long-term care certification may also be used to determine whether a long-term care certification assessment is necessary.

[0075] Figure 9 is a diagram illustrating the process for determining whether an assessment is necessary for modified cases. As shown in Figure 9, in the process for determining whether an assessment is necessary for modified cases, numerical data for every three months from the time of admission to the facility to the time of renewal of the long-term care certification is read out. Subsequently, a numerical range is set, defined by, for example, an upper limit obtained by adding 0.5 to the value at the time of admission to the facility (January 2022) and a lower limit obtained by subtracting 0.5 from the value at the time of renewal of the long-term care certification (January 2024). If the numerical value for any month from the time of admission to the time of renewal of the long-term care certification falls outside the above numerical range, it is determined that an assessment for long-term care certification is necessary.

[0076] This configuration makes it possible to detect temporary changes in the condition of 50 individuals and determine whether or not they require long-term care assessment.

[0077] In contrast to this modified example, for instance, monthly numerical data from the time of admission to the facility to the time of renewal of the long-term care certification could be read, and it could be determined whether or not the monthly values ​​fall outside the above numerical range.

[0078] Furthermore, similar to the graph shown in Figure 8, the graph shown in Figure 9 can also be displayed on the display unit 24 of the terminal device 20, along with the determination result regarding the necessity of the long-term care certification assessment.

[0079] (Second Embodiment) Next, a second embodiment of the present invention will be described with reference to Figure 10. This embodiment is one in which a caption (explanatory text) is added to an image based on imaging data, and the content of the caption is analyzed to quantify the physical and cognitive functions of the subject. Except for the fact that a caption is added to an image based on imaging data and that the caption is analyzed, the configuration of the examination necessity determination system 1 according to this embodiment is the same as the configuration of the examination necessity determination system 1 according to the first embodiment, so a detailed explanation will be omitted.

[0080] Figure 10 is a diagram showing the contents of the storage unit 32 of the server device 30 according to this embodiment. As shown in Figure 10, the storage unit 32 of the server device 30 stores programs corresponding to the acquisition unit 110, the digitization processing unit 120, the determination unit 130, the output unit 140, the assignment unit 150, and the analysis unit 160. The acquisition unit 110, the digitization processing unit 120, the determination unit 130, and the output unit 140 are the same as in the first embodiment, so their description is omitted. The functions of each of the above units are performed by the control unit 31 executing the corresponding programs.

[0081] The captioning unit 150 adds captions to images based on the subject's imaging data. The captioning unit 150 includes a learning model that has learned the relationship between specific situations in images (moving images) based on the subject's imaging data and the content of the captions added to the images for multiple subjects, and adds captions to images based on the subject's imaging data. The captioning unit 150 analyzes the subject's imaging data and adds captions such as "A staff member is putting shoes on the subject" or "The subject is walking to the toilet by themselves" to images of corresponding scenes. Note that the technique of adding captions to images using a learning model such as a neural network is a well-known technique, so a detailed explanation is omitted.

[0082] The analysis unit 160 analyzes the captions attached to images based on the subject's imaging data and quantifies the subject's physical and cognitive functions. The analysis unit 160 includes a learning model that has learned the relationship between the content of multiple captions and numerical values ​​indicating the subject's physical and cognitive functions, and quantifies the subject's physical and cognitive functions from the captions attached to the subject's images.

[0083] According to the examination requirement determination system 1 of this embodiment, configured as described above, a caption is added to the image based on the imaging data of the subject 50, and the caption added to the image is analyzed to quantify the subject 50's physical and cognitive functions. Then, for example, as a numerical value indicating the subject 50's physical and cognitive functions, the average value of the numerical values ​​of the multiple indicators in the first embodiment described above and the numerical value obtained by analyzing the caption is calculated.

[0084] This configuration makes it possible to quantify the physical and cognitive functions of the 50 subjects with greater accuracy.

[0085] The present invention is not limited to the embodiments described above, and can be modified in various ways within the scope of the claims.

[0086] For example, in the embodiment described above, the case in which imaging data, body movement data, and audio data of the subject 50 are acquired as information regarding the subject 50's state was explained as an example. However, information regarding the subject's state is not limited to this data. For example, vital data such as the subject's heart rate and body temperature may be acquired as information regarding the subject's state, or data related to excretion and sleep data may be acquired. In addition, data related to the subject's movement (angular velocity, acceleration) may be acquired by a wearable sensor attached to the subject's body or clothing. For example, instead of a Doppler sensor, body movement data of the subject may be acquired by a wearable sensor. Also, unlike the embodiment described above, audio data of the subject 50 may not be acquired, and only imaging data and body movement data of the subject 50 may be acquired.

[0087] Furthermore, in the embodiment described above, numerical data at the first point in time when the subject 50 entered the facility was compared with numerical data at the second point in time, which was the time of renewal of the long-term care certification. However, the first and second points in time when the numerical data is compared are not limited to the above points in time. For example, the first point in time may be the time when the long-term care certification was last renewed, and the second point in time may be the time of the current (next) renewal of the long-term care certification.

[0088] Furthermore, in the embodiment described above, the detection device 10 collected information regarding the status of the subject 50 daily, and monthly numerical data was stored in the storage unit 32. However, the time interval for data collection is not limited to monthly. For example, only data for the subject 50 for one month after entering the facility and data for the subject for one month before the renewal of their long-term care certification may be collected. Alternatively, data may be collected every two or three months.

[0089] Furthermore, in the embodiment described above, the results of the care needs assessment conducted by the server device 30 were transmitted to the terminal device 20. However, the results of the care needs assessment conducted by the server device 30 may also be transmitted to a mobile terminal device used by the subject 50 or the subject 50's family. Alternatively, the results of the care needs assessment may be transmitted to a printer and output in paper form.

[0090] The processing units in the flowcharts of the embodiments described above are divided according to the main processing content in order to facilitate understanding of each process. The present invention is not limited by how the processing steps are classified. Each process can be further divided into more processing steps. Also, one processing step may perform even more processes.

[0091] In the embodiments described above, the functions of each device may be implemented by other devices. For example, each function of the server device 30 may be implemented by the detection device 10, or by other server devices. For example, the detection device 10 may calculate the values ​​of each indicator from the data of the subjects 50.

[0092] The means and methods for performing various processing in the examination necessity determination device according to the above embodiment can be implemented by either a dedicated hardware circuit or a programmed computer. The program may be provided, for example, on a computer-readable recording medium such as a USB (Universal Serial Bus) memory or a DVD (Digital Versatile Disc)-ROM, or it may be provided online via a network such as the Internet. In this case, the program recorded on the computer-readable recording medium is usually transferred to and stored in a storage unit such as an HDD. Furthermore, the program may be provided as a standalone application software, or it may be incorporated into the software of the examination necessity determination device as a function of the device.

[0093] While embodiments of the present invention have been described and illustrated in detail, the disclosed embodiments are for illustrative purposes only and are not limiting. The scope of the present invention should be interpreted in accordance with the language of the appended claims. [Explanation of Symbols]

[0094] 1. System for determining whether or not an application needs to be reviewed. 10 detection devices, 11,21,31 Control Unit, 12, 23, 33 Communications Department, 13 cameras, 14 Doppler sensors, 15 microphones, 20 terminal devices, 22,32 memory section, 24 Display section, 25 Input section, 30 server devices, 40 networks, 50 target individuals.

Claims

1. An acquisition unit that acquires information about the subject's condition, A determination unit that determines whether or not a care needs assessment is necessary for the subject based on information regarding the subject's condition at a first point in time and information regarding the subject's condition at a second point in time that is later than the first point in time, A device for determining whether or not an examination is necessary.

2. The device for determining whether an examination is necessary, according to claim 1, wherein the first time point is the time when the subject enters the facility, and the second time point is the time when the subject's long-term care certification is renewed.

3. The system further includes a quantification processing unit that quantifies the physical and cognitive functions of the subject based on the information regarding the state acquired by the acquisition unit, The determination unit determines whether or not a care needs assessment is necessary based on numerical values ​​indicating the subject's physical and cognitive functions at a first time point and numerical values ​​indicating the subject's physical and cognitive functions at a second time point, as described in claim 1 or 2.

4. The device for determining whether a care needs assessment is necessary, according to claim 3, wherein the determination unit determines that a care needs assessment is necessary if the difference between the numerical value at the first time point and the numerical value at the second time point exceeds a predetermined amount.

5. The device for determining whether a care needs assessment is necessary, according to claim 4, wherein if the numerical values ​​indicating the physical and cognitive functions of the subject at a third time point between the first and second time points fall outside the numerical range determined by the numerical values ​​at the first time point and the numerical values ​​at the second time point, the determination unit determines that a care needs assessment is necessary.

6. The information relating to the subject's state includes the subject's imaging data, body movement data, and audio data. The examination requirement determination device according to claim 3, wherein the digitization processing unit digitizes the physical and cognitive functions of the subject based on the imaging data, body movement data, and audio data.

7. The information relating to the subject's condition includes the subject's imaging data, The aforementioned device for determining whether or not an examination is required is, A captioning unit that adds captions to images based on the aforementioned imaging data of the subject, The examination requirement determination device according to claim 3, further comprising: an analysis unit that analyzes the caption attached to the image and quantifies the physical and cognitive functions of the subject.

8. The examination requirement determination device according to claim 1 or 2, further comprising an output unit that outputs the determination result from the determination unit.

9. Step (a) to obtain information regarding the subject's condition at the first point in time, (b) A step of obtaining information regarding the subject's condition at a second time point, which is after the first time point; Step (c) of determining whether a care needs assessment is necessary for the subject based on information regarding the subject's condition at the first time point and information regarding the subject's condition at the second time point, A method for determining whether or not an examination is necessary.

10. Procedure (a) for obtaining information regarding the subject's condition at the first point in time, A procedure (b) for obtaining information regarding the subject's condition at a second time point, which is later than the first time point; A procedure (c) for determining whether a care needs assessment is necessary for the subject based on information regarding the subject's condition at the first time point and information regarding the subject's condition at the second time point, A program that uses a computer to determine whether or not an examination is necessary.

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