WO2020119385A1 - Procédé, dispositif, équipement et support de surveillance de génération de prescription sur la base d'une analyse de données - Google Patents

Procédé, dispositif, équipement et support de surveillance de génération de prescription sur la base d'une analyse de données Download PDF

Info

Publication number
WO2020119385A1
WO2020119385A1 PCT/CN2019/118836 CN2019118836W WO2020119385A1 WO 2020119385 A1 WO2020119385 A1 WO 2020119385A1 CN 2019118836 W CN2019118836 W CN 2019118836W WO 2020119385 A1 WO2020119385 A1 WO 2020119385A1
Authority
WO
WIPO (PCT)
Prior art keywords
drug
prescription
target
medication
information
Prior art date
Application number
PCT/CN2019/118836
Other languages
English (en)
Chinese (zh)
Inventor
吴密彬
Original Assignee
平安医疗健康管理股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 平安医疗健康管理股份有限公司 filed Critical 平安医疗健康管理股份有限公司
Publication of WO2020119385A1 publication Critical patent/WO2020119385A1/fr

Links

Classifications

    • 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
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G16H20/13—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers

Definitions

  • This application relates to the medical field, and in particular, to a prescription generation monitoring method, device, equipment, and medium based on data analysis.
  • the main purpose of this application is to provide prescription generation monitoring methods, devices, equipment and media based on data analysis, aiming to realize the automatic generation of prescriptions based on the medical records of doctors, effectively ensuring that the dosage of each drug in the prescriptions is more scientific reasonable.
  • the present application provides a prescription generation monitoring method based on data analysis.
  • the data analysis based prescription generation monitoring method includes the following steps:
  • prescription information includes the target drug, determine whether the target drug strategy of the target drug is optimal;
  • the prescription information is added to a preset prescription template to form a prescription form and output.
  • the present application also provides a prescription generation monitoring device based on data analysis.
  • the data analysis based prescription generation monitoring device includes:
  • the receiving module is used to receive the prescription generation request and obtain the medical record entered by the doctor;
  • An information generation module which is used to generate prescription information according to the disease diagnosis information and the medical information in the medical record;
  • the first judgment module is used for judging whether the prescription information includes the target medicine
  • the second judgment module is used to judge whether the target medication strategy of the target medicine is optimal if the prescription information includes the target medicine;
  • the prescription generation module is configured to add the prescription information to a preset prescription template to form a prescription form and output if the target medication strategy of the target medicine has been optimized.
  • the prescription analysis monitoring device based on data analysis includes: a memory, a processor, and computer-readable instructions stored on the memory and executable on the processor, wherein:
  • the method, device, equipment and computer storage medium for prescription generation and monitoring based on data analysis proposed in the embodiments of the present application obtain the diagnosis and treatment record input by the doctor by receiving the prescription generation request; according to the disease diagnosis information and the medical order information in the diagnosis and treatment record Generate prescription information; determine whether the prescription information includes the target drug; if the prescription information includes the target drug, determine whether the target drug strategy of the target drug is optimal; if the target drug strategy of the target drug is Optimally, the prescription information is added to a preset prescription template to form a prescription form and output.
  • the server performs big data analysis to realize the automatic generation of prescriptions in accordance with the medication specifications based on the doctor's medical records and medication information, effectively ensuring that the dosage of each drug in the prescription is more scientific and reasonable.
  • the doctor inputs disease diagnosis information and medical order information to the server, and the server obtains the disease diagnosis information and medical order information in the medical record (where the medical order information includes: medical order time period , The amount of single-use medication and the duration of drug use of the doctor's order) to obtain the disease type in the disease diagnosis information;
  • the server queries the preset drug database to obtain the drug ID associated with the disease type and the drug instructions corresponding to each drug ID Generating a medication strategy for the drug corresponding to each drug identifier based on the drug usage instructions corresponding to each drug identifier and the medication information prescribed by the doctor;
  • the server summarizes the medication strategy for the drug corresponding to each drug identifier to obtain prescription information.
  • FIG. 1 is a server of a hardware operating environment involved in an embodiment of the present application (also called a prescription analysis monitoring device based on data analysis, where the prescription analysis monitoring device based on data analysis may be a separate data-based
  • the analyzed prescription generation and monitoring device may be formed by combining other devices with the prescription analysis and monitoring device based on data analysis.
  • the server in the embodiment of the present application refers to a computer that manages resources and provides services to users, and is generally divided into a file server, a database server, and an application-readable instruction server.
  • a computer or computer system running the above software is also called a server.
  • the server may include a processor 1001, such as a central processor (Central Processing Unit, CPU), network interface 1004, user interface 1003, memory 1005, communication bus 1002, chipset, disk system, network and other hardware.
  • the communication bus 1002 is used to implement connection communication between these components.
  • the computer software product is stored in a storage medium (storage medium: also called computer storage medium, computer medium, readable medium, readable storage medium, computer readable storage medium, or directly called medium, etc., such as RAM , Disk, CD), including several instructions to enable a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to perform the method described in each embodiment of this application, as a computer
  • the memory 1005 of the storage medium may include an operating system, a network communication module, a user interface module, and computer-readable instructions.
  • the network interface 1004 is mainly used to connect to the back-end database and perform data communication with the back-end database;
  • the user interface 1003 is mainly used to connect to the client and perform data communication with the client;
  • the processor 1001 can be used to Invoke the computer readable instructions stored in the memory 1005, and execute the steps in the recipe generation monitoring method based on data analysis provided by the following embodiments of the present application.
  • This application provides a prescription generation and monitoring device based on data analysis, and proposes a first embodiment of a prescription generation and monitoring method based on data analysis.
  • the server obtains a diagnosis and treatment record input by a doctor, and uses the diagnosis information and the medicine prescribed by the doctor in the diagnosis and treatment record.
  • the information generates prescription information.
  • the server can monitor each medication in the prescription information to realize the automatic generation of prescriptions. Specifically:
  • the data analysis-based prescription generation monitoring method includes:
  • the diagnosis and treatment records include but are not limited to: disease diagnosis information (disease diagnosis information includes: disease type, disease condition and disease history, etc.), medical order medication information (medical order medication information includes medical order medication time period, medical order single dose and drug use Duration, etc.) and patient characteristic information (patient characteristic information includes patient height and weight, patient gender, patient age, ethnicity, genetics and induction, etc.), etc., factors that affect prescription medication.
  • disease diagnosis information includes: disease type, disease condition and disease history, etc.
  • medical order medication information includes medical order medication time period, medical order single dose and drug use Duration, etc.
  • patient characteristic information patient height and weight, patient gender, patient age, ethnicity, genetics and induction, etc.
  • step S20 prescription information is generated according to the disease diagnosis information and the medical information in the medical record.
  • the server can generate prescription information based on the disease diagnosis information and medical order medication information in the medical record, for example:
  • Implementation method 1 The server obtains the disease diagnosis information and medical order medication information in the diagnosis and treatment record (the medical order medication information includes: the medical order medication time period, the medical order single dosage and the duration of drug use), and acquires the disease in the disease diagnosis information Type, the server queries the preset drug database to obtain the drug ID associated with the disease type and the drug use instructions corresponding to each drug ID; based on the drug use instructions corresponding to each drug ID and the medication information prescribed by the doctor, each The drug identification corresponds to the drug use strategy of the drug; the drug use strategy of the drug corresponding to each drug identification is aggregated to obtain prescription information.
  • the medical order medication information includes: the medical order medication time period, the medical order single dosage and the duration of drug use
  • the server queries the preset drug database to obtain the drug ID associated with the disease type and the drug use instructions corresponding to each drug ID; based on the drug use instructions corresponding to each drug ID and the medication information prescribed by the doctor, each The drug identification corresponds to the drug use strategy of the drug; the drug use strategy of the drug
  • Implementation method 2 The server receives the doctor's input of the disease type, the server obtains the drug information related to the disease type, and the server displays the drug information for the doctor to edit the drug information.
  • the doctor can select one drug or multiple drugs in the drug information and set The dosage of each medicine is edited with the medicine information to generate prescription information.
  • the server generates prescription information based on the disease diagnosis information and the medical information in the medical record entered by the doctor.
  • the automatic generation of prescriptions is realized, and doctors do not need to manually write prescription information, which reduces the tedious work of manually inputting prescription information of doctors, and effectively avoids irregularities of doctors manually writing prescriptions.
  • the target medicine can be a special medicine (special medicine refers to a collective name for a disease-specific medicine. Due to the high price of special medicine, the actual medical reimbursement often has a great impact on reimbursement. Therefore, the prescription needs to be Special drugs for monitoring), target drugs can also be drugs with high side effects or use of controlled drugs, etc.
  • special medicine refers to a collective name for a disease-specific medicine. Due to the high price of special medicine, the actual medical reimbursement often has a great impact on reimbursement. Therefore, the prescription needs to be Special drugs for monitoring), target drugs can also be drugs with high side effects or use of controlled drugs, etc.
  • Implementation method 1 Determine the target drug according to the monitoring level of the drug to determine whether the prescription information contains the target drug, specifically :
  • step d1 if there is no drug whose monitoring level is higher than a preset threshold, the prescription information does not include the target drug.
  • the server obtains each drug identifier in the prescription information, and queries a preset drug grade table (the preset drug grade table refers to a preset monitoring grade table corresponding to each drug), and the terminal obtains the drug corresponding to each drug identifier.
  • the preset drug grade table refers to a preset monitoring grade table corresponding to each drug
  • Implementation method 2 preset the target drug identification set (the identification information of each target drug is preset in the preset target drug identification set, for example, the antibiotic identification is set in the preset target drug identification set), and the prescription information is determined Whether the target drug is included, specifically:
  • Step a2 Obtain each drug identifier in the prescription information, and compare each drug identifier with each preset identifier in the preset target drug identifier set;
  • Step b2 If the preset target drug identifier set has a preset identifier matching the drug identifier, the prescription information includes the target drug;
  • Step c2 If there is no preset identifier matching the medicine identifier in the preset target medicine identifier set, the prescription information does not include the target medicine.
  • step S40 if the prescription information includes the target drug, it is determined whether the target drug strategy of the target drug is optimal.
  • step S50 if the target medication strategy of the target medicine has been optimized, the prescription information is added to a preset prescription template to form a prescription form and output.
  • the server adds the prescription information to a preset prescription template (the preset prescription template refers to a preset blank document for entering prescription information) to form a prescription form and output .
  • a preset prescription template refers to a preset blank document for entering prescription information
  • a second embodiment of the prescription generation monitoring method of the present application based on data analysis is proposed. This embodiment is a refinement of step S20 in the first embodiment.
  • Data analysis and monitoring methods for prescription generation include:
  • Step S21 Obtain disease diagnosis information and medical order medication information in the diagnosis and treatment record, and obtain disease type in the disease diagnosis information.
  • the server queries the preset drug database (the preset drug database records various drug information (the drug information includes but is not limited to: drug applicability, drug instructions, drug formula, drug duration, drug origin, generic name, product name, usage and dosage , Adverse reactions, contraindications, precautions, etc.), and in the preset drug database, according to the drug information of each drug, the drug label and the type of disease are associated with each other.
  • the server obtains the drug identifier associated with the disease type, and after obtaining the drug identifier associated with the disease type, the server uses the drug corresponding to the drug identifier associated with the disease type as the drug plan in the prescription.
  • the server It is also necessary to determine the dose of the medicine in the prescription, that is, the server obtains the instructions for using the medicine corresponding to each of the medicine identifiers, so as to determine the dose of the prescription medicine according to the instructions for using the medicine.
  • the server aggregates the medication strategies of the drugs corresponding to the drug identifiers, and obtains the prescription information.
  • the server can automatically generate prescription information without the need for a doctor to manually prescribe.
  • the prescription generation model in this embodiment can accurately determine the dosage of each drug, effectively ensuring the dosage of each drug in the prescription Scientific and reasonable.
  • Step S44 if the target medication strategy matches the theoretical medication strategy, it is determined that the target medication strategy is optimal.
  • the server determines that the target medication strategy is optimal. At this time, the server may return to perform step S50 in the first embodiment, that is, the server adds the prescription information to a preset prescription template to form a prescription form and outputs it.
  • the prescription of the target drug is obtained through different processing models, and the dosage of the target drug is monitored according to the comparison result of the target drug strategy and the theoretical drug strategy, so that the dose of the target drug is more reasonable.
  • Step S45 if the target medication strategy does not match the theoretical medication strategy, it is determined that the target medication strategy is not optimal.
  • the target medication strategy does not match the theoretical medication strategy, it is determined that the target medication strategy is not optimal, that is, the dose of the target medicine calculated multiple times is different, and the dose of the target medicine needs to be adjusted.
  • Step S60 if the target medication strategy of the target drug is not optimal, adjust the target medication strategy according to the theoretical medication strategy of the target medication; when it is detected that the target medication strategy matches the theoretical medication strategy of the target medication , Add the prescription information to a preset prescription template to form a prescription form and output it.
  • a fourth embodiment of the data generation-based prescription generation monitoring method of the application is proposed.
  • the prescription list can be monitored and queried, and the data analysis-based prescription generation
  • the monitoring methods include:
  • Step S70 Obtain the patient identity information in the prescription form, query the preset medical insurance management platform to obtain the personal medical insurance corresponding to the patient identity information; associate and save the prescription form with the personal medical insurance, so as to query the prescription form monitor.
  • the server obtains the patient's identity information in the prescription (the patient's identity information refers to the patient's ID number, or the patient's name, etc.), and the server queries the preset medical insurance management platform based on the patient's identity information (the preset medical insurance management platform refers to A pre-set medical insurance information management platform, for example, a social medical insurance database), the server obtains the personal medical insurance corresponding to the patient identification information of the preset medical insurance management platform; associates the prescription form with the personal medical insurance for prescription Single query monitoring.
  • the server associates prescription information with personal medical insurance.
  • it is convenient for querying prescription information.
  • it allows information to communicate and can effectively monitor medical insurance.
  • this embodiment is proposed.
  • the user applies for medical insurance claims based on the generated prescription form, and the server audits the medical insurance claims.
  • the data analysis-based prescription generation monitoring Methods include:
  • the user triggers a medical claims review request on the terminal, the server receives the medical insurance review request, and the server obtains the prescription form to be reviewed in the medical insurance review request and the drug identifier in the prescription form, that is, the server determines the type of drug contained in the prescription form .
  • Step S100 if the drug identification set includes a special drug identification, obtain a special drug prescription corresponding to the special drug identification; according to the special drug prescription, determine whether the use of the special drug corresponding to the special drug identification is reasonable, and Export medical insurance review conclusions.
  • the server obtains the special medicine prescription corresponding to the special medicine identifier; the server obtains the special medicine dose in the special medicine prescription and determines whether the dose of the special medicine exceeds the preset standard (The preset standard refers to the pre-set drug dose threshold value). If the dose of the special drug exceeds the preset standard, it is determined that the use of the special drug corresponding to the special drug label is unreasonable, and the conclusion that the medical insurance review fails is output; If the dose of the medicine does not exceed the preset standard, it is determined that the special medicine corresponding to the special medicine identifier is used reasonably, and the conclusion passed by the medical insurance review is output.
  • the preset standard refers to the pre-set drug dose threshold value
  • the server obtains the prescription form to determine whether the prescription contains special medicine claims. If the medical insurance claims include special medicine claims, it determines whether the special medicines comply with the medication rules. In this application, the medical insurance review carefully reviewed the special medicines to meet the medication The rules enable comprehensive and accurate medical insurance claims review for medical insurance drugs.
  • an embodiment of the present application also provides an embodiment of a prescription generation monitoring device based on data analysis, and the data analysis based prescription generation monitoring device includes:
  • the receiving module 10 is used to receive a prescription generation request and obtain a medical record entered by a doctor;
  • the information generating module 20 is used to generate prescription information according to the disease diagnosis information and the medical information in the medical record;
  • the first judgment module 30 is used to judge whether the prescription information includes the target medicine
  • the second judgment module 40 is used to judge whether the target medication strategy of the target medicine is optimal if the prescription information includes the target medicine;
  • the information generating module 20 includes:
  • An obtaining unit configured to obtain disease diagnosis information and medical order information in the diagnosis and treatment record, and obtain a disease type in the disease diagnosis information, wherein the medical order information includes: the time period of the medical order, the single dose of the medical order And the duration of use of medicines;
  • the query unit is used to query a preset drug database to obtain the drug ID associated with the disease type and the drug instructions corresponding to each drug ID;
  • a generating unit configured to generate a medication strategy for the drug corresponding to each of the drug identifiers based on the drug instructions corresponding to each of the drug identifiers and the medication information of the doctor's order;
  • the summarizing unit is used for summarizing the medication strategies of the drugs corresponding to the drug identifiers to obtain prescription information.
  • the first judgment module 30 includes:
  • the comparison and judgment unit is used to compare the monitoring level of each medicine with a preset threshold to determine whether there is a medicine with a monitoring level higher than the preset threshold;
  • the conclusion output unit is used to include the target drug in the prescription information if the monitoring level of the existing drug is higher than the preset threshold; if the monitoring level of the non-existent drug is higher than the preset threshold, the target information is not included in the prescription information drug.
  • An obtaining unit configured to obtain the patient body surface data of the diagnosis and treatment record if the prescription information includes the target medicine
  • the information input unit is used to input the target drug identifier of the target drug and the patient's body surface data to a preset dosage prediction model to obtain the theoretical drug strategy of the target drug;
  • a comparison output unit for obtaining the target medication strategy of the target medication in the prescription information, comparing the target medication strategy with the theoretical medication strategy; if the target medication strategy matches the theoretical medication strategy , It is determined that the target medication strategy is optimal; if the target medication strategy does not match the theoretical medication strategy, it is determined that the target medication strategy is not optimal.
  • the prescription generation monitoring device based on data analysis includes:
  • a prescription adjustment module configured to adjust the target medication strategy according to the theoretical medication strategy of the target medication if the target medication strategy of the target medication is not optimal;
  • the detection output module is configured to add the prescription information to a preset prescription template to form a prescription form and output when it detects that the target medication strategy matches the theoretical medication strategy of the target medication.
  • the prescription generation monitoring device based on data analysis includes:
  • a medical insurance acquisition module for acquiring patient identity information in the prescription form, querying a preset medical insurance management platform, and acquiring personal medical insurance corresponding to the patient identity information;
  • the associated preservation module is used to associate and save the prescription form with the personal medical insurance, so as to query and monitor the prescription form.
  • the prescription generation monitoring device based on data analysis further includes:
  • a receiving and reviewing module for receiving a medical insurance review request, and obtaining the prescription form to be reviewed in the medical insurance review request and the drug identification in the prescription form;
  • a summary judgment module configured to aggregate each of the drug identifiers to form a drug identifier set, and determine whether the drug identifier set contains a special drug identifier
  • the conclusion output module is used to judge whether the use of the special medicine corresponding to the special medicine identifier is reasonable according to the special medicine prescription, and output the medical insurance audit conclusion.
  • embodiments of the present application also provide a computer storage medium.
  • Computer-readable instructions are stored on the computer storage medium, and when executed by the processor, the computer-readable instructions implement the operations in the prescription generation monitoring method based on data analysis provided by the foregoing embodiments.

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medicinal Chemistry (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

Procédé, dispositif, équipement et un support de surveillance de génération de prescription sur la base d'une analyse de données. Le procédé comprend les étapes suivantes consistant à : recevoir une demande de génération de prescription, acquérir un dossier de diagnostic entré par un médecin (S10) ; générer des informations de prescription sur la base d'informations de diagnostic de maladie et d'informations de médication prescrites dans le dossier de diagnostic (S20) ; déterminer si les informations de prescription comprennent un médicament cible (S30) ; si les informations de prescription comprennent le médicament cible, alors déterminer si une stratégie de médication cible pour le médicament cible est optimale (S40) ; et si la stratégie de médication cible pour le médicament cible est optimale, alors ajouter les informations de prescription à un modèle de prescription prédéfini pour former une prescription et délivrer celle-ci (S50). Dans les procédé, dispositif, équipement et support, un serveur met en oeuvre la génération automatisée de la prescription sur la base du dossier de diagnostic du médecin sur la base d'une analyse de mégadonnées médicales, garantissant ainsi efficacement que le dosage des médicaments dans la prescription est scientifique et raisonnable.
PCT/CN2019/118836 2018-12-13 2019-11-15 Procédé, dispositif, équipement et support de surveillance de génération de prescription sur la base d'une analyse de données WO2020119385A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811529286.7 2018-12-13
CN201811529286.7A CN109637620A (zh) 2018-12-13 2018-12-13 基于数据分析的处方生成监测方法、装置、设备和介质

Publications (1)

Publication Number Publication Date
WO2020119385A1 true WO2020119385A1 (fr) 2020-06-18

Family

ID=66073768

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/118836 WO2020119385A1 (fr) 2018-12-13 2019-11-15 Procédé, dispositif, équipement et support de surveillance de génération de prescription sur la base d'une analyse de données

Country Status (2)

Country Link
CN (1) CN109637620A (fr)
WO (1) WO2020119385A1 (fr)

Families Citing this family (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109637620A (zh) * 2018-12-13 2019-04-16 平安医疗健康管理股份有限公司 基于数据分析的处方生成监测方法、装置、设备和介质
CN110164524A (zh) * 2019-04-29 2019-08-23 北京国润健康医学投资有限公司 一种偏瘫患者康复训练任务自适应匹配方法及其系统
CN110391006A (zh) * 2019-07-23 2019-10-29 夹江县人民医院 用于医保结算的药物自标方法
CN111009300B (zh) * 2019-10-23 2023-06-30 广州中医药大学第二附属医院 一种中药调剂中的药袋标签生成方法及系统
CN111190931A (zh) * 2019-11-25 2020-05-22 泰康保险集团股份有限公司 一种处方笺数据的处理方法及装置、电子设备、存储介质
CN111063413A (zh) * 2019-12-30 2020-04-24 广州享药户联优选科技有限公司 基于用药情况调整用药方案的方法及装置
CN111161841B (zh) * 2019-12-30 2021-06-01 安徽省立医院 智能肠外营养医嘱系统
CN111145864A (zh) * 2019-12-31 2020-05-12 广州享药户联优选科技有限公司 基于智能药箱的用药控制方法及装置、智能药箱
CN116882377A (zh) * 2021-01-08 2023-10-13 云南力衡医疗技术有限公司 一种处方的生成方法、装置及设备
CN112164441B (zh) * 2020-10-07 2022-09-27 上海常笑健康咨询服务有限公司 基于互联网的在线实时全肠外营养处方合理性优化系统
CN113380362A (zh) * 2021-06-18 2021-09-10 安徽科大讯飞医疗信息技术有限公司 慢病监管方法、平台、系统、电子设备和存储介质
CN113658659B (zh) * 2021-08-20 2023-07-21 深圳平安智慧医健科技有限公司 医疗信息的处理方法、装置、计算机设备和存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030055686A1 (en) * 2001-09-20 2003-03-20 Sharp Kabushiki Kaisha Medical information system
CN102012960A (zh) * 2009-09-07 2011-04-13 北京韩美智恒科技有限公司 基于医疗信息系统的医嘱处理方法
CN105868531A (zh) * 2016-03-23 2016-08-17 遵义医学院 一种基于医疗大数据的自动辅助处方系统及方法
CN106096319A (zh) * 2016-07-14 2016-11-09 广州宝荣科技应用有限公司 一种处方管理应用系统
CN109637620A (zh) * 2018-12-13 2019-04-16 平安医疗健康管理股份有限公司 基于数据分析的处方生成监测方法、装置、设备和介质

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103617343B (zh) * 2013-11-06 2016-08-17 中国人民解放军第四军医大学 一种急诊电子病历系统及其信息处理方法
CN105701342B (zh) * 2016-01-12 2018-05-22 西北工业大学 基于代理的直觉模糊理论医疗诊断模型的构建方法及装置
CN107341345A (zh) * 2017-06-22 2017-11-10 厦门大学 一种基于电子病历大数据的临床合理用药风险评估方法
CN107451401A (zh) * 2017-07-11 2017-12-08 武汉金豆医疗数据科技有限公司 一种医保智能审核方法和系统
CN107403069B (zh) * 2017-07-31 2020-05-12 京东方科技集团股份有限公司 一种药物-疾病关联关系分析系统及方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030055686A1 (en) * 2001-09-20 2003-03-20 Sharp Kabushiki Kaisha Medical information system
CN102012960A (zh) * 2009-09-07 2011-04-13 北京韩美智恒科技有限公司 基于医疗信息系统的医嘱处理方法
CN105868531A (zh) * 2016-03-23 2016-08-17 遵义医学院 一种基于医疗大数据的自动辅助处方系统及方法
CN106096319A (zh) * 2016-07-14 2016-11-09 广州宝荣科技应用有限公司 一种处方管理应用系统
CN109637620A (zh) * 2018-12-13 2019-04-16 平安医疗健康管理股份有限公司 基于数据分析的处方生成监测方法、装置、设备和介质

Also Published As

Publication number Publication date
CN109637620A (zh) 2019-04-16

Similar Documents

Publication Publication Date Title
WO2020119385A1 (fr) Procédé, dispositif, équipement et support de surveillance de génération de prescription sur la base d'une analyse de données
WO2020119116A1 (fr) Procédé, appareil et dispositif de vérification d'assurance médicale basés sur l'analyse de données et support de stockage
WO2020119384A1 (fr) Procédé, appareil et dispositif de détection d'anomalie d'assurance médicale sur la base d'une analyse de mégadonnées, et support
WO2020078058A1 (fr) Procédé et dispositif d'identification d'anomalies de données médicales, terminal et support de stockage
WO2020119131A1 (fr) Procédé et dispositif d'identification d'anomalies de régime médicamenteux, terminal et support de stockage lisible
WO2020108111A1 (fr) Procédé d'identification de comportement de fraude d'assurance médicale, appareil, dispositif et support de mémoire lisible
WO2020113960A1 (fr) Procédé, appareil et dispositif de délivrance de médicaments sur ordonnance partagée, et support de stockage
WO2020087981A1 (fr) Procédé et appareil de génération de modèle d'audit de contrôle de risque, dispositif, et support de stockage lisible
WO2018205373A1 (fr) Procédé et appareil d'estimation de dépenses de dommages corporels et de dépenses de règlement de sinistre, serveur et support
WO2020125251A1 (fr) Procédé d'apprentissage de paramètres de modèle basé sur un apprentissage fédéré, dispositif, appareil et support
JP5967408B2 (ja) 情報取得端末装置および情報取得方法、並びにプログラム
WO2020119402A1 (fr) Procédé et appareil d'identification de médicaments inappropriés, terminal et support de stockage lisible par ordinateur
WO2020113959A1 (fr) Procédé, appareil et dispositif d'évaluation de niveau de dialyse d'institution médicale et support d'informations
WO2020119176A1 (fr) Procédé de vérification de données de remboursement, serveur d'identification et support de stockage
WO2020147385A1 (fr) Procédé et appareil d'entrée de données, terminal et support d'informations lisible par ordinateur
WO2020119403A1 (fr) Procédé, appareil et dispositif de détection d'anomalie de données d'hospitalisation, et support d'informations lisible
WO2020107895A1 (fr) Procédé et appareil de génération de rapport d'examen de maladie chronique, dispositif et support d'informations
WO2020119383A1 (fr) Procédé de supervision d'assurance médicale, dispositif, appareil et support de stockage lisible par ordinateur
WO2020224250A1 (fr) Procédé, appareil et dispositif pour déclenchement de contrat intelligent, et support de stockage
WO2020147384A1 (fr) Procédé, dispositif et appareil de transaction sécurisée à base de chaîne de blocs, et support de stockage
WO2020107899A1 (fr) Procédé, dispositif et équipement de prédiction de coût médical, et support d'informations lisible par ordinateur
WO2020226456A1 (fr) Procédé et dispositif pour fournir des informations médicales par l'intermédiaire d'informations de prescription
WO2020019405A1 (fr) Procédé, dispositif, appareil de surveillance de base de données et support d'informations informatique
WO2020087704A1 (fr) Procédé, appareil et dispositif de gestion d'informations de crédit et support d'enregistrement
WO2020119175A1 (fr) Procédé de contrôle d'anomalies de frais médicaux, serveur de contrôle et support d'enregistrement

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19896835

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 15/10/2021)

122 Ep: pct application non-entry in european phase

Ref document number: 19896835

Country of ref document: EP

Kind code of ref document: A1