KR101510600B1 - Bigdata health record system - Google Patents

Abstract

The big data healthcare system according to an embodiment of the present invention includes: at least one user terminal; at least one medical institution server; and a big data service system of health insurance corporation in which, if it is accessed to cloud via at least one user device or at least one medical institution server account, can send and receive healthcare information of a client including the user terminal or the medical institution server, and entries by at least one user device or clinical information input by the medical institution server, evaluate health risks of the client at the request of at least one user device or one medical institution server, predict stroke risks, provide diagnosis of obesity and improvement plan accordingly, and synthetically manage insulin resistance syndrome and provide given information.

Description

Big Data Personal Health Record System {BIGDATA HEALTH RECORD SYSTEM}

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a Big Data Personal Health Record System (or Big Data Health Service System), and more particularly to a Big Data Personal Health Record System In Big Data Health Service System.

The three strategies of the government are 'Transparent Government', 'Competent Government' and 'Service Government'. The three strategies of the government are 'Transparent Government', 'Competent Government', ' Service government. "As the top 10 projects," public information disclosure "," promotion of private data utilization of public data "," strengthening of public-private cooperation "," elimination of partition in government " , 'Implementing scientific administration with big data', 'Providing customized service integration with customers',' Strengthening one-stop support for start-up and business activities', 'Improving service accessibility of information-vulnerable classes',' To create customized services using technology.

In order to implement these three major strategies and ten major tasks, the National Health Insurance Corporation has opened the standardization of the National Health Information DB, utilized Big Data, provided consultation services for chronic disease management, provided appropriate medication management services, provided personal health records, Services, etc. are presented as implementation tasks.

Korean Patent Laid-Open Publication No. 2003-0062728 discloses the contents of the health management of the user, but only a conceptual description is given, and a specific process for using Big Data, providing personal health record, And algorithms.

Accordingly, an object to be solved by the present invention is to provide a cloud-based big data personal health record system that presents specific processes and algorithms for utilization of big data, provision of personal health records, and public health alert services.

A Big Data Health Service system according to an embodiment of the present invention includes at least one user terminal; At least one medical institution server; And at least one user terminal or a medical institution server, when the cloud connection is established by the account of the at least one user terminal or the at least one medical institution server, the input information input by the at least one user terminal, And transmits the healthcare information to the at least one user terminal or the medical institution server, evaluates the health risk of the subject, predicts stroke risk, provides obesity and improvement measures, , And a health insurance corporation big data service system that integrally manages metabolic syndrome management and provides corresponding information.

Wherein the health insurance corporation big data service system comprises at least one user terminal or a medical institution server and at least one user terminal and at least one user terminal, A communication module for transmitting and receiving healthcare information of a subject including treatment information of the medical institution server; A storage module for allocating and storing a space according to the account of the healthcare information of the subject; And a health integrated management module for assessing the health risk of the subject, predicting the risk of brain damage, providing obesity and improvement measures, and managing the metabolic syndrome integrally to provide the corresponding information .

Wherein the integrated management module is configured to collect information on body mass index, smoking, drinking, exercise, brain stem, heart disease, diabetes, blood pressure, blood glucose, total cholesterol, low density cholesterol, high density cholesterol, A health risk assessment management module for estimating a health risk of a subject by taking into account the height, weight, and waist circumference information of the subject and deriving a health age of the subject; The health care information is subjected to different calculations according to gender in consideration of the subject's age, sex, height, weight, systolic blood pressure, presence of diabetes, total cholesterol, drinking, smoking and exercise, A stroke risk prediction management module that calculates a prediction risk to be taken by the stroke risk prediction module; The method of the present invention predicts the obesity of the subject using the age, sex, height, weight, and waist circumference information of the subject in the health medical information, compares the current state with the target state inputted by the subject, An obesity improvement management module that provides a weight and waist circumference comparison graph; And performing hypertension diagnosis management of the subject by classifying the hypertensive stage and the pre-hypertension stage using the healthcare information of the subject, performing diabetes diagnosis management of the subject using the healthcare information of the subject, And a metabolic syndrome customized information management module for performing diagnosis management of hyperlipidemia of the subject using health medical information of the subject.

In addition, the stroke risk prediction module can calculate a predicted risk (KMP) to be taken for a stroke within 10 years of a male through the following equation.

KM =

0.02411 * (AGE-44.9956) + 0.02148 * (SBP-124.4739) + 0.58797 * (TDM-0.0482) -0.02450 * (EXSMOK- 0.2024) + 0.27720 * (CUSMOK- 0.5909) + 0.06916 * (EXER1-0.7128) + 0.03120 * (BMI-23.2356) + 0.06810 * (DRINK1-0.2329) -0.02830 * (DRINK2-0.5753) + 0.10992 * (DRINK4-0.0586) + 0.16459 * (DRINK5-0.0199) + 0.06051 * (NTTC2-0.2696) + 0.17653 * -0.0956),

KM1 = e ^KM ,

Predicted risk of stroke within 10 years: KMP = 1-0.98485 * KM1

Here, AGE: mannae; SBP: systolic blood pressure; TDM: 1 if there is a history of diabetes mellitus, or if the fasting blood sugar level is over 126 mg / dL or if there is diabetes mellitus taking dose; EXSMOK: 1 if you quit smoking, 0 otherwise; CUSMOK: 1 if smoking now, 0 otherwise; EXER1: 1 if not exercising; 0 if exercising; BMI: body mass index = weight / height ² ; DRINK1: 0 g of drinking or 1 if not drinking, 0 otherwise; DRINK2: 1 if the amount of drinking per day is between 0 and 25 g, otherwise 0; DRINK4: 1 if the amount of drinking per day is 50 ~ 100g; 0 otherwise; DRINK5: 1 if the amount of drinking per day is over 100 g, otherwise 0; NTTC2: 1 if total cholesterol is 200-240 mg / dL, otherwise 0; NTTC3: 1 if the total cholesterol is greater than 240 mg / dL, and 0 otherwise.

Also, the stroke risk prediction module can calculate the predicted risk (KFP) to be taken for a stroke of a woman within 10 years through the following equation.

KF =

0.07836 * (AGE-49.3518) + 0.01606 * (SBP-121.4668) + 0.66432 * (TDM- 0.04060) -0.10626 * (EXSMOK- 0.0203) + 0.31315 * (CUSMOK- 0.0408) + 0.07184 * (EXER1-0.8331) (BMI-23.2290) + 0.01616 * (TDRINK-0.1424) + 0.02277 * (NTTC2-0.2797) + 0.12329 * (NTTC3-0.1193)

KF1 = e ^KF ,

Predicted risk of stroke within 10 years: KFP = 1-0.98410 * KF1

Here, AGE: mannae; SBP: systolic blood pressure; TDM: 1 if there is a history of diabetes mellitus, or if the fasting blood sugar level is over 126 mg / dL or if there is diabetes mellitus taking dose; EXSMOK: 1 if you quit smoking, 0 otherwise; CUSMOK: 1 if smoking now, 0 otherwise; EXER1: 1 if not exercising; 0 if exercising; BMI: body mass index = weight / height ² ; TDRINK: 1 if drinking, 0 if not drinking; NTTC2: 1 if total cholesterol is 200-240 mg / dL, otherwise 0; NTTC3: 1 if the total cholesterol is 240 mg / dL or more, and 0 otherwise.

In addition, the integrated management module may provide the health status of the imaginary target person with the health status of the same group considering the set age range, the set job class, and the set area group, Provides services for recommending medical services and medical institutions considering local groups and provides services for predicting future diseases, prediction of heart disease, prediction of breast cancer or risk of lung cancer, considering the healthcare information of the subject, , Personal information including vaccination data, worker special examination data, persons with disabilities registration data, cause of death data, CT and MRI image data, examination history, blood test history, diagnosis history, weather data and air pollution data And a customized service management module.

According to the Big Data Health Service System according to the present invention, concrete processes and algorithms for Big Data Utilization, Personal Health Record Providing, National Health Insurance Notification Service, etc. are presented.

According to the big data health service system according to the present invention, data of the National Health Insurance Corporation, data of external medical institutions, and the like are integrated to provide integrated national health-related data to be provided to users.

According to the big data health service system according to the present invention, the user can directly confirm his or her integrated health management information through an electronic device such as a smart phone and receive health consultation.

1 is an overall system block diagram illustrating a big data service system provided by a health insurance corporation according to an embodiment of the present invention.
FIG. 2 is a system overall view for explaining a Big Data Service System provided by the health insurance corporation according to an embodiment of the present invention.
FIG. 3 is a flowchart for illustrating the big data service system of FIG. 1 more specifically.
FIG. 4 is a flowchart showing a concrete specific process of the present invention relating to the processing of the stroke risk prediction information in S30 of FIG. 3; FIG.
5A and 5B are flowcharts illustrating a specific process of the present invention relating to a hypertensive prescription management model among the metabolic syndrome customization information in S30 of FIG.
FIG. 6 is a flowchart showing a specific process of the present invention relating to the diabetes prescription management model among the metabolic syndrome customization information in S30 of FIG. 3. FIG.
FIGS. 7A and 7B are flowcharts illustrating a specific process of the present invention relating to a hyperlipidemia prescription management model among the metabolic syndrome association information in S30 of FIG. 3; FIG.
FIGS. 8A and 8B are flowcharts showing specific processes of the present invention relating to the obesity-improving prescription management model in S30 of FIG.

Specific structural and functional descriptions of the embodiments of the present invention disclosed herein are for illustrative purposes only and are not to be construed as limitations of the scope of the present invention. And should not be construed as limited to the embodiments set forth herein or in the application.

The embodiments according to the present invention are susceptible to various changes and may take various forms, so that specific embodiments are illustrated in the drawings and described in detail in this specification or application. It is to be understood, however, that it is not intended to limit the embodiments according to the concepts of the present invention to the particular forms of disclosure, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terms first and / or second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are intended to distinguish one element from another, for example, without departing from the scope of the invention in accordance with the concepts of the present invention, the first element may be termed the second element, The second component may also be referred to as a first component.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, It should be. On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between. Other expressions that describe the relationship between components, such as "between" and "between" or "neighboring to" and "directly adjacent to" should be interpreted as well.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, the terms "comprises ", or" having ", or the like, specify that there is a stated feature, number, step, operation, , Steps, operations, components, parts, or combinations thereof, as a matter of principle.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be construed to have meanings consistent with the context meanings of the related art, and the present invention will be described in detail by explaining them not clearly defined in this specification. Like reference symbols in the drawings denote like elements.

1 is an overall system block diagram illustrating a big data service system provided by a health insurance corporation according to an embodiment of the present invention. The health insurance corporation big data service system 400 is connected to the user terminal 100 and the medical institution server 200 through the network 300. 1, two or more medical institution servers 200 are connected to at least one user terminal 100 and a health insurance corporation big data service system 400 .

In the embodiment of the present invention, 'network', 'communication network' and 'communication' can be used in the same sense. The three terms refer to wired and wireless local and wide area data transmission and reception networks capable of transmitting and receiving a file between a user terminal, a terminal of another user, and a server.

It should be noted that the term 'server' as used herein refers to a logical unit, and is not necessarily a physically separated component, it is obvious to a person skilled in the art to which the present invention belongs.

The user terminal 100 is an electronic device connectable to the health insurance corporation big data service system 400 through the network 300, for example, a smart phone, a tablet, a PC, and the like.

The user terminal 100 can send and receive various user data stored in the user terminal 100 through the application stored in the user terminal 100 or the web provided by the health insurance corporation big data service system 400 Related information that the health insurance corporation Big Data Service System 400 requests to input and transmit the various health related information to the health insurance corporation Big Data Service System 400. [

The medical institution server 200 visits the medical institution and stores the details of the medical treatment of the medical care provider, the result of the medical checkup, and the information on the medical institution in the database.

The health insurance corporation Big Data Service System 400 may request the user terminal 100 or the medical institution server 200 to access the user terminal 100 or the medical institution server 200 And transmits healthcare information data including the details of the medical care of the user terminal 100 or the medical institution server 200 and the health care providers, health examination data, medical institution data, image data, clinical data, do.

The health insurance corporation big data service system 400 allocates a storage space to the storage module of the health insurance corporation big data service system 400 according to the account of the user terminal 100 or the medical institution server 200 Health care information data exchanged with the user terminal 100 or the healthcare institution server 200 and records thereof. That is, the health insurance corporation big data service system 400 may provide the cloud service to the user terminal 100 or the medical institution server 200.

As a result, the user terminal 100 and the medical institution server 200 can access the health insurance corporation big data service system 400 of the cloud function to confirm the user health information and the hospital examination details.

The health insurance corporation big data service system 400 may share the medical record of the clinician with the medical institution server 200 so that when the medical institution server 200 requests the health care information of the clinician, The health care information of the medical care provider can be provided. At this time, it may be necessary to agree with the practitioner, and a separate consent approval procedure may be required.

Also, the health insurance corporation big data service system 400 can provide various services when a user of the user terminal 100 accesses through an electronic device such as a smart phone.

At this time, the services may be customized services by comparing health information with others of the same group (ex. Set age range, set occupation group, set area group, etc.), information of the user (ex. , A set of regional groups, etc.), services for recommending future medical treatments, services for providing personalized health scores, services for predicting heart disease, services for predicting breast cancer or risk of lung cancer, and the like.

For example, the health insurance corporation big data service system 400 may provide a heart disease prediction service and a breast cancer or lung cancer risk prediction service, and the heart disease prediction service is a health checkup patient 30 years or older, (10 years) in consideration of lifestyle, including age, sex, age, height, weight, waist circumference, user information, blood pressure, blood glucose, ill health including cholesterol, family history, And breast cancer or lung cancer risk prediction service is also to predict breast cancer or lung cancer risk considering user information and user's disease and lifestyle habits.

Also, the health insurance corporation Big Data Service System 400 provides the user terminal 100 or the medical institution server 200 with data such as student examination data, vaccination data, worker special examination data, disability registration data, , MRI, etc., and test history, blood test history, diagnosis history, weather data, air pollution data, and various other irregular data.

FIG. 2 is a system overall view for explaining a Big Data Service System provided by the health insurance corporation according to an embodiment of the present invention. 2, the big data service system 400 may include a communication module 410, a storage module 420, a control module 430, a display module 450, and an integrated management module 440 .

The integrated management module 440 may include a health risk assessment management module 442, a stroke risk prediction management module 444, an obesity improvement management module 446 and a metabolic syndrome customization information management module 448.

In the embodiment of the present invention, 'network', 'communication network' and 'communication' can be used in the same sense. The three terms refer to wired and wireless local and wide area data transmission and reception networks capable of transmitting and receiving a file between a user terminal, a terminal of another user, and a server.

As used herein, the term " module " refers to a logical building block, and is not necessarily a physically distinct component, as is apparent to those skilled in the art.

When the cloud connection is established according to the account of the user terminal 100 or the medical institution server 200, the communication module 410 transmits the user's terminal 100 or the medical institution server 200 and the user terminal 100, And healthcare information of the subject including the medical information of the medical institution server 200 can be transmitted and received. The communication module 410 transmits / receives various data to / from the user terminal 100 or the medical institution server 200.

The storage module 420 allocates and stores a space according to the account of the healthcare information of the subject and may allocate a storage space according to the account of the medical institution server 200. [ In addition, the storage module 420 may store the health record of the subject and may store CT, MRI, and other test procedures of the subject.

The display module 450 functions to output a health record of the subject, and output a test procedure history such as CT or MRI of the subject, so that the subject can confirm the test result. In addition, the display module 450 performs a function of outputting other contents that the subject can view in addition to the above-described contents.

The health risk assessment management module 442 performs a function of predicting or evaluating the degree of health such as occurrence of future diseases and risk of death as a present health risk factor of the user.

In order to assess the mortality risk, factors related to the cause of death were BMI, smoking, drinking, exercise, family history (heart, heart, diabetes), blood pressure, blood glucose, blood cholesterol (total cholesterol, low density cholesterol, Cholesterol and gonadal sperm filtration rate information from the user terminal 100 or the medical institution server 200 and may further receive the user's age, sex, height, weight, waist circumference, and the like.

The health risk assessment management module 442 predicts and evaluates the risk of health by considering low-density cholesterol and high-density cholesterol as well as total cholesterol as well as gonadal sperm filtration rate, waist circumference, and the reliability thereof.

The incidence of cerebral hemorrhage, cerebral infarction, and ischemic heart disease was significantly increased at 60 ml / 1.73 m ² or less (Kokubo et al., 2009), and the mortality rate, cardiovascular disease incidence, and hospitalization rate increased (Imai et al., 2008) It is important to set the gonadal sperm filtration rate as a health risk factor for predicting and assessing health risks.

It has also been studied that low-density lipoprotein cholesterol lowered mortality and overall mortality from cardiovascular disease (Scandinavian Simvastatin Survival Study (4S), 1994) and that the lower the high-density cholesterol, the greater the risk of cardiovascular disease Study, it is important to consider low-density cholesterol and high-density cholesterol as well as total cholesterol as health risk factors for predicting and assessing health risks.

In addition, waist circumference has been studied as a risk factor for cerebellar blood pressure independent of body mass index (Janssen et al., 2004), especially in elderly patients, and increases the risk of ischemic stroke, diabetes, It is important to set the waist circumference as the 'health risk factor' of health risk prediction and evaluation.

The health risk assessment management module 442 can predict and evaluate the risk of the user's health through the above-described 'health risk factors', and can provide the user's current health age.

The stroke risk prediction management module 444 may calculate the stroke risk prediction management module 444 according to the gender of the subject in consideration of the age, sex, height, body weight, systolic blood pressure, presence of diabetes, total cholesterol, And performs a function of calculating a predicted risk to be taken by the stroke of the subject. The more specific calculation process of the stroke risk prediction management module 444 will be described later with reference to FIG.

The obesity improvement management module 446 predicts the obesity of the subject using the age, sex, height, weight, and waist circumference information of the subject among the health care information, Can be compared to provide guidance, body composition, weight and waist circumference comparison graphs. Specific services and processes of the obesity improvement management module 446 are shown in Figs. 8A and 8B, which will be described later.

The metabolic syndrome customized information management module 448 performs hypertension diagnosis management of the subject by classifying the hypertensive stage and the pre-hypertensive stage by using the healthcare information of the subject, and, using the healthcare information of the subject, The diabetic diagnosis management of the subject is performed, and diagnosis and management of hyperlipidemia of the subject is performed using the health care information of the subject. The specific process of the metabolic syndrome customization information management module 448 is shown in Figs. 5A to 7B to be described later.

The integrated management module 440 may further include a customized service management module 442 in addition to the health risk assessment management module 442, the stroke risk prediction management module 444, the obesity improvement management module 446 and the metabolic syndrome customization information management module 448 The customized service management module (not shown) may further include a personalized service (e.g., a service) by comparing the health of a user with the same group (e.g., a set age range, a set occupation group, , A service recommending a medical service and a medical institution considering the user's information (ex. Set age range, set occupation group, set area group, etc.), future disease prediction service, heart disease prediction service, breast cancer or lung cancer risk prediction Service and the like can be provided.

In addition, the customized service management module (not shown) may provide the user terminal 100 or the medical institution server 200 with the data such as student's examination data, vaccination data, worker special examination data, And other various non-standard data such as blood test history, diagnosis history, weather data, air pollution data and so on.

3 is a flowchart showing a personalized integrated information service provided by the big data service system of FIG.

3, the health insurance corporation big data service system 400 receives the detailed medical care details, health examination data, medical institution information, image data, clinical data (medical data) of the practitioners from the user terminal 100 or the medical institution server 200 And the like (S10). At this time, the health insurance corporation big data service system 400 may allocate different spaces according to the account of the user terminal 100 or the medical institution server 200. [

When the health insurance corporation Big Data Service System 400 recognizes a cloud connection by an account of a specific user terminal (S20), the input information of the specific user terminal and the accountant information stored by the account, The integrated information including the user's health risk assessment information, stroke risk prediction information, obesity improvement information, and metabolic syndrome customization information according to the account of the specific user terminal in consideration of the specific data sample information stored in the insurance industrial big data service system 400 Is processed by a specific process of the present invention (S30).

Thereafter, the health insurance corporation big data service system 400 provides the processed integrated information according to a request of the specific user terminal (S40). At this time, the processed integrated information may include the health risk assessment information, the stroke risk prediction information, the obesity improvement information, and the metabolic syndrome customization information, and the health insurance corporation big data service system 400 may further include a medical institution server 200, the integrated information may be provided to the medical institution server 200 considering whether the specific user terminal is permitted or not.

FIG. 4 is a flowchart showing a concrete specific process of the present invention relating to the processing of the stroke risk prediction information in S30 of FIG. 3; FIG. FIG. 4 may be performed by the stroke risk prediction management module 444 of FIG.

4, the health insurance corporation Big Data Service System 400 sets a stroke risk prediction model using a cohort study method for a specific period (eg, 1992 to 2007) (S100) . Here, the population with common characteristics about the cause of the disease is called a cohort, and the cohort study method is a method of obtaining information from a specific cohort that is exposed to certain characteristics or causal factors suspected of being involved in disease development And then follow-up observation until the disease occurs in the cohort group. This may be an epidemiological study comparing the incidence of disease in the exposed population compared to the population not exposed to the factor.

In order to establish the stroke risk prediction model, a risk-free prediction model was developed for one-half of the cohort group, and the validity was evaluated in the other half after the cohort was selected as the cohort subject. Can be verified.

The stroke risk prediction model derived from this is shown in Equation (1) or Equation (2) below according to man and woman.

[Equation 1]

0.02411 * (EXER1-0.7128) + 0.06911 * (AGE-44.9956) + 0.02148 * (SBP-124.4739) + 0.58797 * (TDM- 0.0482) -0.02450 * (EXSMOK- (DRINK4-0.0586) + 0.16459 * (DRINK5-0.0199) + 0.06051 * (NTTC2-0.2696) +0.17653 * (NTTC3-0.0956)

KM1 = e ^KM ,

Predicted risk of stroke within 10 years: KMP = 1-0.98485 * KM1

&Quot; (2) "

(EXSMOK-0.0203) + 0.31315 * (CUSMOK-0.0408) + 0.07184 * (EXER1-0.8331) +0.01606 * (SBP-121.4668) + 0.66432 * (TDM- 0.02177 * (BMI-23.2290) + 0.01616 * (TDRINK-0.1424) + 0.02277 * (NTTC2-0.2797) + 0.12329 * (NTTC3-0.1193)

KF1 = e ^KF ,

Predicted risk of stroke within 10 years: KFP = 1-0.98410 * KF1

Here, the variables of the equations (1) and (2) are as follows.

AGE: Mannai

SBP: systolic blood pressure

TDM: 1 if there is a history of diabetes or if the fasting blood glucose level is over 126 mg / dL,

EXSMOK: 1 if you quit smoking, 0 if not

CUSMOK: 1 if smoking now, 0 otherwise

EXER1: 1 if not exercising, 0 if exercising

BMI: body mass index = weight / height ²

DRINK1: 0 g of drinking or 1 if not drinking, 0 otherwise

DRINK2: 1 if the amount of drinking per day is between 0 and 25 g, otherwise 0

DRINK3: 1 if the amount of drinking per day is between 25 and 50 g, otherwise 0

DRINK4: 1 if the amount of drinking per day is 50 ~ 100g, 1 if not

DRINK5: 1 if the amount of drinking per day is over 100 g, 0 if not

TDRINK: 1 if drinking, 0 if not drinking

NTTC1: 1 if less than 200 mg / dL total cholesterol, 0 otherwise

NTTC2: 1 if total cholesterol is 200-240 mg / dL, 1 if not

NTTC3: 1 if total cholesterol is> 240 mg / dL, 0 if not

The health insurance corporation big data service system 400 includes a health insurance information database for storing the healthcare information data, the health-related input information (ex. 1) input by the user terminal 100, The information required for the above equations (1) and (2)), the stroke risk prediction is performed (S200).

At this time, the health insurance corporation big data service system 400 performs a stroke risk prediction according to a result of the check if the user of the user terminal requesting the stroke risk prediction has a health check, and if not, And perform risk prediction to show the result information to the user terminal.

5A and 5B are flowcharts illustrating a specific process of the present invention relating to a hypertensive prescription management model among the metabolic syndrome customization information in S30 of FIG. 5A and 5B may be performed by the metabolic syndrome customization information management module 448 of FIG.

Referring to FIGS. 5A and 5B, the health insurance corporation Big Data Service System 400 provides a customized hypertension prescription to the user who wants to diagnose hypertension according to the flow shown in FIGS. 5A and 5B, I can show you down.

At this time, the health insurance corporation big data service system 400 performs diagnosis of hypertension according to the result of the examination if the user of the user terminal requesting diagnosis of hypertension receives a health check, and if not, diagnoses hypertension And display the result information on the user terminal.

The subject of the hypertension stage may correspond to a person having a systolic blood pressure of 140 mmHg or more, a diastolic blood pressure of 90 mmHg or more, and a subject having a systolic blood pressure of 120 to 139 mmHg or a diastolic blood pressure of 80 to 89 mmHg .

In addition, the standard body weight can be calculated as height (m) * height (m) * 23, and the prescription message contents for HTN1 to HTN14 are as follows.

* Hypertension stage Message number Message Contents HTN1 You are hypertension. Since the risk of cardiovascular disease increases by 2 times every 20 / 10mmHg increase in blood pressure, it is necessary to adjust lifestyle such as low salt and proper aerobic exercise and to adjust to the normal range by taking medication by doctor prescription if necessary. You must. HTN2 You are overweight. You can lower your blood pressure to 5-20 mmHg by lowering your weight to standard weight. HTN3 You are obese. You can lower your blood pressure to 5-20 mmHg by lowering your weight to standard weight. HTN4 You are releasing protein from the urine. It is necessary to take precise medical examination at the hospital about proteinuria. Hypertension may be the cause of proteinuria. If you have proteinuria you should lower your blood pressure to below 130 / 80mmHg. HTN5 Cholesterol is in the boundary range. From now on, please practice your lifestyle to reduce cholesterol. HTN6 There is a possibility of hyperlipemia. You need to have a cholesterol surveillance at the hospital. If bad cholesterol is elevated above normal range, you may need to reduce your cholesterol to a normal range by practicing lifestyle habits that reduce cholesterol through diet and exercise, which can reduce the complications of hypertension. HTN7 Smoking can cause not only cancer diseases such as lung cancer, but also stroke, which is a complication of hypertension, and heart disease more than three times. If you quit smoking, you will start a new life. HTN8 You are not yet diabetic, but you are likely to progress to diabetes. From now on, please be careful about lifestyle control for diabetes control. HTN9 Your blood sugar is in the range of diabetes. If you have diabetes, you need to control your diabetes by adjusting your lifestyle to control your diabetes, and if necessary, by medication prescribed by your doctor. Diabetes control in hypertensive diabetes mellitus can be controlled according to diabetic control in general diabetics.
However, low blood pressure is essential for hypertension. There is no need to restrict or prohibit exercise specifically if hypertension is accompanied by diabetes. Rather, regular exercise is crucial to the control of these diseases. When you exercise, your colleagues should be aware of the symptoms of hypoglycemia.
If you experience hypoglycemic symptoms, you should take simple sugars as soon as possible. If you exercise hard, you should take 15-30 grams of carbohydrates every 30 minutes, and if you have injected fast-acting insulin into your arms and legs, then you should exercise after 1 hour.
In diabetic patients, it is possible that the peripheral nerves may be damaged by foot sensation. You should carefully watch your foot before and after wearing a well-fitting pair of shoes. Drinking can accelerate hypoglycemia after exercise and encourage dehydration, so it is best to avoid exercise after drinking. Because you are diabetic, you need to be more concerned with your blood pressure. HTN10 Your lack of exercise may increase the risk of complications of hypertension. Please exercise regular aerobic exercise. HTN11 If you are eating more than three cups of shochu per day, your chances of complications from hypertension are high. Conversely, when you drink or drink, you can lower your blood pressure by 4-9 mmHg and greatly reduce the complications of hypertension. If you are in a style that can not be bingeed or drunk, you should do it all the same.

* Pre-hypertension Message number Message Contents HTN12 You are at the pre-hypertension stage. People whose blood pressure falls within this range are at twice the risk of developing hypertension compared to those who have lower blood pressure, so active lifestyles should be practiced at this stage. HTN13 You are overweight. Reducing your weight to a standard weight can lower your blood pressure by 5-20mmHg, helping you avoid hypertension. HTN14 You are obese. Reducing your weight to a standard weight can lower your blood pressure by 5-20mmHg, helping you avoid hypertension. HTN15 Protein is detected in the urine. Because proteinuria can not be confirmed at one time, it is better to visit the nearest hospital and have a close examination. In general, elevated blood pressure itself has a negative effect on the kidneys, so it is necessary to try to keep the blood pressure within the normal range as much as possible. HTN16 Cholesterol is in the boundary range. From now on, please practice your lifestyle to reduce cholesterol. HTN17 Smoking can cause not only cancer diseases such as lung cancer, but also stroke, which is a complication of hypertension, and heart disease more than three times. If you quit smoking, you can prevent progression to hypertension and lower your complications from rising blood pressure. HTN18 Your blood sugar is in the range of diabetes. If you have diabetes, you need to control your diabetes by adjusting your lifestyle to control your diabetes, and if necessary, by medication prescribed by your doctor. Diabetes control in hypertensive diabetes mellitus can be controlled according to diabetic control in general diabetics.
You do not have high blood pressure yet, but in the pre-hypertensive phase, low-salt diet is essential to prevent progression to hypertension.
There is no need to restrict or prohibit exercise specifically if you have diabetes. Rather, regular exercise is crucial to the control of these diseases. When you exercise, your colleagues should be aware of the symptoms of hypoglycemia.
If you experience hypoglycemic symptoms, you should take simple sugars as soon as possible. If you exercise hard, you should take 15-30 grams of carbohydrates every 30 minutes, and if you have injected fast-acting insulin into your arms and legs, then you should exercise after 1 hour.
Exercise after 2 to 3 hours of meals, supplementing food 2-3 hours after exercise, and if you have less than 100 mg / dl of pre-exercise blood sugar, take 15-30 g of carbohydrate It is desirable to exercise.
In diabetic patients, it is possible that the peripheral nerves may be damaged by foot sensation. You should carefully watch your foot before and after wearing a well-fitting pair of shoes. Drinking can accelerate hypoglycemia after exercise and encourage dehydration, so it is best to avoid exercise after drinking. Because you are diabetic, you should pay more attention to blood pressure control and keep your blood pressure within the normal range as much as possible.

FIG. 6 is a flowchart showing a specific process of the present invention relating to the diabetes prescription management model among the metabolic syndrome customization information in S30 of FIG. 3. FIG. FIG. 6 may be performed by the metabolic syndrome customization information management module 448 of FIG.

Referring to FIG. 6, the health insurance corporation big data service system 400 may display a customized diabetes prescription to a user who desires to diagnose diabetes according to the flow shown in FIG. 6 in consideration of health information of the user.

At this time, the health insurance corporation big data service system 400 performs diagnosis of diabetes according to the result of the check if the user of the user terminal requesting diagnosis of diabetes has a health check, and if not, diagnoses diabetes And display the result information on the user terminal. Diabetes mellitus is the ICD-10 code in the insurance payroll data.

The standard body weight can be calculated as height (m) * height (m) * 23, and the prescription message contents for DM1 to DM12 are as follows.

Message number Message Contents DM1 You are diabetic. If left untreated, diabetic retinopathy, kidney disease, neuropathy, and foot ulceration may occur, and hypertension, coronary artery, cerebrovascular, and peripheral arterial sclerosis may occur 2 to 4 times more than others There is. However, if you continue to practice diet and exercise to control your blood sugar and continue to strive to reduce risk factors such as hypertension, dyslipidemia, built-up obesity, and smoking, you can reduce your chances of survival to a normal life.
One thing to note is that the customized formulas presented here can not replace the doctor's instructions and instructions. You can get good results if you follow your doctor's instructions and prescriptions faithfully and follow the improvements suggested in your customized prescriptions. DM2 Although you have diabetes, there are very few risk factors that can increase your diabetes complications. Therefore, if you continue to improve your lifestyle habits, you will be able to control your diabetes as well as prevent complications. DM3 You are overweight. Reducing your body weight to standard weight not only lowers your blood sugar level, but it can also improve your insulin resistance, which is a major problem in people with diabetes. DM4 You are obese. Reducing your body weight to standard weight not only lowers your blood sugar level, but it can also improve your insulin resistance, which is a major problem in people with diabetes. DM5 You are releasing protein from the urine. For proteinuria, it is necessary to take a precise examination at the hospital. Diabetes may be the cause of proteinuria. If you have proteinuria, you should make your diabetes control more strict and lower your blood pressure to below 130 / 80mmHg. DM6 Cholesterol is in the boundary range. From now on, please practice your lifestyle to reduce cholesterol. The cholesterol levels shown here are total cholesterol levels. Please consult your physician for a cholesterol surveillance to reduce the low-density cholesterol, the bad cholesterol that causes heart disease, to below 100 mg / dl. DM7 There is a possibility of hyperlipemia. You need to have a cholesterol surveillance at the hospital. If bad cholesterol is increased beyond the normal range, reducing cholesterol to normal range by practicing lifestyle habits that reduce cholesterol through diet and exercise can reduce cardiovascular complications, one of the major complications of diabetes. The cholesterol levels shown here are total cholesterol levels. Please consult your physician for a cholesterol surveillance to reduce the low-density cholesterol, the bad cholesterol that causes heart disease, to below 100 mg / dl. DM8 Smoking can cause not only cancer diseases such as lung cancer but also diabetes complications such as stroke and heart disease as well as various microvascular diseases, so diabetic patients should be quit smoking unconditionally. DM9 Your blood pressure is not high blood pressure yet, but it can progress to hypertension. Now, please be careful about lifestyle control for hypertension control. DM10 Your blood pressure is in the range of hypertension. If you have a high blood pressure, you should take precise medical check-ups at the hospital. If you have hypertension, you should control hypertension through lifestyle control to control hypertension and doctor's prescription if necessary.
Diabetes control in the case of hypertension combined with diabetes can be adjusted according to dietary control in general diabetics. However, low blood pressure is essential for hypertension.
There is no need to restrict or prohibit exercise specifically if diabetes is accompanied by hypertension. Rather, regular exercise is crucial to the control of these diseases. When exercising, patients, carers, and colleagues with exercise should be aware of the symptoms of hypoglycemia.
If you experience hypoglycemic symptoms, you should take simple sugars as soon as possible. If you exercise hard, you should take 15-30 grams of carbohydrates every 30 minutes, and if you have injected fast-acting insulin into your arms and legs, then you should exercise after 1 hour.
Exercise after 2 to 3 hours of meals, supplementing food 2-3 hours after exercise, and if you have less than 100 mg / dl of pre-exercise blood sugar, take 15-30 g of carbohydrate It is desirable to exercise.
In diabetic patients, it is possible that the peripheral nerves may be damaged by foot sensation. You should carefully watch your foot before and after wearing a well-fitting pair of shoes. Drinking can accelerate hypoglycemia after exercise and encourage dehydration, so it is best to avoid exercise after drinking. Because you are diabetic, you should pay more attention to blood pressure control and keep your blood pressure within the normal range as much as possible. DM11 Your lack of exercise may increase the risk of complications of diabetes. Regular aerobic exercise improves blood glucose control, decreases cardiovascular risk factors, decreases weight, and increases the feeling of health. Please exercise regular aerobic exercise. DM12 If you are eating more than three glasses of shochu per day, the likelihood of diabetic complications is high.
Drinking can reduce insulin sensitivity and not only worsen diabetes, but excessive drinking can cause complications such as hypoglycemia. If you are in a style that can not be bingeed or drunk, you should do it all the same.

FIGS. 7A and 7B are flowcharts illustrating a specific process of the present invention relating to a hyperlipidemia prescription management model among the metabolic syndrome association information in S30 of FIG. 3; FIG. 7A and 7B may be performed by the metabolic syndrome customization information management module 448 of FIG.

Referring to FIGS. 7A and 7B, the health insurance corporation Big Data Service System 400 displays a customized hyperlipidemia prescription in consideration of the user's health related information to a user who desires to diagnose hyperlipidemia according to the flow shown in FIGS. 7A and 7B .

At this time, the health insurance corporation big data service system 400 performs diagnosis of hyperlipidemia according to the result of the examination if the user of the user terminal requesting diagnosis of hyperlipidemia receives a health examination, and if not, diagnoses hyperlipidemia And display the result information on the user terminal. The ICD-10 code in the insurance benefit data is a hyperlipidemia, and a personalized prescription can be made by distinguishing between those with cholesterol levels of 200 to 239 mg / dL and those with a cholesterol level of more than 240 mg / dL.

The standard body weight can be calculated as height (m) * height (m) * 23, and the prescription message contents for HL1 to HL14 are as follows.

(All patients who have a diagnosis of hyperlipidemia with a symptom of pancreatic disease or a wounded person provide the message of HL1 to those with cholesterol level of 200 to 240 mg / dL, and the symptom of pancreas and injured person is diagnosed as hyperlipidemia. , Subtype of HL2 that does not meet one of the risk factors of proteinuria, cholesterol, smoking, blood sugar, exercise, and alcohol)

Message number Message Contents HL1 The customized recipe presented here can not replace the doctor's instructions and instructions. You will be able to get good results if you follow your doctor's instructions and prescriptions in faith and follow the improvements suggested in your personalized prescription. HL2 Although you are hyperlipidemia, there are very few risk factors that can increase the complications of hypertension. Therefore, if you continue to improve lifestyle habits, you will be able to control not only complications but also hypertension. HL3 You are overweight. Reducing your weight to standard weight can lower your cholesterol in the boundaries. HL4 You are obese. Reducing your weight to standard weight can lower your cholesterol in the boundaries. HL5 You are releasing protein from the urine. For proteinuria, it is necessary to take a precise examination at the hospital.
Cholesterol elevation can affect the production of proteinuria in addition to hypertension, so be careful about cholesterol reduction. HL6 There is a possibility of high blood pressure. You need to have a high blood pressure test at the hospital.
If you are diagnosed with hypertension, you can practice your lifestyle by lowering your blood pressure through diet and exercise, consult your doctor and consider taking medication if needed. HL7 Hypertension is in the borderline. From now on, please practice lifestyle that lowers blood pressure. HL8 Smoking can increase stroke and heart disease, which are complications of hypertension and hyperlipemia, more than three times, as well as cancers such as lung cancer.
Be sure to quit smoking. HL9 Your blood sugar is not yet diabetic, but it is likely to progress to diabetes. From now on, please be careful about lifestyle control for diabetes control. HL10 Your blood sugar is in the range of diabetes. If you have diabetes, you need to control your diabetes by adjusting your lifestyle to control your diabetes, and if necessary, by medication prescribed by your doctor.
Diabetes control in the case of diabetes mellitus in hyperlipidemia can be controlled according to dietary control in general diabetic patients. However, cholesterol lowering cholesterol diet is essential for hyperlipidemia, please do your efforts.
There is no need to restrict or prohibit exercise specifically if hyperlipidemia is accompanied by diabetes. Rather, regular exercise is crucial to the control of these diseases. When exercising, patients, carers, and colleagues with exercise should be aware of the symptoms of hypoglycemia.
If you experience hypoglycemic symptoms, you should take simple sugars as soon as possible. If you exercise hard, you should take 15-30 grams of carbohydrates every 30 minutes, and if you have injected fast-acting insulin into your arms and legs, then you should exercise after 1 hour. Exercise after 2 to 3 hours of meals, supplementing food 2-3 hours after exercise, and if you have less than 100 mg / dl of pre-exercise blood sugar, take 15-30 g of carbohydrate It is desirable to exercise.
In diabetic patients, it is possible that the peripheral nerves may be damaged by foot sensation. Careful observation of foot injuries before and after exercise in well-fitting shoes is necessary, and it is necessary to prevent blisters and keep feet dry.
Drinking can accelerate hypoglycemia after exercise and encourage dehydration, so it is best to avoid exercise after drinking. HL11 Your lack of exercise may increase the risk of complications of hyperlipidemia. Regular aerobic exercise improves hyperlipidemia and has a positive effect on strengthening cardiopulmonary function to prevent various side effects caused by hyperlipidemia. Please exercise regular aerobic exercise. HL12 If you eat more than three cups of shochu per day, you are more likely to have complications from hyperlipidemia, as well as increase triglycerides, one of the worst cholesterol.
On the other hand, when you drink or drink alcohol, you can not only improve your cholesterol levels, but you can also greatly reduce the complications of hyperlipemia. If you are in a style that can not be bingeed or drunk, you should do it all the same. HL13 You are overweight. You can lower your cholesterol by lowering your weight to standard weight. HL14 You are obese. Reducing your weight to standard weight can lower your cholesterol in the boundaries.

FIGS. 8A and 8B are flowcharts showing specific processes of the present invention relating to the obesity-improving prescription management model in S30 of FIG. 8A and 8B may be performed by the obesity improvement management module 446 of FIG.

8A and 8B, the health insurance corporation big data service system 400 displays a customized obesity improvement prescription in consideration of the user's health related information to a user who desires to diagnose obesity improvement according to the flow of FIGS. 8A and 8B .

At this time, the health insurance corporation Big Data Service System 400 performs the obesity diagnosis according to the result of the examination if the user of the user terminal requesting the diagnosis of obesity receives the health examination, and if not, Can be performed.

The health insurance corporation big data service system 400 requests the user terminal to input basic body information (age, sex, height, weight, waist circumference, complication information) when the user terminal logs in through the account, When the input is completed by the terminal, the obesity diagnosis result (eg, altitude obesity, obesity, overweight, normal, etc.) is output according to the obesity diagnosis process shown in FIG. 8B.

Then, the health insurance corporation Big Data Service System 400 requests the user terminal to newly input a target (e.g., body weight, waist circumference, etc.), compares the current state and the target, A comparison graph can be provided.

In addition, the health insurance corporation Big Data Service System 400 can provide a health diary including a diary, a diary, and a diary to record and confirm the diary and instructions to the user terminal.

Also, the health insurance corporation Big Data Service System 400 may be configured to provide a user data service system 400 with a user data inputting section (inputting a meal therapy statement) about a meal, an inputting statement (entering a exercise therapy statement) ), And when the input from the user terminal is completed, the user can provide a dietary instruction, exercise therapy instruction, behavior therapy instruction, and exercise method guide video in consideration of the inputted information.

In addition, the health insurance corporation Big Data Service System 400 may provide a quiz about obesity, eating, exercise, and behavior to a user terminal, and may provide a service so that a user terminal can set an avatar.

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium.

A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like. (E.g., transmission over the Internet).

The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. And functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers skilled in the art to which the present invention pertains.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

Claims (4)

At least one user terminal;
At least one medical institution server; And
Wherein the at least one user terminal or the medical institution server is connected to the at least one user terminal or the at least one medical institution server by input information input by the at least one user terminal, Information on health risks of the subject, estimating a risk of stroke, estimating the risk of stroke, providing obesity and improvement measures, and transmitting the health risk information to the at least one user terminal or the medical institution server, And a Big Data Service System of Health Insurance Corporation which integrally manages the metabolic syndrome management and provides corresponding information,
The health insurance corporation big data service system comprises:
An integrated management module for evaluating the health risk of the subject, predicting stroke risk, providing obesity and improvement measures, and managing the metabolic syndrome integrally to provide corresponding information,
Wherein the integrated management module comprises:
The health status of the subject is provided to a healthcare service that provides health and comparison services of the same group considering the set age range, the set occupation group and the set area group, and the medical service and medical care service that considers the set age range, Provides a service that recommends the institution and provides the prediction service of future diseases, the prediction of heart disease, the prediction of breast cancer or the risk of lung cancer considering the healthcare information of the target person, and the data on student examination, vaccination data, A personalized service management module for providing customized information including data, persons with disabilities registration data, cause of death data, image data such as CT and MRI, inspection history, blood test history, diagnosis history, weather data and air pollution data Big data health service system with features. The method according to claim 1,
The health insurance corporation big data service system comprises:
Wherein the at least one user terminal or the medical institution server is connected to the at least one user terminal or the medical institution server by the account of the at least one user terminal or the medical institution server, A communication module for transmitting and receiving the healthcare information of the subject; And
And a storage module for allocating and storing a space according to the account of the healthcare information of the subject,
Wherein the integrated management module comprises:
Blood pressure, blood glucose, total cholesterol, low density cholesterol, high density cholesterol, ginsenoside filtration rate information, age, sex, height, body weight, waistline, body weight index, smoking, drinking, exercise, A health risk assessment management module for estimating a health risk of the subject in consideration of circumference information to derive a health age of the subject;
The health care information is subjected to different calculations according to gender in consideration of the subject's age, sex, height, weight, systolic blood pressure, presence of diabetes, total cholesterol, drinking, smoking and exercise, A stroke risk prediction management module that calculates a prediction risk to be taken by the stroke risk prediction module;
The method of the present invention predicts the obesity of the subject using the age, sex, height, weight, and waist circumference information of the subject in the health medical information, compares the current state with the target state inputted by the subject, An obesity improvement management module that provides a weight and waist circumference comparison graph; And
Performing hypertension diagnosis management of the subject by distinguishing the hypertension stage and the pre-hypertension stage using the healthcare information of the subject, performing diabetes diagnosis management of the subject using the healthcare information of the subject, And a metabolic syndrome customized information management module for performing diagnosis management of hyperlipidemia of the subject using the health care information of the metabolic syndrome customized information management module. 3. The method of claim 2,
Wherein the stroke risk prediction management module comprises:
The predicted risk of stroke (KMP) for men within 10 years is calculated by the following equation (1)
<Next 1>
KM =
0.02411 * (AGE-44.9956) + 0.02148 * (SBP-124.4739) + 0.58797 * (TDM-0.0482) -0.02450 * (EXSMOK- 0.2024) + 0.27720 * (CUSMOK- 0.5909) + 0.06916 * (EXER1-0.7128) + 0.03120 * (BMI-23.2356) + 0.06810 * (DRINK1-0.2329) -0.02830 * (DRINK2-0.5753) + 0.10992 * (DRINK4-0.0586) + 0.16459 * (DRINK5-0.0199) + 0.06051 * (NTTC2-0.2696) + 0.17653 * -0.0956),
KM1 = e ^KM ,
Predicted risk of stroke within 10 years: KMP = 1-0.98485 * KM1
EXSMOK: 1 if the cigarette has been cut off; 0 otherwise; CUSMOK: If the diabetic patient has a history of diabetes mellitus or has a fasting blood glucose level of 126 mg / dL or is diabetic, BMI: body mass index = weight / height ² ; DRINK1: 0 g drinking or 1 if not drinking; 0 otherwise DRINK2: drinking per day 0 DRINK4: 1 if the amount of drinking per day is between 50 and 100 g, otherwise 0; DRINK5: 1 if the amount of drinking per day is greater than 100 g, otherwise 0; NTTC2: 1 if the total cholesterol is 200 to 240 mg / dL, Otherwise 0; NTTC3: 1 if the total cholesterol is> 240 mg / dL, otherwise 0)
Wherein the stroke risk prediction management module comprises:
Wherein the predicted risk (KFP) to be taken by a woman within 10 years of stroke is calculated by the following equation (2).
<Next 2>
KF =
0.07836 * (AGE-49.3518) + 0.01606 * (SBP-121.4668) + 0.66432 * (TDM- 0.04060) -0.10626 * (EXSMOK- 0.0203) + 0.31315 * (CUSMOK- 0.0408) + 0.07184 * (EXER1-0.8331) (BMI-23.2290) + 0.01616 * (TDRINK-0.1424) + 0.02277 * (NTTC2-0.2797) + 0.12329 * (NTTC3-0.1193)
KF1 = e ^KF ,
Predicted risk of stroke within 10 years: KFP = 1-0.98410 * KF1
EXSMOK: 1 if the cigarette has been cut off; 0 otherwise; CUSMOK: If the diabetic patient has a history of diabetes mellitus or has a fasting blood glucose level of 126 mg / dL or is diabetic, BMI: body mass index = weight / height ² ; TDRINK: 1 if drinking, 0 if not drinking; NTTC2: total cholesterol 200 to 240 mg / dL 1, otherwise 0; NTTC3: 1 if the total cholesterol is 240 mg / dL or greater; otherwise, 0) delete

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