WO2016120986A1 - Analysis system and health business assistance method - Google Patents

Abstract

Provide is an analysis system comprising: a planning unit which references medical exam information, a medical expense prediction model and a health guidance program effect to calculate, as a medical expense control effect, the difference between a first medical expense for a case where a subscriber has implemented at least one health guidance program and a second medical expense for a case where the subscriber did not implement such a program, determines target individuals for the health guidance program in order starting with the highest medical expense control effect, and creates a health guidance program implementation plan; and an improvement proposal unit which calculates characteristics of target individuals of the health guidance program at the time of planning and characteristics of participants in the health guidance program, selects a characteristic for which the difference is great between the planned head-count of target individuals of the health guidance program at the time of planning and the actual head-count of the participants in the health guidance program, and outputs the selected characteristic as necessary improvement information.

Description

Analysis system and health business support method

The present invention relates to an analysis system for analyzing the effects of health services.

The increase in medical expenses has become a problem, with lifestyle-related diseases increasing with aging. Insurers are implementing health services to prevent subscriber illness and improve health in order to control medical costs. In order to effectively implement health services, it is important to advance the PDCA cycle of planning, execution, evaluation and improvement.

There is JP-A-2004-341611 (Patent Document 1) as background art of this technology. Patent Document 1 discloses an integrated database server having an insured person database for storing insured person health management information, and reads the insured person's health management information from the insured person database, Intervention decision support device that determines intervention target information for intervention targets that require intervention for management, and determines intervention support information that supports health promotion of the intervention target, and application that shows the results of the intervention target applied by the intervention support information An insurer information system including a performance evaluation device that inputs performance data and health management information and evaluates intervention support information determined by the intervention determination support device is described (see summary).

JP 2004-341611 A JP 2014-225176 A

In order to realize the PDCA cycle, it is necessary to improve the effectiveness and efficiency of health services through improvement measures using the evaluation results. In practice, the expected effect at the time of planning may not be obtained. In particular, when the effect is lower than the original forecast, it is necessary to improve the contents and implementation method of the health project. In the technique described in Patent Document 1, what kind of improvement is made and a specific method for creating an improvement proposal is not taken into consideration, which is sufficient to improve the later health business. It was not a thing.

For example, the effect may differ at the time of planning and at the time of evaluation due to problems such as the participation of the participant assumed at the time of planning does not participate in the health guidance program and the participation of a different participant from the assumption. In addition to the status of participation, the continuation rate at the time of planning and the status of efforts to improve lifestyle habits differ, so the health improvement effect expected at the time of planning may differ. In this way, in health business planning, it is necessary to utilize information in order to bridge the gap between the plan and the actual situation.

The present invention aims to provide a system and method for supporting the realization of the PDCA cycle of a health business, thereby predicting the difference between the plan and the implementation result and supporting the improvement of the health business.

A typical example of the invention disclosed in the present application is as follows. That is, an analysis system including a processor and a memory connected to the processor, the analysis system including medical examination information including a result of a health examination of a subscriber, a node corresponding to a random variable representing a disease state, and The medical cost prediction model in which the stochastic dependence between the nodes corresponding to the random variables of the factors that change the pathological condition is defined by the directed side or the undirected side, and the effect expected from the health guidance implemented to the subscriber A database including a health guidance program effect, wherein the processor refers to the health examination information, the medical cost prediction model, and the health guidance program effect, and at least one subscriber Predicting the first medical cost when the health guidance program is implemented and the second medical cost when not implementing the health guidance program, As a medical cost restraint effect, determine the target of the health guidance program in descending order of the medical cost restraint effect, and plan the planning department to plan the implementation of the health guidance program, and the processor participates in the health guidance program An execution recording unit that records the situation, the processor is an evaluation unit that determines the medical cost control effect of the participants of the health guidance program, and the processor is the characteristics of the target person of the health guidance program at the time of planning, the health guidance program The characteristics of the participants of the health guidance program at the time of planning are selected, and the characteristics having a large difference between the number of people at the time of planning and the number of participants of the health guidance program at the time of execution are selected. And an improvement proposing unit that outputs the information as improvement required information.

According to an embodiment of the present invention, a PDCA cycle of planning, execution, evaluation, and improvement for suppressing medical expenses can be performed. Problems, configurations, and effects other than those described above will become apparent from the description of the following embodiments.

It is a figure which shows an example of a structure of the health business plan and improvement system of a present Example. It is a figure which shows an example of the medical examination information of a present Example. It is a figure which shows an example of the health guidance program performance model of a present Example. It is a figure which shows an example of the prediction medical expenses suppression effect of a present Example. It is a figure which shows an example of the health guidance program performance information of a present Example. It is a figure which shows an example of the improvement proposal list | wrist of the participation rate which the improvement proposal part of a present Example outputs. It is a figure which shows an example of the medical expenses prediction model of a present Example. It is a flowchart of the whole process which the health-care business plan and improvement system of a present Example performs. It is a flowchart of the detail of the process which a planning part performs in the planning step of a present Example. It is a detailed flowchart of the process which an evaluation part performs in the evaluation step of a present Example. It is a flowchart of the detail of the process which the improvement proposal part performs in the improvement step of a present Example. It is a flowchart of the detail of the process which the improvement proposal part performs in the improvement step of a present Example. It is a figure which shows an example of the number distribution according to the characteristic of a present Example. It is a figure which shows an example of the improvement proposal screen of a present Example. It is a figure which shows an example of the improvement proposal screen of a present Example. It is a figure which shows the relationship between the stakeholders who utilize the health-project planning / improvement system of a present Example. It is a figure which shows the relationship between the stakeholders who utilize the health-project planning / improvement system of a present Example. It is a figure which shows the relationship between the stakeholders who utilize the health-project planning / improvement system of a present Example. It is a figure which shows an example of the screen displayed at the planning step of a present Example. It is a figure which shows an example of the participation recommendation and implementation recording screen of a present Example. It is a figure which shows an example of the participation recommendation improvement result screen of a present Example.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a diagram showing an example of the configuration of the health business planning / improvement system 100 of the present embodiment.

The health business plan / improvement system 100 of this embodiment is a computer having an input unit 102, a CPU 103, an output unit 104, a storage unit 105, and a data input / output unit 106.

The input unit 102 is a user interface (for example, a keyboard, a mouse, etc.) for the user to input data and instructions to the health business planning / improvement system 100. The CPU 103 is a processor that executes a program stored in the storage unit 105. The output unit 104 is a user interface (for example, a display, a printer, etc.) for presenting the execution result of the program to the user.

The storage unit 105 includes a storage device such as a memory or an auxiliary storage device. Specifically, the memory of the storage unit 105 includes a ROM that is a nonvolatile storage element and a RAM that is a volatile storage element. The ROM stores an immutable program (for example, BIOS). The RAM is a high-speed and volatile storage element such as a DRAM (Dynamic Random Access Memory), and temporarily stores a program stored in the auxiliary storage device and data used when the program is executed. Specifically, the memory realizes functional blocks such as an effect prediction unit 110, a planning unit 111, an execution recording unit 112, an evaluation unit 113, an improvement proposal unit 114, a medical cost prediction model construction unit 115, and a control unit 116. Store the program for

The auxiliary storage device of the storage unit 105 is a large-capacity nonvolatile storage device such as a magnetic storage device (HDD) or a flash memory (SSD). The auxiliary storage device stores a program executed by the CPU 103 and data used when the program is executed. That is, the program is read from the auxiliary storage device, loaded into the memory, and executed by the CPU 103.

The data input / output unit 106 is an interface for inputting / outputting data stored in the database via a network or the like.

The database A120 is a database that stores information used by the health business planning / improvement system 100 for processing, and is managed by a business provider that provides a health business support service. The database A120 includes a medical cost prediction model 121 that stores a model indicating a relationship between a health condition and a medical cost, health guidance plan information 122 that stores a plan of a target person of which health guidance program, and effects of the health guidance program. The health guidance program performance model 123 to be stored, the predicted medical cost restraint effect 124 for storing the predicted result of the medical cost restraint by the health guidance program, and the distribution of the characteristics of the target person at the time of planning the health guidance program Number distribution 125.

The database B130 is a database managed by the insurer, and includes personal attribute information 131 for storing individual attribute information such as gender, age, and address of the insurance subscriber, and a health check result for storing the health check result received by the subscriber. It includes medical information 132 and medical cost payment information 133 that stores information on medical expenses paid for medical practices performed by the medical institution to the subscriber.

The database C140 is a database managed by a medical institution, and stores medical records 141 in which test results, medical practices, and disease names performed by the medical institution are recorded, and information for charging the insurer for medical expenses for medical care. And billing information 142.

The database D150 is a database managed by an organization that provides a health guidance program service (for example, a medical examination organization or a company), and includes health guidance program performance information 151 that is information on participants of the health guidance program. The health guidance program targeted by the health business planning / improvement system 100 of the present embodiment is provided from a health examination organization to a health check recipient, from a company to an employee, from an insurer to an insured person Provided to the employees of the entrusted company and the insured persons of the insurer from the provider providing the health business support service. For this reason, individuals whose information is processed by the health business planning / improvement system 100 are health checkup recipients, company employees, and health insurance insured persons.

The program executed by the CPU 103 is provided to the health business planning / improvement system 100 via a removable medium (CD-ROM, flash memory, etc.) or a network, and is stored in a nonvolatile storage device that is a non-temporary storage medium. Therefore, the health business planning / improvement system 100 may have an interface for reading data from the removable media.

The health business planning / improvement system 100 according to the present embodiment is a computer system configured on a single computer or a plurality of computers configured logically or physically, and on the same computer. It may operate in a separate thread, or may operate on a virtual machine constructed on a plurality of physical computer resources.

FIG. 2 is a diagram showing an example of the medical examination information 132 used by the health business planning / improvement system 100 of the present embodiment.

The medical examination information 132 includes a field for recording a personal ID 201 for uniquely identifying an individual, a medical examination date 202, and a test value. The test values include, for example, the BMI 203, the abdominal circumference 204 as a result of measuring the circumference of the abdomen, the fasting blood glucose level 205, the systolic blood pressure 206, the neutral fat 207, and the like, but may include other test values. The medical examination information 132 may include other information (for example, information on lifestyle habits such as eating habits, exercise habits, and smoking habits). In this example, the medical checkup result is stored in the medical checkup information 132 of the database B130. However, the medical checkup result may be acquired from the medical record 141 of the medical institution.

FIG. 3 is a diagram illustrating an example of a health guidance program performance model 123 used by the health business planning / improvement system 100 according to the present embodiment.

The health guidance program performance model 123 includes fields for recording a health guidance program name 301, an effect item 302 improved by the health guidance program, and an effect amount 303 improved by the health guidance program. In FIG. 3, the improvement effect for each health guidance program is shown by one numerical value, but the improvement effect may be shown by a mathematical expression or a table. For example, it is possible to use a table or function that divides blood glucose levels into a plurality of ranges and defines an improvement effect for each range.

FIG. 4 is a diagram illustrating an example of the predicted medical cost suppression effect 124 used by the health business planning / improvement system 100 of the present embodiment.

The predicted medical cost control effect 124 is a priority 401 for participation in the health guidance program given in descending order of the medical cost control effect, a personal ID 402 for uniquely identifying the health guidance target, and participation in the health guidance program. It includes fields for recording the predicted medical cost 403 when not performing, the predicted medical cost 404 when participating in the health guidance program, and the medical cost restraining effect 405. The predicted medical cost control effect 124 is configured as a separate table for each health guidance program, but may be configured as one table including identification information for identifying the health guidance program.

FIG. 5 is a diagram showing an example of health guidance program performance information 151 used by the health business planning / improvement system 100 of the present embodiment.

The health guidance program performance information 151 is a table in which the results of the health guidance program are stored. The individual ID 501 for identifying an individual, the participation 502 indicating whether or not to participate in the health guidance program, and the implementation of the health guidance program. Degree of activity 503, in the case of a weight loss program, a goal achievement 504 indicating whether the target weight has been achieved or not achieved, a result BMI 505 indicating the amount of improvement in BMI as a result of participation in the health guidance program, and blood glucose It includes a field for recording a result blood glucose level 506 indicating the amount of improvement of the value. The activity level 503 may be, for example, the frequency at which an action performed for health such as weight recording in the health guidance program is performed.

FIG. 6 is a diagram showing an example of the participation rate improvement proposal list output by the improvement proposal unit 114 of the present embodiment.

The improvement proposal list includes a field for recording a participant characteristic item 601, a value range 602, and a participation number difference 603 indicating the number of people who actually participated with respect to the expected number of people.

FIG. 7 is a diagram illustrating an example of a medical cost prediction model 121 used by the health business planning / improvement system 100 according to the present embodiment.

The medical cost prediction model 121 is created based on medical examination information 132 and medical cost payment information 133 held by the insurer, medical record 141 and medical cost billing information 142 held by the medical institution, and the like. Here, using the information for two years, the health check information such as the presence of diabetes in the first year, blood glucose level, blood pressure, etc., the examination information at the medical institution, and the information on the medical expenses for the second year The result stored as a model is illustrated. Actually, the medical cost prediction model 121 is complicated, including various test values and disease states in the first year, and medical costs of various diseases in the second year. Learning using Bayesian network structure learning technology, etc., and constructing a model that predicts medical expenses in the following year for the health status of the first year.

The construction method of the medical cost prediction model 121 is described in detail in, for example, Japanese Patent Application Laid-Open No. 2014-225176 (US Patent Publication No. 2014/0343965). In addition to the method shown in this example, the medical cost prediction model uses another statistical model or function as long as it expresses the relationship between test values, lifestyle and disease states, and future medical costs. Also good.

FIG. 12 is a diagram showing an example of the characteristic-specific population distribution 125 used by the health business planning / improvement system 100 of the present embodiment.

FIG. 12 shows a distribution relating to blood glucose level as a characteristic relating to a certain health guidance program A. The number distribution by characteristic 125 includes a range 1201 in which blood glucose levels are stratified, a number of persons 1202 at the time of planning for the layer, a number of persons 1203 at the time of execution, and a difference in the number of persons indicating the difference between the number of persons at the time of execution and the number of persons at the time of planning. The field includes 1204, a weight 1205 corresponding to the medical cost restraint amount, a weighted number of people 1206 at the time of planning, a weighted number of people 1207 at the time of execution, and a weighted number of people difference 1208.

FIGS. 13A and 13B are diagrams illustrating an example of an improvement proposal screen output by the output unit 104 of the health business planning / improvement system 100 according to the present embodiment.

An improvement proposal screen 1301 shown in FIG. 13A is a screen showing an improvement proposal by the health guidance program A. The number 1302 at the time of planning and execution, a selection field 1303 for comparison method, the distribution of people at the time of planning, and the number at the time of execution Characteristic information 1304 having a difference with the number distribution and a distribution 1305 of participants related to the selected characteristic are displayed. The distribution 1305 of the participants includes a graph 1306 of the distribution of the number of people according to the characteristics of the characteristics at the time of planning and execution, and a graph 1307 of the distribution of the number of people at the time of planning and execution. Further, the range of the number of participants having a large difference between the plan time and the execution time may be highlighted on the graphs 1306 and 1307 (1308, 1309).

Further, the improvement proposal screen 1311 shown in FIG. 13B is a screen showing another improvement proposal by the health guidance program A. The number of people 1302 at the time of planning and execution, the selection field 1303 for comparison method, and the distribution of people at the time of planning. And the information 1304 of the characteristics that have a difference between the distribution of the number of persons at the time of execution and the distribution 1305 of the participants regarding the selected characteristics. Participant distribution 1305 includes a graph 1316 of weighted distribution of people by stratification of characteristics at the time of planning and execution, and a graph 1317 of distribution of weighted differences between people at the time of planning and execution. A method for calculating the weighted difference in the number of persons will be described later. Further, the range of the number of participants having a large difference between the plan time and the execution time may be highlighted on the graphs 1316 and 1317 (1318, 1319).

As described above, the improvement proposal screens 1301 and 1311 display the number of people at the time of planning and the number of people at the time of execution and information indicating the selected hierarchy. Can be used to improve the participation rate in the teaching program.

FIG. 8 is an overall flowchart of processing executed by the health business planning / improvement system 100 according to the present embodiment, which is executed by the control unit 116.

First, in the medical cost prediction preparation step 801, the control unit 116 calls the medical cost prediction model construction unit 115. The medical cost prediction model construction unit 115 uses the medical examination information 132 and medical cost payment information 133 held by the insurer, the medical record 141 and the medical cost billing information 142 held by the medical institution, and the medical treatment shown in FIG. A cost prediction model 121 is created and stored in the database A120.

Next, in the planning step 802, the control unit 116 calls the planning unit 111. The planning unit 111 uses the medical examination information 132, the health guidance program performance model 123, and the medical cost prediction model 121 to determine a target person to which each health guidance program is applied, and formulates a health guidance plan. . Details of the planning step 802 will be described later with reference to FIG.

Next, in the health guidance program implementation step 803, health guidance is implemented for the target person based on the plan formulated in step 802. At this time, the execution recording unit 112 records the participation or non-participation of the subject in the health guidance program. Further, the execution recording unit 112 records the result of guidance and changes in weight and test values in the health guidance program performance information 151. You may store the change of the test value acquired from the medical examination information 132 and compared with before guidance.

Next, in the evaluation step 804, the control unit 116 calls the evaluation unit 113. The evaluation unit 113 uses the medical examination information 132, the health guidance program performance information 151, the medical cost prediction model 121, and the predicted medical cost suppression effect 124 at the time of planning, and the predicted medical cost suppression effect at the time of planning, To compare and evaluate the effect of suppressing medical expenses after the implementation of the health guidance program. Details of the evaluation step 804 will be described later with reference to FIG.

Next, in the improvement proposal step 805, the control unit 116 calls the improvement proposal unit 114. The improvement proposing unit 114 acquires the medical examination information 132, the health guidance program performance information 151, the medical cost prediction model 121, the predicted medical cost suppression effect 124 at the time of planning and evaluation, and the number distribution 125 according to characteristics. Propose plan improvements. Details of the improvement proposing step 805 will be described later with reference to FIG.

These procedures are performed, for example, on a yearly basis, execute the planning step 802 at the start (or before the start) of the year, and then implement the health guidance program at the end of the year (or after the end). ) Executes an evaluation step 804 and an improvement proposal step 805, which are repeated every year (806). Then, using the improvement proposal calculated in the improvement proposal step 805, a plan for the next cycle is made. The cycle for executing the procedure may be set according to the operation of the user such as a half year or a month instead of a year.

FIG. 9 is a flowchart showing details of processing executed by the planning unit 111 of the health business planning / improvement system 100 in the planning step 802 of the present embodiment.

First, the planning unit 111 acquires information necessary for processing (901). Specifically, the planning unit 111 acquires, for example, the medical examination information 132 of the health guidance target person, the health guidance program performance model 123, and the medical cost prediction model 121 via the data input / output unit 106. . Further, according to the budget of the company or the insurer, the input of the number of subjects of each health guidance program is prompted, and the number of subjects is acquired from the input unit 102. In the present embodiment, for example, it is planned to implement the health guidance program A for 150 people and the health guidance program B for 100 people.

Next, using the acquired medical examination information 132 and the medical cost prediction model 121, the predicted medical cost for each individual when not participating in the health guidance program is calculated, and the program of the predicted medical cost suppression effect 124 is not included Recorded in the predicted medical cost 403 (902). Here, the X1, X2, and X3 values of the medical cost prediction model 121 shown in FIG. 7 include the latest diabetes obtained from personal checkup information, the test results such as fasting blood glucose level 205, systolic blood pressure 206, Applying other lifestyle habits, etc., predicting diabetes medical expenses (X4) one year later. For example, it can be predicted that the predicted medical cost after one year of the health guidance target person whose personal ID is K0001 is 50,000 yen. Similarly, the predicted medical expenses for all health guidance subjects are calculated.

Next, the processing of steps 903 to 909 is executed for each health guidance program. First, using the medical examination information 132 and the health guidance program performance information 151, a predicted medical examination result after participation in the health guidance program is calculated for each individual (903). For example, when the health guidance program A is targeted, the fasting blood glucose level 205 of the health guidance target person whose personal ID 201 is K0001 is 115, and referring to the effect item 302 and the effect amount 303 of the health guidance program performance model 123, The effect of the guidance program A is that the blood glucose level is −5%, so the blood glucose level after participation in the health guidance program A is calculated to be 109. Similarly, the health check result after participation of the health guidance program of all who have obtained health check information is predicted. The calculated predicted medical examination result may be temporarily stored in the storage unit 105 or may be stored in a field in which the predicted medical cost suppression effect 124 is not shown.

Next, using the predicted medical examination result after participation in the health guidance program calculated in step 903 and the medical cost prediction model 121, the predicted medical cost when participating in the health guidance program is calculated for each individual, and the predicted medical cost is calculated. The program of the suppression effect 124 is recorded in the predicted medical expenses 404 with participation (904). Specifically, the blood sugar level after participation in the health guidance program predicted in step 903 is applied to the blood sugar level of the medical cost prediction model 121 shown in FIG. For example, when a health guidance target person with personal ID K0001 participates in a health guidance program, the predicted medical cost after one year can be predicted to be 30000 yen. Similarly, acupuncture medical expenses after participation in the health guidance program for all who have obtained medical examination information are predicted.

Next, the difference between the predicted medical cost when not participating in the health guidance program calculated in step 902 and the predicted medical cost after participation in the health guidance program calculated in step 904 is calculated, and the predicted medical cost suppression effect 124 is calculated. Is recorded in the medical cost restraining effect 405 (905). As mentioned above, the estimated medical cost when not participating in the health guidance program for a person with personal ID K0001 is 50000 yen, and the predicted medical cost when participating in the health guidance program is 30000 yen. This is a cost-saving effect. Similarly, the medical cost restraining effect of all who have obtained the medical examination information is calculated.

Next, with respect to the target health guidance program, the health guidance target people are arranged in descending order of the medical cost restraining effect 405, and the priority order for health guidance is determined (906). Specifically, the individuals are sorted by the medical cost restraint effect 405 of the predicted medical cost restraint effect 124 shown in FIG. 4, and the priority 401 of the health guidance program A is assigned to the personal ID 402.

Then, the total amount of medical expenses restrained when the health guidance program is implemented for the planned number of people for each health guidance program is calculated (907). For example, the total value of the medical cost suppression effect when 150 health guidance programs A are executed from the top is calculated, and the calculated total value is recorded in the total medical cost suppression effect 405 column of the predicted medical cost suppression effect 124 To do.

Next, the distribution of the number of persons divided according to the characteristic layer is created for the number of persons scheduled to be implemented from the top of the priority order for each health guidance program (908). For example, the blood glucose level is stratified in increments of 3 mg / dl from the health check result, and the number of people in the range is totaled and recorded in the planned number of people 1202 of the characteristic-specific number distribution 125 shown in FIG. Further, for each characteristic of other test values such as age, weight, blood pressure, etc., a distribution by number of persons 125 (a table recording the range 1201 and the planned number of persons 1202) in FIG. 12 is created and stored in the database A120. The characteristic value for creating the characteristic-specific person distribution 125 is determined separately.

Then, after calculating the number-of-characteristics distribution 125 of all characteristic values (YES in step 909), it is determined whether the processing from step 903 to step 909 has been completed for all health guidance programs (910). If there is an unprocessed health guidance program, the process returns to step 903 to execute the next health guidance program.

On the other hand, after the processing for all the health guidance programs is completed, the priority order for each health guidance program, the medical cost restraint effect, and the distribution of the number of people by characteristics are stored in the database A120 (911), and the processing is terminated.

Develop a health guidance plan through the process described above. In the health guidance program implementation step 803, the health guidance program is preferentially applied to those who can expect the improvement effect of the health guidance program by determining the priority order of the subjects based on the medical cost control effect of the health guidance program. be able to.

FIG. 10 is a flowchart showing details of processing executed by the evaluation unit 113 of the health business plan / improvement system 100 in the evaluation step 804 of the present embodiment.

As shown in FIG. 5, the health guidance program performance information 151 includes participation 502 indicating whether or not individuals participate in health guidance, activity level 503 of the participants, and achievement status of the goal (for example, aiming at weight loss). 504) and test results (BMI 505, result blood glucose level 506, etc.) performed by the health guidance implementation organization as an evaluation of the guidance results. In addition, at the time of execution of the evaluation step 804, the next medical examination is not yet performed and the medical examination information is not available.

First, the evaluation unit 113 acquires data necessary for processing (1001). Specifically, the evaluation unit 113 records, through the data input / output unit 106, the medical checkup information 132 of persons belonging to the group to be evaluated and the implementation status record of the evaluation target group of the health guidance program performance information 151. The medical cost prediction model 121 and the predicted medical cost suppression effect 124 created in the planning step 802 are acquired.

Next, the evaluation unit 113 selects a person who actually participated in the health guidance program from the health guidance program performance information 151, and selects the health examination information of the health guidance program participant from the acquired health examination information 132 (1002). ). Here, a person (that is, a participant) whose “participation” is recorded in the participation field 502 of the health guidance program result information 151 shown in FIG. 5 is selected, and the medical examination information of the participant is acquired from the medical examination information 132. To do.

Next, the evaluation unit 113 uses the medical examination information 132 for the participants and the medical cost prediction model 121 to calculate the predicted medical cost when not participating in the health guidance program for each individual (1003). The processing in step 1003 is the same as that in step 902 described above. Note that the predicted medical cost calculated in step 902 may be stored and used in step 1003.

Next, the medical examination information 132 and the health guidance program performance information 151 are combined to create a predicted health examination result after participation in the health guidance program for each individual (1004). For example, a person whose personal ID is K0003 participates in the health guidance program A. Since the BMI is -2.2 and the blood glucose level is -12 among the health check values, the health check information BMI 203 is 25.8 = 28-2. 2 and the blood glucose level is 99 = 111-12.

Next, the evaluation unit 113 uses the predicted health check result after participation in the health guidance program calculated in step 1004 and the medical cost prediction model 121 to calculate the predicted medical cost when participating in the health guidance program for each individual. (1005). The processing in step 1005 is the same as that in step 904 described above.

Next, the evaluation unit 113 calculates the medical cost that is the difference between the predicted medical cost when not participating in the health guidance program calculated at step 1003 and the predicted medical cost after participation in the health guidance program calculated at step 1004. The suppression effect is calculated (1006). And the evaluation part 113 adds the medical cost suppression effect of all the participants of a health guidance program, and calculates a total medical cost suppression effect (1007).

Thereafter, it is determined whether or not the processing from step 1004 to step 1007 has been completed for all health guidance programs (for example, health guidance programs A and B) (1008). If there is an unprocessed health guidance program, the process returns to step 1004 to execute the next health guidance program.

On the other hand, after the processing for all health guidance programs is completed, the predicted medical costs for the participants in the health guidance program and the medical cost restraint effect are recorded in the predicted medical cost restraint effect 124. (1009).

By the processing described above, it is possible to evaluate the difference in effect due to the difference between the scheduled target person and the target person who actually participated in the health guidance program.

11A and 11B are flowcharts showing details of processing executed by the improvement proposing unit 114 of the health business planning / improvement system 100 in the improvement step 805 of the present embodiment.

First, the improvement proposing unit 114 acquires necessary information (1101). Specifically, the improvement suggestion unit 114, via the data input / output unit 106, provides medical checkup information 132, health guidance program performance information 151, and medical cost prediction for people belonging to the group targeted for improvement proposal. The model 121, the medical cost suppression effect 124 at the time of planning and evaluation, and the number-of-characteristics distribution 125 are acquired. Next, the medical examination information of the health guidance program participant is selected from the acquired medical examination information 132 (1102). The processing in step 1102 is the same as that in step 1002 described above.

Next, the improvement proposing unit 114 creates a distribution of the number of persons divided according to the characteristics of the health guidance program participants, and records it in the number of persons column 1203 at the time of the distribution of the number of persons by characteristic 125 shown in FIG. 12 (1103). Then, the creation of the number distribution is repeated for each characteristic item (1104). The processes of steps 1103 and 1104 execute the processes of steps 908 and 909 for the medical examination information of the health guidance program participants. The created number distribution is recorded in the number-of-implementation number field 1203 of the characteristic-specific number distribution 125 shown in FIG.

Then, after creating the number distribution for all the characteristic items (YES in 1104), the improvement proposing unit 114 selects a certain characteristic value, and the number distribution of the selected characteristic value is changed from the number of people at the time of planning to the time of planning. The difference in the number of persons is calculated by subtracting the number of persons and recorded in the difference in number of persons column 1204 of the distribution by number of persons 125 shown in FIG. 12 (1105).

Next, the improvement proposing unit 114 determines whether to perform weighting (1106). A method of performing weighting will be described later, but a method of not performing weighting will be described first. When weighting is not performed, the improvement proposing unit 114 searches for a layer in which the difference in the number of people is a negative value (that is, a layer in which the number of people at the time of implementation is smaller than the number of people at the time of planning) in the number distribution (1110). In the example of the number distribution by characteristic 125 shown in FIG. 12, the number difference column 1204 is searched from the top, and the difference in the number of people in the layer whose blood glucose level is 105-107 is −5. ) And the information of the number of people−5 is stored in the storage unit 105 (1111). Further, the next layer is searched and repeated until the number distribution is not negative (1112). Here, since the blood glucose levels in the range of 108-110 and 111-113 are negative, it is recorded in the memory that there is a difference of −15 people, which is the total number of people in these three layers. Further, all the layers are searched (1113), and in the layers up to blood glucose level 120-125, the total difference in the number of people is −10, and the difference in the number of people in the two ranges is found. Further, this is repeated for characteristic values other than the blood glucose level (for example, age, differences in medical institutions, blood pressure, etc.) (1114). Then, the improvement proposing unit 114 arranges the layer information in descending order of the absolute value of the total difference (1115), and outputs the information on the improvement proposing screen 1311 shown in FIG. 13A (1116).

In this way, the distribution of the number of people is stratified by characteristics, and the hierarchy with a large difference between the number of people at the time of planning and the number of people at the time of execution is output as improvement proposals. Can do. This makes it possible to identify those who are encouraged to participate in the next health guidance program.

In the improvement proposal screen 1301 shown in FIG. 13A, as described above, the graph 1306 of the distribution of the number of people according to the characteristics at the time of planning and execution and the graph 1307 of the distribution of the number of people at the time of planning and execution are displayed. . In addition, the range of the number of participants having a large difference between the plan time and the execution time obtained in step 1115 is highlighted on the graphs 1306 and 1307 (1308 and 1309).

As described above, by selecting a range of characteristic values with fewer participants than at the time of planning, it is possible to find a layer that needs improvement.

On the other hand, if it is determined in step 1106 that the weighting based on the predicted medical cost is to be performed, the improvement proposing unit 114 first determines the weight from the medical cost restraint amount per person for each characteristic value layer (1107). Specifically, the average value of the medical cost restraining effect of people in each layer is calculated, and the value obtained by normalizing the calculated median average value by 1 as the weight of each layer is shown in FIG. Record in the weight 1205 of the distribution of different people 125. Next, the improvement proposing unit 114 creates a weighted number distribution by multiplying the number of persons according to the characteristic value by the weight (1108). In this case, the planned number of people 1202 is multiplied by the weight 1205 to calculate the weighted planned number of people 1206, and the execution time number of people 1203 is multiplied by the weight 1205 to calculate the weighted execution time number of people 1207. Then, the weighted execution time 1207 is subtracted from the weighted planning time 1206 to calculate a weighted difference (1109). Thereafter, the processing of steps 1110 to 1116 is executed as described above. The medical cost restraining effect used for weighting may be obtained from the medical cost restraining effect 405 obtained in the planning step shown in FIG. Although not shown, a table similar to that shown in FIG. 4 in which actual medical expenses are entered in 404 of FIG. 4 in the evaluation step 804 and a medical cost suppression effect obtained may be used.

When it is determined that weighting is to be performed, the improvement proposal screen 1311 shown in FIG. 13B has a weight distribution graph 1316 for each layer of the characteristics at the time of planning and at the time of execution, as described above, And a graph 1317 of the distribution of the difference in the number of persons with weights. Further, the range of the number of participants having a large difference between the plan time and the execution time obtained in step 1115 is highlighted on the graphs 1316 and 1317 (1318, 1319).

In this way, by selecting the range of characteristic values that have fewer participants than at the time of planning with weighting the amount of medical expenses curtailed, it is possible to find a layer with a large medical cost reduction effect and Encourage participation.

The illustrated improvement proposal screens 1301 and 1311 are examples, and all the illustrated items are not indispensable, and only arbitrary items may be displayed according to the usage pattern, and some items may not be displayed. For example, in the improvement proposal screen 1301, it is not necessary to display only the number distribution graph 1306 and display the number difference distribution graph 1307. Conversely, only the distribution graph 1307 of the difference in the number of people may be displayed, and the distribution graph 1306 of the distribution of the number of people may not be displayed.

In this embodiment, the distribution of the number of people by characteristic not weighted by the predicted medical expenses and the distribution of the number of persons by characteristic weighted by the predicted medical expenses are output and both are output, but only one of them is output. It may be calculated. For example, it is possible to calculate only the distribution by number of characteristics by weight with the predicted medical expenses without calculating the distribution by number of persons by characteristic without weighting.

The user uses this improvement proposal screen 1301 to select the characteristics of the group that need to improve the participation recommendation, and the participation rate of persons with this characteristic is improved at the time of the next planning or the implementation of the health guidance program. You can devise a way to encourage participation. For example, there are various methods such as soliciting by phone to each participant, sending materials introducing the relevant disease in an easy-to-understand manner, and conducting promotional activities at the workplace. Select participants for participation recommendations before the start of the health guidance program, or select a recommendation method that suits the characteristics of the participants.

As described above, the health business planning / improvement system 100 of this embodiment selects the characteristics of a person who is expected to participate in the health guidance program but has not participated. For this reason, when encouraging participation in a health guidance program conducted for another group, it is possible to improve the measures, such as strengthening the encouragement to participate in the health guidance program for people with selected characteristics. In particular, using the characteristics of people who actually participated in the health guidance program, it is possible to extract improvement points for obtaining the effects predicted at the time of planning.

FIG. 15 is a diagram illustrating an example of a screen displayed in the planning step 802 in the health business planning / improvement system 100 according to the present embodiment.

The screen example 1500 shown in FIG. 15 is output based on the plan prepared by the planning unit 111 in the second and subsequent planning steps 802 after performing steps 801 to 805 of the flowchart shown in FIG. 8 at least once. Displayed on the unit 104. A screen example 1500 shows the set scheduled number of persons to be executed 1501, the calculated medical cost restraint effect 1502, the list of candidates 1503 participating in the extracted health guidance program, the number distribution 1504 of candidates according to the test value hierarchy, participation Information 1505 regarding recommendation improvement is displayed.

In the candidate list 1503, among the candidates displayed in the order of priority of the candidates, whether the participation recommendation is determined according to the characteristic of the person who needs the improvement of the participation recommendation determined in the improvement proposal step 805, that is, the improvement of the participation recommendation is performed. Display whether it is necessary or not in the column of recommended participation improvement. This allows a person who plans a health guidance program to easily identify the person to be devised in the participation recommendation.

In addition, in the candidate number distribution 1504, it is possible to highlight a layer of people who need improvement in participation recommendation, and to understand the hierarchy to be devised in participation recommendation and the number of participation recommendation.

In addition, in the information 1505 regarding improvement of the participation recommendation, the characteristics of the layer that improves the participation recommendation selected in the improvement suggestion step 805 of the previous health guidance program and the improvement from the conventional participation recommendation for the people who should improve the participation recommendation. Display how to respond. For example, information on the method of participation recommendation for each characteristic is recorded, the method of participation recommendation is determined for each characteristic item with reference to this information, and displayed on the information 1505 regarding improvement of participation recommendation. It is also possible to record information on the method of participation recommendation for each characteristic and characteristic value range, not for each characteristic, and to determine the method of participation recommendation for each characteristic item and characteristic value range. Specifically, a countermeasure for additionally sending diabetes education materials to a person with a blood glucose level of 120 to 125 mg / dl or calling and inviting a person with an age of 40 to 49 individually is displayed. A countermeasure may be selected from this screen by preparing several methods in advance. Furthermore, the contents individually examined according to the range of characteristics may be recorded and displayed on this screen.

As described above, in the health business planning / improvement system 100 of the present embodiment, in the planning step 802, the characteristics of the person who needs the improvement of the participation recommendation determined in the improvement proposal step 805 already implemented are used. By doing so, it can be displayed in an easy-to-understand manner whether the candidate is a candidate who needs to improve the participation recommendation. In addition, it is possible to display the number of people who need improvement measures for participation encouragement and the details of the improvement measures in an easy-to-understand manner. In addition, the user can use this screen to formulate a health business plan with improved participation recommendations, and improve the participation rate in the health guidance program.

FIG. 16 is a diagram showing an example of a participation recommendation / implementation record screen used in the participation recommendation work in the health guidance program implementation step 803 in the health business planning / improvement system 100 of the present embodiment.

The participation recommendation / execution record screen example 1600 shown in FIG. 16 is displayed on the output unit 104 at the second and subsequent health guidance program implementation steps 803 after performing at least one time from step 801 to step 805 of the flowchart shown in FIG. Is done. The participation recommendation / execution record screen example 1600 displays a candidate list 1601. The candidate list 1601 includes priority 1611 to participate in the health guidance program, ID 1612, name 1613, necessity / unnecessity of additional participation 1614 due to improvement of participation recommendation, participation recommendation additional measure 1615, information 1616 on whether or not to participate, and the like. indicate.

For example, when encouraging participation in the health guidance program A in the health guidance program implementation step 803, refer to the list of the participation recommendation / implementation record screen 1600 and send the participation guidance by e-mail as a normal participation recommendation. Participation encouragement additional measure 1615 sends a diabetes pamphlet to those who are diabetic pamphlet sending. In addition, a person who is a telephone solicitation for the participation encouragement additional measure 1615 is telephoned together with the sending of an e-mail, explaining the necessity of improving lifestyle habits, etc., and performing activities to encourage participation.

When the candidate actually participates in the health guidance program, “participation” is recorded in the participation column 1616, and “non-participation” is recorded when not participating. Then, the health guidance program A is provided to the person whose participation column 1616 is “participation”. In this way, in the health guidance program execution step 803, for those who have characteristics that require improvement of the participation recommendation determined in the improvement proposal step 805 that has already been implemented, an additional participation recommendation measure is displayed on the screen. To do. Thereby, the person in charge of participation encouragement can easily recognize whether each person needs additional measures for participation promotion, and can improve the participation rate in the health guidance program.

FIG. 17 is a diagram showing an example of a participation recommendation improvement result screen displaying the evaluation result of the participation recommendation measure in the health business planning / improvement system 100 of the present embodiment.

The participation recommendation improvement result screen example 1700 shown in FIG. 17 is displayed on the output unit 104 in the second and subsequent evaluation steps 804 after the steps 801 to 805 of the flowchart shown in FIG. (Although not shown, it is output by a process different from the evaluation flowchart described in FIG. 10). The participation recommendation improvement result screen example 1700 displays a participation recommendation result list 1701. Participation recommendation result list 1701 includes a characteristic item 1711 of a target person who has made improvement measures for participation recommendation, a value range 1712 of the characteristic item, a participation recommendation measure 1713 before improvement, the number of people at the time of planning and the number of people at the time of improvement. The ratio 1714 of the improvement, the participation recommendation measure 1715 after the improvement, the ratio 1716 of the number of people at the time of planning after the improvement and the number of people at the time of execution, and the difference 1717 of the number of people before and after the improvement are displayed.

For example, the No1 line shows that the ratio of the number of people at the time of planning to the number of people at the time of execution was 0.2 (for example, last year) Had 50 participants at the time of planning, but 10 participants), the next time (for example, this year), as a result of implementing telephone solicitation measures after improvement, the number of people at the time of planning And the ratio of the number of people at the time of execution became 0.5 (for example, 25 of the 50 people at the time of planning participated), indicating that the difference in the ratio of the number of participants before and after the improvement was improved by 0.3.

These are recorded in the database A120 or the like about information on the characteristics of the person who improves the participation recommendation output from the improvement proposing unit 114, and in the evaluation step 804, the ratio of the number of people at the time of planning for the first year and the number of people at the time of implementation are recorded. The ratio is output so that it can be compared before and after the improvement. Thereby, it is possible to quantitatively grasp the improvement effect of the implemented recommendation. Furthermore, by displaying the participation recommendation improvement result screen example 1700 in the participation recommendation improvement proposal step 805 and the planning step 802, when improvement of the participation recommendation is necessary, the improvement measure is determined with reference to past cases. can do.

FIG. 14A to FIG. 14C are diagrams showing relationships between stakeholders who use the health business plan / improvement system 100 of the present embodiment.

FIG. 14A is a diagram showing the relationship between an insurer 1401, an individual 1404 who is an insurance subscriber, a service provider 1403 providing a health guidance program, and a business establishment 1402 such as a company to which the individual 1404 belongs. In the relationship shown in FIG. 14A, the service provider 1403 creates a health guidance plan by the health business planning / improvement system of the present embodiment, and the business office 1402 provides the health guidance service. FIG. 14B is a diagram showing a relationship among an insurer 1401, an individual 1404 who is an insurance subscriber, a medical institution 1405 used by the individual, and a service provider 1403. In the relationship shown in FIG. 14B, the service provider 1403 creates a health guidance plan by the health business plan / improvement system of this embodiment, and the medical institution 1405 provides the health guidance service. FIG. 14C is a diagram showing a relationship between an individual 1404, a service provider 1403 that provides a health guidance program, and a business establishment 1402 to which the individual 1404 belongs. In the example shown in FIG. 14C, instead of the insurer, the business establishment 1402 to which the individual belongs entrusts the activity to the service provider 1403 to promote employee health.

FIG. 14A shows an example in which the service provider 1403 entrusts a plan for health guidance and implementation of health guidance from the insurer 1401. The insurer 1401 provides medical insurance for individuals 1404 who belong to the office 1402, and provides health guidance to the individuals 1404 in order to optimize medical expenses expenditure. The service provider 1403 has the insurance business plan / improvement system 100, the database A120, and the database D150, and the insurer 1401 has the database B130.

The insurer 1401 provides information such as medical checkup information 132 and medical expenses payment information 133 to the service provider 1403 (1), and the service provider 1403 uses the planning unit 111 of the insurance business plan / improvement system 100. Then, determine the target of each health guidance program and formulate a health guidance plan (2). The service provider 1403 provides the planned plan to the insurer 1401 (3). The insurer 1401 encourages the individual 1404 to participate in the health guidance program according to the provided plan (4). When the individual 1404 agrees to participate in the health guidance program (5), the insurer 1401 provides information about the participant to the service provider 1403 (6).

The service provider 1403 provides the health guidance program to the individual 1404 (7). The service provider 1403 acquires the participation status and results of the individual 1404 during and after the health guidance program (8), and records the health guidance program performance information 151. Then, the service provider 1403 evaluates the health guidance result by the evaluation unit 113 (9), creates the improvement contents of the plan by the improvement proposal unit 114 (10), and reports the evaluation result and the improvement proposal to the insurer 1401. (11).

The insurer 1401 uses the proposed method to improve the participation recommendation method and encourages the target person to participate (12). In addition, participation may be encouraged to the target person through the office 1402 (12). For example, if this suggestion should be recommended because participation in a human health guidance program for certain characteristics (age group, laboratory value group, etc.) is less than planned, the insurer 1401 Encourage improved participation and encouragement activities such as frequent communication of recommendations, direct dialogue, and encouragement of participation through the establishment 1402 to ensure that people with specific characteristics participate in health guidance programs.

The insurer 1401 pays the cost to the service provider 1403 who has performed a series of tasks such as the planning, implementation, evaluation, and improvement proposal of the above-described health guidance (13).

FIG. 14B shows an example in which an insurer 1401 provides medical insurance to a general individual 1404, the insurer 1401 and a medical institution 1405 are operated in the same mother body, and health guidance is provided to a person who consulted the medical institution. Show. In this case, the medical institution 1405 holds the database C 130, uses the medical institution's medical record 141 instead of the insurer's medical examination information 132, and uses the medical expense billing information 142 instead of the medical expense payment information 133. Other data is the same as that shown in FIG. 14A.

First, the medical institution 1405 provides the service provider 1403 with the medical record 141 and the medical cost payment information 133 via the insurer 1401 (1). The service provider 1403 creates a health guidance plan (2), and notifies the insurer 1401 of the drafted plan (3). The insurer 1401 presents the participant's standard information (standards such as test values, age, and lifestyle) based on the plan to the medical institution 1405 (4). The medical institution 1405 encourages the individual who meets the medical institution (5) to participate in the health guidance program (6) and the individual 1404 agrees to participate (6) 7) The agreed individual 1404 is introduced to the service provider 1403 (8).

The service provider 1403 provides a health guidance program to the introduced individual 1404 (9), acquires the participation status and results at that time (10), and records the health guidance program performance information 151. Then, the service provider 1403 evaluates the result of health guidance by the evaluation unit 113 (11) and reports it to the insurer 1401 (12). Further, the service provider 1403 creates the improvement contents of the plan by the improvement proposal unit 114 (13), and reports the evaluation result and the improvement proposal to the insurer 1401 and the medical institution 1405 (14). The medical institution 1405 uses the proposed method to improve the participation recommendation method and encourages the subject to participate (15).

The insurer 1401 pays the cost to the service provider 1403 that has implemented a series of tasks such as the planning, implementation, evaluation, and improvement proposal of the above-described health guidance (16).

FIG. 14C shows an example in which the service provider 1403 entrusts health guidance provided by the establishment 1402 such as a company to the individual 1404 instead of the insurer.

The establishment 1402 has the same information as the database B130, records the result of the medical examination conducted by the establishment 1402 in the medical examination information 132, and pays the medical expenses paid to the insurer by the establishment. Record in information 133. The medical cost payment information 133 may include a loss cost due to absenteeism or a decline in ability caused by an illness of an individual belonging to the office.

The service provider 1403 obtains such information from the establishment 1402 (1), draws up a health guidance plan (2), and provides the established plan to the establishment 1402 (3). The establishment 1402 encourages individuals 1404 to participate in the health guidance program according to the provided plan (4). When the individual 1404 agrees to participate in the health guidance program (5), the establishment 1402 provides the participant information to the service provider 1403 (6).

The service provider 1403 provides the health guidance program to the individual 1404 (7). The service provider 1403 acquires the participation status and results of the individual 1404 during and after the health guidance program (8), and records the health guidance program performance information 151. Then, the service provider 1403 evaluates the health guidance result by the evaluation unit 113 (9), creates the improvement contents of the plan by the improvement proposal unit 114 (10), and reports the evaluation result and the improvement proposal to the insurer 1401. (11).

The establishment 1402 uses the proposed method to improve the participation recommendation method, and encourages the target person to participate (12). The business establishment 1402 pays a cost to the service provider 1403 that has implemented the series of operations of health guidance planning, implementation, evaluation, and improvement proposal described above (13).

As described above, the service provider 1403 uses the health business planning / improvement system 100 of this embodiment to plan health guidance using information held by the insurer 1401 and the business establishment 1402. Implementation, evaluation, and improvement can improve the health of the individual 1404 and reduce medical costs. The service provider 1403 can receive payment for service provision. In particular, even if the information held by each institution differs depending on the roles of the insurer, medical institution, and business establishment, the PDCA cycle of the health business can be realized by utilizing the information held by each institution.

As described above, according to the embodiment of the present invention, the characteristics of a person who is expected to participate in the health guidance program but is not participating are specified, and the person with the specified characteristics in the subsequent health guidance program is targeted. In addition, measures such as encouraging participation in health guidance programs can be improved. That is, the improvement point for obtaining the effect predicted at the time of planning can be extracted from the difference between the characteristics of the target person at the time of planning and the characteristics of the actual participants.

The present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the scope of the appended claims. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and the present invention is not necessarily limited to those having all the configurations described. A part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Moreover, you may add the structure of another Example to the structure of a certain Example. In addition, for a part of the configuration of each embodiment, another configuration may be added, deleted, or replaced.

In addition, each of the above-described configurations, functions, processing units, processing means, etc. may be realized in hardware by designing a part or all of them, for example, with an integrated circuit, and the processor realizes each function. It may be realized by software by interpreting and executing the program to be executed.

Information such as programs, tables, and files that realize each function can be stored in a storage device such as a memory, a hard disk, and an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, and a DVD.

Also, the control lines and information lines indicate what is considered necessary for the explanation, and do not necessarily indicate all control lines and information lines necessary for mounting. In practice, it can be considered that almost all the components are connected to each other.

Claims (14)

1. An analysis system comprising a processor and a memory connected to the processor,
   The analysis system has a stochastic dependency between health check information including a result of a health check of a subscriber, a node corresponding to a random variable representing a disease state, and a node corresponding to a random variable of a factor that changes the disease state. Has access to a database that includes a medical cost forecasting model defined by directed or undirected edges and health guidance program effects, including the benefits that can be expected from the health guidance implemented to subscribers;
   The processor refers to the medical examination information, the medical cost prediction model, and the health guidance program effect, and implements a first medical cost when the subscriber has implemented at least one health guidance program. Predicting the second medical cost when there is not, calculating the difference between the first medical cost and the second medical cost as a medical cost restraining effect, and subjects of the health guidance program in descending order of the medical cost restraining effect A planning department that determines the implementation plan for the health guidance program,
   An execution recording unit for recording the participation status of the health guidance program;
   The processor is an evaluation unit that seeks the medical cost control effect of participants of the health guidance program;
   The processor calculates the characteristics of the target of the health guidance program at the time of planning and the characteristics of the participants of the health guidance program, and the number of target persons of the health guidance program at the time of planning and the participants of the health guidance program An analysis system comprising: an improvement proposing unit that selects a characteristic having a large difference from the number of people at the time of execution and outputs the selected characteristic as improvement required information.
2. The analysis system according to claim 1,
   The improvement proposal section
   The number of people at the time of planning for the target of the health guidance program is weighted according to the amount of medical expenses restrained, and the number of people at the time of planning is calculated.
   Calculating the number of people at the time of execution by weighting the number of participants at the time of the health guidance program according to the amount of medical expenses restrained;
   An analysis system, wherein a characteristic having a large difference between the calculated planned number of persons and the calculated execution number is selected, and the selected characteristic is output as the improvement required information.
3. The analysis system according to claim 1 or 2,
   The improvement proposal section
   Classifying the number of people at the time of planning and the number of people at the time of execution according to the range of the characteristics;
   An analysis system, wherein a range in which the difference between the planned number of people and the execution time number is large is selected, and the selected range is output as the improvement required information.
4. The analysis system according to claim 3,
   The improvement proposing unit outputs screen data for displaying the number of people at the time of planning and the number of people at the time of execution for each classified range, and information indicating the selected range.
5. The analysis system according to claim 3,
   The evaluation unit has a ratio selected between the number of participants and the number of participants in the range recommended to participate in the previous health guidance program because of the characteristics selected by the improvement proposal unit, and An analysis system characterized by outputting screen data for displaying the ratio of the number of subjects and the number of participants in a range recommended to participate so as to be comparable.
6. The analysis system according to claim 1 or 2,
   The planning section includes a method for encouraging a person having the characteristics selected by the improvement proposing section to participate in the health instruction program, and information on whether the characteristic is selected by the improvement proposing section. An analysis system that outputs screen data for displaying a target person.
7. A health business support method executed in a system for evaluating a health business,
   The system includes a processor that executes a program, and a memory that stores the program.
   The system has a stochastic dependency between the medical examination information including the result of the health check of the subscriber and the node corresponding to the random variable representing the disease state and the node corresponding to the random variable of the factor that changes the disease state. Has access to a database containing medical cost forecasting models defined by opposite or undirected sides and health guidance program effects, including the benefits expected from the health guidance implemented for subscribers;
   The method
   The processor refers to the medical examination information, the medical cost prediction model, and the health guidance program effect, and implements a first medical cost when the subscriber has implemented at least one health guidance program. Predicting the second medical cost when there is not, calculating the difference between the first medical cost and the second medical cost as a medical cost restraining effect, and subjects of the health guidance program in descending order of the medical cost restraining effect Planning steps to determine the implementation plan for the health guidance program;
   An execution recording step in which the processor records the participation status of the health guidance program;
   An evaluation step in which the processor obtains a medical cost control effect of a participant of the health guidance program; and
   The processor calculates the characteristics of the target of the health guidance program at the time of planning and the characteristics of the participants of the health guidance program, and the number of target persons of the health guidance program at the time of planning and the participants of the health guidance program A health business support method, comprising: selecting a characteristic having a large difference from the number of people at the time of execution, and outputting the selected characteristic as information requiring improvement.
8. The health business support method according to claim 7,
   In the improvement proposal step,
   The number of people at the time of planning for the target of the health guidance program is weighted according to the amount of medical expenses restrained, and the number of people at the time of planning is calculated.
   Calculating the number of people at the time of execution by weighting the number of participants at the time of the health guidance program according to the amount of medical expenses restrained;
   A health business support method, wherein a characteristic having a large difference between the calculated planned number of persons and the calculated execution number is selected, and the selected characteristic is output as the improvement required information.
9. A health business support method according to claim 7 or 8,
   In the improvement proposal step,
   Classifying the number of people at the time of planning and the number of people at the time of execution according to the range of the characteristics;
   A health business support method, wherein a range in which the difference between the planned number of people and the execution time number is large is selected, and the selected range is output as the improvement required information.
10. The health business support method according to claim 9,
    In the improvement proposing step, health data support for outputting screen data for displaying the number of people at the time of planning and the number of people at the time of execution for each classified range and information indicating the selected range Method.
11. The health business support method according to claim 9,
    In the evaluation step, because of the characteristics selected in the improvement proposal step, the ratio between the number of subjects and the number of participants in the range recommended to participate in the previous health guidance program, and the current health guidance program. A health business support method characterized by outputting screen data for displaying a comparison of the ratio of the number of subjects and the number of participants in the recommended range of participation.
12. A health business support method according to claim 7 or 8,
    In the planning step, the method of encouraging a person having the characteristics selected in the improvement proposal step to participate in the health guidance program, and the health guidance with information on whether the characteristic is selected in the improvement proposal step A health business support method characterized by outputting screen data for displaying a program target person.
13. An analysis system comprising a processor and a memory connected to the processor,
    The analysis system includes health check information in which a health condition including any of a subscriber's test value, lifestyle, and disease state is recorded, and a health care cost prediction in which a relationship between the health check information and future medical expenses is expressed. Access to a database containing models and health guidance program effects, including the benefits that can be expected from health guidance delivered to subscribers;
    The processor refers to the medical examination information, the medical cost prediction model, and the health guidance program effect, and implements a first medical cost when the subscriber has implemented at least one health guidance program. Predicting the second medical cost when there is no medical cost, calculating the difference between the first medical cost and the second medical cost as a medical cost restraining effect, and using the medical cost restraining effect as a target person for a health guidance program A planning department that determines the implementation plan for the health guidance program,
    An execution recording unit for recording the participation status of the health guidance program;
    The processor calculates the number of subjects at the time of planning set by the planning unit and the number of participants at the time of execution recorded by the execution recording unit according to the characteristics indicated by the state of the items of the medical examination information, An analysis system comprising: an improvement proposing unit that selects a characteristic having a large difference between the number of target persons at the time of planning and the number of participants at the time of execution, and outputs the selected characteristic as necessary improvement information.
14. The analysis system according to claim 13,
    The processor comprises an evaluation unit that seeks a medical cost control effect of participants of a health guidance program,
    The improvement proposal section
    Calculate the number of people at the time of planning by weighting the number of subjects at the time of planning of the health guidance program according to the amount of medical cost restraint obtained by the evaluation unit,
    The number of participants at the time of execution of the health guidance program is weighted according to the amount of medical expenses restraint obtained by the evaluation unit, and the number of participants at the time of calculation is calculated.
    An analysis system, wherein a characteristic having a large difference between the calculated planned number of persons and the calculated execution number is selected, and the selected characteristic is output as the improvement required information.

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