WO2018010105A1 - 处方用药信息合理性数据特征分析系统 - Google Patents

处方用药信息合理性数据特征分析系统 Download PDF

Info

Publication number
WO2018010105A1
WO2018010105A1 PCT/CN2016/089837 CN2016089837W WO2018010105A1 WO 2018010105 A1 WO2018010105 A1 WO 2018010105A1 CN 2016089837 W CN2016089837 W CN 2016089837W WO 2018010105 A1 WO2018010105 A1 WO 2018010105A1
Authority
WO
WIPO (PCT)
Prior art keywords
prescription
drug
information
data
risk
Prior art date
Application number
PCT/CN2016/089837
Other languages
English (en)
French (fr)
Inventor
曹庆恒
Original Assignee
曹庆恒
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 曹庆恒 filed Critical 曹庆恒
Priority to PCT/CN2016/089837 priority Critical patent/WO2018010105A1/zh
Priority to CN201680087137.2A priority patent/CN110024039A/zh
Publication of WO2018010105A1 publication Critical patent/WO2018010105A1/zh

Links

Images

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
    • 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
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work
    • 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 invention relates to the technical field of intelligent prescription information processing, in particular to a method and system for intelligently analyzing prescription information based on rationality of data characteristics.
  • the prescription is used as the medical certificate issued by the doctor for the patient. It is the key medical document for judging the rationality of the patient's medication. The pharmacist extracts the valid data related to the rationality of the medication from the information provided by the prescription to analyze and review the reasonableness of each prescription. Sex.
  • the working principle of the intelligent prescription analysis system is to screen the suspected problem prescription according to the pre-set reasonable drug data standard, and the system extracts the basis of the drug from the prescription information, such as the prescription information to provide the drug for a prescription rationality evaluation item.
  • the system prompts that the evaluation item has a suspected unreasonable problem and pays Manual analysis and processing of prescription information by pharmacists. Therefore, the key to using a smart prescription analysis system is to establish a practical and balanced standard for prescription control data. Otherwise, if the standard of prescription control data is too low to meet the target of prescription control, the risk of a large number of drugs cannot be discovered by the system, and the unreasonable cost of a large number of drugs cannot be effectively controlled. If the standard is too high, it will bring a lot of manual audit work to the auditing organization, and it will not play the role of intelligent pre-audit. It will also add unnecessary burden to the doctor's daily medical treatment and medical institution information system.
  • the existing domestic general prescription analysis system basically establishes the prescription review data standard based on the drug manual combined with other authoritative data, and then gives the user a certain personalized data adjustment tool to meet different data characteristics and management requirements of the user.
  • the drug medication information that can be obtained from the prescription is often different from the medication standard of the instructions (including other documents included in the medication standard).
  • the causes of the differences mainly include: data standard categories, information system environment categories, doctor prescription habits, various violations, random errors, and other types of problems.
  • the common diagnostic name is not uniform
  • the name of the administration route is not uniform
  • the unit of medication is not uniform.
  • the technical problem to be solved by the present invention is that there are a large number of differences in the medication standards according to the information and instructions (including other documents incorporating the medication standards) for the medications that can be obtained from the prescription, regardless of the information items or the specific information values.
  • the manual formulation of drug control data standards has difficulties such as workload and consistency, and provides a system for intelligently analyzing the rationality data characteristics of prescriptions (including medical orders), helping managers at all levels to fully grasp the prescriptions of the region or the medical institution.
  • There are various types of suspected drug problems such as the type, level, distribution and possible drug use risk data characteristics, which provide data basis for establishing a practical and balanced prescription management data standard.
  • the invention provides a prescription (including medication prescription) rationality data feature analysis system, which comprises a prescription data acquisition unit, a prescription medication relationship database, a prescription medication risk database, a prescription data feature analysis unit, and a prescription data feature feedback unit.
  • the prescription data acquisition unit of the present invention is installed locally or in the cloud, and can obtain the prescription information required for prescription analysis through real-time data transmission or through data packet overall data transmission.
  • the prescription drug relationship database of the present invention the function of which is to establish a data set and a drug that can be used for providing an analysis basis for a certain rationality evaluation item for drug use from various information points of the relevant prescription information. Evaluate the relationship of the project, including the relationship categories and levels between the two.
  • the prescription drug relationship database consists of the following data items: drug information, prescription evaluation items, prescription evaluation item information element groups, prescription evaluation item information point sets, prescription drug use relationship categories, and prescription drug information relationship levels.
  • Drug information - refers to the general properties of the drug in the prescription, including: generic name, product name, manufacturer, dosage form, specifications, packaging and other information.
  • Prescription evaluation project - refers to the items involved in evaluating the rationality of prescriptions (including medication orders, the same below), including: population, indications, usage and dosage, medical insurance payment rules, administration routes, interactions, incompatibility, repeated medication, Contraindications, skin tests, and prescription writing standards.
  • Prescription evaluation project information element group - When analyzing the rationality of each party's evaluation project, it is necessary to obtain relevant information elements from the prescription information as the basis for explaining the rationality of the project. Different prescription evaluation items of different drugs need to be obtained from the prescription.
  • the information elements are different. These information elements may be one or more pieces combined to provide a reasonable basis for a certain prescription evaluation item of a certain drug.
  • a prescription evaluation project information element group includes several (or one) medication information elements that can fully explain the rationality of the drug evaluation project, a reasonable data range of each information element, and When there is information such as the logical relationship and weight between various information elements in rationality, there may be one or more sets of prescription evaluation item information element groups for a certain prescription evaluation item of a drug.
  • the patient's age, patient's weight, patient's diagnosis, patient's liver/kidney function and other information elements so the patient's age, patient's weight, patient's diagnosis, patient's liver Information elements such as renal function and the reasonable numerical range of age, weight, diagnosis, liver/kidney function, and the logical relationship and weight of the above information elements in the analysis constitute the drug A set of prescription evaluation item information element groups for this usage.
  • the source level of the information element group of the corresponding prescription evaluation item can be divided into five levels.
  • the first level is the legal maximum drug use document: the drug product specification, and other drugs can be used according to the needs of the user, including the national pharmacopoeia, the national formulary, clinical guidelines, medical insurance regulations, evidence-based research results, and experience approved by the pharmacy management agency.
  • Prescription evaluation project information point collection Analyze whether the information element group of different evaluation items has a reasonable basis, and need to obtain corresponding information elements from the prescription data, which may come from (including but not limited to): diagnosis, One or more of the symptoms, patient gender/age/weight, various examinations/surgery/operations, various indicators/parameters, other drugs in the prescription, various special physiological conditions, patient statements, medical orders, other descriptions, etc. article.
  • diagnosis One or more pieces of information in the above information that can provide data for one of the prescription evaluation item information element groups of the medicine is the set of prescription evaluation item information points of the medicine on the prescription evaluation item information element group in the prescription.
  • the set of prescription evaluation item information points may also include information points that can be obtained at the time of prescription evaluation, other prescriptions (including medication prescriptions), such as patient test data, patient symptom description information, etc., as long as the prescription evaluation is performed. It can be obtained at any time, and even if it is not fully reflected in the prescription information, it can be used as a prescription drug information point of the information element of the prescription evaluation item of the medicine.
  • Prescription drug use relationship category - When analyzing the rationality of the project evaluation, it is necessary to obtain relevant information from the evaluation information points of the evaluation project information elements, and the possibility of evaluation of the project information elements and their prescription evaluation project information points by various parties It is a direct correspondence (for example, the information elements of the commonly used prescription evaluation items - the gender of the patient, and the information point of the corresponding prescription evaluation item is the patient's gender in the prescription information). There are also information elements that need to obtain valid information from different information points. They can be divided into different relationship categories according to different sources and data. In particular, it is an information element that plays an important role in a number of prescription evaluation projects.
  • the purpose of the prescription evaluation project information may be: diagnosis, patient symptoms, patient indicators, gender, age, medical order, other drugs, Other prescription information, usage, operation/inspection, etc., and different information points and data on the information points may include: related causes, symptomatic, preventive, examination, surgery/operation related, supplemental nutrition , against adverse drug reactions, health care, etc.
  • Prescription drug information relationship level - a prescription review item for a drug
  • a set of prescription evaluation item information element groups may have a collection of multiple prescription evaluation item information points in the sample.
  • the information level of the project information element group is evaluated by the prescription, and the information elements, the logical relationship and weight between each information element, and the reasonable data range of the information element are used as standards, and the information point set obtained from the prescription information is collected.
  • the relevance level can be divided into 1 to 5 levels of relationship, the highest correlation is 1 level, and the lowest is 5 levels, and the prescription drug information relationship level attribute data items of each information point set are established. It can be considered that, in the prescription rationality analysis, the prescription evaluation item of a medicine has a higher level of relationship of the prescription medication information corresponding to the set of prescription evaluation item information points appearing in the prescription, and the prescription information is evaluated for the prescription. The rationality of the rationality provided by the project will be more sufficient. On the contrary, the lower the level of the relationship between the prescription drug information of a certain drug evaluation item and the prescription evaluation item information point set appearing in the prescription, the more reasonable the prescription information is provided to the prescription evaluation item. Low, the greater the likelihood of a potential medication risk.
  • Prescription Drug Relationship Database Based on the analysis of massive data, establish the correspondence between each drug and the evaluation items of the prescriptions and the set of prescription drug information points that may appear in the prescription, and the corresponding relationship category of prescription drug use among the three
  • the level of prescription drug information relationship, such a database is the prescription drug relationship database.
  • the prescription drug relationship database can continuously add new data—the prescription evaluation item—the prescription drug information point—the relationship category of the prescription drug purpose—the data relationship between the prescription drug information relationship levels.
  • the prescription drug risk database of the present invention is composed of the following data items: drug information, prescription evaluation items, prescription drug information point sets, unreasonable risk categories of prescriptions, and unreasonable risk levels of prescriptions.
  • Different medicines, the different medication information points in the prescription may correspond to the prescription medication information relationship level of different prescription evaluation items, and there may be different categories and levels of irrational medication risks.
  • Unreasonable risk category of prescription when there may be unreasonable medication in the prescription, it may affect one or more of the principles of effective, safe, economic, compliance, normative, etc. of the drug use, in the present invention
  • the category of irrational drug use that may be caused by a potentially unreasonable drug use phenomenon is an unreasonable risk category, including but not limited to: effectiveness risk, safety risk, economic risk, compliance risk, normative risk.
  • Unreasonable risk level of prescriptions When there is a potential irrational risk in the prescription, according to its possible severity, it can be divided into 0-5, which is an unreasonable risk level. The higher the level, the possible The more serious the consequences.
  • Prescription Drug Risk Database Based on the analysis of massive data, establish an unreasonable risk category and irrationality between each drug and the information element group of the prescription project evaluation and the set of prescription drug information points that may appear in the prescription. At the relationship level, the resulting database is the medication risk database. In the course of using the system, the drug risk database can continuously add new drugs—prescription evaluation items—collection of prescription drug information points—prescription unreasonable risk categories—data relationships with unreasonable relationship levels.
  • the prescription data feature analysis unit of the present invention is implemented in two steps.
  • the first step is to process the information on the prescription (or all the prescriptions of the same patient on the same day) based on the prescription medication relationship database, comparing each drug in the prescription sample.
  • Each prescription evaluation item collects the drug information points in the prescription information, and determines the relationship level between the prescription drug use relationship category and the prescription drug information.
  • the second step is to combine the results of the first step data analysis with the prescription drug risk database, analyze the corresponding unreasonable risk categories and unreasonable risk levels in the prescription, and summarize the categories and levels of various potential drug problems in the selected prescription samples. Data characteristics such as distribution, possible drug use risks, and so on.
  • the prescription data feature feedback unit of the present invention displays the data analysis result of the prescription data feature analysis unit to the user, and can view and analyze the characteristics of the prescription rationality data of the region or the medical institution in multiple dimensions, and formulate the prescription control
  • the data standard provides the basis.
  • the medication relationship database, the prescription medication risk database, the prescription data feature analysis unit, and the prescription data feature feedback unit may be partially or completely installed on the user end, or may be installed in the cloud, or may be a cooperative operation between the client and the cloud.
  • Figure 1 is a flow chart of the system of the present invention.
  • Prescription data acquisition In order to comprehensively analyze the characteristics of user prescription data, the system needs to obtain sufficient time and quantity of complete prescription data samples.
  • the data can be obtained by accumulating real-time data obtained through direct interface with the user's business system.
  • the user provides historical sample data with a sufficient sample size at one time, or a combination of the two to obtain dynamic Prescription data.
  • the system performs data processing on the imported prescription information, and identifies the collection of the corresponding evaluation items of the prescription evaluation item in each of the prescription item component groups of each medicine, The relationship between the category of prescription drug use and the level of prescription medication information.
  • the necessity and innovation of the drug relationship database built by the system for analyzing the characteristics of prescription data is that: in the actual prescription evaluation, the information required for the evaluation project does not necessarily come from the fixed prescription information item, but may come from other prescription information items.
  • the invention can quickly identify various situations through the application of related databases and algorithms, and solves the problem well. However, other systems can only be handled manually when encountering such a situation, and the workload and standard consistency are all Unable to protect.
  • the indication information may be acquired.
  • the hormone drug information in the prescription drug list is the set of prescription evaluation item information points of calcium carbonate in the prescription of the prescription, and the prescription drug relationship relationship category
  • the level of prescription drug information is one level.
  • the second step based on the prescription medication risk database, the above-mentioned prescription data analysis results are subsequently processed, and the corresponding categories and levels of prescription medication risks are associated.
  • the third step is based on the evaluation items of the various parties appearing in the prescription samples of each medicine.
  • the collection of information points of prescription evaluation items, the relationship categories of prescription medications, the relationship level of prescription medication information, the unreasonable risk categories of prescriptions, and the unreasonable risk levels of prescriptions analyze the distribution of data problems in each dimension, and complete the rationality of the prescription samples. Analysis and processing of data features.
  • Prescription data feature feedback The system will display the rationality characteristic analysis result of the prescription sample to the user through the prescription data feature feedback unit, and can view and analyze the characteristics of the prescription data of the region or the medical institution in multiple dimensions, and formulate the prescription control
  • the data standard provides the basis.

Abstract

一种处方合理性数据特征分析系统，该系统能够通过对用户处方样本的数据的处理，在处方用药关系数据库和处方用药风险数据库的基础上，全面分析本区域或本医疗机构处方数据的合理性特征，对处方中药品使用与法定用药标准存在差异的各种情况，以及其发生的原因、分布、风险等进行识别，帮助用户(尤其是医疗保险管理机构)能够客观、实际、均衡的建立处方管控数据标准，有效开展处方合理性的智能审核。

Description

处方用药信息合理性数据特征分析系统 技术领域
本发明涉及智能化处方信息处理的技术领域，特别是涉及一种智能分析处方信息中合理性依据数据特征的方法和系统。
背景技术
患者用药是否合理，直接关系到疾病的有效治疗、医疗资源的合理分配、患者的用药安全等，是控制医疗质量，控制不合理医疗费用、保障患者权益的关键。处方作为医生为患者开具的用药凭据，是判断患者用药合理性的关键医疗文件，药师即是从处方提供的信息中提取与用药合理性相关的有效数据，以分析和审核每一张处方的合理性。
应用处方审核与处方点评的方法，由专业药师对患者用药的安全性、有效性、适宜性和经济性进行综合分析已成为保障患者合理用药的基本流程。尤其是随着现代信息技术的发展和应用，智能处方分析系统的出现为药师提供了很好的辅助工具，使得海量处方数据的全面审核成为可能，将逐步在保障患者合理用药上发挥巨大的作用。目前几乎所有发达国家，对患者用药合理性的智能化审核已经成为医疗保险支付的必要手段。
智能处方分析系统的工作原理是根据事先设定好的合理用药数据标准筛查疑似问题处方，系统从处方信息中提取各项用药依据，如处方信息提供药品的某项处方合理性评价项目的用药依据与设定的数据标准不一致，系统即提示该评价项目存在疑似不合理问题，并交 由药师进行处方信息的人工分析和处理。因此，运用智能处方分析系统的关键在于建立一套实用、均衡的处方管控数据标准。否则，如果处方管控数据标准过低，达不到处方管控的目标，大量用药风险不能被系统发现，大量的药品不合理费用得不到有效控制。而标准过高则会给审核机构带来大量的人工审核工作量，没有起到智能预审核的作用，同时也给医生日常诊疗工作和医疗机构信息系统增加不必要的负担。
现有国内一般的处方分析系统，基本是以药品说明书结合其他权威资料为基础来建立处方审核数据标准，再给用户一定个性化数据调整的工具，以满足用户不同的数据特征和管控要求。
但在实际处方审核和点评过程中，能够从处方中获取的药品用药依据信息很多时候与说明书(包括纳入用药标准的其他文件)的用药标准存在差异。差异产生的原因主要包括：数据标准类、信息系统环境类、医生处方习惯类、各种违规现象类、随机性失误类等多种问题类型。如：在数据标准类型的问题中，常见的就有诊断标准名不统一、给药途径名称不统一、用药量单位不统一等。
这些问题在各区域、各医院的出现都有其历史与现实的复杂原因，其隐藏的风险不同，解决的路径和难度也不同，如果不加以区分，简单的要求医生处方时的药品各项用药依据信息与说明书等标准完全一致是不现实的。而且，虽然各类问题产生的原因和机制不同，但大部分问题在处方中会以一定的规律出现，在处方信息中会反映为不同的数据特征表现形式，因此面对这么复杂的数据特征和数据关系，如 果没有相应数据分析工具的支持，仅依靠人工的判断和调整，区分数据出项问题的类别、原因、潜在危害、解决路径等，希望建立起适应本区域、本医疗机构的处方管控数据标准，无论从工作量的角度还是标准一致性的角度都是非常困难的。这也是目前国内绝大部分处方分析系统难以真正应用在较大范围内处方全指标的智能化分析上的主要原因。
发明内容
本发明要解决的技术问题是：针对从处方中能够获取的药品用药依据信息与说明书(包括纳入用药标准的其他文件)的用药标准无论在信息项目上还是在具体信息值上都会存在大量差异，而人工制定用药管控数据标准存在工作量与一致性等困难的情况，提供一种智能化分析处方(包括医嘱)合理性数据特征的系统，帮助各级管理者全面掌握本区域或本医疗机构处方数据中存在各种疑似用药问题的类别、级别、分布情况以及可能存在的用药风险等用药合理性数据特征信息，为建立一套实用、均衡的处方管控数据标准提供数据依据。
本发明提供一种处方(包括用药医嘱)合理性数据特征分析系统，该系统包括处方数据获取单元、处方用药关系数据库、处方用药风险数据库、处方数据特征分析单元、处方数据特征反馈单元。
1、本发明所述处方数据获取单元，安装在本地或是云端，可通过实时数据传输获取也可通过数据包整体数据传输获取处方分析所需的各项处方信息。
2、本发明所述处方用药关系数据库，其作用是建立从相关处方信息的各信息点中获取到的能为药物使用的某一项合理性评价项目提供分析依据的数据集合与药物该合理性评价项目的关系，包括两者之间的关系类别及级别。处方用药关系数据库由以下数据项构成：药品信息、处方评价项目、处方评价项目信息要素组、处方评价项目信息点集合、处方用药目的关系类别、处方用药信息关系级别。
药品信息——指处方中药品的常规属性，包括：药品通用名、商品名、厂家、剂型、规格、包装等信息。
处方评价项目——指评价处方(包括用药医嘱，下同)合理性时涉及的项目，包括：人群、适应症、用法用量、医保支付规则、给药途径、相互作用、配伍禁忌、重复用药、禁忌症、皮试以及处方书写规范性等项目。
处方评价项目信息要素组——分析各处方评价项目合理性时，需要从处方信息中获取相关的信息要素作为说明该项目合理性的依据，不同的药品的不同处方评价项目，需要从处方中获取的信息要素不同，这些信息要素可能是一条或多条组合起来共同为某一药品的某一处方评价项目提供合理性依据。根据药品使用说明书(包括纳入用药标准的其他文件)相关标准建立起来的，多条(或单独一条)能完整说明一种药品的一项处方评价项目合理性的信息要素组合，即为该药品该处方评价项目的一个处方评价项目信息要素组。一个处方评价项目信息要素组包括了能够完整说明药物该项评价项目合理性的几项(或一项)用药信息要素，各项信息要素的合理数据范围，以及在分析合 理性时各项信息要素之间的逻辑关系及权重等信息，药品的某一处方评价项目可能存在一组或多组处方评价项目信息要素组。如：评价某一药品的一条用法用量是否合理时，可能需要考察患者年龄、患者体重、患者诊断、患者肝/肾功能等信息要素，所以处方中的患者年龄、患者体重、患者诊断、患者肝/肾功能等信息要素与该种用法用量适用人群的年龄、体重、诊断、肝/肾功能的合理数值范围，以及上述几项信息要素在分析中的逻辑关系及权重共同该构成了该药品的这一用法用量的一组处方评价项目信息要素组。
根据数据标准的来源的法规及专业性级别，可将相应处方评价项目信息要素组的来源级别划分为5级。一级为法定的最高用药依据文件：药品说明书，其他可以根据用户需求，将国家药典、国家处方集、临床指南、医疗保险规定、循证学研究结果、经过药事管理机构认可的经验用药、文献报道用药等不同来源的用药依据，考虑行业法规、专业性等因素进行分级使用。
处方评价项目信息点集合——分析处方不同的评价项目的信息要素组是否具有合理性依据，需要从处方数据中获取相应的信息要素，这些信息要素可能来自于(包括但不限于)：诊断、症状、患者性别/年龄/体重、各种检查/手术/操作、各种指标/参数、处方中其他药品、各种特殊生理状况、患者主述、医嘱、其他描述等处方信息中的一条或多条。上述信息中能够为药品的某一项处方评价项目信息要素组提供数据的一条或多条信息即为本处方中该药品在这一处方评价项目信息要素组上的处方评价项目信息点集合。
处方评价项目信息点集合也可包括处方评价时能够获得的，处方(包括用药医嘱)之外的其他可提供用药依据的信息点，如患者检验数据、患者症状描述信息等，只要在进行处方评价时可以获得，即便在处方信息中无法全部体现也可作为该药品某一项处方评价项目信息要素的处方用药信息点。
处方用药目的关系类别——在分析各处方评价项目合理性时，需要从该评价项目信息要素的各处方评价项目信息点获取相关信息，各处方评价项目信息要素与其处方评价项目信息点之间可能是直接的对应关系(如：常用的处方评价项目信息要素——患者性别，一般对应的处方评价项目信息点就是处方信息中的患者性别)。也有的信息要素需要从不同的信息点获取有效信息，它们之间可以根据来源与数据的不同而分为不同的关系类别。特别是在多项处方评价项目中都会起到重要作用的信息要素——给药目的，其处方评价项目信息点可能存在于：诊断、患者症状、患者指标、性别、年龄、医嘱、其他药品、其他药品用法用量、手术/操作/检查等不同处方信息中，而不同的信息点以及信息点上的数据对应的关系类别可包括：对病因、对症、预防、检查、手术/操作相关、补充营养、对抗药物不良反应、保健等。
分析不同药品的用药目的与其不同处方用药信息点来源以及信息点上的数据的关系类别，建立之间的对应关系，即为处方用药目的关系类别，药品的用药目的与多项处方评价项目的合理性评价有密切关系。
处方用药信息关系级别——对于一种药品的一项处方点评项目， 一组处方评价项目信息要素组在样本中处方可能存在多个处方评价项目信息点的集合。以处方评价项目信息要素组来源级别，其包含的信息要素、各信息要素之间的逻辑关系及权重、信息要素的合理数据范围等信息为标准，将从这张处方信息中获取的信息点集合以及信息点上的具体信息进行比对，根据处方信息提供的信息点集合的项目是否充分以及各信息点提供的具体数据与信息要素合理数据范围的关系，分析每张处方的该项评价项目的相关性级别，可划分出1——5级关系级别，相关性最高的为1级，最低的为5级，建立各信息点集合的处方用药信息关系级别属性数据项。可以认为在处方合理性分析时，一种药物的某一处方评价项目，其在处方中出现的处方评价项目信息点集合对应的处方用药信息关系级别越高，则该处方信息对这一处方评价项目提供的合理性依据就越充分。反之，一种药物的某一处方评价项目与其在处方中出现的处方评价项目信息点集合对应的处方用药信息关系级别越低，则该处方信息对这一处方评价项目提供的合理性依据级别越低，其存在潜在用药风险的可能性就越大。
处方用药关系数据库——基于海量数据的分析，建立每一种药品以及各处方评价项目与其可能出现在处方中的处方用药信息点集合的对应关系，以及三者之间对应的处方用药目的关系类别、处方用药信息关系级别，这样的数据库即为处方用药关系数据库。处方用药关系数据库在本系统使用过程中，可不断添加新出现的药品——处方评价项目——处方用药信息点——处方用药目的关系类别——处方用药信息关系级别之间的数据关系。
3、本发明所述处方用药风险数据库由以下数据项构成：药品信息、处方评价项目、处方用药信息点集合、处方不合理风险类别、处方不合理风险级别。不同的药品，其在处方中的不同的用药信息点可对应不同处方评价项目的处方用药信息关系级别，其可能存在不同的不合理用药风险的类别和级别。
处方不合理风险类别——当处方中可能存在不合理用药情况时，其可能会影响到药物使用的有效、安全、经济、依从、规范等原则中的一项或多项，在本发明中，一条潜在不合理用药现象可能造成的不合理用药后果类别即为不合理风险类别，其包括但不限于：有效性风险、安全性风险、经济性风险、依从性风险、规范性风险。
处方不合理风险级别——当处方中存在潜在的某类不合理风险时，根据其可能的严重程度，可划分为0——5级，即为不合理风险级别，级别越高，可能引起的后果越严重。
处方用药风险数据库——基于海量数据的分析，建立每一种药品以及各处方评价项目处方的信息要素组与其可能出现在处方中的处方用药信息点集合之间对应的不合理风险类别和不合理关系级别，得到的数据库即为用药风险数据库。用药风险数据库在本系统使用过程中，可不断添加新出现的药品——处方评价项目——处方用药信息点集合——处方不合理风险类别——处方不合理关系级别的数据关系。
4、本发明所述处方数据特征分析单元，分两步实现。第一步是系统基于处方用药关系数据库，对处方(也可是同一患者的当天所有处方合并处理)样本的信息进行处理，比对处方样本中每一种药品的 各处方评价项目在该处方信息中的各处方用药信息点集合，并判断其处方用药目的关系类别与处方用药信息关系级别。第二步是根据第一步数据分析的结果，结合处方用药风险数据库，分析处方中相应的不合理风险类别、不合理风险级别，汇总所选取的处方样本中各种潜在用药问题的类别、级别、分布情况以及可能存在的用药风险等数据特征信息。
5、本发明所述处方数据特征反馈单元，将处方数据特征分析单元的数据分析结果向用户展现，可多维度查看、分析的本区域或本医疗机构的处方合理性数据特征，为制定处方管控数据标准提供依据。
本发明中用药关系数据库、处方用药风险数据库、处方数据特征分析单元、处方数据特征反馈单元等可部分或全部安装在用户端，也可安装在云端，也可是用户端与云端的协同操作。
附图说明
图一为本发明的系统流程图。
具体实施方式
结合本发明的系统流程图，对本发明的具体实施方式说明如下：
1、处方数据获取——本系统为了全面分析用户处方数据特征，需要获取足够时间和数量的完整的处方数据样本，数据的获得可以是通过与用户业务系统直接接口获取的实时数据的累计，也可是用户一次性提供足够样本量的历史处方数据，也可是两者的结合而获得动态 处方数据。
2、处方数据特征分析——首先依据处方用药关系数据库，系统对导入的处方信息进行数据处理，识别每一种药品的各处方评价项目要素组在处方样本中对应的处方评价项目信息点集合、处方用药目的关系类别和处方用药信息关系级别。本系统为分析处方数据特征而建的用药关系数据库的必要性和创新性在于：实际处方评价时，评价项目所需信息并不一定来自于固定的处方信息项目，而可能来自其他处方信息项目，本发明通过相关数据库及算法的应用，能够快速识别各种情况，很好的解决了这个问题，而目前其他系统遇到这样的情况时只能交由人工处理，工作量及标准一致性方面都无法保障。以评价一种药品适应症为例，需要从除了处方诊断之外的其他处方内容中寻找相关依据，例如：碳酸钙用于预防长期使用激素可能引起的骨质疏松时，其适应症信息获取可能来自于处方中的药品信息栏而非诊断信息栏，此时，处方药品例表中激素药品信息即为碳酸钙在本处方中适应症要素的处方评价项目信息点集合，其处方用药目的关系类别为对抗药物不良反应，其处方用药信息关系级别为一级。当系统在处方样本中发现可能存在处方用药关系数据库中未收录的新的处方评价项目信息点集合时，系统引入人工处理环节，完善处方用药关系数据库的相关数据。
第二步，基于处方用药风险数据库，对上述处方数据分析结果进行后续处理，关联其对应的处方用药风险的类别和级别。
第三步，基于各药品在处方样本中出现的各处方评价项目对应的 处方评价项目信息点集合，以及相应处方用药目的关系类别、处方用药信息关系级别、处方不合理风险类别、处方不合理风险级别，分析其各维度的数据问题分布情况，完成对该处方样本合理性数据特征的分析处理。
3、处方数据特征反馈——系统将处方样本的合理性特征分析结果通过处方数据特征反馈单元向用户展现，可多维度查看、分析的本区域或本医疗机构的处方数据特征，为制定处方管控数据标准提供依据。
以上对本发明的具体实施例进行了描述。需要说明的是，本发明并不局限与上述特定实施方式，本领域技术人员可在权利要求的范围内做变形和修改，并不影响本发明的实质。

Claims (9)

  1. 一种处方合理性数据特征分析系统，其特征在于能够基于一定时间一定数量的处方(包括医嘱)数据，智能化分析该区域或医疗机构(可细化到科室和医生)处方信息所提供的药品实际使用依据信息，以及药品实际使用依据信息与药品说明书、药典、用药指南等用药标准所确定的用药依据信息之间存在差异的情况，包括这些差异对应的关系类型、关系级别和风险类型、风险级别，以及这些差异的分布状况情况等处方合理性数据特征，为用户制定符合本区域或本医疗机构实际需求的处方(包括医嘱)合理性评价数据标准提供依据。
  2. 根据权利要求1的处方数据特征分析系统，其特征在于本发明可分析的处方合理性数据特征中涉及的用药合理性评价项目包括但不限于：人群、适应症、用法用量、医保支付规则、给药途径、相互作用、配伍禁忌、重复用药、禁忌症、皮试等。
  3. 根据权利要求1的处方数据特征分析系统，其特征在于本发明可分析的处方合理性数据特征涉及的潜在用药风险类别包括但不限于：有效性风险、安全性风险、经济性风险、依从性风险、规范性风险等。
  4. 根据权利要求1的处方合理性数据特征分析系统，其特征在于本发明分析的处方数据特征的处方评价项目信息点来源包括但不限于处方信息中的医院、科室、医生、患者身份ID、患者性别、患者年龄、体重、诊断、症状、药品名称、药品剂型、药品规格、药品给药途径、药品用法用量、注意事项、患者主述、医嘱、检查、检查结果、操作等信息项目。
  5. 根据权利要求1的处方数据特征分析系统，其特征在于本发明分 析的处方数据特征的处方用药目的关系类别包括但不限于：对病因、对症、预防、检查、手术(操作)相关、补充营养、对抗药物不良反应、保健等。
  6. 根据权利要求1的处方数据特征分析系统，其特征在于本发明分析的处方合理性数据特征中的处方用药信息关系级别是根据原处方评价项目信息点以及信息点上具体数据与所提供的其在处方评价中经过转化后实际提供的合理性依据之间的相关性级别设定的，其中处方用药信息关系的总级别数可按照实际业务需要设定为2到10级。
  7. 根据权利要求1的处方数据特征分析系统，其特征在于本发明分析的处方数据特征的处方不合理风险级别的总级别数可根据潜在的用药风险的严重程度并按照实际业务需要设定为2到10级。
  8. 根据权利要求1的处方数据特征分析系统，其特征在于本发明分析的处方数据特征可以按照区域、医疗机构、科室、医生、患者类别、疾病类别、药品类别等多重维度展现。
  9. 根据权利要求1至8的处方数据特征分析系统，其特征在于本系统可部分或全部安装在用户端，也可安装在云端，也可是用户端与云端的协同操作。
PCT/CN2016/089837 2016-07-12 2016-07-12 处方用药信息合理性数据特征分析系统 WO2018010105A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/CN2016/089837 WO2018010105A1 (zh) 2016-07-12 2016-07-12 处方用药信息合理性数据特征分析系统
CN201680087137.2A CN110024039A (zh) 2016-07-12 2016-07-12 处方用药信息合理性数据特征分析系统

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2016/089837 WO2018010105A1 (zh) 2016-07-12 2016-07-12 处方用药信息合理性数据特征分析系统

Publications (1)

Publication Number Publication Date
WO2018010105A1 true WO2018010105A1 (zh) 2018-01-18

Family

ID=60952295

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2016/089837 WO2018010105A1 (zh) 2016-07-12 2016-07-12 处方用药信息合理性数据特征分析系统

Country Status (2)

Country Link
CN (1) CN110024039A (zh)
WO (1) WO2018010105A1 (zh)

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108447536A (zh) * 2018-03-19 2018-08-24 杭州逸曜信息技术有限公司 基于疾病特征和疾病程度信息的用药信息处理方法
CN109508869A (zh) * 2018-10-23 2019-03-22 平安医疗健康管理股份有限公司 一种基于数据处理的风险检测方法和装置
CN109523395A (zh) * 2018-10-24 2019-03-26 平安医疗健康管理股份有限公司 基于异常操作识别的医疗监管方法、装置、终端及介质
CN109636623A (zh) * 2018-10-19 2019-04-16 平安医疗健康管理股份有限公司 医疗数据异常检测方法、装置、设备及存储介质
CN110911014A (zh) * 2019-05-29 2020-03-24 中国人民解放军联勤保障部队第九二〇医院 一种门诊重复用药查询分析方法及系统
CN111028936A (zh) * 2019-12-14 2020-04-17 曹庆恒 一种医疗检查及检验合理合规性分析的方法、系统和设备
CN112070260A (zh) * 2019-06-11 2020-12-11 复旦大学附属妇产科医院 基于妇产科用药规则的优化方法、审核系统、设备和介质
CN112712864A (zh) * 2021-01-07 2021-04-27 深圳坐标软件集团有限公司 一种可依据业务及政策配置规则的临床用药辅助方法及终端
CN113724829A (zh) * 2021-08-30 2021-11-30 康键信息技术（深圳）有限公司 处方审核方法和装置、电子设备、存储介质
CN114066368A (zh) * 2021-11-23 2022-02-18 宜阳县中医院 一种中医院药房药材存放及自动供给系统
CN114822877A (zh) * 2022-06-21 2022-07-29 阿里健康科技(杭州)有限公司 信息显示方法、问诊装置

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110767277A (zh) * 2019-09-09 2020-02-07 卫宁健康科技集团股份有限公司 区域电子药历的管理方法及系统

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102737165A (zh) * 2012-06-07 2012-10-17 北京太元通软件科技有限公司 临床用药决策支持系统
CN103854136A (zh) * 2014-03-13 2014-06-11 华中科技大学同济医学院附属协和医院 带有用药安全监控干预功能的医院用药管理系统
CN104008464A (zh) * 2014-06-17 2014-08-27 北京大学第一医院 医院药师技能测评系统
CN104463456A (zh) * 2014-12-03 2015-03-25 长沙中科院文化创意与科技产业研究院 一种面向患者的医疗处方审核系统及其方法
CN104487972A (zh) * 2014-09-29 2015-04-01 曹庆恒 一种多维度用药信息处理方法、系统和设备

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102737165A (zh) * 2012-06-07 2012-10-17 北京太元通软件科技有限公司 临床用药决策支持系统
CN103854136A (zh) * 2014-03-13 2014-06-11 华中科技大学同济医学院附属协和医院 带有用药安全监控干预功能的医院用药管理系统
CN104008464A (zh) * 2014-06-17 2014-08-27 北京大学第一医院 医院药师技能测评系统
CN104487972A (zh) * 2014-09-29 2015-04-01 曹庆恒 一种多维度用药信息处理方法、系统和设备
CN104463456A (zh) * 2014-12-03 2015-03-25 长沙中科院文化创意与科技产业研究院 一种面向患者的医疗处方审核系统及其方法

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108447536A (zh) * 2018-03-19 2018-08-24 杭州逸曜信息技术有限公司 基于疾病特征和疾病程度信息的用药信息处理方法
CN109636623A (zh) * 2018-10-19 2019-04-16 平安医疗健康管理股份有限公司 医疗数据异常检测方法、装置、设备及存储介质
CN109508869A (zh) * 2018-10-23 2019-03-22 平安医疗健康管理股份有限公司 一种基于数据处理的风险检测方法和装置
CN109508869B (zh) * 2018-10-23 2023-09-22 平安医疗健康管理股份有限公司 一种基于数据处理的风险检测方法和装置
CN109523395A (zh) * 2018-10-24 2019-03-26 平安医疗健康管理股份有限公司 基于异常操作识别的医疗监管方法、装置、终端及介质
CN109523395B (zh) * 2018-10-24 2023-08-18 平安医疗健康管理股份有限公司 基于异常操作识别的医疗监管方法、装置、终端及介质
CN110911014B (zh) * 2019-05-29 2023-04-25 中国人民解放军联勤保障部队第九二〇医院 一种门诊重复用药查询分析方法及系统
CN110911014A (zh) * 2019-05-29 2020-03-24 中国人民解放军联勤保障部队第九二〇医院 一种门诊重复用药查询分析方法及系统
CN112070260A (zh) * 2019-06-11 2020-12-11 复旦大学附属妇产科医院 基于妇产科用药规则的优化方法、审核系统、设备和介质
CN111028936A (zh) * 2019-12-14 2020-04-17 曹庆恒 一种医疗检查及检验合理合规性分析的方法、系统和设备
CN112712864A (zh) * 2021-01-07 2021-04-27 深圳坐标软件集团有限公司 一种可依据业务及政策配置规则的临床用药辅助方法及终端
CN112712864B (zh) * 2021-01-07 2024-03-29 深圳坐标软件集团有限公司 一种可依据业务及政策配置规则的临床用药辅助方法及终端
CN113724829A (zh) * 2021-08-30 2021-11-30 康键信息技术（深圳）有限公司 处方审核方法和装置、电子设备、存储介质
CN114066368A (zh) * 2021-11-23 2022-02-18 宜阳县中医院 一种中医院药房药材存放及自动供给系统
CN114822877A (zh) * 2022-06-21 2022-07-29 阿里健康科技(杭州)有限公司 信息显示方法、问诊装置

Also Published As

Publication number Publication date
CN110024039A (zh) 2019-07-16

Similar Documents

Publication Publication Date Title
WO2018010105A1 (zh) 处方用药信息合理性数据特征分析系统
Thomas et al. Medication errors in hospitals in the Middle East: a systematic review of prevalence, nature, severity and contributory factors
Naseralallah et al. Impact of pharmacist interventions on medication errors in hospitalized pediatric patients: a systematic review and meta-analysis
Viswanathan et al. Medication therapy management interventions in outpatient settings: a systematic review and meta-analysis
Goddard et al. Automation bias: empirical results assessing influencing factors
Moura et al. Potential drug-drug interactions associated with prolonged stays in the intensive care unit: a retrospective cohort study
WO2018058545A1 (zh) 基于业务单元数据特征的处方管控数据标准管理系统
Matui et al. Computer decision support systems for asthma: a systematic review
Mah et al. Oral magnesium supplementation for insomnia in older adults: a Systematic Review & Meta-Analysis
Shemeikka et al. A health record integrated clinical decision support system to support prescriptions of pharmaceutical drugs in patients with reduced renal function: design, development and proof of concept
US20120101846A1 (en) Computer-Implemented Method For Displaying Patient-Related Diagnoses Of Chronic Illnesses
Jaehde et al. Minimising treatment-associated risks in systemic cancer therapy
Colicchio et al. Health information technology adoption: Understanding research protocols and outcome measurements for IT interventions in health care
Holmström et al. Inter-rater reliability of medication error classification in a voluntary patient safety incident reporting system HaiPro in Finland
Vest et al. Image sharing technologies and reduction of imaging utilization: a systematic review and meta-analysis
Frost et al. Status, challenges and gaps in antimicrobial resistance surveillance around the world
Chiapella et al. Assessment of polypharmacy in elderly patients by using data from dispensed medications in community pharmacies: analysis of results by using different methods of estimation
CN109215756A (zh) 一种医学辅助诊疗系统
Rodríguez-Pérez et al. Validation of the LESS-CHRON criteria: reliability study of a tool for deprescribing in patients with multimorbidity
Fenna et al. Extent of a valsartan drug shortage and its effect on antihypertensive drug use in the Canadian population: a national cross-sectional study
Studer et al. The impact of pharmacist-led medication reconciliation and interprofessional ward rounds on drug-related problems at hospital discharge
Gangwar et al. The role of drug utilization evaluation in medical sciences
CN109243564A (zh) 一种用药风险评估系统
Fountain et al. Fatal toxicity indices for medicine-related deaths in New Zealand, 2008–2013
Khan Medication incidents associated with outpatient computerized prescribing systems

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: 16908433

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16908433

Country of ref document: EP

Kind code of ref document: A1