Program, information processing device, and information processing method

Abstract

To provide a program and the like that allow recognition of a plurality of outcomes of interventions.SOLUTION: A program causes a computer to execute the processing of: obtaining a plurality of intervention item values and a plurality of outcome values of a target person and a non-target person; and outputting a graph indicating each intervention item value of the target person and non-target person for each outcome with a plurality of intervention items as axes, based on each of the obtained intervention items and outcome values.SELECTED DRAWING: Figure 6

Description

Technical Field

[0001] The present invention relates to a program, an information processing apparatus, and an information processing method.

Background Art

[0002] In the clinical field, various intervention guidances and treatments are performed to improve the outcomes of patients. Methods for evaluating such outcomes have been proposed.

[0003] For example, Patent Document 1 discloses a method useful for characterizing the clinical outcomes of a subject. According to the technique of Patent Document 1, it is described that it is possible to improve the labeling of key drugs through adaptive clinical studies published for the expansion of markers of new symptoms, patient subpopulations, and improvement of concerns regarding safety.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The technique described in Patent Document 1 simply evaluates one type of outcome. There are multiple types of outcomes in patients, and their values change independently with respect to the intervention. In considering outcomes, it is important to take into account those multiple outcomes. At present, a technique capable of recognizing multiple outcomes with respect to an intervention has not yet been realized.

[0006] An object of the present disclosure is to provide a program or the like capable of recognizing multiple outcomes with respect to an intervention.

Means for Solving the Problems

[0007] A program according to one aspect of this disclosure acquires multiple intervention item values ​​and multiple outcome values ​​for both target and non-target individuals, and causes a computer to execute a process that outputs a graph showing the respective intervention item values ​​for both target and non-target individuals, with each outcome centered on the multiple intervention items.

[0008] An information processing device according to one aspect of this disclosure includes a control unit that acquires multiple intervention item values ​​and multiple outcome values ​​for subjects and non-subjects, and based on the acquired intervention item values ​​and outcome values, outputs a graph for each outcome showing the multiple intervention items as axes for the subjects and non-subjects.

[0009] An information processing method according to one aspect of this disclosure involves a computer that acquires multiple intervention item values ​​and multiple outcome values ​​for both target and non-target individuals, and then, based on the acquired intervention item values ​​and outcome values, outputs a graph for each outcome showing the multiple intervention items as axes for both target and non-target individuals. [Effects of the Invention]

[0010] According to this disclosure, multiple outcomes for the intervention can be identified. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic diagram of the information processing system according to the first embodiment. [Figure 2] This figure shows an example of the content of information stored in the analysis database. [Figure 3] This diagram illustrates a graph showing the relationship between intervention item values ​​and outcome values. [Figure 4] This is a schematic diagram showing an example of the analysis screen. [Figure 5] This is a schematic diagram showing an example of the analysis screen. [Figure 6] This flowchart shows an example of the processing steps involved in generating a graph. [Figure 7] It is a flowchart showing an example of a processing procedure regarding reception of crossbar operation. [Figure 8] It is a schematic diagram showing an example of an analysis screen in the second embodiment. [Figure 9] It is a schematic diagram showing an example of an analysis screen in the second embodiment. [Figure 10] It is a schematic diagram showing an example of an analysis screen in the second embodiment. [Figure 11] It is a flowchart showing an example of a processing procedure executed by the information processing system in the second embodiment. [Figure 12] It is a schematic diagram showing an example of an analysis screen in the third embodiment. [Figure 13] It is a flowchart showing an example of a processing procedure executed by the information processing system in the third embodiment. [Figure 14] It is a schematic diagram showing an example of an analysis screen in the fourth embodiment. [Figure 15] It is a flowchart showing an example of a processing procedure executed by the information processing system in the fourth embodiment. [Figure 16] It is a schematic diagram showing an example of an analysis screen in the fifth embodiment. [Figure 17] It is a flowchart showing an example of a processing procedure executed by the information processing system in the fifth embodiment.

Embodiments for Carrying Out the Invention

[0012] Specific examples of a program, an information processing apparatus, and an information processing method according to an embodiment of the present invention will be described below with reference to the drawings. Note that the present invention is not limited to these examples, and is defined by the claims, and is intended to include all modifications within the meaning and scope equivalent to the claims. Also, at least a part of each of the embodiments described below may be arbitrarily combined. Note that the sequences shown in each of the embodiments described below are not limited, and within a non - contradictory range, the order of each processing procedure may be changed and executed, or a plurality of processes may be executed in parallel. The subject of each process is not limited, and within a non - contradictory range, the processing of each device may be executed by another device.

[0013] (First Embodiment) FIG. 1 is a schematic diagram of an information processing system 100 according to the first embodiment. The information processing system 100 includes an information processing device 1 and a plurality of information terminal devices 2. The information processing device 1 and the information terminal devices 2 are communicatively connected to a network N such as the Internet, and can transmit and receive data via the network N.

[0014] The information processing device 1 is a device capable of various information processing and information transmission and reception, such as a server computer, a personal computer, a quantum computer, etc. The information processing device 1 outputs information indicating a plurality of outcomes for an intervention in response to an inquiry from the information terminal device 2. The information terminal device 2 is, for example, a personal computer, a smartphone, a tablet terminal, etc. The information terminal device 2 is installed, for example, within a facility such as a hospital or a testing institution and is used by medical staff such as doctors. The information terminal device 2 can transmit and receive data to and from the information processing device 1 via communication.

[0015] Regarding the processing content implemented in the information processing system 100 configured as described above, below, a specific example of application for improving the outcome of an intervention for a type 2 diabetes patient as the target person will be given and described. Note that the target person is not limited to a type 2 diabetes patient, and may be, for example, a patient with lifestyle - related diseases, cancer, or other diseases, or a person engaged in disease prevention, a person engaged in improving lifestyle habits, a subject undergoing an examination, etc.

[0016] As shown in Figure 1, the information processing device 1 comprises a control unit 11, a storage unit 12, and a communication unit 13. The information processing device 1 may be a multicomputer consisting of multiple computers, or it may be a virtual machine virtually constructed by software.

[0017] The control unit 11 includes a processor using one or more CPUs (Central Processing Units), GPUs (Graphics Processing Units), etc. The control unit 11 uses built-in memory such as ROM (Read Only Memory) or RAM (Random Access Memory), a clock, counters, etc., to control each component and execute processing.

[0018] The storage unit 12 includes non-volatile memory such as a hard disk, flash memory, or SSD (Solid State Drive). The storage unit 12 may also be an external storage device connected to the information processing device 1. The storage unit 12 stores programs and data referenced by the control unit 11. The programs stored in the storage unit 12 include a program 1P that causes the computer to perform processing related to the output of information indicating multiple outcomes for an intervention. The storage unit 12 also stores an analysis DB (Data Base) 121. Details of the analysis DB 121 will be described later.

[0019] The program (program product) stored in the storage unit 12 may be recorded on a recording medium in a manner that is computer-readable. The storage unit 12 stores the program read from the recording medium 1A by a reading device (not shown). Alternatively, the program may be downloaded from an external computer (not shown) connected to a communication network (not shown) and stored in the storage unit 12.

[0020] The communication unit 13 includes a communication module for communicating with external devices via the network N. The control unit 11 sends and receives data to and from the information terminal device 2 via the communication unit 13.

[0021] The configuration of the information processing device 1 is not limited to the example described above, and may include, for example, an operation unit for receiving user input, a display unit for displaying various types of information, and so on.

[0022] The information terminal device 2 comprises a control unit 21, a storage unit 22, a communication unit 23, a display unit 24, and an operation unit 25.

[0023] The control unit 21 includes one or more processors, such as CPUs and GPUs. The control unit 21 uses built-in memory such as ROM or RAM, a clock, counters, etc., to control each component and execute processing.

[0024] The storage unit 22 includes non-volatile memory such as a hard disk, flash memory, or SSD. The storage unit 22 stores programs and data referenced by the control unit 21. The programs stored in the storage unit 22 include a program 2P that causes the computer to execute processes related to outcome acquisition. The programs stored in the storage unit 22 may be recorded on a recording medium in a manner that is computer-readable. The storage unit 22 stores programs read from the recording medium 2A by a reading device (not shown). Alternatively, programs may be downloaded from an external computer (not shown) connected to a communication network (not shown) and stored in the storage unit 22.

[0025] The communication unit 23 is a communication module for performing communication-related processing. The control unit 21 sends and receives data to and from the information processing device 1 via the communication unit 23.

[0026] The display unit 24 includes a display device such as a liquid crystal display or an organic electroluminescent (EL) display. The display unit 24 displays various information according to instructions from the control unit 21. The operation unit 25 is an interface that receives user input. The operation unit 25 includes, for example, a keyboard, a touch panel device with a built-in display, a speaker, and a microphone. The operation unit 25 receives operation input from the user and sends control signals to the control unit 21 according to the operation content.

[0027] Figure 2 shows an example of the information stored in the analysis DB121. The analysis DB121 is a database that stores data on intervention guidance for multiple patients (non-target individuals) and is used for outputting outcome data. The analysis DB121 stores records that link information such as patient IDs, characteristics, details, intervention item values, and outcome values ​​to a key, such as an analysis ID to identify the analysis data.

[0028] The characteristics column contains information about the patient's characteristics related to the patient ID. These characteristics are used to classify the characteristics into groups, as described later. Characteristics include, for example, the patient's gender and eating patterns. Eating patterns are information about the patient's diet and can be classified into several categories. Examples of eating patterns include home cooking, eating out, and prepared food consumption. The information that can be considered a characteristic is not limited to the examples above and may include any information used to classify the characteristics into groups, as described later.

[0029] The details column contains details about the patient associated with the patient ID. These details may include information about the patient's diet (e.g., eats three meals a day, eats a lot of fish, etc.) and information about interventions (e.g., exercises daily, goes to the gym, etc.).

[0030] The intervention item value column contains values ​​for multiple intervention items for the patient associated with the patient ID. In the example shown in Figure 2, the intervention item values ​​include exercise volume, calorie intake, and steps taken. The intervention item values ​​are not limited to the example above and may be set as appropriate depending on the type of disease and the target outcome. Intervention items may also include aerobic exercise time, anaerobic exercise time, sleep time, etc.

[0031] The outcome value column contains outcome values ​​for patients associated with a patient ID. Multiple types of outcomes are included, and evaluation values ​​are stored for each type of outcome. In the example shown in Figure 2, the outcome values ​​include blood glucose level, nutritional status, and time to dropout. The possible outcome values ​​are not limited to the example above and may be set appropriately depending on the type of disease and the objective of improvement.

[0032] Blood glucose levels may include, for example, HbA1c (hemoglobin A1c). Nutritional status is a value that indicates information about the patient's nutritional status and may include, for example, scores using the three-group scoring system, blood vitamin concentrations, etc. The time to dropout is information that indicates the degree of dropout, specifically the time until a patient drops out of intervention guidance for lifestyle improvement. The degree of dropout may also be indicated by the dropout rate, etc.

[0033] The information processing device 1 collects the state of multiple existing patients during interventions and the outcomes of those interventions, and stores them as big data in the analysis DB 121. The analysis DB 121 may store multiple data for the same patient. For example, each time a patient's characteristics change, new data is added to the analysis DB 121. The individuals whose data is stored in the analysis DB 121 (non-target individuals) are not limited to patients suffering from a disease, but may also include individuals working to prevent the disease, individuals working to improve their lifestyle, and individuals undergoing examinations. Furthermore, the analysis DB 121 may store not only data for non-target individuals, i.e., other patients other than the target patients, but also past data for the target patients. The information processing device 1 uses the analysis DB 121 to output the outcomes of the interventions for the patients being evaluated (hereinafter also referred to as target patients).

[0034] The outcomes of an intervention vary from patient to patient. Among multiple patients, those with similar intervention item values ​​are likely to exhibit similar outcome behaviors. Based on these findings, the inventors conceived the idea of ​​using a graph (map) to represent the relationship between intervention item values ​​and outcome values. Furthermore, they discovered that by generating graphs for each type of outcome and linking them together, multiple outcomes can be evaluated in an integrated manner.

[0035] Figure 3 illustrates a graph showing the relationship between intervention item values ​​and outcome values. Using Figure 3, we will specifically explain the graph showing the relationship between intervention item values ​​and outcome values ​​in this embodiment, as well as the procedure for generating it. Below, as an example, we will explain the case where exercise volume and calorie intake are used as intervention items, and a graph showing the relationship with HbA1c as the outcome is generated.

[0036] When evaluating outcomes, the information processing device 1 acquires intervention item values ​​and characteristics of the target patient via the information terminal device 2. For example, the information processing device 1 may acquire intervention item values ​​and characteristics entered by a healthcare professional via the information terminal device 2. Alternatively, the information processing device 1 may acquire some or all of the intervention item values ​​and characteristics by linking with a medical record system that manages patient data. In this case, the information processing device 1 receives target patient identification information (e.g., patient ID) via the information terminal device 2 to identify the target patient. The information processing device 1 acquires the intervention item values ​​and characteristics of the target patient identified by the received target patient identification information by referring to the medical record data stored in the medical record system.

[0037] The information processing device 1 obtains intervention item values ​​and outcome values ​​for multiple other patients (hereinafter also referred to as the patient group) other than the target patient, based on the information stored in the analysis DB 121.

[0038] The information processing device 1 classifies the patient data read from the analysis DB 121 into multiple characteristic groups according to the characteristics of each patient. In this embodiment, as an example, characteristic groups are constructed based on dietary patterns and gender. Examples of characteristic groups include a self-cooking male group (where the patient primarily cooks at home and is male), a dining-out male group (where the patient primarily eats out and is male), a self-cooking female group (where the patient primarily cooks at home and is female), and a dining-out female group (where the patient primarily eats out and is female). The information processing device 1 classifies the patient group into each characteristic group according to the dietary patterns and gender of each patient stored in the analysis DB 121. The method for classifying patients is not limited, and known clustering methods may be used for classification.

[0039] Patient characteristics such as dietary patterns and gender significantly influence intervention item values. Therefore, outcomes vary considerably depending on the characteristic group. In this embodiment, by evaluating outcomes while considering such individual patient characteristic groups, it becomes possible to provide information that is more in line with the patient's actual situation. Note that characteristic groups are not limited to those based on dietary patterns and gender; groups may be appropriately formed based on factors that influence intervention item values, such as exercise status and food preferences.

[0040] The information processing device 1 extracts data from patient groups belonging to the same characteristic group as the target patient. For example, if the target patient's characteristics are that they primarily cook for themselves and are male, the information processing device 1 extracts data only from patient groups belonging to the male self-cooking group.

[0041] The information processing device 1 acquires outcome values ​​for the intervention item values ​​of the target patient. The information processing device 1 calculates outcome values ​​for each combination of intervention items selected from among multiple intervention items and for each type of outcome. Note that a predetermined combination of intervention items may be defined as the initial setting for acquiring outcome values. In the following example, the information processing device 1 uses exercise volume and calorie intake as intervention items.

[0042] The information processing device 1 estimates outcome values ​​for the target patient's exercise volume and calorie intake based on the target patient's exercise volume and calorie intake, and the exercise volume, calorie intake, and outcome values ​​of the extracted patient group. Specifically, the information processing device 1 identifies outcome values ​​of patients with exercise volume and calorie intake that approximate the target patient's exercise volume and calorie intake, and obtains the identified outcome values ​​as the target patient's outcome values. The information processing device 1 may calculate the target patient's outcome values ​​by interpolating using outcome values ​​of multiple patients that approximate the intervention item values. Note that outcome values ​​are not limited to those obtained using two intervention items, but may be obtained using three or more intervention items.

[0043] The information processing device 1 generates a graph showing the relationship between intervention item values ​​and outcome values, as shown in Figure 3, based on the obtained intervention item values ​​and outcome values ​​for the target patients and patient groups. The vertical and horizontal axes of the graph represent the intervention item values ​​used to evaluate the outcome. In the example shown in Figure 3, the graph uses exercise volume on the Y axis (vertical axis) and calorie intake on the X axis (horizontal axis). Note that the graph is not limited to showing two intervention item values ​​on two axes, but may also use three or more intervention item values ​​on the axes.

[0044] Information processing device 1 plots the amount of exercise and calorie intake for each patient in the patient group on the graph, as indicated by the black markers in the graph of Figure 3A. As mentioned above, graphs are generated for each characteristic group; for example, Figure 3A is a graph showing the distribution of exercise and calorie intake for the group of men who cook for themselves. Information processing device 1 also plots the amount of exercise and calorie intake for target patients on the graph, as indicated by the white markers in the graph of Figure 3A.

[0045] Although not shown in the graph in Figure 3A, the graph uses HbA1c (outcome value) on the Z axis, and the information processing device 1 plots the HbA1c values ​​for the target patient and patient group along the Z axis of the graph.

[0046] The information processing device 1 removes data from other patients that are inferior to the target patient from the graph in Figure 3A, and extracts only the data from other patients that are not inferior to the target patient. Other patients that are not inferior to the target patient are those in which the value of one or more outcomes is better than that of the target patient.

[0047] There are no limitations on how to extract data from other patients that result in a non-inferior solution; for example, a non-superiority sort can be used. A non-superiority sort performs a superiority comparison based on the definition of superiority comparison and selects only the data of other patients that are not superior to the target patient. Typically, NSGA-II (Non-dominated Sorting Genetic Algorithms-II) can be used for the above non-superior sort, or any other search algorithm such as particle swarm optimization can be used. This generates a graph plotted only with data from other patients that result in a non-inferior solution to the target patient, as shown in Figure 3B.

[0048] The information processing device 1 further generates contour lines showing the distribution of outcome values ​​plotted along the Z-axis and overlays them on the graph. This generates a graph showing the correlation between intervention item values ​​and outcome values, as shown in Figure 3C. The contour lines correspond to a correlation diagram showing the correlation between intervention item values ​​and outcome values.

[0049] The information processing device 1 generates contour lines indicating the HbA1c values, i.e., the positions along the Z-axis, based on the HbA1c values ​​corresponding to the plotted intervention item values ​​of the patient group. The information processing device 1 superimposes the generated contour lines onto the graph so that they correspond to the plotted positions of the intervention item values. The contour lines are generated so that the best outcome value is at the center of the contour line. The best outcome value may be determined, for example, based on the best outcome value of the patient group, or it may be determined based on the recommended value of the guideline. The contour lines may show the distribution of the outcome values ​​themselves, or they may show the distribution of transformed values ​​obtained by transforming the outcome values ​​according to a predetermined rule.

[0050] The distribution of outcome values ​​is not limited to being represented by contour lines; for example, it may be represented by a heatmap. Furthermore, the graph is not limited to being generated in two dimensions; for example, a three-dimensional graph showing outcome values ​​using 3D contour lines may also be used.

[0051] The information processing device 1 generates the aforementioned graphs for each type of outcome. The information processing device 1 transmits analysis screen information, including the generated graphs for each outcome, to the information terminal device 2. The information terminal device 2 displays an analysis screen based on the analysis screen information received from the information processing device 1 to the healthcare professional.

[0052] Figures 4 and 5 are schematic diagrams showing examples of analysis screens. The analysis screen includes a target patient registration field 31, an execution button 32, a graph display field 33, and an evaluation information display field 34. The target patient registration field 31 contains information for receiving information about the target patient, such as the patient's attributes and characteristics. The graph display field 33 displays multiple graphs 33a generated for each outcome. The evaluation information display field 34 displays the intervention item values ​​and outcome values ​​for the target patient.

[0053] The information terminal device 2 receives input of information about the target patient via the target patient registration field 31, by allowing a medical professional to operate the operation unit 25. In the example shown in Figure 4, the input items in the target patient registration field 31 include the target patient's patient ID, name, gender, dietary pattern, and current outcome value. The input items in the target patient registration field 31 may also include the target patient's intervention item values. The information terminal device 2 transmits the received information about the target patient to the information processing device 1.

[0054] The information processing device 1 performs the above processing procedure based on the information received about the target patient, obtains the outcome of the intervention for the target patient, and generates graphs. The information processing device 1 displays multiple graphs 33a generated for each outcome side by side in the graph display area 33, and also displays the value of each intervention item for the target patient and the outcome value for each intervention item in the evaluation information display area 34.

[0055] In the example shown in Figure 4, the graph display area 33 shows three types of graphs 33a, where the Z-axis of each graph represents outcome values: HbA1c, nutritional status, and time to dropout, respectively. Each graph 33a displays the same combination of intervention item values, but with different outcome values ​​along the Z-axis for each type of outcome. Healthcare professionals can easily and visually grasp multiple outcome indicators for an intervention indicator from the information displayed on the analysis screen.

[0056] On each graph 33a displayed on the analysis screen, a crossbar 33b is shown, whose position can be arbitrarily moved. The crossbar 33b functions as an object that accepts the specification of its position on the graph. Each crossbar 33b is displayed on each graph 33a.

[0057] Healthcare professionals can use the crossbar 33b to check changes in various indicators. Specifically, by moving the crossbar 33b displayed on graph 33a, they can recognize changes in the target value of the outcome due to changes in the intervention item values.

[0058] For example, with the analysis screen shown in Figure 4 displayed, a healthcare professional can manipulate the crossbar 33b, which is associated with the graph 33a showing HbA1c on the left side of the graph display area 33, to move the center of the crossbar 33b toward the center of the contour line (towards the upper left of the graph). As a result, the position of the crossbar 33b on the graph 33a changes, as shown in Figure 5.

[0059] Here, all crossbars 33b displayed on each graph 33a may be configured so that the positions of each crossbar 33b are linked. That is, the coordinates of the center position of all crossbars 33b associated with each graph 33a always coincide. As shown in Figure 5, for example, by moving the crossbar 33b on the graph 33a showing HbA1c, the crossbar 33b on the graph 33a showing nutritional status and the crossbar 33b on the graph 33a showing the time until dropping out are moved in conjunction to the same position.

[0060] Subsequently, when a medical professional presses the execute button 32, the position specification by operating the crossbar 33b is input. The information terminal device 2 acquires the coordinate information (X coordinate and Y coordinate) of the center position of the crossbar 33b via the operation unit 25 and transmits the acquired coordinate information to the information processing device 1.

[0061] The information processing device 1 identifies the intervention item values ​​for the vertical and horizontal axes corresponding to the coordinate information, based on the coordinate information received via the information terminal device 2. Furthermore, the information processing device 1 identifies evaluation values ​​for each outcome for the identified intervention item values ​​for the vertical and horizontal axes. The information processing device 1 displays the newly obtained intervention item values ​​and each outcome value in the evaluation information display field 34. The information processing device 1 transmits the updated screen information to the information terminal device 2.

[0062] Information terminal device 2 displays an updated screen based on the updated screen information received from information terminal device 2. Healthcare professionals can check the changes in each outcome due to the intervention through the updated screen.

[0063] In this way, graphs of different outcome indicators work in conjunction with the same value of an intervention indicator, providing an integrated representation of evaluation values ​​for each outcome. Healthcare professionals and target patients can efficiently set optimal intervention item values ​​by comparing them with other outcomes, according to the target outcome. For example, to bring HbA1c closer to the target value, it becomes easy to visually recognize the optimal path (route) for setting intervention indicators to achieve the desired outcome, such as how to combine exercise and calorie intake to minimize deterioration of nutritional status.

[0064] Figure 6 is a flowchart showing an example of a processing procedure for generating a graph. The processing in each of the following flowcharts may be executed by the control unit 11 according to program 1P stored in the storage unit 12 of the information processing device 1, and by the control unit 21 according to program 2P stored in the storage unit 22 of the information terminal device 2, or it may be implemented by dedicated hardware circuits (e.g., FPGA or ASIC) provided in the control unit 11 and the control unit 21 respectively, or by a combination thereof.

[0065] The control unit 11 of the information processing device 1 responds to an inquiry from the information terminal device 2 and acquires multiple intervention item values ​​and characteristics of the target patient (step S11). The control unit 11 may acquire this information, for example, by receiving the intervention item values ​​and characteristics of the target patient transmitted from the information terminal device 2, or by coordinating with a medical record system or the like.

[0066] The control unit 11 acquires multiple intervention item values ​​and multiple outcome values ​​from other patients in the patient group based on the information stored in the analysis DB 121 (step S12). The control unit 11 classifies the acquired patient group data into multiple characteristic groups according to the characteristics of the patients (step S13).

[0067] The control unit 11 identifies the characteristic group to which the target patient belongs based on the acquired characteristics of the target patient, and extracts data of the patient group that belongs to the same characteristic group as the identified characteristic group (step S14).

[0068] The control unit 11 obtains the outcome values ​​for each patient for a predetermined combination of intervention items, based on the values ​​of each intervention item in the target patient and the values ​​of each intervention item and outcome values ​​in the extracted patient group (step S15).

[0069] The control unit 11 generates a graph showing the relationship between intervention item values ​​and outcome values ​​based on the obtained intervention item values ​​and outcome values ​​for the target patients and patient groups (step S16). The control unit 11 generates a graph in which the X and Y axes are set to different intervention item values ​​and the Z axis is set to the outcome value, and plots the data for the target patients and patient groups on the graph.

[0070] The control unit 11 performs a non-superiority sort on the generated graph to exclude data from other patients that are inferior to the target patient, and obtains only the data from other patients that are not inferior to the target patient (step S17). The control unit 11 is not limited to plotting the data of all other patients that are inferior or not inferior to the target patient and then extracting only the data of other patients that are not inferior. The control unit 11 may identify the data of other patients that are not inferior to the target patient based on the information stored in the analysis DB 121 and generate a graph based on the identified data.

[0071] The control unit 11 generates contour lines showing the distribution of outcome values ​​based on the outcome values ​​in the Z-axis direction, and superimposes the generated contour lines onto the graph (step S18). The control unit 11 performs the above process for each of the pre-set multiple outcomes and generates the above graph for each outcome.

[0072] The control unit 11 transmits an analysis screen, including graphs for each generated outcome, to the information terminal device 2 (step S19).

[0073] The control unit 21 of the information terminal device 2 receives the analysis screen (step S20). The control unit 21 displays the received analysis screen on the display unit 24 (step S21) and terminates the process.

[0074] Figure 7 is a flowchart showing an example of the processing procedure for receiving crossbar operation requests. The control unit 21 of the information terminal device 2 receives a position specification by a medical professional operating the operation unit 25 (step S31). More specifically, the control unit 21 receives a position specification by a medical professional moving a crossbar. In step S31, the control unit 21 receives a position specification using one of the multiple crossbars 33b displayed on each graph 33a. In this case, the control unit 21 synchronizes the positions of the other crossbars 33b on each graph 33a in response to the reception of an operation on one of the crossbars 33b.

[0075] The control unit 21 identifies the coordinate information of the center position of the received crossbar 33b and transmits the identified coordinate information of the center position to the information processing device 1 (step S32).

[0076] The control unit 11 of the information processing device 1 receives coordinate information of the center position (step S33). The control unit 11 identifies intervention item values ​​and outcome values ​​corresponding to the coordinate information of the center position received via the information terminal device 2 (step S34). Specifically, the control unit 11 identifies the intervention item values ​​for the vertical and horizontal axes corresponding to the coordinate information. Furthermore, the information processing device 1 identifies evaluation values ​​for each outcome for the identified intervention item values ​​for the vertical and horizontal axes.

[0077] The control unit 11 transmits the identified intervention item values ​​and outcome values ​​to the information terminal device 2 (step S35).

[0078] The control unit 21 of the information terminal device 2 receives the intervention item values ​​and outcome values ​​(step S36). The control unit 21 updates the information on the analysis screen and displays the received intervention item values ​​and each outcome value on the display unit 24 (step S37).

[0079] The entities responsible for processing in each of the flowcharts above are not limited. For example, information terminal device 2 may perform some or all of the processing performed by information processing device 1. The information processing device 1 and information terminal device 2 are not limited to separate devices; they may be a single common information processing device.

[0080] According to this embodiment, multiple outcomes for an intervention can be provided in an integrated manner. Physicians and target patients can visually recognize the degree of intervention for multiple independent outcomes using graphs, and consider the degree of intervention to improve outcomes. By linking toolbars in multiple graphs generated for each outcome, the relationship between multiple intervention factors and multiple different outcome indicators can be evaluated in an integrated manner. In this way, the information processing system 100 functions as a support tool that facilitates smooth decision-making between physicians and target patients in intervention guidance.

[0081] Because the graphs are generated based on actual past patient data, they can accurately estimate the outcomes of the target patients. By generating graphs tailored to different patient characteristic groups, it becomes possible to estimate outcomes that are appropriate to the characteristics of the target patients.

[0082] (Second Embodiment) In the second embodiment, a configuration that accepts various changes to the graph will be described. Below, the differences from the first embodiment will be mainly described, and components common to the first embodiment will be denoted by the same reference numerals and their detailed descriptions will be omitted.

[0083] Figures 8 to 10 are schematic diagrams showing examples of analysis screens in the second embodiment. As shown in Figure 8, the analysis screen in the second embodiment further includes a setting reception field 35. The setting reception field 35 contains information for receiving various settings for the graph. The setting reception field 35 is configured to accept selections for characteristics (e.g., dietary patterns in the example shown in Figure 8), intervention items, and outcomes, respectively.

[0084] For example, healthcare professionals can change the characteristic group of the graph to be generated by selecting a meal pattern from a pull-down menu in the settings reception area 35. The settings reception area 35 may also be configured to accept meal patterns directly by including an input field for receiving meal pattern input.

[0085] Similarly, by changing the intervention items in the settings input field 35, the types of intervention items on the vertical and horizontal axes of the graph can be changed. By changing the outcome in the settings input field 35, the types of outcomes to be generated in the graph can be changed. Alternatively, by changing the outcome setting in the settings input field 35 to "none," the types of outcomes to be displayed can be changed.

[0086] For example, as shown in Figure 8, when an analysis screen is displayed that includes a graph of the group of men who primarily cook at home, and the option "primarily eat out" is selected in the meal pattern pull-down menu, the graph 33a shown in the graph display area 33 will switch to the graph 33a of the group of men who primarily eat out, as shown in Figure 9.

[0087] The information processing device 1 receives a selection for at least one of the characteristics, intervention items, or outcomes via the information terminal device 2, and updates the information on the analysis screen according to the received selection. Specifically, when the information processing device 1 receives a selection for a characteristic, it identifies the characteristic group to be used for graph generation according to the selected characteristic. In the example shown in Figure 8, the information processing device 1 identifies a new characteristic group as the "eating out male group" based on the changed eating pattern "eating out mainly" and the gender of the target patient already obtained, "male". The information processing device 1 generates a new graph using the data from the patient group of the identified "eating out male group".

[0088] Similarly, when the information processing device 1 receives a selection of an intervention item, it changes the vertical and horizontal axes of the graph according to the selected intervention item and plots the values ​​for each intervention item. Furthermore, it superimposes contour lines of the outcome for the new intervention item onto the graph. Also, when the information processing device 1 receives a selection of an outcome, it generates a graph corresponding to the selected outcome. Alternatively, it switches the display or hiding of the graph depending on the selected outcome.

[0089] Furthermore, the meal patterns used to specify characteristic groups may be configured to allow the simultaneous selection of multiple types. When the system receives selections for multiple meal patterns, the information processing device 1 displays superimposed graphs of the multiple characteristic groups in the graph display area 33, as shown in Figure 10.

[0090] For example, if the meal patterns selected are primarily home cooking and primarily eating out, the information processing device 1 generates a first graph using data from the group of patients belonging to the home cooking male group, and a second graph using data from the group of patients belonging to the eating out male group. By overlaying the generated first and second graphs, the information processing device 1 generates a graph that includes plots of intervention item values ​​for both the home cooking male group and the eating out male group. The information processing device 1 also superimposes both contour lines showing the outcomes of the home cooking male group and contour lines showing the outcomes of the eating out male group onto the graph.

[0091] In this case, it is preferable that the information processing device 1 displays graphs for each characteristic group in an identifiable manner. The information processing device 1 may, for example, change the shape and display color of the markers for intervention item values, the line type and display color of the contour lines according to the characteristic group, or otherwise differentiate the display manner of markers and contour lines for intervention item values ​​according to the characteristic group. In the example shown in Figure 10, the group of men who cook at home is displayed with black circular markers and solid contour lines, while the group of men who eat out is displayed with black upward-pointing triangle markers and dashed contour lines. This allows healthcare professionals to efficiently grasp multiple pieces of information and clearly recognize the data for each characteristic group.

[0092] In Figures 8 to 10, as an example, the setting reception field 35 is shown to accept selections for characteristics in order to define characteristic groups, but the configuration of the setting reception field 35 is not limited. The setting reception field 35 may be configured to accept selections for characteristic groups (for example, men who cook at home, men who eat out, etc.).

[0093] Figure 11 is a flowchart showing an example of a processing procedure performed by the information processing system 100 of the second embodiment.

[0094] The control unit 21 of the information terminal device 2 accepts the selection of settings made by a medical professional operating the operation unit 25 (step S41). In step S41, the control unit 21 accepts the selection using the setting acceptance field 35 shown in Figures 8 to 10. The control unit 21 transmits information regarding the accepted setting selection to the information processing device 1 (step S42).

[0095] The control unit 11 of the information processing device 1 receives a selection for the settings (step S43). The control unit 11 switches the graph on the analysis screen to correspond to the selection for the settings received via the information terminal device 2 (step S44). The control unit 11 switches, for example, the characteristic group to be used for graph generation, the intervention items corresponding to each axis of the graph, the graph's outcome, etc.

[0096] The control unit 11 transmits the updated screen, including the graph after the switch, to the information terminal device 2 (step S45).

[0097] The control unit 21 of the information terminal device 2 receives the update screen (step S46). The control unit 21 displays the received update screen on the display unit 24 (step S47), and then terminates the series of processes.

[0098] According to this embodiment, since the elements of the graph can be arbitrarily changed, outcomes can be considered from a wider range of perspectives, improving user convenience.

[0099] (Third embodiment) In the third embodiment, a configuration for displaying inferior data in a graph will be described. The following mainly describes the differences from the first embodiment, and components common to both embodiments are denoted by the same reference numerals, and their detailed descriptions will be omitted.

[0100] Figure 12 is a schematic diagram showing an example of the analysis screen in the third embodiment. As shown in Figure 12, each graph 33a displayed in the graph display area 33 shows not only data from other patients that are not inferior to the target patient (hereinafter also simply referred to as non-inferior data), but also data from other patients that are inferior to the target patient (hereinafter also simply referred to as inferior data).

[0101] The information processing device 1, in generating a graph, classifies inferior data and non-inferior data using, for example, a non-superiority sort. The information processing device 1 generates a graph that includes both inferior data and non-inferior data.

[0102] In this case, it is preferable that the information processing device 1 displays inferior data and non-inferior data in a distinguishable manner. The information processing device 1 may, for example, change the shape and display color of the marker for the intervention item value, and the line type and display color of the contour lines according to the data type (inferior data or non-inferior data), thereby differentiating the display manner of the markers and contour lines for the intervention item value according to the data type. In the example shown in Figure 12, non-inferior data is displayed with black circular markers and solid contour lines, while inferior data is displayed with black downward-pointing triangle markers and dashed contour lines.

[0103] Figure 13 is a flowchart showing an example of a processing procedure performed by the information processing system 100 of the third embodiment.

[0104] The control unit 11 of the information processing device 1 acquires intervention item values ​​and characteristics of the target patient in the same procedure as steps S11 to S15 in Figure 6 in the first embodiment (step S51), acquires intervention item values ​​and outcome values ​​of other patients in the patient group (step S52), classifies them into characteristic groups (step S53), extracts data of the patient group belonging to the same characteristic group as the target patient (step S54), and acquires outcome values ​​for the target patient for each outcome for a predetermined combination of intervention items (step S55).

[0105] The control unit 11 classifies the extracted patient group data into inferior data and non-inferior data, for example, using a non-superiority sort (step S56).

[0106] The control unit 11 generates a graph showing the relationship between intervention item values ​​and outcome values ​​based on the intervention item values ​​and outcome values ​​of the target patients and patient groups (step S57). In this case, the control unit 11 displays the markers for inferior data and non-inferior data differently.

[0107] The control unit 11 generates contour lines showing the distribution of outcome values ​​for both inferior and non-inferior data, and superimposes the generated contour lines onto the graph (step S58). In this case, the control unit 11 displays the contour lines for inferior and non-inferior data in different ways. The control unit 11 performs the above processing for each of the pre-set multiple outcomes and generates the above graph for each outcome.

[0108] The control unit 11 transmits an analysis screen, including graphs for each generated outcome, to the information terminal device 2 (step S19). The processing from step S19 onward is the same as in the first embodiment, so the details are omitted.

[0109] According to this embodiment, more information can be presented based on patient data showing diverse outcomes. Therefore, outcomes can be considered from a wider range of perspectives, improving user convenience.

[0110] (Fourth Embodiment) In the fourth embodiment, a configuration for displaying details about other patients will be described. Below, the differences from the first embodiment will be mainly described, and components common to the first embodiment will be denoted by the same reference numerals and their detailed descriptions will be omitted.

[0111] Figure 14 is a schematic diagram showing an example of the analysis screen in the fourth embodiment. As shown in Figure 14, the analysis screen includes a detail display area 36 that displays details about other patients. The detail display area 36 displays details about other patients corresponding to each marker on the graph.

[0112] When the information processing device 1 receives a selection of any marker on the graph via the information terminal device 2, it displays details about other patients corresponding to the selected marker in the detailed display area 36. The detailed display area 36 displays further information about the patient in question, such as whether they eat three meals a day or exercise daily. This allows for a more detailed understanding of other patients who are close to the target outcome.

[0113] Figure 15 is a flowchart showing an example of a processing procedure performed by the information processing system 100 of the fourth embodiment.

[0114] The control unit 21 of the information terminal device 2 accepts the selection of other patients by a medical professional operating the operation unit 25 (step S61). In step S61, the control unit 21 accepts the selection of other patients corresponding to a marker by, for example, tapping one of the markers shown in the graph on the analysis screen shown in Figure 14.

[0115] The control unit 21 transmits information regarding the selection of other patients received to the information processing device 1 (step S62). The control unit 21 may also transmit, for example, the position coordinates of the selected marker to the information processing device 1.

[0116] The control unit 11 of the information processing device 1 receives information regarding the selection of other patients (step S63). The control unit 11 obtains details about the selected other patients (step S64). Specifically, the control unit 11 identifies a patient ID having an intervention item value corresponding to the selected marker based on the position coordinates of the received marker. The control unit 11 obtains details associated with the identified patient ID based on the information stored in the analysis DB 121. The control unit 11 transmits the obtained details to the information terminal device 2 (step S65).

[0117] The control unit 21 of the information terminal device 2 receives the details (step S66). The control unit 21 updates the information on the analysis screen and displays the received details in the details display field 36 (step S67).

[0118] According to this embodiment, more specific information for achieving the target outcome can be presented, thereby improving the utilization of the information processing system 100.

[0119] (Fifth embodiment) In the fifth embodiment, a configuration for displaying time-series changes in the target patient will be described. Below, the differences from the first embodiment will be mainly explained, and components common to the first embodiment will be denoted by the same reference numerals and their detailed descriptions will be omitted.

[0120] Figure 16 is a schematic diagram showing an example of the analysis screen in the fifth embodiment. As shown in Figure 16, each graph 33a shown in the graph display section 33 of the analysis screen contains multiple white circular markers indicating the data of the target patient. Each marker indicates the data of the target patient acquired at the evaluation time and at time points prior to the evaluation time. The evaluation information display section 34 also displays the intervention item values ​​and outcome values ​​at each time point. The information processing device 1 stores the data of the target patient at each time point in the storage unit 12 in chronological order. The information processing device 1 then reads data from several past time points, including the evaluation time, and displays it on the graph.

[0121] Figure 17 is a flowchart showing an example of a processing procedure performed by the information processing system 100 of the fifth embodiment.

[0122] The control unit 21 of the information terminal device 2 receives a request for time-series data when a medical professional operates the operation unit 25 (step S71). In step S71, the control unit 21 receives the request using, for example, the time-series data display request button 37 included in the analysis screen shown in Figure 16. The control unit 21 transmits the received time-series data request to the information processing device 1 (step S72).

[0123] The control unit 11 of the information processing device 1 receives a request for time-series data (step S73). The control unit 11 generates an update screen including the time-series data (step S74). Specifically, the control unit 11 acquires intervention item values ​​and outcome values ​​for several past points in time, including the evaluation point, for the target patient, based on the information stored in the memory unit 12. The control unit 11 plots the acquired data for several past points in time for the target patient on a graph. The control unit 11 also displays the data for several past points in time in the evaluation information display field 34.

[0124] The control unit 11 transmits the updated screen containing the generated time-series data to the information terminal device 2 (step S75).

[0125] The control unit 21 of the information terminal device 2 receives the update screen (step S76). The control unit 21 displays the received update screen on the display unit 24 (step S77), and then terminates the series of processes.

[0126] In the above-described process, the control unit 11 may change the shape and display color of the intervention item value markers for the target patient according to the time point, thereby making the display manner of the intervention item value markers different for each time point. The control unit 11 may also link each marker with the time point information indicated by each marker, so that when any marker is selected, the time point indicated by that marker is displayed on the analysis screen as text data or the like.

[0127] Furthermore, in the above-described process, the analysis screen may display past graphs for each point in time. The information processing device 1 stores graphs showing the intervention item values ​​and outcome values ​​of other patients at each point in time, corresponding to the intervention item values ​​and outcome values ​​of the target patient at that time. When the information processing device 1 receives a request for time-series data, it displays graphs for each outcome for the past several periods on the analysis screen. The analysis screen includes, for example, graphs for each of the three outcomes at the current, previous, and the time before that point in time. With this configuration, in addition to the time-series changes in the target patient's data, the time-series changes in the graphs can be confirmed.

[0128] According to this embodiment, the trajectory of the target patient's data is shown on the graph. By considering past paths, it is possible to consider the optimal path to achieve the desired outcome. [Explanation of Symbols]

[0129] 1. Information Processing Device 11 Control Unit 12 Storage section 13 Communications Department 1P Program 1A Recording medium 2. Information terminal device 21 Control Unit 22 Memory section 23 Communications Department 24 Display section 25 Control section 2P Program 2A recording medium

Claims

1. Multiple intervention item values ​​and multiple outcome values ​​were obtained for both the target and non-target groups. Based on the acquired values ​​for each intervention item and outcome, a graph is generated showing the values ​​for each intervention item and outcome for both the target and non-target groups, with the outcome and multiple intervention items as axes, for each type of outcome. A program that causes a computer to perform a process.

2. The graph is output excluding the intervention item values ​​for non-target individuals who perform worse than the target individuals. The program according to claim 1.

3. A correlation diagram showing the correlation between each intervention item value and the outcome value is superimposed on the graph. The program according to claim 1 or claim 2.

4. Based on the characteristics of the subjects and non-subjects, the graph is output showing the intervention item values ​​for non-subjects who are classified into the same characteristic group as the subjects. The program according to any one of claims 1 to 3.

5. A graph showing the intervention item values ​​for non-target individuals classified into the same characteristic group as the aforementioned target individuals is superimposed with a graph showing the intervention item values ​​for non-target individuals classified into a different characteristic group than the aforementioned target individuals. The program according to any one of claims 1 to 4.

6. The system accepts the specification of a position on the aforementioned graph. Outputs outcome values ​​and intervention item values ​​for each axis corresponding to the specified location. The program according to any one of claims 1 to 5.

7. We accept selections for characteristics, intervention items, or outcomes. The graph will be switched according to the selected option. The program according to any one of claims 1 to 6.

8. Based on the selection of a position on one of the multiple graphs output for each outcome, the system outputs the target value for the outcome in the other graphs corresponding to the selected position. The program according to any one of claims 1 to 7.

9. The graph is output to distinguish between intervention item values ​​in non-target individuals that are not inferior to those of the target individuals, and intervention item values ​​in non-target individuals that are inferior to those of the target individuals. The program according to any one of claims 1 to 8.

10. Output information showing the time-series changes in the aforementioned graph. The program according to any one of claims 1 to 9.

11. The intervention item values ​​include at least two selected from exercise volume, calorie intake, steps taken, aerobic exercise time, anaerobic exercise time, and sleep time. The program according to any one of claims 1 to 10.

12. The aforementioned outcome values ​​include at least two selected from blood glucose levels, nutritional status, and the degree of decline in lifestyle improvements. S according to any one of claims 1 to 11.

13. Multiple intervention item values ​​and multiple outcome values ​​were obtained for both the target and non-target groups. Based on the acquired values ​​for each intervention item and outcome, a graph is generated showing the values ​​for each intervention item and outcome for both the target and non-target groups, with the outcome and multiple intervention items as axes, for each type of outcome. It includes a control unit that performs processing. Information processing device.

14. Multiple intervention item values ​​and multiple outcome values ​​were obtained for both the target and non-target groups. Based on the acquired values ​​for each intervention item and outcome, a graph is generated showing the values ​​for each intervention item and outcome for both the target and non-target groups, with the outcome and multiple intervention items as axes, for each type of outcome. An information processing method in which a computer performs the processing.

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