WO2017148160A1 - Système d'évaluation de risques d'assurance maladie basé sur des informations biologiques - Google Patents

Système d'évaluation de risques d'assurance maladie basé sur des informations biologiques Download PDF

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Publication number
WO2017148160A1
WO2017148160A1 PCT/CN2016/103037 CN2016103037W WO2017148160A1 WO 2017148160 A1 WO2017148160 A1 WO 2017148160A1 CN 2016103037 W CN2016103037 W CN 2016103037W WO 2017148160 A1 WO2017148160 A1 WO 2017148160A1
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WO
WIPO (PCT)
Prior art keywords
database
risk assessment
index
risk
health insurance
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PCT/CN2016/103037
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English (en)
Chinese (zh)
Inventor
张贯京
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深圳市前海安测信息技术有限公司
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Publication of WO2017148160A1 publication Critical patent/WO2017148160A1/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • G06F19/328—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present invention relates to the field of medical information processing, and in particular, to a health insurance risk assessment system based on biological information.
  • Bioinformatics provides orderly data and related information that grows exponentially. After analysis and collation, the risk control concept and innovative thinking of health insurance can be obtained from massive information. Therefore, it is necessary to establish a nuclear insurance and actuarial system for assessing the risk of health insurance targets, and apply bioinformatics database technology to the underwriting and actuarial risk assessment of health insurance, thereby reducing the underwriting cost of health insurance companies. Strengthen the risk control and core competitiveness of health insurance companies.
  • the main object of the present invention is to provide a bio-information-based health insurance risk assessment system, which aims to solve the technical problem that the existing insurance risk assessment system cannot combine the bio-information assessment health insurance risk to cause a large risk assessment.
  • the present invention provides a bio-information-based health insurance risk assessment system, which includes a risk assessment database system, a database search engine, and a bio-nuclear insurance claims risk index analysis system.
  • the risk assessment database system is connected to the bio-nuclear insurance risk index analysis system by the database search engine, wherein:
  • the risk assessment database system includes a historical risk assessment database, a realistic risk assessment database, a predictive risk assessment database, a financial risk rating database, and a biometric risk assessment data.
  • the biological nuclear insurance risk index analysis system includes a biological genetic detection subsystem, a human health early warning subsystem, and a biological nuclear insurance compensation risk control subsystem;
  • the biological gene detection subsystem is configured to detect a biological gene of a human disease based on a biological brain grid
  • the human health early warning subsystem is configured to use an biosensor to perform an early warning on a human disease type according to a biological genetic detection result
  • the bio-nuclear insurance risk control subsystem is configured to analyze and evaluate risk factors of the insured's health insurance underwriting and health insurance claims to obtain an assessment result of the health insurance risk.
  • the historical risk assessment database comprises a population vital sign database, a family genetic database, a family disease database, an individual past medical history database, an individual growth environment database, and a living area infectious disease incidence database.
  • the real-life risk assessment database includes an air pollution index database of an individual living area, a traffic accident occurrence index database, an individual physical examination index database, an individual real biochemical index library, an individual lifestyle index database, and an individual.
  • the social security index database of living areas includes an air pollution index database of an individual living area, a traffic accident occurrence index database, an individual physical examination index database, an individual real biochemical index library, an individual lifestyle index database, and an individual.
  • the predictive risk assessment database includes a disease gene database.
  • the financial risk rating database includes a health insurance demand index database, a financial status index database, a real financial index database, and a revenue insured ratio information database.
  • the biometric risk assessment database includes an insured fingerprint database and an insured iris database.
  • the health insurance underwriting index database comprises a standard body nuclear insurance index database, a secondary standard body nuclear insurance index database, an extended insurance index database, a refusal index database, and a nuclear insurance comprehensive index database.
  • the actuarial rate index library includes a multi-function life function library, an interest function library, a basic annuity database, an actuarial present value database, a policy cash value database, and a solvency index database.
  • the risk assessment database system is disposed in a database server.
  • the bio-nuclear insurance risk index analysis system is set in an application server.
  • the bio-information-based health insurance risk assessment system of the present invention adopts the above technical solution, and achieves the following technical effects: a multi-dimensional information database is adopted, and data information in all information databases is quantitatively classified. With the advantages of large amount of information and comprehensive information, it can be widely used in the life insurance industry.
  • the assessment of health insurance risks combined with bioinformatics reduces the risk of assessment, reduces the cost of underwriting for life insurance companies, and strengthens the risk control and core competitiveness of life insurance companies.
  • FIG. 1 is a schematic diagram showing the system configuration of a preferred embodiment of the bioinformation-based health insurance risk assessment system of the present invention
  • FIG. 2 is a schematic structural diagram of a preferred embodiment of the risk assessment database system of FIG. 1;
  • FIG. 3 is a schematic structural diagram of a preferred embodiment of the bio-nuclear insurance claim risk index analysis system of FIG. 1.
  • FIG. 1 is a schematic structural diagram of a system of a biometric-based health insurance risk assessment system according to a preferred embodiment of the present invention.
  • the biometric-based health insurance risk assessment system includes a risk assessment database system 1, a database search engine 2, and a bio-nuclear insurance risk index analysis system 3, wherein the risk assessment database system 1
  • the database search engine 2 is connected to the bio-nuclear insurance risk index analysis system 3.
  • the risk assessment database system 1 is disposed in the database server 10, and the bio-nuclear insurance risk index analysis system 3 is disposed in the application server 30.
  • FIG. 2 is a schematic structural diagram of a preferred embodiment of the risk assessment database system of FIG. 1.
  • the risk assessment database system 1 includes a historical risk assessment database 11, a realistic risk assessment database 12, a predictive risk assessment database 13, a financial risk rating database 14, a biometric risk assessment database 15, and health.
  • the historical risk assessment database 11 includes a population vital sign database 111, a family genetic database 1 12, a family disease database 113, an individual past medical history database 114, an individual growth environment database 115, and a living area infectious disease incidence database 116.
  • the real risk assessment database 12 includes an air pollution index database 121 in an individual living area, a traffic accident occurrence index database 122, an individual physical examination index library 123, an individual real biochemical index library 124, and an individual lifestyle index database. 125 and the social security index library 126 of the individual living area.
  • the individual life index library 125 stores a physical index BMI, an intellectual index IQ+EQ, a marital status, a number of children, a smoking habit, a physical exercise, a sleep, an education level, a career, a change, a social situation, a place of residence, and a place to go to work. Distance and other information.
  • the predictive risk assessment database 13 includes a disease gene database 131 for storing genetic test data for common human diseases.
  • genetic testing methods can detect whether anti-cancer genes and oncogenes are defective at a very early stage, and the probability of possible onset; breast cancer mothers have daughters suffering from breast cancer It is 15 times that of ordinary people.
  • People with defective CYP and GST in the liver can eat 60 yuan more than the average person if they often eat stinky tofu, preserved food, and bad habits such as smoking and drinking.
  • the chance of hepatitis B with the original person becoming a liver cancer is 223 times that of a normal person.
  • the genetic susceptibility gene of hepatitis B helps to predict the risk of hepatitis B. If the Apo E gene on chromosome 19 is defective, it is prone to heart disease and Alzheimer's disease (ie, dementia). If the CETP gene on the 16th chromosome has a problem, it is easy to have arteriosclerosis, vascular embolism, and the risk of myocardial infarction.
  • the financial risk rating database 14 includes a health insurance demand index library 141, a financial condition index library 142, a real financial index library 143, and a revenue insured ratio information repository 144.
  • the existing international health insurance demand function model and the health service demand function model are used to estimate the life insurance insurance demand in China under the framework of human capital, and to control the possible selective deviation and endogeneity. Deviation and omission variable deviations are used to distinguish the impact of institutional changes on stability, health and longevity and the impact of health and insurance service needs.
  • the biometric risk assessment database 15 includes an insured fingerprint database 151 and an insured iris database 152.
  • the insured fingerprint database 151 is used to store insured fingerprint information
  • the insured iris database 152 is used to store the insured iris information.
  • the health insurance underwriting index database 16 includes a standard body nuclear insurance index library 161, a secondary standard body nuclear insurance index library 1
  • the actuarial rate index library 17 includes a multivariate life function library 171, an interest function library 172, a basic annuity database 173, an actuarial present value database 174, a policy cash value database 175, and a solvency index library.
  • FIG. 3 is a schematic structural diagram of a preferred embodiment of the bio-nuclear insurance risk index analysis system of FIG. 1.
  • the bio-nuclear insurance risk index analysis system 3 includes a biological genetic detection subsystem 31, a human health early warning subsystem 32, and a biological nuclear insurance compensation risk control subsystem 33.
  • the biological gene detection subsystem 31 is connected to the human health early warning subsystem 32, and the biological genetic detection subsystem 31 and the human health early warning subsystem 32 are connected to the biological nuclear insurance risk control subsystem 33. .
  • the biological gene detection subsystem 31 is configured to detect a biological gene of a human disease based on a biological brain grid; the human health early warning subsystem 32 is configured to use a biosensor to perform an early warning on a human disease type according to a biological genetic detection result;
  • the bio-nuclear insurance risk control subsystem 33 is configured to analyze and evaluate the insured's health insurance underwriting and health insurance claims risk factors to obtain health insurance risk assessment results, thereby reducing the health insurance service risk.
  • the bio-information-based health insurance risk assessment system of the present invention adopts a multi-dimensional information database, and the data information in all information databases are quantitatively graded, and has the advantages of large amount of information and comprehensive information, and has strong operability. , can be widely used in the life insurance industry.
  • the present invention combines bioinformatics to assess health insurance risks, reduces assessment risk, reduces life insurance company's underwriting cost, and enhances life insurance company's risk control and core competitiveness.
  • the bio-information-based health insurance risk assessment system of the present invention adopts the above technical solutions, and achieves the following technical effects:
  • a multi-dimensional information database is adopted, and data information in all information databases is quantized and graded, and has information.
  • the large quantity and comprehensive information advantages can be widely applied in the life insurance industry.
  • the assessment of health insurance risks combined with biological information reduces the risk of assessment, reduces the cost of underwriting for life insurance companies, and strengthens the risk control and core competitiveness of life insurance companies.

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Business, Economics & Management (AREA)
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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Public Health (AREA)
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Abstract

L'invention concerne un système d'évaluation de risques d'assurance maladie basé sur des informations biologiques, comprenant : un système de base de données d'évaluation de risques, un moteur de recherche de base de données et un système d'analyse d'indice de risques d'évaluation de souscriptions et de demandes d'indemnisation basé sur des informations biologiques, le système de base de données d'évaluation de risques étant connecté au système d'analyse d'indice de risques d'évaluation de souscriptions et de demandes d'indemnisation basé sur des informations biologiques au moyen du moteur de recherche de base de données. Ledit système de base de données d'évaluation de risques inclut une base de données d'évaluation de risques passés, une base de données d'évaluation de risques réels, une base de données d'évaluation de risques prédictifs, une base de données d'évaluation de niveau de risques financiers, une base de données d'évaluation de risques à reconnaissance biologique, une bibliothèque d'indices de souscription d'assurance maladie et une bibliothèque d'indices de taux actuariel. Le système d'analyse d'indice de risques d'évaluation de souscriptions et de demandes d'indemnisation basé sur des informations biologiques comporte un sous-système de détection de biogène, un sous-système d'alerte précoce sur la santé humaine et un sous-système de contrôle de risques de souscription basé sur des informations biologiques. La présente invention évalue une assurance maladie grâce à des bases de données d'informations multidimensionnelles ayant des informations classées quantitativement et en association avec des informations biologiques, ce qui réduit les risques d'évaluation et les coûts de souscription.
PCT/CN2016/103037 2016-03-04 2016-10-24 Système d'évaluation de risques d'assurance maladie basé sur des informations biologiques WO2017148160A1 (fr)

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CN201610125536.5A CN105760692A (zh) 2016-03-04 2016-03-04 基于生物信息的健康保险风险评估系统
CN201610125536.5 2016-03-04

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WO2019100601A1 (fr) * 2017-11-22 2019-05-31 平安科技（深圳）有限公司 Procédé et dispositif d'évaluation du risque de demandes d'indemnisation

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US10636525B2 (en) 2014-11-14 2020-04-28 Hi.Q, Inc. Automated determination of user health profile
US10629293B2 (en) 2014-11-14 2020-04-21 Hi.Q, Inc. System and method for providing a health determination service based on user knowledge and activity
US10930378B2 (en) 2014-11-14 2021-02-23 Hi.Q, Inc. Remote health assertion verification and health prediction system
US10672519B2 (en) 2014-11-14 2020-06-02 Hi.Q, Inc. System and method for making a human health prediction for a person through determination of health knowledge
CN105760692A (zh) * 2016-03-04 2016-07-13 深圳市前海安测信息技术有限公司 基于生物信息的健康保险风险评估系统
CN107273699A (zh) * 2017-07-07 2017-10-20 成都脉安科健生物科技有限公司 营养指导方案获取方法、装置及电子设备
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CN107577907B (zh) * 2017-09-08 2021-04-02 成都奇恩生物科技有限公司 一种基于互联网的罕见病辅助诊断系统及使用方法
CN109285076A (zh) * 2018-02-07 2019-01-29 中国平安人寿保险股份有限公司 智能核保处理方法、服务器及存储介质
US20220114674A1 (en) * 2020-10-09 2022-04-14 Hi.Q, Inc. Health lab data model for risk assessment
CN113643139A (zh) * 2021-08-12 2021-11-12 华农财产保险股份有限公司江苏省分公司 基于河蟹目标收入保险目标收入与赔付计算系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101826193A (zh) * 2009-06-18 2010-09-08 张艳红 金融保险第三方海量数据与红指数池管理智能tpa平台
CN102622522A (zh) * 2012-03-19 2012-08-01 中国科学院上海技术物理研究所 一种手持移动式安全远程医疗健康状态监护系统
CN104392110A (zh) * 2014-11-04 2015-03-04 宝鸡数字人信息科技有限公司 人体生理数据可视化监测、分析和评估方法和系统
CN105760692A (zh) * 2016-03-04 2016-07-13 深圳市前海安测信息技术有限公司 基于生物信息的健康保险风险评估系统

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101826193A (zh) * 2009-06-18 2010-09-08 张艳红 金融保险第三方海量数据与红指数池管理智能tpa平台
CN102622522A (zh) * 2012-03-19 2012-08-01 中国科学院上海技术物理研究所 一种手持移动式安全远程医疗健康状态监护系统
CN104392110A (zh) * 2014-11-04 2015-03-04 宝鸡数字人信息科技有限公司 人体生理数据可视化监测、分析和评估方法和系统
CN105760692A (zh) * 2016-03-04 2016-07-13 深圳市前海安测信息技术有限公司 基于生物信息的健康保险风险评估系统

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019100601A1 (fr) * 2017-11-22 2019-05-31 平安科技（深圳）有限公司 Procédé et dispositif d'évaluation du risque de demandes d'indemnisation

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