JP6151016B2 - Health management prediction system - Google Patents

Description

  The present invention relates to a health management prediction system that predicts health indexes and various disease risks based on health checkup results, personal examination results collected for health management, medical history information including past history and subjective symptoms, and lifestyle information. Is.

  Traditionally, as a measure of individual health status, simulations have been conducted on the results of various health examinations such as blood pressure and cholesterol levels, etc. by changing preconditions such as health indices such as healthy age and healthy life span and various disease risks, etc. There are technologies that can be used for personal health management. For example, in the technique disclosed in Patent Document 1, test values of test items are acquired as variation factors such as the health index and the preconditions described above, and various simulations are performed by changing the variation factors.

JP-A-2005-202901

  However, there is a problem in that it is difficult to operate without knowing the meaning of the variable factors and the examination items of the medical examination, and it is difficult to lead to actions for improving the health condition. Further, in Patent Document 1, there is a problem that the simulation result display is mainly a numerical expression, and it is difficult for an individual to understand the degree of improvement and the position in the affiliation population, and it is difficult to trigger a lifestyle change.

  The present invention has been made in view of the above, and an object of the present invention is to provide a health management prediction system capable of easily invoking lifestyle change behavior.

  In order to solve the above-described problems and achieve the object, the health management prediction system according to the present invention includes a management server that simulates health indexes and health risks using data on personal health, and connects the results to a network. A health management prediction system to be displayed on the client terminal, wherein the management server includes the individual test value data as the personal health data, the lifestyle data including the personal lifestyle, and the personal health data. A storage unit for storing a health index and a parameter for each health risk that are predetermined based on the test value data for simulating the health index and health risk, the test value data, the lifestyle data, and the parameter Based on the above, the individual's health index and health risk An output unit that graphically displays the simulation result calculated by the calculation unit on the display unit of the client terminal, and the client terminal includes a display unit that displays the simulation result; A control unit that receives a result of the simulation from the management server and displays the result on the display unit.

  According to the present invention, it is possible to provide a health management prediction system capable of easily invoking behavior change behavior.

It is a figure which shows the structural example of the health care prediction system in this Embodiment. It is an image figure which shows the flow of a process in a health care prediction system. It is a figure which shows the example of test value data. It is a figure which shows the example of past history data. It is a figure which shows the example of lifestyle attribute data. It is a figure which shows the example of a basic calculation parameter. It is a figure which shows the example of the prediction result of the health risk which the basic index and risk calculation part output. It is a figure which shows a mode that a display data output part displays on the display part of a client terminal. It is a figure which shows the example of lifestyle change data. It is a flowchart which shows the process sequence of a simulation process.

  Exemplary embodiments of a health management prediction system according to the present invention will be described below in detail with reference to the accompanying drawings. The health index described below is an index related to personal health such as a healthy age and a healthy life span. The health risk is, for example, an individual death or medical risk such as death risk, hospitalization risk, cancer risk, diabetes risk, etc., but may include a risk of becoming bedridden, a risk of becoming a wheelchair.

  FIG. 1 is a diagram illustrating a configuration example of a health management prediction system 1000 according to the present embodiment. As shown in FIG. 1, in the health management prediction system 1000, a management server 100, a statistics server 200, and a client terminal 300 are connected via a network N. The network N is a general line network such as a WAN (Wide Area Network) or a LAN (Local Area Network). First, the management server 100 will be described.

  The management server 100 is a device that simulates an individual's health index and health risk using the health check result. As illustrated in FIG. 1, the management server 100 includes a storage unit 110, a control unit 120, and a communication unit 130. The storage unit 110 stores personal health data 111, basic calculation parameters 112, change calculation parameters 113, and organization / organization average risk data 114. Furthermore, the personal health data 111 is data relating to the personal health of the user of this system, and includes test value data 1111, past history data 1112, and lifestyle attribute data 1113. It is assumed that the personal health data 111 is stored in the storage unit 110 in advance.

  The inspection value data 1111 is data indicating the results of personal health checkups, medical checkups, and the like. FIG. 3A is a diagram illustrating an example of the inspection value data 1111. As shown in FIG. 3A, in the test value data 1111, diagnostic items including individual height, weight, and waist circumference and their values are stored in association with each other. In the test value data 1111 shown in FIG. 3A, 25 items are exemplified as diagnostic items, but the number of these items can be arbitrarily determined.

  The past history data 1112 is data indicating the presence / absence of the past history of the individual who received the diagnosis result of each item of the test value data 1111. FIG. 3B is a diagram illustrating an example of the past history data 1112. As shown in FIG. 3B, the past history data 1112 is stored in association with the presence or absence of diseases such as heart disease and stroke (seven major diseases in FIG. 3B).

  The lifestyle attribute data 1113 includes attribute information such as the sex and age of the individual who has received the diagnosis result of each item of the test value data 1111 and lifestyle related to the lifestyle such as the individual's habit, exercise habit, rest, smoking, drinking, etc. Data having information. FIG. 3C is a diagram illustrating an example of lifestyle habit attribute data 1113. As shown in FIG. 3C, the lifestyle attribute data 1113 stores the drinking or smoking status of the individual. In the example shown in FIG. 3C, smoking is not performed, and 350 ml of alcoholic beverages are ingested per day. In addition, although it has illustrated about drinking and smoking in FIG. 3C, it is good also as providing an item about lifestyle other than these. Next, returning to FIG. 1, the basic calculation parameters will be described.

  The basic calculation parameter 112 is a parameter for simulating an individual (or organization / organization) health index and health risk, as will be described later. The basic calculation parameter 112 is provided by the statistical server 200 described later (or acquired by the basic index / risk calculation unit 121) and stored in the storage unit 110 in advance.

  FIG. 4 is a diagram illustrating an example of the basic calculation parameter 112. As shown in FIG. 4, the basic calculation parameter 112 defines a cut point (item) for simulating health risk by an epidemiological method. In FIG. 4, for example, in the case of mortality risk (all mortality), the risk of mortality (total mortality) is calculated using the risk occurrence probability, the rank indicating the degree of occurrence of the risk, the life expectancy of the individual, and the age of health. It shows that it is calculated. Similarly, when calculating the risk of death due to cardiovascular disease or the risk of death due to three major illnesses among death risks (all deaths), the risk occurrence probability and rank indicating the degree of occurrence of the risk are factors. As shown, the risk of death due to these is calculated. Similarly, in the case of medical risks (hospitalization), in addition to the risk occurrence probability and rank indicating the degree of occurrence of the risk, the risk is calculated taking into account the number of days of hospitalization, life expectancy, and healthy age. It is shown that.

  These mortality risk and medical risk are calculated by a basic index / risk calculation unit 121 to be described later, but various values are obtained by using test value data 1111, past history data 1112, and lifestyle attribute data 1113 included in the personal health data 111. It may be calculated by various methods. That is, in the health management prediction system 1000 according to the present embodiment, the health risk prediction result calculated using the predetermined basic calculation parameters 112 and the personal health data 111 is output, and the following simulation is performed.

  FIG. 5 is a diagram illustrating an example of a health risk prediction result output by the basic index / risk calculation unit 121. As shown in FIG. 5, the health risk prediction result has the same items as the basic calculation parameter 112, and the result calculated as the health risk is recorded in each item. In the example shown in FIG. 5, the risk of death (all deaths), the risk of death due to cardiovascular disease, the risk of death due to three major diseases is zero, and the level of occurrence is low (rank A). The ages indicate 40 years and 35 years, respectively. In addition, although there is no medical risk due to hospitalization or hospital visit and the risk is low (Rank A), as shown in FIG. 3B, there is a history of liver disease, so it is necessary to go to a pharmacy A certain probability is 10%, which indicates that the degree of occurrence of the risk is slightly higher than rank A (rank A ′). As described above, the basic index / risk calculation unit 121 described later calculates the death risk and the medical risk, and outputs the prediction result for each individual stored in the storage unit 110 as the personal health data 111.

  The change calculation parameter 113 is a parameter indicating the value of an item modified from the basic calculation parameter 112 when performing a simulation described later, and has the same items as the basic calculation parameter 112 shown in FIG. Similar to the basic calculation parameter 112, the change calculation parameter 113 is also provided by the statistical server 200 described later (or acquired by the change index / risk calculation unit 123), and is stored in the storage unit 110 each time the basic calculation parameter 113 is changed. The Next, returning to FIG. 1, the organization / organization average risk parameter 114 will be described.

  The organization / group average risk data 114 includes the basic calculation parameter 112, the change calculation parameter 113, the prediction result of each individual's health risk output by the basic index / risk calculation unit 121 from the personal health data 111, and the organization such as a company department. It is calculated every time and the average value is taken. The organization / organization average risk data 114 is aggregated every time a prediction result of an individual's health risk is output by a basic index / risk calculation unit 121 and a change index / risk calculation unit 123, which will be described later, and the average value is calculated and stored. Stored in the unit 110. In this case, if the organization spans multiple hierarchies (for example, in the case of ◎◎ business unit XX department △△ section, it spans three hierarchies), the prediction results are tabulated for each hierarchy, The average value is calculated. When the display data output unit 124 to be described later outputs the simulation result to the display unit 320 of the client terminal 300, the average health of the organization such as a company to which the individual belongs together with the prediction result of the individual health risk. A risk prediction result is output and displayed on the display unit 320. In the present embodiment, the organization / group average risk data 114 is described by taking the department of the organization as an example. However, the organization / organization average risk data 114 may be aggregated for various organizations such as offices, companies, and health insurance associations. Subsequently, returning to FIG. 1, the control unit 120 will be described.

  As shown in FIG. 1, the control unit 120 includes a basic index / risk calculation unit 121, a lifestyle difference calculation unit 122, a change index / risk calculation unit 123, and a display data output unit 124. ing.

  The basic index / risk calculation unit 121 calculates death risk and medical risk using the personal health data 111 and the basic calculation parameter 112, and outputs the prediction result as basic health index / risk data. As these methods, various methods can be applied as described above.

  The lifestyle difference calculation unit 122 is output from the basic index / risk calculation unit 121, and the display data output unit 124 displays the health risk prediction result on the display unit 320 of the client terminal 300. The life already stored as the personal health data 111 when the contents of the lifestyle attribute data 1113 are changed as a condition for calculating the risk, and the lifestyle change data indicating the changed contents are input from the client terminal 300 The difference with the habit attribute data 1113 is output as lifestyle habit difference data. For example, the lifestyle difference calculation unit 122, when a certain individual reduces the number of smoking per day from 20 to 10 as a lifestyle, the life is assumed that the difference of 10 is the smoking number of the individual. The inertial attribute data 1113 is output.

  The change index / risk calculation unit 123 uses the difference data output from the lifestyle habit difference calculation unit 122 and the change calculation parameter 113, as in the case of the basic index / risk calculation unit 121, Calculate the medical risk and output the prediction result as a modified health index / risk data.

  The display data output unit 124 can display the basic health index risk data output from the basic index / risk calculation unit 121 and the changed health index risk data output from the change index / risk calculation unit 123 on the display unit 320 of the client terminal 300. Display in format.

  FIG. 6 is a diagram illustrating a state in which the display data output unit 124 causes the display unit 320 of the client terminal 300 to display. As shown in FIG. 6, the display data output unit 124 displays each value of the basic health index risk data and the changed health index risk data in a format that is easy to visually understand in a graph format, a table format, or a chart format. In the example illustrated in FIG. 6, the display data output unit 124 displays the health age and the healthy life (life expectancy) included in the basic health index risk data as a bar graph. If there is no changed health index risk data, that portion is displayed blank. Then, when the contents of the lifestyle attribute data 1113 are changed and the lifestyle change data indicating the changed contents is input from the client terminal 300, the changed health index risk data is displayed together with the basic health index risk data. In the example shown in FIG. 6, the case where the contents of the lifestyle attribute data 1113 are changed is described. However, input of each item included in the test value data 1111 such as weight and waist circumference. It is good also as providing a display column and changing these contents.

  In addition, the display data output unit 124 displays various risks included in the basic health index risk data and the changed health index risk data (death risk, medical risk, hospitalization risk and communication risk below these, risk of three major diseases, etc.). Display on radar chart. Further, when there is changed health index risk data, the display data output unit 124 displays various risks after the change on the radar chart together with the basic health index risk data. In the example illustrated in FIG. 6, the display data output unit 124 displays the radar chart of the changed health index risk data as the updated contents, and the radar chart of the changed health index risk data as the current contents.

  Further, the display data output unit 124 displays the organization / group average risk data stored in the storage unit 110 on the radar chart together with the basic health index risk data and the changed health index risk data. In the example shown in FIG. 6, the display data output unit 124 displays the basic health index risk data with a solid line, the changed health index risk data with a dotted line, and the organization / organization average risk data with a one-dot chain line. It is shown that. In FIG. 6, when the client terminal 300 accepts selection of organization / group average risk data (in the example shown, selection by pull-down), the organization / group average risk data of the selected department or the like is used as a basis. Display with health index risk data and changed health index risk data. In these displays, in consideration of the ease of viewing the entire screen, other graphs such as bar graphs or charts may be displayed, or items improved as a result of simulation may be highlighted.

  The display data output unit 124 displays the lifestyle attribute data 1113 stored in the storage unit 110 in a table format for each item. In the example shown in FIG. 6, the display data output unit 124 displays items such as the number of smoking and the drinking status, as well as the amount of food intake, exercise status, and sleeping time as the current contents. All of the information is included in the lifestyle attribute data 1113 shown in FIG. 3C. When the content of the lifestyle attribute data 1113 is changed and the lifestyle change data indicating the changed content is input from the client terminal 300, the display data output unit 124 sets the content as the changed content as the current content. Display in parallel with the contents.

  Thus, the display data output unit 124 superimposes the current basic health index risk data and the changed health index risk data, and the changed basic health index risk data and the changed health index risk data on one screen, Or since it displays in parallel, the individual can grasp | ascertain the health index and health risk in the content after a change easily. When the contents of the lifestyle attribute data 1113 are changed, lifestyle change data indicating the changed contents is input from the client terminal 300, and a simulation execution instruction (simulation button in the example shown in FIG. 6) is received, In accordance with the execution instruction, the change index / risk calculation unit 123 calculates the death risk and medical risk reflecting the difference data that is the content after the change, and outputs the changed health index / risk data. The display data output unit 124 The changed content will be displayed as changed health index risk data.

  FIG. 7 is a diagram illustrating an example of lifestyle change data. As shown in FIG. 7, the lifestyle change data includes values obtained by changing each item of the lifestyle attribute data 1113 (how much the amount has been increased or decreased), health age and healthy life (life expectancy), and various risks. Is associated data. When the lifestyle change data is transmitted to the management server 100, the change index / risk calculation unit 123 calculates various risks after the change, and the display data output unit 124 includes the changed health index / risk data including the contents. Is displayed on the display unit 320 of the client terminal 300 as shown in FIG. Next, returning to FIG. 1, the communication unit 130 will be described.

  The communication unit 130 is configured by a communication device such as a modem or a NIC (Network Interface Card), for example, and transmits / receives the various data described above to / from the statistics server 200 and the client terminal 300. Next, the statistics server 200 will be described.

  The statistical server 200 is a device that provides the basic calculation parameter 112 described above using the personal health data 111 or provides the change calculation parameter 113 described above using the personal health data 111 after the change. As shown in FIG. 1, the statistical server 200 includes a storage unit 210, a control unit 220, and a communication unit 230.

  The storage unit 210 stores the basic calculation parameter 112 and the change calculation parameter 113. These parameters are determined in advance by various epidemiological methods, for example, what kind of items are set as prediction risk items.

  The control unit 220 creates basic calculation parameters 112 and change calculation parameters 113 from the personal health data 111, transmits these created parameters to the management server 100, and stores them in the storage unit 110. For example, when the personal health data 111 of each individual provided is biased in the number of data by age compared to the personal health data 111 of each individual provided in the past, for example, Is corrected, a new basic calculation parameter 112 and a change calculation parameter 113 are created, and the parameters are transmitted to the management server 100 and stored in the storage unit 110.

  Similar to the communication unit 130, the communication unit 230 includes a communication device such as a modem or a NIC, and transmits / receives the various data described above to / from the management server 100 and the client terminal 300. Next, the client terminal 300 will be described.

  The client terminal 300 uses the basic calculation parameter 112, the change calculation parameter 113, and the personal health data 111 to display the basic health index risk data and the changed health index risk data, or to display the displayed data. A terminal that performs simulation. As illustrated in FIG. 1, the client terminal 300 includes an input receiving unit 310, a display unit 320, a printing unit 330, a control unit 340, and a communication unit 350.

  The input receiving unit 310 is a general input device such as a keyboard, and changed lifestyle changes from an operator of the client terminal 300 (for example, a doctor or an assistant explaining the results of a medical checkup or a medical checkup). Various operations such as input of personal health data 111 such as data 1113 and test value data 1111 or selection of a section of organization / group average risk data are accepted.

  The display unit 320 is a general display device such as an LCD (Liquid Crystal Display), and the basic health index risk data and the changed health index risk data output by the display data output unit 124 or various types of data included in these data. The contents shown in FIG. 6 such as a risk radar chart and simulation results are displayed.

  The printing unit 330 is a general printing device such as a laser printer, and prints the content displayed by the display unit 320 on a medium such as paper. Each user can take home a medium such as a sheet on which the above-described contents are printed, and store the medium.

  The control unit 340 controls the operation of each unit of the client terminal 300. The communication unit 350 includes a communication device similar to the communication unit 130 and the like, and transmits and receives the various data described above to and from the management server 100 and the statistics server 200.

  Here, the flow of processing in the health care prediction system 1000 will be described. FIG. 2 is an image diagram showing a flow of processing in the health care prediction system 1000. As described above, in the health management prediction system 1000, the basic index / risk calculation unit 121 receives the personal health data 111 and the basic calculation parameters 112 of the individual user, and calculates the health risk prediction result as the basic health index / risk data. When output, the display data output unit 124 converts the basic health index / risk data and organization / organization average risk data into the format shown in FIG. 6 and outputs the converted data. Then, the user visually confirms the radar chart graphically displayed on the display unit 320 of the client terminal 300 and the contents of the simulation result to confirm his / her health condition.

  Then, if the input reception part 310 receives the input of the lifestyle change data supposing the case where the lifestyle was changed, for example, the lifestyle difference calculation part 122 will be the personal health data 111 and the input lifestyle change data and To generate lifestyle difference data. Then, the change index / risk calculation unit 123 refers to the change calculation parameter 113 to generate changed health index / risk data that reflects the contents of the lifestyle difference data, and the display data output unit 124 sends the contents to the client It is displayed on the display unit 320 of the terminal 300. In this way, while displaying each person's health index and health risk graphically with charts, graphs, charts, each individual's lifestyle and health checkup test items are changed and the results are simulated. Individuals can easily visually recognize changes in their own health indicators and health risks. Subsequently, a simulation process performed in the health management prediction system 1000 will be described.

  FIG. 8 is a flowchart showing the processing procedure of the simulation processing. As shown in FIG. 8, in the simulation process, first, the basic index / risk calculation unit 121 captures the personal health data 111 (step S801), and uses the captured personal health data 111 and the basic calculation parameter 112 to determine the individual. The basic index / risk is calculated to generate basic health index / risk data (step S802), and the display data output unit 124 displays the generated basic health index / risk data on the display unit 320 of the client terminal 300. (Step S803).

  Thereafter, after the individual receives an interview with a doctor or the like about lifestyle habits, when the input receiving unit 310 receives an input of lifestyle change data (step S804), the lifestyle habit difference calculating unit 122 After the input lifestyle change data and the personal health data 111 are compared to generate lifestyle difference data, the change index / risk calculation unit 123 changes using the change calculation parameter 113 and the lifestyle difference data The index / risk is calculated to generate the changed health index / risk data (step S805), and the display data output unit 124 causes the display unit 320 of the client terminal 300 to display the generated changed health index / risk data ( Step S806). Then, the input receiving unit 310 receives whether or not there is a further change, and when the control unit 340 determines that there is no change (end) (step S807; Yes), the simulation process illustrated in FIG. 8 is ended. . On the other hand, when the control unit 340 determines that there is a change (does not end) (step S807; No), the process returns to step S804 and the subsequent processing is repeated.

  In this way, by performing the simulation process in the present embodiment, it is possible to easily arouse the behavior change behavior to the individual. Specifically, using lifestyle and personal health data that is quantitatively expressed as a variable factor, we will present prevention and improvement measures for lifestyle-related diseases while simulating the health of individuals. It becomes easy to lead to concrete countermeasure action. In addition, simulation results are not simply displayed as results, but the degree of improvement, positioning in the population, balance of various disease risks, etc. can be seen graphically, so the results can be easily recognized. can do. In addition, it is possible to objectively and intuitively grasp one's health level, and to provide a motivation that strongly changes lifestyle habits. In addition, in order to obtain a balanced improvement effect, it becomes possible to find a specific measure of how to change which lifestyle habits.

  The present invention is not limited to the above-described embodiments as they are, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the above embodiments. For example, it is of course possible to configure the management server and the statistics server as one server, or to perform the above-described simulation processing by one server including the functions of the client terminal.

  The present invention can be widely applied to, for example, health examinations, health management / guidance services, etc. implemented in medical institutions, medical examination institutions, and other health-related industries. It can also be applied to lifestyle disease countermeasures and guidance for employees, union members, and residents in companies, health insurance associations, and local governments.

1000 Health management prediction system 100 Management server 110 Storage unit 111 Personal health data 1111 Test value data 1112 History data 1113 Lifestyle attribute data 112 Basic calculation parameter 113 Change calculation parameter 114 Organization / group average risk data 120 Control unit 130 Communication unit 200 Statistics server 210 Storage unit 220 Control unit 230 Communication unit 300 Client terminal 310 Input reception unit 320 Display unit 330 Printing unit 340 Control unit 350 Communication unit N Network.

Claims (4)

A management server that simulates health indicators and health risks using data on personal health is a health management prediction system that displays the result on a client terminal connected to the network,
The management server
Based on the individual's test value data and medical history data as the data relating to the individual's health, lifestyle data including the individual's lifestyle, and the test value data for simulating the individual's health index and health risk A storage unit for storing a parameter for each health index and health risk determined in advance and a parameter for a risk of going to a dispensing pharmacy determined as a hospital risk included in the health risk ;
Based on the test value data and past history data , the lifestyle data and the parameters, a calculation unit for simulating the health risk including the individual's health index and the risk of going to the dispensing pharmacy ,
Change data indicating a difference in lifestyle with respect to the simulation result is received from the client terminal, and the change data is reflected based on the received change data, the lifestyle data, the test value data, and the past history data. A change calculation unit for simulating the health risk including the health index of the individual after and the risk of going to the dispensing pharmacy;
An output unit that graphically displays a result of the simulation after reflecting the change data calculated by the change calculation unit on the display unit of the client terminal;
The client terminal is
An input receiving unit for receiving change data for the result of the simulation;
A display unit for displaying the result of the simulation;
A control unit that transmits the change data received by the input receiving unit to the management server, receives a result of the simulation from the management server, and displays the result on the display unit;
A health management prediction system characterized by comprising: The management server
The calculation unit calculates the average value of the results of health index and health risk simulation for each organization or group to which the individual belongs,
The storage unit stores an average value for each organization or group to which the individual belongs,
The output unit displays the result of the simulation of the individual and the average value of the result of the simulation for each organization or group,
The health management prediction system according to claim 1 . The output unit displays the simulation result on the display unit of the client terminal graphically by a bar graph or a radar chart.
The health management prediction system according to claim 1 or 2 , wherein The calculation unit executes the simulation using the individual's death risk, hospitalization risk, the outpatient risk, and the morbidity risk as prediction risk items,
The health care prediction system according to any one of claims 1 to 3 .

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