KR102501899B1 - Method for selling medical data - Google Patents

Abstract

The present invention comprises: a 101 step; a 102 step; a 103 step; a 104 step; a 105 step; a 106 step; a 107 step; a 108 step; a 109 step; a 110 step; a 111 step; a 112 step; and a 113 step. Therefore, the present invention is capable of having an effect of securing good quality and excellent medical data.

Description

Method for selling medical data}

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, to be used by pharmaceutical companies, research institutes, public institutions, healthcare companies, insurance companies, financial companies, etc. It relates to a method of selling medical data that can contribute to related industries by providing a lot of medical data to disease prediction, new drug development, and medical image analysis by providing them to consumers.

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 made 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 pharmaceutical companies, research institutes, public institutions, and healthcare companies It is to provide a method of selling medical data that can contribute to related industries by utilizing a large number of medical data for disease prediction, new drug development, medical image analysis, etc.

In addition, an object of the present invention is to provide a method for selling medical data that can provide benefits through rewards such as points to a plurality of data providers corresponding to a plurality of sales data when selling medical data to a plurality of consumers.

In addition, an object of the present invention is to analyze a plurality of health checkup result data through AI, respectively, and provide a plurality of generated health reports and health guides to a plurality of consumers, respectively, so that the health checkup results, It is to provide a method of selling medical data that can utilize health report and health guide data in various ways in the medical and health industries.

In order to solve the above technical problems, the method for selling medical data according to the present invention provides personal information and personal information of a plurality of data providers provided by a plurality of user terminals Step 101 of collecting medical data including health checkup results and prescriptions, the analyzer 22 of the platform server 20 analyzes each of the plurality of health checkup result data collected in step 101 through AI Step 102 of generating a plurality of health reports and health guide data respectively, Step 103 of processing a plurality of medical data by the processing unit 24 of the platform server 20, respectively, of the platform server 20 A 104th step in which the pseudonym processing unit 25 performs pseudonymization processing so that personal information cannot be identified for the plurality of data processed in the step 103, and the registration unit 26 of the platform server 20 Step 105 of registering a plurality of pseudonymized data in the information providing platform 40 according to the number of data, region, age group, and gender, list check unit 41 of the information providing platform 40 Step 106 of displaying a plurality of data registered in step 105, and the purchase application unit 42 of the information providing platform 40 submits a purchase application based on the plurality of data displayed in step 106. Step 107 of requesting a purchase from the sales unit 29 of the platform server 20 through the step 107, the extraction unit 27 of the platform server 20 from the plurality of pseudonymized data in the step 104 Step 108 of extracting a plurality of data according to the purchase condition input and processed in the step 108, the selling price calculation unit 28 of the platform server 20 sets a reference unit price in advance for the plurality of data extracted in step 108, and Step 109 of calculating a selling price by multiplying and summing the quantities written in the purchase application form, the selling price calculated in step 109 by the sales unit 29 and step 108 Step 110 of providing a plurality of data extracted from the data to the data checking unit 43 of the information providing platform 40, respectively. In step 111, the reward payment unit 30 of the platform server 20 displays points to the point confirmation unit 12 of the plurality of user terminals 10 corresponding to the plurality of data sold in step 110. A step 112 of providing a receipt corresponding to the point and the point confirmation unit 12 of the user terminal 10 respectively providing points and receipts provided in step 112 so that the data provider can recognize them. It is characterized in that it includes a 113th step of displaying.

In addition, in step 102, the analyzer 22 analyzes the plurality of health examination result data collected in step 101 through the AI, and provides predictable disease information according to region, age group, and gender. A 102-1 step of generating a plurality of health report data including a , and the analyzer 22 analyzes a plurality of disease information included in the plurality of health report data generated in the 102-1 step, respectively, , a step 102-2 of generating a plurality of health guide data including opinions such as exercise or diet, and in step 103, the processing unit 24 is the main factor of the national health examination result data 22 Step 103-1 of analyzing branches and classifying them by disease; Step 103-1 of classifying a plurality of diseases classified in step 103-1 by the processing unit 24 by patient based on the number of patients suspected of having the disease Step 103: Step -2 and the processing unit 24 classifies the number of patients classified in step 103-2 into age groups, regions, and genders based on personal information provided from a plurality of user terminals 10 It includes -3 stages, and the diseases are characterized in that they include obesity, hypertension, anemia, diabetes, dyslipidemia, chronic kidney disease, liver disease, pulmonary tuberculosis, and chest disease.

In addition, in step 107, 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 a purchase condition in the purchase application form. The application unit 42 inputs and processes at least one selected data from among the health checkup results, prescriptions, and health reports suitable for the purchase conditions input and processed in step 107-1 and the quantity of the corresponding data into the purchase application, respectively. Step 107-2 and a step 107-3 in which the purchase application unit 42 inputs and processes purchaser information selected from among AI-related educational institutions, pharmaceutical companies, insurance companies, financial companies, and public institutions into the purchase application form; In step 110, for the plurality of data extracted in step 108, the sales unit 29 determines the title of data, description content, type of data, subject to be extracted, name of region, gender, age group, name of disease, major factors, and data. Step 110-1 of generating detailed data by describing the quantity and expiration date of data, and the sales unit 29 converts the sales price calculated in step 109 to the data confirmation unit 43 of the information providing platform 40 ) and the sales unit 29 adds the detailed data generated in the step 110-1 to the plurality of data extracted in the step 108, and the data confirmation unit 43 It is characterized in that it comprises a step 110-3 providing.

Further, in step 112, the reward payment unit 30 collects 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 110. Step 112-1 of assigning high points in order, the reward payment unit 30 determines the date and time of transaction, type of data, destination, Step 112-2 of issuing a receipt displaying the consenter and the points, and the reward payment unit 30 sends a message to the point confirmation unit 12 of the plurality of user terminals 10 where the receipts were issued in the step 112-2. It is characterized by including a step 112-3 of providing points and providing a corresponding receipt.

In addition, step 113 is step 113-1 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 113-2 of (12) summing up the points provided in step 112 and the small amount of points granted in step 113-1; It is characterized in that it includes a step 113-3 of displaying points and receipts, respectively, and a step 113-4 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 for selling medical data 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 plurality of demanders such as pharmaceutical companies, research institutes, public institutions, healthcare companies, insurance companies, and financial companies. , There is an effect that 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, the method of selling medical data according to the present invention provides points that can be used like cash to a plurality of data providers when selling medical data to a plurality of consumers, so that the data provider is continuously synchronized to upload a plurality of medical data. By giving, there is an effect of securing excellent medical data of good quality.

In addition, the method for selling medical data according to the present invention analyzes a plurality of health checkup result data through AI and provides a plurality of generated health reports and health guides to a plurality of consumers, respectively. It has the effect of utilizing health checkup results, health reports, and health guide data in various ways in the medical and health industries.

1 is a block diagram of a medical data sales platform according to the present invention.
2 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 flowchart of steps S101 to S107 in the method for selling medical data according to the present invention.
15 is a flowchart of steps S108 to S113 in the method for selling medical data according to the present invention.
Figure 16 is a flow chart for the health checkup result analysis, health report and health guide generation process (S102).
17 is a flowchart of a process of processing medical data (S103).
18 is a flowchart of a purchase request process (S107).
19 is a flowchart of a process of providing selling price and data (S110).
20 is a flowchart of a point payment and receipt provision process (S112).
21 is a flowchart of a point and receipt display process (S113).

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.

2 is a configuration diagram of the user terminal 10.

Referring to FIG. 2 , the 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 sugar (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 Service.

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.

In addition, buyer information may be input and processed in the purchase application form.

At this time, the purchaser information may include AI-related educational institutions, pharmaceutical companies, insurance companies, financial companies, and public institutions.

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 "total cholesterol is a level that includes HDL, LDL, and triglycerides. Generally, more than 240 mg/dL is considered dyslipidemia. High LDL cholesterol levels increase the risk, so angina, It causes heart attacks, strokes, etc. The main management 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, disease name is disease: endocrine system/metabolic disease (hyperlipidemia), the main factor is total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride disease Suspected level or higher, the number of data is 100 cases, the validity period of data is 1 year (1 year) repurchase after one year 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.

Next, a method of selling medical data (S100) according to the present invention will be described.

14 is a flowchart of steps S101 to S107 in the method for selling medical data according to the present invention.

Referring to FIG. 14, the collection unit 21 of the platform server 20 collects personal information of a plurality of data providers provided by a plurality of user terminals 10, health examination results, and medical data including prescriptions, respectively. .(S101)

After that, the analysis unit 22 of the platform server 20 analyzes each of the plurality of health examination result data collected in step S101 through AI, and generates a plurality of health reports and health guide data, respectively. (S102)

At this time, the plurality of personal information and medical data collected in step S101 and the plurality of health reports and health guide data generated in step S102 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. (S103)

Thereafter, the pseudonymization processing unit 25 of the platform server 20 performs pseudonymization on the plurality of data processed in step S103 so that personal information cannot be identified. (S104)

After that, the registration unit 26 of the platform server 20 registers a plurality of pseudonymized data in step S104 in the information providing platform 40 according to the number of data, region, age group, and gender. (S105 )

After that, the list checking unit 41 of the information providing platform 40 displays a plurality of data registered in step S105. (S106)

After that, the purchase application unit 42 of the information providing platform 40 applies for a purchase to the sales unit 29 of the platform server 20 through the purchase application based on the plurality of data displayed in step S106. ( S107)

15 is a flowchart of steps S108 to S113 in the method for selling medical data according to the present invention.

Referring to FIG. 15, the extraction unit 27 of the platform server 20 extracts a plurality of data according to the purchase condition input and processed in step S107 from the plurality of data pseudonymized in step S104. (S108)

Thereafter, the selling price calculation unit 28 multiplies the plurality of data extracted in step S108 by the standard unit price set in advance and the quantity described in the purchase application, and then adds them up to calculate the selling price (S109).

After that, the sales unit 29 provides the sales price calculated in step S109 and a plurality of data extracted in step S108 to the data confirmation unit 43 of the information providing platform 40, respectively. (S110)

After that, the data confirmation unit 43 of the information providing platform 40 displays the selling price and a plurality of data provided in step S110, respectively. (S111)

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 S110, respectively, and the points A receipt corresponding to is provided. (S112)

After that, the point confirmation unit 12 of the user terminal 10 displays the points and receipts provided in step S112 so that the data provider can recognize them. (S113)

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 (S102) as follows.

Figure 16 is a flow chart for the health checkup result analysis, health report and health guide generation process (S102).

Referring to FIG. 16, the analysis unit 22 analyzes the plurality of health examination result data collected in step S101 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. (S102-1)

After that, the analyzer 22 analyzes the plurality of disease information included in the plurality of health report data generated in step S102-1, respectively, and provides a plurality of health guide data including opinions on exercise or diet, respectively. Create. (S102-2)

Next, the process of processing medical data by the processing unit 24 (S103) is as follows.

17 is a flowchart of a process of processing medical data (S103).

Referring to FIG. 17, the processing unit 24 analyzes 22 major factors of the national health examination result data and classifies them by disease. (S103-1)

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 S103-1 into each patient based on the number of suspected patients. (S103-2)

Then, the processing unit 24 classifies the plurality of patients classified in step S103-2 into age groups, regions, and genders based on the personal information provided from the user terminal 10 (S103-3).

Next, the purchase request process (S107) by the purchase request unit 42 is as follows.

18 is a flowchart of a purchase request process (S107).

Referring to FIG. 18, the purchase application unit 42 inputs the disease name, region, age group, and gender of a plurality of data to be purchased as purchase conditions into the purchase application form (S107-1).

Thereafter, the purchase application unit 42 inputs at least one selected data from among the health checkup results, prescriptions, and health reports suitable for the purchase conditions entered in step S107-1 and the quantity of the corresponding data into the purchase application, respectively. .(S107-2)

After that, the purchase application unit 42 inputs and processes purchaser information selected from AI-related educational institutions, pharmaceutical companies, insurance companies, financial companies, and public institutions into the purchase application form (S107-3).

Next, a step (S110) in which the sales unit 29 provides the selling price and a plurality of data to the data confirmation unit 43 is as follows.

19 is a flowchart of a process of providing selling price and data (S110).

Referring to FIG. 19, the sales unit 29 determines the title of the data, description content, data type, extraction target, region name, gender, age group, disease name, main factor, and data for a plurality of data extracted in step S108. The quantity and validity period of the data are described respectively to generate detailed data. (S110-1)

After that, the sales unit 29 provides the sales price calculated in step S109 to the data confirmation unit 43 of the information providing platform 40. (S110-2)

After that, the sales unit 29 adds the detailed data generated in step S110-1 to the plurality of data extracted in step S108 and provides it to the data confirmation unit 43 of the information providing platform 40. (S110- 3)

Next, the process of point payment and receipt provision by the reward payment unit 30 (S112) is as follows.

20 is a flowchart of a point payment and receipt provision process (S112).

Referring to FIG. 20, 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 S110. is given. (S112-1)

Thereafter, the reward payment unit 30 issues receipts indicating the date and time of the transaction, type of data, demand destination, consenter, and points to the plurality of user terminals 10 to which points are assigned in step S112-1. (S112 -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 S112-2, and provides the corresponding receipt. (S112-3)

Next, the process of displaying points and receipts by the point confirmation unit 12 (S113) is as follows.

21 is a flowchart of a point and receipt display process (S113).

Referring to FIG. 21, 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. (S113-1)

After that, the point confirmation unit 12 adds up the points provided in step S112 and the small amount of points granted in step S113-1. (S113-2)

After that, the point confirmation unit 12 displays the summed points and receipts in step S113-2. (S113-3)

After that, the point confirmation unit 12 of the user terminal 10 displays the point shop and digital voucher shortcut icons. (S113-4)

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.

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
40: information provision platform 41: list confirmation unit
42: purchase application unit 43: data confirmation unit

Claims (6)

In the method of selling medical data,
The method of selling medical data
Step 101 of collecting personal information of a plurality of data providers provided by a collection unit 21 of the platform server 20 from a plurality of user terminals 10, health checkup results, and medical data including prescriptions, respectively;
Step 102, in which the analyzer 22 of the platform server 20 analyzes the plurality of health examination result data collected in step 101 through AI, and generates a plurality of health reports and health guide data, respectively;
Step 103, wherein the processing unit 24 of the platform server 20 processes a plurality of medical data, respectively;
Step 104, whereby the pseudonymization processing unit 25 of the platform server 20 performs pseudonymization on the plurality of data processed in step 103 so that personal information cannot be identified;
Step 105, in which the registration unit 26 of the platform server 20 registers the plurality of data pseudonymized in step 104 in the information providing platform 40 according to the number of data, region, age group, and gender ;
Step 106 of displaying a plurality of data registered in step 105 by the list confirmation unit 41 of the information providing platform 40;
The purchase application unit 42 of the information providing platform 40 applies a purchase request to the sales unit 29 of the platform server 20 through a purchase application based on the plurality of data displayed in step 106. step 107;
a step 108 in which the extraction unit 27 of the platform server 20 extracts a plurality of data according to the purchase condition input and processed in step 107 from the plurality of data pseudonymized in step 104;
The selling price calculation unit 28 of the platform server 20 multiplies the plurality of data extracted in the step 108 by the standard unit price set in advance and the quantity described in the purchase application, and then sums them to calculate the selling price Step 109;
Step 110, wherein the sales unit 29 provides the sales price calculated in step 109 and a plurality of data extracted in step 108 to the data checking unit 43 of the information providing platform 40, respectively;
Step 111, wherein the data check unit 43 displays the selling price and a plurality of data provided in step 110, respectively;
The reward payment unit 30 of the platform server 20 provides points to the point confirmation units 12 of the plurality of user terminals 10 corresponding to the plurality of data sold in step 110, respectively, and the points Step 112 of providing a receipt corresponding to; and
Step 113 of displaying the points and receipts provided in step 112 so that the point confirmation unit 12 of the user terminal 10 can recognize the data provider;
Step 102 is
The analysis unit 22 analyzes the plurality of health checkup result data collected in step 101 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 102-1 of generating data respectively; and
The analyzer 22 analyzes the plurality of disease information included in the plurality of health report data generated in step 102-1, respectively, and provides a plurality of health guide data including opinions such as exercise or diet, respectively. Including; step 102-2 of generating;
The 103rd step is
Step 103-1, in which the processing unit 24 analyzes 22 major factors of the national health examination result data and classifies them by disease;
a 103-2 step in which the processing unit 24 classifies the plurality of diseases classified in the step 103-1 into each patient based on the number of patients suspected of having the disease; and
a step 103-3 in which the processing unit 24 classifies the plurality of patients classified in the step 103-2 into age groups, regions, and genders based on the personal information provided from the plurality of user terminals 10; including,
the disease is
including obesity, hypertension, anemia, diabetes, dyslipidemia, chronic kidney disease, liver disease, pulmonary tuberculosis and chest disease;
The 107th step is
a step 107-1 in which 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;
The purchase application unit 42 inputs at least one selected data from the health checkup results, prescriptions, and health reports suitable for the purchase conditions input and processed in step 107-1 and the quantity of the corresponding data into the purchase application, respectively. Step 107-2 to do; and
A step 107-3 in which the purchase application unit 42 inputs and processes purchaser information selected from AI-related educational institutions, pharmaceutical companies, insurance companies, financial companies, and public institutions into the purchase application form;
Step 110 is
For the plurality of data extracted in the step 108, 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. Step 110-1 of generating detailed data by describing each effective period;
a step 110-2 in which the sales unit 29 provides the sales price calculated in the step 109 to the data checking unit 43 of the information providing platform 40; and
Step 110-3, wherein the sales unit 29 adds detailed data generated in step 110-1 to the plurality of data extracted in step 108, and provides the data to the data confirmation unit 43; do,
Step 112 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 110 in the order of health guide, health report, prescription and health checkup result data Step 112-1;
112-step in which 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 to which points are assigned in step 112-1. Step 2; and
a step 112-3 in which the reward payment unit 30 provides points to the point confirmation units 12 of the plurality of user terminals 10 for which the receipts were issued in the step 112-2, and provides corresponding receipts; including,
The reward payment unit 30
Regardless of the number of purchases of buyers registered in the information providing platform 40, points are paid to a plurality of user terminals 10 each time a plurality of data is sold by the sales unit 29. Characterized in that How to sell medical data. delete delete delete According to claim 1,
Step 113 is
Step 113-1, 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 113-2 in which the point confirmation unit 12 adds up the points provided in step 112 and the small amount of points granted in step 113-1;
Step 113-3, wherein the point confirmation unit 12 displays the summed points and receipts in Step 113-2, respectively; and
A method for selling medical data comprising a; step 113-4, wherein the point confirmation unit 12 displays shortcut icons for point shops and digital vouchers. According to claim 5,
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, 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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