JP2020024695A - System, method, and program for analyzing medical checkup - Google Patents

Abstract

To provide a medical checkup analysis system for preventing a healthy subject of diagnosis from becoming unhealthy.SOLUTION: The medical checkup analysis system is for analyzing the result of a medical checkup run on a subject of diagnosis. The system includes: a reference range setting unit for setting a reference range by using one of the upper limit value and the lower limit value of a reference value and the center value as the middle value between the upper limit value and the lower limit value, for every plural examination items of the medical checkup; a risk value calculation unit for linearly evaluating the examination values acquired by examinations with respect to the reference range and calculating the risk value for each examination item; and a diagnosis result evaluation unit for digitizing the health state of each tissue evaluated for the examination items on the basis of the risk value calculated for each examination item.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a health check analysis system, a health check analysis method, and a health check analysis program.

2. Description of the Related Art A management system that analyzes and manages a result of a health check has been known.
For example, Patent Literature 1 discloses a configuration in which a health check result is analyzed and classified, a map is created and visualized, and the map is conveyed to a person to be diagnosed easily.

JP 2013-191021 A

  However, the conventional management system does not evaluate whether the subject is healthy or unhealthy based on the reference value. There was room for improvement in understanding what it was.

  Therefore, the present invention provides a health condition that can prevent a healthy subject from going unhealthy by quantitatively grasping how close the subject is to an unhealthy condition. It is intended to provide a diagnostic analysis system.

  In order to solve the above-mentioned problems, a health diagnosis analysis system of the present invention is a health diagnosis analysis system for analyzing a result of a health diagnosis of a subject, wherein a standard One of the upper limit value and the lower limit value, and a median value that is the median of the upper limit value and the lower limit value, using a reference range setting unit that sets a reference range, A risk value calculator that linearly evaluates the test value obtained by each test and calculates a risk value for the test item, and evaluates the test item based on the risk value calculated for each test item. And a diagnosis result evaluation unit for quantifying the health state of each tissue to be performed.

  Further, the risk value calculation unit may calculate a risk value for an inspection item with respect to the inspection value remaining within the reference range.

  In addition, the diagnosis result evaluation unit may determine which of the plurality of preset types corresponds to the type to be diagnosed, based on the combination of the health states of the tissues quantified. .

  The types may be classified by identifiers represented by characters imitating animals.

  In addition, a measure proposal unit that recommends a measure for shifting the test value toward the median of the reference values based on the type determined by the diagnosis result evaluation unit may be provided.

  Further, the health check analysis method of the present invention is a health check analysis system for analyzing a result of a health check of a person to be diagnosed, wherein the computer has a reference value range for each of a plurality of test items in the health check. As a reference range setting step of setting at least one of the upper limit value and the lower limit value, and the median value that is the median of the upper limit value and the lower limit value, A risk value calculating step of linearly evaluating the numerical values of the obtained test values and calculating a risk value for the test items, and each organization evaluated by the test items based on the risk value calculated for each test item. A diagnostic result evaluation step of quantifying the health condition of the subject.

  Further, the health check analysis program of the present invention is a health check analysis program for analyzing the result of the health check of the subject, and for each of a plurality of test items in the health check, an upper limit is set as a reference value range. Value and the lower limit, the median that is the median of the upper and lower limits, the reference range setting function to be set respectively, and the test obtained by each test for the reference range. A risk value calculation function that linearly evaluates the value of the value and calculates a risk value for the test item, and based on the risk value calculated for each test item, a health condition of each organization evaluated by the test item. And a diagnosis result evaluation function to be quantified.

  Since the health examination analysis system of the present invention includes the reference range setting unit and the risk value calculation unit, it is possible to evaluate the position of the test value with respect to the set reference range. This makes it possible to prevent a subject in a healthy state from moving toward an unhealthy state by quantitatively grasping how close the subject is to an unhealthy state.

FIG. 1 is a schematic diagram illustrating a health diagnosis analysis system according to a first embodiment of the present invention and a configuration around the system. FIG. 2 is a block diagram illustrating a configuration of a health examination analysis system illustrated in FIG. 1. It is a schematic diagram which shows the calculation method of potential medical expenses. FIG. 2 is a flowchart showing a processing flow in the health examination analysis system shown in FIG. 1. It is a block diagram showing composition of a health examination analysis system concerning a second embodiment of the present invention. It is a figure which shows the list of the specific example of the median value and the upper limit (lower limit) of each test item used in the health examination analysis system concerning 2nd embodiment. It is the 1st example of the inspection item which comprises the risk value of each organization. It is a 2nd example of the inspection item which comprises the risk value of each organization. It is the 3rd example of the inspection item which comprises the risk value of each organization. It is the 4th example of the inspection item which comprises the risk value of each organization. It is the 5th example of the inspection item which comprises the risk value of each organization. It is a 6th example of the inspection item which comprises the risk value of each organization. FIG. 6 is a flowchart showing a processing flow in the health examination analysis system shown in FIG. 5.

(1st Embodiment)
A first embodiment of the present invention will be described with reference to FIGS.
FIG. 1 is a schematic diagram showing a health diagnosis analysis system 100 (hereinafter, simply referred to as an analysis system 100) according to an embodiment of the present invention, and a configuration around it.
The analysis system 100 is connected to the database of the health check-up center 30 that performs the health check, and the user terminal 10 via the network 40. For this reason, the analysis system 100 can obtain the health check result from the database of the health check center 30 and can output data obtained by analyzing the health check result to the user terminal 10.

The user terminal 10 is, for example, a personal computer of the user 20 who is a person to be subjected to a health check, a personal computer of a company to which the user 20 belongs, or the like. The user 20 can confirm data analyzed by the analysis system 100 using the user terminal 10. The user terminal 10 is connected to a network 40.
The health check center 30 stores the result of the health check of the user 20 in a database. This database is connected to the network 40.

The network 40 is a network for interconnecting the analysis system 100 and various devices, and is, for example, a wireless network or a wired network.
Specifically, the network 40 includes a wireless LAN (wireless LAN: WLAN), a wide area network (wide area network: WAN), ISDNs (integrated service digital networks), wireless LANs, LTE (long term evolution, and volume evolution). Fourth generation (4G), fifth generation (5G), CDMA (code division multiple access), WCDMA (registered trademark), Ethernet (registered trademark), and the like.

  The network 40 is not limited to these examples, and may be, for example, a public switched telephone network (PSTN), Bluetooth (Bluetooth (registered trademark)), Bluetooth Low Energy, an optical line, or an optical line. (Asymmetric Digital Subscriber Line) A line, a satellite communication network or the like may be used, and any network may be used.

  The network 40 may be, for example, NB-IoT (Narrow Band IoT) or eMTC (enhanced Machine Type Communication). Note that NB-IoT and eMTC are wireless communication systems for IoT, and are networks capable of long-distance communication with low cost and low power consumption.

  The network 40 may be a combination of these. Further, the network 40 may include a plurality of different networks obtained by combining these examples. For example, the network 40 may include a wireless network based on LTE and a wired network such as an intranet that is a closed network.

  The analysis system 100 is an information processing server that receives various data of a health examination result, analyzes the received data, and outputs the data to the user terminal 10. The analysis system 100 may be realized by, for example, artificial intelligence. Hereinafter, the configuration of the analysis system 100 will be described in detail. FIG. 2 is a block diagram showing a configuration of the analysis system 100 shown in FIG.

As shown in FIG. 2, the analysis system 100 includes a receiving unit 110, a storage unit 120, a processing unit 130, and an output unit 140.
The reception unit 110 is a communication interface that receives data of a health examination result from the database of the health examination center 30 via the network 40 shown in FIG.
The receiving unit 110 also receives an analysis instruction input from the user 20 to the user terminal 10. When receiving various data, the receiving unit 110 transmits the data to the processing unit 130.

  The storage unit 120 has a function of storing various control programs and various data required for the processing unit 130 to operate. The storage unit 120 is realized by various storage media such as an HDD, an SSD, and a flash memory.

  Further, the analysis system 100 may store the control program in the storage unit 120, execute the analysis program, and the processing unit 130 may realize each function to be realized as the analysis system 100. The functions referred to here include a diagnosis value evaluation function, a potential medical expenses calculation function, a potential medical expenses report function, a determination function, and a measure recommendation function, which will be described later.

Further, the storage unit 120 stores, as one of the stored various data, reference value data of the inspection item. The reference value data is a value (range) serving as an index of whether or not the diagnosis value of each test item is healthy.
That is, when the diagnostic value falls within a predetermined range defined by the reference value data, the state is set to be appropriate for the test item.
On the other hand, if the diagnostic value falls outside the predetermined range defined by the reference value data, the state is determined to be inappropriate for the test item. If all of the test items are in a proper state, the user 20 is determined to be in a healthy state. If at least one of the test items is in an inappropriate state, the user 20 is determined to be in an unhealthy state. Is done.

Further, the storage unit 120 stores medical cost data as one of the stored various data. Medical cost data refers to medical costs required to provide standard treatment in an unhealthy state.
In other words, if any of the above-mentioned test items is deviated from any one of the above-mentioned test items and it is determined that the condition is unhealthy, the standard treatment method required to improve the condition is assumed. This is data on medical expenses to be paid. The storage unit 120 stores, for each test item, a plurality of medical cost data that are assumed when the value deviates from the reference value.

  Further, the storage unit 120 stores, as one of the stored various data, a plurality of type models used in a determination step described later. In the type model, the evaluation result of each test item is associated with a plurality of types classified so as to correspond to the evaluation result. In the present embodiment, 21 types including a healthy state are stored. Characters imitating animals are assigned to these 21 types. As a result, the user 20 can easily remember the type to which the user 20 pertains.

Further, the storage unit 120 stores an action recommendation model used for specifying a measure recommended by the recommendation unit 136 described later.
In the action recommendation model, the type determined by the determination unit 135 described later is associated with the content of a measure proposed to the user 20, that is, exercise habits, diet improvement, medical department information that is preferable for medical care, and the like.

  In addition, the storage unit 120 stores, as one of the stored various data, a report format for displaying an analysis result. The report format includes columns for entering personal information such as the name, affiliation, and address of a diagnostician, as well as diagnostic values, the types and animal characters described above, and recommended measures.

  The processing unit 130 is a computer that controls each unit of the analysis system 100, and may be, for example, a central processing unit (CPU), a microprocessor, an ASIC, an FPGA, or the like. The processing unit 130 is not limited to these examples, and may be any type.

The processing unit 130 includes a calculation unit 131 and a data processing unit 132. The calculation unit 131 is a unit that performs each calculation described below. The data processing unit 132 creates output data using the calculation result of the calculation unit 131 and a report format.
The calculation unit 131 includes a diagnosis value evaluation unit 133, a medical cost calculation unit 134, a determination unit 135, and a recommendation unit 136.

  The diagnostic value evaluation unit 133 quantitatively evaluates a diagnostic value that remains within a reference value set for each test item of the health check. Here, as a method of quantitative evaluation, a method of calculating a difference between a diagnostic value and a reference value and then assigning a score according to the amount of the difference may be employed. That is, the diagnostic value evaluation unit 133 quantitatively evaluates how close the diagnostic value that can be determined to be in an appropriate state is closer to the reference value by staying within the reference value.

  The medical cost calculation unit 134 calculates a potential medical cost that is potentially assumed at the time of a health examination using the medical cost data stored in the storage unit 120 and the evaluation result of the diagnostic value evaluation unit 133. . Here, the potential medical expenses are unnecessary at the present time, but are assumed medical expenses in the event that the reference value is not reached in the future.

The potential medical cost may be calculated linearly based on the ratio of the diagnostic value to the reference value, for example, as shown in FIG. 3, or may be calculated using a coefficient set corresponding to the ratio. Is also good. Here, FIG. 3 is a schematic diagram showing an example of a method for calculating potential medical expenses.
In addition, in this figure, the case where the diagnostic value indicates a value higher than the median value is described, but the present invention is not limited to such an embodiment, and the case where the diagnostic value indicates a value lower than the median value is described. Can be calculated in the same way.

  In addition, the medical cost calculation unit 134 totals the potential medical costs calculated for the group of persons to be diagnosed. The aggregated potential medical costs are reported to the manager who manages the group of diagnoses. The report is performed by the output unit 140 transmitting the report to the administrator terminal.

The determination unit 135 determines which of the plurality of preset types the user 20 corresponds to, based on the type model and the evaluation results for the plurality of test items in the diagnostic value evaluation step. .
The recommendation unit 136 recommends a measure such that the diagnosis value is the median of the reference values based on the behavior recommendation model and the type determined in the determination step.

  The output unit 140 is a communication interface having a function of transmitting data processed by the processing unit 130 to the user terminal 10. That is, the output unit 140 transmits the report created by the data processing unit 132 to the user terminal 10 so that the user 20 can confirm the report.

Next, a control flow of the analysis system 100 will be described with reference to FIG. FIG. 4 is a flowchart showing a processing flow in the analysis system 100.
First, the reception unit 110 receives data of a result of a health examination (S501). Next, as a diagnostic value evaluation step, the diagnostic value evaluation unit 133 evaluates a diagnostic value for each test item (S502). At this time, the diagnostic value evaluation unit 133 uses the reference value data stored in the storage unit 120 to quantitatively evaluate the diagnostic value by comparing the reference value for each test item with the diagnostic value.

  Next, as a potential medical cost calculation step, the medical cost calculator 134 calculates a potential medical cost (S503). At this time, in the potential medical cost calculation step, as described above, the potential medical cost can be calculated according to the ratio of the diagnostic value to the reference value using the medical cost data stored in the storage unit 120.

  Next, as a determination step, the determination unit 135 determines the type of the diagnostician (S504). At this time, the determination unit 135 determines the type of the user 20 corresponding to the evaluation result in the diagnostic value evaluation step using the type model stored in the storage unit 120.

Next, as a measure recommendation step, the recommendation unit 136 specifies a measure to be recommended to the user 20 (S505). At this time, the recommendation unit 136 uses the action recommendation model stored in the storage unit 120 to specify a measure to be recommended for the type corresponding to the user 20.
Next, the data processing unit 132 creates a report (S506). At this time, the data processing unit 132 creates report data by using the report format stored in the storage unit 120 and inputting the calculation result of the calculation unit 131 as the content of the report.

  The output unit 140 outputs report data to the user terminal 10 (S507). At this time, as a potential medical expense reporting step, the total sum of the potential medical expenses is reported to a manager who manages a group of diagnosed persons (S508). Then, the user 20 can check the report data by accessing the user terminal 10.

As described above, according to the analysis system 100 according to the present embodiment, since the computer executes the diagnostic value evaluation step, if the diagnostic value temporarily stays within the reference value, the computer performs the diagnostic value evaluation step based on the difference from the reference value. The diagnostic value can be evaluated quantitatively.
For this reason, even if the diagnostic value is within the reference value, it is possible to easily understand the degree to which the diagnostician approaches an unhealthy state in a healthy state. It is possible to prevent an unhealthy state from occurring.

  In addition, since the computer executes the potential medical cost calculation step, the potential medical cost is calculated in a non-disease state that has not yet become ill, and the economic risk in the current health condition is calculated by the user. 20 can be recognized. Thereby, the user 20's awareness of health can be increased.

  In addition, since the computer executes the potential medical expenses report step, the administrator to which the group to which the group of diagnoses belongs belongs can be made aware of how much medical expenses will be required in the future. Thereby, the convenience for the manager can be improved.

  In addition, since the computer performs the determination step, the user 20 determines the corresponding type, and manages the user 20 who has a similar tendency as the health condition as one type, thereby implementing the same measure. A plurality of diagnosed persons can be managed efficiently, for example, recommendations can be made.

  In addition, since the computer executes the measure recommendation step, the computer 20 recommends to the user 20 various measures, such as exercise habits, diet improvement, and consultation in a hospital, which are required in the future to improve the health condition. Can be. Accordingly, the user 20 can maintain the health condition of the user 20 by providing the recommended measures for health management.

(2nd Embodiment)
Next, a health diagnosis analysis system 200 according to the second embodiment will be described. In this embodiment, the same components as those of the first embodiment are denoted by the same reference numerals, and description thereof will be omitted. FIG. 5 is a block diagram showing a configuration of a health examination analysis system 200 according to the second embodiment of the present invention.

As illustrated in FIG. 5, in the health examination analysis system 200 according to the present embodiment, the calculation unit 231 includes a reference range setting unit 233, a risk value calculation unit 235, a diagnosis result evaluation unit 236, and a measure proposal unit 237. Is further provided.
The reference range setting unit 233 uses, for each of a plurality of test items in the medical examination, one of the upper limit value and the lower limit value of the reference value, and the median value that is the median of the upper limit value and the lower limit value, Set the reference range. This will be described with reference to FIG. FIG. 6 is a diagram showing a list of specific examples of the median and the upper limit (lower limit) of each inspection item.

As shown in FIG. 6, the reference range setting unit 233 sets data from the median value to the upper limit value for the inspection item. This data (test item data) is stored in the storage unit 120 as reference range data.
Most of the inspection item data has a median and an upper limit set, but for the inspection items indicated by * in FIG. 6, a median and a lower limit are set. This means that the upper limit is managed from the median for test items that become unhealthy as the value increases, and the lower limit is managed from the median for test items that become unhealthy as the value decreases. Means.

That is, the reference range in the present invention is a range between the median value and the upper limit value for a test item that becomes unhealthy as the value increases, and a median value for a test item that becomes unhealthy as the value decreases. And the lower limit.
In the test item data, a reference range is set for each gender depending on the test item. For this reason, when the reference value differs depending on the gender, different ranges are indicated.

The risk value calculation unit 235 linearly evaluates the numerical value of the test value obtained by each test with respect to the reference range, and calculates the risk value for the test item.
Specifically, the median value in the reference range of each test item is set to a risk value of 10, and the maximum value is set to a risk value of 100, and then the test values obtained for each test item are evaluated linearly. Calculate the risk value for the item.

Here, for test items that become unhealthy as the value increases, if the test value is larger than the upper limit and indicates an abnormal value, the risk value is assumed to increase linearly and the test value is increased. If the value is smaller than the median, the risk value is set to 0.
On the other hand, if the test value is smaller than the lower limit and the test value indicates an abnormal value, the risk value will increase linearly and the test value If the value is larger than the value, the risk value is set to 0.

That is, the difference between the test value and the median value is proportional to the difference 90 between the median value and the maximum risk value, and the risk value corresponding to the difference between the test values is calculated.
As a specific example, in the test item data shown in FIG. 6, for the test item “neutral fat”, the median is 100 (risk value 10) and the upper limit is 150 (risk value 100). Is 120, the risk value is 46.

  Further, as another specific example, in the test item “eGFR”, the median value is 80 (risk value 10) and the lower limit value is 60 (risk value 100) in the test item “eGFR” as the value decreases, so If the value is 70, the risk value is 55.

  That is, the risk value calculation unit 235 can calculate a risk value for an inspection item with respect to an inspection value that remains within the reference range, and can also calculate a risk value that indicates an abnormal value outside the reference range. A risk value for an inspection item can also be calculated.

The diagnosis result evaluation unit 236 quantifies the health state of each tissue evaluated by the test item based on the risk value calculated for each test item. This digitizing method will be described with reference to FIGS.
FIG. 7 is a first example of a test item constituting a risk value of each tissue, and is used particularly for liver evaluation. FIG. 8 is a second example of a test item constituting a risk value of each tissue, and particularly complements the evaluation of the liver.

In the case of the liver, first, as shown in the liver A of FIG. 7, ALT × 0.5 + (γGTP + cholinesterase + AST) /3×0.5 is set as the liver risk value.
Here, ALT refers to alanine aminotransferase. AST refers to aspartate aminotransferase. γGTP refers to γ-glutamyltransferase.
When the AST risk value is 0, the ALT risk value can be neglected. In this case, as shown in the liver B in FIG. 8, cholinesterase × 0.5 + γGTP × 0.5 Risk value.

  FIG. 9 shows a third example of a test item constituting a risk value of an organ, which is used particularly for evaluating a kidney. In the case of kidney, as shown in FIG. 9, (urine albumin + urine protein + eGFR + blood pressure) /4×0.75+ (uric acid + potassium + urine occult blood) /3×0.25 is defined as the risk value of kidney. . Here, eGFR indicates the estimated glomerular filtration value.

  FIG. 10 is a fourth example of a test item constituting a risk value of an organ, and is particularly used for evaluating a muscle. In the case of muscle, as shown in FIG. 10, the SMI × 0.75 + (blood ketone + serum albumin + erythrocyte) /3×0.25 is defined as the muscle risk value. Here, SMI indicates a skeletal muscle mass index.

  FIG. 11 shows a fifth example of a test item constituting a risk value of an organ, which is used particularly for evaluation of blood vessels. In the case of a blood vessel, a blood pressure (upper) × 0.35 + blood pressure (lower) × 0.35 + blood sugar level × 0.15 + (neutral fat + LDL_C + uric acid) /3×0.15 is defined as a risk value of the blood vessel. Here, LDL_C indicates bad cholesterol.

FIG. 12 shows a sixth example of a test item constituting a risk value of an organ, which is used particularly for evaluating obesity. In the case of obesity, BMI × 0.75 + (γGTP + cholinesterase + neutral fat) /3×0.25 is set as the risk value of obesity. Here, BMI indicates a body mass index.
The risk values of the respective organizations described above are merely examples, and all of the exemplified risk values may not be used, or other risk values may be used.

The diagnosis result evaluation unit 236 also determines which type of the plurality of preset types corresponds to the subject based on the digitized combination of the health states of the tissues.
This type is classified by an identifier represented by a character imitating an animal. The types are classified into, for example, 21 types according to the combination of the health states of the respective tissues described above. This classification is a combination of a predetermined type and a range value that defines the range of the health state of each tissue corresponding to the type, that is, there is information in which a combination of the health state of each tissue is associated. If the value detected in the health check corresponds to a combination of the range values of each tissue, it is determined that the value falls under the corresponding type.

  The identifier is expressed by a character imitating an animal while avoiding medically and mentally burdensome expressions such as “bad liver”. For example, a type that is obese with a large amount of fat and has no problem with other organs is “a snake with only a circle”, and a type that is prone to obesity and a burden on the liver is “too much toy poodle”.

  Then, by labeling each of these characters (identifiers) on information on the Internet, food displayed at a supermarket, or the like, selecting a character can lead to own health behavior.

  In addition, the identifier realizes a more personalized health risk value by differentiating the health risk value for the same character depending on the organ condition, combination, age, gender, numerical level of each test item, etc. can do.

  The measure proposal unit 237 recommends a measure for shifting the test value toward the median of the reference values based on the type determined by the diagnosis result evaluation unit 236. Using the action recommendation model stored in the storage unit 120, the measure proposal unit 237 specifies a measure to be recommended for the type corresponding to the user 20. The behavior recommendation model is associated with the classified type and the contents of a measure proposed to the user 20, that is, information on exercise habits, diet improvement, and medical departments where it is preferable to perform medical care. The measures also include taking supplements and drugs.

Next, a processing flow of the health diagnosis analysis system 2 will be described with reference to FIG. FIG. 13 is a diagram illustrating a processing flow of the health diagnosis analysis system 2.
As shown in FIG. 13, in the health examination analysis method using the health examination analysis system 2, first, the accepting unit accepts data of a health examination result (S601).
Next, the reference range setting unit 233 sets a reference range for each of the plurality of inspection items (reference range setting step: S602).

Next, the risk value calculation unit 235 calculates a risk value for each test item (risk value calculation step: S603).
Next, the diagnosis result evaluation unit 236 quantifies the health state of each tissue based on the risk value calculated for each test item (diagnosis result evaluation step: S604).

  Next, the diagnosis result evaluation unit 236 classifies the person to be diagnosed into a type (type classification step: S605). At this time, the diagnosis result evaluation unit 236 classifies the combination of the health status of each tissue into a preset type and assigns an identifier.

  Finally, the measure proposal unit 237 recommends a measure for shifting the inspection value toward the median of the reference values based on the classified type (measure proposal step: S606). Thereby, the person to be diagnosed can grasp the measures to be taken in the future.

  As described above, according to the health examination analysis system 200 according to the present embodiment, since the reference range setting unit 233 and the risk value calculation unit 235 are provided, the test value It can be evaluated whether it is located. This makes it possible to prevent a subject in a healthy state from moving toward an unhealthy state by quantitatively grasping how close the subject is to an unhealthy state.

  In addition, since the health diagnosis analysis system 200 includes the diagnosis result evaluation unit 236, the health status of each tissue evaluated by the test item can be quantified based on the risk value calculated for each test item. it can. Thus, by calculating the risk value of each organization, it is possible to grasp the risk value of each organization that can be inferred from the inspection value, which is difficult to understand only by checking the inspection value.

In addition, since the risk value calculation unit 235 calculates the risk value for the test item with respect to the test value remaining within the reference range, it is possible to capture the change in the health state of each tissue within the reference range (normal range). Can be.
In other words, it is not necessary to take countermeasures after abnormal values, that is, when each tissue becomes ill, in other words, to evaluate the health status by subdividing the health status rather than for the early detection of the disease. it can.

In general, if a health checkup diagnoses “healthy” or “no outliers (no findings)”, it is judged that there is no need to check for diet, exercise, and preventive measures that are appropriate for health management and health investment. Awareness tends to decline.
Due to such a determination, lifestyle habits such as eating habits are deteriorated, and as a result, there is a problem that treatment starts after an abnormal value appears. The health diagnosis analysis system 2 of the present invention proposes meal management, exercise management, information, services, and health-related products optimized for each user 20 by further subdividing the health (no abnormality). Can be.

  In addition, the diagnosis result evaluation unit 236 determines which of the plurality of preset types corresponds to the type to be diagnosed, based on the digitized combination of the health states of the tissues. As a result, information to be provided to the diagnosed person can be narrowed down to a certain number by classifying the diagnosed person into a preset type based on the health condition of each tissue, thereby improving convenience. can do.

  The types are classified by identifiers represented by characters imitating animals. As a result, even if you do not know the meaning of your own health examination result or the state of each tissue including organs, you know the character that expresses the corresponding identifier and optimized information using the character as a landmark Can find food, exercise, and health-related products, and can solve the current situation in which people are unable to act because they are strayed and difficult due to behaviors for health management.

  Further, based on the type determined by the diagnosis result evaluation unit 236, a measure proposal unit 237 for recommending a measure for shifting the test value toward the median of the reference values is provided. And propose the most appropriate measures.

It goes without saying that the system according to the above embodiment is not limited to the above embodiment, and may be realized by another method. Hereinafter, various modifications will be described.
For example, if the test value is found to be an abnormal value outside the reference range, a test at a medical institution can be prompted by an alert, mail, or the like.
In addition, alerts and e-mails can be used to alert you to any test findings related to specific health guidance, such as metabolic syndrome. Re-examination, specific guidance health, etc. can be prompted by alerts or e-mails. As a result, the person in charge of such a department in the past can reduce the labor that has been promoted by telephone and face-to-face, and can spend time and labor in the original work.

The health check analysis system 2 can analyze the results of the annual health check in the company and the blood test results using a commercially available micro blood sampling kit or the like.
The health examination analysis system 2 is also capable of performing an average analysis not only on which identifier a user corresponds to, but also on a group, department, or company basis to which the user 20 belongs. In other words, if used in a company, it is possible to understand the health status of each department and the average health status of all employees, and to implement optimal health benefits for groups, departments and companies .

  Specifically, health management, in-house health seminars, new employee training, department-based health seminars, etc., provide health information appropriate to the health risks faced by many of the company's employees and promote health promotion activities. It becomes possible. For example, the average character of the accounting department is "Snake of the circle only" (obesity tendency), so we are promoting diet seminars and promoting health. For example, holding a drinking seminar.

  Further, the program of the above embodiment may be provided in a state stored in a computer-readable storage medium. The storage medium is capable of storing the program on a “temporary tangible medium”. The storage medium may include any suitable storage medium such as an HDD or an SDD, or a suitable combination of two or more thereof. The storage medium may be volatile, non-volatile, or a combination of volatile and non-volatile. The storage medium is not limited to these examples, and may be any device or medium as long as it can store a program.

  In addition, the analysis system 100 can realize the functions of the plurality of functional units described in each embodiment, for example, by reading a program stored in a storage medium and executing the read program. The program may be provided to the analysis system 100 via an arbitrary transmission medium (such as a communication network or a broadcast wave). The analysis system 100 realizes the functions of the plurality of functional units described in each embodiment by executing a program downloaded via the Internet or the like, for example.

  Also, the program may be implemented using a script language such as ActionScript or Javascript (registered trademark), an object-oriented programming language such as Objective-C or Java (registered trademark), or a markup language such as HTML5. Good.

  At least a part of the processing in the analysis system 100 may be realized by cloud computing including one or more computers. Further, each functional unit of the analysis system 100 may be realized by one or a plurality of circuits realizing the functions described in the above-described embodiment, and the functions of the plurality of functional units may be realized by one circuit. Good.

  Although the embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can easily make various changes and modifications based on the present disclosure. Therefore, it should be noted that these variations and modifications are included in the scope of the present disclosure. For example, the functions and the like included in each means, each step, and the like can be rearranged so as not to be logically inconsistent, and a plurality of means, steps, and the like can be combined into one or divided. . Further, the configurations shown in the embodiments may be appropriately combined.

<Appendix>
A method of analyzing a result of a health check for analyzing a result of a health check, wherein a computer converts a diagnostic value remaining within a reference value set for each test item of the health check into a difference from the reference value. A method of analyzing a result of a health check, which executes a diagnostic value evaluation step of performing a quantitative evaluation based on the result.

Computer
Based on the evaluation result in the diagnostic value evaluation step and the medical cost required for the treatment assumed when the diagnostic value is outside the reference value, a potential medical treatment that is potentially assumed at the time of the medical examination. The method for analyzing a health examination result according to paragraph 0087, wherein a potential medical cost calculating step of calculating a cost is performed.

Computer
Performing a potential medical expense reporting step of summing the potential medical expenses calculated for the group of diagnosed persons and reporting the totalized potential medical expenses to a manager managing the group of diagnosed persons; The method for analyzing a health examination result according to paragraph 0088, wherein

  A discriminating step of a computer discriminating which type of the plurality of preset types corresponds to the subject based on the evaluation results for the plurality of test items in the diagnostic value evaluating step; Any one of paragraphs 0087 to 0089, wherein a policy recommendation step of recommending a policy in which the diagnostic value is a median of reference values based on the type determined in step is performed. The method for analyzing the results of the medical examination described in 1.

  A health check result analysis program for analyzing a result of a health check, wherein a computer converts a diagnostic value remaining within a reference value set for each test item of the health check into a difference from the reference value. A program for analyzing health check results that realizes a diagnostic value evaluation function that performs quantitative evaluation based on the results.

  A health diagnosis analysis system for analyzing a result of a health check, wherein a computer diagnoses a diagnosis value staying within a reference value set for each test item of the health check based on a difference from the reference value. , A health check analysis system including a diagnostic value evaluation unit for quantitatively evaluating.

100 Health check analysis system 133 Diagnosis value evaluation unit 134 Medical cost calculation unit 135 Determination unit 136 Recommendation unit

Claims (7)

A health examination analysis system for analyzing a result of a health examination of a subject,
For each of a plurality of test items in the health check, a reference range is set using one of an upper limit value and a lower limit value of a reference value and a median value that is a median value of the upper limit value and the lower limit value. A reference range setting section for
For the reference range, by linearly evaluating the numerical value of the test value obtained by each test, a risk value calculating unit that calculates a risk value for the test item,
A health diagnosis analysis system, comprising: a diagnosis result evaluation unit that quantifies a health state of each tissue evaluated by the test item based on the risk value calculated for each test item.   2. The health examination analysis system according to claim 1, wherein the risk value calculation unit calculates a risk value for the test item with respect to the test value remaining within the reference range.   The diagnosis result evaluation unit, based on the combination of the health state of each of the tissues is quantified, to determine which of the plurality of preset types, the type corresponds to the subject to be diagnosed. The medical examination analysis system according to claim 1 or 2, wherein:   The health diagnosis analysis system according to claim 3, wherein the types are classified by an identifier represented by a character imitating an animal.   The method according to claim 4, further comprising: a measure suggestion unit that recommends a measure for shifting the test value toward a median of reference values based on the type determined by the diagnosis result evaluation unit. Health check analysis system as described. A health examination analysis system for analyzing the result of a health examination of a subject,
Computer
For each of a plurality of test items in the health check, as a range of reference values, at least one of an upper limit and a lower limit, and a median that is a median of the upper limit and the lower limit, respectively. A reference range setting step to be set;
For the reference range, by linearly evaluating the numerical value of the test value obtained by each test, a risk value calculating step of calculating a risk value for the test item,
A health diagnosis analysis method for performing a diagnosis result evaluation step of quantifying a health state of each tissue evaluated by the test item based on the risk value calculated for each test item. A health check analysis program for analyzing the result of the health check of the subject,
For each of a plurality of test items in the health check, a reference value range is set as at least one of an upper limit value and a lower limit value, and a median value which is a median of the upper limit value and the lower limit value, respectively. Reference range setting function
For the reference range, a numerical value of the test value obtained by each test is linearly evaluated, and a risk value calculation function for calculating a risk value for the test item,
A health diagnosis analysis program for realizing a diagnosis result evaluation function of quantifying a health state of each tissue evaluated by the test item based on the risk value calculated for each test item.

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