JP7723038B2 - Patient information measurement system and patient information measurement method - Google Patents

Description

The present invention relates to a patient information measurement system and a patient information measurement method.

Various methods for displaying sensor information acquired by sensors have been known in the past. For example, Patent Document 1 discloses a method for displaying sensor information acquired by a sensor on a map in conjunction with the sensor's location.

International Publication No. 2018/179232

We provide a patient information measurement system and patient information measurement method suitable for community-based integrated care systems.

One aspect of the present disclosure relates to a patient information measurement system that includes a patient information acquisition unit that acquires patient information including location information of patients, including home-based patients in community-based integrated care and multiple institutionalized patients residing in facilities, and a display processing unit that performs processing to display the patient information of the home-based patients on a map based on the location information of the home-based patients, and to display statistical information regarding the patient information of the multiple institutionalized patients on the map based on the location information of the multiple institutionalized patients.

Another aspect of the present disclosure relates to a patient information measurement method that acquires patient information including location information of patients, including home-based patients in community-based integrated care and multiple institutionalized patients residing in a facility, displays the patient information of the home-based patients on a map based on the location information of the home-based patients, and displays statistical information regarding the patient information of the multiple institutionalized patients on the map based on the location information of the multiple institutionalized patients.

1 is a configuration example of a patient information measurement system. 1 is a configuration example of an information processing system including a patient information measurement system. 1 is a configuration example of a server system. 1 is a diagram illustrating an example of the configuration of a management terminal device. FIG. 1 is a diagram illustrating an example of an information processing system and the relationship between users of each device. 1 is an example of a patient device. 1 is a configuration example of a patient terminal device. 10 is an example of the data configuration of patient information for a home-care patient. 10 shows an example of the data configuration of patient information of facility patients and examples of statistical information. 1 is a configuration example of a staff terminal device. 10 is an example of a data configuration of staff information. FIG. 2 is a sequence diagram illustrating the processing of the present embodiment. 10 is a flowchart illustrating a process of the server system. 10 is an example of a display screen displayed by a display processing unit. 10 is an example of a facility details screen relating to a facility patient displayed by a display processing unit. FIG. 1 is a diagram illustrating an example of an information processing system and the relationship between users of each device. 10 shows an example of a display screen displayed by a display processing unit and an example of a patient movement operation. 10 is a flowchart illustrating an alert notification process. 10 is a flowchart illustrating a process of estimating a work time. This is an example of past work history by staff. This is an example of a statistical value obtained from a business history. 10 is an example of a display screen displayed by a display processing unit. 10 is an example of a display screen displayed by a display processing unit. This is an example of past work history by staff. This is an example of a work history by a staff member, where the working hours are inappropriate. 10 is a flowchart illustrating a wage approval process. FIG. 1 is a diagram illustrating an example of an information processing system and the relationship between users of each device. 10 is a flowchart illustrating a staff evaluation process. 10 is a flowchart illustrating a process for determining a requested staff member. This is an example of the scope of work for nursing staff. This is an example of the scope of work for medical staff. This is an example of past work history by staff. 10 is an example of a display screen displayed by a display processing unit. 10 is a flowchart illustrating a process for determining whether a visit is necessary. 10 is an example of a display screen displayed by a display processing unit. 10 is an example of a display screen displayed by a display processing unit.

The present embodiment will be described below with reference to the drawings. In the drawings, identical or equivalent elements are designated by the same reference numerals, and duplicate explanations will be omitted. Note that the present embodiment described below does not unduly limit the content of the claims. Furthermore, not all of the configurations described in the present embodiment are necessarily essential components of the present disclosure.

1. System Configuration Example Fig. 1 shows a configuration example of a patient information measurement system 10 according to this embodiment. The patient information measurement system 10 includes, for example, a patient information acquisition unit 11 and a display processing unit 12. However, the configuration of the patient information measurement system 10 is not limited to that shown in Fig. 1, and various modifications are possible, such as omitting some components or adding other components.

The patient information acquisition unit 11 acquires patient information including location information of patients, including home-based patients in community-based integrated care and multiple institutional patients residing in facilities. The patient information may include information representing the state of the patient's biological activity (hereinafter referred to as biological information) and information representing the patient's surrounding environment (hereinafter referred to as environmental information). Details of each type of information will be provided below.

The display processing unit 12 performs processing to display patient information for home-based patients on a map based on the location information of the home-based patients. The display processing unit 12 also performs processing to display statistical information regarding the patient information of multiple facility-based patients on the same map based on the location information of multiple facility-based patients.

Here, a home-based patient is a patient receiving care at home. Note that in this embodiment, we are assuming patients who are in high need of home-visit medical care and home-visit nursing care through the community-based integrated care system, so a home-based patient may also be a patient living alone and separate from their family. However, a home-based patient may also be a patient living with their family and utilize home-visit medical care, etc., to obtain the assistance of a specialist. A facility-based patient is a patient who resides in a facility with multiple patients. The term facility-based patient can also be referred to as a resident patient. The facility here may be a hospice, a housing complex for the elderly, or any other type of facility where multiple patients reside.

Statistical information is information statistically derived from patient information (biometric information and environmental information) obtained from each of multiple facility patients, and includes the total number of abnormal values (facility) and the total number of abnormal individuals, which will be described later using Figure 8B. Details of statistical information will be provided later.

In recent years, community-based integrated care systems have become known, providing comprehensive care, including medical care, nursing care, and lifestyle support, within a community. In community-based integrated care systems, patients may receive care at home or in a facility with multiple patients, making it necessary to consider both home-based and facility-based patients. In this case, a home-based patient is assumed to be the only patient in the target location (the patient's home), whereas a facility-based patient is assumed to be accompanied by other patients in the target facility. Therefore, while displaying patient information in association with a map is useful for patient management, there is a risk that information about facility-based patients may be concentrated in one location. It is also possible that multiple patients may reside in a patient's home, such as in the case of a married couple where both patients require care. Therefore, in this embodiment, if only one patient resides in a target location, the patient is considered a home-based patient (a patient living alone), and if multiple patients reside in the target location, the patient is considered a facility-based patient. Therefore, in this embodiment, if multiple patients reside in a patient's home, the patient's home is considered a facility, and each of the multiple patients is treated as a facility-based patient.

In this regard, with the method of this embodiment, statistically determined statistical information is displayed for patient information on multiple facility patients. Therefore, even when information on home patients and multiple facility patients is displayed together on a single map, it is possible to display it in an easy-to-understand manner. As a result, for example, a manager viewing the display screen can make appropriate decisions regarding patient management, staff dispatch, etc.

Figure 2 is a diagram showing an example configuration of an information processing system 1 including a patient information measurement system 10 according to this embodiment. The information processing system 1 includes a server system 100, a patient device 200, a staff device 300, and a management terminal device 400. However, the configuration of the information processing system 1 is not limited to that shown in Figure 1, and various modifications are possible, such as omitting some components or adding other components. For example, Figure 2 shows three patient devices 200 corresponding to one home patient and two facility patients, but the number of patient devices 200 may be changed depending on the number of patients. Similarly, the number of staff devices 300 may be changed depending on the number of staff members.

The patient information measurement system 10 according to this embodiment may be a server system 100. For example, the patient information acquisition unit 111 of the server system 100 described below corresponds to the patient information acquisition unit 11 in FIG. 1, and the display processing unit 114 of the server system 100 corresponds to the display processing unit 12 in FIG. 1. However, the patient information measurement system 10 may also be implemented by other devices included in the information processing system 1. For example, the patient information measurement system 10 may be implemented by the management terminal device 400, or by distributed processing between the server system 100 and the management terminal device 400. The patient information measurement system 10 may also include at least one of a patient device 200 and a staff device 300. The following mainly describes an example in which the patient information measurement system 10 corresponds to the server system 100.

The server system 100 shown in FIG. 2 is connected to a patient device 200, a staff device 300, and a management terminal device 400, for example, via a network. The network here is, for example, a public communications network such as the Internet. However, the network is not limited to a public communications network and may be a LAN (Local Area Network) or the like. For example, the server system 100 may communicate in accordance with the IEEE 802.11 standard. However, various variations in the communication method between each device are possible.

The server system 100 may be a single server, or may include multiple servers. For example, the server system 100 may include a database server and an application server. The database server stores patient information for home patients and patient information for facility patients. The database server can also store various types of information, such as staff information, which will be described later using FIG. 10, and staff work history (task history), which will be described later using FIG. 19. The application server performs various processes. The application server executes the processes, which will be described later using, for example, FIG. 12. The multiple servers here may be physical servers or virtual servers. If a virtual server is used, the virtual server may be located on a single physical server, or may be distributed across multiple physical servers. As described above, the specific configuration of the server system 100 in this embodiment can be modified in various ways.

The patient device 200 includes one or more devices associated with the patient. For example, the patient device 200 may include a detection device 220 that detects body movement, a thermometer 230, a hygrometer 240, etc., as described below with reference to FIG. 6. The patient device 200 measures the patient's biological information and environmental information based on these devices, and transmits the measurement results to the server system 100. The biological information and environmental information are used as part of the patient information.

The patient device 200 may also include a patient terminal device 210 placed near the patient, as described below with reference to FIG. 7. The patient terminal device 210 is, for example, a mobile terminal device such as a smartphone or tablet terminal. However, the patient terminal device 210 may also be other devices, such as a PC (Personal Computer), a headset, or a wearable device such as AR (Augmented Reality) glasses or MR (Mixed Reality) glasses. Details of the patient device 200 will be described below.

The staff device 300 is a device used by staff performing work (care) related to patients. For example, the staff device 300 includes a staff terminal device 310 carried by the staff, as described below using FIG. 9. The staff terminal device 310 is a smartphone or tablet terminal, but may also be other devices such as a PC. For example, the staff device 300 measures location information and transmits the measurement results to the server system 100. The staff location information is used as part of the staff information.

The staff in this embodiment may be care workers, care managers, and other care-related personnel (hereinafter referred to as care staff), or medical professionals such as nurses and doctors (hereinafter referred to as medical staff). The staff in this embodiment are staff in charge of home care and home medical care who are dispatched to patients' homes, facilities, etc. to provide care to the patients at the dispatched locations.

The management terminal device 400 is a device used by the administrator who manages patients and staff. The management terminal device 400 is a PC, but it may also be a smartphone, tablet device, etc. The management terminal device 400 is placed at the administrator's workplace. The administrator's workplace may be, for example, a dispatch station that is a staff dispatch base, a hospital, or another facility. Furthermore, the management terminal device 400 is not limited to being fixed in a predetermined location, but may also be a device that the administrator can carry with them.

Figure 3 is a block diagram showing a detailed example configuration of the server system 100. The server system 100 includes, for example, a processing unit 110, a memory unit 120, and a communication unit 130. However, the configuration of the server system 100 is not limited to that shown in Figure 3, and modifications such as omitting some components or adding other components are possible.

The processing unit 110 of this embodiment is composed of the following hardware. The hardware may include at least one of a circuit for processing digital signals and a circuit for processing analog signals. For example, the hardware may be composed of one or more circuit devices or one or more circuit elements mounted on a circuit board. The one or more circuit devices may be, for example, an IC (Integrated Circuit), an FPGA (Field-Programmable Gate Array), etc. The one or more circuit elements may be, for example, a resistor, a capacitor, etc.

The processing unit 110 may also be implemented by the following processor. The server system 100 of this embodiment includes a memory that stores information and a processor that operates based on the information stored in the memory. The information may be, for example, a program and various data. The memory may be the storage unit 120 or another memory. The processor includes hardware. Various processors can be used as the processor, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or a DSP (Digital Signal Processor). The memory may be semiconductor memory such as SRAM (Static Random Access Memory), DRAM (Dynamic Random Access Memory), or flash memory, or may be a register, a magnetic storage device such as a hard disk drive (HDD), or an optical storage device such as an optical disk drive. For example, the memory stores computer-readable instructions, and the processor executes these instructions to realize the functions of the processing unit 110 as processing. The instructions here may be instructions from an instruction set that constitutes a program, or instructions that instruct the processor's hardware circuitry to operate.

The processing unit 110 may include a patient information acquisition unit 111, a staff information acquisition unit 112, a judgment processing unit 113, a display processing unit 114, and a notification processing unit 115.

The patient information acquisition unit 111 acquires patient information. This patient information may include pre-registered information and information measured using sensors, etc. Registered information may be, for example, location information representing the patient's home or facility, and attribute information such as name and age, while measured information may be, for example, biometric information and environmental information. Note that location information may be measured by the patient device 200 (e.g., the patient terminal device 210). Specific examples of this information will be described later.

For example, the patient information acquisition unit 111 may perform processing to acquire patient information registered in an external device. Registration may be performed using any of the patient terminal device 210, the staff terminal device 310, and the management terminal device 400. The patient information acquisition unit 111 also performs processing to acquire biometric information and environmental information measured using the patient device 200. For example, the patient information acquisition unit 111 controls communication with the patient device 200 via the communication unit 130.

The staff information acquisition unit 112 acquires staff information. Like patient information, the staff information may include pre-registered information and information measured using sensors, etc. Registered information may include job type information indicating the staff member's job type, and measured information may include location information, etc. For example, the staff information acquisition unit 112 controls communications with the staff device 300, etc. via the communication unit 130.

The determination processing unit 113 performs determination processing based on the information acquired by the patient information acquisition unit 111 and the staff information acquisition unit 112. The determination processing unit 113 determines the priority (priority score) indicating the degree to which a visit to the target location (patient's home, facility) should be prioritized, the recommended visiting route when staff visit the target location, etc. The determination processing unit 113 can also perform various processes such as predicting work time and evaluating staff based on the prediction results. Specific processes will be described later.

The display processing unit 114 executes display processing for a display screen containing patient information, etc. This display screen may be displayed, for example, on the display unit 440 of the management terminal device 400. In this case, the display processing unit 114 of the server system 100 executes processing for transmitting the display screen itself and information used to generate the display screen in order to display the display screen on the management terminal device 400.

When an abnormality is detected based on patient information, etc., the notification processing unit 115 executes processing to notify the abnormality. It is assumed that this notification is executed, for example, by the management terminal device 400, but it may also be executed by the patient terminal device 210 or the staff terminal device 310. For example, the notification processing unit 115 executes processing to instruct the target device to issue a notification in a predetermined manner. Notification here can be realized in various ways, such as display on a display unit, illumination of a light-emitting unit (e.g., an LED), sound output from a speaker, or vibration of a vibration unit such as a motor. Furthermore, when an alert is issued using a display unit, the notification processing unit 115 may execute processing to instruct the display processing unit 114 on specific display content.

The memory unit 120 is a work area for the processing unit 110 and stores various information. The memory unit 120 can be implemented using various types of memory, and the memory may be semiconductor memory such as SRAM, DRAM, ROM (Read Only Memory), or flash memory, or it may be a register, a magnetic storage device, or an optical storage device.

The communication unit 130 is an interface for communicating over a network, and when the server system 100 performs wireless communication, it includes, for example, an antenna, an RF (radio frequency) circuit, and a baseband circuit. However, the server system 100 may also perform wired communication, in which case the communication unit 130 may include a communication interface such as an Ethernet connector and a control circuit for the communication interface. The communication unit 130 may operate under control of the processing unit 110, or may include a processor for communication control that is different from the processing unit 110. The communication unit 130 may perform communication according to a method specified in, for example, IEEE 802.11 or IEEE 802.3. However, the specific communication method can be varied in various ways.

Figure 4 is a block diagram showing a detailed example configuration of the management terminal device 400. The management terminal device 400 may include, for example, a processing unit 410, a memory unit 420, a communication unit 430, a display unit 440, and an operation unit 450. However, the configuration of the management terminal device 400 is not limited to that shown in Figure 4, and modifications such as omitting some components or adding other components are possible.

The processing unit 410 is configured by hardware including at least one of a circuit for processing digital signals and a circuit for processing analog signals. The processing unit 410 may also be implemented by a processor. Various types of processors can be used, such as a CPU, GPU, or DSP. The processor executes instructions stored in the memory of the management terminal device 400, thereby realizing the functions of the processing unit 410 as processing.

The memory unit 420 is the work area of the processing unit 410 and is realized by various types of memory such as SRAM, DRAM, and ROM.

The communication unit 430 is an interface for communicating over a network and includes, for example, an antenna, an RF circuit, and a baseband circuit. The communication unit 430 communicates with the server system 100, for example, over a network. The communication unit 430 may perform wireless communication with the server system 100, for example, in accordance with the IEEE 802.11 standard.

The display unit 440 is an interface that displays various information and may be a liquid crystal display, an organic EL display, or another type of display. The display unit 440 displays various screens, which will be described later using, for example, Figure 13. The operation unit 450 is an interface that accepts user operations. The operation unit 450 may be a mouse or keyboard, or may be another operation interface. The display unit 440 and operation unit 450 may also be a touch panel that is integrally configured.

Figure 5 shows a specific example of the information processing system 1 according to this embodiment, and the relationship between users who use each device. Figure 5 illustrates two patients: Patient A and Patient B, who are home patients, and Patient C and Patient D, who are institutionalized patients. Patient A and Patient B each receive care at home. Patient C and Patient D reside in the same facility, an apartment complex for the elderly.

In addition, Figure 5 shows staff A and staff B, who provide home care or home medical care, as examples of staff. Staff A and staff B travel between patient homes, facilities, dispatch stations, etc., by means of transportation such as a car. The manager performs management tasks at a management facility such as a dispatch station. As mentioned above, the manager may be mobile while carrying the management terminal device 400. Therefore, the location where the manager performs management tasks may change as the manager moves.

As shown in Figure 5, patient devices 200, such as a detection device 220 and a thermometer 230, are provided in association with each of patients A to D. These patient devices 200 periodically measure biological information and environmental information and transmit the data (measurement results) to the server system 100. The server system 100 performs monitoring, including determining whether there are any abnormalities in the biological information and environmental information, for example by comparing the numerical values that are the measurement results with normal ranges.

Furthermore, staff member A and staff member B each carry a staff member terminal device 310. The staff member terminal device 310 periodically detects their location information and transmits the detection results to the server system 100. Furthermore, when each staff member performs a task, they may use the staff member terminal device 310 to input information related to that task (hereinafter also referred to as task information). The staff member terminal device 310 transmits the task information input by the staff member to the server system 100.

The server system 100 transmits data for the administrator to the management terminal device 400 based on information from patients A through D, staff A, and staff B. For example, as described below using Figure 13, the server system 100 may transmit screen information to the management terminal device 400 for displaying patient information and staff information on a map in association with the location information of each patient and staff member.

The administrator who views the screen using the management terminal device 400 monitors the patient and manages the staff. For example, if the administrator determines that an abnormality has occurred with the patient and that work by staff is required, the administrator may issue work instructions to staff A and staff B. Specifically, the management terminal device 400 transmits information indicating the administrator's instructions to the staff terminal device 310.

Upon receiving the work instructions, the staff member performs the visit service. Figure 5 shows an example in which staff member A visits Patient A's home, and staff member B visits the facilities where Patients C and D reside. However, as described below, the method of this embodiment displays a screen that supports the decision on which staff member to dispatch to which location, allowing the administrator to flexibly set the dispatch destination. Staff members may also be able to view patient information by accessing the server system 100 using the staff terminal device 310. This makes it possible to encourage staff members to take appropriate measures, such as by considering the care content during the visit in advance. For example, if fecal leakage is detected, the administrator or staff member can infer that the care content is a diaper change. If physical abnormalities such as breathing or heart rate are detected, the administrator or staff member can infer that the care content is measuring vital signs, adjusting the ventilator, contacting a doctor, and responding to an ambulance. Furthermore, the system according to this embodiment (e.g., the server system 100) may infer and present the care content.

Furthermore, some or all of the processing performed by the patient information measurement system 10 of this embodiment may be realized by a program. In a narrow sense, the processing performed by the patient information measurement system 10 is processing performed by the processing unit 110 of the server system 100, but it may also be processing executed by the processing unit 410 of the administrator terminal device 400. Furthermore, the processing performed by the patient information measurement system 10 may include processing executed by a processor included in the patient device 200 or the staff device 300.

The program according to this embodiment can be stored in, for example, a non-transitory information storage medium (information storage device), which is a medium readable by a computer. The information storage medium can be realized, for example, by an optical disc, memory card, HDD, or semiconductor memory. The semiconductor memory is, for example, ROM. The processing unit 110 and the like perform various processes of this embodiment based on the program stored in the information storage medium. In other words, the information storage medium stores a program that causes a computer to function as the processing unit 110 and the like. A computer is a device that includes an input device, a processing unit, a memory unit, and an output unit. Specifically, the program according to this embodiment is a program that causes a computer to execute each step described below using Figure 12 and the like.

The technique of this embodiment can also be applied to a patient information measurement method that includes the following steps. The patient information measurement method includes the steps of acquiring patient information including location information of patients, including home patients in community-based integrated care and multiple facility patients residing in facilities, displaying the patient information of the home patients on a map based on the location information of the home patients, and displaying statistical information regarding the patient information of multiple facility patients on the map based on the location information of the multiple facility patients.

2. Examples of Patient Information and Staff Information Next, specific examples of patient information and staff information will be described.

2.1 Patient Information Fig. 6 is a diagram showing a specific example of a device for measuring information about a patient, among the patient-use devices 200. As shown in Fig. 6, the patient-use device 200 includes a detection device 220 that measures biological information.

The detection device 220 is a sheet- or plate-shaped device that is placed between the bottom of the bed 610 and the mattress 620, as shown in FIG. 6, for example. The detection device 220 is a device that senses information related to the patient's sleep. The detection device 220 includes a pressure sensor (e.g., an air pressure sensor) that outputs a pressure value.

When the user goes to bed, the detection device 220 detects the user's body vibrations (body movement, vibrations) via the mattress 620. Based on the detected body vibrations, the detection device 220 obtains information related to the respiration rate, heart rate, activity level, posture, awake/asleep, and whether the user is out of bed or in bed. The detection device 220 may output sensor data representing the body vibrations, and another device, such as the server system 100, may execute a process to obtain information such as the respiration rate based on the sensor data. Below, an example in which the detection device 220 outputs information such as the respiration rate will be described.

For example, the detection device 200 may analyze the periodicity of body movement and calculate the respiratory rate and heart rate from the peak frequency. The periodicity may be analyzed using, for example, a Fourier transform. The respiratory rate is the number of breaths per unit time. The heart rate is the number of heartbeats per unit time. The unit time is, for example, one minute. The detection device 220 may also detect body vibrations per sampling unit time and output the number of detected body vibrations as the amount of activity. Furthermore, when the user gets out of bed, the detected pressure value decreases compared to when the user is in bed. Therefore, the detection device 220 may determine whether the user is out of bed or in bed based on the pressure value or a time-series change. However, the method for determining whether the user is out of bed or in bed is not limited to this, and various modifications are possible, such as detecting vibrations. The detection device 220 may also determine whether the user is in non-REM sleep or REM sleep, or the depth of sleep. The sleep determination may be performed based on the respiratory rate and heart rate, the amount of body movement (e.g., activity level), or both.

The detection device 220 may also determine whether the patient has started to move. For example, the detection device 220 may determine that a patient has started to move when the patient transitions from a bed-sitting state to an out-of-bed state. Furthermore, from the perspective of detecting signs of movement at an earlier stage, the detection device 220 may also determine that a patient has started to move when the patient transitions from a sleeping state to an awake state. The detection device 220 may output the movement detection result as biometric information to the server system 100.

Furthermore, the patient device 200 for detecting the patient's biological information is not limited to the detection device 220. For example, the patient device 200 may include a thermometer, electrocardiogram, pulse meter (heart rate monitor), pulse oximeter, body composition monitor, and stethoscope. In this case, the patient device 200 transmits information such as body temperature, electrocardiogram, pulse rate (heart rate), blood oxygen saturation, height, weight, body fat, muscle mass, and respiratory sounds as biological information to the server system 100.

The patient device 200 for detecting biometric information may also include a device for detecting the patient's excretion status. For example, the patient device 200 may include a sensor that is attached inside a diaper or clothing and detects the presence or absence of urine or feces. The sensor here may be, for example, a sensor that detects changes in capacitance due to the presence or absence of urine, an odor sensor that detects the odor of urine or feces, or some other sensor. In this case, the patient device 200 transmits excretion information indicating the patient's excretion status to the server system 100 as biometric information. Furthermore, the device for detecting the excretion status is not limited to being attached inside a diaper or the like, but may also be a device placed in a toilet.

As shown in FIG. 6, the patient device 200 also includes a thermometer 230 and a hygrometer 240 as devices for measuring environmental information. The thermometer 230 detects the temperature around the patient. The hygrometer 240 detects the humidity around the patient. The thermometer 230 and the hygrometer 240 transmit the temperature and humidity as environmental information to the server system 100.

Furthermore, the patient device 200 used to detect the patient's environmental information is not limited to the thermometer 230 and hygrometer 240. For example, the patient device 200 may include a CO2 measuring device, a light meter, etc. In this case, the patient device 200 transmits information such as carbon dioxide concentration and light intensity to the server system 100 as environmental information.

A patient terminal device 210 such as a smartphone may also be installed near the patient. The patient terminal device 210 may be used by the patient themselves, or by the patient's family or staff.

Figure 7 shows an example configuration of the patient terminal device 210. The patient terminal device 210 includes a processing unit 211, a memory unit 212, a communication unit 213, a display unit 214, an operation unit 215, and an imaging unit 216.

The processing unit 211 is configured with hardware including at least one of a circuit for processing digital signals and a circuit for processing analog signals. The processing unit 211 may also be realized by a processor. The storage unit 212 is the work area of the processing unit 211 and is realized by various types of memory such as SRAM, DRAM, and ROM. The communication unit 213 is an interface for communicating over a network. The display unit 214 is an interface for displaying various types of information. The operation unit 215 is an interface for accepting user operations.

The imaging unit 216 has an image sensor that captures an image of a predetermined imaging range and outputs image information. This image information may be a still image or a moving image. The image information may also be in color or monochrome.

The patient information in this embodiment may include information acquired by the patient terminal device 210. For example, the location information included in the patient information may be measured by the patient terminal device 210. The patient information may also include image information (captured images) of the target patient, audio data of the patient's speech, snoring, etc., etc.

Figures 8A and 8B show the data structure of patient information. Figure 8A is an example of patient information for a patient at home. As shown in Figure 8A, patient information may include location information, body movement information, environmental information, excretion information, and total number of abnormal values.

Location information is information that indicates the patient's location. In the case of a patient at home, location information that indicates the location of the patient's home is used. Location information may be information expressed using latitude and longitude, or information expressed using an address or postal code, for example. Location information may also be information expressed using distance and direction from a specific reference point. For example, location information may be information registered by an administrator or staff member when a patient is added to the system of this embodiment.

The location information here may also include information that indicates the attributes of the location corresponding to that location. For example, location information for a patient at home may include, in addition to information that indicates the patient's location, information that indicates that the location is the patient's home. Location information for a patient in a facility, which will be described later using Figure 8B, may include, in addition to information that indicates the patient's location, information that indicates that the location is a facility that houses multiple facility patients. Information that identifies the home/facility may also be managed as information separate from the location information.

Although omitted from Figure 8A, the patient information may also include various other information to be registered in addition to location information. Possible pre-registered information includes the patient's name, gender, medical history, medication history, etc. Furthermore, if automatic measurement using a body composition analyzer is not performed, information such as height and weight may be set manually. The patient information may also include information from the electronic medical record. For example, the patient information may include diagnostic values and results for blood pressure, blood glucose, SpO2, body temperature, electrocardiogram, etc., contained in the electronic medical record. This information may be registered by an administrator or staff member based on the electronic medical record, or may be registered automatically when a device such as the server system 100 acquires the electronic medical record. For example, if the server system 100 is linked to a system that handles electronic medical records, the patient information acquisition unit 111 acquires patient information based on the electronic medical record.

In the above, the location information has been assumed to be pre-registered information, but this is not limited to this. For example, the patient terminal device 210 shown in FIG. 7 may detect location information based on a sensor such as GPS, the communication status with a Wi-Fi base station, or the communication status with a mobile communication base station such as 5G. The patient information acquisition unit 111 may then acquire the location information detected by the patient terminal device 210. Furthermore, a patient device 200 other than the patient terminal device 210 may be able to detect location information, and the patient information acquisition unit 111 may acquire the location information detected by that patient device 200.

Body movement information is information detected by the detection device 220 described above, and may be the sensor output itself indicating body movement, or information regarding respiratory rate, heart rate, activity level, posture, awake/asleep, and whether the patient is out of bed or in bed, or both. Furthermore, excretion information is information indicating the patient's excretory status, as described above.

Although not shown in FIG. 8A, the patient information may also include biological information such as the above-mentioned body temperature, electrocardiogram, pulse rate (heart rate), blood oxygen saturation, height, weight, body fat, muscle mass, and respiratory sounds. As described above, this information may be registered based on the information in the electronic medical record, or may be measured by the patient device 200.

Environmental information is information that describes the state of the patient's surrounding environment. As mentioned above, environmental information includes information such as temperature, humidity, carbon dioxide concentration, and illuminance.

The total number of abnormal values is information that indicates the number of items of biological information and environmental information included in the patient information for which abnormal values were obtained. The total number of abnormal values is determined, for example, by the determination processing unit 113. Details of the processing by the determination processing unit 113 will be described later.

Figure 8B is a diagram showing the data configuration of patient information for facility patients. As shown in Figure 8B, patient information for facility patients may include location information, body movement information, environmental information, excretion information, and total number of abnormal values.

As can be seen from a comparison of Figures 8A and 8B, even when targeting institutional patients, patient information can use the same data format as for home patients. However, the location information for institutional patients is information that indicates the location of the facility in which the institutional patient resides, and is common information for multiple institutional patients residing in the same facility.

Furthermore, as shown in Figure 8B, statistical information representing the characteristics of the entire facility may be obtained based on patient information obtained for each of multiple facility patients. Here, statistical information includes, for example, the total number of abnormal values (facility), the total number of abnormal individuals, and the total number of patients.

The total number of abnormal values (facility) is the sum of the total number of abnormal values (individuals) obtained for each of the multiple facility patients residing in the facility. The total number of abnormal values (facility) represents how much abnormal biological information and environmental information has been obtained for the entire facility. The total number of abnormal values (facility) is obtained, for example, by the determination processing unit 113.

The total number of abnormal cases is information that indicates the number of patients with abnormalities in a certain number or more of the items of biological information or environmental information. In a narrow sense, the number of patients in whom an abnormal value is measured in at least one item of biological information or environmental information is counted as the number of abnormal cases. The total number of abnormal cases is calculated, for example, by the determination processing unit 113 in the same way as the total number of abnormal values.

The total number of patients is information that indicates the number of facility patients currently residing in the facility. The total number of patients may be information that is registered in advance, similar to location information, for example.

As explained above, patient information includes at least one of sleep state information, breathing information, heart rate information, and excretion information obtained based on the patient's body movements. Sleep state information may be information indicating either sleep or wakefulness, or may be information indicating the depth of sleep. Breathing information is, for example, the breathing rate, as described above. However, the breathing information may be waveform information for determining the breathing rate (a waveform indicating body movements), or information indicating the amount of change in the breathing rate. Similarly, heart rate information is not limited to the heart rate, and may include information for determining the heart rate or information determined from the heart rate.

According to the method of this embodiment, information indicating a patient's condition (particularly the state of biological activity) is collected and displayed as patient information, enabling, for example, a community-based integrated care system to appropriately monitor each patient's condition and have staff take appropriate measures. For example, because the item in which an abnormality was detected (the sensor that detected the abnormality) is clearly displayed, administrators can estimate the care required. Furthermore, administrators can make urgency judgments, such as determining that physical abnormalities such as breathing or heart rate pose a greater risk to life and require immediate action than fecal incontinence. As a result, administrators can make appropriate decisions, such as selecting staff with specialized knowledge, when a physical abnormality is detected. Note that with only breathing and heart rate measurements, sensors may issue alerts, potentially resulting in the dispatch of specialized staff, even when the patient's immediate prior exercise is less likely to warrant such an action. Therefore, in this embodiment, by using a camera to determine the patient's condition in advance, such as whether the patient is conscious or unconscious, the need for staff to be dispatched due to unnecessary alerts may be reduced. Techniques for reducing unnecessary visits will be described later using Figures 33-35.

As explained above, patient information may include at least one of temperature information, humidity information, heat index, illuminance information, and carbon dioxide information obtained based on environmental sensors placed around the patient. Temperature information may be the temperature itself, or other information based on temperature. The same applies to humidity information. The heat index is, for example, WBGT (Wet Bulb Globe Temperature), which is calculated based on temperature, humidity, and the surrounding environment (such as solar radiation and radiant heat), but other indices may also be used. WBGT is effective, for example, for determining the risk of heatstroke. Illuminance information is, for example, a value in units of lux, but other information may also be used. Carbon dioxide information is, for example, the carbon dioxide concentration in the patient's room, but other information related to carbon dioxide may also be used.

According to the method of this embodiment, information describing the patient's surrounding environment is collected and displayed as patient information, making it possible, for example, in a community-based integrated care system, to monitor whether each patient's environment is being properly maintained, and to have staff take appropriate action if a problem occurs in the environment.

2.2 Staff Information The staff device 300 includes a staff terminal device 310 such as a smartphone. However, the staff device 300 may also include other devices such as a headset, a wearable device such as AR glasses or a watch-type device.

Figure 9 is a diagram showing an example configuration of the staff terminal device 310. The staff terminal device 310 includes a processing unit 311, a memory unit 312, a communication unit 313, a display unit 314, an operation unit 315, and an imaging unit 316. These components are similar to those of the patient terminal device 210 described above using Figure 7, for example, and therefore will not be described in detail.

The staff terminal device 310 may also include a sensor that detects location information. For example, the staff terminal device 310 may acquire location information using a Global Navigation Satellite System (GNSS) such as the Global Positioning System (GPS). Alternatively, the staff terminal device 310 may detect location information by performing positioning based on the results of communication with a Wi-Fi base station or a mobile communication base station such as 5G.

Figure 10 shows an example of the data structure of staff information. Staff information includes location information, work information, distance to the abnormal patient, preferred route, etc. Location information is measured by the staff terminal device 310 as described above and transmitted to the server system 100.

Task information is information that describes the tasks performed by staff, and includes information such as the start time of the task, the end time of the task, the target patient, and the work content. Task information may also be information that describes the history of tasks performed in the past, as will be described later using Figure 19, for example. Task information may also include information about tasks that staff are scheduled to perform and tasks that are currently being performed.

The distance to the abnormal patient is information that indicates the distance from the current location of the staff member to the location of the patient if an abnormality occurs in the patient. The distance to the abnormal patient is calculated by the judgment processing unit 113 based on, for example, patient information and staff information.

The preferred route is information that indicates the travel route that is preferred by the target staff member. The preferred route is calculated by the determination processing unit 113 based on factors such as the distance between the staff member and the abnormal patient. Details of the process for determining the preferred route will be described later.

3. Details of the Process Fig. 11 is a sequence diagram illustrating the process of this embodiment. Note that Fig. 11 illustrates patient devices 200 corresponding to a home patient (e.g., patient A in Fig. 5) and two facility patients (e.g., patients C and D in Fig. 5), but the number of patients is not limited to this. Also, Fig. 11 illustrates one staff device 300, but the number of staff is also not limited to this.

When this process begins, information from the patient device 200 and staff device 300 is sent to the server system. Specifically, in step S101, the patient device 200 of the patient at home measures biological information and environmental information. In step S102, the patient device 200 of the patient at home sends the measurement results as part of the patient information.

Similarly, in step S103, the patient device 200 of the facility patient measures biometric information and environmental information. In step S104, the patient device 200 of the facility patient transmits the measurement results as part of the patient information. The same applies to steps S105-S106.

In step S107, the staff terminal device 310 acquires staff information. This staff information may be location information or business information. In step S108, the staff terminal device 310 transmits the staff information to the server system 100.

Note that the processes shown in steps S101-S108 are not limited to being performed in this order. For example, the timing of information measurement and information transmission may be scheduled for each patient device 200, and the patient device 200 may perform measurement and transmission processes according to the schedule. Furthermore, the measurement cycle and transmission cycle do not need to be the same; multiple measurement results obtained over a certain period of time may be transmitted together. Different measurement cycles may also be set depending on the information being measured. For example, the detection device 220, thermometer 230, and hygrometer 240 may transmit their measurement results to the server system 100 at the timing set for each device. Furthermore, information from each device may be transmitted to the patient terminal device 210, and the patient terminal device 210 may then transmit the measurement results to the server system 100 according to a predetermined schedule.

The timing of acquiring and transmitting staff information can also be varied in various ways. For example, location information may be acquired and transmitted at a predetermined interval. Furthermore, work information may be manually entered by staff at any time (for example, immediately after completing work or upon returning to the dispatch station), with this input serving as a trigger for transmission processing to the server system 100.

In step S109, the server system 100 (determination processing unit 113) performs processing based on the collected patient information and staff information.

Figure 12 is a flowchart explaining the processing of the server system 100 in step S109. First, in step S201, the determination processing unit 113 determines whether the patient information contains any abnormal values.

The determination processing unit 113 compares the values of the biological information and environmental information obtained as patient information with the normal range for the acquired patient information of home patients and facility patient information corresponding to multiple facility patients. For example, the storage unit 120 of the server system 100 may store, as the normal range, a numerical range corresponding to a normal state for each item of biological information or environmental information. The determination processing unit 113 determines that the values of the biological information or environmental information are abnormal when they fall outside the normal range.

If no abnormal values are detected in the patient information (step S201: No), processing from step S202 onwards is skipped, and the processing shown in Figure 12 ends.

If at least one abnormal value is detected (step S201: Yes), in step S202, the determination processing unit 113 determines whether the patient in whom the abnormal value was detected (hereinafter, the abnormal patient) is a home patient. For example, the determination processing unit 113 may perform the determination processing of step S202 by reading the location information of the patient information and referencing the information indicating the home/facility included in the location information.

If the abnormal patient is a facility patient (step S202: No), in step S203, the determination processing unit 113 determines how many abnormal patients there are in the facility under consideration, thereby determining the total number of abnormal patients. For example, the determination processing unit 113 determines whether each of multiple facility patients residing in the facility under consideration is an abnormal patient based on whether their biometric information or environmental information contains abnormal values. The determination processing unit 113 then determines the total number of abnormal values by counting the facility patients determined to be abnormal in the facility under consideration.

Although not shown in Figure 12, the determination processing unit 113 may also determine the total number of patients, which is the total number of facility patients residing in the facility. The determination processing unit 113 can determine the total number of patients by counting how many patient information items have been acquired from the facility in question. Alternatively, considering that patient admissions and departures are registered, the total number of patients does not need to be determined each time, but may be calculated and registered when there is a change in the registered information.

If the abnormal patient is a home patient (step S202: Yes), in step S204, the determination processing unit 113 sets the total number of abnormal patients to 1. This is because when targeting home patients, it is assumed that there are no other patients in the patient's home. As mentioned above, in this embodiment, home patients are patients living alone, and if there are multiple patients, such as a married couple, in the patient's home, those multiple patients are determined to be institutional patients.

In step S205, the determination processing unit 113 calculates the total number of abnormal values. For example, the determination processing unit 113 calculates the total number of abnormal values for each patient by counting the number of items determined to be abnormal for each patient. This corresponds to the total number of abnormal values shown in Figure 8A or the total number of abnormal values (individual) shown in Figure 8B. For home patients, this completes the process of calculating the total number of abnormal values. On the other hand, when targeting institutional patients, the number of abnormal values for the entire facility is calculated as shown in Figure 8B. For example, the determination processing unit 113 calculates the total number of abnormal values (facility) by adding up the total number of abnormal values (individual) for all institutional patients residing in the facility.

Through the above processing, the judgment processing unit 113 can determine whether or not there are any abnormalities, the number of abnormal values if there are any abnormalities, the number of abnormal patients, etc. By displaying this information on the display unit 440 of the management terminal device 400, it is possible to display useful information to the administrator.

However, from the perspective of supporting the administrator's judgment, the judgment processing unit 113 may request further information. For example, the judgment processing unit 113 determines the priority of home-based patients and facilities based on the patient information of home-based patients and the patient information of multiple facility-based patients. In this way, it is possible to support the administrator in determining the priority of each individual home and facility. For example, it becomes possible for the administrator to make appropriate decisions regarding the order in which staff should be dispatched, etc.

In step S206, the determination processing unit 113 determines the priority. Note that the following describes an example in which a priority score, which is numerical data, is calculated as the priority, but the priority may also be tiered information such as (high, medium, low) or (yes, no).

For example, the determination processing unit 113 may determine the priority of home patients and facilities based on at least one of the number of abnormalities (total number of abnormal values), which indicates the number of items in the patient information where abnormalities have occurred, and the number of abnormalities (total number of abnormal individuals), which is the number of people where abnormalities have occurred. If abnormalities have occurred in multiple facility patients, the facility in question will likely have a higher priority because the total number of abnormal values and total number of abnormal individuals will be larger. Therefore, the method of this embodiment makes it possible to set priorities that take into account the difference in the number of patients at home and in facilities.

For example, in step S206, the determination processing unit 113 may determine the priority of a home patient based on the number of abnormalities (total number of abnormal values), which indicates the number of items in which abnormalities have occurred. In this way, the priority can be easily determined by counting the presence or absence of abnormalities for each item. For example, the priority score may be the total number of abnormal values itself, the ratio of the total number of abnormal values to the total number of items for which values have been obtained, or other information using the total number of abnormal values.

The determination processing unit 113 may also determine the priority for home-based patients based on the total number of abnormal patients, which represents the number of patients experiencing abnormalities. When targeting home-based patients, the total number of abnormal patients is set to a maximum of 1 as shown in step S203, so the priority determined using the total number of abnormal patients is unlikely to be an extremely high value.

The determination processing unit 113 may also determine the priority of a home-based patient based on the severity of the patient's condition. Here, severity may be determined, for example, based on the degree to which the values of biological information or environmental information deviate from the normal range. Alternatively, an importance level is set for each item, and the determination processing unit 113 may determine that when an abnormal value is detected in an item with a high importance level, the severity is higher than when an abnormal value is detected in an item with a low importance level. Alternatively, the determination processing unit 113 may determine the severity level based on the patient's medical history and medication history. The determination processing unit 113 may also determine the priority of a home-based patient based on two or more of the total number of abnormal values, the total number of abnormal individuals, and the severity level.

The determination processing unit 113 may also determine priority based on the total number of abnormal values when targeting a facility. In this case, the total number of abnormal values corresponds to the total number of abnormal values (facility) in Figure 8. The determination processing unit 113 may also determine priority based on the total number of abnormal individuals. When targeting a facility, the upper limit of the total number of abnormal individuals is the total number of patients, so the upper limit of priority is higher than when targeting patients at home. Therefore, when targeting a facility, the priority is likely to be higher than when targeting a patient's home (a patient's home living alone).

For example, the determination processing unit 113 may calculate the priority score based on the following formula (1): where a, b, and c are given constants. However, as described above, in calculating the priority score, weighting may be performed based on the patient's attributes (age, medical history, level of care required), the item or type of sensor in which the abnormal value was detected, the degree to which the abnormal value deviates from the normal range, etc.
Priority score = a × total number of abnormalities + b × total number of abnormal values + c (1)

In step S207, the determination processing unit 113 determines a recommended visiting route for staff based on the priority of the home-based patient, the priority of the facility, and the location information of the staff. This makes it possible to manage not only priorities that take into account the patient information of the home-based patient and the facility, but also the ease of staff visits.

For example, the determination processing unit 113 determines that the higher the priority score of a target location (patient's home, facility) and the closer the distance from the staff member, the more the staff member should visit the target location. For example, the determination processing unit 113 may determine the visit priority based on the following formula (2). Note that the priority in this embodiment may be the priority score, the visit priority, or both.
Visit priority = (priority score / distance between visit destination and staff member) ... (2)

For example, consider the case where patient home A has a priority score of 1 and facility A has a priority score of 5. Furthermore, suppose a staff member is 3.5 km from patient home A and 5 km from facility A, and is available to visit either location. In this case, patient home A is closer in terms of distance, but facility A has a higher priority score, so the administrator may be unsure of the order in which to dispatch staff.

In this regard, with the method of this embodiment, the visit priority of patient home A is 1/3.5 = 0.29, and the visit priority of facility A is 5/5 = 1. Therefore, the determination processing unit 113 can support the efficient dispatch of staff by outputting a visit route that prioritizes visiting facility A, which has a higher visit priority, over patient home A.

Furthermore, when there are multiple staff members, the determination processing unit 113 may determine the priority based not only on the distance between the visit destination and the staff member, but also on information about the staff member. For example, the determination processing unit 113 may determine the priority based on one or a combination of two or more of (1) the staff member's occupation, (2) the staff member's evaluation, and (3) the items the staff member possesses. For example, the determination processing unit 113 may determine the priority so that the priority of staff members who satisfy the conditions of occupation, evaluation, and item is higher than the priority of staff members who do not satisfy the conditions. Alternatively, the determination processing unit 113 may determine the priority for staff members who satisfy the conditions of occupation, evaluation, and item, and exclude staff members who do not satisfy the conditions from the priority calculation. In addition, various modifications are possible to the specific examples of processing using the above conditions (1) to (3).

Here, the occupation of the staff member may be based on official qualifications such as caregiver, nurse, doctor, etc., or on the internal qualifications of the business providing the home visit service. For example, caregivers, nurses, and doctors each have different capabilities, so even if the staff member is close to the visit destination, there may be situations where it is not desirable for that staff member to treat the patient. In this regard, the determination processing unit 113 determines the priority taking into account the staff member's occupation, which makes it possible for the administrator to urge the dispatch of staff member with the appropriate occupation. Details of occupations will be described later using Figures 29 and 30.

Staff evaluation is a measure of whether a staff member can properly perform the visiting service. For example, as will be described later using Figure 27, staff evaluation may be calculated by the determination processing unit 113 based on the predicted response time. Alternatively, staff evaluation may be performed by the manager, the patient, or their family. For example, even if the staff member is close to the visit destination, if the staff member's evaluation is low, the priority may be calculated to be low, which makes it possible to encourage the manager to dispatch staff with appropriate skills. Note that staff evaluation here may also be calculated based on the content of the response. For example, an evaluation result may be obtained in which a certain staff member is highly rated for responding to temperature abnormalities, but is poorly rated for responding to blood pressure abnormalities. In this case, by calculating the priority taking into account the abnormality that occurred and the staff evaluation related to that abnormality, it becomes possible to encourage the manager to dispatch more appropriate staff member.

The items carried by the staff may be measuring equipment (such as a blood pressure monitor) carried by the staff, treatment equipment (such as a ventilator), or consumables (such as diapers, water, and oxygen for inhalation). Depending on the nature of the patient's abnormality, it may be impossible to respond to the abnormality unless these items are carried. Therefore, the determination processing unit 113 determines the priority by taking into account the items that are estimated to be necessary based on the abnormality that has occurred and the items that the staff are carrying, and can urge the manager to dispatch staff who are carrying appropriate items. Specific examples of items and examples of screens displayed on the display unit 440 of the management terminal device 400 will be described later using Figure 22.

Returning to Figure 11, we will continue our explanation. Based on the processing of step S109 described using Figure 12, in step S110, the display processing unit 114 generates a display screen to be viewed by the administrator and instructs the management terminal device 400 to display the display screen. In step S111, the display unit 440 of the management terminal device 400 displays the display screen based on the instruction from the display processing unit 114.

Figure 13 is an example of a screen displayed on the display unit 440 of the management terminal device 400. As shown in Figure 13, the display screen of this embodiment simultaneously displays, on top of map information, an object OB1 corresponding to the patient information of a home patient and an object OB2 corresponding to a facility where multiple institutional patients reside. Note that the dashed-line frames corresponding to objects OB1 and OB2 are for the purpose of conveniently indicating the range of each object, and these frames do not need to be displayed on the actual display screen. This also applies to objects OB3 and OB4, described below, and to other figures such as Figure 16.

The display processing unit 114 performs processing to display object OB1 at a position on a map indicated by the location information included in the patient information of the at-home patient. For example, object OB1 includes a pin-shaped object, and the base of the object is set to a position corresponding to the location information of the at-home patient. In the example of Figure 5, object OB1 includes text indicating that the position indicated by the pin corresponds to the "home of elderly person A living alone."

Furthermore, object OB1 displays an object indicating the number of detected abnormalities (total number of abnormal values) as patient information for the home patient. In the example of Figure 5, object OB1 includes information indicating that one abnormal value has been detected (total number of abnormal values = 1) from the biometric information and environmental information of home patient Mr. A.

This makes it possible to clearly present the home patient's status along with the patient's location. Since it is assumed that there are no other patients in the home of the home patient, the information contained in object OB1 is only for the home patient in question.

The display processing unit 114 also performs processing to display object OB2 at a position on the map represented by the location information included in the patient information of multiple facility patients. For example, object OB2 includes an object representing a building, and this object is set at a position corresponding to the location information of the multiple facility patients. The location information of the multiple facility patients is information representing the location of the facility where the multiple facility patients reside, and corresponds to the "facility location information" in Figure 8B. In the example of Figure 5, object OB2 includes text indicating that the target facility is "facility A."

Object OB2 further displays an object indicating the total number of abnormal patients (total number of abnormal patients) as statistical information based on the patient information of multiple facility patients. In the example of Figure 5, object OB2 includes information indicating that abnormalities were detected in five patients at the facility in question. Object OB2 may also include, as statistical information, the total number of abnormal values (facility), which is the total number of detected abnormal values across the entire facility. In the example of Figure 5, object OB2 includes information indicating that eight abnormal values were detected at the facility in question.

Object OB2 may also include the total number of patients residing in the facility. In the example of Figure 5, object OB2 includes information indicating that five patients are residing in the facility.

As shown in Figure 13, when targeting a facility, by displaying different information than for patients at home, it is possible to display information appropriate for each target location in association with location information, even if the number of patients at the target location is expected to vary. This makes it possible to present information to managers and others in an easy-to-understand manner about where on the map the patients are and what kind of patients are present.

Furthermore, as shown in FIG. 13, the display processing unit 114 performs processing to display staff information on a map based on the staff's location information. In this way, in addition to information indicating the patient's location and condition, it is possible to display information about the staff working on that patient on the same map. The ability to clearly display the relative positions of the patient and staff makes it possible to appropriately support administrators in making decisions regarding staff dispatch, etc.

In the example of Figure 13, the display processing unit 114 performs processing to display object OB3 corresponding to staff member A and object OB4 corresponding to staff member B on the map information.

The display processing unit 114 performs processing to display object OB3 at a position on a map represented by the location information included in staff member A's staff information. For example, object OB3 includes an object representing a car, which is staff member A's means of transportation, and the position of this object is set to a position corresponding to staff member A's location information. The location information is updated sequentially using the GPS or the like of the staff member terminal device 310 carried by staff member A. Therefore, the display processing unit 114 may perform processing to update the position of object OB3 on the screen based on updated location information. Furthermore, if it is determined that a staff member is moving based on chronological location information, the display processing unit 114 may perform processing to display the direction of movement.

As shown in FIG. 13, object OB3 may also include task information for staff member A. The task information here is a planned route, which is information representing staff member A's work schedule. In the example of FIG. 13, staff member A is scheduled to perform work related to patient A, who corresponds to object OB1. Therefore, the display processing unit 114 displays object OB3 including the text "Planned route: Mr. A's home (distance 3.5 km)," which represents the task. Note that "distance 3.5 km" here is distance information calculated from the staff member's location information and Mr. A's location information, and may represent a straight-line distance or a distance along a travel route. When the distance along a travel route is used, for example, the determination processing unit 113 performs processing to calculate the distance information based on map information including road information.

Furthermore, when the priority score and visit priority are calculated as described above using formulas (1) and (2), the display processing unit 114 may perform processing to display the priority route as staff information. The priority route here refers to a route with a high visit priority. For example, in the above example, patient's home A is the closest in terms of distance, but facility A, which has a high value for the total number of abnormal values (facilities) and total number of abnormal individuals, has a high visit priority. Therefore, the display processing unit 114 performs processing to display the text "Recommended route: facility A (distance 5.0 km)" as the priority route in object OB3.

The display processing unit 114 also performs processing to display object OB4 at a position on the map represented by the location information included in staff member B's staff information. For example, object OB4 includes an object representing a car, which is staff member B's means of transportation, and the position of this object is set to a position corresponding to staff member B's location information.

In the example of Figure 13, the task information included in the staff information for staff member B indicates that staff member B has reached the task destination and is currently working at the destination. The destination here may be, for example, a patient's home or a facility, and may be a location represented by a pin-shaped object displayed near object OB4 in Figure 13. In this case, the display processing unit 114 displays the text "Currently working" as task information. To indicate that the destination has been reached, the display processing unit 114 may also display object OB4 including a checkered flag.

As mentioned above, the screen shown in FIG. 13 displays statistical information about multiple facility patients as facility-related information (object OB2). Using statistical information reduces the amount of information, making it possible to display a screen with high visibility. However, managers and staff may also want to know information about individual patients residing at the facility. Therefore, the display processing unit 114 may perform processing to individually display information about each of the multiple facility patients residing at the facility based on user operation.

Figure 14 is an example of a facility details screen that displays information about multiple facility patients. For example, the display processing unit 114 performs processing to transition to the facility details screen shown in Figure 14 when a selection operation for object OB2 is performed on the screen shown in Figure 13.

As shown in Figure 14, the facility details screen includes patient information for each of multiple facility patients residing at the facility. In the example of Figure 14, patient information for four facility patients, named AAA, BBB, CCC, and DDD, is displayed. Each piece of patient information includes objects OB5 to OB10 that represent, for example, sleep state information (OB5), heart rate information (OB6), breathing information (OB7), temperature information (OB8), humidity information (OB9), and the presence or absence of abnormalities (OB10).

For example, object OB5 has a circular frame when the target patient is asleep and an approximately rectangular frame when the target patient is awake. Object OB6 includes a heart-shaped object and a numerical value representing the number of heartbeats per minute. Object OB7 includes a lung-shaped object and a numerical value representing the number of respirations per minute. Object OB8 includes an object representing a thermometer and a numerical value representing the temperature. Object OB9 includes an object representing a hygrometer and a numerical value representing the humidity.

In the example of Figure 14, the temperature and humidity of patient AAA are higher than the normal range. Furthermore, patient CCC's heart rate and respiratory rate are higher than the normal range. Therefore, the patient information of patients AAA and CCC contains abnormal values. In this case, the display processing unit 114 displays the objects OB10 of patients AAA and CCC, who are patients in whom abnormal values have been detected, in a first mode, and displays the objects OB10 of patients BBB and DDD, who are patients in whom abnormal values have not been detected, in a second mode different from the first mode. The first and second modes may differ in color, size, or blinking, or in a combination of two or more of these, or in other elements. Furthermore, the display processing unit 114 may change the display mode depending on the patient, in addition to the presence or absence of abnormal values. For example, the display processing unit 114 may perform processing to display the object OB10 of a specific patient in the second mode (without issuing an alert notification) even if abnormal values have been detected. The specific patient here may be determined by an administrator or automatically based on attributes (such as medical history). In addition, the specific display format of the facility details screen can be modified in various ways.

By displaying the facility details screen, it becomes possible to properly present patient information for each of the multiple facility patients, which is omitted on the display screen using the map shown in Figure 13.

4. Modifications Several modifications will be described below.

4.1 Alert Notification In a community-based integrated care system, patients may move between their homes, facilities, hospitals, etc. on an irregular basis.

Figure 15 is a diagram showing a specific example of the information processing system 1 according to this embodiment. The difference from Figure 5 is that Patient B, who had been receiving care at home, has moved to an elderly housing complex, which is the facility where Patients C and D reside. In this case, Patient B is changed from a home patient to a facility patient.

For example, the server system 100 accepts a change operation indicating that patient B has moved from home to a senior citizens' housing complex. This change operation is executed, for example, by the management terminal device 400, but may also be executed by the patient terminal device 210 or the staff terminal device 310. The change operation may also be an operation to rewrite the location information of the patient information, which is text information. For example, if patient A's location information includes the address "bb, aa-ku, Tokyo, Japan" and the attribute "home," the administrator or staff member rewrites the location information to the address "dd, cc-ku, Tokyo, Japan" and the attribute "facility." In this way, the patient's location information is updated and the patient is changed from a home patient to a facility patient.

Alternatively, this operation may be performed using map information. Figure 16 is an example display screen for explaining another example of an operation interface related to patient movement. As with the example in Figure 13, the screen shown in Figure 16 displays an object OB1 related to patient A and an object OB2 related to the facility. For convenience of explanation, some of the information included in Figure 13 has been omitted.

Consider the case where patient A moves to a facility corresponding to object OB2. For example, the user performing the change operation (or, more narrowly, the administrator) may use pointer PT to drag and drop object OB1 related to patient A onto object OB2, which represents the destination. Based on this operation, the processing unit 410 of the management terminal device 400 determines that the patient corresponding to the object being operated on has moved to the location where the drop operation was performed. In the example of FIG. 16 , the processing unit 410 determines that patient A corresponding to object OB1 has moved to the facility corresponding to object OB2. Based on the received operation, the processing unit 410 sends a request to update the patient information to the server system 100. Note that the association between object OB1 and the patient, and the association between object OB2 and the location (e.g., address) and attributes (home/facility) can be established from existing patient information. This allows for intuitive operation on the screen to realize patient movement. As described above, managing patient movements in a community-based integrated care system can be cumbersome. However, making the change operation intuitive reduces the burden on users, such as administrators.

In this embodiment, the patient device 200 and the patient may be managed in association with each other. For example, the storage unit 120 of the server system 100 stores patient sensor information, which is information associating a patient with a sensor (including a device equipped with the sensor) that outputs the patient's biometric information and environmental information. For example, the patient sensor information may be table data that associates a patient ID that identifies the patient, a detection device ID that identifies the detection device 220, a thermometer ID that identifies the thermometer 230, and a hygrometer ID that identifies the hygrometer 240. Here, the detection device ID is, for example, the serial number of the target device, but other information that can uniquely identify the detection device 220 may also be used. The same applies to the thermometer ID and hygrometer ID. As described above, the patient device 200 can include various devices, and the patient sensor information may include an ID that identifies each of these devices. This makes it possible to appropriately manage which device is used for which patient.

In this case, as the patient moves, the patient device 200 used by that patient will also be moved. In the example of Figure 16, the patient device 200 used by patient A at home is moved to the elderly housing complex where patient A is moving. This makes it possible to appropriately measure patient information for patient A at his or her new location.

However, since the patient device 200 is moved by staff or other personnel, there is a possibility that the sensor (device) may be forgotten to be retrieved. If this occurs, the detection device 220 or other device will be located far away from the patient, making it impossible to measure appropriate patient information.

The server system 100 may therefore compare sensor position information indicating the sensor's position with the position information included in the patient information, and output alert information if the sensor position information differs from the position information by a predetermined amount. In this way, it is possible to notify an administrator or other person that the patient device 200 may have been forgotten to be collected, thereby encouraging collection.

For example, each device included in the patient device 200 measures sensor position information that indicates the location of that device. For example, each device included in the patient device 200 may be equipped with a GPS. Alternatively, each device included in the patient device 200 may measure sensor position information by communicating with a Wi-Fi base station or a mobile communication base station. Also, rather than all of the patient devices 200 detecting sensor position information, sensor position information may be detected by some of the devices. In this case, the decision to output alert information is made for the devices that measure sensor position information.

Figure 17 is a flowchart illustrating the alert information output process. First, in step S301, the notification processing unit 115 determines whether the patient has moved. The process of step S301 may be, for example, a process of determining whether the user operation described above with reference to Figure 16 has been accepted by the management terminal device 400, etc. More specifically, the notification processing unit 115 determines whether there has been a change in the location information in the patient information since the previous process was executed. If the patient has not moved (step S301: No), the process shown in Figure 17 ends.

If the patient has moved (step S301: Yes), in step S302, the notification processing unit 115 acquires sensor position information for each patient device 200 associated with the target patient.

In step S303, the notification processing unit 115 determines whether the sensor position information is appropriate. Specifically, the notification processing unit 115 acquires the post-movement position information of a patient who has moved, and determines whether the distance between the position information and the sensor position information is equal to or less than a predetermined threshold. If the distance is equal to or less than the predetermined threshold, the notification processing unit 115 determines that the sensor position information is appropriate.

If the sensor position information is inappropriate (step S303: No), there is a possibility that the sensor (patient device 200) has been forgotten to be collected. Therefore, in step S304, the notification processing unit 115 outputs alert information urging collection. This alert may be output by the management terminal device 400, or by the staff terminal device 310 of the staff member responsible for transporting the patient in question. The notification may be a text or image display, or may use light, sound, vibration, etc.

If the sensor position information is appropriate (step S303: Yes), the alert information is not notified and the processing shown in FIG. 17 ends.

Note that although the above describes an example in which location information is changed based on user operation, the processing of this embodiment is not limited to this. For example, as described above, the location information included in the patient information may be detected by the patient terminal device 210. For example, the notification processing unit 115 uses the location information detected by the patient terminal device 210 as a reference to determine whether the sensor location information of each of the other patient devices 200 is in a nearby location. In this case, if the patient terminal device 210 has been collected, it becomes possible to determine whether the other patient devices 200 have been forgotten to be collected.

Furthermore, the location information included in the patient information may be detected by a patient device 200 other than the patient terminal device 210. In this case, if the patient device 200 in question has been properly collected, it will be possible to determine whether other patient devices 200 have been forgotten to be collected.

4.2 Working Time The determination processing unit 113 may perform processing to calculate a first working time, which is the working time (time required for working or responding) when a staff member responds to a home-based patient, based on the patient information of the home-based patient and the location information of the staff member. The determination processing unit 113 may also perform processing to calculate a second working time, which is the working time when a staff member responds to a collective facility, based on the patient information of multiple facility-based patients and the location information of the staff member. The determination processing unit 113 may also perform processing to calculate both the first working time and the second working time.

The method of this embodiment makes it possible to estimate the time required for work (including travel). For example, by predicting the work time before the actual work begins, the subsequent work of the staff can be predicted, which can encourage managers to manage staff more efficiently. Furthermore, the server system 100 may select a location for staff to visit from multiple candidate locations based on the work time, or select a staff member to request a visit from multiple staff members. In this way, it is possible to appropriately support the manager's decisions.

Alternatively, after the work is actually performed, a process can be performed to compare the actual work time with the estimated standard work time required for that work. This makes it possible to determine compensation for the work (staff wages, fees charged to patients, etc.) and evaluate staff. Specific examples of processing related to work time are described below.

<Work time prediction>
First, an example of predicting the work time will be described with reference to the flowchart of FIG.

In step S401, the determination processing unit 113 estimates the content of the required work based on the patient information. For example, the determination processing unit 113 may identify the work content based on the item (sensor) in which an abnormal value was detected. Specifically, if patient information is acquired indicating that the respiratory rate and blood oxygen saturation of patient C, who is a home patient, are outside the normal range, the determination processing unit 113 determines that the work content is "responding to patient C's abnormal breathing."

In step S402, the judgment processing unit 113 acquires task statistics based on past history. Figure 19 shows information representing the history of tasks performed in the past, and is a timetable for multiple staff members. In the example of Figure 19, for example, staff members A to C each have experience responding to abnormal breathing in patient C. Using the information shown in Figure 19, the travel distance and travel time for each staff member when traveling to patient C's home, and the time required to respond to abnormal breathing after arriving at patient C's home, can be determined.

Figure 20 is a diagram extracting information related to the response to abnormal breathing for patient C from Figure 19. Staff member A took 1.5 hours to travel the 40.5 km to patient C's home, so his travel speed was 27 km/h. Staff member B took 1.25 hours to travel the 35.0 km to patient C's home, so his travel speed was 28 km/h. Staff member C took 1.25 hours to travel the 30.5 km to patient C's home, so his travel speed was 24.4 km/h. The determination processing unit 113 calculates statistics for the travel speed based on this information. For example, as shown in Figure 20, the average value of the travel speed is approximately 26 km/h, and the standard deviation is SD = 1.86.

Furthermore, it took staff member A 1.5 hours from start to finish responding to abnormal breathing at patient C's home. Staff member B took 1.25 hours from start to finish responding to abnormal breathing at patient C's home. Staff member C took 1.75 hours from start to finish responding to abnormal breathing at patient C's home. The judgment processing unit 113 calculates statistics for abnormal breathing responses based on this information. For example, as shown in Figure 20, an average value of 1.50 hours and a standard deviation SD = 0.25 are calculated as the statistics for abnormal breathing responses.

In step S403, the judgment processing unit 113 estimates the task time based on the task content and statistics. Here, the task content is responding to abnormal breathing of patient C, and the statistics calculated are the average and standard deviation of the travel speed to patient C's home and the average and standard deviation of the time required to respond to abnormal breathing after arrival.

For example, consider the case where staff member D is 2.5 km from patient C's home and is asked to respond to patient C's abnormal breathing. In this case, based on past history, it is estimated that staff member D can also travel to patient C's home at a speed of approximately 26 km/h. Therefore, the determination processing unit 113 estimates that the travel time will be approximately 6 minutes.

Furthermore, when considering a variability of, for example, approximately ±1 SD, the determination processing unit 113 estimates that the task of responding to abnormal breathing after arriving at patient C's home will be completed in approximately 1.5 ±0.25 hours. It is also possible to anticipate cases where the task will take longer; for example, the determination processing unit 113 may estimate the task time to be between 1 and 2 hours by calculating the 95% confidence interval as 1.5 ±2 x 0.25. Furthermore, the determination processing unit 113 may use the upper limit of the 95% confidence interval to determine that the task time, including travel time, is unlikely to be 2 hours and 6 minutes or more.

Figure 21 is an example of a screen displaying estimated work time, and is an example of a screen displayed, for example, on the display unit 440 of the management terminal device 400. In Figure 21, an object OB11 representing patient information corresponding to patient C and an object OB12 representing staff information corresponding to staff member D are displayed. The display content of object OB11 is the same as that of object OB1 in Figure 13, so a detailed description will be omitted.

Here, object OB12 for staff member D may include information about the predicted work time, as shown in Figure 21. In Figure 21, object OB12 includes text indicating that the predicted travel time is 6 minutes and the predicted response time is 1.0 to 2.0 hours (+/- 2SD), as in the example above. This allows the time required to be displayed in advance if staff member D is requested to perform the work, allowing the manager to more appropriately manage staff.

The object OB12 may also include an expected cost. For example, the storage unit 120 may store information that associates the work content with the cost incurred for the work per unit time (e.g., 1 hour). In this example, information indicating that the cost incurred per hour is 1,800 yen is associated with responding to abnormal breathing. In this case, the judgment processing unit 113 calculates the expected cost based on the expected response time and the cost per unit time. In this way, it becomes possible to present financial information in advance.

In the example of Figure 21, object OB12 displays the text "Request a response?" along with Yes and No buttons. The management terminal device 400 accepts the administrator's input of either button. For example, if the Yes button is selected, the communication unit 430 of the management terminal device 400 sends information (e.g., a message) to the staff terminal device 310 of staff member D requesting that staff member D respond to abnormal breathing in patient C. If the No button is selected, this indicates that the administrator has no intention of making a request to staff member D. In this case, for example, the display processing unit 114 performs processing to display, for example, the estimated work time, estimated cost, and a button indicating whether to make a request, on the staff information corresponding to staff members other than staff member D.

Figure 22 is another example of a screen displaying predicted work times. In Figure 22, objects OB1b to OB4b are displayed for Patient A, Facility A, Staff A, and Staff B, respectively. Detailed explanations of objects OB1b to OB4b that have the same information as objects OB1 to OB4 in Figure 13 will be omitted.

As described above using FIG. 13, in this example, abnormal values have been detected for both Patient A, who is a home patient, and a facility patient at Facility A, and Staff A, who is currently available, is recommended to head to Facility A based on visit priority. The determination processing unit 113 may, for example, calculate the predicted work time for each facility patient experiencing an abnormality at Facility A and add up the predicted work times to calculate the predicted work time for the entire target facility. The display processing unit 114 displays the predicted work time as staff information for Staff A. In the example of FIG. 22, object OB3b includes the same planned route and preferred route as object OB3, as well as information that the work time (predicted response time) of 1.0 hour will be if the preferred route is adopted.

Here, staff member B has arrived at the patient's home or facility, as in the example described above in Figure 13, and is currently performing some task (changing a diaper in the example in Figure 22). In this case, since an abnormality in patient A has already been detected, it is desirable for the administrator to plan whether to have staff member A head to patient A's home after completing their work at facility A, or to have staff member B, who is performing a different task, head to patient A's home after completing their current task.

As shown in FIG. 22, the display processing unit 114 may display the predicted completion time based on the predicted work time and actual work time in the object OB4b related to staff member B. For example, if the predicted work time for staff member B is predicted to be 1.0 hour and 30 minutes have passed since staff member B actually started working (traveling), the judgment processing unit 113 estimates the predicted completion time to be 30 minutes. The display processing unit 114 displays the estimated predicted completion time in the object OB4b related to staff member B.

In this way, it becomes clear that staff member B's work will be completed faster than staff member A's work at facility A, allowing the manager to make the decision that it would be more efficient to have staff member B go to patient A's home. In addition, the display screen of this embodiment displays staff member B's current location, the location where staff member A will be when they finish their work at facility A (the location of facility A), and other information, allowing the manager to make decisions that take into account factors such as travel time after completing the previous task.

The determination processing unit 113 may also perform processing to select and recommend staff suitable for performing the target task. For example, when the staff includes multiple staff members, the determination processing unit 113 performs processing to select from the multiple staff members the staff suitable for handling the patient by calculating at least one of the first task time required for the home patient task and the second task time required for the facility patient task for each of the multiple staff members. For example, the determination processing unit 113 may prompt the administrator to take action such as assigning the staff member with the shortest first task time to handle the target home patient and the staff member with the shortest second task time to handle the target facility. In the example of Figure 22, the display processing unit 114 displays recommended instructions in the lower right area of the screen to have staff member A handle facility A and staff member B handle patient A's home.

Furthermore, as shown in FIG. 22, the display processing unit 114 may display information such as tools and equipment required for the work as patient information. For example, the determination processing unit 113 estimates the items required for the work based on past history.

Figure 23 shows information representing the history of work performed in the past, and is a timetable for multiple staff members. For example, each staff member may use the staff terminal device 310 to input the items required for that work when or after performing the work. In the example of Figure 23, staff member A's past work has input information such as the need for small-size diapers to treat patient A's excretion and the need for a blood pressure monitor to treat patient B's abnormal heart rate, and information indicating this is stored in the memory unit 120 of the server system 100. The memory unit 120 of the server system 100 may store information that associates users, work content, and required items. Furthermore, while there is a large degree of individual variation in diapers among patients, there are cases where the required items can be standardized for treating abnormal breathing or abnormal heart rate regardless of the patient. In this case, the memory unit 120 may store information that associates work content with required items.

When an abnormal patient is detected, the determination processing unit 113 identifies the target patient and specifies the work content from the patient information. The determination processing unit 113 then identifies the necessary items based on past history, the patient, and the work content.

For patients at home, the display processing unit 114 displays the items needed for the patient in association with the patient information for that patient. For example, object OB1b includes information such as "one medium-sized diaper" as a needed item.

The display processing unit 114 also displays the necessary items for facility-specific patients, associating them with the facility. In the example of Figure 22, five abnormal patients have been detected at facility A, so the display processing unit 114 displays the total necessary items determined for each of the five abnormal patients, associating them with facility A. For example, object OB2b includes information on the necessary items: "One large diaper, two small diapers, three plastic bottles of water, and one blood pressure monitor."

This allows staff to work more efficiently because the items needed for the job are displayed in advance. For example, when staff visit a facility, etc., it is possible to prevent them from having to return to a dispatch station, etc., to retrieve items they need, thereby shortening work time. Furthermore, when a staff member is away from the dispatch station, the determination processing unit 113 may perform processing to determine recommended instructions based on information about the tools the staff member is carrying and information about the items they need. For example, even if a staff member is located close to the target facility, etc., the determination processing unit 113 may determine that it is not recommended to dispatch the staff member if they are not carrying the necessary items. Furthermore, the determination processing unit 113 may output information instructing the handover of tools between staff members.

<Wages, fees, and evaluations>
The determination processing unit 113 may also perform evaluation of the staff by comparing the predicted work time with the actual work time. For example, consider an example in which the travel time and work time of staff member D responding to abnormal breathing of patient C are estimated to be 6 minutes and 1.0 to 2.0 hours, respectively, by the process described above with reference to Figures 19 to 21.

Figure 24 shows an example of the work history of Staff D, who performed work including responding to abnormal breathing on Patient C. In the example in Figure 24, Staff D took over one hour to travel to Patient C's home, which is clearly longer than the predicted travel time of six minutes. Comparing travel speed, Staff D took 1.25 hours to travel 2.5 km, resulting in a travel speed of 2.0 km/h. This is clearly a small value when considering the average of approximately 26 km/h and standard deviation of 1.86 mentioned above in Figure 20. For example, 2.0 km/h is well below the lower limit of the 95% confidence interval (mean - 2SD). Furthermore, Staff D spent over four hours responding to abnormal breathing at Patient C's home, which is well above the upper limit of the 95% confidence interval of 2.0 hours. In this case, it is possible that Staff D was not working normally.

In such a case, even if staff member D requests wages for the work shown in Figure 24 (particularly responding to patient C's abnormal breathing), it would not be appropriate to pay the requested wages. Therefore, the judgment processing unit 113 may make a judgment on whether to approve or reject the wage claim based on the predicted work time and the actual work time.

Figure 25 is a flowchart explaining the wage approval process. In step S501, the determination processing unit 113 calculates the actual wage. For example, the determination processing unit 113 calculates the actual wage by multiplying the work hours by the unit price based on the work data such as Figure 24.

In step S502, the determination processing unit 113 determines whether the actual wage is within the predicted wage. For example, the determination processing unit 113 determines a predicted time range (e.g., a range of ±2SD) based on statistics of work time including travel time, and determines a predicted wage range from the predicted time range and unit price. The determination processing unit 113 then determines whether the wage calculated in step S501 is within the predicted wage range calculated in step S502.

If the actual wage is within the predicted wage range (step S502: Yes), in S505, the judgment processing unit S505 calculates the actual wage calculated in step S501 as the staff member's wage and terminates the process. In other words, the target work data is determined to be appropriate.

If the actual wage is not within the predicted wage range (step S502: No), the judgment processing unit 113 outputs a notification to the manager. For example, the display processing unit 114 performs processing to display a screen containing information such as the name of the staff member in question, work data, actual wage, predicted wage range, etc. on the display unit 440 of the management terminal device 400.

In step S504, the management terminal device 400 accepts the administrator's approval/rejection input based on the display screen. For example, the administrator may consider the attributes of the staff member in question, the task in question, the patient, etc., and determine whether there is a valid reason for the work time exceeding the normal range. For example, if the staff member is a new employee, it is unavoidable that the work will take longer than normal staff, and it may be appropriate to pay the requested wage. Furthermore, if there is congestion or a road closure on the main road leading to the patient's home, the travel time may exceed the expected range. Furthermore, if an irregular event occurs during the response to the abnormal breathing (for example, if the abnormal breathing is highly severe, or if another incident such as a fall occurs), it is reasonable for the time required to respond to the abnormal breathing to be longer. In this way, the notification to the administrator shown in step S503 is useful, as it allows the administrator to consider additional information before making an approval/rejection decision.

If the manager determines that there is a valid reason and performs an approval operation (step S504: Approve), in step S505 the determination processing unit S505 calculates the actual wage calculated in step S501 as the staff member's wage, and ends the process. If the manager determines that there is no valid reason and performs a rejection operation (step S504: Reject), the process ends without performing step S505. In other words, the work data in question is deemed inappropriate and is excluded from wage payment targets.

Depending on the services provided by the staff, the costs may not be covered by insurance and may have to be borne by the recipient. Furthermore, since the patient may be physically unable to pay the costs themselves, the patient's family may have to pay the out-of-pocket costs.

For example, the information processing system 1 of this embodiment may perform processing to bill family members for payment based on the service content and the patient's insurance status (nursing care insurance, medical insurance, uninsured, etc.).

Figure 26 is a diagram showing an example of the configuration of the information processing system 1 in this case. Note that only Patient A and Staff A in charge of Patient A are shown here, with other patients and staff omitted. The roles of the patient, staff, and administrator are the same as those in Figure 5. In the example of Figure 26, the administrator may understand the work performed for Patient A based on the work data described above, and calculate the copayment based on the work and the patient's insurance status. Note that the calculation does not have to be performed by the administrator himself, but may be performed automatically by the judgment processing unit 113. When the administrator performs a billing operation on the management terminal device 400 to bill the family for the copayment, this is transmitted to the server system 100, and the server system 100 then processes the billing notification to the family terminal device 500 used by the patient's family. If the server system 100 has a payment function, it may also perform the payment process for the billed expenses. The billing operation can also be automated, and the judgment processing unit 113 may automatically notify the family terminal device 500 without the administrator's operation.

This makes it possible to bill the appropriate party for expenses. As mentioned above, by determining whether each staff member's work is appropriate, it is possible to prevent inappropriate billing of patients and their families.

Furthermore, if the predicted work time indicates that the out-of-pocket expenses will be greater than a predetermined amount, the determination processing unit 113 may execute a process to inquire with the family about whether or not the staff member will be able to carry out the work before the work begins. This can prevent the family member from being billed for a large amount of money without prior notice.

The judgment results based on the predicted work time and actual work time may also be used to evaluate staff. Figure 27 is a flowchart explaining the staff evaluation process. The processing of steps S601-S607 in Figure 27 is generally similar to steps S501-S505 in Figure 25, with the only differences being that the value of a, which represents the approval flag, is set to 0 (step S602) after the actual wage calculation (step S601), and that if the wage based on the actual work is rejected by the manager (step S605: No), the value of a, which represents the approval flag, is set to 1 (step S607).

By processing steps S601-S607, if the wage is approved, a is maintained at 0, and if the wage is rejected, a is set to 1. In step S608, the judgment processing unit 113 performs staff evaluation based on the value of a, which represents the approval flag. Specifically, when a = 1, the judgment processing unit 113 performs processing to lower the staff evaluation compared to when a = 0. As mentioned above, wages are rejected when work hours are excessively long and there is no valid reason for this. Therefore, in this case, it is considered that the staff member did not perform the work appropriately, and by relatively lowering the evaluation, appropriate staff management is possible.

The determination processing unit 113 may also perform a process to determine the staff member to whom the work will be assigned based on the obtained staff evaluation. Figure 28 is a flowchart explaining the staff member determination process.

In step S701, the determination processing unit 113 detects that an abnormality has occurred in one of the patients. In step S702, the determination processing unit 113 calculates the priority of each home patient or facility. The priority is, for example, the priority score shown in equation (1) above. The processing of step S702 is as described above with reference to Figure 12. In step S702, the determination processing unit 113 may also calculate the visit priority shown in equation (2) above.

In step S703, the determination processing unit 113 determines a requested staff candidate, who is a candidate for staff to be requested to visit the abnormal patient. For example, the determination processing unit 113 selects the staff member with the highest visit priority as the requested staff candidate.

In step S704, it is determined whether the evaluation of the staff member selected as the requested staff candidate is above a predetermined threshold. The evaluation here is numerical data that increases or decreases, for example, through the process shown in Figure 27.

If the evaluation of the requested staff candidate is above the threshold (step S704: Yes), in step S705, the determination processing unit 113 determines the requested staff candidate as the staff member to be requested to perform the work. For example, the determination processing unit 113 transmits the determined staff member and the request details to the management terminal device 400 and the staff terminal device 310 used by the target staff member. In this way, work is automatically assigned to reliable staff members, reducing the burden on the manager.

On the other hand, if the evaluation of the requested staff candidate is below the threshold (step S704: No), in step S706, the judgment processing unit 113 notifies the administrator regarding staff selection. Specifically, the display processing unit 114 performs processing to display a screen containing information such as the patient with an abnormality, the abnormality details, the requested staff candidate, and the evaluation value of the requested staff candidate on the display unit 440 of the management terminal device 400.

The management terminal device 400 accepts staff selection input based on the display screen. For example, the administrator considers the requested staff candidate's attributes, work history, target task, patient, etc., and determines whether or not problems will arise if the requested staff candidate performs the target task.

If the administrator inputs a request to the requested staff candidate (step S707: Yes), the management terminal device 400 sends information indicating this to the server system 100. In step S708, the determination processing unit 113 executes processing to request the requested staff candidate to perform the work. For example, the determination processing unit 113 sends a work request to the staff terminal device 310 used by the target staff member.

On the other hand, if the administrator inputs an input indicating that the work will not be requested from the requested staff candidate (step S707: Yes), the management terminal device 400 sends information to that effect to the server system 100. In step S709, the determination processing unit 113 executes processing to request the work from a staff member other than the requested staff candidate. For example, if the administrator inputs an input specifying a replacement staff member, the determination processing unit 113 sends a work request to the staff terminal device 310 used by that staff member. Alternatively, the determination processing unit 113 may automatically determine a new requested staff candidate. In this case, the determination processing unit 113 may return to the processing of step S703 and perform an evaluation judgment again (step S704), and, if necessary, notify the administrator (step S706).

In the process shown in Figure 28, if a task is requested of a staff member with a low rating, approval from a manager is required, thereby preventing the task from being assigned to an inappropriate staff member.

4.3 Occupation of Staff As described above, the staff in this embodiment may include multiple staff members with different occupations. For example, the staff in this embodiment may include nursing staff (caregivers, care managers, etc.) who provide home care and medical staff (nurses, doctors) who provide home medical care. In this case, the tasks performed by the staff members may differ depending on their occupations.

Figure 29 is a diagram showing the scope of work performed by care staff. As shown in Figure 29, the scope of work performed by care staff includes toilet assistance, positioning assistance, meal assistance, bathing assistance, dressing assistance, and inquiries to medical professionals. Toilet assistance may be further subdivided into tasks such as guiding the patient to the toilet, changing diapers, and changing sheets. The same applies to other tasks such as positioning assistance.

The scope of work for care staff also includes the task of confirming the cause when an abnormal value is detected. For example, as described in the section titled "Judgment that there is no problem" in Figure 29, when abnormal values are detected in heart rate information, respiratory information, body movement, etc., the care staff's duties may include determining that no special action is necessary.

Figure 30 shows the scope of work for medical staff. Figure 30 shows specific examples divided into the scope of work for nurses and the scope of work for doctors. The scope of work for nurses includes "pain control" and "administration of sleeping pills," among others. Furthermore, "measurement of blood pressure, pulse, oxygen saturation, and breath sounds" can be performed in person or remotely. Furthermore, "ambulance response" refers to responding to highly urgent situations such as atrial fibrillation. Furthermore, "terminal care for terminal and end-of-life cancer patients" can be separated from other responses, for example, because breathing gradually becomes shallower and less frequent.

The scope of a doctor's duties may include "prescribing medication to a patient" and "suggesting an X-ray." Medication here includes various medications, such as sleeping pills and sedatives. "Suggesting an X-ray" may be performed, for example, when the impact on body movement, etc., is likely due to pain from a fracture. "Instructions to a visiting nurse" refers to having a nurse visit the patient's home and having the doctor give instructions remotely. "Remote listening to breath sounds" may be performed when the impact on body movement is likely due to respiratory disease or swallowing disorders. Similarly, "remote electrocardiogram testing" may be performed when the impact on body movement is likely due to heart disease. The scope of a doctor's duties may also include "preparing a death certificate." The method of this embodiment collects sensor information (e.g., breathing and heart rate measurements) before the time of death diagnosis, which can support a doctor's determination of the cause of death and create a database of breathing and other trends immediately before death. Databased information could be used, for example, to predict death during the end-of-life care period.

For example, the tasks performed by medical staff shown in Figure 30 may not be performed unless they have the corresponding qualifications. Specifically, care staff such as caregivers and care managers cannot perform the tasks shown in Figure 30. Therefore, when these tasks become necessary, the administrator must request that medical staff with the corresponding qualifications perform the tasks.

On the other hand, the tasks performed by care staff shown in Figure 29 could conceivably be performed by medical staff such as nurses and doctors. However, as mentioned above, there are tasks that can only be performed by medical staff, and these tasks must be performed as a priority. Since it may be inefficient to have medical staff perform the tasks shown in Figure 29, when these tasks become necessary, the administrator must request that care staff perform them as a priority.

As described above, efficient staff management is possible by taking into account the required work content and staff occupations in addition to the patient's condition and staff location. Therefore, the determination processing unit 113 may determine the work content, which is the content of the work, based on patient information. The determination processing unit 113 then performs processing to select a staff member from multiple staff members who is suitable for the patient's work based on the work content, occupation information indicating the occupations of each of the multiple staff members, and the work that can be performed for each occupation (job scope). In this way, it becomes possible to display recommendations that take into account the work content and staff occupations, making it possible to achieve more efficient staff management without increasing the burden on the administrator.

Here, the determination processing unit 113 may estimate the work required for the patient based on past history. Figure 31 shows information representing past work history, and is a timetable for multiple staff members. The example in Figure 31 shows nursing staff A and nursing staff B, who are nurses, and care staff C, who is a caregiver.

For example, nursing staff A has a history of measuring patient A's blood pressure after detecting an abnormal value on their blood pressure monitor. Similarly, nursing staff A has a history of responding to an abnormal heart rate after detecting an abnormal value on patient B's body movement sensor (pressure sensor). The same applies to nursing staff A's subsequent history, as well as the histories of care staff C and nursing staff B.

For example, the storage unit 120 of the server system 100 may store table data that associates patient IDs, items of biometric information or environmental information in which abnormal values were detected, and the work content that was performed. For example, when an abnormal value is detected for a certain patient, the determination processing unit 113 performs a search process in the table data using the patient ID that identifies the patient and the item in which the abnormal value was detected as a search key, and determines that the work content associated with the search key is necessary work content.

However, the process by which the determination processing unit 113 determines the required work content is not limited to this. For example, the determination processing unit 113 may perform processing using, in addition to the patient and the item in which the abnormal value was detected, the degree to which the abnormal value deviates from the normal range, or the time-series changes in values before and after the deviation from the normal range. Furthermore, the patient ID is not required, and the process of determining the required work content may be implemented as a process common to multiple patients. Furthermore, a trained model may be acquired by machine learning, using the patient ID, the item in which the abnormal value was detected, etc. as input data and the work content as output data. When an abnormal value is detected for a certain patient, the determination processing unit 113 determines the required work content by inputting the input data acquired for that patient into the trained model.

The determination processing unit 113 then performs processing to identify the occupation that should perform the required work content based on the required work content and the scope of work for each occupation. For example, the determination processing unit 113 compares the work content with the data shown in Figures 29 and 30 to determine whether the work should be performed by a caregiver, nurse, or doctor.

Next, the determination processing unit 113 performs a process to select staff to be requested to be dispatched, prioritizing dispatch of staff registered in the corresponding job category from among the staff candidates for dispatch.

Figure 32 is an example of a screen that displays processing results that take occupational type into consideration. In Figure 32, the display unit 440 of the management terminal device 400 displays objects OB1c and OB1c related to patient A and facility A, respectively. Here, the objects related to the patient or facility may include, in addition to the information shown in Figure 22, information related to the required work content and the occupation in which the work should be performed.

For example, object OB1c indicates that the required task is changing diapers and that the task should be performed by a care worker (nursing staff). The determination processing unit 113 may determine the number of staff required in addition to the job type of staff who should perform the task. For example, the determination processing unit 113 may set the number of staff to two or more when there is a task that can only be performed by multiple staff members working together (such as assisting a large patient with movement), or when there are so many tasks that it would take a predetermined amount of time for one person to complete all of the tasks. In the example of Figure 32, object OB1c indicates that the number of nursing staff required is one.

Similarly, object OB2c, which corresponds to facility A where multiple facility patients reside, indicates that the required tasks are changing diapers, turning on the air conditioner, and measuring blood pressure, and that of these tasks, changing diapers and turning on the air conditioner should be performed by care staff, while measuring blood pressure should be performed by nursing staff (nurses among medical staff). Note that changing diapers in this case may include the task of changing diapers for multiple people. Object OB2c also indicates that the number of required care staff members is one, and the number of required medical staff members is one.

In FIG. 32, the display unit 440 displays objects OB13 and OB14 relating to a medical staff member who is a nurse (nursing staff member A) and care staff member B, respectively. Here, the display objects relating to the staff may include information on the work content estimated to be required as task information. For example, object OB13 corresponding to nursing staff member A includes information that the work content estimated to be required at facility A is blood pressure measurement. Furthermore, the display objects relating to the staff may include information on items required to perform the estimated work content. For example, object OB13 includes information that a sphygmomanometer is required to measure blood pressure.

Display objects related to staff members may also include information about the staff member's occupation. For example, object OB14 includes the text "nursing staff" and an icon representing a nurse. Object OB14 also includes the text "care staff" and an icon representing a caregiver. This allows the manager to easily determine the occupation of each staff member, and when the required work content and occupation are displayed (objects OB1c, OB2c), the manager can easily select the staff member to be dispatched from the screen shown in Figure 32. Note that the information representing the occupation is not limited to the icons shown in Figure 32, and various modifications are possible. Furthermore, as shown in the lower right of the screen, the display processing unit 114 may perform processing to display recommended instructions indicating the work content that is recommended for each staff member to perform.

In the above example, it is assumed that each staff member travels by car, and an example has been described in which the objects corresponding to the staff members (e.g., OB13, OB14) include a car icon. However, the means of transportation for staff members is not limited to cars, and various variations are possible, such as bicycles or walking. In this case, the travel time to the target location varies depending on the means of transportation. Therefore, when displaying staff information on a map, the display processing unit 114 may display different information depending on the means of transportation. For example, an object containing staff information may include any of a first icon representing a car, a second icon representing a bicycle, or a third icon representing walking. In this way, the administrator can manage staff members taking into account their means of transportation.

The determination processing unit 113 may also perform processing using the means of transportation when estimating the travel time required for a staff member to travel to a target location. For example, as described above with reference to Figures 19 and 20, when calculating statistical values (average value, standard deviation) of travel time based on past history information, the determination processing unit 113 may calculate statistical values for each means of transportation. Furthermore, when estimating travel time, the determination processing unit 113 reads out statistical values corresponding to the target staff member's means of transportation and estimates travel time based on these statistical values. In this way, appropriate travel time estimation is possible even if the means of transportation differs depending on the staff member. As a result, managers can manage staff appropriately.

4.4 Reducing Unnecessary Visits Since visiting services involve travel time (for example, travel time from the staff waiting base to the patient's home or facility), it is possible to reduce staff work hours by reducing unnecessary visits. This makes it possible to properly manage staff work. Situations in which a visit is less necessary, for example, could be when environmental information such as temperature and humidity indicates abnormal values but the patient is not in the room. Also, even if there are abnormalities in respiratory and cardiac rhythm, there is less need to visit if the patient has just engaged in some kind of exercise.

Therefore, in this embodiment, a process may be executed to determine whether a visit is necessary. For example, the patient device 200 includes an imaging device for capturing images of the patient. Here, the imaging device may be a camera included in the patient terminal device 210, or may be a device separate from the patient terminal device 210. Images captured by the imaging device are sent to the management terminal device 400, where they can be viewed by the administrator. For example, the imaging device may send the captured images to the server system 100, and the server system 100 may then send the captured images to the management terminal device 400. This allows the administrator to check the condition of the resident using the captured images.

Figure 33 is a flowchart explaining the processing of the server system 100. First, in step S801, the determination processing unit 113 determines whether a sensor has an abnormal value and issues an alert notification. The abnormal value determination process may be similar to the processing shown in steps S201-S205 of Figure 12, for example.

Figure 34 is an example of a screen on which an alert notification is displayed, for example, on the display unit 440 of the management terminal device 400. The left side of the screen shown in Figure 34 is similar to, for example, Figure 13, so a detailed description will be omitted. The display processing unit 114 displays the alert notification on, for example, the right side of the screen shown in Figure 34.

As shown in Figure 34, the alert notification here includes information about the facility name, room number, patient name, details of the abnormality, and the timing of the abnormality. This makes it possible to notify the administrator of information about the abnormal patient. The alert notification may also include a patient status confirmation icon and an object for inputting whether or not a visit is required. The patient status confirmation icon is, for example, the icon representing a camera shown in Figure 34, but other icons may also be used. The object for inputting whether or not a visit is required is, for example, a required button and an unrequired button, but other types of objects may also be used.

33 , the determination processing unit 113 sets the value of the visit flag v, which indicates whether a visit is required, to 1 for all patients for whom an abnormality has occurred. v = 1 indicates that a visit is required, and v = 0 indicates that a visit is not required. Next, in step S803, the captured image is output. Specifically, the display processing unit 114 first displays a screen containing the alert notification shown in FIG. 34 , and when a patient status check icon is selected on the screen, performs processing to display a captured image of the target patient on the display unit 440 of the management terminal device 400. For example, when a patient status check icon is selected, the server system 100 may turn on an imaging device located near the target patient and then acquire an image of the patient from the imaging device. Alternatively, the imaging device may be always on, and the server system 100 may start acquiring images from the imaging device when a patient status check icon is selected.

The administrator views the captured images to determine whether a visit is necessary and enters the results of the determination. For example, as described above, even if environmental abnormalities such as temperature or humidity are detected, if the images confirm that the patient is not in the sensor location (e.g., bedroom), the need for a visit is low. Alternatively, even if abnormalities such as heart rate are detected, if the images confirm that the patient is exercising or watching an exciting television program, the need for a visit is low. Furthermore, even if the patient has already finished exercising, if the images confirm that the patient appears healthy (e.g., conscious), the need for a visit is low. The administrator may also use the imaging device to have a video call with the patient. In this case, the administrator can determine whether a visit is necessary based not only on the images but also on the content of the conversation with the patient. The management terminal device 400 accepts the selection of either the "Necessary" button or the "Not Necessary" button on the screen shown in FIG. 34 and sends the result of the selection to the server system 100.

In step S804, the determination processing unit 113 determines whether a visit is necessary for the target patient. Specifically, if the administrator selects the "Necessary" button, the determination processing unit 113 determines that a visit is necessary, and if the administrator selects the "Not Necessary" button, the determination processing unit 113 determines that a visit is unnecessary. If a visit is necessary, in step S805, the determination processing unit 113 maintains the value of v, which represents the visit flag, at 1. If a visit is not necessary, in step S806, the determination processing unit 113 changes the value of v, which represents the visit flag, to 0.

In step S807, the determination processing unit 113 determines the patient's visit flag. If the value of v, which represents the visit flag, is 1 (step S807: Yes), the determination processing unit 113 selects the target patient as a target for calculating the priority (priority score, visit priority). Specifically, in step S808, the determination processing unit 113 performs processing similar to steps S206-S207 in FIG. 12 using the target patient's information. On the other hand, if the value of v, which represents the visit flag, is 0 (step S807: No), the determination processing unit 113 excludes the target patient from the target for calculating the priority (priority score). In this way, patients with a low need for a visit can be excluded from the targets for the processing shown in steps S206-S207 in FIG. 12.

As described above, by using images to prompt the administrator to input whether or not a visit is necessary, if a patient's sensor abnormality is detected, the administrator can immediately check the patient's condition and have the results of the check reflected in the system. As a result, it is possible to reduce unnecessary visits by staff.

In the above, we have explained an example in which the administrator views the images and determines whether a visit is necessary, but this is not limited to this. For example, images of the patient may be displayed on the display unit 314 of the staff terminal device 310, and the staff may determine whether a visit is necessary.

The display screen for alert notifications is not limited to that shown in Figure 34; for example, information about multiple patients may be displayed in a list. Figure 35 is an example of a display when an alert notification is made using a list. As shown in Figure 35, the display processing unit 114 performs processing to display a list including information such as the patient's name, affiliation (home or facility type, etc.), sleep/wake or in/out of bed status, heart rate, respiratory rate, and temperature. The display processing unit 114 may also perform alert notifications by displaying an object containing an exclamation mark (!") for items in which abnormal values have been detected. In this way, the specific items in which abnormalities have been detected can be presented in an easy-to-understand manner.

The display processing unit 114 may also perform processing to display a patient status confirmation icon associated with each patient, as shown in FIG. 35. When a patient status confirmation icon is selected, processing to display an image of the corresponding patient is performed, similar to the example described above using FIG. 34. In this case, too, it is possible to appropriately support managers and others in determining whether or not a visit is necessary. Note that although not shown in FIG. 35, the list shown in FIG. 35 may include a column displaying information indicating the result of the determination of whether or not a response (visit) is necessary.

The display processing unit 114 may also display a list based on priority (priority score or visit priority). For example, the display processing unit 114 performs processing to display an alert notification including a list sorted in descending order of priority on the display unit 314 of the staff terminal device 310. In other words, the display processing unit 114 may display a list of destinations that staff should visit based on priority. By displaying the list, if staff are unable to visit for some reason, it becomes possible to encourage flexible responses from staff, such as visiting the destination with the next highest priority.

For example, the display processing unit 114 can display a list sorted in the order of patient A, patient B, patient C, and patient D, thereby clearly indicating that the visit priority is highest in that order. Alert notifications may be issued on a patient-by-patient basis, or on a facility or patient home basis. By issuing alert notifications using priority, staff can check patient status in order of priority, thereby improving work efficiency. For example, the display processing unit 114 creates a list of patients for whom staff member A has been selected as the visiting person, sorted in order of visiting priority, and displays this list on staff member A's staff terminal device 310. However, the display processing unit 114 may also display on staff member A's staff terminal device 310 a list that includes patients for whom a visiting person has not yet been assigned, or patients for whom another staff member B has been selected as the visiting person. This is because these patients may also be taken care of by staff member A depending on the work situation.

The list here may be, as described above, a list of which patients a specific staff member should visit (for example, information displaying a list of patients that staff member A should visit as a priority), but is not limited to this. For example, the list may be a list displaying which patients require attention for an administrator. For example, the display processing unit 114 may create a list of all patients who need to be visited, sorted in order of visit priority, and display this list on the display unit 440 of the management terminal device 400. In this way, it is possible to encourage the administrator to prioritize patients with high visit priority (for example, by assigning visiting staff).

While the present embodiment has been described in detail above, those skilled in the art will readily understand that many modifications are possible that do not substantially depart from the novel features and advantages of the present embodiment. Therefore, all such modifications are intended to be within the scope of the present disclosure. For example, a term that appears at least once in the specification or drawings together with a different term with a broader or equivalent meaning may be replaced with that different term anywhere in the specification or drawings. Furthermore, all combinations of the present embodiment and modifications are also within the scope of the present disclosure. Furthermore, the configurations and operations of the server system, patient devices, staff devices, management terminal devices, etc. are not limited to those described in the present embodiment, and various modifications are possible.

1...information processing system, 10...patient information measurement system, 11...patient information acquisition unit, 12...display processing unit, 100...server system, 110...processing unit, 111...patient information acquisition unit, 112...staff information acquisition unit, 113...determination processing unit, 114...display processing unit, 115...alert processing unit, 120...storage unit, 130...communication unit, 200...patient device, 210...patient terminal device, 211...processing unit, 212...storage unit, 213...communication unit, 214...display unit, 215...operation unit, 216...imaging unit, 220... Detection device, 230...thermometer, 240...hygrometer, 300...staff device, 310...staff terminal device, 311...processing unit, 312...storage unit, 313...communication unit, 314...display unit, 315...operation unit, 316...imaging unit, 400...management terminal device, 410...processing unit, 420...storage unit, 430...communication unit, 440...display unit, 450...operation unit, 500...family terminal device, 610...bed, 620...mattress, OB1-OB14, OB1b-OB4b, OB1c-OB2c...objects

Claims (11)

a patient information acquisition unit that acquires patient information including location information of patients, including home patients in community-based integrated care and multiple facility patients residing in facilities;
a display processing unit that performs processing to display the patient information of the home-based patient on a map based on the location information of the home-based patient, and to display statistical information regarding the patient information of the plurality of facility-based patients on the map based on the location information of the plurality of facility-based patients;
a determination processing unit that determines priorities of the home patient and the facility based on the patient information of the home patient and the patient information of the plurality of facility patients;
Includes patient information measurement system. In claim 1 ,
The determination processing unit
A patient information measurement system that determines the priority of the home patient and the priority of the facility based on the number of abnormalities, which represents the number of items in the patient information in which abnormalities have occurred, and the number of abnormalities, which is the number of people in which abnormalities have occurred. In claim 1 ,
a staff information acquisition unit that acquires staff information including location information of staff performing work related to at least some of the home patients and the plurality of facility patients;
The determination processing unit
A patient information measurement system that determines a recommended visiting route for the staff member based on the priority of the at-home patient, the priority of the facility, and the location information of the staff member. In claim 1,
a staff information acquisition unit that acquires staff information including location information of staff performing work related to at least some of the home patients and the plurality of facility patients;
The display processing unit
A patient information measurement system that performs processing to display the staff information on the map based on the position information of the staff. In claim 4 ,
A patient information measurement system including a judgment processing unit that performs at least one of the following processes: a process for calculating a first working time, which is the working time when the staff responds to the patient at home, based on the patient information of the patient at home and the location information of the staff; and a process for calculating a second working time, which is the working time when the staff responds to the facility, based on the patient information of the multiple facility patients and the location information of the staff. In claim 5 ,
The determination processing unit
A patient information measurement system that, when the staff includes multiple staff members, performs a process of selecting the staff member from the multiple staff members who is most suitable for treating the patient by calculating at least one of the first working time and the second working time for each of the multiple staff members. In claim 6 ,
The determination processing unit
determining work content, which is content of work related to the patient, based on the patient information;
A patient information measurement system that performs a process of selecting a staff member from the plurality of staff members who is most suitable for treating the patient based on the work content, job type information representing the job type of each of the plurality of staff members, and the tasks that can be performed for each job type. In any one of claims 1 to 7 ,
a storage unit that stores patient sensor information that associates the patient with a sensor that outputs biological information or environmental information of the patient;
A patient information measurement system including an alarm processing unit that performs a comparison process between sensor position information representing the position of the sensor and the position information included in the patient information, and outputs alert information if the sensor position information and the position information differ by a predetermined amount or more. In any one of claims 1 to 7 ,
The patient information includes:
A patient information measurement system including at least one of sleep state information, breathing information, heart rate information, and excretion information acquired based on the patient's body movements. In claim 9 ,
The patient information includes:
A patient information measurement system including at least one of temperature information, humidity information, heat index, illuminance information, and carbon dioxide information obtained based on environmental sensors arranged around the patient. The computer
Acquire patient information including location information of patients, including home patients in community-based comprehensive care and multiple facility patients residing in facilities;
displaying the patient information of the at-home patient on a map based on the location information of the at-home patient;
displaying statistical information regarding the patient information of the plurality of facility patients on the map based on the location information of the plurality of facility patients;
determining priorities of the home patient and the facility based on the patient information of the home patient and the patient information of the plurality of facility patients;
Patient information measurement methods.