KR102501900B1 - Method for selling medical data for specific buyers - Google Patents

Abstract

The present invention relates to a method for selling medical data for specific buyers, which includes: a step (201) of collecting medical data; a step (202) of generating a plurality of health reports and health guide data; a step (203) of processing a plurality of types of medical data; a step (204) of performing pseudonymization on a plurality of types of processed data; a step (205) of performing advertising and publicity work; a step (206) of screening a plurality of diseased persons according to certain criteria; a step (207) of marketing to a specific buyer; a step (208) of applying for purchase; a step (209) of extracting a plurality of types of data according to the inputted purchase conditions and symptoms; a step (210) of calculating various costs; a step (211) of providing the calculated various costs and the extracted plurality of types of data; a step (212) of displaying the various costs and the plurality of types of data, respectively; a step (213) of paying points, respectively, and providing receipts corresponding to the points, respectively; and a step (214) of displaying the points and receipts provided, respectively.

Description

Method for selling medical data for specific buyers}

The present invention relates to a method for selling medical data, and more particularly, by processing and pseudonymizing a plurality of medical data collected with the consent of a plurality of data providers and providing them to a specific purchaser such as an insurance company or a financial company, It relates to a method of selling medical data to a specific purchaser that can contribute to related industries by utilizing prediction, new drug development, and medical image analysis.

Recently, the demand for medical data is increasing in the fields of medical, health, health, and healthcare artificial intelligence.

Medical data can be used in various fields such as R&D of pharmaceutical companies, clinical data, billing and cost data, research and development of new drugs and new medical techniques, provision of health care services, and decision-making of health care policies.

In addition, the medical data can be usefully used for disease prediction, medical, health, research cost reduction in the health field, inventory management and demand forecasting of pharmaceutical companies.

For example, the National Health Insurance Corporation established a national health information database in 2012 based on vast data such as health insurance qualifications and insurance premiums, treatment details, health care institution status, cancer and rare intractable disease patient registration information, and senior long-term care insurance data. did.

On the other hand, medical my data means that people voluntarily collect and manage their own medical data in one place based on the right to self-determination of personal information, and actively utilize it for desired medical treatment and health management services.

However, the chronic problems in using medical my data are as follows.

First, even if a user wants to utilize his/her own medical data, it is difficult to access the medical data and cannot reliably grasp the contents of the medical data.

In addition, the medical my data industrial ecosystem that can encompass public institutions, medical institutions, and the industry as a whole has not been established.

In addition, even if the medical my data ecosystem is established, the personal information of users who provide medical data may be leaked, which acts as a factor limiting the construction and utilization of a large number of medical data.

KR 10-2022-0133539 A

The present invention has been devised to solve the above problems, and an object of the present invention is to process and pseudonymize a plurality of medical data collected with the consent of a plurality of data providers, and provide them to specific buyers such as insurance companies and financial companies, It is to provide a method of selling medical data to a specific buyer who can contribute to related industries by utilizing a large number of medical data for disease prediction, new drug development, and medical image analysis.

In addition, an object of the present invention is to provide a method for selling medical data for a specific purchaser that can select a specific purchaser, such as an insurance company, a financial company, or a pharmaceutical company, and provide the specific purchaser with disease patient information for each symptom, such as severe, mild, and suspected disease. are doing

In addition, an object of the present invention is to calculate the processing cost, reward cost, advertising cost, service cost, insurance linkage cost, and target selection cost according to the criteria set in advance for a plurality of disease patient information for each symptom for a specific purchaser, respectively, and add them up according to the weight. It is to provide a method of selling medical data for a specific buyer that can be provided at all costs.

In order to solve the above technical problem, the method of selling medical data for a specific purchaser according to the present invention provides a plurality of data providers provided by a plurality of user terminals 10 by the collection unit 21 of the platform server 20. Step 201 of collecting personal information, health checkup results, and medical data including prescriptions, the analysis unit 22 of the platform server 20 converts the plurality of health checkup result data collected in step 201 to AI Step 202 of generating a plurality of health report and health guide data, respectively, by analyzing each through, Step 203 of processing a plurality of medical data by the processing unit 24 of the platform server 20, respectively, the platform server Step 204, in which the pseudonymization processing unit 25 of (20) performs pseudonymization so that personal information cannot be identified for the plurality of data processed in step 203, the advertisement unit 31 of the platform server 20 ) is based on the plurality of pseudonymized data in step 204, and performs advertising and promotion tasks through notification services such as text messages, voice messages, or images to the information providing platform 40. Step 205 Step 206, in which the target selection unit 32 of the platform server 20 classifies the plurality of data pseudonymized in step 204 according to symptoms of the disease, and selects a plurality of patients according to a predetermined standard, the platform Step 207, in which the marketing unit 33 of the server 20 performs marketing for a specific purchaser registered in the information providing platform 40 based on the information on the plurality of disease patients selected in step 206, the information Step 208 of the purchase application unit 42 of the providing platform 40 requesting a purchase from the sales unit 29 of the platform server 20 through the purchase application, the extraction unit 27 of the platform server 20 Step 209 of extracting a plurality of pieces of data according to the purchase conditions and symptoms input and processed in step 208 from the information on the plurality of patients with diseases selected in step 206, cost calculation of the platform server 20 Step 210 in which the unit 34 calculates various costs for the plurality of data extracted in the step S209, and the sales unit 29 calculates the various costs calculated in the step 210 and Step 211 of providing data to the data confirmation unit 43 of the information providing platform 40, respectively, and the data confirmation unit 43 displaying various costs and a plurality of data provided in step 211, respectively Step 212, the reward payment unit 30 of the platform server 20 provides points to the point confirmation unit 12 of the plurality of user terminals 10 corresponding to the plurality of data sold in step 211, respectively; , Step 213 of providing receipts corresponding to the points, and Step 213 of displaying the points and receipts provided in Step 213 so that the point confirmation unit 12 of the user terminal 10 can recognize the data provider. It is characterized by including 214 steps.

In addition, in step 202, the analyzer 22 analyzes the plurality of health examination result data collected in step 201 through the AI, and provides predictable disease information according to region, age group, and gender. Step 202-1 of generating a plurality of health report data including each, and the analyzer 22 analyzes the plurality of disease information included in the plurality of health report data generated in step 202-1, , a step 202-2 of generating a plurality of health guide data including opinions such as exercise or diet, and in step 203, the processing unit 24 determines the main factors of the national health examination result data 22 Step 203-1 of analyzing the branches and classifying them by disease. Step 203-1 of classifying the plurality of diseases classified in step 203-1 by the processing unit 24 by patient based on the number of patients suspected of having the disease. -203-3, in which the processing unit 24 classifies the plurality of patients classified in the step 203-2 into age group, region, and gender based on the personal information provided from the user terminal 10 The disease is characterized by including obesity, hypertension, anemia, diabetes, dyslipidemia, chronic kidney disease, liver disease, pulmonary tuberculosis, and chest disease.

Further, in step 206, based on the plurality of health reports generated in step 202, the subject selection unit 32 classifies a plurality of patients into those with severe diseases, those with mild diseases, and those with suspected diseases, respectively. and a step 206-2 in which the subject selection unit 32 selects a plurality of patients with diseases suitable for criteria of a disease, age group, and gender set in advance from among the plurality of patients classified according to symptoms of the disease in step 206-1. It is characterized by including.

In addition, in step 207, the purchaser registration unit 45 of the information providing platform 40 inputs and processes purchaser information selected from insurance companies, financial companies, pharmaceutical companies, AI-related educational institutions, and public institutions. Step 207-1, Step 207-2 in which the purchaser registration unit 45 inputs and processes whether life insurance or non-life insurance is handled and whether insurance or financial products are recommended; Step 207-3 of selecting a specific purchaser who handles life insurance or non-life insurance and a specific purchaser who recommends insurance or financial products to the general public. Step 207-4 of performing marketing for a specific purchaser who handles life insurance or non-life insurance among purchasers by using information on a number of severely ill patients, and the marketing unit 33 selects the specific purchaser in step 207-3 Step 207-5 of performing marketing using information on persons with mild diseases and persons suspected of having diseases for a specific purchaser who recommends insurance or financial products to the general public.

In addition, in step 208, the purchase application unit 42 inputs and processes the disease name, region, age group, and gender of a plurality of data to be purchased as purchase conditions in the purchase application form. Step 208-2, in which the application unit 42 inputs and processes one or more selected symptoms from among severe symptoms, mild symptoms, and suspected disease into the purchase application form, and the purchase application unit 42 inputs and processes one or more selected symptoms from health examination results, prescriptions, and health reports and a step 208-3 of inputting and processing the types of selected data and the quantity of the selected data into the purchase application, respectively, and the step 210 includes the cost calculation unit 34 extracting the data extracted in the step 209. Step 210-1 of multiplying the processing cost, reward cost, advertisement promotion cost, and service cost calculated for the plurality of data by a first weight value, a second weight value, a third weight value, and a fourth weight value, respectively, and summing them up; Step 210-2, in which the cost calculation unit 34 calculates insurance linkage costs and target selection costs, respectively; It is characterized in that it includes a step 210-3 of calculating overall costs by adding the calculated insurance connection cost and target selection cost, respectively.

Further, in step 211, the sales unit 29 determines the title of the data, the description content, the type of data, the target of extraction, the name of the region, the gender, the age group, the name of the disease, and the major information about the plurality of data extracted in the step 209. Step 211-1 of generating detailed data by describing factors, quantity of data, and expiration date of data, and the sales unit 29 converts the overall costs calculated in step 210 to the information providing platform 40 Step 211-2 provided to the data checking unit 43, and the sales unit 29 adds the detailed data generated in step 211-1 to the plurality of data extracted in step 209 to check the data It is characterized in that it includes a step 211-3 providing to the unit 43.

In addition, in step 213, the reward payment unit 30 provides health guides, health reports, prescriptions, and health examination result data for a plurality of user terminals 10 corresponding to the plurality of data sold in step 211. Step 213-1 of assigning high points in order, the reward payment unit 30 determines the transaction date, type of data, demand destination, Step 213-2 of issuing receipts marked with the consenter and points, and the reward payment unit 30 reports to the point confirmation unit 12 of the plurality of user terminals 10 where the receipts were issued in step 213-2. It is characterized by including a step 213-3 of providing points and providing a corresponding receipt.

In addition, step 214 is step 214-1 in which the additional point payment unit 13 of the user terminal 10 grants a small amount of points to the user terminal 10 that has gone through a log-in process, the point confirmation unit Step 214-2 of (12) summing up the points provided in step 213 and the small amount of points granted in step 214-1. It is characterized by including a step 214-3 of displaying points and receipts, respectively, and a step 214-4 of displaying the point shop and digital voucher shortcut icons by the point confirmation unit 12.

In addition, the point shop is a purchase site where data providers can purchase gifticons they want by using the points available in the point confirmation unit 12, and the digital voucher is linked to local currency, so it can be used as an affiliate site in the region. It is characterized in that it is a currency that can be used in the same way as cash.

The method of selling medical data for a specific purchaser according to the present invention processes and pseudonyms a plurality of medical data collected with the consent of a plurality of data providers, and provides them to a specific purchaser such as an insurance company or a financial company, thereby predicting disease of a plurality of medical data , new drug development, medical image analysis, etc., it has the effect of contributing to related industries.

In addition, the method of selling medical data for a specific purchaser according to the present invention selects a specific purchaser, such as an insurance company, a financial company, or a pharmaceutical company, and provides the specific purchaser with disease information for each symptom, such as severe, mild, and suspected disease, to the specific purchaser. There is an effect of providing a large number of medical data suitable for the user's taste in a timely manner.

In addition, the method for selling medical data according to the present invention calculates processing cost, reward cost, advertising cost, service cost, insurance linkage cost, and target selection cost according to pre-set criteria for a plurality of disease patient information for each symptom for a specific purchaser, respectively, and weights them. Therefore, it is possible to provide a large number of medical data to a specific buyer transparently and at a reasonable price.

1 is a block diagram of a medical data management platform according to the present invention.
1 is a configuration diagram of a user terminal.
3 is an exemplary diagram of prescription data.
4 is a configuration diagram of a platform server.
5 is a data flow diagram of a platform server.
6 is a block diagram illustrating a data processing process by a processing unit.
7 is a configuration diagram of an information providing platform.
8 is a further configuration diagram of a platform server.
9 is a data flow diagram between an extraction unit, a sales price calculation unit, a sales unit, and a reward payment unit of the platform server.
10 is a block diagram of a reward payment process by a reward payment unit.
11 is a configuration diagram of a point confirmation unit of a user terminal.
12 is a configuration diagram of a point shop.
13 is a configuration diagram of a digital voucher.
14 is a block diagram of a buyer registration process by a buyer registration unit.
15 is a data flow diagram among an extraction unit, a sales unit, an advertising unit, a target selection unit, a marketing unit, and a cost calculation unit.
16 is a flowchart of a marketing process by a marketing unit.
17 is a flow chart of the overall cost calculation process by the cost calculation unit.
18 is a flowchart of steps S201 to S207 in the method for selling medical data according to the present invention.
19 is a flowchart of steps S208 to S214 in the method for selling medical data according to the present invention.
Figure 20 is a flow chart for the health checkup result analysis, health report and health guide generation process (S202).
21 is a flowchart of a process of processing medical data (S203).
22 is a flow chart for the disease patient selection process (S206).
23 is a flowchart for the marketing process 207.
24 is a flowchart of a purchase request process (S208).
25 is a flowchart of the overall cost calculation process (S210).
26 is a flow chart of the process of providing various costs and data (S211).
27 is a flowchart of a point payment and receipt provision process (S213).
28 is a flowchart of a point and receipt display process (S214).

First, the medical data sales platform according to the present invention will be described.

1 is a block diagram of a medical data sales platform according to the present invention.

Referring to FIG. 1 , a medical data sales platform according to the present invention includes a user terminal 10 , a platform server 20 and an information providing platform 40 .

First, the user terminal 10 is provided to a plurality of data providers and respectively inputs and processes personal information and medical data of the data providers.

At this time, the user terminal 10 may input and process personal information and medical data, respectively, after the data provider's personal information and medical data collection and use agreement is input and processed.

In addition, the platform server 20 collects personal information and medical data of data providers from a plurality of user terminals 10, comprehensively manages them based on blockchain, mediates them to the information providing platform 40, and sells them. do.

Also, in the information providing platform 40, a plurality of buyers may each purchase medical data managed by the platform server 20 through the information providing platform 40.

1 is a configuration diagram of a user terminal 10 .

Referring to FIG. 1 , a user terminal 10 may include an input unit 11 .

First, the input unit 11 inputs and processes the consent form of the data provider, personal information, and medical data, respectively.

Here, consent means a document agreeing to the collection and use of personal information and medical data.

At this time, in the input unit 11, personal information and medical data may be sequentially input and processed after the consent form of the data provider is input and processed.

Meanwhile, the medical data may include data such as health checkup results, prescriptions, medical records, and genetic test results.

In addition, the health checkup result data may include data such as diagnosis results, measurement tests, blood tests, urine tests, and imaging tests.

Specifically, the main factors of health examination result data are height (cm), weight (kg), waist circumference (cm), body mass index (kg/m2), vision left/right, hearing left/right, systolic blood pressure (mmHg) , diastolic blood pressure (mmHg), urinary protein, hemoglobin (g/dL), fasting blood glucose (mg/dL), total cholesterol (mg/dL), HDL cholesterol (mg/dL), triglyceride (mg/dL), LDL Cholesterol (mg/dL), serum creatinine (mg/dL), glomerular filtration rate (GFR) (mL/min), AST (serum GT) (U/L), ALT (serum GT) (U/L) , gamma-GTP (U/L), pulmonary tuberculosis, chest disease, and osteoporosis.

3 is an exemplary diagram of prescription data.

Referring to FIG. 3 , the prescription data may include a disease classification code, medical institution information, prescription drug information, and examinee information.

Further, the medical institution information may include data such as the issuance date of the prescription, the name of the medical institution, and the contact information of the medical institution.

For example, the issuance date of the prescription data may be January 25, 2021, the name of the medical institution may be a university hospital, the telephone number of the medical institution may be 051-520-5500, and the fax number of the medical institution may be 051-520-5501.

In addition, the drug information of the prescription drug may include a drug name, a drug code, and a single dose.

For example, the drug name may be Actos Tablets 15mg (Pioglitazone Hydrochloride) (16.53mg/1 tablet), the drug code may be 696300140, and the dosage may be 1 tablet.

In addition, the medical history may include data such as medical records, certificates, and diagnosis information.

In addition, genetic test results may include data such as aging, skin/hair, major diseases, cancer, and health care items.

4 is a configuration diagram of the platform server 20, and FIG. 5 is a data flow diagram of the platform server 20.

4 and 5, the platform server 20 includes a collection unit 21, an analysis unit 22, a storage unit 23, a processing unit 24, a pseudonym processing unit 25 and a registration unit 26. composed of

First, the collection unit 21 collects personal information and medical data of a plurality of data providers provided by a plurality of user terminals 10 .

Then, the analysis unit 22 analyzes a plurality of health examination result data through AI, respectively, and generates a plurality of health reports and health guide data, respectively.

Specifically, the analysis unit 22 analyzes a plurality of health examination result data through AI, respectively, and generates a plurality of health report data including a plurality of predictable disease information according to region, age group, and gender.

In addition, the analysis unit 22 analyzes a plurality of disease information included in a plurality of health report data, respectively, and generates a plurality of health guide data including opinions on exercise or diet, respectively.

In addition, the storage unit 23 stores a plurality of personal information and medical data collected by the collection unit 21 and a plurality of health reports and health guide data generated by the analysis unit 22, respectively.

Also, the processing unit 24 processes a plurality of medical data stored in the storage unit 23, respectively.

Also, the pseudonym processing unit 25 performs pseudonymization so that personal information cannot be identified for the plurality of data processed by the processing unit 24 .

Then, the registration unit 26 registers the plurality of data pseudonymized by the pseudonymization processing unit 25 in the information providing platform 40 according to the number of data, region, age group, and gender.

6 is a block diagram illustrating a data processing process by the processing unit 24 .

Referring to FIG. 6, the processing unit 24 analyzes 22 major factors of the national health examination result data and classifies them by disease.

In this case, the disease may include obesity, hypertension, anemia, diabetes, dyslipidemia, chronic kidney disease, liver disease, pulmonary tuberculosis, and chest disease.

In addition, the processing unit 24 classifies the plurality of diseases classified by the processing unit 24 into each patient based on the number of suspected diseases provided by the National Health Insurance Corporation.

Further, the processing unit 24 classifies the plurality of diseased patients classified by the processing unit 24 into age groups, regions, and genders based on the personal information provided from the user terminal 10 .

7 is a configuration diagram of the information providing platform 40.

Referring to FIG. 7 , the information providing platform 40 includes a list confirmation unit 41 and a purchase request unit 42 .

First, the list confirmation unit 41 can check a plurality of data registered by the registration unit 26 of the platform server 20 .

In addition, the purchase application unit 42 applies for purchase through a purchase application form for a plurality of data that can be confirmed by the list confirmation unit 41 .

At this time, in the purchase application, disease names, regions, age groups, and genders of a plurality of data to be purchased as purchasing conditions may be input.

Further, in the purchase application form, one or more pieces of data may be selected from among health checkup results, prescriptions, and health reports suitable for the purchase conditions, and the quantity of the corresponding data may be input.

8 is a further configuration diagram of the platform server 20.

9 is a data flow diagram between the extraction unit 27, the sales price calculation unit 28, the sales unit 29, and the reward payment unit 30 of the platform server 20.

Referring to FIGS. 8 and 9 , the platform server 20 further includes an extraction unit 27 , a sales price calculation unit 28 , a sales unit 29 , and a reward payment unit 30 .

First, the extraction unit 27 extracts a plurality of data requested by the purchase request unit 42 from a plurality of data processed by the processing unit 24 when a purchase request is made by the purchase request unit 42 .

And, the sales price calculation unit 28 calculates the sales price for the plurality of data extracted by the extraction unit 27 .

Then, the sales unit 29 provides the information providing platform 40 with the plurality of data extracted by the extraction unit 27 and the sales price calculated by the sales price calculation unit 28 .

And, the reward payment unit 30 provides points to a plurality of user terminals 10 corresponding to the plurality of data sold by the sales unit 29 and provides receipts corresponding to the points.

On the other hand, the selling price calculation unit 28 multiplies the reference unit price set in advance and the quantity provided by the purchase request unit 42 for the plurality of data extracted by the extracting unit 27, and then sums them to determine the selling price. yield

Then, the sales unit 29 provides the sales price calculated by the sales price calculation unit 28 to the information providing platform 40 .

Then, the sales unit 29 provides a plurality of data extracted by the extraction unit 27 to the information providing platform 40 . At this time, the sales unit 29 may provide a plurality of data extracted by the extraction unit 27 in a web view, CSV, JSON, or the like method.

In addition, the plurality of data provided by the sales department 29 includes the title of the data, the description content, the type of data, the extraction target, the name of the region, gender, age group, disease name, main factor, quantity of data, expiration date of the data, etc. Detailed data may be included.

For example, the title of the data may be the results of health examinations for men in their 30s and 40s in Seoul who are suspected of endocrine/metabolic diseases with a total cholesterol level of 240 or higher.

And, the explanation of the data is that total cholesterol is a number that includes HDL, LDL, and triglycerides. Generally, more than 240 mg/dL is considered dyslipidemia. High levels of LDL cholesterol increase the risk of angina pectoris, heart attack, and stroke. The main control points can be exercise, eating habits, and medications are effective.

In addition, the type of data may be a result of a national health examination, the subject of extraction may be consent to provide information to a third party, the region may be Seoul, the gender may be male, and the age group may be 30s to 40s.

In addition, the name of the disease is endocrine system/metabolic disease (hyperlipidemia), the main factor is total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride disease, the number of cases is 100, and the validity period of the data is 1 year (after 1 year) repurchase or data destruction).

The purchaser can grasp at a glance the health status of a large number of people suspected of having a disease or onset through 22 major factors of the national health checkup results provided by the sales unit 29 .

10 is a block diagram of a reward payment process by the reward payment unit 30.

Referring to FIG. 10 , the reward payment unit 30 may provide different points to the user terminal 10 for each health examination result, prescription, health report, and health guide data.

Specifically, the reward payment unit 30 may provide high points to the user terminal 10 in the order of health guide, health report, prescription, and health examination result data.

For example, the reward payment unit 30 provides the user terminal 10 with 1000 points for health examination result data, 1200 points for prescription data, 2000 points for health report data, and 2500 points for health guide data, respectively. can provide

In addition, the reward payment unit 30 issues receipts indicating the date and time of transaction, type of data, demand destination, consenter, and points for the plurality of user terminals 10 corresponding to the plurality of data sold by the sales unit 29. do.

Then, the reward payment unit 30 provides points to a plurality of user terminals 10 corresponding to the plurality of data sold by the sales unit 29 and provides corresponding receipts.

At this time, the reward payment unit 30 gives points to a plurality of user terminals 10 whenever a plurality of data is sold by the sales unit 29, regardless of the number of purchases of buyers registered in the information providing platform 40. each can be paid.

11 is a configuration diagram of the point confirmation unit 12 of the user terminal 10.

Referring to FIGS. 3 and 11 , the user terminal 10 may further include a point confirmation unit 12 and an additional point payment unit.

First, the point confirmation unit 12 is paid by the reward payment unit 30 and can check usable points and receipts.

12 is a configuration diagram of a point shop, and FIG. 13 is a configuration diagram of a digital voucher.

Referring to FIGS. 11 to 13 , the point confirmation unit 12 may be connected to a point shop and a digital voucher.

Here, the point shop refers to a purchase site where a data provider can purchase a desired gifticon by utilizing points available in the point confirmation unit 12 .

In addition, the digital pouch refers to currency that can be used in the same way as cash at affiliate sites in the region by being linked with local currency.

Further, the additional point payment unit 13 additionally provides a small amount of points to the user when the user logs in to the user terminal 10 .

For example, the additional point payment unit 13 may additionally provide 100 points to the user terminal 10 whenever the user logs in to the user terminal 10 .

In the present invention, when the user logs in, the user can log in through the additionally provided small amount points and motivate the user to periodically provide medical data.

On the other hand, the information providing platform 40 may be configured to further include a data confirmation unit 43.

At this time, the data confirmation unit 43 can check a plurality of data provided by the sales unit 29 of the platform server 20 .

On the other hand, the download and rights period of a plurality of data provided by the sales unit 29 is set to a pre-specified period.

In addition, the sales unit 29 may restrict access rights to a plurality of data for a specific buyer registered in the information providing platform 40 when the plurality of data is downloaded and the right period elapses.

For example, the download and right period of data provided by the sales unit 29 is set to 1 year, and after 1 year, the sales unit 29 may restrict access to a plurality of data.

14 is a block diagram of a buyer registration process by the buyer registration unit 45 .

Referring to FIG. 14 , the information providing platform 40 may further include a buyer registration unit 45 .

First, the purchaser registration unit 45 inputs information about the purchaser.

Specifically, the purchaser registration unit 45 inputs and processes items selected from among insurance companies, financial companies, pharmaceutical companies, AI-related educational institutions, and public institutions.

And, the purchaser registration unit 45 inputs and processes whether life insurance or non-life insurance is handled and whether insurance or financial products are recommended to the general public.

15 is a data flow diagram between the extraction unit 27, the sales unit 29, the advertisement unit 31, the target selection unit 32, the marketing unit 33, and the cost calculation unit 34.

Referring to FIG. 15 , the platform server 20 may further include an advertising unit 31, a target selection unit 32, a marketing unit 33, and a cost calculation unit 34.

First, the advertisement unit 31 provides the information providing platform 40 with respect to a plurality of data registered in the information providing platform 40 by the registration unit 26 through a notification service such as a text message, a voice message, or an image. Perform advertising and publicity work respectively.

In addition, the subject selection unit 32 classifies a plurality of data processed under pseudonymization by the pseudonymization unit 25 according to symptoms of the disease, and selects a plurality of patients with the disease according to a predetermined criterion.

Further, the marketing unit 33 performs marketing for a specific purchaser registered in the information providing platform 40 based on the information on a plurality of disease patients selected by the target selection unit 32 .

Then, the cost calculation unit 34 calculates various costs for the plurality of data extracted by the extraction unit 27.

On the other hand, the subject selection unit 32 classifies a plurality of patients with severe diseases, mild diseases, and suspected diseases, respectively, based on the plurality of health reports generated by the analysis unit 22 .

In addition, the target selection unit 32 selects a plurality of diseased patients suitable for a predetermined disease, age group, and gender criteria from among a plurality of diseased patients classified according to symptoms of the disease.

16 is a flowchart of a marketing process by the marketing unit 33.

Referring to FIG. 16, the marketing unit 33 recommends specific buyers handling life insurance or non-life insurance and insurance or financial products among the buyers registered in the buyer register 45 of the information providing platform 40 to the general public. Select each specific buyer.

In addition, when a specific buyer registered in the purchaser register 45 handles life insurance or non-life insurance, the marketing unit 33 sends information to a specific buyer registered in the information providing platform 40 based on information on a number of severely ill patients. do marketing for

In addition, when a specific purchaser registered in the purchaser register 45 recommends an insurance or financial product to the general public, the marketing unit 33 recommends the information of a person with a mild disease such as high blood pressure or diabetes and a person suspected of having a specific disease to the general public. Marketing is performed for a specific buyer registered in the information providing platform 40 .

17 is a flow chart of the overall cost calculation process by the cost calculation unit 34.

Referring to FIG. 17, the cost calculation unit 34 has a first weight value and a second weight value set in advance for processing cost, reward cost, advertisement promotion cost, and service cost calculated for a plurality of data extracted by the extraction unit 27. , the third weight and the fourth weight are multiplied and summed to calculate overall costs.

Here, the reward ratio means a compensation expense provided to the data provider. And, the advertising publicity cost refers to the expenses required for the advertising unit 31 to perform advertising and publicity.

In addition, the service fee refers to expenses for a plurality of services provided within the platform server 20 .

And, the sum of the first weight, the second weight, the third weight, and the fourth weight is set to 100%.

In addition, the first weight, the second weight, the third weight, and the fourth weight are set to be larger in the order of the fourth weight, the first weight, the third weight, and the second weight.

For example, the first weight may be 30%, the second weight may be 10%, the third weight may be 20%, and the fourth weight may be 40%.

In addition, the cost of the data includes an insurance connection fee and a target selection fee.

At this time, the insurance linkage fee refers to an expense set according to the specific insurance when linking a specific insurance company or financial company to the information providing platform 40 .

And, the target selection cost refers to the screening cost for a patient with a specific disease selected by the target selection unit 32 .

Meanwhile, the sales unit 29 may provide the overall cost calculated by the cost calculation unit 34 to the data confirmation unit 43 of the information providing platform 40 .

14 is a block diagram of a buyer registration process by a buyer registration unit.

Referring to FIG. 14 , the information providing platform may further include a buyer registration unit.

First, the buyer registration unit inputs and processes information about a buyer.

Specifically, the purchaser register inputs and processes items selected from insurance companies, financial companies, pharmaceutical companies, AI-related educational institutions, and public institutions.

And, the purchaser registration unit inputs and processes whether life insurance or non-life insurance is handled and whether insurance or financial products are recommended to the general public.

15 is a data flow diagram among an extraction unit, a sales unit, an advertising unit, a target selection unit, a marketing unit, and a cost calculation unit.

Referring to FIG. 15 , the platform server may further include an advertising unit , a target selection unit , a marketing unit, and a cost calculation unit.

First, the advertising unit performs advertising and publicity tasks through a text message, voice message, or notification service such as an image to the information providing platform for a plurality of data registered in the information providing platform by the registration unit.

In addition, the target selection unit classifies a plurality of data pseudonymized by the pseudonymization unit according to symptoms of the disease, and selects a plurality of patients with the disease according to a predetermined criterion.

Further, the marketing unit performs marketing for a specific purchaser registered in the information providing platform based on the information on a plurality of disease patients selected by the target selection unit.

And, the cost calculation unit calculates various costs for the plurality of data extracted by the extraction unit.

On the other hand, the subject selection unit classifies a plurality of patients with severe diseases, mild diseases, and suspected diseases, respectively, based on the plurality of health reports generated by the analysis unit.

Then, the target selection unit selects a plurality of diseased patients suitable for a predetermined standard of disease, age, and gender from among a plurality of diseased patients classified according to symptoms of the disease.

16 is a flowchart of a marketing process by a marketing unit.

Referring to FIG. 16 , the marketing unit selects specific buyers who handle life insurance or non-life insurance and specific buyers who recommend insurance or financial products to the general public from among buyers registered in the buyer register of the information providing platform.

In addition, the marketing unit performs marketing for a specific purchaser registered in the information providing platform based on a number of severely ill patients' information when a specific purchaser registered in the purchaser's register handles life insurance or non-life insurance.

In addition, the marketing department recommends insurance or financial products to the general public when a specific buyer registered in the buyer's register recommends insurance or financial products to the general public, based on the information of patients with mild diseases such as high blood pressure and diabetes and those suspected of having specific diseases. Marketing to buyers.

17 is a flow chart of the overall cost calculation process by the cost calculation unit.

Referring to FIG. 17, the cost calculation unit has a first weight value, a second weight value, a third weight value, and a fourth weight value set in advance to the processing cost, reward cost, advertisement promotion cost, and service cost calculated for the plurality of data extracted by the extraction unit. After multiplying each of the weights, they are summed to calculate the overall cost.

Here, the reward ratio means a compensation expense provided to the data provider. And, the advertising publicity cost refers to the expenses required for the advertising department to perform advertising and publicity.

In addition, the service fee refers to expenses for a number of services provided within the platform server.

And, the sum of the first weight, the second weight, the third weight, and the fourth weight is set to 100%.

In addition, the first weight, the second weight, the third weight, and the fourth weight are set to be larger in the order of the fourth weight, the first weight, the third weight, and the second weight.

For example, the first weight may be 30%, the second weight may be 10%, the third weight may be 20%, and the fourth weight may be 40%.

In addition, the cost of the data includes an insurance connection fee and a target selection fee.

In this case, the insurance connection fee refers to an expense set according to the specific insurance when linking a specific insurance company or financial company to the information providing platform.

And, the target selection cost refers to the screening cost for a patient with a specific disease selected by the target selection unit.

Meanwhile, the sales unit may provide the overall cost calculated by the cost calculation unit to the data checking unit of the information providing platform.

Next, a method of selling medical data (S200) according to the present invention will be described.

18 is a flowchart of steps S201 to S207 in the method for selling medical data according to the present invention.

Referring to FIG. 18, the collection unit 21 of the platform server 20 collects personal information, health checkup results, and medical data including prescriptions of a plurality of data providers provided by a plurality of user terminals 10, respectively. .(S201)

After that, the analysis unit 22 of the platform server 20 analyzes each of the plurality of health examination result data collected in step S201 through AI, and generates a plurality of health reports and health guide data, respectively. (S202)

At this time, the plurality of personal information and medical data collected in step S201 and the plurality of health reports and health guide data generated in step S202 are stored in the storage unit 23 of the platform server 20, respectively.

After that, the processing unit 24 of the platform server 20 processes a plurality of medical data stored in the storage unit 23, respectively. (S203)

Thereafter, the pseudonymization processing unit 25 of the platform server 20 performs pseudonymization on the plurality of data processed in step S203 so that personal information cannot be identified. (S204)

Thereafter, the advertisement unit 31 performs advertising and promotion tasks through notification services such as text messages, voice messages, or images to the information providing platform 40 based on the plurality of pseudonymized data in step S204. Perform (S205)

Thereafter, the subject selection unit 32 classifies the plurality of data pseudonymized in step S204 according to symptoms of the disease, and selects a plurality of patients with the disease according to a predetermined criterion (S206).

Thereafter, the marketing unit 33 performs marketing for a specific purchaser registered in the information providing platform 40 based on the information on the plurality of disease patients selected in step S206. (S207)

19 is a flowchart of steps S208 to S214 in the method for selling medical data according to the present invention.

Referring to FIG. 19, after that, the purchase application unit 42 of the information providing platform 40 applies for purchase to the sales unit 29 of the platform server 20 through the purchase application form. (S208)

Thereafter, the extraction unit 27 of the platform server 20 extracts a plurality of data according to the purchase conditions and symptoms input and processed in step S208 from the plurality of disease patient information selected in step S206. (S209)

After that, the cost calculation unit 34 calculates various costs for the plurality of data extracted in step S209. (S210)

After that, the sales unit 29 provides each of the various costs calculated in step S210 and a plurality of data extracted in step S209 to the data confirmation unit 43 of the information providing platform 40. (S211)

After that, the data confirmation unit 43 of the information providing platform 40 displays the various costs and a plurality of data provided in step S211, respectively. (S212)

After that, the reward payment unit 30 of the platform server 20 provides points to the point confirmation unit 12 of the plurality of user terminals 10 corresponding to the plurality of data sold in step S212, respectively, and the points Receipts corresponding to each are provided. (S213)

After that, the point confirmation unit 12 of the user terminal 10 displays the points and receipts provided in step S213 so that the data provider can recognize them. (S214)

Next, the analysis unit 22 of the platform server 20 analyzes the health examination result data and generates the health report and health guide data (S202) as follows.

Figure 20 is a flow chart for the health checkup result analysis, health report and health guide generation process (S202).

Referring to FIG. 20, the analysis unit 22 analyzes each of the plurality of health checkup result data collected in step S201 through AI, and provides a number of diseases including a plurality of predictable disease information according to region, age group, and gender. Each health report data is generated. (S202-1)

After that, the analysis unit 22 analyzes the plurality of disease information included in the plurality of health report data generated in step S202-1, respectively, and provides a plurality of health guide data including opinions on exercise or diet, respectively. Create. (S202-2)

Next, the process of processing medical data by the processing unit 24 (S203) is as follows.

21 is a flowchart of a process of processing medical data (S203).

Referring to FIG. 21, the processing unit 24 analyzes 22 major factors of the national health examination result data and classifies them by disease. (S203-1)

In this case, the disease may include obesity, hypertension, anemia, diabetes, dyslipidemia, chronic kidney disease, liver disease, pulmonary tuberculosis, and chest disease.

Then, the processing unit 24 classifies the multiple diseases classified in step S203-1 into each patient based on the number of suspected patients. (S203-2)

Then, the processing unit 24 classifies the multiple patients classified in step S203-2 into age group, region, and gender based on the personal information provided from the user terminal 10 (S203-3).

Next, the disease patient selection process (S206) by the target selection unit 32 is as follows.

22 is a flow chart for the disease patient selection process (S206).

Referring to FIG. 22, the subject selection unit 32 classifies a plurality of patients with severe diseases, those with mild diseases, and suspected diseases, respectively, based on the plurality of health reports generated in step S202. (S206-1)

In addition, the subject selection unit 32 selects a plurality of diseased patients suitable for the criteria of the disease, age group, and gender set in advance from among the plurality of diseased patients classified by symptom of the disease in step S206-1 (S206-2).

Next, the marketing execution process (S207) by the marketing unit 33 is as follows.

23 is a flowchart for the marketing process 207.

Referring to FIG. 23, the purchaser registration unit 45 of the information providing platform 40 inputs and processes purchaser information selected from among insurance companies, financial companies, pharmaceutical companies, AI-related educational institutions, and public institutions. (S207-1)

After that, the purchaser registration unit 45 inputs and processes whether life insurance or non-life insurance is handled and whether insurance or financial products are recommended. (S207-2)

After that, the marketing unit 33 selects a specific buyer who handles life insurance or non-life insurance and a specific buyer who recommends insurance or financial products to the public from among the buyers input processed in step S207-2. (S207- 3)

Thereafter, the marketing unit 33 performs marketing for a specific purchaser who handles life insurance or non-life insurance among the specific purchasers selected in step S207-3 by using information on a number of patients with severe diseases (S207-4).

Then, the marketing unit 33 performs marketing for a specific purchaser who recommends insurance or financial products to the general public among the specific purchasers selected in step S207-3 using information on patients with mild diseases and suspected patients. (S207- 5)

Next, the purchase request process (S208) by the purchase request unit 42 is as follows.

24 is a flowchart of a purchase request process (S208).

Referring to FIG. 24 , the purchase application unit 42 inputs disease names, regions, age groups, and genders of a plurality of data to be purchased as purchase conditions into the purchase application form (S208-1).

After that, the purchase application unit 42 inputs and processes one or more symptoms selected from severe symptoms, mild symptoms, and suspected disease into the purchase application form (S208-2).

After that, the purchase application unit 42 inputs and processes the type and quantity of data selected from one or more of the health checkup result, prescription, and health report into the purchase application, respectively (S208-3).

Next, the overall cost calculation step (S210) by the cost calculation unit 34 is as follows.

25 is a flowchart of the overall cost calculation process (S210).

Referring to FIG. 25 , the cost calculation unit 34 includes a first weight, a second weight, and a third weight previously set to processing costs, reward costs, advertising and publicity costs, and service costs calculated for a plurality of data extracted in step S209. and the fourth weight, respectively, and then summed. (S210-1)

After that, the cost calculation unit 34 calculates insurance linkage costs and target selection costs, respectively (S210-2).

Thereafter, the cost calculation unit 34 calculates overall costs by adding the insurance linkage cost and target selection cost calculated in step S210-2 to the values summed in step S210-1. (S210-3)

Next, a step (S211) in which the sales unit 29 provides various costs and a plurality of data to the data checking unit 43 is as follows.

26 is a flow chart of the process of providing various costs and data (S211).

Referring to FIG. 26, the sales unit 29 determines the title of the data, description content, data type, extraction target, region name, gender, age group, disease name, major factors, and data for a plurality of data extracted in step S209. The quantity and expiration date of the data are described, respectively, and detailed data is generated (S211-1).

After that, the sales unit 29 provides the various costs calculated in step S210 to the data confirmation unit 43 of the information providing platform 40. (S211-2)

After that, the sales unit 29 adds the detailed data generated in step S211-1 to the plurality of data extracted in step S209 and provides it to the data confirmation unit 43 of the information providing platform 40. (S211- 3)

Next, the process of point payment and receipt provision by the reward payment unit 30 (S213) is as follows.

27 is a flowchart of a point payment and receipt provision process (S213).

Referring to FIG. 27, the reward payment unit 30 has high points in the order of health guide, health report, prescription and health examination result data for the plurality of user terminals 10 corresponding to the plurality of data sold in step S211. is given. (S213-1)

Thereafter, the reward payment unit 30 issues receipts displaying the date and time of transaction, type of data, consumer, consenter, and points to the plurality of user terminals 10 to which points are assigned in step S213-1. (S213-1) -2)

Thereafter, the reward payment unit 30 provides points to the point confirmation unit 12 of the plurality of user terminals 10 for which receipts were issued in step S213-2, and provides the corresponding receipt. (S213-3)

Next, the process of displaying points and receipts by the point confirmation unit 12 (S214) is as follows.

28 is a flowchart of a point and receipt display process (S214).

Referring to FIG. 28, the additional point payment unit 13 grants a small amount of points to the user terminal 10 that has gone through a log-in process. (S214-1)

After that, the point confirmation unit 12 adds up the points provided in step S213 and the small amount of points granted in step S214-1. (S214-2)

After that, the point confirmation unit 12 displays the summed points and receipts in step S214-2. (S214-3)

After that, the point confirmation unit 12 of the user terminal 10 displays the point shop and digital voucher shortcut icons. (S214-4)

Here, the point shop refers to a purchase site where a data provider can purchase a desired gifticon by utilizing points available in the point confirmation unit 12 .

And, thereafter, the digital pouch is linked to the local currency and means a currency that can be used the same as cash at affiliate sites in the region.

The method of selling medical data for a specific purchaser according to the present invention processes and pseudonyms a plurality of medical data collected with the consent of a plurality of data providers, and provides them to a specific purchaser such as an insurance company or a financial company, thereby predicting disease of a plurality of medical data , new drug development, medical image analysis, etc., it has the effect of contributing to related industries.

In addition, the method of selling medical data for a specific purchaser according to the present invention selects a specific purchaser, such as an insurance company, a financial company, or a pharmaceutical company, and provides the specific purchaser with disease patient information for each symptom, such as severe, mild, and suspected disease, to the specific purchaser. There is an effect of providing a large number of medical data suitable for the user's taste in a timely manner.

In addition, the method for selling medical data according to the present invention calculates processing cost, reward cost, advertising cost, service cost, insurance linkage cost, and target selection cost according to pre-set criteria for a plurality of disease patient information for each symptom for a specific purchaser, respectively, and weights them. Therefore, it is possible to provide a large number of medical data to a specific buyer transparently and at a reasonable price.

5: Medical data sales platform 10: User terminal
11: input unit 12: point confirmation unit
13: additional point payment unit 20: platform server
21: collection unit 22: analysis unit
23: storage unit 24: processing unit
25: pseudonym processing unit 26: registration unit
27: extraction unit 28: sales price calculation unit
29: sales department 30: reward payment department
31: advertising unit 32: target selection unit
33: marketing department 34: cost calculation unit
40: information provision platform 41: list confirmation unit
42: purchase application unit 43: data confirmation unit
45: buyer register

Claims (9)

In the method of selling medical data for a specific buyer,
The method of selling medical data for the specific buyer
Step 201 of collecting, by the collection unit 21 of the platform server 20, medical data including personal information, health examination results, and prescriptions of a plurality of data providers provided by a plurality of user terminals 10, respectively;
Step 202, in which the analyzer 22 of the platform server 20 analyzes the plurality of health examination result data collected in step 201 through AI, and generates a plurality of health reports and health guide data, respectively;
Step 203, wherein the processing unit 24 of the platform server 20 processes a plurality of medical data, respectively;
Step 204, whereby the pseudonymization processing unit 25 of the platform server 20 performs pseudonymization on the plurality of data processed in step 203 so that personal information cannot be identified;
Based on the plurality of data pseudonymized in step 204, the advertising unit 31 of the platform server 20 provides text messages, voice messages, and image notification services to the information providing platform 40 to advertise and publicize. Step 205, each task is performed;
Step 206, in which the subject selection unit 32 of the platform server 20 classifies the plurality of data pseudonymized in step 204 according to symptoms of the disease, and selects a plurality of patients with the disease according to a predetermined standard;
a step 207 in which the marketing unit 33 of the platform server 20 performs marketing for a specific purchaser registered in the information providing platform 40 based on the plurality of disease patient information selected in step 206;
Step 208 of the purchase application unit 42 of the information providing platform 40 requesting a purchase from the sales unit 29 of the platform server 20 through the purchase application form;
Step 209, in which the extraction unit 27 of the platform server 20 extracts a plurality of pieces of data according to the purchase conditions and symptoms input and processed in Step 208 from the plurality of information on patients with diseases selected in Step 206;
Step 210, wherein the cost calculator 34 of the platform server 20 calculates various costs for the plurality of data extracted in step S209;
Step 211 of the sales unit 29 providing the various costs calculated in step 210 and a plurality of data extracted in step 209 to the data check unit 43 of the information providing platform 40, respectively;
Step 212, wherein the data confirmation unit 43 displays the overall cost and a plurality of data provided in Step 211, respectively;
The reward payment unit 30 of the platform server 20 provides points to the point confirmation unit 12 of the plurality of user terminals 10 corresponding to the plurality of data sold in step 211, respectively, and the points Step 213 of providing receipts corresponding to each; and
Step 214 of displaying the points and receipts provided in step 213 so that the point confirmation unit 12 of the user terminal 10 can recognize the data provider;
The 207th step is
Step 207-1 of inputting and processing purchaser information selected from among insurance companies, financial companies, pharmaceutical companies, AI-related educational institutions and public institutions by the buyer registration unit 45 of the information providing platform 40;
Step 207-2, in which the purchaser registration unit 45 inputs and processes whether life insurance or non-life insurance is handled and whether insurance or financial products are recommended;
207-3, in which the marketing unit 33 selects a specific buyer who handles life insurance or non-life insurance and a specific buyer who recommends insurance or financial products to the general public from among the buyers input processed in step 207-2. step;
a step 207-4 in which the marketing unit 33 performs marketing for a specific purchaser who handles life insurance or non-life insurance among the specific purchasers selected in the step 207-3 by using a plurality of severely ill patient information; and
207-th, in which the marketing unit 33 performs marketing for a specific purchaser who recommends insurance or financial products to the general public among the specific buyers selected in step 207-3 by using information on patients with mild diseases and suspected patients. step 5; including;
Step 208 is
Step 208-1 of inputting and processing disease names, regions, age groups, and genders of a plurality of data that the purchase application unit 42 wants to purchase as purchase conditions into the purchase application form;
step 208-2, in which the purchase application unit 42 inputs and processes one or more selected symptoms from severe symptoms, mild symptoms, and suspected disease into the purchase application form; and
A step 208-3 in which the purchase application unit 42 inputs and processes the type and quantity of data selected from one or more of the health checkup result, prescription, and health report into the purchase application, respectively,
Step 210 is
The cost calculation unit 34 calculates the processing cost, reward cost, advertisement promotion cost, and service cost for the plurality of data extracted in step 209 with first weights, second weights, third weights, and fourth weights set in advance. Step 210-1 of multiplying the weights and summing them;
a step 210-2 in which the cost calculation unit 34 calculates an insurance connection fee and a target selection fee; and
Step 210-3, wherein the cost calculation unit 34 calculates overall costs by adding the insurance linkage cost and target selection cost calculated in step 210-2 to the value added in step 210-1 including;
The reimbursement fee
Compensation expenses provided to data providers,
Advertising and publicity expenses
The advertising unit 31 is the cost required to perform advertising and publicity,
The service fee
Expenses for a number of services provided within the platform server 20,
The sum of the first weight, the second weight, the third weight and the fourth weight is
set to 100%,
The magnitudes of the first weight, the second weight, the third weight and the fourth weight are
The fourth weight, the first weight, the third weight, and the second weight are set to be large in the order,
The insurance linkage fee
When the information providing platform 40 is linked to a specific insurance company or financial company, it is an expense determined according to the specific insurance,
The target selection fee
A method of selling medical data for a specific purchaser, characterized in that the cost of screening for a patient with a specific disease selected by the target selection unit (32). According to claim 1,
The 202nd step is
The analyzer 22 analyzes each of the plurality of health examination result data collected in step 201 through the AI, and reports a plurality of health reports including a plurality of predictable disease information according to region, age group, and gender. Step 202-1 of generating data respectively; and
The analyzer 22 analyzes each of the plurality of disease information included in the plurality of health report data generated in step 202-1, and provides a plurality of health guide data including opinions such as exercise or diet, respectively. Including; step 202-2 of generating;
The 203rd step is
Step 203-1, in which the processing unit 24 analyzes 22 major factors of the national health examination result data and classifies them by disease;
Step 203-2, in which the processing unit 24 classifies the plurality of diseases classified in step 203-1 into individual patients based on the number of patients suspected of having the disease; and
A 203-3 step of classifying, by the processing unit 24, the plurality of patients classified in the 203-2 step into age groups, regions, and genders based on the personal information provided from the user terminal 10; do,
the disease is
A method of selling medical data for a specific purchaser, characterized in that it includes obesity, hypertension, anemia, diabetes, dyslipidemia, chronic kidney disease, liver disease, pulmonary tuberculosis, and chest disease. According to claim 1,
Step 206 is
Step 206-1, in which the subject selection unit 32 classifies a plurality of patients with severe diseases, patients with mild diseases, and suspected diseases, respectively, based on the plurality of health reports generated in step 202; and
a step 206-2 in which the target selection unit 32 selects a plurality of patients with diseases suitable for criteria of a disease, age group, and gender set in advance from among the plurality of patients classified according to symptoms of the disease in step 206-1; A method of selling medical data for a specific buyer, characterized in that. delete delete According to claim 1,
Step 211 is
For the plurality of data extracted in step 209, the sales unit 29 determines the title of the data, the description, the type of data, the extraction target, the name of the region, the gender, the age group, the name of the disease, the main factor, the quantity of the data, and the data. a step 211-1 of generating detailed data by describing each effective period;
a step 211-2 in which the sales unit 29 provides the various costs calculated in the step 210 to the data confirmation unit 43 of the information providing platform 40; and
211-3 step of adding the detailed data generated in step 211-1 to the plurality of data extracted in step 209 by the sales unit 29 and providing the data to the data verification unit 43; A method of selling medical data for a specific buyer, characterized in that. According to claim 1,
Step 213 is
The reward payment unit 30 gives high points to the plurality of user terminals 10 corresponding to the plurality of data sold in step 211 in the order of health guide, health report, prescription, and health checkup result data. Step 213-1;
In step 213-1, the reward payment unit 30 issues receipts displaying the date and time of transaction, type of data, demand destination, consenter, and points for the plurality of user terminals 10 to which points are assigned in step 213-1. Step 2; and
a step 213-3 in which the reward payment unit 30 provides points to the point confirmation unit 12 of the plurality of user terminals 10 for which the receipts were issued in the step 213-2, and provides corresponding receipts; A method of selling medical data for a specific purchaser, comprising: According to claim 1,
The 214th step is
Step 214-1, wherein the additional point payment unit 13 of the user terminal 10 grants a small amount of points to the user terminal 10 that has gone through a log-in process;
a step 214-2 in which the point confirmation unit 12 adds up the points provided in step 213 and the small amount of points granted in step 214-1;
Step 214-3, wherein the point confirmation unit 12 displays the summed points and receipts in Step 214-2, respectively; and
A method of selling medical data for a specific purchaser, characterized in that it comprises a; step 214-4, wherein the point confirmation unit 12 displays a point shop and a digital voucher shortcut icon. According to claim 8,
The point shop
It is a purchase site where a data provider can purchase a desired gifticon by using the points available in the point confirmation unit 12;
The digital voucher
A method of selling medical data for a specific purchaser, characterized in that the currency is linked to the local currency and can be used as cash at affiliate sites in the region.

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