Information processing method, information processing program, and information processing device

Abstract

The present invention provides an information processing method, an information processing program, and an information processing device for evaluating the status of care services provided. [Solution] The information processing method includes the steps of: accumulating work data when a care worker performs a service-related task; obtaining a care plan relating to the plan for performing the service-related task; evaluating the service by associating the work data with the care plan; and outputting the service evaluation results.

Description

Technical Field

[0001] The present disclosure relates to an information processing method, an information processing program, and an information processing apparatus for caregiving.

Background Art

[0002] Conventionally, a method of aggregating work data collected by time study using a device has been known (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a need to evaluate the provision status of caregiving services.

[0005] An object of the present disclosure is to provide an information processing method, an information processing program, and an information processing apparatus for evaluating the provision status of caregiving services.

Means for Solving the Problems

[0006] (1) An information processing method according to an embodiment of the present disclosure is a method executed by an information processing apparatus for evaluating services provided by a caregiver to a care recipient, the method including: accumulating work data when the caregiver performs work related to the services; obtaining a care plan regarding a plan to perform work related to the services; evaluating the services by associating the work data with the care plan; and outputting an evaluation result of the services.

[0007] (2) In the step of evaluating the service of the information processing method described in (1) above, the number or percentage of time spent on tasks that were actually performed out of the tasks planned in the care plan may be calculated.

[0008] (3) In the step of evaluating the service of the information processing method described in (1) or (2) above, at least one of the following may be calculated: the difference between the length of time of the work planned in the care plan and the length of time of the work actually performed; the difference between the place where the work was planned to be performed in the care plan and the place where the work was actually performed; or the difference between the care worker who was planned to perform the work in the care plan and the care worker who actually performed the work.

[0009] (4) In the step of evaluating the service of the information processing method described in any one of (1) to (3) above, the ratio of the number of services actually provided by the care worker to the number of services planned to be provided by the care worker in the care plan may be calculated.

[0010] (5) In the step of evaluating the service of the information processing method described in any one of (1) to (4) above, the ratio of the number of services that the care worker was scheduled to provide in the care plan to the number of services provided by the care worker may be calculated.

[0011] (6) An information processing program according to one embodiment of the present disclosure is a program to be executed by an information processing device for evaluating services provided by a care worker to a person receiving care, and includes the steps of: accumulating work data when the care worker performs work related to the service; obtaining a care plan relating to the plan for performing work related to the service; evaluating the service by associating the work data with the care plan; and outputting the evaluation result of the service.

[0012] (7) An information processing device according to one embodiment of the present disclosure is a device for evaluating services provided by a care worker to a person receiving care, comprising: a data storage unit for storing work data when the care worker performs work related to the service; a comparison unit for acquiring a care plan relating to the plan for performing work related to the service and associating the work data with the care plan; a calculation unit for evaluating the service; and an output unit for outputting the evaluation result of the service. [Effects of the Invention]

[0013] According to an information processing method, information processing program, and information processing apparatus according to one embodiment of the present disclosure, the status of care service provision is evaluated. [Brief explanation of the drawing]

[0014] [Figure 1] This is a block diagram showing an example configuration of the information processing system related to this disclosure. [Figure 2] This is a block diagram showing an example of the structure of the learning section. [Figure 3] This is a block diagram showing an example of the configuration of the work division estimation unit. [Figure 4] This is a block diagram showing an example configuration of the evaluation unit. [Figure 5] This flowchart shows an example of a procedure for evaluating work. [Figure 6] This diagram shows an example of a hierarchical structure for work categories. [Figure 7A] This is a diagram representing independent processes. [Figure 7B] This diagram illustrates parallel processes where some actions are performed simultaneously. [Figure 7C] This diagram illustrates parallel processes where the initial actions are performed simultaneously. [Figure 7D] This diagram represents a parallel process where all actions are performed simultaneously. [Figure 7E] This diagram illustrates parallel processes where the final action is performed concurrently. [Figure 7F] This is a diagram representing the interrupt process. [Figure 8] It is a timeline representing the time period when it is estimated that the caregiver has performed the work of each section. [Figure 9] It is a timeline representing the time period when the caregiver has stayed at each position. [Figure 10] It is a bar graph representing the length of time when it is estimated that the caregiver has performed the work of each section.

Embodiments for Carrying out the Invention

[0015] In the field of care services, a shortage of caregivers has become a problem. There is a demand for improving the productivity of care services so that even with a small number of personnel, the work can be efficiently carried out. Also, there is a demand for improving the quality of care services to satisfy the care recipients who receive the care services. A general method for improving the productivity and quality of care services is to understand the process of care services, which is a series of flows at the care service site, and to carry out improvements to care services such as technology introduction or process improvement.

[0016] Care services are carried out based on a care plan. A care plan is a plan for providing care services. The care plan may include, for example, the content of the care services to be provided to the care recipient, or the plan for the timing or frequency of providing care services to the care recipient. That is, the care plan may represent when, where, who, to whom, and what to do. The content of care services may include direct assistance tasks such as meal assistance, transfer assistance, bathing assistance, or watching over. The content of care services may include indirect tasks such as carrying out recreation, cleaning the facility, record-keeping, or various preparations or tidying up. The sampling period of the information included in the care plan may be set, for example, for one month, one week, one day, one hour, or one minute, but may also be set to any other length. A long-term care plan may be created, for example, as a care implementation plan. A short-term care plan may be created, for example, as a daily work plan.

[0017] Providing care services according to the care plan leads to satisfaction for the care recipient or their family members. It is useful to evaluate care services by comparing the work performed by care workers with the care plan. Hereinafter, in this disclosure, an information processing system 1 (see Figure 1) that evaluates care services by comparing the work performed by care workers with the care plan will be described with reference to the drawings.

[0018] (Overview of Information Processing System 1) As shown in Figure 1, an information processing system 1 according to one embodiment comprises an information processing device 10, a sensor 40, an input device 50, a display device 60, and a database 70.

[0019] The information processing device 10 acquires information about care workers in care facilities and other care settings. The information about care workers may include information about the locations where care workers have moved within the care facilities and other care settings, and information about the time spent at each location. Information about the location of care workers is also referred to as location information. Information about the time spent at each location by care workers is also referred to as time information. Location information may include locations where care workers have moved and stayed, or locations that care workers have passed through while moving. In other words, location information may include a history of care workers moving to multiple locations. In this disclosure, locations in care facilities and other care settings are also referred to as places within the care facilities and other care settings. Time information may include the length of time that care workers have stayed at each location in the past, or the time that care workers have started and ended their stay at each location in the past. The time that care workers started staying at a certain location corresponds to the time that care workers completed their movement to that location. The time that care workers ended their stay at a certain location corresponds to the time that care workers started moving away from that location. Location and time information may be generated based on measurement results from sensor 40, as described later. Information regarding care workers may further include the schedule of tasks related to care or indirect care tasks that care workers perform at the care site. The schedule of tasks performed by care workers may also be simply called the work schedule. The work schedule may include schedules set based on the care plan at the care site.

[0020] The information processing device 10 may estimate the tasks performed by the care worker based on information about the care worker. As will be described later, the tasks performed by the care worker may be classified into multiple categories. The tasks performed by the care worker may include tasks performed while the care worker moves to multiple locations. In other words, one task performed by the care worker may be a task that combines actions performed by the care worker at each of the multiple locations. One task performed by the care worker may be a task that combines the care worker moving between multiple locations and actions performed by the care worker at each of the multiple locations. The information processing device 10 may generate a task category estimation model, as described later, for example by performing machine learning, and use the generated task category estimation model to estimate the categories of tasks performed by the care worker. The information processing device 10 may associate the estimation results of the task categories with the length of time the task takes or the frequency of the task.

[0021] The information processing device 10 may acquire the results of a time study that investigates the categories of tasks performed by care workers and the length of time or frequency of those tasks.

[0022] The information processing device 10 may display estimated results or survey results regarding the tasks performed by the care worker as a timeline on the display device 60. The information processing device 10 may also aggregate the length of time or frequency of the tasks performed by the care worker and display the aggregated results on the display device 60.

[0023] The information processing device 10 acquires a care plan at the caregiving site. As described above, a care plan is a plan for providing care services. The care plan may include, for example, the content of the care services to be provided to the person receiving care, or the timing or frequency of providing care services to the person receiving care. The content of the care services may include, for example, the categories of tasks to be performed for the person receiving care, the length of time the care services are provided to the person receiving care, information identifying the care worker providing the care services to the person receiving care, and the location where the care services are provided to the person receiving care. The timing of providing care services may be planned, for example, on a monthly, daily, hourly, or minute basis. The frequency of providing care services may be planned, for example, as the number of tasks or the duration of tasks performed within a predetermined period. The predetermined period may be, for example, a period on a monthly, daily, hourly, or minute basis.

[0024] The information processing device 10 compares the estimated results or survey results regarding the work performed by the care worker with the care plan and evaluates the status of care service provision by the care worker. The evaluation of the status of care service provision may include an evaluation of whether the care service was provided according to the care plan. For example, the evaluation of the status of care service provision may include an evaluation of whether the work was performed at the time or frequency planned in the care plan, or whether the work was performed for the length of time planned in the care plan.

[0025] (Example configuration of Information Processing System 1) The following describes an example configuration of Information Processing System 1.

[0026] <Information Processing Device 10> As shown in Figure 1, the information processing device 10 comprises a work category definition unit 12, a location definition unit 14, a schedule management unit 16, a learning unit 20, a work category estimation unit 30, and an evaluation unit 80. The work category definition unit 12 defines the categories of work performed by the care worker. The location definition unit 14 defines the locations where the care worker moved and stayed, or the locations where the care worker passed through while moving, or the locations where the care worker performed work. The schedule management unit 16 manages the care worker's work schedule. The learning unit 20 generates a work category estimation model used to estimate the categories of work performed by the care worker. The work category estimation unit 30 estimates the categories of work performed by the care worker using the work category estimation model. The evaluation unit 80 evaluates the work performed by the care worker based on work data that includes information about the work performed by the care worker.

[0027] Each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16 may include one or more processors. The processors may include, but are not limited to, general-purpose processors or dedicated processors specialized for specific processing. Each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16 may include one or more dedicated circuits. The dedicated circuits may include, for example, FPGAs (Field-Programmable Gate Arrays) or ASICs (Application Specific Integrated Circuits). Each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16 may include a dedicated circuit instead of a processor, or may include a dedicated circuit together with a processor. Each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16 may be configured as separate components. At least a part of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16 may be configured as a single unit.

[0028] Each of the work division definition unit 12, the location definition unit 14, and the schedule management unit 16 may include a storage unit. The storage unit may store programs executed by each of the work division definition unit 12, the location definition unit 14, and the schedule management unit 16, or information or data used in the processing of each of the work division definition unit 12, the location definition unit 14, and the schedule management unit 16. The storage unit may include, for example, semiconductor memory, magnetic memory, or optical memory. The storage unit may include an electromagnetic storage medium such as a magnetic disk. The storage unit may include a non-temporary computer-readable medium. The storage unit may function as, for example, main memory, auxiliary memory, or cache memory. The storage unit may function as the work memory of each of the work division definition unit 12, the location definition unit 14, and the schedule management unit 16. The memory unit may be configured integrally with the processors of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16, or it may be configured separately from the processors of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16.

[0029] <<Learning Section 20>> As shown in Figure 2, the learning unit 20 includes an action measurement unit 22, a position measurement unit 24, a time measurement unit 25, and a model generation unit 26.

[0030] Each component of the learning unit 20 may include one or more processors or one or more dedicated circuits, similar to the work category definition unit 12, the location definition unit 14, and the schedule management unit 16. The learning unit 20 may also include a storage unit, similar to the work category definition unit 12, the location definition unit 14, and the schedule management unit 16.

[0031] <<Work classification estimation section 30>> As shown in Figure 3, the work section estimation unit 30 includes a position measurement unit 32, a position recognition unit 33, a time measurement unit 34, an estimation unit 35, and an output unit 36.

[0032] Each component of the work category estimation unit 30 may include one or more processors or one or more dedicated circuits, similar to each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16, or each of the components of the learning unit 20. The work category estimation unit 30 may also include a storage unit, similar to each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16, or the learning unit 20.

[0033] <<Evaluation Section 80>> As shown in Figure 4, the evaluation unit 80 includes a data storage unit 81, a comparison unit 82, a calculation unit 83, an analysis unit 84, and an output unit 85.

[0034] Each component of the evaluation unit 80 may include one or more processors or one or more dedicated circuits, similar to each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16, or to each of the components of the learning unit 20 or the work category estimation unit 30. The evaluation unit 80 may also include a storage unit, similar to each of the work category definition unit 12, the location definition unit 14, and the schedule management unit 16, or to the learning unit 20 or the work category estimation unit 30.

[0035] The work category definition unit 12, the location definition unit 14, the schedule management unit 16, the learning unit 20, the work category estimation unit 30, and the evaluation unit 80 may each be configured as separate units. At least a part of the work category definition unit 12, the location definition unit 14, the schedule management unit 16, the learning unit 20, the work category estimation unit 30, and the evaluation unit 80 may be configured as an integrated unit.

[0036] <<Other configurations of the information processing device 10>> The information processing device 10 may include a communication module configured to communicate with other devices such as a sensor 40, an input device 50, a display device 60, or a database 70. The communication module may be configured to communicate with other devices via a network, or it may be configured to communicate with other devices via P2P (Peer to Peer) without a network. The communication module may be configured to communicate with other devices via wired or wireless connections. The communication module may support mobile communication standards such as 4G (4th Generation) or 5G (5th Generation). The communication module may support communication standards such as LAN (Local Area Network). The communication module may support wired or wireless communication standards. The communication module is not limited to these and may support various communication standards.

[0037] The information processing device 10 may be configured to include at least one server. The information processing device 10 may be implemented as a computer such as a desktop PC (Personal Computer), notebook PC, or tablet PC. The information processing device 10 may be implemented as a smartphone or tablet. The information processing device 10 is not limited to these examples and may include various devices.

[0038] The information processing device 10 may be configured as a device equipped with a learning unit 20 and a device equipped with a work category estimation unit 30. The information processing device 10 equipped with the learning unit 20 is also called a learning device. The information processing device 10 equipped with the work category estimation unit 30 is also called a work category estimation device. The information processing device 10 may not be equipped with the learning unit 20 and may acquire a work category estimation model generated by an external device.

[0039] <Sensor 40> Sensor 40 may be configured to detect the location of care workers in care facilities or other care settings, as information relating to care workers. Sensor 40 outputs the detection result of the care worker's location to the information processing device 10. Sensor 40 may include, for example, a location measurement device that uses radio waves from wireless communication installed at the care setting, and detect the location information of care workers. Sensor 40 may include a human presence sensor or camera installed at a location to be targeted for detecting the location of care workers, so as to detect the location of care workers in the care setting. Sensor 40 may include a location measurement device that uses a satellite positioning system such as GPS (Global Positioning System). Sensor 40 may include a location measurement device that uses an Autonomous Activity Measurement System (PDR). Sensor 40 is not limited to these examples and may include various other devices.

[0040] Sensor 40 may be configured to detect the body movements or posture of a care worker as information about the care worker. Sensor 40 may include, for example, an accelerometer or an angular velocity sensor worn by the care worker. Sensor 40 may include, for example, a depth camera that photographs the care worker and generates point cloud data of the care worker. Sensor 40 is not limited to these examples and may include various other devices such as a magnetic sensor, a barometric pressure sensor, a BLE (Bluetooth Low Energy) sensor, or an UWB (Ultra-Wide Band) sensor.

[0041] The sensor 40 may be configured to measure time. The sensor 40 may output to the information processing device 10 the detection result of information about the care worker and the time when the information was detected.

[0042] <Input device 50> The input device 50 accepts information input. The input device 50 may include, for example, a pointing device such as a touch sensor or a mouse. The input device 50 may include physical keys. The input device 50 may include an audio input device such as a microphone. The input device 50 may include a display device that displays the content of the input. The input device 50 may be configured as a touch display in which the display device and the touch panel are integrated.

[0043] The input device 50 may be implemented as, for example, a computer such as a desktop PC, notebook PC, or tablet PC, or a terminal such as a smartphone or tablet. The input device 50 is not limited to these examples and may be implemented as various devices.

[0044] <Display device 60> The display device 60 displays information generated by the information processing device 10. The display device 60 may be configured to include various displays, such as a liquid crystal display, an organic EL (Electro-Luminescence) or inorganic EL display, or an LED (Light Emitting Diode) display, so that the information can be displayed as characters, symbols, or images.

[0045] The display device 60 may be implemented as, for example, a computer such as a desktop PC, notebook PC, or tablet PC, or as a terminal such as a smartphone or tablet. The display device 60 is not limited to these examples and may be implemented as various devices.

[0046] <Database 70> The database 70 may store information about care workers collected by the information processing device 10. The database 70 may also store the estimated results of the care worker's work category estimated by the information processing device 10.

[0047] The database 70 may include at least one server or storage device. The database 70 may include, for example, semiconductor memory, magnetic memory, or optical memory. The database 70 may include an electromagnetic storage medium such as a magnetic disk. The database 70 may include a communication module configured to communicate with other devices such as the information processing device 10.

[0048] The information processing system 1, information processing device 10, or database 70 described above may be implemented using cloud services or in an on-premise environment.

[0049] (Example of an action to estimate the division of work) The following describes an example of how the information processing device 10 estimates the category of work performed by a care worker in the information processing system 1, with reference to Figures 1 to 3.

[0050] Referring to Figure 1, in the information processing device 10, the work category definition unit 12 defines multiple categories for classifying the tasks performed by care workers. The tasks performed by care workers may be classified, for example, by the type of care service. Examples of categories for classifying the tasks performed by care workers will be described later. The information processing device 10 may also obtain definitions of categories for classifying the tasks performed by care workers from an external device, without having a work category definition unit 12.

[0051] As described later, the information processing device 10 uses a work category estimation unit 30 to estimate the category of work performed by the care worker based on information about the care worker. The work category estimation unit 30 may select and output at least one category as the estimated category of work performed by the care worker from among a plurality of categories defined by the work category definition unit 12. The plurality of categories defined by the work category definition unit 12 are candidate categories to be selected as the estimated category of work performed by the care worker, and are also called candidate categories.

[0052] Information regarding care workers includes the locations where care workers move. In the information processing device 10, the location definition unit 14 defines the locations where care workers move. The locations where care workers move may include locations where care workers stay or locations where care workers pass through. The locations where care workers move may be defined as places classified by the function of providing care services within the care facility. The locations where care workers move may be defined as metadata such as, for example, the rooms of care service users, dining rooms, bathrooms, toilets, recreation rooms, or corridors. The locations where care workers move may also be defined as coordinate information that can be associated with the coordinates of a floor plan within the care facility. The information processing device 10 may obtain the definition of the locations where care workers move from an external device without having a location definition unit 14.

[0053] Information regarding care workers includes their work schedules. In the information processing device 10, the schedule management unit 16 manages the care workers' work schedules. The care workers' work schedules may include information regarding the care workers' shifts. Care workers' shifts may be defined as early shifts or late shifts, or day shifts or night shifts, etc. The care workers' work schedules may include information that associates the category of the scheduled work with the time or place where the work is scheduled to be performed. The schedule management unit 16 may set work schedules based on input from the care workers themselves or from the managers or supervisors of the care site. The schedule management unit 16 may also set work schedules based on care plans at the care site. The schedule management unit 16 may also set work schedules based on actual work performance.

[0054] <Example of operation of learning unit 20> The following describes an example of how the learning unit 20 of the information processing device 10 generates a work category estimation model, with reference to Figure 2. The work category estimation model is a model used by the work category estimation unit 30 to estimate the categories of work performed by the care worker.

[0055] The behavior measurement unit 22 acquires information regarding the care worker's behavior. The care worker's behavior may be measured by the sensor 40. The sensor 40 may measure the care worker's behavior by detecting the movement of various parts of the care worker's body. When the care worker's behavior is measured by the sensor 40, the behavior measurement unit 22 may acquire information regarding the care worker's behavior from the sensor 40.

[0056] The behavior measurement unit 22 obtains the definition of the work category performed by the care worker from the work category definition unit 12. The behavior measurement unit 22 associates the information regarding the care worker's behavior with at least one of several work categories performed by the care worker. The work category performed by the care worker may be associated with the information regarding the care worker's behavior by inputting it into the input device 50 by the care worker themselves or another worker.

[0057] The behavior measurement unit 22 outputs the classification of tasks performed by the care worker, which is associated with information about the care worker's actions, to the model generation unit 26 as the correct behavior.

[0058] The position measurement unit 24 obtains the definition of the location to which the care worker moves from the position definition unit 14. The position measurement unit 24 obtains the care worker's location information. The position measurement unit 24 may obtain metadata defining the location to which the care worker moves as the care worker's location information. The position measurement unit 24 may obtain the care worker's coordinate information, convert the coordinate information into metadata, and obtain it as the care worker's location information. In other words, the care worker's location information may include metadata defining the location to which the care worker moves. The care worker's location information may include the care worker's coordinate information. The care worker's location information may include categories of tasks that can be performed at each location to which the care worker can move. The care worker's location information may include information on equipment installed at each location to which the care worker can move.

[0059] The position of the care worker may be measured by the sensor 40. The sensor 40 may measure the position of the care worker, for example, by detecting the position of the care worker as coordinates. The sensor 40 may also measure the position of the care worker by detecting the presence of the care worker at a specific location in a care facility or other care setting, and the location where the presence of the care worker is detected is taken as the position of the care worker. When the position of the care worker is measured by the sensor 40, the position measurement unit 24 may acquire the position information of the care worker from the sensor 40.

[0060] The position of the care worker may be measured by the care worker themselves or by another worker inputting the position into the input device 50. When the care worker's position is input into the input device 50, the position measurement unit 24 may acquire the care worker's position information from the input device 50.

[0061] The position measurement unit 24 outputs the locations where the care worker has moved or stayed as location information of the care worker to the model generation unit 26.

[0062] Care workers may move to multiple locations. The position measurement unit 24 may output information about the multiple locations to which the care worker has moved as care worker position information to the model generation unit 26. The behavior measurement unit 22 acquires information about the care worker's behavior at at least one of the multiple locations to which the care worker has moved. When the behavior measurement unit 22 acquires information about the care worker's behavior at one location, it associates the information about the care worker's behavior at that location with the category of work performed by the care worker at that location. When the behavior measurement unit 22 acquires information about the care worker's behavior at two or more locations, it associates the information about the care worker's behavior at each location with the category of work performed by the care worker at each location. The behavior measurement unit 22 outputs information to the model generation unit 26 that associates the information about the care worker's behavior at each location with the category of work performed by the care worker.

[0063] The care worker's location information may include information about the location where the care worker was located before the location where the behavior measurement unit 22 acquired information about the care worker's behavior. The care worker's location information may include information about the location to which the care worker moved after the location where the behavior measurement unit 22 acquired information about the care worker's behavior. The care worker's location information may include categories of work that can be performed at at least one of the multiple locations to which the care worker moved. The care worker's location information may include information about equipment installed at at least one of the multiple locations to which the care worker moved.

[0064] The time measurement unit 25 acquires time information of the care worker. The time information includes the time the care worker stayed at a single location if the care worker moved to that location. The time information includes the time the care worker stayed at each of the multiple locations if the care worker moved to multiple locations. The time information may include the time the care worker stayed at each location. The time the care worker stayed at a particular location may be expressed as the length of time the care worker stayed at that location. The time the care worker stayed at a particular location may be expressed as at least one of the time the care worker started staying at that location or the time the care worker ended staying at that location, or as a combination of these.

[0065] The time a care worker spends at a particular location may be measured by the sensor 40, as described later. When the time a care worker spends at a particular location is measured by the sensor 40, the time measurement unit 25 may acquire the care worker's time information from the sensor 40. Thus, the sensor 40 may be equipped with a time measurement function. The time measurement unit 25 may acquire the time a care worker spends at one location or at each of multiple locations using the sensor 40.

[0066] The time a care worker spends in a particular location may be measured by the care worker themselves or another care worker inputting the information into the input device 50. When the time a care worker spends in a particular location is input into the input device 50, the time measurement unit 25 may acquire the care worker's time information from the input device 50.

[0067] The time measurement unit 25 outputs to the model generation unit 26 the time spent at each of the one or more locations the care worker has moved to, i.e., the time spent at each location, as time information for the care worker.

[0068] When a care worker moves to multiple locations, the time measurement unit 25 may output information regarding the time the care worker spent at each of the multiple locations as time information to the model generation unit 26. The care worker's time information may include information regarding the time the care worker spent at the location where the care worker was before the location where the behavior measurement unit 22 acquired information regarding the care worker's behavior. The care worker's time information may also include information regarding the time the care worker spent at the location to which the care worker moved after the location where the behavior measurement unit 22 acquired information regarding the care worker's behavior.

[0069] The schedule management unit 16 outputs the work schedule of the care workers to the model generation unit 26.

[0070] The information used for model generation may include information recording the actual duration or number of times a task was performed for each defined location in the care setting where the categories of tasks performed by care workers are estimated. The information used for model generation may include information recording the duration or number of times a planned task was performed for each defined location in the care setting. The information used for model generation may include information defining tasks that are expected to occur for each defined location in the care setting. The location-specific information used for model generation may include information recorded by time studies or information estimated by machine learning models. The locations defined in the care setting may include the target locations for time studies or indoor positioning, or the locations where the task is planned to be performed.

[0071] The information used for model generation may include information recording the actual duration or number of tasks performed for each time slot defined in the caregiving setting. The information used for model generation may include information recording the duration or number of tasks planned for each time slot defined in the caregiving setting. The information used for model generation may include information defining tasks expected to occur for each time slot defined in the caregiving setting. The information for each time slot used for model generation may include information recorded by time studies or information estimated by machine learning models. The time slots defined in the caregiving setting may include the time slots targeted by time studies or indoor positioning, or the time slots in which tasks are planned to be performed.

[0072] The information used to generate the model may include information recording the actual duration or number of tasks performed for each role category defined in the caregiving setting. The information used to generate the model may include information recording the duration or number of tasks planned for each role category defined in the caregiving setting. The information used to generate the model may include information defining tasks expected to occur for each role category defined in the caregiving setting. The information for each role category used to generate the model may include information recorded by time studies or information estimated by machine learning models. The role categories defined in the caregiving setting may include, for example, the scope of work that a caregiver is responsible for, or the job title of a caregiver.

[0073] <<Model Generation>> The following describes an example of how to generate a work classification estimation model based on information about care workers.

[0074] The model generation unit 26 obtains the classification of tasks performed by care workers as correct actions from the behavior measurement unit 22.

[0075] The model generation unit 26 acquires information about the care worker. The model generation unit 26 may acquire the location where the care worker moved from the location measurement unit 24. The model generation unit 26 may acquire the time the care worker stayed at the location where they moved from the time measurement unit 25. In other words, the model generation unit 26 may acquire the location where the care worker moved and the time the care worker stayed at that location as information about the care worker. The model generation unit 26 may acquire the care worker's work schedule from the schedule management unit 16. The model generation unit 26 may acquire all or some of the above-mentioned information as information about the care worker.

[0076] The model generation unit 26 generates a work category estimation model by using information about care workers as training data and performing learning using the tasks performed by care workers, i.e., correct actions, as training data. For example, the model generation unit 26 may use data combining the location where the care worker moved and the time the care worker stayed at that location as training data. The data used as training data is not limited to this example and may be single data or various other combinations. The model generation unit 26 may generate a work category estimation model by performing learning using data that associates location information and time information included in the training data with the work category performed by the care worker, i.e., correct actions, included in the training data. The model generation unit 26 outputs the generated work category estimation model to the work category estimation unit 30.

[0077] When a care worker moves to multiple locations, the model generation unit 26 may obtain location information from the location measurement unit 24, which includes information about the multiple locations the care worker has moved to, and time information from the time measurement unit 25, which includes information about the time the care worker spent at each of the multiple locations the care worker has moved to. The combined information of location information, which includes information about the multiple locations the care worker has moved to, and time information, which includes information about the time the care worker spent at each of the multiple locations the care worker has moved to, is also referred to as the care worker's movement history information. In other words, when a care worker moves to multiple locations, the model generation unit 26 can obtain the care worker's movement history information and the categories of work performed by the care worker at each location included in the movement history information.

[0078] The model generation unit 26 may perform learning using data that combines the care worker's movement history information and information regarding the time the care worker stayed at each location, i.e., time information, with the categories of work performed by the care worker at each location included in the movement history information, and generate a work category estimation model. In this case, the generated work category estimation model may be configured to accept the care worker's movement history information as input and output the estimation result of the category of work performed by the care worker at at least one of the multiple locations to which the care worker moved included in the care worker's movement history information. In other words, the work category estimation model is configured to accept location information regarding the multiple locations to which the care worker moved and time information regarding the time the care worker stayed at each location as input and output the estimation result of the category of work performed by the care worker at at least one of the multiple locations. Thus, an information processing device that estimates the category of work performed by a care worker with high probability from the care worker's location information and time information is based on the inventor's unique knowledge.

[0079] <Example of operation of the work category estimation unit 30> The following describes an example of how the work category estimation unit 30 of the information processing device 10 estimates the category of work performed by a care worker using a work category estimation model, with reference to Figure 3.

[0080] The position measurement unit 32 obtains the definition of the location where the care worker moves or stays from the position definition unit 14. The position measurement unit 32 measures the location where the care worker moves or stays and outputs the measurement result of the location where the care worker moved or stayed to the position recognition unit 33. The position measurement unit 32 obtains the coordinate information of the care worker as the measurement result of the location where the care worker moved or stayed. Based on the coordinate information of the care worker obtained by the position measurement unit 32, the position recognition unit 33 recognizes the position of the care worker as metadata defined in the position definition unit 14. In other words, the position recognition unit 33 may generate metadata of the location where the care worker moved as the result of recognizing the care worker's position. The position recognition unit 33 outputs the recognition result of the care worker's position to the estimation unit 35. The position recognition unit 33 may output the recognition result of each of the multiple locations included in the care worker's movement history to the estimation unit 35. The position measurement unit 32 and the position recognition unit 33 may be configured as a single unit.

[0081] The time measurement unit 34 measures the time spent by the care worker at one location or multiple locations, i.e., the time spent at each location. The time measurement unit 34 outputs the measurement results of the time spent by the care worker at one location or multiple locations, i.e., the time spent at each location, to the estimation unit 35. The time measurement unit 34 may be configured identically to or similarly to the time measurement unit 25 of the learning unit 20.

[0082] The estimation unit 35 operates the work category estimation model generated by the learning unit 20. As described above, the work category estimation model is configured to accept location information and time information of the care worker as input and to output the estimation result of the work category performed by the care worker at at least one location. The estimation unit 35 inputs the location recognition result of the care worker obtained from the location recognition unit 33 as the care worker's location information to the work category estimation model. The estimation unit 35 inputs the measurement result of the time the care worker stayed at the location to which they moved, obtained from the time measurement unit 34, as the care worker's time information to the work category estimation model. The estimation unit 35 outputs the estimation result of the care worker's work category output from the work category estimation model to the output unit 36.

[0083] The estimation unit 35 may input information obtained from the position recognition unit 33, which recognizes multiple locations to which the care worker has moved, and the time measurement results obtained from the time measurement unit 34, which measure the time the care worker spent at each of the multiple locations, as the care worker's movement history information into the work category estimation model. The estimation unit 35 may output to the output unit 36 ​​the estimated result of the work category performed by the care worker at at least one location included in the care worker's movement history information output from the work category estimation model.

[0084] When a care worker moves between multiple locations, the care worker's location information included in the movement history information may include information about the locations where the care worker was located before the location where the care worker performed the task for which classification is to be estimated. Furthermore, the care worker's location information included in the movement history information may include information about the locations where the care worker was located after the location where the care worker performed the task for which classification is to be estimated. The care worker's time information included in the movement history information may include information about the time the care worker spent at the location where the care worker was located before the location where the care worker performed the task for which classification is to be estimated. Furthermore, the care worker's time information included in the movement history information may include information about the time the care worker spent at the locations where the care worker moved after the location where the care worker performed the task for which classification is to be estimated.

[0085] The output unit 36 ​​outputs the estimated results of the care worker's work category obtained from the estimation unit 35, and either displays them on the display device 60 or stores them in the database 70.

[0086] <Summary> As described above, the information processing system 1 can estimate the categories of work performed by a care worker. The work category estimation results may be used as work data in the work evaluation by the evaluation unit 80 described later. Furthermore, in order to perform the means of estimating the categories of work performed by a care worker from the care worker's location information and time information of this embodiment, location information may be measured for each of the locations within the care facility where the care worker whose work category is to be estimated moved or stayed. In addition, information regarding the time spent at each of the locations within the care facility where the care worker whose work category is to be estimated stayed, i.e., time information, may be measured. For example, as illustrated as a timeline in Figure 9 described later, information regarding the time spent at each of the locations within the care facility where the care worker moved or stayed may be measured for the total working hours of a care worker, i.e., the period from 8:30 to 17:15 which is the subject of measurement in the timeline of Figure 9. Note that the start time or end time of working hours is just an example and is not limited to this. As described above, by measuring location and time information for care workers who are the target of work category estimation, it becomes possible to estimate all work categories performed by the care worker throughout their entire working hours. For example, as illustrated in Figure 8 below, the time spent by a care worker performing each work category during their entire working hours, i.e., the period from 8:30 to 17:15 measured in the timeline in Figure 9, can be estimated. By estimating the time spent by a care worker performing each work category throughout their entire working hours, it becomes possible to evaluate which work category is consumed the most time.

[0087] (Example of actions to evaluate the work performed by care workers) The following describes an example of how the evaluation unit 80 of the information processing device 10 evaluates the work performed by the care worker using work data, with reference to Figure 4.

[0088] <Accumulation of work data> The data storage unit 81 acquires and stores work data related to the tasks performed by the care worker. The data storage unit 81 may store the work data in the storage unit of the information processing device 10 or in the database 70. The data storage unit 81 may acquire the work category estimation results from the work category estimation unit 30 and store them as work data. The data storage unit 81 may acquire the aggregated results of work categories collected by the time study and store them as work data. The aggregated results of work categories by the time study may be input from the input device 50. The data storage unit 81 may acquire information about the care worker measured by the sensor 40 and store it as work data.

[0089] <Comparison of work data> The comparison unit 82 acquires the accumulated work data. The comparison unit 82 may extract target data from the work data based on work extraction conditions. The target data is the work data to be compared with the care plan.

[0090] Task extraction criteria may be set by users such as care workers and care recipients, as well as administrators or managers of care facilities. Task extraction criteria may include, for example, conditions that specify data related to tasks performed by a specific care worker, conditions that specify data related to tasks performed for a specific care recipient, or conditions that specify data related to tasks performed on a specific day or time. Task extraction criteria may include conditions that specify multiple care workers or multiple care recipients together. Task extraction criteria may include conditions that specify multiple days or time periods together. Task extraction criteria may include conditions that combine conditions that specify a care worker or care recipient with conditions that specify the day or time period on which the task was performed.

[0091] The comparison unit 82 acquires care plans. The comparison unit 82 may extract target plans from the care plans based on plan extraction conditions. Target plans are care plans to be compared with work data.

[0092] Plan extraction criteria may be set by the user. Plan extraction criteria may include, for example, conditions that specify tasks planned to be performed by a specific caregiver, conditions that specify tasks planned to be performed for a specific person receiving care, or conditions that specify tasks planned to be performed on a specific day or time. Plan extraction criteria may include conditions that specify multiple caregivers or multiple persons receiving care together. Plan extraction criteria may include conditions that specify multiple days or time periods together. Plan extraction criteria may include conditions that combine conditions that specify a caregiver or person receiving care with conditions that specify the day or time period on which the task was performed.

[0093] The comparison unit 82 may match the time resolution of the work data with that of the care plan so that it can compare the work data with the care plan. When comparing target data with target plans, the comparison unit 82 may match the time resolution of the target data with that of the target plan. The time resolution of the work data is the unit of time for which the work performed by the care worker is aggregated. The time resolution of the care plan is the unit of time for which care services are provided. The time resolution may be expressed in minutes or hours, for example. If the time resolution of the work data is greater than the time resolution of the care plan, the comparison unit 82 may match the time resolution of the care plan with that of the work data. If the time resolution of the care plan is greater than the time resolution of the work data, the comparison unit 82 may match the time resolution of the work data with that of the care plan.

[0094] The comparison unit 82 may match the names of tasks included in the work data with the names of tasks included in the care plan so that the work data and the care plan can be compared. When comparing target data with target plan, the comparison unit 82 may match the names of tasks included in target data with the names of tasks included in target plan. The comparison unit 82 may match the work categories included in the work data with the work categories included in care plan. The comparison unit 82 may match the names of tasks included in the work data with the names of tasks included in care plan by referring to a conversion table that associates the names or categories of tasks in the work data with the names or categories of tasks in the care plan.

[0095] The comparison unit 82 associates the tasks included in the work data with the tasks included in the care plan so that the work data and the care plan can be compared. When comparing target data with target plan, the comparison unit 82 associates the tasks included in the target data with the tasks included in the target plan.

[0096] The comparison unit 82 may associate the tasks included in the work data with the tasks included in the care plan based on the work category or name. For example, the comparison unit 82 may associate the tasks included in the work data with the tasks included in the care plan so that the work categories or names match. The comparison unit 82 may extract tasks from the work data that are similar to the work categories or names included in the care plan and associate them with the tasks included in the care plan.

[0097] The comparison unit 82 may associate the tasks included in the work data with the tasks included in the care plan based on the timing of the work. For example, the comparison unit 82 may associate the tasks included in the work data with the tasks included in the care plan so that the timing of when the tasks included in the work data were performed matches the timing of when the tasks included in the care plan were planned. The comparison unit 82 may associate the tasks included in the work data with the tasks included in the care plan so that the difference between the timing of when the tasks included in the work data were performed and the timing of when the tasks included in the care plan were planned is less than or equal to a timing threshold. The timing threshold may be set according to the time resolution.

[0098] The comparison unit 82 may calculate a similarity value that represents the degree to which the tasks included in the work data and the tasks included in the care plan are similar. The comparison unit 82 may associate the tasks included in the work data and the tasks included in the care plan with combinations in which the similarity value is equal to or greater than a similarity threshold.

[0099] The comparison unit 82 may use a machine learning model to determine whether the tasks included in the work data are similar to the tasks included in the care plan, and associate the tasks included in the work data with the tasks included in the care plan in combinations that are determined to be similar.

[0100] The comparison unit 82 may convert one of the work data and care plan formats to match the other format and associate the work data with the care plan. Alternatively, the comparison unit 82 may convert each of the work data and care plan formats to a common format and associate the work data with the care plan.

[0101] <Calculation of the degree of achievement of the care plan> The calculation unit 83 calculates the degree of achievement of the care plan. The calculation unit 83 classifies the care plan into achieved plans and unachieved plans. Achieved plans are tasks that were planned in the care plan and could be associated with work data. Unachieved plans are tasks that were planned in the care plan and could not be associated with work data.

[0102] The calculation unit 83 may calculate the degree of achievement of the care plan by comparing data that have been associated with the work data and the care plan. The degree of achievement may be calculated as the ratio of the work actually performed to the work planned in the care plan. The degree of achievement may be calculated as the ratio of the number of times the work was actually performed to the number of times the work was planned in the care plan. The degree of achievement may be calculated as the ratio of the length of time the work was actually performed to the length of time the work was planned in the care plan. The degree of achievement may be calculated as the difference between the time the work was planned to be performed in the care plan and the time the work was actually performed. The degree of achievement may be calculated as the difference between the frequency the work was planned to be performed in the care plan and the frequency the work was actually performed. The degree of achievement may be calculated based on the difference between the care worker who was planned to perform the work in the care plan and the care worker who actually performed the work. The degree of achievement may be calculated based on the difference between the place where the work was planned to be performed in the care plan and the place where the work was actually performed.

[0103] The calculation unit 83 may calculate the proportion of tasks that fall under the unfulfilled plan among the tasks planned in the care plan. The calculation unit 83 may calculate the proportion of the number of tasks that fall under the unfulfilled plan to the number of tasks planned in the care plan. The calculation unit 83 may calculate the proportion of the time spent on tasks that fall under the unfulfilled plan to the time spent on tasks planned in the care plan.

[0104] <Evaluation of Service Provision Status> The analysis unit 84 may generate data that visualizes achieved plans and unachieved plans as an evaluation result of the service provision status. The analysis unit 84 may generate data that visualizes the degree of achievement in the achieved plans for each task, each time period, or each care worker as an evaluation result of the service provision status. If the degree of achievement is high, it is expected that the satisfaction of the care recipient or their family or other related parties with the care services will be high. The analysis unit 84 may generate data that visualizes whether the degree of achievement is above the achievement threshold. The achievement threshold may be set, for example, as a result of correlating the results of a questionnaire on whether the care recipient or their related parties were satisfied with the care services with the numerical value of the achievement of the care services.

[0105] <Output of evaluation results> The output unit 85 may output and visualize the achievement level calculated by the calculation unit 83 or the service provision status evaluated by the analysis unit 84. The output unit 85 may output the evaluation results so that the care plan is displayed on a timeline or graph. The output unit 85 may display the evaluation results on a display device. The output unit 85 may print the evaluation results on paper. The output unit 85 may output the evaluation results so that they can be viewed remotely outside the care facility. The visualized information may be presented to the care facility's managers, administrators, employees, or care workers. The visualized information may also be presented to the care recipient or their family or other related parties.

[0106] Managers and administrators of care facilities can more easily identify issues in care services by referring to the evaluation results of service provision. These issues may include, for example, the occurrence of unnecessary work, unreasonable work, or inconsistent work. By identifying or understanding these issues, managers and administrators of care facilities can efficiently improve care services.

[0107] <Example of evaluation 1> The evaluation unit 80 may calculate the degree of agreement between the work data and the care plan. The degree of agreement represents the degree to which the work data and the care plan match. The higher the degree of agreement, the smaller the difference between the work data and the care plan.

[0108] The comparison unit 82 acquires the care plan for a care worker for one day and the work data for the same care worker for the same day. The care plan is assumed to be created on a per-care worker basis and in minute increments. The work data is assumed to be measurement data from a time study.

[0109] The comparison unit 82 converts the names of tasks included in the care plan to the names of tasks included in the work data so that the care plan and the work data can be compared. The comparison unit 82 may use a conversion table to convert the names of tasks.

[0110] The comparison unit 82 associates care plans with work data. In Embodiment 1, the comparison unit 82 uses the care worker's shift information to divide the care worker's daily work time into multiple periods, using the care worker's breaks as demarcations. Within each of the divided periods, the comparison unit 82 associates care plans with work data in combinations where the location where the care worker performed the work matches the person receiving care for whom the work was performed. If multiple work data matches a single care plan, the comparison unit 82 associates the work data that was performed by the care worker most recently with the care plan.

[0111] The calculation unit 83 calculates the degree of achievement based on data that associates the care plan with the work data. In Example 1, the calculation unit 83 also calculates the coverage rate and the concentration rate in addition to the degree of achievement. The coverage rate represents the ratio of the number of tasks or the length of time spent on tasks performed by the care worker to the number of tasks or the length of time spent on tasks that the care worker was scheduled to perform. The concentration rate represents the ratio of the number of tasks or the length of time spent on tasks performed by the care worker to the number of tasks or the length of time spent on tasks that the care worker was scheduled to perform.

[0112] The output unit 85 outputs and visualizes the achievement rate, fielding rate, and concentration rate. This makes it easier for managers or administrators of nursing care facilities to identify issues in nursing care services by referring to the achievement rate, fielding rate, and concentration rate. By identifying or understanding these issues, managers or administrators of nursing care facilities can efficiently improve nursing care services.

[0113] <Example of evaluation 2> The evaluation unit 80 compares the workload of care workers with work data and care plans.

[0114] The comparison unit 82 acquires the care plan for a care worker for one day and the work data for the same care worker for the same day. The care plan is assumed to be created on a per-care worker basis and in minute increments. The work data is assumed to be measurement data from a time study.

[0115] The comparison unit 82 converts the names of tasks included in the care plan to the names of tasks included in the work data so that the work data and the care plan can be compared. The comparison unit 82 may use a conversion table to convert the names of tasks.

[0116] The comparison unit 82 performs the acquisition of work data and care plans, and the conversion of work names, on data for each shift of care workers, for example, over a period of 3 or 4 days.

[0117] The calculation unit 83 sums up the duration of each task for both the work data and the care plan, and calculates the ratio of each task to the total duration of all tasks.

[0118] The output unit 85 visualizes, for each task, the ratio of the time spent on the task planned to be performed in the care plan to the ratio of the time spent on the task actually performed according to the work data by displaying it in a graph. This makes it easier for care facility managers or administrators to visually understand which tasks have the largest differences in time between the care plan and the work data, and makes it easier to revise the care plan or review the method of performing the tasks. As a result, care services are improved more efficiently.

[0119] <Example of evaluation 3> The evaluation unit 80 compares the care worker's stay time with the work data and the care plan.

[0120] The comparison unit 82 acquires the care plan for a care worker for one day and the work data for the same care worker for the same day. The care plan is assumed to be created on a per-care worker basis and in minute increments. The work data is assumed to be measurement data from indoor positioning using the sensor 40, etc. The work data includes, for each care worker, the location of the room or other place where the work was performed and the time spent at that location.

[0121] The calculation unit 83, for each care worker, considers the length of time spent at each location as equivalent to the time spent performing work at that location, and sums up the length of time spent at each location as the length of time spent performing work at that location. The calculation unit 83 also sums up the length of time for all tasks that were planned to be performed at each location in the care plan.

[0122] The calculation unit 83 calculates the difference between the total length of time the work was planned in the care plan and the total length of time the care worker actually stayed at that location, for each location. The calculation unit 83 also divides the day into four 6-hour time slots and calculates the difference between the total length of time the work was planned in the care plan and the total length of time the care worker actually stayed at that location, for each time slot.

[0123] The output unit 85 visualizes the difference between the total length of time planned for each task in the care plan and the total length of time the care worker actually spent at that location, by displaying it as a graph for each location. This makes it easier for care facility managers or administrators to visually understand where the difference in the length of work time between the care plan and the work data is large, that is, where work time is likely to be exceeded or shortened, and to revise the care plan or review the method of performing the tasks. As a result, care services are improved more efficiently.

[0124] The output unit 85 may display personal information such as the level of care required, ADL (Activities of Daily Living), or chronic illnesses of the care recipients residing in the rooms corresponding to each location, along with the difference in the total length of time for each location. Personal information of care recipients is useful information that supports the improvement of care services. By displaying personal information of care recipients, care services can be improved more efficiently compared to when it is not displayed.

[0125] <Example of evaluation 4> The evaluation unit 80 evaluates the care plan. The care plans to be evaluated are expected to be those provided in assisted living facilities, special nursing homes, or other facility-based care facilities.

[0126] The data storage unit 81 measures and stores daily work data from the nursing care facility.

[0127] The comparison unit 82 extracts the tasks of the care services to be provided as a care plan from the care implementation plan for each person receiving care, and acquires them as a care plan. From the task data, the comparison unit 82 extracts the tasks performed for the person receiving care for whom the care plan was acquired, and the tasks performed in the person receiving care's room.

[0128] The comparison unit 82 uses a conversion table to convert the names of tasks included in the care plan to the names of tasks included in the task data, and then extracts them.

[0129] The comparison unit 82 calculates the total length of time spent on each task extracted from the care plan, i.e., the total length of time spent on each task extracted from the care plan. In other words, the comparison unit 82 calculates how much time was spent on each task extracted from the care plan within the work data.

[0130] The calculation unit 83 evaluates that a care plan has been achieved for a task if the total length of time spent actually performing the tasks extracted from the care plan is equal to or greater than the evaluation threshold. The evaluation threshold is set to a value as appropriate. The calculation unit 83 calculates the number of tasks for which the care plan has been evaluated as achieved, and calculates the degree of achievement as the ratio of the number of tasks evaluated as achieved to the total number of tasks included in the care plan.

[0131] The output unit 85 outputs the achievement level as an evaluation result of the service provision status. In this way, the evaluation result of the service provision status is fed back to the family of the person receiving care. In addition, the manager or administrator of the care facility can revise the care plan or review the method of carrying out the work according to the achievement level. As a result, care services are improved efficiently.

[0132] <Example of an evaluation flowchart> The evaluation unit 80 of the information processing device 10 may evaluate the work of care workers by executing an information processing method that includes the steps of the flowchart illustrated in Figure 5. The information processing method may be implemented as an information processing program to be executed by the processor constituting the evaluation unit 80. The information processing program may be stored on a non-temporary computer-readable medium.

[0133] The data storage unit 81 of the evaluation unit 80 stores work data (step S1). The comparison unit 82 of the evaluation unit 80 acquires the care plan (step S2). The comparison unit 82 associates the work data with the care plan (step S3). The calculation unit 83 and analysis unit 84 of the evaluation unit 80 evaluate the status of care service provision based on the data associating the work data with the care plan (step S4). The output unit 85 of the evaluation unit 80 outputs the evaluation results (step S5). After executing the procedure in step S5, the evaluation unit 80 finishes executing the procedure in the flowchart of Figure 5.

[0134] <Summary> As described above, the information processing device 10 relating to this disclosure can evaluate the service provision status by comparing the work data of care workers with care plans. The evaluation results of the service provision status are useful information for supporting the discovery or understanding of challenges in providing services and for efficiently improving services. By evaluating the service provision status, the information processing device 10 can generate information that supports the efficient improvement of care services.

[0135] (Other examples) Other embodiments are described below.

[0136] <Example of estimating work divisions> An embodiment for estimating the work categories of a care worker will be described by applying the operation example of the work category estimation unit 30 of the information processing device 10 described above to the following environment.

[0137] First, a time study was conducted to measure the work performed by a total of 15 day and night shift care workers at a nursing care facility. Specifically, the start time, end time, work location, and actions of each care worker were measured.

[0138] Definition data was generated to classify the work area into 10 categories. The work area categories were defined as: mobile area, user's room, dining room, living room, bathroom, toilet, office, staff room, corridor, and other areas.

[0139] Definition data was generated to classify the tasks performed by care workers into 35 categories. The categories of tasks were determined to be: getting up and going to bed, changing positions, dressing and grooming, assisting the user's movement, toileting, meals, hygiene, environmental maintenance, laundry, going out, recreation, transportation, medical procedures, medication management, vital sign measurement, medical examinations, direct interventions on physical function, physical therapy, occupational therapy, speech therapy, care plans, nutritional management, meal service, hygiene management, care worker movement, meetings, office cleaning, and other tasks; understanding the user, information sharing, record keeping, verification, handling visitors, and other services; and breaks.

[0140] Based on the information measured by the time study, the learning unit 20 generated training data that included the location and time at which the care worker performed the task, plus the locations and duration of the 10 tasks performed immediately preceding the task. The learning unit 20 also generated data on the task categories performed by the care worker as training data to generate a task category estimation model. However, in this embodiment, the training data generated based on the measurement results from the time study included 25 out of 35 task categories.

[0141] As described above, the work category estimation model may accept information about the care worker's movement history as input and output an estimated result of the work category performed by the care worker at at least one location to which the care worker moved, as included in the movement history information. In this embodiment, the work category estimation model estimates the work category of the care worker based on location information about the location to which the care worker moved before the location where the action to be estimated was performed, and time information about the time the care worker stayed at that location.

[0142] The learning unit 20 performed machine learning on the training data and target data using a random forest, support vector machine (SVM), or a three-layer convolutional neural network to generate a work portion estimation model.

[0143] The work category estimation unit 30 estimated the work categories of care workers using the work category estimation model generated as described above. Here, the recognition rate of each model was verified by 5-fold cross-validation. The recognition rate is the percentage of the estimated work category that matches the correct category. In the verification, the work category estimation unit 30 input location information and time information when performing a work for which the correct category was known into the work category estimation model. The work category estimation unit 30 obtained the estimated work category from the work category estimation model and calculated the recognition rate by comparing it with the correct category. As a result, the recognition rate using the model generated by machine learning with random forest was 41.7%. The recognition rate using the model generated by machine learning with SVM was 52.2%. The recognition rate using the model generated by machine learning with neural network was 52.5%.

[0144] <Examples of categories of caregiving tasks performed by care workers> The tasks related to caregiving performed by care workers may be classified into multiple hierarchical levels, as illustrated in Figure 6. In the example in Figure 6, the tasks related to caregiving performed by care workers are divided into three levels called major, medium, and minor classifications. A major classification includes at least one medium classification. That is, the number of classifications belonging to a major classification is less than or equal to the number of classifications belonging to a medium classification. A medium classification includes at least one minor classification. That is, the number of classifications belonging to a medium classification is less than or equal to the number of classifications belonging to a minor classification. A major classification is also called the first level. A medium classification is also called the second level. A minor classification is also called the third level. The second level is included in the first level. That is, the second level is a lower level than the first level. The third level is included in the second level. That is, the third level is a lower level than the second level. The number of levels is not limited to three; there may be two or four or more levels.

[0145] In this embodiment, the major classification, or first level, is a classification that categorizes the work performed by care workers by the type of service. The major classification may include, for example, caregiving, nursing, rehabilitation, care support, meals and nutrition, indirect work, non-work-related work, common work, or other work. The major classification may also include measurement errors as a classification for when the work performed by care workers cannot be classified into any of the above categories. The major classification may include various categories, but is not limited to these examples.

[0146] In this embodiment, the intermediate classification, or second level, is a classification that categorizes the tasks performed by care workers according to the purpose or circumstances of the task. The intermediate classification corresponds to the classification that categorizes actions into 35 types in the above-described embodiment of classification estimation.

[0147] The intermediate classification may include, as a category belonging to the major classification of care, for example, getting up and going to bed, changing positions, dressing and grooming, user mobility, excretion, meals, hygiene, environmental maintenance, laundry, going out, recreation, or transportation. The intermediate classification may also include, as a category belonging to the major classification of nursing, for example, medical procedures, medication management, vital sign measurement, physical examination, or direct intervention on physical function.

[0148] The subcategory may include, for example, physical therapy, occupational therapy, or speech-language therapy as a division belonging to the major category of rehabilitation. The subcategory may include, for example, care plans as a division belonging to the major category of care support. In this disclosure, comparing the work actually performed by care workers with the care plan can be used to revise the care plan itself. The subcategory may include, for example, nutritional management, meal service, or hygiene management as a division belonging to the major category of food and nutrition.

[0149] The subcategory may include, for example, the movement of care workers, meetings, or office cleaning, as it is a category belonging to the major category of indirect work. The subcategory may include, for example, breaks, as it is a category belonging to the major category of non-work-related work. The subcategory may include, for example, understanding users, information sharing, record keeping, verification, handling visitors, or other services, as it is a category belonging to the major category of common work.

[0150] The subcategory, or third level, is defined as a classification of tasks performed by care workers based on their content.

[0151] A subcategory may include, for example, assistance with getting up or assistance with going to bed, as a category belonging to the intermediate categories of getting up and going to bed. A subcategory may include, for example, assistance with changing body position or reclining adjustment, as a category belonging to the intermediate categories of dressing and grooming. A subcategory may include, for example, assistance with dressing or grooming, as a category belonging to the intermediate categories of user mobility. A subcategory may include, for example, wheelchair guidance, walking assistance, transfer assistance, or standing assistance, as a category belonging to the intermediate categories of excretion. A subcategory may include, for example, assistance with excretion, diaper changing, or handwashing assistance, as a category belonging to the intermediate categories of meals. The subcategory may include, for example, assistance with bathing, foot bathing, face washing, wiping, perineal cleansing, oral care, earwax removal, nail trimming, shaving, hair washing, hand washing assistance, or gargling assistance, as a subcategory of the hygienic category. The subcategory may include, for example, changing sheets, garbage collection, room cleaning, checking user's belongings, adjusting room temperature, humidity control, lighting control, or ventilation, as a subcategory of the laundry category, for example, washing or collecting laundry. The subcategory may include, for example, assistance with shopping or accompanying users on shopping trips, as a subcategory of the outing category. The subcategory may include, for example, exercise, oral exercises, music, picture storytelling, or cooking, as a subcategory of the recreation category. The subcategory may include, for example, assistance with transportation or getting on and off vehicles, as a subcategory of the transportation category.

[0152] The subcategory may include, as a division within the medium category of medical procedures, for example, tracheal suctioning, wound care, ointment application, disinfection, drug application, intravascular pressure monitoring, intravenous infusion, gastrostomy management, urinary management, enemas, or oxygen therapy. The subcategory may include, as a division within the medium category of drug management, for example, oral administration, enteral administration, dispensing, infusion, injection, suppository administration, or inventory checks. The subcategory may include, as a division within the medium category of vital sign measurement, for example, temperature measurement, SpO2 measurement, pulse measurement, blood pressure measurement, weight measurement, or vital sign measurement. The subcategory may include, as a division within the medium category of medical examinations, for example, attending medical examinations or accompanying patients to hospitals. The subcategory may include, as a division within the medium category of direct interventions on bodily functions, for example, massage or functional recovery.

[0153] The subcategory may include, for example, range of motion exercises, thermotherapy, gait training, standing training, stair climbing, exercise training, or physical therapy assistance, as it belongs to the intermediate category of physical therapy. The subcategory may include, for example, occupational tasks, calculation tasks, cognitive tasks, memory tasks, artistic tasks, play tasks, or occupational therapy assistance, as it belongs to the intermediate category of rehabilitation. The subcategory may include, for example, expression training, auditory comprehension training, swallowing function assessment, indirect swallowing training, or direct swallowing training.

[0154] The subcategories may include, for example, care plan creation, conferences, monitoring, or assessment, as categories belonging to the intermediate categories of care plans. Of these, care plan creation has the advantage of making care plan creation easier, as, as mentioned above, comparing the work actually performed by care workers in this disclosure with the care plan is effective for reviewing the care plan. The subcategories may include, for example, nutrition care plan creation, conferences, monitoring, nutrition assessment, nutrition screening, or nutritional diet consultation, as categories belonging to the intermediate categories of nutrition management. The subcategories may include, for example, menu creation, cooking, meal count management, or ingredient procurement, as categories belonging to the intermediate categories of food service. The subcategories may include, for example, health management, ingredient management, or equipment management, as categories belonging to the intermediate categories of hygiene management.

[0155] A subcategory may include, for example, movement, waiting, or transportation, as a category belonging to the intermediate category of movement of care workers. A subcategory may include, for example, morning meetings, evening meetings, or conferences, as a category belonging to the intermediate category of meetings. A subcategory may include, for example, cleaning of common areas or tidying up, as a category belonging to the intermediate category of office cleaning.

[0156] The subcategory may include, for example, verbal communication, active listening, monitoring, checking the user's condition, or responding to nurse calls, as it belongs to the intermediate category of understanding the user. The subcategory may include, for example, communication, handover, telephone calls, or sending and receiving faxes, as it belongs to the intermediate category of information sharing. The subcategory may include, for example, record making, calculations, printing, and copying, as it belongs to the intermediate category of record making. The subcategory may include, for example, record checking, work checking, or equipment checking, as it belongs to the intermediate category of confirmation. The subcategory may include, for example, dealing with family members or dealing with visitors, as it belongs to the intermediate category of dealing with visitors.

[0157] Subcategories may include common tasks such as preparation, cleanup, or handwashing.

[0158] The learning unit 20 may identify the categories of work performed by care workers and generate training data based on the categories belonging to each of the hierarchical classifications described above. As mentioned above, the number of categories belonging to major classifications is less than the number of categories belonging to intermediate classifications. Also, the number of categories belonging to intermediate classifications is less than the number of categories belonging to minor classifications.

[0159] Here, we assume that the number of pieces of information about the care worker's behavior that the learning unit 20 can collect from the behavior measurement unit 22 is constant. When associating the collected information about the care worker's behavior with work categories, the number of pieces of information about the care worker's behavior that can be associated with each work category is inversely proportional to the number of work categories. In other words, the fewer the number of work categories classified by the work category estimation model, the larger the amount of training data corresponding to that work category. The larger the amount of training data, the higher the estimation accuracy of that work category. Therefore, the learning unit 20 may generate multiple sets of training data and training data that combine different numbers of work categories associated with the collected information about the care worker's behavior, and generate a work category estimation model trained using each set of data.

[0160] For example, the learning unit 20 may generate training data by classifying the collected information on the behavior of care workers into categories belonging to major classifications, and then perform learning using that training data and the corresponding training data to generate a work category estimation model that can estimate the work category of care workers within the major classifications. The learning unit 20 may generate training data by classifying the collected information on the behavior of care workers into categories belonging to medium classifications, and then perform learning using that training data and the corresponding training data to generate a work category estimation model that can estimate the work category of care workers within the medium classifications. The learning unit 20 may generate training data by classifying the collected information on the behavior of care workers into categories belonging to minor classifications, and then perform learning using that training data and the corresponding training data to generate a work category estimation model that can estimate the work category of care workers within the minor classifications.

[0161] The learning unit 20 may generate a work classification estimation model that can estimate the classification of a care worker's work in various other classification groups, not limited to major, medium, or minor classifications. For example, the learning unit 20 may generate a work classification estimation model that estimates the work performed by a care worker as either a work involving movement or a work that does not involve movement. In the above embodiment, when classifying into classifications limited to work involving movement and work that does not involve movement, the recognition rate was increased to 82.8% using the above method with a neural network.

[0162] The learning unit 20 may generate a work classification estimation model that can estimate the classification of a care worker's work using one of the major, medium, or minor classifications. The learning unit 20 may generate a work classification estimation model that can estimate the classification of a care worker's work using two or more of the major, medium, or minor classifications. For example, the learning unit 20 may generate a work classification estimation model that can estimate the classification of a care worker's work using both the major and medium classifications. In this case, the work classification estimation model outputs both the estimation results for the classifications included in the major classification and the estimation results for the classifications included in the medium classification.

[0163] <Estimated using subsequent movement history> In the embodiment described above, the work classification estimation model was configured to estimate the classification of a caregiver's work based on location information relating to the locations the caregiver moved to before the location where the work to be classified was performed, and time information relating to the time the caregiver stayed at those locations. In other words, the classification of a work performed by a caregiver at a certain location was estimated based on the locations the caregiver had moved to in the past.

[0164] The work classification estimation model may be configured to estimate the classification of a caregiver's work based on location information regarding the location the caregiver moved to after the location where the work to be classified was performed, and time information regarding the time the caregiver stayed at that location. In other words, the classification of a work performed by a caregiver at a certain location may be estimated based on the caregiver's future locations.

[0165] In this example, the learning unit 20 generated training data by combining location information representing the work location where the work to be estimated as a work category was performed and time information representing the time the work was performed, based on the information measured by the time study, with location information representing the location where the five tasks immediately preceding the work to be estimated as a work category were performed and time information representing the time the tasks were performed, and location information representing the location where the five tasks immediately following the work to be estimated as a work category were performed and time information representing the time the tasks were performed. The learning unit 20 generated training data to be used as training data for generating a work category estimation model, which included the work categories performed by care workers at the locations identified by the location information in the training data. The learning unit 20 generated a work category estimation model by performing training using the training data and training data.

[0166] The work classification estimation unit 30 estimated the work classification of the care worker using the work classification estimation model generated as described above. Here, the recognition rate of each model was verified by 5-fold cross-validation. The recognition rate using the model generated by machine learning with a neural network was 55.6%. The recognition rate using the model generated by machine learning with a neural network based on the locations the care worker has moved to in the past was 52.5%. Therefore, the recognition rate can be improved by using a model generated based not only on the locations the care worker has moved to in the past but also on the locations they will move to in the future.

[0167] On the other hand, if the categories of tasks performed by a care worker are estimated by a model generated based on the care worker's past locations, they can be estimated in real time or near real time by measuring the locations the care worker moves to and the time the care worker spends at each location.

[0168] <Generating training data through data assimilation> In the above-described embodiment, the training data generated based on the measurement results from the time study contained 25 out of 35 types of tasks. In other words, there were 10 types of tasks that were not included in the training data. When there are tasks that are not included in the training data, the model generated by performing training using that training data is unlikely to be configured to output tasks that are not included in the training data as estimated results. Furthermore, the model generated by performing training using that training data may not output tasks that are not included in the training data as estimated results.

[0169] Tasks not included in the measurement results from time studies are considered to be tasks that rarely occur. These rarely occurring tasks may include, for example, tasks performed in the event of a disaster or accident. It is difficult to collect data on these rarely occurring tasks through time studies.

[0170] Therefore, the learning unit 20 may use a method called data assimilation to generate training data that corresponds to the training data, which includes work categories not included in the measurement results from the time study. Data assimilation is a method for generating training data or training data through simulation. The model generated by performing learning using the training data or training data thus generated can be configured to output as estimation results even work categories that rarely occur and are not included in the measurement results from the time study.

[0171] <Examples of other items included in the training data> The training data may include other items. For example, the training data may include nurse call information, monitoring sensor information, care equipment logs, or work manual information. The training data may include seasonal variation or calendar information. The training data may include climate data such as weather or temperature. The training data may include information about care workers that can be obtained using IoT (Internet of Things) devices, other than the location and time information of care workers.

[0172] <Description of the care process> In care services, the tasks performed by care workers can be described as a care process that combines multiple actions. A care process can be described as an independent process in which a care worker performs multiple actions one by one in sequence, as shown in Figure 7A, for example. In Figure 7A, the care worker proceeds from (1) "Action 1" to "Action 2," and then from (2) "Action 2" to "Action 3."

[0173] The care process can be described not only as an independent process, but also as a parallel process in which a caregiver performs multiple actions simultaneously. A parallel process can be described as one in which some actions are performed in parallel, as shown in Figure 7B, for example. In Figure 7B, the caregiver (1) proceeds from "Action 1" to "Action 2", (2) and (3) performs "Action 2" and "Action 3" in parallel, and (4) proceeds from "Action 2" or "Action 3" to "Action 4".

[0174] A parallel process can be described as having the first actions performed in parallel, as shown in Figure 7C, for example. In Figure 7C, the caregiver (1) proceeds from "Action 1" to "Action 2" and "Action 3" in parallel, (2) performs "Action 2" and "Action 3" in parallel, and (3) proceeds from "Action 2" to "Action 4".

[0175] A parallel process can be described as all actions occurring in parallel, as shown in Figure 7D, for example. In Figure 7D, the care worker (1) proceeds from "Action 1" to "Action 2" and "Action 3" in parallel, performing "Action 2" and "Action 3" in parallel, and (2) proceeds from "Action 2" and "Action 3" to "Action 4".

[0176] A parallel process can be described as having parallel final actions, as shown in Figure 7E, for example. In Figure 7E, the caregiver (1) proceeds from "Action 1" to "Action 2", (2) performs "Action 2" and "Action 3" in parallel, and (3) proceeds from "Action 2" and "Action 3" to "Action 4" in parallel.

[0177] The care process can also be described as an interruption process, as illustrated in Figure 7F, in which a caregiver temporarily suspends a specific action to perform another action and then returns to the original action. In Figure 7F, the caregiver (1) proceeds from "Action 1" to "Action 2", (2) interrupts "Action 2" to perform "Action 3", (3) after completing "Action 3", returns to the interrupted "Action 2", and (4) proceeds from "Action 2" to "Action 4".

[0178] The learning unit 20 may generate movement history information of care workers that takes into account the flow of actions in these care processes as learning data, generate work categories corresponding to the learning data as training data, and generate a work category estimation model by performing learning using the training data. The work category estimation model may be configured to output estimation results of work categories that include some of the actions included in the care process. The work category estimation model may be configured to treat the entire care process as a single task and output estimation results of the work categories for that task.

[0179] The learning unit 20 may generate movement history information, including the order of movement to the locations where each action in the care process is performed, as learning data when each action in the care process is performed at a different location, generate work categories corresponding to that learning data as training data, and generate a work category estimation model by performing learning using that training data. In this case, the work category estimation model is configured to treat the entire care process as a single task and output the estimation result of the work category for that task.

[0180] <Example of displaying estimation results> As described above, the output unit 36 ​​of the work category estimation unit 30 may display the estimated results of the work categories performed by the care worker on the display device 60. The display device 60 may display the estimation results in the form of a timeline corresponding to the time period in which the care worker is estimated to have performed each work category, as illustrated in Figure 8. The horizontal axis in Figure 8 represents the passage of time from left to right. The time period in which each work category was performed is shown as a black rectangle. Displaying it in this way makes it easier to understand the estimated results of the care worker's work categories.

[0181] The display device 60 may display the time periods spent by care workers at each location in the form of a timeline, as illustrated in Figure 9. The horizontal axis in Figure 9 represents the passage of time from left to right. The time periods spent by care workers at each location are shown as black rectangles.

[0182] The display device 60 may display the total estimated time spent by the care worker on each task category as a bar graph, as illustrated in Figure 10. In the graph in Figure 10, the horizontal axis corresponds to the task category. The vertical axis represents the estimated time spent by the care worker on each task category. If a task category is performed in multiple sessions, the estimated time spent on that task category is the sum of the time spent on each session. The display device 60 may also display the frequency of each task category performed by the care worker as a histogram. In other words, the display device 60 may display statistical data on the task categories performed by the care worker. Displaying the data in this way makes it easier to understand the estimation results of the care worker's task categories.

[0183] When the work category estimation unit 30 performs estimation in real time using the estimation unit 35, the display device 60 may change the displayed content in real time according to the real-time estimation results. The display device 60 may display the estimation results of work categories performed by multiple care workers in a comparable format. The display device 60 may display in a comparable format the work categories performed by care workers estimated based on location and time information acquired before the procedure of the work performed by the care worker was changed, and the work categories performed by care workers estimated based on location and time information acquired after the procedure of the work performed by the care worker was changed. The display device 60 is not limited to these examples and may display the estimation results of work categories performed by care workers in various other forms. The output unit 36 ​​of the work category estimation unit 30 may output the content to be displayed on the display device 60 as data or information to another device such as a database 70.

[0184] (summary) As described above, the information processing device 10 according to this embodiment can evaluate the service provision status by comparing the work data of care workers with the care plan. The evaluation results of the service provision status are useful information for identifying or understanding issues when providing services and for efficiently improving services. By evaluating the service provision status, the information processing device 10 can generate information that supports the efficient improvement of care services.

[0185] Furthermore, the information processing device 10 can estimate the categories of care-related tasks performed by care workers in care facilities and other care settings by inputting the care worker's location and time information into a work category estimation model and obtaining the estimation results of the work category from the work category estimation model. By using the work category estimation model, the information processing device 10 can collect work data from care workers without requiring human intervention such as observers. As a result, work data from care workers is collected efficiently. By efficiently collecting work data from care workers, the improvement of care services using the work data from care workers is efficiently supported.

[0186] While embodiments relating to this disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can make various modifications or alterations based on this disclosure. Therefore, it should be noted that these modifications or alterations are included within the scope of this disclosure. For example, the functions included in each component or step can be rearranged in a logically consistent manner, and multiple components or steps can be combined into one or divided. While embodiments relating to this disclosure have been described primarily in terms of apparatus, embodiments relating to this disclosure can also be realized as methods including steps performed by each component of the apparatus. Embodiments relating to this disclosure can also be realized as methods, programs, or storage media recording programs executed by a processor in the apparatus. These should also be understood to be included within the scope of this disclosure. [Explanation of symbols]

[0187] 1. Information Processing System 10. Information processing device (12: Work category definition unit, 14: Location definition unit, 16: Schedule management unit) 20. Learning Unit (22: Behavior Measurement Unit, 24: Location Measurement Unit, 25: Time Measurement Unit, 26: Model Generation Unit) 30. Work Classification Estimation Unit (32: Position Measurement Unit, 33: Position Recognition Unit, 34: Time Measurement Unit, 35: Estimation Unit, 36: Output Unit) 40 sensors 50 Input devices 60 Display device 70 Databases 80 Evaluation Unit (81: Data Storage Unit, 82: Comparison Unit, 83: Calculation Unit, 84: Analysis Unit, 85: Output Unit)

Claims

1. An information processing method performed by an information processing device for evaluating the services provided by care workers to care recipients, A step of accumulating work data when the care worker performs the work related to the service, The steps include obtaining a care plan relating to the plan for performing the work related to the aforementioned service, A step of evaluating the service by correlating the aforementioned work data with the aforementioned care plan, A step of outputting the evaluation results of the service mentioned above. Information processing methods, including those mentioned above.

2. The information processing method according to claim 1, wherein in the step of evaluating the service, the number or percentage of the number of tasks or the time spent on tasks planned in the care plan that were actually performed is calculated.

3. The information processing method according to claim 1 or 2, in the step of evaluating the service, comprising calculating at least one of the following: the difference between the length of time of work planned in the care plan and the length of time of work actually performed; the difference between the place where work was planned to be performed in the care plan and the place where work was actually performed; or the difference between the care worker who was planned to perform work in the care plan and the care worker who actually performed the work.

4. The information processing method according to claim 1 or 2, comprising the step of evaluating the services, which includes calculating the ratio of the number of services actually provided by the care worker to the number of services planned to be provided by the care worker in the care plan.

5. The information processing method according to claim 1 or 2, wherein in the step of evaluating the services, the ratio of the number of services that the care worker was scheduled to provide in the care plan to the number of services provided by the care worker.

6. An information processing program to be executed by an information processing device for evaluating the services provided by care workers to care recipients, A step of accumulating work data when the care worker performs the work related to the service, The steps include obtaining a care plan relating to the plan for performing the work related to the aforementioned service, A step of evaluating the service by correlating the aforementioned work data with the aforementioned care plan, A step of outputting the evaluation results of the service mentioned above. Information processing programs, including those mentioned above.

7. An information processing device for evaluating the services provided by care workers to care recipients, A data storage unit that stores work data when the care worker performs the work related to the service, A comparison unit obtains a care plan relating to the plan for performing the work related to the said service and associates the said work data with the said care plan, A calculation unit for evaluating the aforementioned service, An output unit that outputs the evaluation results of the aforementioned service and An information processing device equipped with the following features.

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