Medical institution medicine warning method and related equipment

Abstract

The invention discloses a medical institution medicine warning method and related equipment, which can be applied to the technical field of medicine warning data processing. According to the method, after the drug alert index system and the index weight are constructed, the user login information of different group types is obtained, the drug use report corresponding to the user login information is obtained, then the content of the drug use report is analyzed according to the drug alert index system and the index weight, and the drug alert information is obtained. And then drug alert is carried out according to the drug alert information, so that dependence on drug alert of personnel is reduced, and drug monitoring efficiency and monitoring accuracy are effectively improved.

Description

Technical Field

[0001] This application relates to the field of pharmacovigilance data processing technology, and in particular to a pharmacovigilance method and related equipment for medical institutions. Background Technology

[0002] In related technologies, medical institutions, as the primary locations for drug use, face certain safety risks in the procurement, storage, dispensing, and administration of drugs. Currently, pharmacovigilance monitoring in medical institutions is mainly handled by relevant personnel, leading to sporadic and discontinuous drug monitoring reports, which hinders the detection and handling of drug risks. Furthermore, the quality of reports uploaded by different medical institutions varies, making it difficult for relevant personnel to quickly obtain accurate drug monitoring results during the monitoring and analysis process.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main objective of this application is to propose a pharmacovigilance method and related equipment for medical institutions, which can effectively improve the efficiency and accuracy of drug monitoring.

[0005] To achieve the above objectives, one aspect of this application proposes a pharmacovigilance method for medical institutions, the method comprising the following steps:

[0006] Construct a pharmacovigilance indicator system and indicator weights;

[0007] Obtain user login information for different user groups;

[0008] Obtain the drug usage report corresponding to the user login information;

[0009] The content of the drug use report is analyzed based on the pharmacovigilance index system and the index weights to obtain pharmacovigilance information;

[0010] Pharmacovigilance is performed based on the pharmacovigilance information.

[0011] In some embodiments, the construction of the pharmacovigilance indicator system and indicator weights includes:

[0012] Obtain several drug literature and policy documents;

[0013] A preliminary indicator system was constructed based on the aforementioned drug literature and policy documents;

[0014] The preliminary indicator system was adjusted based on the Delphi expert consultation method to obtain the target indicator system;

[0015] The weights of the indicators corresponding to the target indicator system are determined by the pecking order graph method.

[0016] In some embodiments, constructing a preliminary indicator system based on the drug literature and the policy documents includes:

[0017] The drug literature and policy documents were sorted and summarized to obtain relevant information about medical institutions. This relevant information includes the current status of pharmacovigilance in medical institutions and the requirements for pharmacovigilance in different types of medical institutions.

[0018] Based on the aforementioned drug literature analysis, information on differences in pharmacovigilance across different regions was analyzed.

[0019] Based on the aforementioned discrepancy information, analyze the obstacles to pharmacovigilance in medical institutions in the target region;

[0020] A preliminary indicator system is constructed based on the relevant information of the medical institution and the obstacle information.

[0021] In some embodiments, adjusting the preliminary indicator system based on the Delphi expert consultation method to obtain the target indicator system includes:

[0022] An expert consultation questionnaire is constructed, which is used to collect relevant information on pharmacovigilance from practitioners in pre-set medical institutions;

[0023] Multiple rounds of expert consultation information were collected through the aforementioned expert consultation questionnaire;

[0024] The preliminary indicator system was adjusted based on the information from multiple rounds of expert consultations to obtain the target indicator system.

[0025] In some embodiments, determining the indicator weights corresponding to the target indicator system using the pecking order graph method includes:

[0026] Based on the second round of data from the Delphi expert consultation method, the importance scores of the target indicators in the target indicator system by experts are transformed into a priority order matrix, wherein the rows and columns of the priority order matrix correspond to the same target indicators.

[0027] Each pair of target indicators in the priority order matrix is ​​compared, and the first score corresponding to the target indicator is determined by combining the preset scale.

[0028] The first scores of the rows corresponding to the target indicator are added together to obtain the original score of the target indicator;

[0029] The original scores of all the target indicators are summed to obtain a total score, which is used as the weight of the indicator.

[0030] In some embodiments, the analysis of the content of the drug use report based on the pharmacovigilance index system and the index weights includes:

[0031] Feature extraction was performed on the content of the drug use report to obtain the feature extraction results;

[0032] Obtain the target weight corresponding to the feature extraction result from the indicator weight;

[0033] The pharmacovigilance data to be analyzed is determined based on the target weights and the feature extraction results;

[0034] Pharmacovigilance analysis is performed on the pharmacovigilance data to be analyzed based on the pharmacovigilance index system.

[0035] To achieve the above objectives, another aspect of this application provides a pharmacovigilance device for medical institutions, the device comprising:

[0036] The module is used to build a pharmacovigilance indicator system and indicator weights;

[0037] The first acquisition module is used to acquire user login information for different user groups.

[0038] The second acquisition module is used to acquire the drug usage report corresponding to the user login information;

[0039] The analysis module is used to analyze the content of the drug use report according to the pharmacovigilance indicator system and the indicator weights to obtain pharmacovigilance information;

[0040] The pharmacovigilance module is used to perform pharmacovigilance based on the pharmacovigilance information.

[0041] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0042] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0043] To achieve the above objectives, another aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0044] The embodiments of this application include at least the following beneficial effects: This application provides a pharmacovigilance method and related equipment for medical institutions. This solution obtains user login information for different group types after constructing a pharmacovigilance indicator system and indicator weights, and obtains drug use reports corresponding to the user login information. Then, it analyzes the content of the drug use reports according to the pharmacovigilance indicator system and indicator weights to obtain pharmacovigilance information, and then performs pharmacovigilance based on the pharmacovigilance information, thereby reducing the reliance on personnel for pharmacovigilance and effectively improving the efficiency and accuracy of drug monitoring. Attached Figure Description

[0045] Figure 1 This is a flowchart of the pharmacovigilance method for medical institutions provided in the embodiments of this application;

[0046] Figure 2 This is a schematic diagram illustrating the construction of the indicator system and indicator weights provided in the embodiments of this application;

[0047] Figure 3 This is a schematic diagram of the structure of the medical institution drug vigilance device provided in the embodiments of this application;

[0048] Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0050] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0051] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0053] Before providing a detailed description of the embodiments of this application, some of the nouns and terms used in the embodiments of this application will be explained first. The nouns and terms used in the embodiments of this application shall be interpreted as follows:

[0054] Medical institutions are a general term for health institutions established in accordance with the law to provide disease diagnosis, treatment and related health services, including but not limited to hospitals, health centers, clinics and health stations.

[0055] In related technologies, pharmacovigilance monitoring in medical institutions is primarily handled by designated personnel, leading to sporadic and discontinuous drug monitoring reports, which hinders the detection and management of drug risks. Furthermore, the quality of reports uploaded by different medical institutions varies, making it difficult for relevant personnel to quickly obtain accurate drug monitoring results during the analysis process.

[0056] In view of this, the embodiments of this application provide a pharmacovigilance method and related equipment for medical institutions, which can effectively improve the efficiency and accuracy of drug monitoring.

[0057] The pharmacovigilance method for medical institutions provided in this application relates to the field of pharmacovigilance data processing technology. The pharmacovigilance method for medical institutions provided in this application can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the pharmacovigilance method for medical institutions, but is not limited to the above forms.

[0058] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0059] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0060] The embodiments of this application will be described in detail below with reference to the accompanying drawings:

[0061] Figure 1 This is an optional flowchart of the pharmacovigilance method for medical institutions provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S106.

[0062] Step S110: Construct a pharmacovigilance indicator system and indicator weights;

[0063] Step S120: Obtain user login information for different group types;

[0064] Step S130: Obtain the drug usage report corresponding to the user login information;

[0065] Step S140: Analyze the content of the drug use report according to the pharmacovigilance indicator system and indicator weights to obtain pharmacovigilance information;

[0066] Step S150: Perform pharmacovigilance based on pharmacovigilance information.

[0067] It is understood that, in constructing the drug vigilance indicator system and indicator weights in this embodiment, a preliminary indicator system can be built by acquiring several drug literature and policy documents, and then adjusted based on these documents to obtain the target indicator system using the Delphi expert consultation method. Finally, the indicator weights corresponding to the target indicator system are determined using the pecking order graph method. Specifically, the drug literature in this embodiment includes, but is not limited to, publicly available domestic and international feedback information regarding drug production, sales, and use. This feedback information includes, but is not limited to, information on patient efficacy with the drug and the effectiveness of clinical trials conducted by doctors. Policy documents can be domestic guidelines issued within a certain period regarding drug sales, use, and related processes.

[0068] It is understandable that, in constructing the preliminary indicator system in this embodiment, relevant information about medical institutions can be obtained by sorting and summarizing drug literature and policy documents. Then, based on the drug literature analysis, differences in pharmacovigilance across different regions can be identified, and based on these differences, obstacles to pharmacovigilance in target regions can be analyzed. Finally, a preliminary indicator system can be constructed based on the relevant information about medical institutions and the obstacles. The relevant information about medical institutions includes the current status of pharmacovigilance in medical institutions and the requirements for pharmacovigilance in different types of medical institutions. Specifically, this embodiment, through collecting, sorting, and summarizing drug literature and policy documents, aims to gain a preliminary understanding of the current status of pharmacovigilance in medical institutions and the relevant requirements for pharmacovigilance in different types of medical institutions from the perspectives of pediatric medication, traditional Chinese medicine preparations, traditional Chinese medicine decoction pieces, hospital preparations, and product safety evaluation. This provides data support for the construction of the indicator system.

[0069] It is understandable that this embodiment can also use comparative analysis to compare the differences in pharmacovigilance management organizations, laws and regulations, guidelines, adverse reaction monitoring and reporting systems, and risk management systems at home and abroad, based on the research results of drug literature. At the same time, it can compare with the legal system, organizational structure, and work content of pharmacovigilance in medical institutions, and summarize the obstacles currently faced by the connection of pharmacovigilance rules in medical institutions. This can provide basic data for the construction of a pharmacovigilance system in medical institutions.

[0070] It is understandable that the process of adjusting the preliminary indicator system based on the Delphi expert consultation method in this embodiment can be achieved by constructing an expert consultation questionnaire, collecting multiple rounds of expert consultation information through the questionnaire, and then adjusting the preliminary indicator system based on the multi-round expert consultation information to obtain the target indicator system. The expert consultation questionnaire is used to collect relevant information on pharmacovigilance from practitioners in pre-defined medical institutions.

[0071] Specifically, the Delphi expert consultation method utilizes a series of questionnaires with controlled feedback mechanisms to systematically apply expert opinions. After statistical analysis of the returned questionnaires, the results are combined with expert opinions and suggestions to optimize and improve the indicator system. Once expert opinions have gradually converged, the final results are analyzed to derive the target indicator system.

[0072] It is understandable that the expert consultation questionnaire includes two rounds of questions. The first round of the questionnaire is designed based on the initially drafted pharmacovigilance indicator system for medical institutions, and includes a basic information form for experts and an expert consultation form. The second round of the questionnaire presents the statistical results analysis of the first round and is used to collect expert opinions again. For example, this embodiment can form an expert consultation group by inviting 15 staff members from monitoring institutions, doctors, nurses, and pharmacists engaged in the field of pharmacovigilance in medical institutions. Then, according to the Delphi method, the expert consultation questionnaires are distributed and collected online, with each round limited to one week for collection. After collecting the expert questionnaires, the research team performs statistical analysis on the questionnaire data. Specifically, the statistical analysis process in this embodiment includes, but is not limited to, the following processes:

[0073] (1) Assigning values ​​to the importance, familiarity and judgment criteria of indicators: This embodiment adopts the Likert 5-level rating method, which divides the evaluation of the importance of indicators into five levels: very unimportant, unimportant, neutral, important and very important, and assigns a score of 1-5; the judgment criteria of indicators include four categories: theoretical knowledge, practical experience, reference to domestic and foreign materials, and subjective feelings, and the degree of the criteria is divided into four levels: none, small, medium and large, and assigned a score of 0-3; the familiarity with indicators is divided into five levels: unfamiliar, not very familiar, generally familiar, relatively familiar and very familiar, and assigned a score of 1-5, with corresponding scores of 1, 0.8, 0.6, 0.4 and 0.2.

[0074] (2) Screening of indicators: In this embodiment, the threshold method is used to construct an indicator screening standard system. By calculating the critical values ​​of the indicator importance mean, full score ratio and coefficient of variation, the quantitative standard for indicator removal is clarified. At the same time, a dual filtering mechanism is set up, requiring that indicators must meet two or more removal conditions before being included in the candidate removal list. Finally, the indicator screening is completed through collective decision-making. The decision-making process integrates expert feedback and multiple rounds of demonstration by the research group to ensure that the screening results meet both statistical standards and practical rationality.

[0075] (3) Analyze the statistical data of the screened indicators using statistical methods: In this embodiment, SPSS 26.0 software is used for statistical analysis. The analysis process covers the following:

[0076] Quantitative evaluation indicators include the mean score, full score rate, and coefficient of variation.

[0077] Expert authority indicators: Expert judgment coefficient (Ca), Familiarity coefficient (Cs), Authority coefficient (Cr);

[0078] The compatibility test index is Kendal's W test, which measures the coefficient of compatibility of expert opinions.

[0079] Specifically, in this embodiment, when collecting expert questionnaires, the field survey method can also be combined to conduct in-depth research on the theme of building an integrated pharmacovigilance indicator system for monitoring, identification, evaluation and control in medical institutions, so as to provide a reference for the construction of a pharmacovigilance system in medical institutions.

[0080] It is understandable that in the process of determining the indicator weights corresponding to the target indicator system using the priority graph method in this embodiment, the second round of data from the Delphi expert consultation method can be used to transform the experts' importance ratings of the target indicators in the target indicator system into a priority order matrix, where the rows and columns of the priority order matrix correspond to the same target indicators. Then, each pair of target indicators in the priority order matrix is ​​compared, and a first score corresponding to the target indicator is determined by combining it with a preset scale. The first scores of the rows corresponding to the target indicators are added together to obtain the original score of the target indicator. Finally, the original scores of all target indicators are added together to obtain the total score as the indicator weight. Specifically, when the target indicators include n indicators, the second round of data from the Delphi expert consultation method can be used to transform the experts' importance ratings of the n indicators into a priority order matrix. Then, each pair of indicators in the priority order matrix is ​​compared to determine which indicator is relatively more important. After scoring according to a preset scale to obtain the first score, for each indicator, the scores of its corresponding row are added together to obtain the original score of that indicator. Finally, the original scores of all indicators are added together to obtain the total score as the indicator weight.

[0081] Specifically, such as Figure 2 As shown, the construction process of the indicator system and indicator weights in this embodiment can be achieved by summarizing the excellent experiences of pharmacovigilance in medical institutions at home and abroad, selecting three-level indicator items based on the review of laws, regulations and academic literature and expert interviews, initially proposing a pharmacovigilance system that integrates different types of medical institutions, constructing a preliminary indicator system, and designing a Delphi expert consultation questionnaire to consult with experts from drug regulatory departments, universities and colleges, and experts with rich theoretical knowledge or practical experience in the field of pharmacovigilance in medical institutions. The consultation covers practitioners in medical institutions of preset regions and types. The results of each round are statistically analyzed to screen factors related to pharmacovigilance in medical institutions of preset regions. The pecking order graph method is used to invite relevant experts to assign weights to the above indicator systems, thereby determining the final indicator system and indicator weights.

[0082] It is understood that, in this embodiment, after establishing the pharmacovigilance indicator system and indicator weights, the content of drug use reports can be analyzed using these indicators. Specifically, this embodiment obtains feature extraction results by extracting features from the content of the drug use reports, then obtains the target weights corresponding to the feature extraction results from the indicator weights, and then determines the pharmacovigilance data to be analyzed based on the target weights and feature extraction results. Finally, it performs pharmacovigilance analysis on the data based on the pharmacovigilance indicator system. In this embodiment, indicator weights can be used to characterize the importance of pharmacovigilance corresponding to each indicator. Since the pharmacovigilance type corresponding to each feature extraction result is different, its corresponding indicator weights are also different. In this embodiment, after obtaining the indicator weights corresponding to the feature extraction results as target weights, the pharmacovigilance information corresponding to the feature extraction results can be generated by comparing the calculated results of the feature extraction results and target weights with the pharmacovigilance indicator system.

[0083] It is understood that, after obtaining pharmacovigilance information, this embodiment can perform pharmacovigilance through a preset visual interface. For example, a prompt indicating the need for pharmacovigilance can be automatically displayed on the visual interface, allowing relevant personnel to promptly understand the prompt and thus enabling human intervention in the relevant medication, improving the safety and reliability of medication use. Specifically, this embodiment displays different content on the visual interface for different types of personnel. For example, the visual interface for doctors can display information on the efficacy of pharmacovigilance, while the visual interface for medication holders can display information on the price and efficacy of pharmacovigilance. By displaying different content on different interfaces, this embodiment allows different personnel to obtain relevant information more effectively.

[0084] Please see Figure 3 This application also provides a drug vigilance device for medical institutions, the device comprising:

[0085] Module 310 is used to construct a pharmacovigilance indicator system and indicator weights;

[0086] The first acquisition module 320 is used to acquire user login information for different group types;

[0087] The second acquisition module 330 is used to acquire the drug usage report corresponding to the user login information;

[0088] Analysis module 340 is used to analyze the content of drug use reports based on the pharmacovigilance indicator system and indicator weights to obtain pharmacovigilance information;

[0089] The pharmacovigilance module 350 is used to perform pharmacovigilance based on pharmacovigilance information.

[0090] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0091] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0092] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0093] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0094] The processor 410 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0095] The memory 420 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 420 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 420 and is called and executed by the processor 410 using the methods described above in the embodiments of this application.

[0096] Input / output interface 430 is used to realize information input and output;

[0097] The communication interface 440 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0098] Bus 450 transmits information between various components of the device (e.g., processor 410, memory 420, input / output interface 430, and communication interface 440);

[0099] The processor 410, memory 420, input / output interface 430 and communication interface 440 are connected to each other within the device via bus 450.

[0100] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0101] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0102] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0103] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0104] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0105] This application provides a pharmacovigilance method and related equipment for medical institutions. By constructing a pharmacovigilance indicator system and indicator weights, it obtains user login information for different group types and corresponding drug usage reports. Then, it analyzes the content of the drug usage reports according to the pharmacovigilance indicator system and indicator weights to obtain pharmacovigilance information, and then performs pharmacovigilance based on the pharmacovigilance information. This reduces the reliance on personnel for pharmacovigilance and effectively improves the efficiency and accuracy of drug monitoring.

[0106] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0107] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0108] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0110] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0112] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0113] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0114] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A pharmacovigilance method for medical institutions, characterized in that, The method includes the following steps: Construct a pharmacovigilance indicator system and indicator weights; Obtain user login information for different user groups; Obtain the drug usage report corresponding to the user login information; The content of the drug use report is analyzed based on the pharmacovigilance index system and the index weights to obtain pharmacovigilance information; Pharmacovigilance is performed based on the pharmacovigilance information.

2. The method according to claim 1, characterized in that, The construction of the pharmacovigilance indicator system and indicator weights includes: Obtain several drug literature and policy documents; A preliminary indicator system was constructed based on the aforementioned drug literature and policy documents; The preliminary indicator system was adjusted based on the Delphi expert consultation method to obtain the target indicator system; The weights of the indicators corresponding to the target indicator system are determined by the pecking order graph method.

3. The method according to claim 2, characterized in that, The preliminary indicator system constructed based on the drug literature and policy documents includes: The drug literature and policy documents were sorted and summarized to obtain relevant information about medical institutions. This relevant information includes the current status of pharmacovigilance in medical institutions and the requirements for pharmacovigilance in different types of medical institutions. Based on the aforementioned drug literature analysis, information on differences in pharmacovigilance across different regions was analyzed. Based on the aforementioned discrepancy information, analyze the obstacles to pharmacovigilance in medical institutions in the target region; A preliminary indicator system is constructed based on the relevant information of the medical institution and the obstacle information.

4. The method according to claim 2, characterized in that, The preliminary indicator system is adjusted based on the Delphi expert consultation method to obtain the target indicator system, including: An expert consultation questionnaire is constructed, which is used to collect relevant information on pharmacovigilance from practitioners in pre-set medical institutions; Multiple rounds of expert consultation information were collected through the aforementioned expert consultation questionnaire; The preliminary indicator system was adjusted based on the information from multiple rounds of expert consultations to obtain the target indicator system.

5. The method according to claim 4, characterized in that, The step of determining the indicator weights corresponding to the target indicator system using the pecking order graph method includes: Based on the second round of data from the Delphi expert consultation method, the importance scores of the target indicators in the target indicator system by experts are transformed into a priority order matrix, wherein the rows and columns of the priority order matrix correspond to the same target indicators. Each pair of target indicators in the priority order matrix is ​​compared, and the first score corresponding to the target indicator is determined by combining the preset scale. The first scores of the rows corresponding to the target indicator are added together to obtain the original score of the target indicator; The original scores of all the target indicators are summed to obtain a total score, which is used as the weight of the indicator.

6. The method according to claim 1, characterized in that, The analysis of the drug use report content based on the pharmacovigilance index system and the index weights includes: Feature extraction was performed on the content of the drug use report to obtain the feature extraction results; Obtain the target weight corresponding to the feature extraction result from the indicator weight; The pharmacovigilance data to be analyzed is determined based on the target weights and the feature extraction results; Pharmacovigilance analysis is performed on the pharmacovigilance data to be analyzed based on the pharmacovigilance index system.

7. A drug vigilance device for medical institutions, characterized in that, The device includes: The module is used to build a pharmacovigilance indicator system and indicator weights; The first acquisition module is used to acquire user login information for different user groups. The second acquisition module is used to acquire the drug usage report corresponding to the user login information; The analysis module is used to analyze the content of the drug use report according to the pharmacovigilance indicator system and the indicator weights to obtain pharmacovigilance information; The pharmacovigilance module is used to perform pharmacovigilance based on the pharmacovigilance information.

8. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

Images