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JP-2026074557-A - Prediction device, prediction method, and prediction program

JP2026074557AJP 2026074557 AJP2026074557 AJP 2026074557AJP-2026074557-A

Abstract

[Challenge] To accurately predict the effects of interventions on factors for which there is no prior intervention history through intervention programs. [Solution] The prediction device includes a storage device that stores intervention effect performance information representing the actual intervention effect of an intervention program that provides interventions for a predetermined health condition to each participant in the past, for at least one of a plurality of factors that may cause the said health condition, and a processing device that performs intervention effect prediction processing that predicts the intervention effect for factors for which there is no intervention history by the intervention program, based on the intervention effect performance information and the relationships between each factor, and output processing that outputs the prediction results. [Selection Diagram] Figure 1

Inventors

  • 勝沼 聡
  • 直野 健

Assignees

  • 株式会社日立製作所

Dates

Publication Date
20260507
Application Date
20241021

Claims (10)

  1. A storage device that stores intervention effect performance information representing the actual effectiveness of interventions on at least one of multiple factors that may cause a given health condition in past participants, provided by an intervention program that provides interventions for a predetermined health condition to each participant, and An intervention effect prediction process that predicts the intervention effect on factors for which there is no intervention record under the intervention project, based on the aforementioned intervention effect performance information and the relationships between each factor, Output processing to output the results of the prediction, A prediction device equipped with a processing unit that performs the following.
  2. The aforementioned processing apparatus is In the intervention effect prediction process, the risk of developing a preventable target factor, which is a pre-selected factor, or the relationship between each factor is calculated based on the causal relationship between each factor. The prediction device according to claim 1.
  3. The memory device stores personal factor information representing the history of factors possessed by each person who can be intervened in by the intervention project, The aforementioned processing apparatus is Based on the aforementioned personal factor information, if the probability that a person who has the first factor and is eligible for intervention will have the second factor at a predetermined time in the future is greater than or equal to a predetermined threshold, a factor-causal relationship calculation process is performed to generate factor-causal relationship information in which the first factor is the causal factor of the second factor and the second factor is the consequence factor of the first factor. In the intervention effect prediction process, the relationship between each factor is calculated based on the proportion of causal and consequent factors common to each factor, by referring to the causal relationship information between factors. The prediction device according to claim 2.
  4. The memory device stores personal factor information representing the history of factors possessed by each person who can be intervened in by the intervention project, The aforementioned processing apparatus is Based on the aforementioned personal factor information, a process is performed to calculate the probability that a person who is eligible for intervention and possesses a predetermined factor will have the aforementioned preventable factor at a predetermined time in the future, as the preventable factor onset risk. The prediction device according to claim 2 or 3.
  5. The memory device stores personal factor information representing the history of factors possessed by each person who can be intervened in by the intervention project, The aforementioned processing apparatus is Referencing the aforementioned personal factor information, an intervention effect calculation process is performed to calculate the change in the probability that a participant with a predetermined factor has a preventable target factor as a result of the intervention of the intervention project, as a change in the risk of developing the preventable target factor for the predetermined factor. In the aforementioned intervention effect prediction process, the change in the risk of developing the target factor for the factor most highly associated with the factor that has not been intervened is used as the change in the risk of developing the target factor for the factor that has not been intervened, and the intervention effect on that factor is predicted. The prediction device according to claim 1.
  6. The aforementioned processing apparatus is In the intervention effect prediction process described above, the difference between the reduction in future costs required for care or medical treatment of participants, based on changes in the risk of developing the preventable target factor for factors that have not been previously intervened, and the intervention cost required by the intervention program, is defined as the intervention effect for the factors that have not been previously intervened. The prediction device according to claim 5.
  7. The memory device stores personal factor information representing the history of factors possessed by each person who can be intervened in by the intervention project, The aforementioned processing apparatus is Referencing the aforementioned personal factor information, the change in the probability that a participant with a predetermined factor has the target factor due to past interventions is defined as the change in the risk of developing the target factor. The difference between the reduction in future costs required for the participant's care or medical treatment based on the change in the risk of developing the target factor and the intervention cost required by the intervention is calculated as the actual intervention effect for the predetermined factor. An intervention effect calculation process is then performed to store the intervention effect information, which represents the change in the risk of developing the target factor and the actual intervention effect, in the storage device. The prediction device according to claim 1.
  8. The aforementioned processing apparatus is In the output processing described above, the predicted intervention effect for factors without prior intervention history, the relationship with factors that have prior intervention history in the intervention program, the risk of developing the preventable target factor, the causal factor, and the outcome factor are output, respectively. The prediction device according to claim 3.
  9. Information processing device, Intervention effect performance information representing the past intervention effect of an intervention program that provides interventions for a predetermined health condition to each participant, for at least one of several factors that may cause the said health condition in past participants, and intervention effect prediction processing that predicts the intervention effect for factors for which there is no prior intervention performance by the intervention program, based on the relationships between each factor. Output processing to output the results of the prediction, A prediction method that performs this task.
  10. In an information processing device, Intervention effect performance information representing the past intervention effect of an intervention program that provides interventions for a predetermined health condition to each participant, for at least one of several factors that may cause the said health condition in past participants, and intervention effect prediction processing that predicts the intervention effect for factors for which there is no prior intervention performance by the intervention program, based on the relationships between each factor. Output processing to output the results of the prediction, A prediction program that executes the prediction.

Description

This invention relates to a prediction device, a prediction method, and a prediction program. In intervention programs implemented by local governments and other organizations to prevent the worsening of diseases or to prevent the need for long-term care, there is a need to accurately select individuals who are highly likely to benefit from the intervention, based on factors such as medical claims or health checkup results. Patent Document 1 discloses an intervention processing system that estimates the intervention effect obtained as a result of an intervention performed on a user receiving a content distribution service, using an intervention model that utilizes user characteristics and intervention characteristics, and generates intervention materials to be used for new interventions based on the estimated intervention effect. Patent Document 2 discloses a system for selecting the most cost-effective intervention or treatment for a specific patient by utilizing data such as medical records of other patients related to that patient. Patent Document 3 discloses an analysis system that predicts changes in the patient's condition when an intervention is implemented and when it is not, and calculates medical costs based on health information, medical information, and disease transition models. International Publication No. 2022/107596U.S. Patent Application Publication No. 2014/0129247International Publication No. 2016/181490 This is a diagram showing an example of a prediction system configuration.This figure shows an example of the functional configuration of an intervention effect prediction server.This figure shows an example of information on preventable risk factors.This figure shows an example of personal factor information.This figure shows an example of past business performance information.This is a process flow chart explaining the calculation process for the risk of developing preventable factors.This figure shows an example of information on the risk factors for developing the disease that can be prevented.This is a process flow chart explaining the calculation of causal relationships between factors.This is a process flow diagram that explains the details of the causal factor extraction process.This figure shows an example of information regarding causal relationships between factors.This graph displays information about causal relationships between factors.This is a process flow diagram explaining the process for calculating the effectiveness of interventions.This figure shows an example of intervention effectiveness data.This is a processing flow chart explaining the intervention effect prediction process.This is a process flow diagram that explains the details of the calculation process for the degree of causal relationship (A).This is a process flow chart that explains the details of the calculation process for the degree of association (B) of the risk of developing the preventable factor.This figure shows an example of relevance information.This is a process flow diagram that explains the details of the process for predicting the intervention effect.This figure shows an example of information predicting the effectiveness of an intervention.This figure shows an example of a screen displaying the effects of factor interventions. Embodiments of the present invention will be described in detail below with reference to the drawings. The following description and drawings are illustrative for illustrating the present invention, and have been omitted and simplified as appropriate for clarity of explanation. The present invention can also be carried out in various other forms. Unless otherwise specified, each component may be singular or plural. The positions, sizes, shapes, and ranges of the components shown in the drawings may not represent their actual positions, sizes, shapes, and ranges in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the positions, sizes, shapes, and ranges disclosed in the drawings. In the following explanation, various types of information may be described using terms such as "table,""list," and "queue," but these types of information may also be represented using other data structures. To indicate independence from data structure, "XX table,""XXlist," etc., may be referred to as "XX information." When describing identification information, terms such as "identification information,""identifier,""name,""ID," and "number" will be used, but these terms are interchangeable. When there are multiple components with the same or similar function, they may be described using the same symbol but with different subscripts. However, if it is not necessary to distinguish between these multiple components, the subscripts may be omitted in the description. Furthermore, while the following explanation may describe the processes performed by executing a program, the processor (e.g., CPU, GPU) executes the program, perform