Information processing system and information processing method

Abstract

Providing information processing systems and methods suitable for patient care. [Solution] The information processing system includes a processing unit that performs automatic work schedule creation processing and a storage unit that stores the work schedule. The processing unit determines which of several team attributes a work team consisting of multiple staff members that are determined to be working simultaneously during a given time period by the automatic creation processing has, and based on the team attributes, performs setting processing to set the execution conditions for patient notification processing during the work team's shift. If it determines that the frequency of notification processing is above a given threshold, it causes the display unit to display at least one of a first display prompting correction of the work schedule or a second display prompting correction of the execution conditions.

Description

Technical Field

[0001] The present invention relates to an information processing system, an information processing method, and the like.

Background Art

[0002] Conventionally, a method for obtaining information about patients has been known. For example, Patent Document 1 discloses a method for automatically evaluating the risk of hospital-acquired conditions (HACs).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] To provide an information processing system, an information processing method, and the like suitable for the care of patients and the like.

Means for Solving the Problems

[0005] One aspect of this disclosure relates to an information processing system that includes a processing unit for automatically creating a work schedule at a facility that provides patient care, based on conditions including at least one of a first condition regarding the number of staff working in each work period, a second condition based on prohibited shifts, and a third condition regarding combinations of staff; and a storage unit for storing the work schedule. The processing unit determines, based on information relating staff and skill levels, which of a plurality of team attributes the work team has, including a first team attribute that includes staff with a skill level below a predetermined level, and a second team attribute that does not include staff with a skill level below a predetermined level. Based on the team attributes, the processing unit performs a setting process to set execution conditions for notification processing regarding the patient during the work period of the work team. If it determines that the frequency of the notification processing is above a given threshold, the processing unit causes a display unit to display at least one of a first display prompting modification of the work schedule or a second display prompting modification of the execution conditions.

[0006] Other aspects of this disclosure relate to an information processing method in which an information processing system performs an automatic creation process of a work schedule for a facility that provides patient care based on conditions including at least one of a first condition regarding the number of staff working for each work period, a second condition based on prohibited shifts, and a third condition regarding combinations of staff; for a work team consisting of multiple staff members determined to be working simultaneously during a given time period by the automatic creation process, the system determines, based on information relating staff to their skill levels, which of a plurality of team attributes it has, including a first team attribute that includes staff members with a skill level below a predetermined level and a second team attribute that does not include staff members with a skill level below a predetermined level; based on the team attributes, the system performs a setting process to set execution conditions for notification processing regarding the patient during the work period of the work team; and if it is determined that the frequency of occurrence of the notification processing is above a given threshold, the system causes the display unit to display at least one of a first display prompting correction of the work schedule or a second display prompting correction of the execution conditions. [Brief explanation of the drawing]

[0007] [Figure 1] This diagram explains the background of this disclosure. [Figure 2] This is a diagram illustrating an example of the configuration of an information processing system. [Figure 3] This is a diagram illustrating an example of a bed configuration. [Figure 4] This diagram illustrates an example configuration of a bedside terminal device. [Figure 5] This diagram illustrates an example of a server system configuration. [Figure 6] This diagram illustrates an example of a terminal device configuration. [Figure 7A] This is a flowchart explaining the process for automatically creating work schedules. [Figure 7B] This is a flowchart explaining the process of updating work schedules. [Figure 8] This is a flowchart explaining the process of automatically generating work schedules. [Figure 9] This diagram shows an example of staff information. [Figure 10] This figure shows an example of a work schedule. [Figure 11] The following is an example of a work assignment schedule. [Figure 12] This diagram illustrates the process of updating work schedules. [Figure 13] This diagram shows an example of the correspondence between team attributes and notification settings for each notification process. [Figure 14A] This diagram shows an example of data that correlates medical departments with risk sets. [Figure 14B] This diagram shows an example of a risk set. [Figure 14C] This figure shows an example of data that correlates risk, sensors, and algorithms. [Figure 15] This is a sequence diagram illustrating the process of presenting risk-related information. [Figure 16] This figure shows an example of a screen displaying the results of a risk assessment. [Figure 17A] This figure shows an example of data that links medical departments with prescription sets. [Figure 17B] This is a diagram showing an example of an instruction set. [Figure 17C] This is a diagram showing an example of data associating instructions, sensors, and algorithms. [Figure 18A] This is a diagram showing an example of a screen for displaying the content of an instruction from a doctor. [Figure 18B] This is a diagram showing an example of a screen for displaying the determination result of an instruction. [Figure 19A] This is a diagram showing an example of a screen displayed on a terminal device when a nurse call is notified. [Figure 19B] This is a diagram showing an example of a screen displayed on a terminal device when responding to a nurse call. [Figure 19C] This is a diagram showing an example of a screen for displaying measures (countermeasures) against a nurse call. [Figure 20] This is a diagram showing an example of a patient screen. [Figure 21] This is a diagram showing an example of a patient screen. [Figure 22] This is a diagram showing an example of a patient screen. [Figure 23] This is a diagram showing an example of a patient screen. [Figure 24] This is a diagram showing an example of a patient screen. [Figure 25] This is a diagram showing an example of a patient screen. [Figure 26A] This is a flowchart for explaining a learning process. [Figure 26B] This is a flowchart for explaining an inference process using a learned model. [Figure 27A] This is an example of a display screen of a workload survey application. [Figure 27B] This is an example of a display screen of a workload survey application. [Figure 28] This is an example of a report screen showing the results of a workload survey.

Embodiments for Carrying Out the Invention

[0008] This embodiment will be described below with reference to the drawings. In the drawings, the same or equivalent elements are denoted by the same reference numerals, and redundant descriptions are omitted. This embodiment described below is not intended to unduly limit the content described in the claims. Furthermore, not all of the configurations described in this embodiment are essential components of this disclosure.

[0009] 1. Background Figure 1 is a diagram illustrating the background of the invention relating to this disclosure, and illustrates the work environment of a nurse working in a hospital or the like. As shown in Figure 1, devices for sensing the patient's condition, such as an imaging device 700 and a detection device 810, are placed near the patient's bed 100. The nurse determines the patient's condition by acquiring sensing data obtained by these devices. For example, the nurse may view the sensing data displayed on the display unit 240 of the bedside terminal device 200, or she may view the sensing data using a terminal device 600 that she carries with her (details will be described later with reference to Figure 2). Also, if it is determined that the patient's condition has suddenly changed based on the sensing data, the nurse may receive a notification to that effect.

[0010] Patients may also use a nurse call system to summon a nurse. For example, the bedside terminal device 200 may have a function to execute a nurse call, or a separate nurse call device with buttons, a microphone, a speaker, etc., may be placed near the bed 100.

[0011] As shown in Figure 1, nurses receive instructions from physicians. These instructions specify actions that nurses must follow in order to provide appropriate treatment to patients, such as "imposing dietary restrictions on the patient" or "administering specific medications to the patient." The term "physician" here may include both physicians from the department to which the nurse belongs (hereinafter also referred to as the "affiliated department") and physicians from other departments, as shown in Figure 1. Physicians from other departments may be physicians from different departments within the same hospital as the nurse, or physicians from different hospitals.

[0012] Instructions from a physician may be communicated verbally or in writing by the physician or other nurses during handover or other means. Alternatively, data representing the physician's instructions may be registered in the electronic medical record, and nurses may access the electronic medical record using devices such as bedside terminals 200 or terminals 600 to obtain the physician's instructions.

[0013] Furthermore, as shown in Figure 1, nurses can provide more appropriate care by utilizing the tacit knowledge of highly skilled nurses or by delegating some of their tasks to staff from other professions such as occupational therapists and physical therapists.

[0014] It should be noted that methods for digitizing the tacit knowledge of experienced nurses are already known, and similar methods may be applied to the sharing of tacit knowledge in this embodiment. Digitization here may involve, for example, creating training data that represents the tacit knowledge of experienced nurses using digital data, or creating application software (hereinafter simply referred to as "application") that allows users to perform care according to the training data. By using such an application, it becomes possible for less experienced nurses to perform the same actions as experienced nurses.

[0015] As described above, nurses must comply with physicians' instructions and take appropriate action when changes in a patient's condition are observed based on sensing data, or when a nurse call is made. To achieve this, nurses are required to clearly understand the physician's instructions, know how to respond appropriately to sudden changes in a patient's condition, and appropriately understand the patient's wishes when a nurse call is made. However, some of this information is not easy for nurses to grasp, making it difficult for them to take appropriate action.

[0016] While the above explanation focused on nurses, the difficulty in obtaining information about other healthcare professionals, such as caregivers, is also true. Furthermore, facilities where information that is difficult for healthcare professionals to grasp may arise are not limited to hospitals; the same applies to other facilities such as nursing homes. Hereafter, healthcare professionals will also be referred to as staff. The various facilities where staff work will also be referred to as medical facilities.

[0017] Information that may be difficult for staff to grasp includes instructions (patient behavior and changes in instructions), risks (sudden deterioration of the patient's condition), and the patient's wishes.

[0018] For example, if a patient has multiple illnesses, the doctor's instructions regarding the patient may include instructions related to the staff's department and instructions related to other departments. For instance, if a patient being treated for diabetes develops a severe condition and is hospitalized in the ophthalmology department due to cataracts, the ophthalmology staff will receive instructions regarding cataracts from their ophthalmologist and instructions regarding diabetes from an internist, and will monitor the patient's behavior to ensure compliance with both sets of instructions. In this example, the ophthalmology nurse needs to monitor the patient's behavior based on the instructions regarding dietary and fluid restrictions for diabetes. However, ophthalmology staff are often unfamiliar with caring for diabetic patients, making it difficult for them to understand how to comply with the instructions (how to monitor the patient's behavior).

[0019] Furthermore, in the acute phase, when a patient's condition is likely to change rapidly, physicians' instructions may change suddenly. In this case, regardless of the medical department, it is not easy for staff to grasp the changes in physicians' instructions. For example, staff check the latest instructions when handover takes place, but if the instructions change after that handover, it is not easy for staff to grasp the change. It is assumed that the changed instructions will be registered in the electronic medical record, but for staff to grasp these instructions, they would need to proactively check the details of the electronic medical record, and considering the workload, it is difficult to force staff to do such a check.

[0020] Furthermore, patient risks (which may specifically include risks related to changes in condition, and which will also be referred to as sudden changes in patient condition hereafter) can be detected using sensing data, etc., as described above, and by having staff take appropriate measures according to the risks, it becomes possible to suppress the worsening of the patient's condition. However, as can be seen from the examples of internal medicine and ophthalmology above, staff may have difficulty understanding risks that they do not frequently encounter in their respective departments, and therefore may also have difficulty understanding countermeasures. For example, if a patient with asthma is hospitalized in ophthalmology, the ophthalmology staff can understand the patient's asthma using electronic medical records, but even if they detect symptoms such as coughing, they may not immediately connect the detection result with asthma. This difficulty in linking symptoms and risks (such as asthma) is particularly pronounced at night or when staff who are not assigned to the patient are responding. This is because the staff do not necessarily have the information necessary to interpret what the patient's behavior means.

[0021] Furthermore, when a patient uses the nurse call system, the patient's requests can be diverse, making it difficult to understand the patient's needs (or understand their wishes) solely from the nurse call system. For example, even if a patient complains of a headache via the nurse call system, staff may not be able to identify the underlying illness or determine the necessary response. This is particularly noticeable when the patient has multiple illnesses, as in the example above.

[0022] Therefore, the information processing system 10 according to this embodiment enables staff to easily recognize information that is difficult to grasp. Specifically, the information processing system 10 automatically activates sensors and performs automatic monitoring to automatically monitor "patient behavior that is difficult to grasp" in relation to physician's instructions. The information processing system 10 also automatically evaluates "sudden changes in the patient's condition that are difficult to grasp" in relation to risks and notifies the nurse of the evaluation results. Furthermore, the information processing system 10 automatically interprets "patient intentions that are difficult to grasp" in relation to patient intentions (nurse calls) and notifies the staff of the interpretation results.

[0023] Furthermore, the information processing system 10 may utilize the above-mentioned information that is difficult to grasp for various processes in the medical facility. For example, when the information processing system 10 creates work schedules (shift schedules) for multiple staff members working at the medical facility, it may utilize information that is difficult for staff members to grasp. Specifically, when notifications regarding "patient behavior," "risk," and "patient wishes" are issued, the information processing system 10 may perform display processing to prompt the revision of the work schedule or the revision of notification settings so that the notification frequency estimated from the work schedule falls within an appropriate range.

[0024] The following will first describe the configuration examples of the information processing system 10 and the devices included in the information processing system 10. Then, the processing flow of this embodiment, including the process of creating work schedules that take into account information that is difficult for staff to grasp, will be explained. Furthermore, in relation to work management in medical facilities, time studies will also be explained.

[0025] 2. Example System Configuration Figure 2 is a diagram illustrating an example configuration of the information processing system 10 according to this embodiment. The information processing system 10 includes a bed 100, a bedside terminal device 200, a server system 300, an electronic medical record server 400, a station terminal device 500, and a terminal device 600 (portable terminal device). The information processing system 10 may also include an imaging device 700, a detection device 810, a measuring device 820, an authentication card 830, etc. However, the configuration of the information processing system 10 is not limited to the example in Figure 2, and various modifications can be made, such as omitting some components or adding other components. For example, the information processing system 10 according to this embodiment corresponds to the server system 300 in Figure 2, and the other components may be external devices directly or indirectly connected to the information processing system 10 of this embodiment. Furthermore, the information processing system 10 according to this embodiment may be realized by distributed processing of two or more of the devices shown in Figure 2. Also, the bedside terminal device 200 may be omitted from the configuration shown in Figure 2. For example, some or all of the processing performed by the bedside terminal device 200 described below may be performed by other devices such as the terminal device 600. Furthermore, modifications such as omitting or adding components to the configuration are possible, as is also the case with Figure 3 and other diagrams described later.

[0026] The bed 100 is bedding used by a patient. For example, a mattress 170 is placed on the bed 100, and the patient lies on the mattress 170. An imaging device 700 and a detection device 810 are provided near the bed 100. The imaging device 700 is a camera fixed to, for example, the frame of the bed 100, but it may also be fixed to the wall of the patient's room. The detection device 810 is a sheet-like or plate-like device provided between, for example, the bed 100 and the mattress 170.

[0027] The imaging device 700 outputs captured images using sensors such as a CCD (Charge-Coupled Device) image sensor or a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor. The captured images here may be moving images or still images. The imaging device 700 is installed near the bed 100 and captures images of patients, for example, in a hospital room or living room.

[0028] The detection device 810 is a device that senses information related to the patient's sleep. The detection device 810 includes a pressure sensor (e.g., a pneumatic sensor) that outputs a pressure value. When the user lies down, the detection device 810 detects the user's body vibrations (body movement, vibration) via the mattress 170. Based on the detected body vibrations, the detection device 810 obtains information related to respiratory rate, heart rate, activity level, posture, wakefulness / sleep, and getting out of bed / staying in bed. The detection device 810 may output sensor data representing body vibrations, and other devices such as the server system 300 may perform processing to obtain information such as respiratory rate based on this sensor data. The following describes an example in which the detection device 810 outputs information such as respiratory rate.

[0029] For example, the detection device 810 may analyze the periodicity of body movement and calculate the respiratory rate and heart rate from the peak frequency. The periodicity analysis may be performed 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 810 may also detect body vibrations per sampling unit time and output the number of detected body vibrations as the activity level. Furthermore, when the user gets out of bed, the detected pressure value decreases compared to when the user is in bed, so the detection device 810 may determine whether the user is in bed or out of bed based on the pressure value and its time-series changes. However, the method for determining whether the user is in bed or out of bed is not limited to this, and various modifications such as detecting vibrations can be implemented. The detection device 810 may also determine non-REM sleep and REM sleep, and determine the depth of sleep. The sleep-related determination may be performed based on the respiratory rate and heart rate, based on the amount of body movement (e.g., activity level), or using both.

[0030] The detection device 810 outputs biological information (such as respiration and heart rate) representing the patient's biological activity status, and sleep information (such as sleep / wake status, sleep depth, and whether the patient is out of bed or in bed) to the server system 300. The detection device 810 may output the sensing results to the server system 300 via the bedside terminal device 200, or it may output the sensing results to the server system 300 without going through the bedside terminal device 200.

[0031] A device equipped with a load sensor may be used as the bed 100. In this case, the bed 100 may output at least one of the patient's biological information and sleep information. The bed 100 may also output information representing changes in the patient's center of gravity and information representing their sleeping posture. Furthermore, the detection device 810 and the bed 100 with a load sensor may be used in combination.

[0032] The bedside terminal device 200 is a device that has a patient status notification function (notification function) and may be connected to the detection device 810 or to other devices included in the information processing system 10 via a network.

[0033] For example, the bedside terminal device 200 may include a display device and a connection device. The display device is, for example, a tablet-type display terminal that displays various information and accepts input for various operations. The connection device is a hub device for connecting the display device and the various devices. For example, the connection device may be connected to a detection device 810 to continuously acquire the patient's biometric information. The connection device may also receive biometric information from various measuring devices 820 (for example, a thermometer) or from a device worn by the patient (for example, a wristwatch-type wearable measuring device). The connection device may also perform authentication processing (for example, patient authentication or login processing for nurses, etc.) by reading an authentication card 830. The connection device may perform authentication processing using NFC (Near Field Communication), which is an example of short-range wireless communication, or it may perform authentication processing using other methods such as barcodes, infrared, or IC tags. For example, staff (nurses, doctors, care staff) can check the values ​​of biometric information and notification content by logging in, and can register that information in the electronic medical record as needed.

[0034] The network is connected to, for example, a server system 300, an electronic medical record server 400, a station terminal device 500, and a terminal device 600.

[0035] The server system 300 is a server that provides various services and may be connected to the LAN within the medical facility or may be located externally via the internet.

[0036] The server system 300 may consist of one server or may include multiple servers. For example, the server system 300 may include a database server and an application server. The database server stores various data such as biometric information and sleep information. The application server performs processing described later using Figures 7A-8, etc. The multiple servers here may be physical servers or virtual servers. If virtual servers are used, the virtual servers may be located on a single physical server or distributed across multiple physical servers. As described above, the specific configuration of the server system 300 in this embodiment can be modified in various ways.

[0037] The electronic medical record server 400 is a server that stores electronic medical record information about patients. The electronic medical record server 400 is typically a server connected to a network within a medical facility, but it may also be an external cloud server, for example. Electronic medical records can contain various types of information. Electronic medical records include, for example, basic information, medical history, diagnostic information, medication information, test results, consultation information, treatment information, rehabilitation history, vaccination history, lifestyle information, family history, consent forms and signatures, insurance and medical information, medical team information, social background, mental health, emergency response plan, medical resource history, communication with family, infection control, risk assessment, physician's instructions, measurement results, response history, nurse call history, rehabilitation care history, transfer / referral letter history, therapeutic guidance history, patient complaints / chief complaint history, patient behavior information, blood glucose information, dietary therapy information, water intake information, electrocardiogram information, pulse information, information on visits to multiple departments, interdepartmental coordination information, behavioral video recordings, video file storage information, physician / nurse responses based on videos, respiratory rate information, arterial blood oxygen saturation information, excretion information, room temperature and humidity information, etc. However, the above are specific examples of information included in electronic medical records, and various modifications are possible, such as omitting some information or adding other information.

[0038] The electronic medical record system of this embodiment may include other systems. Examples of other systems include nursing support systems, rehabilitation department systems, critical care department systems, and nutrition department systems.

[0039] The station terminal device 500 is a terminal device installed in the nurse station or management room. By using the station terminal device 500, staff can monitor the status of the bedside terminal device 200 (i.e., the status of the patient corresponding to the bedside terminal device 200) from a location different from the patient's room or living room.

[0040] The terminal device 600 is a portable device used by staff, such as doctors and nurses. The staff terminal device 600 connects to a network (e.g., LAN) via a wireless connection. By using the terminal device 600, staff can access information from the bedside terminal device 200 from various locations within the medical facility.

[0041] Furthermore, at least one of the station terminal device 500 and the terminal device 600 may perform a process to notify (inform) the staff of the patient's condition. The notification process performed by the station terminal device 500 and / or the terminal device 600 may be initiated by the bedside terminal device 200 or by the server system 300.

[0042] Next, using Figures 3-6, we will explain an example of the configuration of each device included in the information processing system 10.

[0043] Figure 3 shows an example configuration of the bed 100. The bed 100 includes, for example, a processing unit 110, a storage unit 120, a communication unit 130, an operation unit 140, a drive unit 150, and a movable part 160. The bed 100 may also include load sensors and the like, which are not shown in Figure 3.

[0044] The processing unit 110 of this embodiment is composed of the following hardware. The hardware may include at least one of a circuit that processes digital signals and a circuit that processes analog signals. For example, the hardware may consist of one or more circuit devices or one or more circuit elements mounted on a circuit board. One or more circuit devices may be, for example, an IC (Integrated Circuit) or an FPGA (Field-Programmable Gate Array). One or more circuit elements may be, for example, a resistor or a capacitor.

[0045] Furthermore, the processing unit 110 may be implemented by the following processor. The bed 100 in this embodiment includes a memory for storing information and a processor that operates based on the information stored in the memory. The information is, for example, a program and various data. The memory may be a storage unit 120 or another type of memory. The processor includes hardware. Various types of processors can be used, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or a DSP (Digital Signal Processor). The memory may be a semiconductor memory such as SRAM (Static Random Access Memory), DRAM (Dynamic Random Access Memory), or flash memory, or a register, or 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 instructions that can be read by the computer, and the functions of the processing unit 110 are realized as processing when the processor executes these instructions. The instructions here may be instructions from an instruction set that constitutes a program, or instructions that instruct the hardware circuit of the processor to operate.

[0046] The storage unit 120 is the work area of ​​the processing unit 110 and stores various information. The storage 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 storage unit 120 may also store drive programs, etc., for driving the drive unit 150, which will be described later.

[0047] The communication unit 130 is an interface for communication over a network, and when the bed 100 performs wireless communication, it includes, for example, an antenna, an RF (radio frequency) circuit, and a baseband circuit. However, the bed 100 may also perform wired communication, in which case the communication unit 130 may include a communication interface such as a USB connector or an Ethernet connector, and a control circuit for said communication interface. The communication unit 130 may operate according to the control of the processing unit 110, or it may include a communication control processor different from the processing unit 110.

[0048] The operating unit 140 is an operating interface for controlling the position and angle of the movable part 160. For example, the operating unit 140 may be an operating panel connected by wire or wirelessly to a control box where the processing unit 110 is located. The operating panel may include, for example, buttons for setting the driving direction and amount of the movable part 160.

[0049] The drive unit 150 is an actuator or the like that drives the movable part 160 of the bed 100. The bed 100 in this embodiment may be, for example, a nursing care bed in which the angle of the bottom, which is the surface on which the mattress is placed, can be adjusted. For example, the bed 100 has a plurality of bottoms divided into a plurality of members as the movable part 160, and the drive unit 150 adjusts the angle of the bottom by changing the position and orientation of at least a part of the plurality of bottoms based on the control of the processing unit 110. For example, the drive unit 150 may control the back angle (control of the bottom on the head side) or the foot angle (control of the bottom on the foot side).

[0050] The bed 100 may also be a bed with adjustable leg height. In this case, the drive unit 150 is an actuator or the like that drives the leg, which is the movable part 160. In this way, the height of the entire bed 100 can be adjusted by driving the drive unit 150.

[0051] As shown in Figure 3, the bed 100 may be connected to the imaging device 700 via the communication unit 130. The processing unit 110 may perform image processing such as object recognition on the captured image captured by the imaging device 700.

[0052] Figure 4 shows an example configuration of a bedside terminal device 200. The bedside terminal device 200 includes, for example, a processing unit 210, a storage unit 220, a communication unit 230, a display unit 240, an operation unit 250, a notification unit 260, and an interface unit 270. The bedside terminal device 200 may also include a display device and a connection device as described above. For example, the display device includes the display unit 240 in Figure 4, and the connection device includes the processing unit 210, storage unit 220, communication unit 230, operation unit 250, notification unit 260, and interface unit 270 in Figure 4. However, the configuration shown in Figure 4 can be provided in either the display device or the connection device at will, and it is not prohibited for them to be distributed and provided in both the display device and the connection device.

[0053] The processing unit 210 is comprised of hardware including at least one of a circuit for processing digital signals and a circuit for processing analog signals. The processing unit 210 may also be implemented by a processor. Various types of processors can be used, such as a CPU, GPU, or DSP. The functions of the processing unit 210 are realized as processing when the processor executes instructions stored in the memory of the bedside terminal device 200.

[0054] The storage unit 220 is the work area of ​​the processing unit 210 and is implemented by various types of memory such as SRAM, DRAM, and ROM. For example, the storage unit 220 stores biological information acquired from the detection device 810 and the measuring device 820.

[0055] The communication unit 230 is an interface for communication over a network and includes, for example, an antenna, an RF circuit, and a baseband circuit. The communication unit 230 communicates with the server system 300, for example, over a network. The communication unit 230 may perform wireless communication or wired communication, and the specific communication method is not limited.

[0056] The display unit 240 is an interface for displaying various information, and may be a liquid crystal display, an organic EL display, or another type of display. The operation unit 250 is an interface for receiving user input. The operation unit 250 may be a button or the like provided on the display device or connection device. Alternatively, the display unit 240 and the operation unit 250 may be a touch panel configured as an integrated unit.

[0057] The notification unit 260 may include a light-emitting unit, a vibration unit, a sound output unit, etc. The light-emitting unit is, for example, an LED (light-emitting diode) and provides notification by emitting light. The vibration unit is, for example, a motor and provides notification by vibration. The sound output unit is, for example, a speaker and provides notification by sound.

[0058] The interface unit 270 is the interface for connecting the measuring device 820 and reading the authentication card 830. The interface unit 270 is a port that accepts connections of connectors such as USB (Universal Serial Bus). However, the communication unit 230 may also function as the interface unit 270, as is the case when the authentication card 830 is read using NFC.

[0059] Figure 5 is a block diagram showing a detailed configuration example of the server system 300. The server system 300 includes, for example, a processing unit 310, a storage unit 320, and a communication unit 330.

[0060] The processing unit 310 is comprised of hardware including at least one of a circuit for processing digital signals and a circuit for processing analog signals. The processing unit 310 may also be implemented by a processor. Various types of processors can be used, such as a CPU, GPU, or DSP. The functions of the processing unit 310 are realized as processing when the processor executes instructions stored in the memory of the server system 300.

[0061] The memory unit 320 is the work area of ​​the processing unit 310 and stores various information. The memory unit 220 is implemented by various types of memory.

[0062] The communication unit 330 is an interface for communication over a network, and when the server system 300 performs wireless communication, it includes, for example, an antenna, an RF circuit, and a baseband circuit. The specific communication method of the communication unit 330 can be implemented in various variations.

[0063] The electronic medical record server 400, like the server system 300, is a device that includes a processing unit, a storage unit, a communication unit, and the like. A detailed explanation of the configuration of the electronic medical record server 400 will be omitted.

[0064] Figure 6 is a block diagram showing a detailed configuration example of the terminal device 600. The terminal device 600 may include, for example, a processing unit 610, a storage unit 620, a communication unit 630, a display unit 640, and an operation unit 650.

[0065] The processing unit 610 is comprised of hardware including at least one of a circuit for processing digital signals and a circuit for processing analog signals. The processing unit 610 may also be implemented by a processor. Various types of processors can be used, such as a CPU, GPU, or DSP. The functions of the processing unit 610 are realized as processing when the processor executes instructions stored in the memory of the terminal device 600.

[0066] The memory unit 620 is the work area of ​​the processing unit 610 and is implemented by various types of memory such as SRAM, DRAM, and ROM.

[0067] The communication unit 630 is an interface for communication over a network and includes, for example, an antenna, an RF circuit, and a baseband circuit. The communication unit 630 communicates with the server system 300, for example, over a network. For example, the communication unit 630 may communicate with the server system 300 over a LAN and also communicate with the bed 100 and the bedside terminal device 200 using short-range wireless communication such as Bluetooth®. Various variations are possible for the specific communication method of the communication unit 630.

[0068] The display unit 640 is an interface for displaying various information, and may be a liquid crystal display, an organic EL display, or another type of display. The operation unit 650 is an interface for receiving user input. The operation unit 650 may be a button or the like provided on the terminal device 600. Alternatively, the display unit 640 and the operation unit 650 may be a touch panel configured as an integrated unit.

[0069] Furthermore, the terminal device 600 may include configurations not shown in Figure 6. For example, the terminal device 600 may have various sensors such as motion sensors like acceleration sensors and gyro sensors, pressure sensors, and GPS (Global Positioning System) sensors. The terminal device 600 may also include a light-emitting unit, a vibration unit, a sound input unit, a sound output unit, and the like.

[0070] The station terminal device 500, like the terminal device 600, is a device that includes a processing unit, a storage unit, a communication unit, a display unit, an operation unit, etc. The terminal device 600 may be, for example, a smartphone or a tablet terminal, and the station terminal device 500 may be, for example, a PC (Personal Computer). A detailed explanation of the configuration of the station terminal device 500 is omitted.

[0071] The information processing system 10 according to this embodiment includes a processing unit that performs automatic work schedule creation processing for a facility that provides patient care, based on conditions including at least one of a first condition regarding the number of staff working for each work period, a second condition based on prohibited shifts, and a third condition regarding combinations of staff, and a storage unit that stores the work schedule. Details of these conditions and details of the automatic creation process based on the conditions will be described later. The processing unit determines, based on information that associates staff with their skill levels, which of a plurality of team attributes the work team consisting of multiple staff members determined to be working simultaneously in a given time period has a first team attribute that includes staff with a skill level below a predetermined level, and a second team attribute that does not include staff with a skill level below a predetermined level. Skill level is information determined based on, for example, years of experience in medical work, whether or not a staff member has qualifications, and evaluation results from a manager. The device that stores the skill level of each staff member (information that associates staff with their skill level) may be a server system 300, an electronic medical record server 400, or a device corresponding to the hospital's management system (station terminal device 500 or other PC, etc.). The processing unit performs a setting process to set the execution conditions for patient notification processing during the shift of a work team, based on team attributes. Hereinafter, the setting of the execution conditions for notification processing will also be referred to as notification settings. When the processing unit determines that the frequency of notification processing exceeds a given threshold, it causes the display unit to display at least one of either a first display prompting correction of the work schedule or a second display prompting correction of the execution conditions.

[0072] The information processing system 10 may be, for example, a server system 300. In this case, the processing unit of the information processing system 10 corresponds to the processing unit 310 of the server system 300. The storage unit of the information processing system 10 corresponds to the storage unit 320 of the server system 300. The display unit that performs the first or second display may be an unillustrated display unit provided in the server system 300, the display unit 640 of the terminal device 600, the display unit 240 of the bedside terminal device 200, or the display unit of another device. The display unit may also display a work schedule.

[0073] As described above, the information processing system 10 in this embodiment is not limited to the server system 300, but may be a terminal device 600 or a bedside terminal device 200. That is, the processing unit of the information processing system 10 may be the processing unit 610 of the terminal device 600 or the processing unit 210 of the bedside terminal device 200. Furthermore, the information processing system 10 may be implemented by distributed processing of multiple devices, in which case the processing unit of the information processing system 10 may be implemented by a combination of two or more of the processing units 310, 610, and 210. Below, an example in which the processing unit of the information processing system 10 is implemented by the processing unit 310 of the server system 300 will be described.

[0074] As described above using Figure 1, types of information that are difficult for staff to grasp include risks (sudden changes in patient condition), instructions (patient behavior), and patient wishes. However, the degree to which the information in question is difficult to grasp varies depending on the staff member. Furthermore, in medical facilities, it is expected that multiple staff members will be working together, so it is effective to consider whether information is difficult to grasp, or in other words, whether notification is necessary, on a team basis, which is a collection of such staff members. In the method of this embodiment, when the staff members constituting the team are determined by the automatic creation of the work schedule, the processing unit 310 sets notification settings based on the team attributes and then performs display processing that takes into account the notification frequency estimated from the notification settings. Adjustments (modification of the work schedule, modification of notification settings) are encouraged so that notifications appropriate for the team are sent, making it possible to send highly necessary notifications at an appropriate frequency, and as a result, work efficiency can be improved.

[0075] Furthermore, some or all of the processing performed by the information processing system 10 in this embodiment may be implemented by a program. The processing performed by the information processing system 10 refers, in a narrow sense, to the processing performed by the server system 300, but may also include processing performed by other devices such as the terminal device 600 and the bedside terminal device 200.

[0076] The program according to this embodiment can be stored in a non-temporary information storage medium (information storage device), which is a medium readable by a computer. The information storage medium can be implemented as, for example, an optical disc, a memory card, an HDD, or a semiconductor memory. The semiconductor memory is, for example, a ROM. The processing unit 310 and others perform various processing according to this embodiment based on the program stored in the information storage medium. That is, the information storage medium stores a program that causes the computer to function as the processing unit 310 and others. The computer is a device that includes an input device, a processing unit, a storage unit, and an output unit. Specifically, the program according to this embodiment is a program that causes the computer to execute each of the steps described later using Figures 7A-8 and others.

[0077] Furthermore, the method of this embodiment can be applied to an information processing method that includes the following steps: The information processing system performs an automatic creation process of a work schedule at a facility that provides patient care, based on conditions including at least one of a first condition regarding the number of staff working for each work period, a second condition based on prohibited shifts, and a third condition regarding combinations of staff; for a work team consisting of multiple staff members that the automatic creation process determines will work simultaneously during a given time period, it determines, based on information that associates staff with skill levels, which of a number of team attributes, including a first team attribute that includes staff with skill levels below a predetermined level and a second team attribute that does not include staff with skill levels below a predetermined level, has the work team perform a setting process that sets the execution conditions for patient notification processing during the work team's shift, based on the team attributes; and when it is determined that the frequency of notification processing is above a given threshold, it causes the display unit to display at least one of a first display prompting correction of the work schedule or a second display prompting correction of the execution conditions.

[0078] 3. Processing Flow Next, the processing of the information processing system 10 according to this embodiment will be described. In the following, an example will be described in which the information processing system 10 is a server system 300. First, the overall flow will be explained, and then the work schedule creation process, addition verification process, work schedule update process, and notification process will be described. In addition, an example will be described in which the work schedule is updated based on the patient's wishes, along with a concrete example of a patient UI (User Interface).

[0079] 3.1 Overall Processing Figure 7A is a flowchart illustrating the processing of the server system 300. In step S101, the processing unit 310 performs the process of creating a work schedule. Details of the process will be described later using Figure 8.

[0080] In step S102, the processing unit 310 performs an addition verification process based on the created work schedule. For example, in medical facilities, various additions are known, such as the daily life support addition, service system addition, nursing system addition, and night shift staff allocation addition. Details of the additions will be described later. If it is determined that the requirements for the addition are not met, in step S102, the processing unit 310 may prompt the user to correct the work schedule by highlighting the parts of the work schedule that do not meet the addition requirements. Alternatively, the processing unit 310 may automatically correct a part of the work schedule based on the result of the addition requirement determination.

[0081] In step S103, the processing unit 310 identifies a work team consisting of multiple staff members working together based on the work schedule, and sets up notifications based on that work team. Here, "working together" may mean, for example, that at least part of the work hours overlap. The processing unit 310 may also estimate the frequency of notifications based on the notification settings. The notifications here may include notifications regarding information that is difficult for staff to grasp, as described above. Details of the notification processing will be described later using Figures 13-19C. If it is determined that the notification frequency is above a predetermined level, the processing unit 310 performs output processing that prompts at least one of the following: correction of the work schedule and correction of the notification settings.

[0082] When the processing unit 310 receives a correction input from the user, it performs a process to correct at least one of the work schedule and notification settings based on the correction input. The processing unit 310 may also perform at least one of the following processes: automatically correcting a portion of the work schedule and automatically correcting the notification settings so that the notification frequency is below a predetermined level.

[0083] In steps S102 and S103 described above, the work schedule created in step S101 is modified as necessary. Then, in step S104, the processing unit 310 automatically creates other data, such as a work assignment schedule, based on the processed work schedule. Details of the work assignment schedule will be described later with reference to Figure 11. Also in step S104, the processing unit 310 outputs the created work assignment schedule, etc. This output may be displayed on the display unit, stored in the storage unit 320, or transmitted to another device via the communication unit 330.

[0084] Furthermore, if a separate work management application for the medical facility is used in addition to the application for creating work schedules, the processing unit 310 in step S104 may perform the following processes: determining the format of the target work application, converting the created work schedule into a format that conforms to that format, and outputting the converted data to the work application. For example, if the system according to this embodiment is implemented as a web application and the work application is installed on a PC at the medical facility, it becomes easy to import data created in the web application into the local work application.

[0085] Figure 7B is a flowchart illustrating the work schedule update process that is performed after the process shown in Figure 7A. For example, the process shown in Figure 7B is performed periodically from the time the work schedule shown in Figure 7A is created until the period corresponding to that work schedule ends.

[0086] In step S201, the processing unit 310 determines whether a change to the work schedule is necessary. For example, the processing unit 310 determines whether it has obtained information indicating the absence of a staff member who was scheduled to work. Alternatively, the processing unit 310 may determine whether the patient has performed a user operation requesting the attention of a specific staff member, as will be described later using Figure 25.

[0087] If it is determined that a change to the work schedule is necessary (step S201: Yes), in step S202, a portion of the work schedule is set as the scope of change. For example, if the work schedule is created on a monthly basis, the scope of change will be a period shorter than one month, such as a few days to about a week. Then, the processing unit 310 fixes the portion of the work schedule that is not subject to change and automatically determines the value of the scope of change. Details of this process will be described later with reference to Figure 12.

[0088] When the work schedule is updated, the same processing as when the work schedule was created is performed. Specifically, the processing unit 310 performs an addition verification process (step S203), determines the notification frequency (step S204), and creates a work assignment table (step S205). The processing in steps S203-S205 is the same as steps S102-S104 in Figure 7A, except that the processing target is limited to data corresponding to the above-mentioned range of changes.

[0089] Furthermore, if it is determined that no change to the work schedule is necessary (step S201: No), the processing in steps S202-S205 is omitted.

[0090] Although not shown in Figures 7A and 7B, the processing unit 310 may also perform a process to evaluate the actual work performed after the work for the period corresponding to the work schedule has been completed. For example, the processing unit 310 may perform an addition verification process similar to step S102 or S203 based on the actual work history. In this way, the user can be shown which additions are available based on the actual results. The processing unit 310 may also determine how to add staff to obtain the additions based on a comparison process between work performance and addition requirements, and present the determination result. The processing unit 310 may also display the contents of the confirmation items for obtaining the additions. For example, the processing unit 310 may indicate that registration of sputum suctioning and other related tasks is required to obtain the additions, and provide specific registration methods. The registration here refers to, for example, the registration stipulated in Article 48-3, Paragraph 1 of the Social Workers and Certified Care Workers Act.

[0091] 3.2 Automatic creation of work schedules, etc. Figure 8 is a flowchart illustrating the automatic work schedule creation process shown in step S101 of Figure 7A. The process described below is also applicable to step S202 of Figure 7B, except that the target period is different.

[0092] In step S301, the processing unit 310 determines the conditions (rules) related to work. These conditions may include a first condition regarding the number of staff on duty each day and each working hour. For example, if the staff at a medical facility work in a four-shift system consisting of early shift, day shift, late shift, and night shift, the first condition may include the minimum number of staff for the early shift, the minimum number of staff for the day shift, the minimum number of staff for the late shift, and the minimum number of staff for the night shift on a daily basis.

[0093] The conditions may also include a second condition based on prohibited shifts. The second condition may be a condition to ensure rest time between shifts. For example, a staff member who works a night shift on a given day may be prohibited from coming to work the next day. Or, a staff member who works a late shift on a given day may be prohibited from working an early shift the next day. Alternatively, the second condition may be based on the number of consecutive night shifts. For example, the second condition may be a condition prohibiting three consecutive late shifts.

[0094] Furthermore, the conditions may include a third condition regarding the combination of staff members. For example, if a less skilled first staff member is working, a more skilled second staff member may be assigned to work simultaneously to support the first staff member. Alternatively, if a third staff member is working due to interpersonal problems, a fourth staff member who is incompatible with them may be excluded from the assignment. Thus, the third condition may be a condition requiring two or more staff members to work simultaneously, or a condition requiring two or more staff members not to work simultaneously.

[0095] Furthermore, not all of the above conditions 1 through 3 are mandatory, and it may be possible to switch whether or not to apply each condition. Also, the details of each condition may be modified for each medical facility.

[0096] In step S101, the processing unit 310 acquires staff information as setting items for determining the work schedule. The staff information includes the types of time slots available for work, the days of the week available for work, and the maximum number of days available.

[0097] Figure 9 shows an example of staff information. In Figure 9, ten staff members, Staff A to Staff J, are shown as an example, but the number of staff is not limited to this. Also, considering that the staff may be divided into three units, Staff A to Staff C of the first unit, Staff D to Staff F of the second unit, and Staff G to Staff J of the third unit are displayed in an identifiable manner. Here, the units correspond to multiple floors in a medical facility, for example. However, units may be defined from a different perspective than floors, or the definition of units may be omitted.

[0098] In Figure 9, "Maximum Possible Days" indicates the maximum number of days a staff member can work in a week. For example, Staff A's maximum possible days are 5, meaning Staff A can work 5 days a week. Also, for example, Staff C's maximum possible days are 4, meaning Staff C can only work 4 days a week.

[0099] The "Sun" to "Sat" columns indicate whether the staff member in question is available to work on each day of the week. A value of "1" means that the staff member is available to work on that day, and a value of "0" means that the staff member is unavailable to work on that day. For example, staff member A has a value of "1" for all days of the week, so they are available to work on any day of the week. Staff member J, on the other hand, has a value of 0 for Friday and Saturday, and a value of 1 for the other days, so they are available to work from Sunday to Thursday, but not on Friday and Saturday.

[0100] The "Early," "Late," "Day," and "Night" columns indicate whether the staff member in question is available to work during the respective time slots: early, late, day, and night. A value of "1" means that the staff member is available to work during the time slot, while a value of "0" means that the staff member is not available to work during the time slot. For example, staff member A is available for all early, late, day, and night shifts. Staff member J, on the other hand, is only available for the early or day shift, and is not available for the late or night shift.

[0101] The "set" column contains information related to the third condition mentioned above, and identifies the staff members to be combined. For example, in set1, a staff member whose value is set to 1 must work simultaneously with one of the staff members whose value is set to 2. "Simultaneously" here is not limited to completely matching work hours; partial overlap is also acceptable. Furthermore, if they work on the same day, their work hours do not need to overlap. In the example in Figure 9, staff member J must work simultaneously with one of staff members G through H. Note that a staff member whose value is set to 2 is not required to work simultaneously with a staff member whose value is set to 1. For example, staff member G can work on a day when staff member J is not working. Also, if a staff member whose value is set to 1 cannot work simultaneously with any of the staff members whose value is set to 2, they may work simultaneously with one of the staff members whose value is set to 3. For example, if staff member J cannot work simultaneously with any of staff members G through H, they will work simultaneously with one of staff members A through B. While this example shows multiple staff members working simultaneously, as mentioned above, combinations of staff members who cannot work simultaneously may also be set using the "set" column. For example, as shown in Figure 9, multiple conditions can be set, such as set1, set2, etc., depending on the combination of staff.

[0102] The "Full-time" column indicates whether a staff member is full-time or part-time. A value of "1" indicates that the staff member is full-time, while a value of "0" indicates that the staff member is part-time.

[0103] The processing unit 310 creates a work schedule based on the information obtained in step S301. Figure 10 is a diagram showing a specific example of a work schedule, illustrating the completed state. The work schedule may be a matrix-like table in which staff are arranged on the first axis (vertical axis in Figure 10) and dates are arranged on the second axis (horizontal axis in Figure 10) that intersects with the first axis. Figure 10 shows an example of a work schedule in which staff members are arranged on the vertical axis, including care staff (Staff A-J), nurses (Staff K-L), functional training staff (Staff M), doctors (Staff N-O), office staff (Staff P-Q), and facility manager (Staff R). Figure 10 also illustrates a work schedule for October 2024, with October 1st to October 31st arranged on the horizontal axis.

[0104] Each cell in the work schedule contains information representing the work schedule of the staff member corresponding to the vertical axis and the work schedule of the day corresponding to the horizontal axis. In the example in Figure 10, the cell values ​​are strings such as "Early," "Day," "Late," and "Night," which indicate which time slot the staff member works during (early shift, day shift, late shift, or night shift). The cell value "Holiday" indicates leave (statutory holiday, scheduled holiday). "Morning" indicates leave granted the day after a night shift. "Paid" indicates paid leave. It may also be possible to input unique time slots for each medical facility, such as "Late Night" to indicate night shift work. Furthermore, as shown in Figure 10, the work schedule may also include information summarizing the number of staff members per time slot for the day. For example, as shown in Figure 10, the work schedule includes information summarizing the number of staff members per day for both care staff and nursing staff.

[0105] The process of creating a work schedule corresponds to the process of entering values ​​for all staff members that represent their work schedule for all days within the target period. Once the values ​​for each staff member have been entered, the processing unit 310 aggregates the number of staff members for each time slot for each day.

[0106] In step S302, the processing unit 310 obtains each staff member's desired shift and enters values ​​into the work schedule according to that desired shift. The desired shift here may include information indicating the days the staff member wishes to take off, or information indicating the dates and times they wish to work (early shift, day shift, late shift, or night shift). The desired shift does not determine the entirety of a staff member's work schedule for a month, but may also determine only a portion of it. For example, in the case of a staff member who works 20 days and takes 10 days off in a month, the desired shift may represent a number of desired work days and times less than 20 (e.g., a few days), a number of desired leave days less than 10 (e.g., a few days), or both. In this way, it is possible to reflect the staff member's preferences for days they particularly wish to work or take off, while flexibly determining the work schedule for other days, taking into account the relationship with other staff members. However, some staff members are not prevented from specifying all of their work and leave days for a month.

[0107] After the processing unit 310 reflects the desired shifts in the work schedule (step S302), it performs the process of filling in the parts of the work schedule that are not filled with the desired shifts, based on the data obtained in step S301, as shown in steps S303-S308. First, in step S303, the processing unit 310 may determine the degree of constraint for each staff member, which is determined from information such as the number of days available to work, the days of the week, and the time slots.

[0108] For example, staff with a limited number of available days are less likely to be able to determine their work schedule compared to staff with a larger number of available days. Specifically, even if there are days when no staff are scheduled to work, staff with a limited number of available days are relatively more likely to be unable to come to work on those days. Therefore, the processing unit 310 sets a higher degree of constraint on staff the less available their maximum number of available days is.

[0109] Furthermore, staff members with fewer available working days have more difficulty deciding on their work schedules compared to staff members with more available days. Specifically, even if there are days when no staff members are scheduled to work, staff members with fewer available working days are relatively more likely to be unable to come to work on those days. Therefore, the processing unit 310 sets a higher degree of constraint on staff members the fewer days they are available to work.

[0110] However, it is possible that some days of the week are easier to recruit staff than others. For example, in a medical facility where many staff members are available to work on weekdays but not on weekends, there is often a shortage of staff on Saturdays and Sundays. In such cases, staff members who are available to work on Saturdays and Sundays can easily decide on their working days, even if they are only available on a limited number of days (for example, only Saturdays and Sundays), and the degree of constraint is relatively small. On the other hand, staff members who are only available to work on weekdays may find it difficult to decide on their working days due to overlaps with other staff members, even if they are available on many days, and therefore the degree of constraint is relatively large. Accordingly, the processing unit 310 may weight each day of the week according to how easily staff can be recruited and then determine the degree of constraint related to the day of the week.

[0111] Similarly, staff members with fewer available time slots will find it more difficult to determine their working days compared to staff members with more available time slots. Therefore, the processing unit 310 sets a higher degree of constraint for staff members with fewer available time slots. However, the processing unit 310 may also determine the degree of constraint by weighting each time slot considering the ease with which staff members can gather, similar to the example of days of the week. The processing unit 310 determines the degree of constraint for staff members based on the sum or average (including weighted addition and weighted average) of the degree of constraint obtained from the number of available working days, days of the week, and time slots.

[0112] In step S304, the processing unit 310 selects the staff member whose work schedule has not yet been entered into the work schedule and who has the highest degree of constraint determined in step S303.

[0113] Next, in steps S305-S307, the processing unit 310 inputs the selected staff into the work schedule so that the setting items shown in Figure 9 and the first to third conditions described above are met. This process may be carried out, for example, by the following procedure.

[0114] In step S305, the processing unit 310 first divides the work schedule into shorter intervals. These intervals are, for example, one week. Then, in step S306, the processing unit 310 refers to the parts of the one-week work schedule that already have values ​​filled in, determines the locations where the number of staff members exceeds a predetermined amount, and assigns the leave of the staff member selected in step S304 to those locations. For example, consider the case where the minimum number of staff members for the early shift per day is one (first condition), and one staff member is already assigned to the early shift on a given day of the week. In this example, even if the selected staff member is available for the early shift, there is little point in having them work the early shift on the same day. Therefore, efficient staffing becomes possible by assigning the selected staff member's leave day to that day. Also, "the number of staff members exceeds a predetermined amount" does not mean that the minimum number of staff members is met, but is not limited to this. For example, consider the case where the minimum number of staff members for the early shift is three, and two of the early shifts on a given day are already filled. In this case, although the minimum number of staff has not been reached, a certain number has already been secured, so there is a high probability that the minimum number of staff can be secured by other staff without assigning the selected staff member. Therefore, the processing unit 310 may assign the selected staff member's vacation day to that day. Thus, the processing unit 310 may assign the selected staff member's vacation day to a day on which a predetermined percentage or more of the minimum number of staff has been secured, and this percentage may be 100% or a smaller number.

[0115] Next, in step S307, the processing unit 310 assigns specific values ​​to cells in the work schedule where the value for the selected staff member has not yet been determined, so as to satisfy the conditions such as the first to third conditions. At this time, the processing unit 310 may determine the values ​​so that the values ​​for "night shift," "late shift," "early shift," and "day shift" are entered in this order of priority. For example, since the night shift is physically more demanding than other work shifts, the proportion of staff members who can work the night shift is considered to be relatively low. Therefore, if the selected staff member is able to work the night shift, assigning that staff member to the night shift as a priority makes it possible to create an appropriate work schedule. Similarly, the processing unit 310 prioritizes assignments in the order of late shift, early shift, and day shift, which are considered to be physically demanding for staff.

[0116] Furthermore, if the staff members who will work together are determined by the third condition described above, the processing unit 310 may create a work schedule that satisfies the third condition by performing a masking process. For example, consider the case where staff member J needs to work together with staff members G to H or staff members A to B, as shown in Figure 9. If staff member J is selected after the processing of staff members G to H or staff members A to B has been completed, the processing unit 310 performs a masking process so that only the dates (and time slots) in which staff members G to H or staff members A to B will be working can be selected, and all other dates and time slots cannot be selected. Also, if staff member J has been processed and either staff members G to H or staff members A to B have been selected, and the third condition described above has not yet been met, the processing unit 310 performs a masking process so that only the dates (and time slots) in which staff member J will be working can be selected, and all other dates and time slots cannot be selected.

[0117] Similarly, if the third condition determines that staff members will not work together, the processing unit 310 may create a work schedule that satisfies the third condition by performing a masking process. For example, if staff member A's work schedule has already been determined and staff member B, who cannot work with staff member A, is selected, the processing unit 310 performs a masking process so that the dates and time slots in which staff member A works cannot be selected. In this way, a work schedule that satisfies the third condition can be created.

[0118] After the input of values ​​for the selected staff is complete, in step S308, the processing unit 310 determines whether processing for all staff has been completed. If there are still staff remaining to be processed (step S308: No), the processing unit 310 returns to step S304 to process. Specifically, the processing unit 310 then selects the next staff with the highest degree of constraint (step S304), and then determines the work schedule of the selected staff according to the above procedure (steps S305-S307).

[0119] If the processing unit 310 determines that processing for all staff has been completed (step S308: Yes), it terminates the automatic creation process of the work schedule shown in Figure 8. Through the above process, a work schedule is created using Figure 10 with values ​​entered in each of the cells described above.

[0120] As explained above, the processing unit 310 determines the degree of constraints on work for each of the multiple staff members based on at least one of the number of days, days of the week, and time slots they can work (step S303), and then performs the automatic creation of a work schedule by determining the work schedule for the staff members who are determined to have the highest degree of constraints based on at least one of the first to third conditions (steps S304-S308).

[0121] In this way, it becomes possible to create a work schedule according to predetermined conditions. Normally, such staff allocation is an optimization problem that requires finding a solution under various conditions, and is therefore solved using linear programming (specifically the simplex method). In contrast, in this embodiment, as described above, a work schedule is created by sequentially determining the work patterns of multiple staff members. Therefore, processing can be made faster compared to using linear programming. In this case, since the processing order of staff is determined based on the degree of constraints, it is possible to suppress cases where a work schedule cannot be created. For example, in the method of this embodiment, staff members who can work many days and days of the week and can handle various time slots remain until later, so even if there are remaining dates and time slots for which staff members have not yet been assigned, the probability of filling those dates and time slots can be increased.

[0122] As shown in step S104 of Figure 7A, the processing unit 310 may also create data other than the work schedule based on the created work schedule. Figure 11 shows an example of a work assignment schedule created by the processing unit 310.

[0123] As shown in Figure 11, the work schedule is information created on a daily basis and may include the names of staff members assigned to early shift, day shift, late shift, and night shift for each unit. This makes it possible to automatically record who is working which shift on a given day. A medical facility may also have multiple nurse call buttons (NCs) for patients to call staff. Each of these NCs may be associated with a unit and a time slot. For example, Nurse Call 101 may correspond to the early shift of Unit 1, and Nurse Call 102 may correspond to the late shift and night shift of Unit 1. Therefore, if staff names are automatically entered, the information indicating which staff member is in charge of which NC can be automatically determined. Furthermore, as will be described later using Figure 25, if information indicating that a patient has requested a specific staff member is registered, the processing unit 310 may change the NC assignment based on that information.

[0124] Furthermore, the work schedule may include the names of nurses, and these names are automatically entered based on the work schedule. In addition, the special notes column (the "Announcements, Training, and Committee Schedule" column in the example in Figure 11) is automatically filled with information about events included in the work schedule and information representing the doctors' work schedules.

[0125] The work assignment sheet may also include fields for entering information related to bathing, admission and discharge for short-term stays, and information related to going out. For example, as shown in Figure 11, the processing unit 310 may automatically input values ​​for items that can be determined from the work schedule and output a work assignment sheet with the values ​​for other items left blank. For example, the processing unit 310 may fill in the blanks by accepting manual input from staff. In this way, information that can be identified from the work schedule is automatically reflected in other data such as the work assignment sheet, thus reducing the burden on staff. In addition, although the work assignment sheet was used as an example of data other than the work schedule above, other data such as handover sheets may also be used.

[0126] 3.3 Addition Verification As shown in step S102 of Figure 7A and step S203 of Figure 7B, the processing unit 310 may perform an addition verification process based on the created work schedule. In this embodiment, various additions such as the daily life support addition, service system addition, nursing system addition, and night shift staff allocation addition can be targeted.

[0127] The Daily Life Support Allowance is a system that encourages the acceptance of elderly people who have difficulty living at home by increasing the care fees of special nursing homes that accept elderly people who require care. The Service System Allowance (Service Provision System Enhancement Allowance) is a system that promotes the improvement of service quality by increasing the care fees of facilities that are judged to have a certain level of service quality or higher. The Nursing System Allowance is a system that increases the number of facilities with well-established medical systems by increasing the care fees of care facilities that have a sufficient number of nurses. The Night Shift Staffing Allowance is a system that promotes the improvement of the quality of nighttime care services by increasing the care fees of facilities that have a sufficient number of staff at night. Furthermore, the allowances are not limited to the above examples, and various changes are possible in accordance with the laws of the country or region where the medical facility is established.

[0128] Each additional payment has specific requirements for receiving it. For example, the nursing care system payment requires that at least one full-time nurse be assigned, and that an additional number of nurses be provided in proportion to the number of users. The night staffing payment requires that the number of staff assigned during nighttime hours be equal to or greater than the number determined based on the number of users.

[0129] In step S101, the process shown in Figure 8, a work schedule is created that determines on a daily basis how many staff members are assigned to each shift, such as early shift, day shift, late shift, and night shift (see Figure 10). The attributes of each staff member are also known. These attributes include full-time / part-time status, whether they have caregiver qualifications, whether they have nursing qualifications, etc. (Figure 9). Therefore, in step S102, the processing unit 310 determines whether various additions are applicable based on the number of staff members and qualifications calculated from the work schedule. For example, the processing unit 310 may perform addition verification for each unit period and highlight the periods that are determined not to meet the requirements for the addition. The unit period here is, for example, one day, but may be changed depending on the type of addition. The processing unit 310 may also perform a process to display the requirements for additions that are not met in the existing work schedule. In this way, it becomes possible to prompt the user (medical facility administrator, etc.) to revise the work schedule.

[0130] For example, in the case of the night staffing allowance, as mentioned above, the number of staff working at night is one of the requirements. Therefore, the processing unit 310 performs a process to calculate the number of staff working at night on a daily basis based on the work schedule.

[0131] The start and end times for each shift of care staff—night shift, early shift, day shift, and late shift—are known for each medical facility. Specifically, "nighttime" refers to the 16 hours from 17:00 to 9:00 the following day. Therefore, it is possible to calculate the time in each time slot on the work schedule that corresponds to nighttime. For example, in a night shift from 21:45 to 7:15, the entire 9 hours and 30 minutes of work correspond to nighttime. Similarly, in an early shift from 7:00 to 16:00, the 2 hours from 7:00 to 9:00 correspond to nighttime. The same applies to other time slots; for example, the nighttime period in a day shift is 1 hour, and the nighttime period in a late shift is 5 hours.

[0132] In the work schedule shown in Figure 10, on October 1st, the number of care staff on the night shift, early shift, day shift, and late shift is 1, 2, 2, and 1, respectively. Processing unit 310 calculates that there is 1 care staff member on the night shift, and that this person works for 9 hours and 30 minutes, so the night shift hours are 1 × 9.5 hours = 9.5 hours. Similarly, processing unit 310 calculates that there are 2 care staff members on the early shift, and that these 2 people work for 2 hours, so the night shift hours are 2 × 2 hours = 4 hours. The same applies to the other time slots, and processing unit 310 calculates the day shift hours as 2 × 1 hour = 2 hours and the late shift hours as 1 × 5 hours = 5 hours. Processing unit 310 calculates the total hours of 20.5 by summing the hours calculated for each work time slot.

[0133] As mentioned above, the nighttime period is 16 hours. Since all care staff worked 20.5 hours on October 1st, the processing unit 310 calculates the daily number of staff assigned to the nighttime period on October 1st by dividing the total hours of 20.5 by the length of the nighttime period, which is 16. In the example of October 1st, the daily number of staff is approximately 1.3. The same applies to October 2nd and subsequent days, and the processing unit 310 calculates the daily number of staff for all days for which a work schedule was created. The start and end times of the early and late shifts for nurses are also known, and the number of nurses on the early and late shifts for each day is also known from the work schedule shown in Figure 10. Therefore, the processing unit 310 may also calculate the daily number of staff for nurses.

[0134] Under the night staffing allowance, the number of staff required per day varies depending on the number of users (patients). Therefore, the processing unit 310 calculates the required number of staff from the number of users of the medical facility in question and determines whether the above daily number is equal to or greater than the required number of staff. If the daily number is equal to or greater than the required number of staff, the processing unit 310 sets the result for the day in question to "pass," and otherwise sets the result to "fail." If there is a day that is judged to be "fail," the processing unit 310 may highlight the cell corresponding to that day in the work schedule. The processing unit 310 may also determine, based on the difference between the daily number and the required number of staff, how many staff members should be added at which time slots to make the result "pass." The processing unit 310 may also perform processing to present information that identifies the staff that should be added.

[0135] The above explains the night staffing allowance, but other allowances can also be determined based on work schedules.

[0136] 3.4 Updating the work schedule As shown in steps S201-S202 of Figure 7B, the processing unit 310 may update the existing work schedule if a change to the work schedule is necessary. In this case, if the processing unit 310 determines that a change to the work schedule is necessary after creating the work schedule for a given first period, it performs an update process that executes the automatic creation process again, targeting the second period, which is part of the first period.

[0137] Here, the first period is, for example, one month, and the second period is, for example, a few days to a week, but the specific length of the periods can be varied in various ways. By limiting the update target to certain periods, the work schedules that have already been created for other periods can be maintained. This makes it possible to reduce the processing load.

[0138] The update process here is executed, for example, when a given staff member is unable to come to work due to an infectious disease or some other reason. Figure 12 is a diagram illustrating the process of updating the work schedule.

[0139] For example, suppose a staff member who was scheduled to work on October 15th becomes unable to work at a time prior to October 15th. In this case, the processing unit 310 determines that October 15th is a day that needs to be changed and sets the period including that day as the second period. The second period is, for example, a predetermined number of days starting from the day on which the change became necessary. However, days prior to the day on which the change became necessary may also be included in the second period.

[0140] In the example shown in Figure 12, the processing unit 310 deletes the values ​​representing the work schedule for the period from October 15th to October 19th, and then runs the automatic work schedule creation process again for that period. In other words, the specific processing flow is basically the same as the process explained using Figure 8, with a few differences. The differences here include, for example, that the target period is limited to the second period, and that if there is a staff member who is unable to work, the value for that staff member is fixed to leave. Also, although Figure 12 shows an example in which the work schedule is updated for all staff, including care staff, nursing staff, and doctors, only the staff types that require updating may be targeted for processing. For example, if a care staff member is absent, the work schedule may be updated only for the care staff member. Note that some of the conditions obtained in step S301, such as the first condition, require consideration of whether or not there is work for two or three days, and the working hours. For example, when the processing unit 310 enters the work schedule for October 18th and 19th, it may determine whether or not the conditions are met by referring to the existing work schedule for October 20th and 21st. Thus, there is no preclude referencing information from periods after the second period (periods not subject to renewal) in order to enter the work pattern value for the second period.

[0141] Furthermore, updating the work schedule may change the number and attributes of staff members who will be working on each date and time slot during the second period. Therefore, as described above using Figure 7B, the processing unit 310 may re-execute the processes that use the work schedule, specifically the addition verification process, the notification frequency determination process, and the creation of the work assignment table, etc. (steps S203-S205 in Figure 7B).

[0142] 3.5 Notification Settings Next, we will explain the relationship between work schedules and notification processing. First, we will provide an overview of notification settings based on work schedules, and then we will explain specific examples of notification processing for information that is difficult to grasp, focusing on risks, patient behavior, and patient wishes.

[0143] 3.5.1 Overview of Notification Processing As described above, the processing unit of the information processing system 10 (more specifically, the processing unit 310 of the server system 300) may configure notification settings according to the team attributes for work teams consisting of multiple staff members who are determined to be working simultaneously during a given time period by the automatic work schedule creation process. Notification settings refer to settings related to notification processing.

[0144] The notification process here specifically includes at least one of the following processes: risk notification processing to notify of risks related to a patient, patient behavior notification processing regarding patient actions based on physician's instructions, and patient will notification processing to notify the results of the interpretation of the patient's wishes. In this way, it becomes possible to appropriately notify the aforementioned staff who may have difficulty grasping the information. In this case, by using the work team determined based on the automated work schedule creation process as the notification unit, it becomes possible to provide appropriate notifications. For example, if the information is sufficient for one person in the work team to grasp, it becomes possible to reduce the burden on other staff by suppressing notifications even if the information is difficult for them to grasp.

[0145] Figure 13 shows an example of the correspondence between team attributes and notification settings for each notification process. Details of each notification process will be described later using Figures 14-19.

[0146] In Figure 13, Team X and Team W represent work teams with different team attributes. For example, Team X, corresponding to the first team attribute, is a team that includes staff with low skill levels. Skill level here is determined based on one or more of the following: years of service, registration status of qualifications and skills, evaluation results by experts, etc. Specifically, Team X may be a team that includes staff with less than three years of experience in healthcare.

[0147] Team Y, corresponding to the second team attribute, is a team that does not include staff with low skill levels. The determination regarding skill levels is the same as in the example of Team X. For example, Team Y may be a team consisting of staff members, all of whom have more than three years of work experience.

[0148] Team Z, corresponding to the third team attribute, is a team that includes trainers and trainees. Here, a trainee is a staff member who requires support from a trainer. For example, a trainee is a staff member who is permitted to perform certain tasks on the condition that they are supervised by a trainer. Alternatively, a trainee may be a staff member who is permitted to perform only a limited number of tasks that are relatively easy, by sharing the work with a trainer. Note that the "less skilled staff" of the first team attribute (Team X) differ from trainees in that they have short years of service but are permitted to perform tasks without support from a trainer. A trainer is a staff member who supports trainees as described above.

[0149] Team W, corresponding to the fourth team attribute, is a team consisting of staff who perform specific tasks. These specific tasks could be, for example, rehabilitation. In this case, the staff of Team W are responsible for patient guidance and care during rehabilitation, but they perform general tasks typically performed by nurses and caregivers, such as administering IVs or changing patient positions, with less frequency.

[0150] In Figure 13, "○" indicates that the notification process will be executed, and "×" indicates that the notification process will be omitted. "△" represents an intermediate state, where the notification process is executed, but less frequently than "○".

[0151] As shown in Figure 13, the processing unit 310 may be configured to perform notification processing for physician instructions (patient behavior) for either Team X or Team W. In the case of patient behavior, for example, as will be described later, staff members restrict the diet and fluid intake of diabetic patients based on physician instructions. In this case, since the foods and fluids that are permissible for non-diabetic patients are monitored, it is not easy for staff members to grasp the monitoring items for all their assigned patients. Therefore, by setting the notification processing for patient behavior to be on by default, it becomes possible to present appropriate information. However, the processing unit 310 may also configure notification settings so that the content of notifications regarding patient behavior differs depending on the team attribute.

[0152] As shown in Figure 13, the processing unit 310 sets the number of risk types notified to Team X to be greater than the number of risk types notified to Team Y. In this way, in the case of teams with less experienced staff, it is possible to encourage appropriate responses to risks by performing notification processing relatively frequently. For example, even if the staff member in charge of a patient experiencing a risk is less experienced, it is possible to instruct them on appropriate responses (actions) through notification processing. In the case of teams composed of highly experienced staff, it is possible to reduce the frequency of notification processing to prevent staff from feeling bothered.

[0153] Furthermore, the processing unit 310 performs notification processing with a relatively high frequency for Team Z, and sets the target of the notification processing to the trainer. For example, suppose a trainee is performing duties away from the trainer, and a risk arises for a patient under the trainee's care. In this case, even if the trainee is presented with countermeasures through the notification processing, the trainee is a staff member who is unable to perform duties alone, and may not be able to take appropriate action. By setting the target of the notification processing to the trainer, it becomes possible to appropriately understand that the trainee may be facing an event that they cannot handle on their own.

[0154] Furthermore, the processing unit 310 may set the notification processing for risks related to the tasks handled by Team W to be turned off. This is because Team W consists of specialists in their respective tasks, and it is assumed that they will be able to recognize the occurrence of risks and take appropriate action even if no notification processing is performed for those tasks. On the other hand, the staff belonging to Team W may be unfamiliar with tasks other than their assigned tasks. Therefore, the processing unit 310 may set the notification processing to be turned on for a wide range of risks unrelated to Team W's tasks.

[0155] As shown in Figure 13, the processing unit 310 sets the notification processing for Team X to ON and the notification processing for Team Y to OFF for patient notification processing. This is because less experienced staff have a high need for support because they have difficulty judging what the patient wants and what actions are necessary even when a nurse call is made, while more experienced staff have a low need for support. The processing unit 310 also sets the notification processing for Team W to OFF. This is because staff engaged in specific tasks are less likely to respond to nurse calls, etc.

[0156] The processing unit 310 may also turn on notification processing for Team Z and set the notification destination according to the type of notification. For example, the processing unit 310 may estimate the difficulty of the response based on the patient's medical condition and activity level, and set the notification destination for patients with low difficulty to the trainee and for patients with high difficulty to the trainer. Alternatively, as will be described later using Figure 20, the requests may be subdivided on the patient screen for notifying staff of the patient's wishes. The processing unit 310 may set whether to notify the trainee or the trainer depending on which item the request relates to. Alternatively, as will be described later, the processing unit 310 may estimate a course of action that is in line with the patient's wishes based on the patient's utterances, etc., and notify the estimation result. In this case, the processing unit 310 may set it to notify the trainee if the course of action is within the scope of relatively easy tasks that the trainee can perform independently, and notify the trainer otherwise. Thus, in this embodiment, the notification destination may be set from the viewpoint of whether the trainee can perform the action independently or whether trainer support is required.

[0157] For example, in step S103 in Figure 7A or step S204 in Figure 7B, the processing unit 310 identifies work teams consisting of staff working on the target day on a daily basis, based on the work schedule created by the automatic creation process. If the medical facility has multiple floors, the processing unit 310 may determine work teams on a floor-by-floor basis. In the example in Figure 10A, the work teams for Wednesday, October 1st include Team 1 consisting of staff A and C, Team 2 consisting of staff E and F, and Team 3 consisting of staff G, H, and I. In addition, while the above examples illustrate work teams for care workers, a separate work team for nurses may be created. Alternatively, one team including both care workers and nurses may be created.

[0158] The processing unit 310 then determines the team attribute of the work team based on the attribute information of each staff member. The staff attributes may include information that serves as an indicator for determining skill level, such as years of service. The processing unit 310 then determines that the team attribute is the first team attribute if the team includes staff members whose skill level is below a predetermined threshold, and determines that the team attribute is the second team attribute otherwise.

[0159] Furthermore, the staff attributes may include information indicating whether they are trainees or trainers. This information may include, for example, information that identifies the third condition in the automatic work schedule creation process (e.g., the set column in Figure 9). The processing unit 310 determines that staff members who are required to work simultaneously with other staff members are trainees, and staff members who support such trainees are trainers. In the example in Figure 9, the processing unit 310 determines, based on the information in set1, that staff member J is a trainee and that either staff member G-staff H or staff member A-staff B is a trainer. If a work team includes both trainees and trainers, the processing unit 310 determines that the team attribute is the third team attribute. Note that the information representing trainees and trainers is not limited to this and may include information different from the third condition.

[0160] Furthermore, the staff attributes may include information indicating whether or not they are engaged in specific tasks such as rehabilitation. The processing unit 310 determines that the team attribute is a fourth team attribute if it has an attribute indicating that a certain percentage or more of the staff (in the narrow sense, all) of the work team are engaged in the same tasks.

[0161] The processing unit 310 sets the notification settings based on the determined team attributes and information (Figure 13) that associates pre-configured team attributes with notification settings.

[0162] Furthermore, staff are not prevented from manually changing each of the notification settings described above. For example, staff belonging to a work team may manually change the notification settings for that work team, or the administrator of the medical facility may manually change the notification settings for each work team.

[0163] The changes referred to here may be the switching of the corresponding function on or off. For example, a staff member belonging to the work team with the first team attribute may turn off the patient behavior notification processing, which is set to on by default. The same applies to patient sudden changes and patient-physician notifications; the processing unit 310 may switch the corresponding function off based on user operation.

[0164] Alternatively, the changes referred to here may involve changing the scope of the function. For example, as will be described later using Figure 14B, the risk (sudden change in patient condition) notification process may include notification processes for diabetes risk, heart failure risk, cardiomyopathy risk, etc. In this case, the processing unit 310 may change the scope of the risk notification process based on user operation. For example, the processing unit 310 may individually set the on / off status of the diabetes risk notification process, the heart failure risk notification process, and the cardiomyopathy risk notification process. Alternatively, each notification process may allow not only on / off status but also changes in the notification method. In this case, the processing unit 310 may change the scope of the function by changing the notification method. Changes in the notification method include changing the device to be notified, changing the staff to be notified, changing the screen content, changing the on / off status of sound and light notifications, etc.

[0165] Then, in step S103 in Figure 7A or step S204 in Figure 7B, the processing unit 310 estimates the notification frequency (the frequency of notification processing) on ​​a daily basis based on the notification settings. For example, the processing unit 310 may determine that the more items that are set to turn on notifications, the higher the notification frequency. Alternatively, a weight representing the notification frequency may be set for each item, and the processing unit 310 may determine the notification frequency based on the items that are set to turn on notifications and the weight of those items.

[0166] The processing unit 310 then determines that the frequency of notification processing exceeds a given threshold, and displays at least one of the following on the display unit: a first display prompting correction of the work schedule, or a second display prompting resetting of the execution conditions for notification processing. For example, the processing unit 310 may highlight the target area of ​​the work schedule, similar to when it is determined to be unsuccessful in the addition verification. The target area here refers to the set of cells corresponding to a unit period in which the notification frequency is determined to be above a predetermined level, and the unit period is, for example, one day. Alternatively, the processing unit 310 may display a notification settings screen (not shown) and display a message on that screen prompting a reduction in the number of items subject to notification.

[0167] As shown in step S104 of Figure 7A and step S205 of Figure 7B, the processing unit 310 may create a work assignment table based on the work schedule. The work assignment table includes information identifying the staff member who will respond to the nurse call, as shown in Figure 11 (see the "NC" column). If the team attribute of the work team is determined to be a third team attribute including trainees and trainers, the processing unit 310 may perform a process to reflect the notification recipient set in the notification settings above in the nurse call assignment. For example, if the notification setting is such that a notification regarding the first patient is sent to the trainee and a notification regarding the second patient is sent to the trainer, the processing unit 310 will determine the value in the "NC" column of the work assignment table so that the notification setting is reflected based on the information that associates the patient with the nurse call number.

[0168] 3.5.2 Risk The processing unit 310 may perform a setting process based on data that associates clinical departments with risk sets representing the risks of patients associated with those departments, such that the level of notification for risks related to the first clinical department, to which the staff member belongs, is lower than the level of notification for risks related to the second clinical department, which is different from the first clinical department. In this way, it becomes possible to appropriately present information that is difficult to grasp due to differences in clinical departments to the staff. The specific data and processing flow will be explained below.

[0169] <Example of table data> First, let's explain the data used in risk processing. Figures 14A and 14B show examples of the first data set, which associates a clinical department with the risks expected in that department. In the following, we will describe examples where each data is table data such as a relational database, but the data format is not limited to this.

[0170] As shown in Figure 14A, the first data associates information identifying a medical department with a risk set related to that department. The medical departments here include various specialties such as internal medicine, surgery, pediatrics, gynecology, dermatology, and ophthalmology. Furthermore, subspecialized departments such as cardiology, respiratory medicine, and gastroenterology may be included under internal medicine. Similarly, subspecialized departments such as cardiac surgery and neurosurgery may be included under surgery. The medical departments are not limited to those exemplified above. Also, the number and types of medical departments set may differ from hospital to hospital.

[0171] A risk set is a collection of risks that may occur in a corresponding medical specialty. As shown in Figure 14B, a single risk set can contain multiple risks. For example, in Figure 14A, specialty A is internal medicine, and risk set A is a collection of risks that may occur in internal medicine. As shown in Figure 14B, risk set A includes, for example, diabetes risk, heart failure risk, cardiomyopathy risk, etc. These risks represent risks related to diseases such as diabetes, heart failure, and cardiomyopathy. For example, a high risk of diabetes means that there is a high probability of developing diabetes, or that existing diabetes is likely to become severe.

[0172] For example, the processing unit 310 of the server system 300 may identify a disease with a history of occurrence in a specific medical department based on the electronic medical records stored in the electronic medical record server 400, and perform processing to add the risk related to that disease to the risk set corresponding to that medical department. The processing unit 310 stores the risk sets for each of the multiple medical departments, and information identifying the specific risks included in each risk set (Figures 14A and 14B), as first data in the storage unit 320.

[0173] Alternatively, the processing unit 310 of the server system 300 may perform a process to identify a risk set corresponding to a medical department based on operational input from an expert in that medical department. Here, the expert is, for example, a physician. Alternatively, the processing unit 310 may perform a process to identify a risk set corresponding to a medical department based on data other than the electronic medical record. For example, the processing unit 310 may identify a risk set based on data obtained from a recording server (not shown in Figure 2) that stores data other than the electronic medical record. Here, the recording server may be a server that stores patient data not included in the electronic medical record, such as data obtained outside the hospital. Alternatively, the recording server may store open data that is widely available in the medical and nursing care fields (for example, publicly available academic journals).

[0174] The processing unit 310 may also perform a process to push notification of the identified risk set to the staff's terminal device 600. For example, an application installed on the terminal device 600 may present the risk set requested by the processing unit 310 to the nurse and receive the nurse's judgment on whether each risk in the risk set is difficult to grasp or not. The processing unit 310 may also store the risk set consisting of risks selected by the nurse as first data in the storage unit 320.

[0175] Figure 14C shows an example of second data that associates sensors used in risk assessment processing with the specific processing content (algorithm) of the assessment process. Here, risk refers to individual risks such as diabetes risk, heart failure risk, and cardiomyopathy risk, as shown in Figure 14B. For example, if risk A is diabetes risk, sensor A is information that identifies the sensor used in the diabetes risk assessment process, and model A is information that identifies the algorithm for the diabetes risk assessment process.

[0176] The sensors and algorithms used here may also be data corresponding to the tacit knowledge of experts. For example, highly skilled doctors and nurses can determine the degree of risk based on sensing data representing a patient's biometric information. This biometric information can include various types of data such as heart rate (pulse rate), respiratory rate, blood pressure, and arterial oxygen saturation (SpO2). Experts can also estimate a patient's risk from various other pieces of information such as facial expressions, complexion, activity level, frequency of bowel movements, temperature, and humidity. In other words, experts implicitly know which of these diverse pieces of information are useful for risk assessment and how to use that information to accurately determine the risk.

[0177] Therefore, by identifying the sensors used by experts to acquire information and the processing algorithms for the sensing data output by those sensors, it becomes possible to digitize the tacit knowledge of experts. For example, the algorithm in this embodiment may be a trained model obtained by performing machine learning such as a neural network. For example, the processing unit 310 of the server system 300 creates a trained model by performing machine learning using data that associates sensing data acquired for a certain patient with the expert's judgment result regarding the patient's risk (for example, a score representing the degree of risk) as training data. The identification of sensing data, i.e., the identification of the sensors to be used, may be based on the expert's selection or may be done using machine learning. The processing unit 310 stores the data in which the identified sensors and the information of the trained model are associated with the risk as second data in the storage unit 320.

[0178] The input to the algorithm (trained model) is sensing data. The output of the algorithm, in a narrow sense, is information such as a score representing the degree of risk, but it may also include other information. For example, the algorithm may perform a process to determine the actions (countermeasures, actions) that staff should take in response to a risk, based on the sensing data. For example, in the machine learning described above, by including the actions that experts have actually taken in response to a risk as training data, it is possible to generate a trained model that outputs the recommended staff actions in response to that risk.

[0179] Alternatively, the storage unit 320 of the server system 300 may pre-store table data (not shown) that associates recommended staff actions for each risk. For example, the storage unit 320 stores table data that associates a risk with an action that a staff member should take if the evaluation result of that risk (the score output by the algorithm) meets predetermined conditions. Note that multiple different actions may be associated with a single risk depending on the evaluation result (the numerical range of the risk). In this case, it is possible to identify the action that a staff member should take by comparing the table data with the output of the algorithm shown in Figure 14C.

[0180] Furthermore, the learning process is not limited to that performed on the server system 300, but may be executed on other learning servers, etc. Also, the algorithm is not limited to a model using a neural network, but may be a model using other methods such as SVM (support-vector machine). In addition, the algorithm may be obtained by methods that do not use machine learning (e.g., regression analysis).

[0181] <Example Sequence> Figure 15 is a sequence diagram illustrating the process of presenting information about risks that are difficult for staff to grasp. For example, steps S401-S403 in Figure 15 are processes that are executed when a new patient is admitted to the hospital. Steps S404-S406 are notification settings based on the work team, corresponding to step S103 in Figure 7A or step S204 in Figure 7B. In other words, steps S404-S406 are executed when a work schedule is created or modified. The subsequent processes S407-S410 are processes that are executed during the period when the target work team is actually working, for example, on a daily basis.

[0182] First, in step S401, the server system 300 receives input information about the hospitalized patient. The input operation may be performed, for example, on a station terminal device 500, or on a terminal device of the department that handles administrative procedures related to hospitalization. Here, the information about the hospitalized patient includes information about the department in which the patient is hospitalized, and information about other departments in which the patient has a medical history. Although hospitalization is used as an example here, the method of this embodiment can be applied to other situations such as admission to a nursing home.

[0183] In step S402, the processing unit 310 obtains a risk set for departments other than the department in which the patient is hospitalized, based on the department associated with the hospitalized patient and the first data described above using Figures 14A and 14B. For example, based on the information received in step S401, the processing unit 310 identifies departments other than the department in which the hospitalized patient has a medical history, and identifies the risk set associated with that department based on the first data (Figure 14A).

[0184] As in the example above, in a case where a patient who was being treated in internal medicine for diabetes is hospitalized in ophthalmology due to developing cataracts, the processing unit 310 performs a process to obtain a risk set associated with internal medicine from the first data. This allows for the appropriate identification of risks that are difficult for ophthalmology staff to grasp and that have a high probability of occurring in the patient. As can be seen from this example, the risk set obtained in step S402 may be limited to the risk sets of departments other than the staff member's department, and only include departments that the hospitalized patient has a history of visiting. In the example above, the processing unit 310 may exclude the risk set of departments other than ophthalmology and internal medicine (e.g., surgery) from the risk set obtained in step S402. In this way, information on risks with a low probability of occurring can be excluded from processing. In the example above, since the patient has no history of visiting surgery, risks related to surgery are not selected in step S402 because they have a low probability of occurring. However, the processing of this embodiment is not limited to this. For example, in step S402, the processing unit 310 may select both the risk set of medical departments other than the staff member's department where the inpatient has a history of visiting, and the risk set of medical departments where the inpatient has not a history of visiting. More precisely, the processing unit 310 may select the risk set for all medical departments other than the staff member's department. In this way, it becomes possible to select a risk set that broadly covers risks that would be difficult for staff members to grasp if they occur.

[0185] In step S403, the processing unit 310 identifies the sensor and algorithm to be used for the risk evaluation process for each risk in the risk set identified in step S402 by referring to the second data (Figure 14C).

[0186] In step S404, the processing unit 310 determines the work team for each day and the team attributes of the work team based on the automatically generated work schedule. In step S405, the processing unit 310 sets up notifications regarding risks based on the team attributes. For example, the processing unit 310 performs the initial setup of the notification process based on the risk set selected based on the processing in steps S401-S403, the team attributes, and the data shown in Figure 13. For example, if the team attribute of the work team is the first team attribute (team X), the processing unit 310 turns on notifications for all risks included in the risk set selected in steps S401-S403. If the team attribute of the work team is the second team attribute (team Y), the processing unit 310 turns on notifications for only some of the risks included in the risk set selected in steps S401-S403.

[0187] Alternatively, if the team attribute of the work team is the first team attribute (Team X), the processing unit 310 may turn on notifications not only for the risk sets selected in steps S401-S403, but also for the risk sets that were not selected. For example, the processing unit 310 turns on notifications for the risk sets of the staff member's department, in addition to the risk sets of departments other than the staff member's department. If the team attribute of the work team is the second team attribute (Team Y), the processing unit 310 turns on notifications only for risks included in the risk sets extracted in steps S401-S403. For example, the processing unit 310 turns on notifications for risk sets of departments other than the staff member's department, and turns off notifications for risk sets of the staff member's department. Thus, in the method of this embodiment, it is sufficient to perform notification settings according to the team attribute, and various variations are possible in the specific implementation.

[0188] In step S406, the processing unit 310 determines the notification frequency based on the notification settings, and if it determines that the notification frequency is above a predetermined level, it performs a display process to prompt correction. This display process is, for example, the process of highlighting a part of the work schedule as described above, but other processes may also be performed.

[0189] In step S407, the processing unit 310 performs the process of activating the sensor determined in step S403. Various devices such as the imaging device 700, detection device 810, and measuring device 820 can be used as the sensor here. This makes it possible to acquire sensing data necessary for risk assessment processing that is difficult for staff to grasp.

[0190] In step S408, the sensor acquires sensing data. The sensor transmits the acquired sensing data to the server system 300. The transmission of sensing data may be done directly or via the bedside terminal device 200 or terminal device 600.

[0191] In step S409, the processing unit 310 takes the acquired sensing data as input and performs a risk assessment process according to the algorithm (trained model) identified in step S403. The assessment result here may be information such as a score representing the degree of risk, as described above, or it may be information including recommended actions for the staff.

[0192] The processing unit 310 executes a process to display the risk assessment results on the terminal device 600 used by the staff. For example, the processing unit 310 performs a process to display a screen on the display unit 640 of the terminal device 600 that includes the risk assessment results (presence or absence of risk, or score) and recommended actions for the staff.

[0193] This process may be performed via the bedside terminal device 200. Specifically, the processing unit 310 causes the display unit 240 of the bedside terminal device 200 to display the link data for displaying the screen. The link data here may be code information such as a QR code (registered trademark).

[0194] Figure 16 shows an example of a risk assessment results screen displayed on the display unit 640 of a terminal device 600 that reads a QR code. As shown in Figure 16, the risk assessment results screen may include information identifying the target patient, the date and time, specific assessment results, and information on actions recommended for staff (countermeasures, actions taken).

[0195] In the example shown in Figure 16, blood glucose levels are acquired as sensing data, and the evaluation results screen includes specific numerical values ​​for blood glucose levels. Furthermore, the risk assessment based on blood glucose levels displays that the risk of impaired consciousness and the risk of falls are high. This allows for the presentation of diabetes-related risks in a way that is easily understandable to, for example, ophthalmology staff who are not accustomed to caring for diabetic patients.

[0196] Furthermore, as shown in Figure 16, the evaluation results screen includes actions recommended to staff (nurses in the narrow sense), such as "administer glucose solution intravenously" and "remove obstacles around the bed and set the bed height to the lowest setting." This makes it possible to encourage appropriate actions regarding risks that are difficult for nurses to identify. As shown in Figure 16, the actions (measures) here may include both highly urgent and less urgent actions (those that should be implemented from a permanent perspective).

[0197] As shown in Figure 16, the evaluation results screen may also include a call button and a share button. The call button is, for example, a button for staff to start a call with a doctor. For example, if instructions from a doctor are needed to address a risk, staff can use this button to quickly seek the doctor's judgment. The doctor's instructions given verbally during the call may be included in the doctor's instructions, which are an example of information that is difficult for staff to grasp. For example, the doctor's instructions given during the call may be stored in the electronic medical record as doctor's instruction information. Registration in the electronic medical record may be performed automatically by the processing unit 310, etc., using speech recognition processing, or it may be performed manually by a doctor or nurse. For example, instructions given verbally by a doctor to a staff member may be information that is difficult for other staff members to grasp, but in this embodiment, it is possible to appropriately manage such instructions. The share button is a button for sharing risk-related information with other nurses. For example, when the share button is pressed, the terminal device 600 may perform a process to send the evaluation results screen to the terminal device 600 used by other staff members. In this way, it becomes possible to share information about high-risk patients among multiple staff members.

[0198] Furthermore, while the above example shows a staff member actively viewing the evaluation results screen by scanning a QR code, the method is not limited to this. For example, as shown in step S410 of Figure 14, if the evaluation result satisfies the given conditions, the processing unit 310 may push notification of the evaluation result to the staff member's terminal device 600. The screen displayed on the display unit 640 of the terminal device 600 is similar to that shown in Figure 16, for example. In this way, it becomes possible to appropriately notify staff members when urgent measures are needed.

[0199] 3.5.3 Patient behavior The processing unit 310 may perform a setting process based on data that associates clinical departments with instruction sets representing instructions given by physicians in those departments to staff, so that the level of notification for instructions associated with the first clinical department, to which the staff member belongs, is lower than the level of notification for instructions related to the second clinical department, which is different from the first clinical department. In this way, it becomes possible to appropriately present information that is difficult for staff members to grasp. The specific data and processing will be explained below.

[0200] <Example of table data> This section explains the data used in processing instructions (patient behavior). Figures 17A and 17B are examples of third-party data that associate clinical departments with the expected physician instructions within those departments, specifically the patient behaviors that staff (nurses in the narrow sense) should monitor.

[0201] As shown in Figure 17A, the third data set associates information identifying the clinical department with a set of instructions related to that department. The clinical departments are identified in the same way as in the example described above using Figure 14A.

[0202] An instruction set is a collection of instructions that are highly likely to be given to nurses in a corresponding medical department. An instruction set can also be described as a collection of patient behaviors that nurses in a corresponding medical department need to monitor. As shown in Figure 17B, one instruction set contains multiple instructions. For example, in Figure 17A, medical department A is internal medicine, and instruction set A is a collection of patient behaviors that internal medicine nurses need to monitor. As shown in Figure 17B, instruction set A includes, for example, dietary restrictions, fluid restrictions, and blood glucose management.

[0203] For example, the processing unit 310 of the server system 300 may identify instructions that a doctor has given to a nurse in a particular medical department based on the electronic medical records stored in the electronic medical record server 400, and add those instructions to the instruction set corresponding to that medical department. The processing unit 310 stores the instruction sets for each of the multiple medical departments, and information identifying the specific instructions included in those instruction sets (Figures 17A and 17B), as third data in the storage unit 320. Also, similar to the example of the first data, the processing unit 310 of the server system 300 may identify the instruction set corresponding to a medical department based on expert input related to that medical department.

[0204] Figure 17C shows an example of the fourth data set, which associates the sensors used in the patient behavior determination process with the specific processing content (algorithm) of the determination process. Here, the instruction (patient behavior) refers to individual instructions such as dietary restrictions and water restrictions shown in Figure 17B. For example, if instruction a is dietary restrictions, sensor a is information that identifies the sensor used in the evaluation process of dietary restrictions, and model a is information that identifies the algorithm for the evaluation process of dietary restrictions.

[0205] For example, a method for determining the amount of food consumed and the amount of nutrients based on changes in images taken of the area where tableware is placed before and after a meal is described in U.S. Patent Application No. 18 / 120116, filed on March 10, 2023, titled "INFORMATION PROCESSING SYSTEM AND AN INFORMATION PROCESSING METHOD." This patent application is incorporated by reference in its entirety in this specification. It is also possible to determine the amount of water consumed by taking time-series images of beverage containers such as PET bottles. In this case, the imaging device 700 may be used as a sensor related to dietary and water restrictions. Alternatively, the amount of food and water intake may be determined by placing scales (weighing scales) in the area where food is served and the area where beverage containers are placed. In this case, the scales may be used as sensors related to dietary and water restrictions. Furthermore, the amount of food and water intake may be determined based on changes in weight using a weighing scale. The weighing scale may be a dedicated device or a load sensor provided on the bed 100.

[0206] Furthermore, detecting specific intake amounts is not essential when determining patient behavior related to dietary and fluid restrictions. For example, if an object estimated to be food (dish) is detected by object detection processing on the captured image at a time other than a regular mealtime, the algorithm may omit a specific determination of whether or not the food was consumed and instead estimate that the dietary restriction has been violated. Similarly, in the case of fluid restrictions, instead of specifically detecting changes in the amount of liquid in the beverage container, processing to detect human movement may be performed. For example, the algorithm may detect throat movement based on the captured image and estimate that the fluid restriction has been violated if swallowing is detected a predetermined number of times. Alternatively, the algorithm may estimate that the fluid restriction has been violated if a beverage container is detected from the captured image and swallowing is detected a predetermined number of times. Assuming that the number of swallows is proportional to the amount of fluid intake, the threshold for the number of swallows required to determine a fluid restriction violation can be determined according to the allowable amount of fluid intake. Note that the sensor for detecting swallowing is not limited to the imaging device 700, but may be other sensors such as a throat microphone attached to the throat.

[0207] Furthermore, the algorithm is the same as that for the second data, and may, for example, be data corresponding to the tacit knowledge of an expert. For example, the processing unit 310 or an external learning device may generate a trained model by performing machine learning using the expert's judgment results as training data.

[0208] The output of the algorithm (trained model) is, in a narrow sense, the result of determining whether or not the nurse is following the doctor's instructions (whether or not the patient's behavior is in accordance with the doctor's instructions). Alternatively, the output of the algorithm may be information such as a score representing the degree to which the nurse is following the doctor's instructions.

[0209] <Example Sequence> The processing flow is basically the same as in Figure 14, and the table data described above has been acquired in advance using Figures 17A-17C. The processing unit 310 receives information including the instructions given by the doctor regarding the patient. Next, the processing unit 310 acquires a set of instructions other than those given by the hospital, based on the medical department associated with the patient and the third data described above using Figures 17A and 17B. Furthermore, the processing unit 310 may identify instructions from the doctor that are included in the set of instructions identified based on the third data. Since the set of instructions identified based on the third data is a collection of instructions that are difficult for nurses to grasp, if the instructions actually given by the doctor are included in this set of instructions, those instructions will be information that is difficult for staff to grasp. For each of the instructions that are difficult for staff to grasp, the processing unit 310 identifies the sensor and algorithm to be used for the instruction determination process by referring to the fourth data (Figure 17C).

[0210] The processing unit 310 also displays the contents of one or more identified instructions on the terminal device 600. Figure 18A is an example of an instruction confirmation screen displayed on the display unit 640 of the terminal device 600. The instruction confirmation screen may also be displayed on the display unit 240 of the bedside terminal device 200.

[0211] As shown in Figure 18A, the instruction confirmation screen includes information about the specific instructions from the physician. In the example in Figure 18A, the instruction confirmation screen includes text representing instructions such as "Measure the patient's blood glucose level four times daily," "Adjust the insulin treatment dosage," and "Collaborate with a dietitian to create a meal plan and limit calorie intake." Similar to the evaluation results screen shown in Figure 16, call and share buttons may also be displayed. These buttons allow nurses to confirm the instructions with the physician and share the instructions with other nurses.

[0212] The above is a process that is executed triggered, for example, by a patient's hospitalization, and this selects a set of instructions corresponding to the patient. Next, the processing unit 310 sets up notifications regarding patient behavior by executing the process corresponding to step S103 in Figure 7A or step S204 in Figure 7B. Specifically, it is similar to the example of risk, and the processing unit 310 determines the notification method for each of the multiple patient behaviors based on the set of instructions corresponding to the patient, the team attributes of the work team identified from the work schedule, and the data shown in Figure 13. After that, the processing unit 310 executes the following process when the work team actually performs their duties.

[0213] The processing unit 310 performs a process to activate sensors corresponding to patient behaviors that have been turned on in the notification settings. This makes it possible to acquire sensing data necessary for processing instructions that are difficult for staff to grasp. The sensors acquire sensing data and transmit it to the server system 300.

[0214] The processing unit 310 takes the acquired sensing data as input and performs instruction determination processing according to the algorithm (trained model) identified in the fourth data. The result of this determination processing may be information on whether or not the instruction has been followed, as described above, or it may be information such as a score.

[0215] The processing unit 310 executes a process to display the instruction judgment result on the terminal device 600 used by the staff. This process may be executed when the judgment result satisfies a given condition (for example, when it is determined that the instruction has not been followed). For example, the processing unit 310 pushes information indicating the judgment result to the terminal device 600.

[0216] Figure 18B shows an example of a judgment result screen for instructions displayed on the display unit 640 of the terminal device 600. Here, we consider an example where dietary restrictions and water intake restrictions are set as instructions that are difficult for staff to grasp. Therefore, the judgment result screen includes information that the patient is acting in violation of the dietary and water intake restrictions. Specifically, the judgment result screen may include text indicating that the patient may have eaten or drunk outside of the prescribed limits, a thumbnail of a video image (e.g., an image captured by the imaging device 700) showing the eating or drinking outside of the prescribed limits, and a play button to play the video. For example, the processing unit 310 processes to display a video image of the most recent meal if the intake amount or weight change exceeds a prescribed value, or if it detects eating or drinking outside of the prescribed meal times. Whether or not the video image represents a meal may be determined using the results of object detection such as a plastic bottle or tableware, or other processing may be used. Similar to the instruction confirmation screen shown in Figure 18A, the judgment result screen may also display a call button and a share button.

[0217] 3.5.4 Patient intention The processing unit of the information processing system 10 in this embodiment may perform processing to estimate the cause of the call or the recommended response to the call for the staff, based on the patient's electronic medical record information, the patient's speech content, and the staff's speech content, when a patient makes a call to summon staff (nurse call). Specifically, the processing unit 310 may estimate the cause or response by inputting information (prompts described later) that specifies the electronic medical record information, the patient's speech content, and the nurse's speech content as processing conditions (inputs) and the cause or response content as output into a trained model. The trained model here may be, for example, a model corresponding to generative AI.

[0218] Patient intent (what the patient was thinking when they made a nurse call) can be difficult information for staff to grasp. For example, even if a patient makes a nurse call due to pain or discomfort, various factors such as specific diseases, medication side effects, or mental stress could be contributing to the pain or discomfort, making it difficult for staff to make an appropriate judgment. Furthermore, depending on the patient's condition, such as in the case of dementia, the patient may not be able to adequately verbalize their symptoms. In this respect, the method of this embodiment allows for the estimation of the factors behind a nurse call from the electronic medical record and the content of conversations between the patient and the nurse, thereby appropriately presenting information regarding the patient's intent to the nurse. As a result, it becomes possible to encourage staff to respond appropriately to nurse calls. In addition, as described above, the method of this embodiment can also support staff responses by estimating the recommended response to a call.

[0219] For example, if a patient admitted to the first clinical department is receiving treatment from the second clinical department, and the patient makes a call to summon a nurse from the first clinical department, the processing unit 310 may acquire information including the second risk set (risks that are difficult for nurses to grasp) as electronic medical record information, and estimate the cause or response based on the acquired electronic medical record information. In other words, information including the second risk set may be extracted from the electronic medical record server 400 as electronic medical record information used in the process of estimating the patient's intentions.

[0220] As mentioned above, the second risk set is a collection of risks that can be anticipated in medical departments other than the department to which the staff member belongs. When such risks are the cause of a call, it is difficult for staff members to grasp these risks, making it difficult to identify the cause of the nurse call or to determine the appropriate response. For example, if a patient with asthma is admitted to the ophthalmology department, staff members belonging to the ophthalmology department may not immediately connect a nurse call complaining of coughing with asthma. In this respect, by using electronic medical record information including the second risk set to estimate the cause or response, it becomes possible to present appropriate information that takes into account the staff member's department. In the above example, it becomes possible to draw attention to the link between coughing and asthma from the conversation during the nurse call. The specific processing flow will be explained below.

[0221] First, the call system receives the patient's request to initiate a nurse call. The call system is, for example, a device installed near the bed 100, which includes a microphone to acquire the patient's voice, a speaker to output the staff's voice, and an operating unit to instruct the nurse call to begin. The call system may be a dedicated device, a bedside terminal device 200, or a smartphone used by the patient.

[0222] The call system notifies the server system 300 and the terminal device 600 of the designated staff member that a nurse call has been made. Alternatively, the nurse call notification may first be sent to the server system 300, which then forwards the notification to the designated staff member's terminal device 600. This allows the patient and staff member to initiate a conversation using the call system and the terminal device 600. The processing unit 310 acquires the patient's voice from the call system and the staff member's voice from the terminal device 600.

[0223] The processing unit 310 obtains information contained in the target patient's electronic medical record (hereinafter also referred to as electronic medical record information) from the electronic medical record server 400. Based on the electronic medical record information, patient voice, and staff voice, the processing unit 310 performs processing to estimate the cause of the nurse call and / or the response. Specifically, the processing unit 310 may estimate the cause and response using artificial intelligence (AI). In this case, the processing to estimate the cause and / or the response may be the process of creating a prompt that represents an instruction to the AI.

[0224] For example, a prompt includes the task to be executed by the generating AI, the conditions for executing that task, and the output content. The processing unit 310 sets a scenario in the task field where a patient makes a nurse call, and then sets a task to output the patient's intention in making the nurse call and effective countermeasures (response content). The processing unit 310 also instructs the task to use patient speech (patient voice), staff speech (staff voice), electronic medical record (electronic medical record information), and sensor output (sensing data) for processing. The processing unit 310 also indicates in the output content field that the data to be output by the generating AI is the patient's intention (factor) and countermeasures (response content).

[0225] In the conditions column, patient speech, staff speech, electronic medical records, and sensor output are specifically set. For example, the processing unit 310 adds data that has been converted into text from patient speech using speech recognition processing to the conditions column as "patient speech". The processing unit 310 adds data that has been converted into text from staff speech using speech recognition processing to the conditions column as "staff speech". The processing unit 310 adds electronic medical record information to the conditions column as "electronic medical records". The processing unit 310 adds sensing data acquired from sensors placed around the patient to the conditions column as "sensor output". In this way, the processing unit 310 can automatically create prompts for the generation AI based on the data acquired regarding nurse calls. Note that the input to the generation AI may be the audio file itself, in which case the text conversion by speech recognition processing for at least one of the patient speech and staff speech may be omitted.

[0226] The processing unit 310 inputs the generated prompt to the generating AI to estimate the factors and corresponding content, and transmits the estimation results to the terminal device 600. The display unit 640 of the terminal device 600 displays the received estimation results.

[0227] For example, the server system 300 and terminal device 600 perform the above processing in real time while the patient and staff are conversing. In this way, staff can view the estimated causes and appropriate responses while conversing with the patient, enabling them to take appropriate action in response to nurse calls.

[0228] Figures 19A and 19C show examples of screens displayed on the display unit 640 of the terminal device 600. When a nurse call is notified, the display unit 640 of the terminal device 600 may display information identifying the patient who made the nurse call, as well as some basic information about the patient, as shown in Figure 19A. Figure 19A shows an example where the display unit 640 displays the patient's age, medical history, and sensing data. The display unit 640 may also display two buttons, "Reject" and "Accept," to prompt the staff to decide whether or not to accept the nurse call. If the "Accept" button is selected, a call between the patient and the staff is initiated using the call system and the terminal device 600.

[0229] Figure 19B is an example of a screen displayed on the display unit 640 while a patient and staff member are on a call, before the estimation process by the generating AI. As shown in Figure 19B, the display unit 640 may display data that has been transcribed from the patient's voice and data that has been transcribed from the staff member's voice. The operation unit 650 of the terminal device 600 may also accept correction operations from the staff member on the text data. In the example in Figure 19B, a button labeled "Confirm Action" is displayed, and when this button is selected, the estimation result of the generating AI is displayed. However, the "Confirm Action" button may be omitted, and the estimation result may be displayed on the terminal device 600 once the estimation process by the generating AI is complete.

[0230] Figure 19C shows an example of a screen displaying the estimation results by the generating AI. For example, when the generating AI displays actions, the display unit 640 may display one or more corresponding actions. In the example of Figure 19C, the display unit 640 presents two actions: checking the level of consciousness and administering antihypertensive drugs according to the doctor's instructions. In addition, the estimation process of the processing unit 310 may determine an index representing the likelihood of the estimation result (for example, similarity to past cases), and the actions may be displayed in descending order of the index value. In the example of Figure 19C, the display unit 640 displays action 1 with a similarity of 98 and action 2 with a similarity of 95 in that order.

[0231] In the method of this embodiment, for example, the display of the estimation results shown in Figure 19C may be turned on or off depending on the team attributes of the work team (Figure 13). In this embodiment, not only the display of the estimation results can be turned on or off, but the display of the conversation content shown in Figure 19B may also be set on or off.

[0232] Furthermore, as with the evaluation results screen shown in Figure 16, the screen shown in Figure 19C may also display call buttons and share buttons. The display unit 640 may also switch the presence or absence of the call button depending on the content of the action, such as not displaying the call button when the action can be performed independently by the staff (for example, checking the level of consciousness) and displaying the call button when the action requires instructions from a doctor (for example, administering antihypertensive drugs). For example, the storage unit 320 may store a table that associates actions with whether or not instructions from a doctor are necessary, and the processing unit 310 may send information regarding the presence or absence of the call button associated with the action when sending the estimation results to the terminal device 600. Alternatively, the processing unit 310 may obtain information representing the doctor's instructions from the electronic medical record and determine whether or not the estimated action matches the doctor's instructions. The processing unit 310 may then perform a process to associate the call button with the action and display it if the action and the doctor's instructions do not match (if an action different from the doctor's instructions is recommended). This approach allows staff to seek the doctor's judgment on the feasibility of implementing measures that do not align with the doctor's instructions.

[0233] 3.6 Patient UI As mentioned above, patient wishes can be difficult for staff to grasp. Therefore, the information processing system 10 of this embodiment may provide a patient UI that facilitates input according to the patient's wishes. The patient UI here refers to a patient screen that includes, for example, display objects for presenting information to the patient and display objects for accepting patient operations. The patient screen is displayed, for example, on the display unit 240 of the bedside terminal device 200. Alternatively, the display unit 240 of the bedside terminal device 200 may display a QR code, which is information for displaying the patient screen. When a terminal device used by the patient reads the QR code, the display unit of the terminal device may display the patient screen. The bedside terminal device 200 is provided near the bed 100. If the bed 100, the bedside terminal device 200, and the patient are associated, the bedside terminal device 200 can display a screen suitable for the patient using the corresponding bed 100.

[0234] Figure 20 shows an example of a patient screen, which is a dashboard screen containing links to various items. The patient screen shown in Figure 20 includes buttons corresponding to the following items: "Today's Schedule," "Meal Selection," "Shopping," "Floor Guide," and "Consultation."

[0235] Figure 21 is an example of a patient screen that appears when the "Today's Schedule" option is selected on the dashboard screen shown in Figure 20. As shown in Figure 21, the patient screen here includes information representing the patient's daily schedule. As described above, this example assumes that the correspondence between bed 100, bedside terminal device 200, and patient has been completed. Therefore, the bedside terminal device 200, or a terminal device that reads the QR code on the bedside terminal device 200, can identify the target patient and display that patient's schedule.

[0236] In the example shown in Figure 21, the patient screen includes information about patient-related events such as vital sign measurement, blood sampling and examination, and lunch, as well as the time of these events. The patient screen may also display details and precautions related to the events. For example, the patient screen may display vital sign information related to vital sign measurement. The patient screen may also display information about meals and fluid restrictions before blood sampling related to blood sampling and examination. Furthermore, if medication is required, the patient screen may display information indicating the type of medication.

[0237] Furthermore, the patient screen may include links to more detailed information. For example, the patient screen in Figure 21 may only display the name of the medication as information associated with lunch, and when the patient selects a link, it may display detailed information such as the shape of the medication, dosage, and efficacy. The detailed information may be displayed by transitioning to a different screen from Figure 21, or it may be displayed as a pop-up. By presenting the schedule to the patient in an easy-to-understand manner in this way, the patient's questions can be resolved, thus reducing the frequency of nurse calls. The ability to display link information is also applicable to other events such as vital sign measurement, blood sampling, and medical examinations.

[0238] The link information here may also be information for executing a nurse call. For example, when a link information selection operation is performed, a call is initiated between the bedside terminal device 200 or the patient's terminal device and the staff's terminal device 600. At this time, the bedside terminal device 200 or the patient's terminal device may send the event associated with the link information to the staff's terminal device 600. For example, when a link information associated with "lunch" is selected, the staff's terminal device 600 will first indicate that it is an inquiry regarding "lunch" for patient "AAAA" before initiating the call. By making nurse calls associated with specific events in this way, it becomes easier for staff to understand the patient's wishes.

[0239] Figure 22 is an example of a patient screen displayed when the "Meal Selection" operation is performed on the dashboard screen of Figure 21. As shown in Figure 22, the patient screen includes multiple menus and information such as photos showing specific menu items. When any menu is selected, the bedside terminal device 200 or the patient's terminal device associates the patient "AAAA" with the selection result and transmits it to an external device. The recipient device may be a staff terminal device 600. In this way, the staff can easily see which menu the patient prefers, i.e., the patient's wishes regarding meals. Alternatively, the selection result may be transmitted to equipment used by the kitchen staff in the dining hall. In this case, medical staff such as nurses and caregivers do not need to communicate meal preferences to the kitchen staff, thus reducing their workload. Note that Figure 22 illustrates a patient screen for selecting a single meal menu, but the screen used for meal selection is not limited to this. For example, the patient screen may be a screen for selecting multiple meals on a daily or weekly basis. Alternatively, the patient screen may not be limited to selecting all items on the menu, but could be a screen that only allows selection of the main dish, such as bread or rice. Furthermore, various variations of the screen used for meal selection are possible.

[0240] The menu displayed here may vary depending on the patient's condition. For example, the processing unit 310 of the server system 300 may display different menus on the display unit of the bedside terminal device 200 or the like, depending on whether the patient is subject to dietary restrictions or not. If it is determined that the patient is not allowed to select a menu due to dietary restrictions, etc., the processing unit 310 may perform a process that prevents the display of the patient screen shown in Figure 22 (prevents screen transitions) even if the "Select Meal" operation is performed on the dashboard screen. Alternatively, the processing unit 310 may omit the display of the object corresponding to "Select Meal" on the dashboard screen. Alternatively, the processing unit 310 may display a menu on the display unit of the bedside terminal device 200 or the like, according to the patient's swallowing ability.

[0241] Figure 23 is an example of a patient screen that appears when the "Shopping" option is selected on the dashboard screen shown in Figure 21. As shown in Figure 23, the patient screen includes information on products available for purchase by the patient, information on selected products (cart contents), and payment method selection buttons. The products here are, for example, products from a store within the medical facility, but they could also be products from an external e-commerce (electronic commerce) site.

[0242] When a purchase is made with items in the cart, the bedside terminal 200 or the patient's terminal device associates the patient "AAAA" with the purchased items and transmits the information to an external device. The recipient device may be a staff member's terminal device 600. This makes it easy for staff to see which items the patient wishes to purchase. Alternatively, the selection results may be transmitted to a device used by the shop staff. In this case, medical staff such as nurses and caregivers do not need to communicate the purchase preferences to the shop staff, thus reducing their workload.

[0243] In recent years, electronic payments using QR codes have become widely used. Therefore, in this embodiment, the display unit 240 of the bedside terminal device 200 or the like may display a QR code for electronic payment. For example, when the patient's terminal device reads the QR code, a QR code payment application may be launched, and payment may be made in the same way as for general shopping. The QR code payment application here may be an application for using a widely used payment platform, or it may be an application for using a system-specific service according to this embodiment. In this way, there is no need to prepare cash or prepaid cards, thus reducing the burden on the patient.

[0244] Figure 24 is an example of a patient screen that appears when the "Floor Map" option is selected on the dashboard screen shown in Figure 21. As shown in Figure 24, the patient screen includes a map of the medical facility. The map displayed here is, in a narrow sense, a map of the floor where the patient resides, but it may also display information about other floors, including places used by many patients, such as the dining hall, shop, and rehabilitation room.

[0245] Furthermore, patients who have not been hospitalized for long may not have sufficient information about their hospital floor. Therefore, the floor map shown in Figure 24 is useful information for such patients. Accordingly, the processing unit 300 may display information representing hospitalization guidelines and explanations on the patient screen, which includes the floor map. Alternatively, the processing unit 300 may display information for renting an inpatient set, which includes items necessary for hospitalization such as clothing, towels, and daily necessities, on the patient screen, which includes the floor map. The rental of the inpatient set may be displayed on a screen that includes a QR code for electronic payment, similar to the patient screen described above using Figure 23. In this way, it becomes possible to determine the patient based on the time elapsed since hospitalization and present information that is considered necessary for patients who have recently been hospitalized.

[0246] Figure 25 is an example of a patient screen displayed when the "Consultation" option is selected on the dashboard screen shown in Figure 21. As shown in Figure 25, the patient screen includes an area for entering the content of the inquiry to the staff, an area for displaying an object for selecting a consultation partner, and an area for entering the patient's name. After the patient has entered the information for each item, pressing the send button causes the bedside terminal device 200, etc., to send information indicating the consultation content to the server system 300. The destination of the consultation content may also be the terminal device 600 of the staff member selected as the consultation partner. In this way, the patient can specify a particular person to consult with before conducting the consultation, making it easier to communicate the patient's wishes to the staff.

[0247] For example, in step S201 of this embodiment, the processing unit 310 may determine, using Figure 25, whether or not a consultation specifying a particular staff member has been sent to the server system 300 based on the patient screen described above. If a consultation specifying a staff member is registered in the server system 300, the processing unit 310 determines that a change to the work schedule is necessary (step S201: Yes).

[0248] The processing unit 310 modifies the work schedule to assign a specific nurse or caregiver to work as soon as possible if that nurse or caregiver is specified in the patient's consultation. For example, in step S202, the processing unit 310 sets the range of modification to the specified number of days from tomorrow onwards and updates the work schedule. The processing unit 310 first determines the values ​​to assign the staff member to work on the earliest possible date and time from tomorrow onwards, based on the information of the specified staff member (see Figure 9). Subsequent processing is the same as in the example described above; for example, the processing unit 310 determines the values ​​of each cell in the work schedule in order of the degree of constraint for the staff member. After updating the work schedule, the processing unit 310 performs addition verification processing, notification setting determination processing, and work assignment table update processing, as in the example described above (steps S203-S205 in Figure 7B).

[0249] In this way, based on the patient's actions on the interface for inputting the patient's wishes, if the processing unit 310 obtains a patient's wish to be handled by the first staff member, it adds a fourth condition to the set of conditions, which is to prioritize the dispatch of the first staff member designated by the patient, and then executes an automated creation process for the second period. In this way, when a patient's wish is registered, it becomes possible to appropriately reflect that wish in the work schedule.

[0250] 4. Time Study Traditionally, a method of conducting workload surveys (time studies) to improve operational efficiency has been known. By conducting workload surveys, it becomes possible to visualize when, who, what tasks, and to what extent they are being performed.

[0251] For example, in this embodiment, the automatic creation process of the work schedule is performed as described above. The processing unit 310 may determine whether or not to conduct a workload survey based on the contents of the work schedule. For example, once the work schedule is created, it becomes possible to determine how many staff members will be working in each time slot, and for each staff member, whether they are full-time / part-time, whether or not they have caregiver qualifications, etc. For example, the processing unit 310 may determine whether or not the staff's work patterns determined from the work schedule are appropriate, that is, whether or not a workload survey is unnecessary.

[0252] Figure 26A is a flowchart illustrating the learning process. When this process begins, in step S501, for example, the processing unit 310 of the server system 300 acquires information such as the work performance of staff at other medical facilities, facility type, number of users, level of care required, and usage status of ICT (Information and Communication Technology) equipment. Facility type refers to information such as whether it is a conventional type or a unit type.

[0253] In step S502, the processing unit 310 obtains correct data indicating whether or not the work record at other medical facilities is appropriate.

[0254] The correct data here may be determined based on whether or not additional personnel were added on a spot basis at the facility in question. If additional personnel were added, it means that the work schedule at the planning stage was inappropriate, so the processing unit 310 sets the correct data to a value that indicates the work pattern was inappropriate (e.g., "0"). If no additional personnel were added, it means that the work was carried out smoothly based on the work schedule at the planning stage, so the processing unit 310 sets the correct data to a value that indicates the work pattern was appropriate (e.g., "1"). The processing unit 310 may also set the correct data to a value between 0 and 1 depending on the degree to which additional personnel were added.

[0255] Alternatively, the above correct answer data may be determined based on the patient's condition (ADL, degree of care required) and the skills of the nurse / caregiver. For example, the processing unit 310 may determine a first index value representing the skills of the staff required based on the patient's condition, and a second index value representing the skills of the staff who actually worked. The processing unit 310 sets the value of the correct answer data to a value closer to "1" the lower the degree of discrepancy between the first index value and the second index value.

[0256] Alternatively, the above correct answer data may be determined based on information regarding staff turnover and / or the health status of staff. For example, the processing unit 310 sets the value of the correct answer data to a value closer to "1" the lower the number of staff who have left the company or the lower the ratio of staff who have left to the total number of staff. The processing unit 310 also sets the value of the correct answer data to a value closer to "1" the lower the degree of staff leave due to illness or injury. This is because a lower number of staff turnover or fewer sick leave cases indicates that the workload is appropriate.

[0257] In step S503, the processing unit 310 creates a trained model based on the above training data. The trained model here may be a model that outputs appropriate work patterns (for example, the appropriate number of people for each of the early shift, day shift, late shift, and night shift) when the facility type, number of users, level of care required, and usage of ICT equipment are input. Alternatively, the trained model may be a model that outputs an index value indicating whether or not the work pattern is appropriate when the facility type, number of users, level of care required, usage of ICT equipment, and work schedule are input.

[0258] In step S504, the processing unit 310 stores the trained model in the storage unit 320. Although the above describes an example in which the processing unit 310 performs the training process, the training process may be performed on a training server different from the server system 300.

[0259] Furthermore, when a work schedule is created, the processing unit 310 uses a trained model to estimate whether the work patterns identified from the work schedule are appropriate (i.e., whether a workload survey is necessary).

[0260] FIG. 26B is a flowchart for explaining inference processing using a learned model. In step S601, the processing unit 310 acquires the work schedule created in step S101 of FIG. 7A or step S202 of FIG. 7B.

[0261] In step S602, the processing unit 310 acquires the facility type, number of users, degree of care required, and usage status of ICT devices of the target medical facility. For example, the processing unit 310 may acquire this information from the electronic medical record server 400, or may acquire it from another device such as the management server of the medical facility.

[0262] In step S603, the processing unit 310 inputs the acquired information into the learned model. In step S604, the processing unit 310 determines whether the work status for each day determined from the work schedule is appropriate based on the output of the learned model. If the output of the learned model is the probability that the work status is appropriate, the processing unit 310 determines whether the output value is less than or equal to a given threshold. If the output of the learned model is the appropriate number of staff in each time period, the processing unit 310 determines whether the degree of deviation between the output value and the value in the work schedule is greater than or equal to a predetermined value.

[0263] If there is a day determined to have an inappropriate work status from the work schedule (step S604: Yes), in step S605, the processing unit 310 outputs a recommendation to conduct a workload survey. For example, when the number of staff in the medical facility to be determined is large compared to the data of another facility, the processing unit 310 proposes to conduct a workload survey.

[0264] In step S605, the processing unit 310 may change the content of the workload survey according to the specific situation. For example, if the number of staff in the medical facility to be determined is large compared to the data of other facilities and the ICT devices are not used in the target medical facility, the processing unit 310 may propose a time study survey for the items corresponding to the ICT devices. Alternatively, if there are more staff than necessary arranged during the early shift time period, the processing unit 310 may propose a time study for cause identification. For example, the processing unit 310 performs a process of determining the execution period and the target staff of the application for conducting the workload survey. Specifically, the processing unit 310 targets the days when the number of early shift staff is determined to be excessive, and executes a process of operating an application for workload survey on the terminal device 600 of the staff working in the early shift on the target day.

[0265] If there are surplus staff by time period, the processing unit 310 may not only propose to conduct a workload survey, but also propose to modify the work schedule. For example, if the early shift is excessive, the processing unit 310 may propose adding one person to the late shift and reducing two people from the early shift.

[0266] Figures 27A and 27B are examples of the display screens of the workload survey application. The workload survey application may operate on the terminal device 600 of the staff. Figure 27A is a selection screen for business content. Here, the business in the medical facility is classified into a plurality of groups (genres), and each group includes a plurality of businesses. An example of the business group and the businesses included in each group is as follows. The processing unit 610 of the terminal device 600 starts measuring for the selected business from the moment any business is selected on the screen shown in Figure 27A.

[0267] · Group of excretion, bathing, and cleaning Excretion assistance, diaper / pad replacement, bathing preparation, bathing assistance, dressing, grooming, and oral care · Movement assistance group Position change and transfer, waking and bedtime care, movement and guidance · Meal group Meal preparation and cleanup, meal assistance and hydration • Pharmaceutical and drug dispensing group Medication preparation, medication assistance, vital sign checks ·communication Conversations with users and their families, and handling of problems.

[0268] Figure 27B shows an example of a screen that the workload survey application displays on the display unit while measuring work time. As shown in Figure 27B, the display screen includes text indicating that measurement is in progress, the measurement time, and text indicating the work item being measured. The display screen in Figure 27B may also include the text, "Swipe to display buttons and switch tasks." By swiping the screen from bottom to top while using the terminal device 600, the display unit 640 can display a work screen (for example, Figure 27A).

[0269] Figure 28 shows an example of a report screen displayed based on the measurement results from each terminal device 600. The report screen may be displayed on, for example, an unillustrated display unit of the server system 300, or on a display unit of a device in a medical facility such as a station terminal device 500. The report screen includes an area R202 that displays basic information, an area R204 that displays the total work time, work time by category, and step count, and an area R206 that displays the work time and step count for each individual work item.

[0270] As shown in Figure 28, a report showing the results of a workload survey may include a comparative report that displays multiple data sets in a comparable manner. For example, if there are two survey subjects, the first and second, area R202 in the comparative report includes basic information for both the first and second survey subjects. Area R204 displays the total work hours, work hours by category, and step count information for both the first and second survey subjects side by side. Area R206 displays the work hours and step counts for both the first and second survey subjects side by side for each work item. In this way, when there are multiple survey subjects, the survey results can be output in a manner that makes comparison easy.

[0271] For example, the first survey target mentioned above could be the medical facility that created the work schedule, while the second survey target could be any other medical facility. In this way, it becomes possible not only to conduct a workload survey at the target medical facility, but also to present the results of comparisons with other medical facilities to the user in an easy-to-understand manner.

[0272] The processing unit 310 may also display the devices used in other medical facilities for comparison, as well as the operating status of those devices. For example, if there are devices used in other medical facilities with high operational efficiency, the processing unit 310 may propose the installation of those devices in the medical facility being processed. The processing unit 310 may also propose operating settings for the devices to be installed based on the operating status of the devices in other medical facilities.

[0273] The above describes an example of determining whether a work schedule is appropriate based on a trained model created using information from other medical facilities. However, machine learning is not essential in this embodiment. Furthermore, while the above describes an example of determining whether a workload survey is necessary based on a work schedule, the method is not limited to this, and the necessity of conducting a workload survey may be determined based on actual work performance.

[0274] Although this embodiment has been described in detail above, it will be readily apparent to those skilled in the art that many modifications are possible without substantially departing from the novel aspects and effects of this embodiment. Therefore, all such modifications are included within the scope of this disclosure. For example, any term that appears at least once in the specification or drawings together with a broader or synonymous term may be replaced with that different term anywhere in the specification or drawings. Furthermore, all combinations of this embodiment and its modifications are also included within the scope of this disclosure. In addition, the configuration and operation of the information processing system, bed, bedside terminal device, server system, terminal device, etc., are not limited to those described in this embodiment, and various modifications are possible. [Explanation of Symbols]

[0275] 10... Information processing system, 100... Bed, 110... Processing unit, 120... Memory unit, 130... Communication unit, 140... Operation unit, 150... Drive unit, 160... Movable unit, 170... Mattress, 200... Bedside terminal device, 210... Processing unit, 220... Memory unit, 230... Communication unit, 240... Display unit, 250... Operation unit, 260... Notification unit, 270... Interface unit, 300... Server system, 310... Processing unit, 320... Storage unit, 330... Communication unit, 400... Electronic medical record server, 500... Station terminal device, 600... Terminal device, 610... Processing unit, 620... Storage unit, 630... Communication unit, 640... Display unit, 650... Operation unit, 700... Imaging device, 810... Detection device, 820... Measurement device, 830... Authentication card, R202, R204, R206... Area

Claims

1. A processing unit that performs automatic work schedule creation processing for a facility that provides patient care, based on conditions including at least one of the following: a first condition regarding the number of staff members for each work period, a second condition based on prohibited shifts, and a third condition regarding the combination of staff members. A storage unit for storing the aforementioned work schedule, Includes, The aforementioned processing unit, For a work team consisting of multiple staff members determined to be working simultaneously during a given time period by the aforementioned automatic creation process, it is determined, based on information that associates staff members with their skill levels, which of the multiple team attributes the team possesses includes a first team attribute that includes staff members with a skill level below a predetermined level, and a second team attribute that does not include staff members with a skill level below a predetermined level. Based on the team attributes, a setting process is performed to set the execution conditions for notification processing regarding the patient during the working hours of the work team. An information processing system that, when it is determined that the frequency of the notification process is above a given threshold, causes the display unit to display at least one of either a first display prompting the correction of the work schedule or a second display prompting the correction of the execution conditions.

2. In the information processing system described in claim 1, The aforementioned notification process is: An information processing system including at least one of the following processes: a risk notification process for notifying the patient of risks related to the patient; a patient behavior notification process for monitoring the patient's behavior based on physician's instructions; and a patient will notification process for notifying the results of interpreting the patient's will.

3. In the information processing system described in claim 2, The aforementioned processing unit, An information processing system that performs the setting process based on data that associates a medical department with a risk set representing the risks of the patient related to the medical department, such that the degree of notification of risks related to the first medical department, to which the staff member belongs, is lower than the degree of notification of risks related to the second medical department, which is different from the first medical department.

4. In the information processing system described in claim 2, The aforementioned processing unit, An information processing system that performs the setting process based on data that associates a clinical department with a set of instructions representing instructions given by a physician in the clinical department to the staff, such that the level of notification regarding instructions associated with the first clinical department, to which the staff member belongs, is lower than the level of notification regarding instructions related to a second clinical department, which is different from the first clinical department.

5. In the information processing system according to any one of claims 1 to 4, The aforementioned processing unit, For each of the multiple staff members, the degree of constraints on their work is determined based on at least one of the following: the number of days, days of the week, and time slots they can work. An information processing system that performs the automatic creation process of the work schedule by determining the work schedule based on the conditions, starting with the staff members who are determined to have the highest degree of constraint.

6. In the information processing system described in claim 5, The aforementioned processing unit, An information processing system that, after creating the aforementioned work schedule for a given first period, determines that a change to the work schedule is necessary, performs an update process by re-executing the automatic creation process for a second period, which is part of the first period.

7. In the information processing system described in claim 6, The aforementioned processing unit, If, based on the patient's actions on the interface for inputting the patient's wishes, the patient's intention to be handled by the first staff member is obtained, An information processing system that adds a fourth condition to the conditions, which is to prioritize the attendance of the first staff member designated for the patient, and then executes the automated creation process for the second period.

8. Information processing system, Based on conditions including at least one of the following:

1. Conditions regarding the number of staff working in each shift period; 2. Conditions based on prohibited shifts; and 3. Conditions regarding staff combinations, an automated process for creating work schedules in facilities that provide patient care is performed. For a work team consisting of multiple staff members determined to be working simultaneously during a given time period by the aforementioned automatic creation process, it is determined, based on information that associates staff members with their skill levels, which of the multiple team attributes the team possesses includes a first team attribute that includes staff members with a skill level below a predetermined level, and a second team attribute that does not include staff members with a skill level below a predetermined level. Based on the team attributes, a setting process is performed to set the execution conditions for notification processing regarding the patient during the working hours of the work team. If it is determined that the frequency of the notification process is above a given threshold, the display unit will prompt at least one of the following: a first display prompting the correction of the work schedule, or a second display prompting the correction of the execution conditions. An information processing method that performs processing.

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