JP6799403B2 - Health guidance support device, health guidance support method and program - Google Patents

Description

The present invention relates to a technique for effectively and efficiently determining the selection of the optimum instructor for a patient in health instruction.

In order to curb medical expenses due to the increase in lifestyle-related diseases, programs are being implemented to provide appropriate health guidance according to the individual's health condition, as represented by specific health guidance. In such a health guidance program, public health nurses, registered dietitians, and other instructors provide guidance for improving lifestyle habits related to diet, exercise, etc. to instructors (hereinafter referred to as users). In general, a user in charge is assigned to a user registered in a health guidance program, and guidance is given for a certain period of time through various methods such as telephone, email, and face-to-face guidance. The purpose of the instruction is wide-ranging, for example, weight loss instruction for persons with metabolic syndrome, blood sugar control, medication instruction, etc., but in order to obtain a high instruction effect, the user should maintain motivation and continuously work on the program without dropping out. is important. Therefore, instructors are required to have the ability to properly communicate with users and control their motivation. Therefore, it is necessary to select an appropriate leader for the user, and it is necessary to be able to execute it easily in consideration of a plurality of leader resources.

Patent Document 1 discloses a technique for assigning an experienced nurse to a person in charge based on a past experience case.

Japanese Unexamined Patent Publication No. 2008-234185

Judgment as to whether or not the allocation rule is satisfied when the patients are assigned to inexperienced nurses whose disease names are not included in the experienced cases in descending order of years of experience, as in the technique described in Patent Document 1. When the treatment is performed and the nurse in charge is assigned when the allocation rule is satisfied, it becomes difficult to make a judgment based on the experienced case when the subject does not necessarily have the disease, as in the case of health guidance. Also, no consideration is given to the part of communication between the leader and the user.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a leader selection technique for appropriately selecting a leader and a user from the viewpoint of the guidance effect and obtaining a higher guidance effect. ..

The present invention is a health guidance support device having a processor and a storage unit that can be read and written from the processor to support the health guidance of a participant, and the storage unit is a user information of the participant and the user information of the participant. The processor holds lifestyle information that accumulates the results of health guidance for each participant, classifies the participants from the user information, generates a plurality of clusters, and provides health guidance for the participants for each cluster. Based on the results of, the appropriate scores of a plurality of instructors are calculated and held in the appropriate judgment information, and the appropriate scores are calculated from the results of lifestyle information accumulating the results of the health guidance, and the instructors Is set with unit price information regarding instruction, the unit price information includes the hourly reward of the instructor, and the processor corrects the appropriate score with the unit price information.

According to the health guidance support device according to the present invention, it is possible to efficiently and quickly determine the optimum person in charge selection among a plurality of leaders and a plurality of participants, and a higher guidance effect can be obtained. .. In addition, even if it is unavoidable to change the instructor, the instructor can be determined quickly, and the work related to the selection of the instructor can be significantly reduced.

It is a block diagram which shows 1st Example of this invention and shows an example of the structure of the health guidance support device. It is a figure which shows the 1st Example of this invention and shows an example of the user attribute table. It is a figure which shows the 1st Example of this invention and shows an example of the lifestyle-related information table (meal). It is a figure which shows the 1st Example of this invention and shows an example of the lifestyle information table (exercise). It is a figure which shows the 1st Example of this invention and shows an example of the lifestyle information table (improvement target). It is a figure which shows the 1st Example of this invention and shows an example of the interview information table. It is a figure which shows the 1st Example of this invention and shows an example of a leader attribute table. It is a figure which shows the 1st Example of this invention and shows an example of the instruction schedule table. It is a figure which shows the 1st Example of this invention and shows an example of the instruction performance table. It is a figure which shows the 1st Example of this invention and shows an example of the leader grade table. It is a figure which shows the 1st Example of this invention and shows an example of a cluster management table. It is a figure which shows the 1st Example of this invention and shows an example of the appropriateness determination table. It is a figure which shows the 1st Example of this invention and shows an example of the medical knowledge management table. It is a figure which shows the 1st Example of this invention and shows an example of the usage situation table. It is a flowchart which shows the 1st Example of this invention and shows an example of the process of calculating an appropriate score. It is a flowchart which shows the 1st Example of this invention and shows an example of the process of selecting a person in charge of instruction based on an appropriate score. It is a figure which shows the 1st Example of this invention and shows an example of the screen for setting the optimization index (KPI). It is a figure which shows the 1st Example of this invention and shows an example of the screen for displaying and selecting a leader selection result. It is a flowchart which shows the 2nd Example of this invention and shows an example of the process which selects the person in charge of instruction based on the appropriate score in consideration of the instruction unit price. It is a figure which shows the 2nd Example of this invention, and shows an example of the screen for displaying and selecting a leader selection result in consideration of a guidance unit price. It is a block diagram which shows the 3rd Example of this invention and shows an example of the structure of the health guidance support apparatus. It is a figure which shows the 3rd Example of this invention and shows an example of the screen for making a plan for securing a leader human resources.

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

Hereinafter, as Example 1 of the present invention, an example of selecting the most suitable instructor for a user (user) by using a health instruction program provided through the Internet will be described with reference to the drawings.

FIG. 1 is a block diagram showing a configuration example of the health guidance support device 101 according to the first embodiment of the present invention. The health guidance support device 101 is connected to the instructor terminal 109 and the user terminal 110 via the network 108. The instructor terminal 109 is used by an instructor who gives guidance to users (participants) of the health guidance program. The user terminal 110 is operated by a user (participant) who uses the health guidance program.

The health guidance support device 101 is a computer including an input unit 102 such as a keyboard and a mouse, an output unit 103 representing a display, a CPU 104, a memory 105, and a storage medium 106. The leader terminal 109 and the user terminal 110 are similar computers. The memory 105 and the storage medium 106 can function as a storage unit.

The health guidance support device 101 stores a program that provides a predetermined function in the storage medium 106, loads it into the memory 105, and executes it by the CPU 104. The storage medium 106 includes a user registration unit 111, a recommended instructor presentation unit 112, a lifestyle-related feature amount extraction unit 113, a cluster construction unit 114, a cluster allocation unit 115, an instructor grade processing unit 116, and the like. The appropriate score calculation unit 117, the instructor allocation determination unit 118, and the medical knowledge processing unit 119 are stored as programs.

The CPU 104 operates as a functional unit that provides a predetermined function by processing according to the program of each functional unit. For example, the CPU 104 functions as the user registration unit 111 by processing according to the user registration program. The same applies to other programs. Further, the CPU 104 also operates as a functional unit that provides each function of a plurality of processes executed by each program. A computer and a computer system are devices and systems including these functional parts.

The user registration unit 111 accepts the user of the health guidance program and registers it in the user attribute table 120, and also receives the inquiry information and registers it in the inquiry information table 122. In addition, the user registration unit 111 receives daily reports of users and stores them in the lifestyle-related information table 121.

As will be described later, the recommended leader presentation unit 112 presents a combination of a leader and a user who can obtain a high teaching effect from a combination of a plurality of leaders and a plurality of users. The lifestyle feature amount extraction unit 113 calculates the feature amount from the user's lifestyle information table 121 and the interview information table 122.

The cluster construction unit 114 generates a group of users from the features of users and instructors, and registers them in the cluster management table 127. The cluster allocation unit 115 allocates a group (cluster) of users to a leader. The leader grade processing unit 116 manages the leader grade table 126.

The appropriate score calculation unit 117 calculates the instruction appropriate score of the instructor for the group of users. The leader allocation determination unit 118 assigns the optimum leader to the user based on the guidance appropriate score and the guidance schedule of the leader.

A database 107 storing information used by each functional unit is connected to the health guidance support device 101. The database 107 includes a user attribute table 120, a lifestyle information table 121, an interview information table 122, an instructor attribute table 123, an instruction schedule table 124, an instruction record table 125, an instructor grade table 126, a cluster management table 127, and an appropriate judgment. The table 128, the medical knowledge management table 129, and the usage status table 130 are stored.

As shown in FIGS. 3 to 5, the lifestyle information table 121 includes a diet-related lifestyle information table 121-1, an exercise-related lifestyle information table 121-2, and improvement target-related lifestyle information. It is composed of tables 121-3.

FIG. 2 is a diagram showing an example of the user attribute table 120. The user attribute table 120 includes a user ID 201 that stores an identifier that identifies the user, a usage status 202 of the user's health guidance program, a guidance available date and time 203 that indicates the time that the user can secure for guidance, and a date of birth. Day 204, height 205, weight 206, gender 207, occupation 208, language 209, area of residence 210, time zone 211, health status 212, program enrollment history 213, and user type 215. And are included in one entry.

This information has the effect of enabling classification based on user attributes. At the start of the health guidance program, the user registration unit 111 receives the user information and generates or updates the user attribute table 120. In the health state 212, "00" indicates healthy and "01" indicates metabolic. The program subscription history 213 stores the number of times the health guidance program has been used. Further, the user type 214 stores the degree of positivity of the user for the health guidance program. For example, the larger the value, the higher the positivity.

FIG. 3 is a diagram showing an example of a diet-related lifestyle information table 121-1. The meal-related lifestyle information table 121-1 includes a user ID 201 that stores a user's identifier, a meal ID 301 that stores an identifier for identifying meal information for each user, and a meal that stores the date and time when the meal was eaten. The date and time 302, the meal category 303 that stores the types of breakfast, lunch, and dinner, the meal content 304 that records the content of the meal that was ingested, the eating out flag 305 that indicates whether or not to eat, and whether or not there was drinking. The indicated drinking flag 306 and is included in one entry.

In the meal-related lifestyle information table 121-1, information on meals among the user information input from the user terminal 110 is generated or updated by the user registration unit 111. The user inputs the information specified in the health guidance program from the user terminal 110 to the health guidance support device 101 at a predetermined timing (for example, every day).

This information has the effect of enabling classification based on the characteristics of the user's eating habits. The user ID 201 uses the same information as the user attribute table 120.

FIG. 4 is a diagram showing an example of the exercise-related lifestyle information table 121-2. The exercise-related lifestyle information table 121-2 includes a user ID 201 that stores a user's identifier, an exercise date and time 401 that indicates the date and time when the user exercised, a weight 402 that day, and a number of steps 403 that the user walked on that day. One entry includes a physical activity level 404 determined from a predetermined exercise standard. The physical activity level 404 stores a value indicating the intensity of exercise, and for example, a value set in a Mets (physical activity intensity) table or the like is stored.

This information has the effect of enabling classification based on the characteristics of the user's physical activity. In the exercise-related lifestyle information table 121-1, information on exercise among the user information input from the user terminal 110 is generated or updated by the user registration unit 111.

FIG. 5 is a diagram showing an example of a lifestyle information table 121-3 related to improvement goals. The lifestyle information table 121-3 related to the improvement goal includes the user ID 201 that stores the user's identifier, the improvement goal 501 that indicates the preset lifestyle improvement goals such as increasing the number of steps and improving the diet, and the achievement of the improvement goal. A target date 502 indicating a target date and a target achievement level 503 indicating whether or not the target has been achieved are included in one entry. As for the target achievement level 503, for example, "0" indicates that the goal has not been achieved, and "1" indicates that the goal has been achieved.

This information has the effect of enabling classification based on the user's efforts to improve lifestyle habits. In the lifestyle information table 121-3 related to the improvement goal, the information about the improvement goal among the user information input from the user terminal 110 is generated or updated by the user registration unit 111.

FIG. 6 is a diagram showing an example of the interview information table 122. The interview information table 122 shows a user ID 201 that stores a user's identifier, an employment presence / absence 601 that indicates whether or not the user is working, a desired instruction style 602 that indicates a desired instruction method, and a medication status that indicates the content of medication. 603, medical history 604, exercise habit 605 showing the average exercise status, eating habit 606 showing the contents such as how to eat normally, and drinking amount 607 showing the amount of normal drinking, average. One entry includes a sleep amount 608 indicating a typical sleep time and a smoking presence / absence 609 indicating the presence / absence of smoking. This information has the effect of enabling the classification of users based on their daily lifestyle.

In the interview information table 122, the contents of the interview conducted at the start of the health guidance program or the like are stored in the interview information table 122 by the user registration unit 111 or the like.

FIG. 7 is a diagram showing an example of the leader attribute table 123. The leader attribute table 123 includes a leader ID 701 that stores an identifier that identifies a leader, a date of birth 702, a height 703, a weight 704, a gender 705, a grade 706, a language 707, and a residence area 708. And, the time zone 709 of the area of residence, the instruction style 710 indicating the instruction style, and the qualification information 711 indicating the qualification contents of the instructor are included in one entry.

This information has the effect of enabling classification based on the attribute information of the leader. A value indicating the rank of each instructor is set for the grade 706. The leader attribute table 123 is preset by an administrator or the like.

FIG. 8 is a diagram showing an example of the instruction schedule table 124. The instruction schedule table 124 holds the information input from the instructor terminal 109. The instruction schedule table 124 is a target of instruction, an instructor ID 701 that stores an instructor's identifier, an instruction date and time 801 that indicates the date and time of instruction, an instruction state 802 that indicates whether or not instruction is being implemented or scheduled. The instruction target user 803 that stores the identifier of the user who is the user is included in one entry.

This information has the effect of making it possible to grasp the availability of instructors and appropriately select the person in charge. The leader ID 701 has the same value as the leader attribute table 123 in FIG. Further, the instruction schedule table 124 is generated or updated by input from the instructor terminal 109.

FIG. 9 is a diagram showing an example of the instruction record table 125. The guidance record table 125 is information preset by the manager of the health guidance program or the like.

The instruction record table 125 includes an instructor ID 701 that stores an instructor identifier, an instruction year 901 that indicates the amount of experience of the instructor, an instruction number 902 that stores the number of users who have instructed in the past, and a total instruction day 903. The number of users who dropped out in the middle of the instruction period is 904, the weight loss result 905 which shows the average weight loss of the users obtained as a result of the instruction, and the user who shows the quantitative evaluation value for the instruction from the user. The evaluation value 906 and is included in one entry. This information has the effect of enabling classification based on the achievements of the instructor.

The instruction record table 125 is updated at a predetermined cycle (for example, every day) to reflect the input and evaluation of the weight loss record from the user terminal 200, the fluctuation of the number of instructors, and the like.

FIG. 10 is a diagram showing an example of the leader grade table 126. The leader grade table 126 is information preset by the manager of the health guidance program or the like.

The leader grade table 126 includes a leader ID 701 that stores the leader's identifier, a leader grade 1001 that is determined from the achievements of the leader, and a guidance unit price 1002 that stores the reward per hour of the leader. Included in the entry. This information has the effect of enabling classification that takes into account the level and unit price of leaders.

FIG. 11 is a diagram showing an example of the cluster management table 127. The cluster management table 127 stores the information generated or updated by the cluster construction unit 114. The cluster management table 127 includes a cluster ID 1101 that identifies the classified group, a cluster target 1102 that indicates the type of cluster, a cluster label 1103 that indicates the characteristics of the cluster, and a feature amount set that indicates the feature amount used for group classification. One entry includes 1104 and the corresponding user 1105 indicating the ID of the user included in the cluster. This information has the effect of making it possible to select appropriate leaders using the classified results.

FIG. 12 is a diagram showing an example of the appropriateness determination table 128. The appropriateness determination table 128 is information generated by the appropriateness score calculation unit 117.

The aptitude judgment table 128 includes a leader ID 701 that stores an identifier of a leader, a target cluster 1201 that indicates a cluster that is a target for determining the suitability of a leader, and an appropriate score 1202 that indicates the degree of suitability for the corresponding cluster. Included in one entry. This information has the effect of making it possible to select a leader with a higher teaching effect.

FIG. 13 is a diagram showing an example of the medical knowledge management table 129. The medical knowledge management table 129 is information preset by an instructor, an administrator, or the like.

One entry includes a health condition 1301 indicating a disease or physical condition, an exercise guidance contraindication 1302 corresponding to the health condition, a dietary guidance contraindication 1303, and a drug guidance contraindication 1304. This information has the effect of making it possible to determine whether or not there is experience in the past teaching history and select an appropriate instructor.

FIG. 14 is a diagram showing an example of the usage status table 130. The usage status table 130 is information generated and updated by the user registration unit 111 and the like.

The usage status table 130 includes a user ID 201 that stores a user's identifier, a login rate 1401 that the user is instructing, an input rate 1402 that indicates the information input status, a weight loss result 1403 that indicates the amount of weight loss, and the weight. One entry includes a weight loss rate of 1404, which indicates the rate of weight loss from the initial value (at the start of the health guidance program).

The weight loss result and the weight loss rate are examples, and any other index can be managed. This information has the effect of being able to classify based on the guidance effect. The login rate 1401 stores a ratio to the number of inputs within a preset period. For example, if the input is set once a day, the login rate is 1401 = 1.0 by inputting once a day. Further, the input rate 1402 can store the ratio of the number of designated input items to the number of actually input items.

The usage status table 130 is updated at a predetermined cycle (for example, one day), and the weight loss result 1403 and the weight loss rate 1404 are calculated and updated from the weight 402 of the lifestyle information table 121-2 input from the user terminal 200. To. Further, the login rate 1401 and the input rate 1402 are calculated and updated according to the login frequency of the user terminal 200 and the input contents.

Next, the procedure for classifying the users and calculating the appropriate score 1202 for the user group will be described with reference to the figures. FIG. 15 is a flowchart showing an example of a procedure for calculating the appropriate score 1202. This process is executed when the health guidance support device 101 receives a predetermined command from the input unit 102 or the instructor terminal 109 (1501).

First, the cluster construction unit 114 sets the method used for clustering in step 1502. For example, a well-known or known method such as the k-means method can be used as a typical clustering method. At that time, along with the setting of the clustering method, the setting is also made including how many clusters are classified. The number of clusters classified can be received from the input unit 102 or the instructor terminal 109.

Next, the cluster construction unit 114 sets the feature amount used for clustering in step 1503. The cluster construction unit 114 receives the designation of the feature amount from the input unit 102 and the instructor terminal 109. Depending on the feature amount set here, the classification can be adjusted according to the purpose of using the appropriate score 1202. For example, if the attribute information is set as the feature amount, the classification can be performed based on the attribute information of the user or the like, or if the interview result is mainly set, the user can be classified by reflecting the interview result.

For classification based on attribute information, for example, clustering can be performed by designating the date of birth 204 (age), gender 207, health condition 212, etc. of the user attribute table 120. Further, for the classification based on the interview result, clustering can be performed by designating the medical history 604, the exercise habit 605, the eating habit 606, and the drinking amount 607 of the interview information table 122.

Next, in step 1504, the lifestyle-related feature amount extraction unit 113 extracts the feature amount from the database 107 based on the information set in step 1503. Here, the lifestyle-related feature amount extraction unit 113 processes the extracted data into a data format capable of clustering.

For example, in the case of data recorded as a character string, in addition to summarizing by name identification, preprocessing such as converting categorical data into numerical values is performed. In addition, when the set feature quantities are diverse, variable selection is performed to narrow down the variables to an appropriate quantity.

Next, in step 1505, the cluster construction unit 114 executes clustering by the clustering method set in step 1502, and classifies the users with a specified number of clusters. Next, in step 1506, the cluster allocation unit 115 records the obtained classification result in the cluster management table 127.

Next, in step 1507, the appropriate score calculation unit 117 calculates the appropriate score 1202 for each instructor. The appropriate score calculation unit 117 does not calculate the appropriate score 1202 when a predetermined number of samples cannot be secured, such as an instructor with a short career.

The appropriate score calculation unit 117 extracts the past achievements in charge included in the classified cluster for each instructor, and calculates the average weight loss rate. The appropriate score calculation unit 117 calculates the average weight loss rate for all leaders and all clusters, and then calculates the appropriate score 1202, which is standardized and the value adjusted from 0 to 1.

The appropriate score Si can be obtained, for example, by linearly converting the value calculated for each instructor by the method shown in the following equation (1) into the range of 0 to 1.

In the above equation (1), μ indicates the average weight loss rate between instructors, σ indicates the standard deviation of the weight loss rate between instructors, and wi indicates the weight loss rate as an instruction result of a certain instructor. There is.

Next, in step 1508, the appropriate score calculation unit 117 records the appropriate score 1202 calculated for each leader ID 701 and the target cluster 1201 in the appropriate determination table 128.

The appropriate score calculation process is executed by the above procedure, and the appropriate score 1202 is set in the leader ID 701 and the target cluster 1201 of the user.

Next, a process of selecting the optimum instructor will be described using the appropriate score 1202 calculated by the appropriate score calculation unit 117.

FIG. 16 is a flowchart showing an example of a leader selection procedure for selecting a leader for a newly registered user. This process is executed when the health guidance support device 101 receives a predetermined command from the input unit 102 or the instructor terminal 109 (1601).

First, the leader allocation determination unit 118 extracts a user to be selected as a leader from the user attribute table 120 in step 1602. The target user can specify, for example, the user ID 201 of a new user or a user who changes the instructor.

Next, the leader allocation determination unit 118 refers to the interview information table 122 in step 1603 to determine whether or not there is a prior interview. If there is a pre-interview result, the process proceeds to step 1604, and if there is no pre-interview result, the process proceeds to step 1610.

In step 1604, the instructor allocation determination unit 118 refers to the interview information table 122 and extracts the feature amount of the interview result. Here, the feature amount is extracted from the user attribute table 120 and the interview information table 122 according to the feature amount set 1104 recorded in the cluster management table 127.

On the other hand, when there is no prior interview information in step 1610, for example, attribute information or the like is used. In this case, allocation can be executed by using a cluster in which the feature amount set 1104 of the cluster management table 127 is composed of attribute information.

Next, the leader allocation determination unit 118 calculates and allocates the closest cluster for each user in step 1605. Specifically, the leader allocation determination unit 118 calculates the distance to each cluster center based on the feature amount extracted for each user, searches for the nearest cluster, and allocates the user.

The leader allocation determination unit 118 assigns a user to a cluster by setting a user ID for the corresponding user 1105 corresponding to the cluster ID 1101 in the cluster management table 127.

Next, in step 1606, the leader allocation determination unit 118 sets an index (KPI: Key Performance Indicator) to be optimized.

FIG. 17 shows an example of a screen for setting a KPI. On the KPI setting screen 1701, the performance graph display 1705 that visualizes the quantitative value based on the past guidance performance of each instructor A to G, the performance index selection 1702 that selects the performance index to be displayed, and the graph display are performed. There is a display button 1703 and a KPI addition button 1704 used when adopting a performance index. On this screen, for example, when the average weight loss rate is selected as the performance index, the performance graph display 1705 displays information on the average weight loss rate and standard deviation of the users who have been in charge of each instructor A to G so far.

In this way, the performance index is displayed on the KPI setting screen 1701 to extract the index that needs to be optimized, and the manager or instructor uses the KPI addition button 1704 to select the KPI to be used when selecting the optimum instructor. Can be set.

In the illustrated example, the average weight loss rate was used as the performance index, but other performance indexes such as the dropout rate from the health guidance program and user evaluation can be selected. Moreover, although the standard deviation is taken as an example as a supplementary index, any index can be used without limitation.

Next, the leader allocation determination unit 118 selects a leader using the appropriate score 1202 calculated in the process of FIG. 15 in step 1607. Here, referring to the appropriateness judgment information managed in the appropriateness judgment table 128, the leader ID 701 having the highest appropriateness score 1202 (predetermined value or more) for the cluster to which the target user belongs is extracted and sorted in descending order of the appropriateness score 1202. I do.

The instructor allocation determination unit 118 selects the instructor ID 701 having the highest rank of the appropriate score 1202 among the rearrangements, and in the next schedule confirmation step (1608), the instructor schedule managed in the instruction schedule table 124. The information is compared with the user's instructable date and time 203 managed in the user attribute table 120, and when the instructor can actually be instructed, the instructor is selected in the next instructor setting step.

In the schedule confirmation step (1608), if the user's instructable date and time and the instructor's instructable date and time do not match, the process returns to the optimum instructor selection step (1607), and the same processing as above is applied to the next instructor ID 701. repeat.

FIG. 18 shows an example of the instructor selection screen 1801 that selects an instructor based on the appropriate score 1202 calculated for a certain user. On the instructor selection screen 1801, the KPI set on the KPI setting screen of FIG. 17 is displayed on the selection condition display 1802 as a selection condition. The user information to be selected by the instructor is displayed on the selection target user information display 1804.

For this user, the calculation execution button 1803 is pressed to calculate the selection result. The selection result is displayed in the leader selection information 1805 at the top of the screen. In the instructor selection information 1805, the appropriate score calculated for each instructor's ID and whether or not the schedule is suitable (possible or not) are displayed.

At the lower right of the screen, the leader selection display 1806 is displayed in descending order of priority for selecting leaders based on the value of the appropriate score. In the example of the figure, the instructor with the highest appropriate score is selected, and the selection is completed by pressing the selection confirmation button 1807. Through the above series of processes, it is possible to select an instructor for the purpose of optimizing the instruction effect more easily than before.

As described above, according to the first embodiment, the health guidance support device 101 is based on the past guidance performance data of the instructor, the attributes of the past users, and the accumulated data such as the lifestyle information table 121. Therefore, a group of users who can exert a high teaching effect for a certain instructor is calculated from the data, an appropriate instruction score 1202 for each group (cluster) is calculated, and the appropriate score 1202 is taken into consideration when selecting an instructor. Select a leader. As a result, it is possible to efficiently and quickly determine the optimum person in charge among a plurality of instructors and a plurality of users, and a higher instruction effect can be obtained. In addition, even if it is unavoidable to change the instructor, the person in charge can be determined quickly, and the work related to the selection of the instructor can be greatly reduced.

Hereinafter, as Example 2 of the present invention, an example of ensuring the possibility of selection for an instructor with a small instruction record by considering the instruction unit price when selecting an instructor will be described with reference to the figure.

FIG. 19 is a flowchart showing an example of a leader selection procedure in consideration of the guidance unit price. This flowchart is obtained by adding step 1901 to the flowchart of FIG. 16 of the first embodiment, and other configurations are the same as those of the first embodiment.

The instructor allocation determination unit 118 calculates the unit price coefficient to be multiplied by the appropriate score 1202 in the instruction unit price calculation step (1901). For example, the unit price function is calculated by using a function in which the unit price coefficient is set to a maximum value of 1 and a minimum value of 0 and used as an argument of a model function such as a sigmoid function, and the unit price coefficient increases as the unit price decreases.

Then, the instructor allocation determination unit 118 can calculate an appropriate score 1202 corrected by multiplying the calculated unit price coefficient with the appropriate score 1202, and can adjust so that even an instructor with a small career can be selected. is there. The unit price coefficient may be proportional to the guidance unit price 1002 of the leader grade table 126 shown in FIG. 10 of the first embodiment.

FIG. 20 is an example of the leader selection screen 1801 based on the corrected appropriate score. FIG. 20 shows the leader selection information 2005 by adding the guidance unit price and the corrected appropriate score to the leader selection information 1805 on the leader selection screen 1801 shown in FIG. 18 of the first embodiment. Is the same as in Example 1.

In the leader selection information 2005, the appropriate score 1202, the schedule, and the coefficient of the guidance unit price are displayed. Advisor1 has an appropriate score of 1202 of 1, Advisor2 has an appropriate score of 0.9, and Advisor3 has an appropriate score of 0.7. Advisor1 is 0.5, Advisor2 is 0.63, Advisor3 is 0.7, and Advisor3 has the highest selection priority.

In this way, according to the second embodiment, it is possible to secure the possibility of selection by applying the method of considering the appropriate score 1202 and the instruction unit price even for the instructor with a small instruction career according to the purpose. Optimal utilization of instructors is possible.

Hereinafter, as Example 3 of the present invention, an example of providing planning support for securing human resources necessary as an instructor will be described with reference to the drawings. FIG. 21 is a block diagram showing a configuration example of the health guidance support device 101 according to the third embodiment of the present invention.

The health guidance support device 101 of the third embodiment has a management index setting unit 2101 that sets management target indexes such as personnel expenses and a plan of necessary leader human resources in order to create a plan for securing necessary leader human resources. It has a necessary instructor human resources presentation unit 2102, an instructor candidate management table 2103 showing candidates for instructors before the contract, and an administrator terminal 2104. Other configurations are the same as those in the first embodiment.

For example, when starting a new guidance service for users who are enrolled in advance, it is first necessary to plan to secure the necessary instructors, and at that time, it is important to optimize the securing of human resources according to the user group. ..

An example of a human resources securing plan is shown with reference to FIG. FIG. 22 is an example of the instructor human resources planning screen 2201 that presents the necessary instructor human resources provided by the necessary instructor human resources presentation unit 2102. On the instructor human resources planning screen 2201, the user cluster constructed by the cluster construction unit 114 is displayed on the user cluster display 2202.

The required number of instructors display 2203 displays each cluster and the number of instructors required for each cluster. The required number of instructors is optimized according to the number of users in charge per instructor set by the management index setting unit 2101, the instruction unit price setting, and the like.

In FIG. 22, the plan of the total labor cost is displayed on the human resources plan setting display 2205 on a monetary basis. According to the set value, the guidance unit price is referred to from the leader candidates, and the optimum leader is extracted within the planned range. At that time, it is possible to extract the optimum leader by calculating the cluster to be assigned using the appropriate score.

When the management index setting unit 2101 gives priority to cost reduction, for example, by extracting a cluster in which the effect of instruction does not depend on the instructor so much from the cluster of users, an instructor with few instruction careers and a low instruction unit price It is possible to maintain the teaching effect as much as possible even if you are in charge of.

Alternatively, by assigning leaders to each cluster in descending order of appropriate score 1202, not only the number of leaders required for the cluster but also leaders who can handle features such as attributes of each cluster can be assigned. It is also possible to enhance the effect of instruction.

The present invention is not limited to the above-mentioned examples, and includes various modifications. For example, the above-described embodiment is described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one having all the configurations described. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, for a part of the configurations of each embodiment, any of addition, deletion, or replacement of other configurations can be applied alone or in combination.

Further, each of the above configurations, functions, processing units, processing means and the like may be realized by hardware by designing a part or all of them by, for example, an integrated circuit. Further, each of the above configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be stored in a memory, a hard disk, a recording device such as an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

In addition, the control lines and information lines indicate those that are considered necessary for explanation, and do not necessarily indicate all the control lines and information lines in the product. In practice, it can be considered that almost all configurations are interconnected.

101 Health guidance support device 107 Database 109 Instructor terminal 110 User terminal 111 User registration unit 112 Recommended instructor presentation unit 113 Lifestyle feature amount extraction unit 114 Cluster construction unit 115 Cluster allocation unit 116 Instructor grade processing unit 117 Appropriate score calculation Department 118 Instructor Assignment Decision Department 119 Medical Knowledge Processing Department 120 User Attribute Table 121 Lifestyle Information Table 122 Interview Information Table 123 Instructor Attribute Table 124 Guidance Schedule Table 125 Guidance Performance Table 126 Instructor Grade Table 127 Cluster Management Table 128 Appropriate Judgment table 129 Medical knowledge management table 130 Usage table

Claims (10)

It is a health guidance support device that has a processor and a storage unit that can be read and written from the processor to support the health guidance of participants.
The storage unit
Holds user information of the participants and lifestyle-related information that accumulates the results of health guidance for each participant.
The processor
A plurality of clusters are generated by classifying the participants from the user information, and appropriate scores of the plurality of instructors are calculated for each cluster based on the results of the health guidance of the participants and held in the appropriate judgment information. , The appropriate score is calculated from the results of lifestyle-related information that accumulates the results of the health guidance.
A health guidance support device, characterized in that unit price information regarding guidance is set for the instructor, the unit price information includes a reward per hour for the instructor, and the processor corrects the appropriate score with the unit price information. .. The health guidance support device according to claim 1.
The processor
When the user information of the participant to whom the leader is assigned is received, the participant is assigned to one of the clusters based on the user information, and the appropriateness determination information is referred to for the cluster to which the participant is assigned. A health guidance support device characterized in that a leader having the highest appropriate score among the appropriate scores of a plurality of instructors and capable of instructing the participant is selected. The health guidance support device according to claim 1.
The user information is a health guidance support device including at least one of participant attribute information and interview information. It is a health guidance support method that supports the health guidance of participants with a computer having a processor and a storage unit that can be read and written from the processor.
A first step in which the computer classifies the participants from the user information stored in the storage unit and generates a plurality of clusters.
The second step, in which the computer calculates the appropriate score for each of a plurality of instructors for each cluster based on the lifestyle information accumulated as the result of the health guidance of the participants and holds it in the appropriate judgment information. Including the second step
The appropriate score is calculated from the results of lifestyle-related information accumulating the results of the health guidance, unit price information regarding the guidance is set for the instructor, and the unit price information includes the hourly reward of the instructor. A health guidance support method characterized by correcting the appropriate score with the unit price information. The health guidance support method according to claim 4.
The third step in which the computer receives the user information of the participant to whom the leader is assigned,
A fourth step in which the computer assigns the participant to one of the clusters based on the user information.
The computer selects a leader who has the highest appropriate score among the appropriate scores of a plurality of instructors and can instruct the participant with reference to the appropriateness determination information for the cluster to which the participant is assigned. Fifth step and
A health guidance support method characterized by further including. The health guidance support method according to claim 4.
The user information is a health guidance support method comprising at least one of participant attribute information and interview information. A program that controls a computer having a processor and a storage unit that can be read and written from the processor.
The first step of classifying participants from the user information stored in the storage unit to generate a plurality of clusters, and
The second step of calculating the appropriate score for each of a plurality of instructors for each cluster based on the lifestyle information accumulated as the result of the health guidance of the participants and holding it in the appropriate judgment information is executed on the computer. Let me
The second step is
The appropriate score is calculated from the results of lifestyle-related information accumulating the results of the health guidance, unit price information regarding the guidance is set for the instructor, and the unit price information includes the hourly reward of the instructor. A program characterized in that the appropriate score is corrected by the unit price information. The health guidance support device according to claim 1.
The processor is characterized in that the unit price coefficient is calculated so as to become larger as the value of the unit price information becomes lower by using a predetermined function, and the appropriate score is corrected by multiplying the calculated unit price coefficient by the appropriate score. Health guidance support device. The health guidance support method according to claim 4.
The second step is
Health guidance characterized in that the unit price coefficient is calculated to be larger as the value of the unit price information is lower using a predetermined function, and the appropriate score is corrected by multiplying the calculated unit price coefficient by the appropriate score. Support method. The program according to claim 7.
The second step is
A program characterized in that the unit price coefficient is calculated so as to become larger as the value of the unit price information becomes lower using a predetermined function, and the appropriate score is corrected by multiplying the calculated unit price coefficient by the appropriate score.

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