WO2017148170A1 - 医疗大数据分析及预警系统及方法 - Google Patents

医疗大数据分析及预警系统及方法 Download PDF

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Publication number
WO2017148170A1
WO2017148170A1 PCT/CN2016/104127 CN2016104127W WO2017148170A1 WO 2017148170 A1 WO2017148170 A1 WO 2017148170A1 CN 2016104127 W CN2016104127 W CN 2016104127W WO 2017148170 A1 WO2017148170 A1 WO 2017148170A1
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weather
information
medical
patient
disease
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French (fr)
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张贯京
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Shenzhen Qianhai AnyCheck Information Technology Co Ltd
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Shenzhen Qianhai AnyCheck Information Technology Co Ltd
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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
    • 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
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • 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
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Definitions

  • the present invention relates to the field of big data analysis and mining, and in particular, to a medical big data analysis and early warning system and method.
  • Big data technology can accelerate medical conjectures, discover the transformation of medical practice, and with the growing private and public medical data, big data technology helps people store and manage medical big data and from large volume, high complexity The value of the data will be extracted, and related medical technologies and products will continue to emerge, which will likely open up a new golden generation for the medical industry.
  • the current medical data analysis system does not consider the influence of weather factors in the analysis and processing of medical big data, nor does it warn patients according to weather conditions, which reduces the accuracy of medical data.
  • the main object of the present invention is to provide a medical big data analysis and early warning system and method, aiming at solving the technical problem of not being able to warn patients through weather conditions during the processing of medical big data.
  • the present invention provides a medical big data analysis and early warning system, which is operated in a data center, and the data center is connected to a hospital information system, a client, and a weather information platform through a network.
  • Data analysis and early warning systems include: [0007] an obtaining module, configured to acquire medical data from the hospital information system;
  • a search module configured to search for a sick date in the medical data
  • the acquiring module is configured to acquire historical weather information corresponding to a diseased date in the medical data from the weather information platform, and associate the medical data with the historical weather information;
  • an analysis module configured to analyze medical data associated with the historical weather information to obtain a patient affected by weather factors
  • the acquiring module is configured to acquire weather forecast information from the weather information platform
  • a determining module configured to determine whether the patient is affected by the weather forecast information
  • a generating module configured to generate an early warning information and send the warning information to the client corresponding to the patient when the patient is affected by the weather forecast information.
  • the medical data includes a patient name, a patient's age, a diseased day, a disease name, a disease cause, a drug name, a drug quantity, a doctor's name, a doctor's office, a medical fee, and a patient's contact method.
  • the weather information includes a location, a temperature, a wind direction, a weather condition, and an air quality.
  • the manner of analyzing the medical data associated with the weather information to obtain a patient affected by weather factors is as follows:
  • the disease is determined to be affected by weather factors
  • a patient affected by weather factors is retrieved from medical data based on the name of the disease affected by weather factors.
  • the warning information includes a patient name, weather forecast information, a disease in the same weather condition, and a precaution to prevent the disease.
  • the present invention further provides a medical big data analysis and early warning method, which is applied to a data center, wherein the data center is connected to a hospital information system, a client, and a weather information platform through a network, and the method includes:
  • the warning information is generated and sent to the client corresponding to the patient affected by the weather factor.
  • the medical data includes a patient name, a patient's age, a diseased day, a disease name, a disease cause, a drug name, a drug quantity, a doctor's name, a medical department, a medical fee, and a contact form of the patient.
  • the weather information includes a location, a temperature, a wind direction, a weather condition, and an air quality.
  • the manner of analyzing the medical data associated with the weather information to obtain the patient affected by the weather factor is as follows:
  • the disease is determined to be affected by weather factors
  • the warning information includes a patient name, weather forecast information, a disease in the same weather condition, and a precaution to prevent the disease.
  • the medical big data analysis and early warning system and method of the present invention adopts the above technical solutions, and the technical effects are as follows:
  • the medical big data can be associated with the weather information, and the medical big data analysis related to the weather information is analyzed.
  • DRAWINGS 1 is a schematic diagram of an application environment of a medical big data analysis and early warning system of the present invention.
  • FIG. 2 is a block diagram of a preferred embodiment of the medical big data analysis and early warning system of the present invention.
  • FIG. 3 is a flow chart of a preferred embodiment of the medical big data analysis and early warning method of the present invention.
  • FIG. 4 is a schematic diagram of a disease name corresponding to weather information and the number of each disease name according to the present invention.
  • FIG. 1 is a schematic diagram of an application environment of a medical big data analysis and early warning system of the present invention.
  • the medical big data analysis and early warning system 20 of the present invention operates in the data center 2.
  • the data center 2 is communicatively coupled to one or more hospital information systems 1 (illustrated by three in FIG. 1) via the network 3 to obtain medical data from the hospital information system connection 1.
  • the medical data includes, but is not limited to, patient name, patient's age, disease, disease name, cause of illness, drug name, number of drugs, name of doctor, department of visit, cost, and contact information of patient (eg, electronic Information such as email address, mobile phone number, instant messaging account, etc.).
  • the network 3 may be a wired communication network or a wireless communication network.
  • the network 3 is preferably a wireless communication network including, but not limited to, a GSM network, a GPRS network, a CDMA network, a TD-SCDMA network, a WiMAX network, a TD-LTE network, an FDD-LTE network, and the like.
  • the data center 2 is communicatively connected to the one or more clients 4 (illustrated by three in FIG. 1) through the network 3, and transmits the medical data corresponding to the patient to the patient.
  • the data center 2 may further analyze and process the medical data, and send the analyzed medical data (for example, medical data associated with historical weather information) to the corresponding network through the network 3.
  • Client 4
  • the data center 2 is communicatively connected to the weather information platform 5 through the network 3, and is used to acquire historical weather information and weather forecast information (also referred to as future weather information) from the weather information platform 5.
  • the weather information platform 5 is configured to provide historical weather information and weather forecast information, including, but not limited to, location, temperature (highest temperature and minimum temperature), wind direction (eg, Information such as southerly winds, northerly winds, weather conditions (eg weather conditions such as fine weather, light rain, heavy rain, snow, heavy snow) and air quality (eg PM 2.5 values).
  • the data center 2 is a server of a cloud platform or a data center, and can better manage and/or assist with the data transmission capability and data storage capability of the cloud platform or the data center.
  • the data center 2 is connected to the client 4, which helps the patient to understand his or her medical data.
  • the client 4 may be, but is not limited to, any other suitable portable electronic device such as a smart phone, a tablet computer, a personal digital assistant (PDA), a personal computer, an electronic signboard, and the like.
  • a smart phone such as a smart phone, a tablet computer, a personal digital assistant (PDA), a personal computer, an electronic signboard, and the like.
  • PDA personal digital assistant
  • FIG. 2 there is shown a block diagram of a preferred embodiment of the medical big data analysis and early warning system of the present invention.
  • the medical big data analysis and early warning system 20 is applied to the data center 2.
  • the data center 2 includes, but is not limited to, a medical big data analysis and early warning system 20, a storage unit 22, a processing unit 24, and a communication unit 26.
  • the storage unit 22 may be a read only storage unit ROM, an electrically erasable storage unit EEPRO
  • flash memory unit FLASH or solid hard disk FLASH or solid hard disk.
  • the processing unit 24 may be a central processing unit (CPU), a microcontroller (MCU), a data processing chip, or an information processing unit having a data processing function.
  • CPU central processing unit
  • MCU microcontroller
  • data processing chip or an information processing unit having a data processing function.
  • the communication unit 26 is a wireless communication interface with remote wireless communication function, for example, support
  • GSM Global System for Mobile communications
  • GPRS Wireless Fidelity
  • WCDMA Wideband Code Division Multiple Access
  • CDMA Code Division Multiple Access
  • TD-SCDMA Wideband Code Division Multiple Access
  • WiMAX TD-LTE
  • FDD-LT Frequency Division Multiple Access
  • the medical big data analysis and early warning system 20 includes, but is not limited to, an acquisition module 200, a search module 210, an analysis module 220, a determination module 230, and a generation module 240.
  • a module referred to in the present invention refers to a series of computer program instruction segments that can be executed by the processing unit 24 of the data center 2 and that are capable of performing a fixed function, which are stored in the storage unit 22 of the data center 2.
  • the acquisition module 200 is configured to acquire medical data from the hospital information system 1.
  • the hospital information system 1 provides a data import interface (eg, an application program interface, an API), and a device or system that accesses the data import interface can
  • the hospital information system 1 acquires medical data.
  • the obtaining module 200 invokes an API interface provided by the hospital information system 1 to obtain medical data.
  • the medical data belongs to private information
  • the medical data is sent to the data center 2, and the encryption and decryption algorithm is adopted (for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm).
  • DES encryption and decryption algorithm for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm.
  • DSA encryption and decryption algorithm for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm
  • AES encryption and decryption algorithm etc.
  • the search module 210 is configured to search for a sick date in the medical data. Specifically, the search module 2
  • the obtaining module 200 is configured to acquire historical weather information corresponding to a diseased date in the medical data from the weather information platform 5, and associate the medical data with the historical weather information.
  • the weather information platform 5 provides an API interface, and the device or system accessing the API interface can obtain historical weather information and weather forecast information from the weather information platform 5.
  • the obtaining module 200 invokes an API interface provided by the weather information platform 5 to obtain historical weather information and weather forecast information.
  • the obtaining module 200 invokes an API interface provided by the weather information platform 5 and sends the diseased period to the weather information platform 5, and the weather information platform 5 searches for the diseased disease by using the diseased date as a key.
  • the corresponding historical weather information is returned to the data center 2.
  • the analysis module 220 is configured to analyze medical data associated with historical weather information to obtain a patient affected by weather factors.
  • the manner of analyzing medical data associated with historical weather information to obtain a patient affected by weather factors is as follows: (1) classifying medical data associated with historical weather information to obtain each historical weather information. Corresponding disease name and the number of each disease name. For example, as shown in FIG. 4, in the case of heavy snow weather, there are four diseases in the medical data, namely, a cold, a fever, an asthma, and a fracture, wherein There are fifty-eight pens for colds, twenty pens for fever, fifteen strokes for asthma, and twenty-seven for fractures. (2) Calculate the weight of the disease affected by weather factors based on the number of each disease name.
  • the calculated weight is equal to the number of each disease name, that is, in the case of FIG. 4, the number of asthma is fifteen, and the weight of asthma affected by weather factors is ten. Fives. (3) If the weight exceeds a preset value (for example, 10) ⁇ , the disease is considered to be affected by weather factors, as shown in Figure 4. For example, the number of asthma is 15, and the default value is 10, which determines that asthma is affected by weather factors. (4) Retrieving the patient in the medical data according to the name of the disease affected by the weather factor, the patient being searched for is a patient affected by weather factors, for example, using "asthma" as a key, searching for the disease in the medical data Asthmatic patients.
  • the obtaining module 200 is further configured to acquire weather forecast information from the weather information platform 5.
  • the weather forecast information includes weather information in a future preset interval, for example, weather information for the next week.
  • the determining module 230 is configured to determine whether the patient affected by the weather factor is affected by the weather forecast information. Specifically, the determining module 230 can retrieve the patient affected by the weather factor according to the weather information in the future preset interval in the weather forecast information. As shown in Figure 4, the weather forecast information is heavy snow weather, and the heavy snow is used as a key to retrieve asthma patients affected by weather factors.
  • the generating module 240 is configured to generate an early warning information and send the patient affected by the weather factor after being affected by the weather forecast information (for example, according to the contact information of the patient in the medical data)
  • the client 4 corresponding to the patient affected by the weather factor.
  • the warning information includes, but is not limited to, a patient name, weather forecast information, a disease in the same weather condition, and a precautionary matter for preventing the disease.
  • the warning information may be sent to the client 4 in the form of text, voice and/or audio and video.
  • the warning message is as follows: "Respected XXX, cold weather will occur in the next few days, the minimum temperature will drop below zero, and the lowest temperature in the past will drop to zero.
  • FIG. 3 a flow chart of a preferred embodiment of the medical big data analysis and early warning method of the present invention is shown.
  • the medical big data analysis and early warning method is applied to the data center 2, and the method includes the following steps:
  • Step S10 The obtaining module 200 acquires medical data from the hospital information system 1.
  • the hospital information system 1 provides a data import interface (eg, an application program interface, an API), and a device or system that accesses the data import interface can be from the hospital information system.
  • a data import interface eg, an application program interface, an API
  • the obtaining module 200 calls the hospital information system 1
  • An API interface is provided to obtain medical data.
  • the medical data belongs to private information
  • the medical data is sent to the data center 2, and the encryption and decryption algorithm is adopted (for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm).
  • DES encryption and decryption algorithm for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm.
  • DSA encryption and decryption algorithm for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm
  • AES encryption and decryption algorithm etc.
  • Step S11 The search module 210 searches for a diseased date in the medical data. Specifically, the search module 210 searches for the date of illness in the medical data by means of keyword search. For example, with "date of illness"
  • Step S12 The obtaining module 200 acquires historical weather information corresponding to the diseased period in the medical data from the weather information platform 5, and associates the medical data with the historical weather information.
  • the weather information platform 5 provides a data import interface (eg, an application interface, Application)
  • a data import interface eg, an application interface, Application
  • Program Interface, API the device or system accessing the data import interface can obtain historical weather information from the weather information platform 5.
  • the obtaining module 200 invokes an API interface provided by the weather information platform 5 to obtain historical weather information.
  • the acquiring module 200 invokes an API interface provided by the weather information platform 5 and sends the disease date to the weather information platform 5, and the weather information platform 5 uses the disease date as a key.
  • the historical weather information corresponding to the diseased date is retrieved for return to the data center 2.
  • Step S13 The analysis module 220 analyzes the medical data associated with the historical weather information to obtain a patient affected by the weather factor.
  • the manner of analyzing the medical data associated with historical weather information to obtain a patient affected by weather factors is as follows: (1) classifying medical data associated with historical weather information to obtain each historical weather information. Corresponding disease name and the number of each disease name. For example, as shown in FIG. 4, in the case of heavy snow weather, there are four diseases in the medical data, namely, a cold, a fever, an asthma, and a fracture, wherein There are fifty-eight pens for colds, twenty pens for fever, fifteen strokes for asthma, and twenty-seven for fractures. (2) Calculate the weight of the disease affected by weather factors based on the number of each disease name.
  • the calculated weight is equal to the number of each disease name, that is, in the case of FIG. 4, the number of asthma is fifteen, and the weight of asthma affected by weather factors is ten. Fives. (3) If the weight exceeds a preset value (for example, 10) ⁇ , the disease is considered to be affected by weather factors, as shown in Figure 4. For example, the number of asthma is 15, and the default value is 10, which determines that asthma is affected by weather factors. (4) Retrieving the patient in the medical data according to the name of the disease affected by the weather factor, the patient being searched for is a patient affected by weather factors, for example, using "asthma" as a key, searching for the disease in the medical data Asthmatic patients.
  • Step S14 The acquiring module 200 acquires weather forecast information from the weather information platform 5.
  • the weather forecast information includes weather information in a future preset interval, for example, weather information for the next week.
  • Step S15 The determining module 230 is configured to determine whether the patient affected by the weather factor is affected by the weather forecast information. Specifically, if the weather forecast information is used for searching in the patient affected by the weather factor, if there is a patient affected by the weather forecast factor, the patient affected by the weather factor needs to be notified, as shown in FIG. 4, The weather forecast information is a heavy snow weather, and the asthma patient affected by the weather factor is retrieved by using the heavy snow as a keyword, and the flow proceeds to step S16. Otherwise, if the patient affected by the weather factor is not affected by the weather forecast information, the process returns to step S14.
  • Step S16 The generating module 240 generates the early warning information and sends the information to the client 4 corresponding to the patient affected by the weather factor.
  • the warning information includes, but is not limited to, a patient name, weather forecast information, a disease in the same weather condition, and a precaution to prevent the disease.
  • the warning information may be sent to the client 4 in the form of text, voice and/or audio and video.
  • the warning message is as follows: "Respected XXX, cold weather will occur in the next few days, the minimum temperature will drop below zero, and the lowest temperature in the past will drop to zero. You have had asthma and are in the First People's Hospital and The Second People's Hospital has been treated once, and please pay attention to strengthening asthma prevention.
  • preventive measures please refer to: (1) Avoid crowd gathering; (2) Carry out the N95 model mask when going out; (3) Keep warm, In particular, keep your head, chest and back warm to avoid coldness; (4) Pay attention to drugs such as bronchodilators, inhalants, aerosols, etc. Finally, I wish you good health!
  • the medical big data analysis and early warning system and method of the present invention adopts the above technical solutions, and the technical effects brought by the following are:
  • the medical big data can be associated with the weather information, and the medical information associated with the weather information is Big data analysis processing to obtain patients affected by weather factors, and early warning of the weather-affected patients and sputum, reduces the risk of patients being re-affected by weather factors.

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Abstract

一种医疗大数据分析及预警系统(20)及方法，该方法包括：从所述医院信息系统(1)获取医疗数据；搜索医疗数据中患病日期；从所述天气信息平台(5)获取医疗数据中患病日期对应的天气信息，并将医疗数据与所述天气信息关联；分析与天气信息关联的医疗数据以获得受天气因素影响的患者；从所述天气信息平台(5)获取天气预报信息；根据所述天气预报信息判断是否有受天气因素影响的患者；当所述患者受所述天气预报信息的影响时，生成预警信息并发送给受天气因素影响的患者所对应的客户端(4)。可以对所述受天气因素影响的患者及时预警，降低了患者受天气因素影响而再次患病的风险。

Description

发明名称：医疗大数据分析及预警系统及方法 技术领域
[0001] 本发明涉及大数据分析与挖掘领域， 尤其涉及一种医疗大数据分析及预警系统 及方法。
背景技术
[0002] 近年来随着互联网、 云计算、 移动和物联网等的迅猛发展， 无所不在的移动设 备、 RFID、 无线传感器每分每秒都在产生数据， 数以亿计用户的互联网服务吋 吋刻刻在产生巨量的交互， 要处理的数据量巨大， 数据一直都在以每年 50%的速 度增长， 而业务需求和竞争压力对数据处理的实吋性、 有效性又提出了更高要 求， 传统的常规技术手段根本无法应付， 因此， 大数据技术 （BigData) 成为近 来的一个技术热点， 引起了广泛的重视。
[0003] 通过大数据技术可以加速医学的猜想、 发现到医疗实践的转化， 借助于不断增 长的私密和公幵医疗数据， 大数据技术帮助人们存储管理好医疗大数据并从大 体量、 高复杂的数据中提取价值， 相关的医疗技术、 产品将不断涌现， 将有可 能给医疗行业幵拓一个新的黄金吋代。
[0004] 然而， 现阶段的医疗数据分析系统在针对医疗大数据进行分析处理吋， 并没有 考虑天气因素的影响， 也不会根据天气情况对患者进行预警， 降低了医疗大数 据的准确性。
技术问题
[0005] 本发明的主要目的在于提供一种医疗大数据分析及预警系统及方法， 旨在解决 现有对医疗大数据处理过程中无法通过天气情况对患者进行预警的技术问题。 问题的解决方案
技术解决方案
[0006] 为实现上述目的， 本发明提供了一种医疗大数据分析及预警系统， 运行于数据 中心， 所述数据中心通过网络与医院信息系统、 客户端及天气信息平台连接， 所述医疗大数据分析及预警系统包括： [0007] 获取模块， 用于从所述医院信息系统获取医疗数据；
[0008] 搜索模块， 用于搜索医疗数据中的患病日期；
[0009] 所述获取模块， 用于从所述天气信息平台获取医疗数据中的患病日期所对应的 历史天气信息， 并将医疗数据与所述历史天气信息关联；
[0010] 分析模块， 用于分析与所述历史天气信息关联的医疗数据以获得受天气因素影 响的患者；
[0011] 所述获取模块， 用于从所述天气信息平台获取天气预报信息；
[0012] 判断模块， 用于判断所述患者是否受所述天气预报信息的影响； 及
[0013] 生成模块， 用于当所述患者受所述天气预报信息的影响吋， 生成预警信息并发 送给所述患者所对应的客户端。
[0014] 优选的， 所述医疗数据包括患者姓名、 患者年齢、 患病吋间、 疾病名称、 患病 原因、 药品名称、 药品数量、 医生姓名、 就诊科室、 医疗费用及患者的联系方 式。
[0015] 优选的， 所述天气信息包括地点、 温度、 风向、 天气情况及空气质量。
[0016] 优选的， 所述分析与天气信息关联的医疗数据以获得受天气因素影响的患者的 方式如下：
[0017] 将与天气信息关联的医疗数据进行分类， 以得到每种历史天气信息对应的疾病 名称及每种疾病名称的数量；
[0018] 根据每种疾病名称的数量计算该疾病受天气因素影响的权重；
[0019] 若所述权重超过预设值吋， 则认定该疾病受天气因素影响； 及
[0020] 根据受天气因素影响的疾病名称在医疗数据中检索出受天气因素影响的患者。
[0021] 优选的， 所述预警信息包括患者名称、 天气预报信息、 相同天气情况下所患的 疾病及预防所患的疾病的注意事项。
[0022] 另一方面， 本发明还提供一种医疗大数据分析及预警方法， 应用于数据中心， 所述数据中心通过网络与医院信息系统、 客户端及天气信息平台连接， 该方法 包括：
[0023] 从所述医院信息系统获取医疗数据；
[0024] 搜索医疗数据中的患病日期； [0025] 从所述天气信息平台获取医疗数据中的患病日期所对应的历史天气信息， 并将 医疗数据与所述历史天气信息关联；
[0026] 分析与历史天气信息关联的医疗数据以获得受天气因素影响的患者；
[0027] 从所述天气信息平台获取天气预报信息；
[0028] 根据所述天气预报信息判断是否有受天气因素影响的患者； 及
[0029] 当所述患者受所述天气预报信息的影响吋， 生成预警信息并发送给受天气因素 影响的患者所对应的客户端。
[0030] 优选的， 所述医疗数据包括患者姓名、 患者年齢、 患病吋间、 疾病名称、 患病 原因、 药品名称、 药品数量、 医生姓名、 就诊科室、 医疗费用及患者的联系方 式。
[0031] 优选的， 所述天气信息包括地点、 温度、 风向、 天气情况及空气质量。
[0032] 优选的， 所述分析与天气信息关联的医疗数据以获得受天气因素影响的患者的 方式如下：
[0033] 将与天气信息关联的医疗数据进行分类， 以得到每种历史天气信息对应的疾病 名称及每种疾病名称的数量；
[0034] 根据每种疾病名称的数量计算该疾病受天气因素影响的权重；
[0035] 若所述权重超过预设值吋， 则认定该疾病受天气因素影响； 及
[0036] 根据受天气因素影响的疾病名称在医疗数据中检索受天气因素影响的患者。
[0037] 优选的， 所述预警信息包括患者名称、 天气预报信息、 相同天气情况下所患的 疾病及预防所患的疾病的注意事项。
发明的有益效果
有益效果
[0038] 本发明所述医疗大数据分析及预警系统及方法采用上述技术方案， 带来的技术 效果为： 可以对医疗大数据与天气信息关联， 将通过对与天气信息关联的医疗 大数据分析处理以得到受天气因素影响的患者， 并对所述受天气因素影响的患 者及吋预警， 降低了患者受天气因素影响而再次患病的风险。
对附图的简要说明
附图说明 [0039] 图 1是本发明医疗大数据分析及预警系统的应用环境示意图。
[0040] 图 2是本发明医疗大数据分析及预警系统的优选实施例的模块示意图。
[0041] 图 3是本发明医疗大数据分析及预警方法的优选实施例的流程图。
[0042] 图 4是本发明一种天气信息对应的疾病名称及每种疾病名称的数量的示意图。
[0043] 本发明目的的实现、 功能特点及优点将结合实施例， 参照附图做进一步说明。
实施该发明的最佳实施例
本发明的最佳实施方式
[0044] 为更进一步阐述本发明为达成预定发明目的所采取的技术手段及功效， 以下结 合附图及较佳实施例， 对本发明的具体实施方式、 结构、 特征及其功效， 详细 说明如下。 应当理解， 此处所描述的具体实施例仅仅用以解释本发明， 并不用 于限定本发明。
[0045] 参照图 1所示， 图 1是本发明医疗大数据分析及预警系统的应用环境示意图。 本 发明中的医疗大数据分析及预警系统 20运行于数据中心 2。 所述数据中心 2通过 网络 3与一个或多个医院信息系统 1 (图 1中以三个为例进行说明） 通信连接， 以 从所述医院信息系统连接 1获取医疗数据。 所述医疗数据包括， 但不限于， 患者 姓名、 患者年齢、 患病吋间、 疾病名称、 患病原因、 药品名称、 药品数量、 医 生姓名、 就诊科室、 费用及患者的联系方式 （例如， 电子邮箱地址、 手机号码 、 即吋通信账号等） 等信息。
[0046] 所述网络 3可以是有线通讯网络或无线通讯网络。 所述网络 3优选为无线通讯网 络， 包括但不限于， GSM网络、 GPRS网络、 CDMA网络、 TD-SCDMA网络、 W iMAX网络、 TD-LTE网络、 FDD-LTE网络等无线传输网络。
[0047] 所述数据中心 2通过所述网络 3与一个或多个客户端 4 (图 1中以三个为例进行说 明） 通信连接， 将患者对应的所述医疗数据发送给患者。 在其它实施例中， 所 述数据中心 2还可以对所述医疗数据进行分析处理， 并将分析处理后的医疗数据 (例如， 与历史天气信息关联后的医疗数据） 通过网络 3发送给对应的客户端 4
[0048] 所述数据中心 2通过所述网络 3与天气信息平台 5通信连接， 用于从所述天气信 息平台 5获取历史天气信息及天气预报信息 （也可称为未来天气信息） 。 具体地 说， 所述天气信息平台 5用于提供历史天气信息及天气预报信息， 所述历史天气 信息及天气预报信息均包括， 但不限于， 地点、 温度 （最高气温及最低气温） 、 风向 （例如， 偏南风、 偏北风等） 、 天气情况 （例如， 天晴、 小雨、 大雨、 雪、 大雪等天气情况） 及空气质量 （例如， PM 2.5值） 等信息。
[0049] 需要说明的是， 所述数据中心 2是云平台或数据中心的某一台服务器， 通过云 平台或数据中心的数据传输能力及数据存储能力， 可以更好地管理及 /或协助与 该数据中心 2连接的客户端 4， 有利于患者了解自身的医疗数据。
[0050] 所述客户端 4可以是， 但不限于， 智能手机、 平板电脑、 个人数字助理 （Person al Digital Assistant, PDA) 、 个人电脑、 电子看板等其它任意合适的便携式电子 设备。
[0051] 参照图 2所示， 是本发明医疗大数据分析及预警系统的优选实施例的模块示意 图。 在本实施例中， 所述医疗大数据分析及预警系统 20应用于数据中心 2。 该数 据中心 2包括， 但不仅限于， 医疗大数据分析及预警系统 20、 存储单元 22、 处理 单元 24及通讯单元 26。
[0052] 所述的存储单元 22可以为一种只读存储单元 ROM, 电可擦写存储单元 EEPRO
M、 快闪存储单元 FLASH或固体硬盘等。
[0053] 所述的处理单元 24可以为一种中央处理器 （Central Processing Unit, CPU) 、 微控制器 （MCU) 、 数据处理芯片、 或者具有数据处理功能的信息处理单元。
[0054] 所述的通讯单元 26为一种具有远程无线通讯功能的无线通讯接口， 例如， 支持
GSM、 GPRS、 WCDMA、 CDMA、 TD-SCDMA、 WiMAX、 TD-LTE、 FDD-LT
E等通讯技术的通讯接口。
[0055] 所述医疗大数据分析及预警系统 20包括， 但不局限于， 获取模块 200、 搜索模 块 210、 分析模块 220、 判断模块 230及生成模块 240。 本发明所称的模块是指一 种能够被所述数据中心 2的处理单元 24执行并且能够完成固定功能的一系列计算 机程序指令段， 其存储在所述数据中心 2的存储单元 22中。
[0056] 所述获取模块 200用于从医院信息系统 1获取医疗数据。
[0057] 具体而言， 所述医院信息系统 1提供数据导入接口 （例如， 应用程序接口， App lication Program Interface, API) ， 接入该数据导入接口的设备或系统都可以从 所述医院信息系统 1中获取医疗数据。 所述获取模块 200调用所述医院信息系统 1 提供的 API接口以获取医疗数据。
[0058] 需要说明的是， 由于所述医疗数据属于隐私信息， 为了确保信息安全， 所述医 疗数据发送给数据中心 2吋， 会通过加解密算法 （例如， MD5加解密算法、 RSA 加解密算法、 DES加解密算法、 DSA加解密算法、 AES加解密算法等） 先对医疗 数据进行加密处理， 之后传输给所述数据中心 2。
[0059] 所述搜索模块 210用于搜索医疗数据中的患病日期。 具体地说， 所述搜索模块 2
10通过关键字检索的方式搜索医疗数据中的患病日期。 例如， 以"患病日期"或" 患病吋间"作为关键字， 检索出医疗数据中的患病日期。
[0060] 所述获取模块 200用于从所述天气信息平台 5获取医疗数据中的患病日期所对应 的历史天气信息， 并将医疗数据与所述历史天气信息关联。
[0061] 具体地说， 所述天气信息平台 5提供 API接口， 接入该 API接口的设备或系统都 可以从所述天气信息平台 5中获取历史天气信息及天气预报信息。 所述获取模块 200调用所述天气信息平台 5提供的 API接口以获取历史天气信息及天气预报信息 。 所述获取模块 200调用所述天气信息平台 5提供的 API接口并发送所述患病曰期 给天气信息平台 5， 天气信息平台 5以所述患病日期为关键字， 检索所述患病曰 期对应的历史天气信息以回传给所述数据中心 2。
[0062] 所述分析模块 220用于分析与历史天气信息关联的医疗数据进行以获得受天气 因素影响的患者。
[0063] 所述对与历史天气信息关联的医疗数据进行分析以获得受天气因素影响的患者 的方式如下： （1) 将与历史天气信息关联的医疗数据进行分类， 以得到每种历 史天气信息对应的疾病名称及每种疾病名称的数量， 举例而言， 如图 4所示， 大 雪的天气情况下， 所述医疗数据中有四种疾病， 分别为感冒、 发烧、 哮喘及骨 折， 其中， 感冒有五十八笔、 发烧有二十笔、 哮喘有十五笔及骨折有二十七笔 。 （2) 根据每种疾病名称的数量计算该疾病受天气因素影响的权重。 在本实施 例中， 为了简化起见， 所述计算的权重等于每种疾病名称的数量， 也就是说， 以图 4为例， 哮喘的数量十五笔， 则哮喘受天气因素影响的权重为十五。 （3) 若所述权重超过预设值 （例如， 10) 吋， 则认定该疾病受天气因素影响， 以图 4 为例， 哮喘的数量为 15， 预设值为 10， 则认定哮喘受天气因素影响。 （4) 根据 受天气因素影响的疾病名称在医疗数据中检索出患者， 所述检索的患者即为受 天气因素影响的患者， 例如， 以"哮喘"作为关键字， 在医疗数据中检索出患哮喘 的患者。
[0064] 所述获取模块 200还用于从所述天气信息平台 5获取天气预报信息。 所述天气预 报信息包括未来预设吋间段内的天气信息， 例如， 未来一周的天气信息。
[0065] 所述判断模块 230用于判断所述受天气因素影响的患者是否受所述天气预报信 息的影响。 具体地说， 所述判断模块 230根据所述天气预报信息中的未来预设吋 间段内的天气信息能够检索出受天气因素影响的患者。 如图 4所示， 天气预报信 息为大雪天气， 以大雪为关键字检索出受天气因素影响的哮喘患者。
[0066] 所述生成模块 240用于当所述受天气因素影响的患者受所述天气预报信息的影 响吋， 生成预警信息并发送 （例如， 根据医疗数据中患者的联系方式进行发送 ) 给受天气因素影响的患者所对应的客户端 4。 所述预警信息包括， 但不限于， 患者名称、 天气预报信息、 相同天气情况下所患的疾病、 预防所患的疾病的注 意事项等。 所述预警信息可以以文字、 语音及 /或影音的方式发送给客户端 4。 举 例而言， 所述预警信息为如下文字"尊敬的 XXX， 未来几天将出现寒冷天气， 最 低气温降到零度以下， 以往最低气温降到零度吋， 您出现过哮喘且在第一人民 医院及第二人民医院各就医过一次， 还请注意加强哮喘预防， 以下为预防措施 ， 请参考： （1) 避免到人群聚集； （2) 出门吋， 请携带 N95型号口罩； （3) 注意保暖， 尤其确保头部、 胸背和足部保暖以免着凉； （4) 注意携带支气管扩 张剂、 吸入剂、 雾化剂等药物。 最后， 祝您身体健康！ 。 "
[0067] 参照图 3所示， 是本发明医疗大数据分析及预警方法的优选实施例的流程图。
在本实施例中， 所述的医疗大数据分析及预警方法应用于数据中心 2， 该方法包 括以下步骤：
[0068] 步骤 S10: 所述获取模块 200从医院信息系统 1获取医疗数据。
[0069] 具体而言， 所述医院信息系统 1提供数据导入接口 （例如， 应用程序接口， App lication Program Interface, API) ， 接入该数据导入接口的设备或系统都可以从 所述医院信息系统 1中获取医疗数据。 所述获取模块 200调用所述医院信息系统 1 提供的 API接口以获取医疗数据。
[0070] 需要说明的是， 由于所述医疗数据属于隐私信息， 为了确保信息安全， 所述医 疗数据发送给数据中心 2吋， 会通过加解密算法 （例如， MD5加解密算法、 RSA 加解密算法、 DES加解密算法、 DSA加解密算法、 AES加解密算法等） 先对医疗 数据进行加密处理， 之后传输给所述数据中心 2。
[0071] 步骤 S11 : 所述搜索模块 210搜索医疗数据中的患病日期。 具体地说， 所述搜索 模块 210通过关键字检索的方式搜索医疗数据中的患病日期。 例如， 以"患病日期
"或"患病吋间"作为关键字， 检索出医疗数据中的患病日期。
[0072] 步骤 S12: 所述获取模块 200从所述天气信息平台 5获取医疗数据中的患病曰期 所对应的历史天气信息， 并将医疗数据与所述历史天气信息关联。
[0073] 所述天气信息平台 5提供数据导入接口 （例如， 应用程序接口， Application
Program Interface, API) ， 接入该数据导入接口的设备或系统都可以从所述天气 信息平台 5中获取历史天气信息。 所述获取模块 200调用所述天气信息平台 5提供 的 API接口以获取历史天气信息。
[0074] 具体地说， 所述获取模块 200调用所述天气信息平台 5提供的 API接口并发送所 述患病日期给天气信息平台 5， 天气信息平台 5以所述患病日期为关键字， 检索 所述患病日期对应的历史天气信息以回传给所述数据中心 2。
[0075] 步骤 S13: 所述分析模块 220分析与历史天气信息关联的医疗数据以获得受天气 因素影响的患者。
[0076] 所述对与历史天气信息关联的医疗数据进行分析以获得受天气因素影响的患者 的方式如下： （1) 将与历史天气信息关联的医疗数据进行分类， 以得到每种历 史天气信息对应的疾病名称及每种疾病名称的数量， 举例而言， 如图 4所示， 大 雪的天气情况下， 所述医疗数据中有四种疾病， 分别为感冒、 发烧、 哮喘及骨 折， 其中， 感冒有五十八笔、 发烧有二十笔、 哮喘有十五笔及骨折有二十七笔 。 （2) 根据每种疾病名称的数量计算该疾病受天气因素影响的权重。 在本实施 例中， 为了简化起见， 所述计算的权重等于每种疾病名称的数量， 也就是说， 以图 4为例， 哮喘的数量十五笔， 则哮喘受天气因素影响的权重为十五。 （3) 若所述权重超过预设值 （例如， 10) 吋， 则认定该疾病受天气因素影响， 以图 4 为例， 哮喘的数量为 15， 预设值为 10， 则认定哮喘受天气因素影响。 （4) 根据 受天气因素影响的疾病名称在医疗数据中检索出患者， 所述检索的患者即为受 天气因素影响的患者， 例如， 以"哮喘"作为关键字， 在医疗数据中检索出患哮喘 的患者。
[0077] 步骤 S14: 所述获取模块 200从所述天气信息平台 5获取天气预报信息。 所述天 气预报信息包括未来预设吋间段内的天气信息， 例如， 未来一周的天气信息。
[0078] 步骤 S15: 所述判断模块 230用于判断所述受天气因素影响的患者是否受所述天 气预报信息的影响。 具体地说， 若通过所述天气预报信息在所述受天气因素影 响的患者中进行检索， 若存在受天气预报因素影响的患者， 则需要通知受天气 因素影响的患者， 如图 4所示， 天气预报信息为大雪天气， 以大雪为关键字检索 出受天气因素影响的哮喘患者， 流程进入步骤 S16。 否则， 若所述受天气因素影 响的患者不受所述天气预报信息的影响， 返回步骤 S14。
[0079] 步骤 S16: 所述生成模块 240生成预警信息， 并发送给受天气因素影响的患者所 对应的客户端 4。 所述预警信息包括， 但不限于， 患者名称、 天气预报信息、 相 同天气情况下所患的疾病、 预防所患的疾病的注意事项等。 所述预警信息可以 以文字、 语音及 /或影音的方式发送给客户端 4。 举例而言， 所述预警信息为如下 文字"尊敬的 XXX， 未来几天将出现寒冷天气， 最低气温降到零度以下， 以往最 低气温降到零度吋， 您出现过哮喘且在第一人民医院及第二人民医院各就医过 一次， 还请注意加强哮喘预防， 以下为预防措施， 请参考： （1) 避免到人群聚 集； （2) 出门吋， 请携带 N95型号口罩； （3) 注意保暖， 尤其确保头部、 胸背 和足部保暖以免着凉； （4) 注意携带支气管扩张剂、 吸入剂、 雾化剂等药物。 最后， 祝您身体健康！ "
[0080] 以上仅为本发明的优选实施例， 并非因此限制本发明的专利范围， 凡是利用本 发明说明书及附图内容所作的等效结构或等效流程变换， 或直接或间接运用在 其他相关的技术领域， 均同理包括在本发明的专利保护范围内。
工业实用性
[0081] 本发明所述医疗大数据分析及预警系统及方法采用上述技术方案， 带来的技术 效果为： 可以对医疗大数据与天气信息关联， 将通过对与天气信息关联的医疗 大数据分析处理以得到受天气因素影响的患者， 并对所述受天气因素影响的患 者及吋预警， 降低了患者受天气因素影响而再次患病的风险。

Claims

权利要求书
[权利要求 1] 一种医疗大数据分析及预警系统， 运行于数据中心， 其特征在于， 所 述数据中心通过网络与医院信息系统、 客户端及天气信息平台连接， 所述医疗大数据分析及预警系统包括： 获取模块， 用于从所述医院信 息系统获取医疗数据； 搜索模块， 用于搜索医疗数据中的患病日期； 所述获取模块， 用于从所述天气信息平台获取医疗数据中的患病曰期 所对应的历史天气信息， 并将医疗数据与所述历史天气信息关联； 分 析模块， 用于分析与所述历史天气信息关联的医疗数据以获得受天气 因素影响的患者； 所述获取模块， 用于从所述天气信息平台获取天气 预报信息； 判断模块， 用于判断所述患者是否受所述天气预报信息的 影响； 及生成模块， 用于当所述患者受所述天气预报信息的影响吋， 生成预警信息并发送给所述患者所对应的客户端。
[权利要求 2] 如权利要求 1所述的医疗大数据分析及预警系统， 其特征在于， 所述 医疗数据包括患者姓名、 患者年齢、 患病吋间、 疾病名称、 患病原因 、 药品名称、 药品数量、 医生姓名、 就诊科室、 医疗费用及患者的联 系方式。
[权利要求 3] 如权利要求 1所述的医疗大数据分析及预警系统， 其特征在于， 所述 天气信息包括地点、 温度、 风向、 天气情况及空气质量。
[权利要求 4] 如权利要求 1至 3任一项所述的医疗大数据分析及预警系统， 其特征在 于， 所述分析与天气信息关联的医疗数据以获得受天气因素影响的患 者的方式如下： 将与天气信息关联的医疗数据进行分类， 以得到每种 历史天气信息对应的疾病名称及每种疾病名称的数量； 根据每种疾病 名称的数量计算该疾病受天气因素影响的权重； 若所述权重超过预设 值吋， 则认定该疾病受天气因素影响； 及根据受天气因素影响的疾病 名称在医疗数据中检索出受天气因素影响的患者。
[权利要求 5] 如权利要求 1所述的医疗大数据分析及预警系统， 其特征在于， 所述 预警信息包括患者名称、 天气预报信息、 相同天气情况下所患的疾病 及预防所患的疾病的注意事项。
[权利要求 6] 一种医疗大数据分析及预警方法， 应用于数据中心， 其特征在于， 所 述数据中心通过网络与医院信息系统、 客户端及天气信息平台连接， 该方法包括： 从所述医院信息系统获取医疗数据； 搜索医疗数据中的 患病日期； 从所述天气信息平台获取医疗数据中的患病日期所对应的 历史天气信息， 并将医疗数据与所述历史天气信息关联； 分析与历史 天气信息关联的医疗数据以获得受天气因素影响的患者； 从所述天气 信息平台获取天气预报信息； 根据所述天气预报信息判断是否有受天 气因素影响的患者； 及当所述患者受所述天气预报信息的影响吋， 生 成预警信息并发送给受天气因素影响的患者所对应的客户端。
[权利要求 7] 如权利要求 6所述的医疗大数据分析及预警方法， 其特征在于， 所述 医疗数据包括患者姓名、 患者年齢、 患病吋间、 疾病名称、 患病原因 、 药品名称、 药品数量、 医生姓名、 就诊科室、 医疗费用及患者的联 系方式。
[权利要求 8] 如权利要求 6所述的医疗大数据分析及预警方法， 其特征在于， 所述 天气信息包括地点、 温度、 风向、 天气情况及空气质量。
[权利要求 9] 如权利要求 6至 8任一项所述的医疗大数据分析及预警方法， 其特征在 于， 所述分析与天气信息关联的医疗数据以获得受天气因素影响的患 者的方式如下： 将与天气信息关联的医疗数据进行分类， 以得到每种 历史天气信息对应的疾病名称及每种疾病名称的数量； 根据每种疾病 名称的数量计算该疾病受天气因素影响的权重； 若所述权重超过预设 值吋， 则认定该疾病受天气因素影响； 及根据受天气因素影响的疾病 名称在医疗数据中检索受天气因素影响的患者。
[权利要求 10] 如权利要求 6所述的医疗大数据分析及预警方法， 其特征在于， 所述 预警信息包括患者名称、 天气预报信息、 相同天气情况下所患的疾病 及预防所患的疾病的注意事项。
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