Patient education propagation method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of digital marketing, and discloses a patient education propagation method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the clustering analysis of social media data, and obtaining a topic hotspot of a target disease; determining a target circle layer associated with the target disease and a target propagation strategy for the target circle layer based on the topic hotspot and a pre-constructed disease user circle layer library; screening a target propagator according to the target disease and the target propagation strategy, wherein the target propagator is used for being entrusted to carry out patient education propagation on the target disease in the social media; and obtaining a preset evaluation index in the social media, and evaluating the patient education transmission effect for the target disease based on the evaluation index. Through social media data clustering analysis, interest circle layer accurate matching, propagator dynamic screening and closed-loop effect evaluation, the defects in the aspects of sample size, timeliness, cost and effect tracking in the patient education process are overcome, and patient education propagation can be completed quickly and efficiently.

Description

Technical Field

[0001] The present disclosure relates to the technical field of digital marketing, for example, to a patient education and communication method, device, electronic device, and storage medium. Background Art

[0002] In the pharmaceutical market, with changes in pharmaceutical policies and market trends, pharmaceutical companies are increasingly focusing on direct-to-consumer channels to better meet patient needs. Traditional pharmaceutical marketing relies on offline communication between pharmaceutical representatives and doctors and traditional media advertising. However, the widespread use of the internet and social media has led patients to increasingly access medical information through these platforms.

[0003] Related technologies primarily utilize quantitative surveys and qualitative interviews for patient education, but these methods present the following challenges: small sample sizes fail to fully reflect patient needs; long research cycles result in significant time-consuming efforts and an inability to respond promptly to market changes; patient education requires significant capital investment; data can quickly become outdated due to poor timeliness; and real-time monitoring and evaluation of social media communication effectiveness is difficult. Furthermore, the various components of these technologies are relatively independent and lack integration, making it difficult to deliver agile and efficient patient education.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] The embodiments of the present disclosure provide a patient education communication method, device, electronic device and storage medium, which solve the shortcomings of the patient education methods in related technologies in terms of sample size, timeliness, cost and effect tracking, and can complete patient education communication quickly and efficiently.

[0007] According to a first aspect of the present disclosure, there is provided a patient education communication method, comprising:

[0008] Perform cluster analysis on social media data to obtain hot topics of target diseases;

[0009] Based on hot topics and a pre-built disease user circle database, identify target circles associated with the target disease and target communication strategies for these circles;

[0010] Screen target communicators based on the target disease and target communication strategy. Target communicators are commissioned to conduct patient education and communication on social media for the target disease.

[0011] Obtain preset evaluation indicators in social media and evaluate the effectiveness of patient education communication for target diseases based on the evaluation indicators.

[0012] In some embodiments, cluster analysis is performed on social media data to obtain hot topics for the target disease, including:

[0013] Identify discussion data related to the target disease in social media data;

[0014] Cluster analysis is performed on the discussion data to obtain hot topics of the target disease, where the hot topics include patient demand information and cognitive information about the target disease and related drugs.

[0015] In some embodiments, based on hot topics and a pre-built disease user circle library, a target circle associated with the target disease and a targeted communication strategy for the target circle are determined, including:

[0016] Cross-analyze hot topics and pre-built disease user circle databases to identify target circles with the highest correlation with the target disease;

[0017] Based on the population attributes, content preferences and cross-discussion characteristics of the target circle and the disease, a targeted communication strategy for the target circle is generated.

[0018] In some embodiments, the targeted communication strategy includes topic carriers and social media contacts.

[0019] In some embodiments, screening target communicators based on target diseases and target communication strategies includes:

[0020] Screen candidate communicators matching the target disease and target communication strategy from the communicator database;

[0021] Obtaining data on the potential risk of each candidate spreader;

[0022] Based on the potential risk data of each candidate communicator, target communicators are screened out from the candidate communicators.

[0023] In some embodiments, obtaining preset evaluation indicators from social media and evaluating the effectiveness of patient education and communication for the target disease based on the evaluation indicators include:

[0024] Obtain data on dissemination content related to target diseases and related drugs in social media;

[0025] Determining a communication effectiveness index based on the communication content data, wherein the communication effectiveness index is an evaluation index used to evaluate the immediate communication effect of the patient education content;

[0026] Mindset change indicators are calculated based on the communication content data. The mindset change indicators are used to evaluate the long-term impact of patient education communication on the audience's cognition of the target disease.

[0027] Evaluate the effectiveness of patient education communication for target diseases based on communication effectiveness indicators and mindset change indicators.

[0028] In some embodiments, determining a communication effectiveness indicator based on the communication content data includes:

[0029] Extract the volume, interaction, exposure, and sentiment related to the target disease and related drugs from the communication content data;

[0030] The volume of voice, interaction, exposure and emotion are integrated to obtain the communication effectiveness index.

[0031] In some embodiments, based on the communication effectiveness index and the mindset change index, including:

[0032] Analyze the changing trends of opinions on target diseases and related drugs, feedback attitudes on educational content, and changes in cognitive opinions from the communication content data;

[0033] The trend of opinion change, attitude towards feedback on educational content and tendency of cognitive opinion change are integrated to obtain the index of mental change.

[0034] According to a second aspect of the present disclosure, there is provided a patient education dissemination device comprising:

[0035] The data analysis module is configured to perform cluster analysis on social media data to obtain hot topics of the target disease;

[0036] A strategy determination module is configured to determine target circles associated with the target disease and a targeted communication strategy for the target circles based on topic hotspots and a pre-built disease user circle library;

[0037] a communicator determination module, configured to screen target communicators according to the target disease and the target communication strategy, wherein the target communicators are commissioned to carry out patient education communication on the target disease on social media;

[0038] The effect evaluation module is configured to obtain preset evaluation indicators in social media and evaluate the effect of patient education communication on the target disease based on the evaluation indicators.

[0039] According to a third aspect of the present disclosure, an electronic device is provided, comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the patient education dissemination method provided in the third aspect of the present disclosure when running the program instructions.

[0040] According to a fourth aspect of the present disclosure, a storage medium is provided, in which computer program instructions are stored. When the computer program instructions are executed by a processor, the patient education and communication method provided by the third aspect of the present disclosure is executed.

[0041] The patient education dissemination method, device, electronic device, and storage medium provided by the embodiments of the present disclosure can achieve the following technical effects:

[0042] The disclosed embodiment adopts cloud services, big data processing and digital marketing technologies, and is a patient education and communication method. First, by collecting and analyzing massive patient discussion data on social media platforms, cluster analysis is performed on the data to identify the core hot topics of the target disease, thereby breaking through the traditional small sample limitations, dynamically tracking the latest discussion trends, and ensuring that the analysis results are synchronized with the current market environment; then, the hot topics obtained by cluster analysis are associated and matched with the pre-built disease user circle library, and interest circles with high correlation with the target disease are screened out. Based on the characteristics of the circle population, a customized communication strategy is formulated to shorten the strategy generation cycle and avoid the separation of various links; then, according to the target disease and communication strategy, professional matching communicators are screened out, automated screening reduces manual research costs, accurate matching improves communication conversion rate, and real-time tracking of communication effects is carried out to adjust resource allocation in a timely manner; finally, multi-dimensional evaluation indicators are set to quantify the communication effect, provide data-driven effect attribution analysis, and help to improve and improve subsequent communication strategies. The above solution systematically solves the shortcomings of patient education methods of related technologies in terms of sample size, timeliness, cost and effect tracking through social media big data cluster analysis, precise matching of interest circles, dynamic screening of communicators and closed-loop effect evaluation. It can complete patient education communication in a quick and efficient manner, and provides core technical support for pharmaceutical companies to enhance their competitiveness in the market.

[0043] The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] One or more embodiments are exemplarily described by corresponding drawings. These exemplary descriptions and drawings do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation. In addition,

[0045] Figure 1 It is a flowchart of a patient education and communication method provided by an embodiment of the present disclosure;

[0046] Figure 2 is a flowchart of another patient education and communication method provided by an embodiment of the present disclosure;

[0047] Figure 3 is a flowchart of another patient education and communication method provided by an embodiment of the present disclosure;

[0048] Figure 4 is a flowchart of another patient education and communication method provided by an embodiment of the present disclosure;

[0049] Figure 5 is a flowchart of another patient education and communication method provided by an embodiment of the present disclosure;

[0050] Figure 6 It is a structural diagram of a patient education and communication device provided by an embodiment of the present disclosure;

[0051] Figure 7 It is a structural diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0052] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The accompanying drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0053] In the description and claims of the embodiments of the present disclosure, as well as in the accompanying drawings, the terms "first," "second," and the like are used to distinguish similar items and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate to describe the embodiments of the present disclosure herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions.

[0054] Unless otherwise stated, the term "plurality" means two or more.

[0055] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0056] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0057] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0058] The present disclosure provides an electronic device, which is a device with computing capabilities, such as a personal computer, a server, or a network device. The electronic device can be used to execute the patient education dissemination method provided by the present disclosure.

[0059] In conjunction with the electronic device provided by the embodiment of the present disclosure (hereinafter referred to as the device), the embodiment of the present disclosure provides a patient education communication method, Figure 1 As shown, patient education communication methods include:

[0060] In step S101, the device performs cluster analysis on social media data to obtain hot topics of the target disease.

[0061] S102, the device determines the target circle associated with the target disease and the target communication strategy for the target circle based on the topic hot spots and the pre-built disease user circle library.

[0062] S103: The device screens target spreaders according to the target disease and the target spreading strategy.

[0063] In the disclosed embodiment, the communicator needs to be able to spread information on social media. In the medical field, communicators are usually health care professionals (HCPs), medical experts, health education specialists, or other personnel with relevant professional knowledge.

[0064] Here, we define target communicators as those selected based on the target disease and targeted communication strategy. Target communicators are commissioned to conduct patient education and dissemination on social media regarding the target disease. Specifically, they can be commissioned by brands or medical institutions to deliver healthcare information to target patient groups on social media platforms. Their primary mission is to enhance patient awareness, management, and treatment compliance regarding specific diseases through effective communication strategies and content creation. Trust-building: By consistently publishing high-quality, authoritative content, they build patient trust, thereby increasing the effectiveness of information dissemination.

[0065] In step S104 , the device obtains preset evaluation indicators from social media and evaluates the effectiveness of patient education and communication for the target disease based on the evaluation indicators.

[0066] The patient education communication method provided by the embodiment of the present disclosure first collects and analyzes massive patient discussion data on social media platforms, performs cluster analysis on the data, and identifies the core hot topics of the target disease, thereby breaking through the traditional small sample limitation, dynamically tracking the latest discussion trends, and ensuring that the analysis results are synchronized with the current market environment; then, the hot topics obtained by the cluster analysis are correlated and matched with the pre-built disease user circle library, and interest circles with a high correlation with the target disease are screened out, and customized communication strategies are formulated based on the characteristics of the circle population, shortening the strategy generation cycle and avoiding the separation of various links; then, according to the target disease and communication strategy, professional matching communicators are screened out, automated screening reduces manual research costs, accurate matching improves communication conversion rate, and real-time tracking of communication effects is carried out to adjust resource allocation in a timely manner; finally, multi-dimensional evaluation indicators are set to quantify the communication effect, provide data-driven effect attribution analysis, and contribute to the improvement and improvement of subsequent communication strategies. The above solution systematically solves the shortcomings of patient education methods of related technologies in terms of sample size, timeliness, cost and effect tracking through social media big data cluster analysis, precise matching of interest circles, dynamic screening of communicators and closed-loop effect evaluation. It can complete patient education communication in a quick and efficient manner, and provides core technical support for pharmaceutical companies to enhance their competitiveness in the market.

[0067] In some embodiments, cluster analysis is performed on social media data to obtain hot topics for the target disease, including: determining discussion data related to the target disease in the social media data; cluster analysis is performed on the discussion data to obtain hot topics for the target disease, wherein the hot topics include patient demand information and cognitive information about the target disease and related drugs.

[0068] By accurately identifying discussion data related to the target disease within massive amounts of social media data and performing cluster analysis on this discussion data, we can efficiently extract core hot topics about the target disease. These hot topics not only encompass patient needs but also their understanding of the target disease and related medications, providing a solid data foundation for the subsequent development of precise patient education and communication strategies. Furthermore, this method for obtaining hot topics for the target disease can significantly increase sample size coverage, ensuring a comprehensive reflection of patients' true needs and attitudes. It also shortens research cycles and improves timeliness, enabling pharmaceutical companies to quickly respond to market changes and promptly adjust communication strategies, ultimately achieving more efficient and targeted patient education and communication.

[0069] Combine Figure 2 As shown, the embodiment of the present disclosure provides another patient education communication method, which includes:

[0070] S201: The device determines discussion data related to a target disease in social media data.

[0071] In the disclosed embodiments, keywords related to the target disease can be pre-set. For example, the standardized name of the target disease and its common aliases or abbreviations, common symptoms, complications, and treatments related to the target disease, and the names and brand names of commonly used therapeutic drugs for the target disease can be included. Based on these keywords, discussion data related to the target disease can then be collected from social media data on social media platforms.

[0072] In step S202 , the device performs cluster analysis on the discussion data to obtain hot topics of the target disease.

[0073] In the disclosed embodiments, hot topics include patient demand information and knowledge about the target disease and related drugs. Specifically, in the discussion data, topic elements such as pharmaceutical brand, molecular formula, disease treatment, treatment effect, side effects, patient experience, drug price, and scientific research trends are split and clustered to obtain hot topics for the target disease.

[0074] In some embodiments, after initially obtaining the hot topics of the target disease, the hot topics can be deeply analyzed to extract valuable information and insights. The extracted hot topic information is then further clustered and classified to obtain the final hot topics, ensuring the accuracy and comprehensiveness of the analysis.

[0075] S203: The device determines a target circle associated with the target disease and a target communication strategy for the target circle based on the topic hot spots and a pre-built disease user circle library.

[0076] S204: The device screens target spreaders according to the target disease and the target spread strategy.

[0077] In step S205 , the device obtains preset evaluation indicators from social media, and evaluates the effect of patient education and communication on the target disease based on the evaluation indicators.

[0078] In some embodiments, based on hot topics and a pre-built database of disease user circles, target circles associated with the target disease and targeted communication strategies for these circles are determined. This includes: cross-analyzing hot topics and the pre-built database of disease user circles to identify the target circles with the highest degree of correlation with the target disease; and generating targeted communication strategies for these target circles based on the target circle's demographic attributes, content preferences, and cross-discussion characteristics related to the disease. Here, the targeted communication strategy includes topic carriers and social media touchpoints.

[0079] Topic carriers refer to the specific themes or content formats used to carry and convey specific information. Topic carriers include articles, videos, graphics, and interactive content. Social media touchpoints refer to the specific channels and methods for interacting with target audiences on social media platforms. Social media touchpoints include blogs, forums, and short video platforms.

[0080] By cross-analyzing hot topics extracted from social media data with a pre-built database of disease user circles, we can accurately screen out the target circles with the highest correlation with the target disease, ensuring the communication strategy is highly targeted and effective. Furthermore, based on the demographic attributes, content preferences, and cross-discussion characteristics of these target circles with the disease, we can generate customized communication strategies, including clarifying communication goals, selecting appropriate topic carriers and social media touchpoints, to achieve more precise content push and interaction methods, and improve the effectiveness and efficiency of patient education communication. This customized communication strategy not only clarifies the specific goals of communicating with the target circle, but also selects topic carriers that can arouse their interest and resonance (such as specific health topics or related activities), and disseminates them through the most appropriate social media platforms to maximize the coverage and influence of the information.

[0081] Combine Figure 3 As shown, the embodiment of the present disclosure provides another patient education communication method, which includes:

[0082] In step S301, the device performs cluster analysis on social media data to obtain hot topics of the target disease.

[0083] In step S302, the device cross-analyzes the hot topics and the pre-built disease user circle library to select the target circle with the highest correlation with the target disease.

[0084] In the disclosed embodiment, data collection is performed on the social media platform to ensure that a large amount of public postings are obtained in real time, and relevant keywords and tags are set according to the target disease and related topics (such as pharmaceutical brands, molecular formulas, treatment methods, effects, side effects, etc.). Then, a text clustering algorithm (such as K-means, hierarchical clustering) is used to classify the discussion content and identify different interest circles (such as drug treatment, diet control, exercise therapy, etc.); next, a user portrait is constructed based on the user's public information (such as personal profile, historical posting content), and the user is classified into the corresponding interest circle (such as insulin treatment circle) according to the discussion content and behavior pattern of the user; finally, a reasonable database structure is designed to store the account ID and related information (such as public information, discussion content, emotional tendency, interaction frequency, etc.) in each interest circle, and add tags to the accounts in each circle population library (such as "diabetes drug treatment circle", "diabetes diet control circle"), and finally a disease user circle library is obtained.

[0085] In the disclosed embodiment, the hot topics are matched with the various interest circles in the disease user circle, the correlation between each interest circle and the target disease is evaluated, and the interest circles whose discussion content is most correlated with the target disease are found as target circles. Specifically, a variety of methods such as keyword matching, semantic analysis, and context understanding can be used to ensure accurate identification of interest circles that are highly relevant to the target disease. For example, in diabetes management, the hot topic of "blood sugar control" may be highly correlated with the "diet control circle", while "insulin injection techniques" are closely linked to the "insulin treatment circle"; finally, based on the results of the cross-analysis, the interest circles with the highest correlation with the target disease are screened out as target circles.

[0086] S303: The device generates a target communication strategy for the target circle based on the target circle’s population attributes, content preferences, and cross-discussion characteristics with the disease.

[0087] S304: The device screens target spreaders according to the target disease and the target spread strategy.

[0088] S305 , the device obtains preset evaluation indicators from social media, and evaluates the effect of patient education and communication on the target disease based on the evaluation indicators.

[0089] In some embodiments, target communicators are screened according to the target disease and the target communication strategy, including: screening candidate communicators that match the target disease and the target communication strategy from a communicator database; obtaining potential risk data for each candidate communicator; and screening target communicators from the candidate communicators based on the potential risk data for each candidate communicator.

[0090] In the disclosed embodiments, by screening candidate communicators from the communicator database that match the target disease and target communication strategy, and obtaining the potential risk data for each candidate communicator, it is possible to accurately identify communicators who have high influence in specific fields and meet brand needs. Targeted communicators selected in this way can effectively convey patient education information on social media and effectively avoid potential risks.

[0091] Combine Figure 4 As shown, the embodiment of the present disclosure provides another patient education communication method, which includes:

[0092] In step S401, the device performs cluster analysis on social media data to obtain hot topics of the target disease.

[0093] S402: The device determines a target circle associated with the target disease and a target communication strategy for the target circle based on topic hotspots and a pre-built disease user circle library.

[0094] S403: The device screens candidate communicators that match the target disease and the target communication strategy from the communicator database.

[0095] In order to screen candidate communicators that match the target disease and target communication strategy from the communicator database, it is first necessary to build a comprehensive and detailed communicator database that contains relevant information about various potential communicators, such as their professional background, social media influence, historical published content, and audience characteristics.

[0096] Based on the specific needs of the target disease and the pre-defined targeted communication strategy (including communication objectives, topic carriers, and social media touchpoints), screening criteria are set. For example, a targeted communication strategy for diabetes management might include communication objectives for different aspects such as medication, diet control, and exercise therapy, and appropriate social media platforms are selected as the primary communication channels. Next, using technical means such as keyword matching, semantic analysis, and contextual understanding, an in-depth analysis of the communicators' historical content is conducted to identify those communicators who are suitable for the targeted communication strategy as candidate communicators.

[0097] In the disclosed embodiment, the target communication strategy includes topic carriers and social media contacts. Candidate communicators that match the target disease and the target communication strategy are screened from the communicator database, including: determining a first matching degree between the communicator's professional background and the target disease; determining the communicator's social media influence in the social media contacts included in the target communication strategy; determining a second matching degree between the communicator's historical published content published in the social media contacts included in the target communication strategy and the target disease; determining a third matching degree between the communicator's audience group in the social media contacts included in the target communication strategy and the target circle; determining a fourth matching degree between the carrier form of the communicator's historical published content published in the social media contacts included in the target communication strategy and the topic carrier included in the target communication strategy. Based on the first matching degree, social media influence, second matching degree, third matching degree and fourth matching degree, the matching score of the communicator is determined, and the candidate communicator is determined based on the matching score of each communicator.

[0098] In the disclosed embodiment, information such as the communicator's education background, professional qualifications, and work experience is extracted from the communicator database. Natural language processing techniques are used to analyze the communicator's professional background description and extract keywords related to the target disease. Based on the keyword matching results, each communicator is scored to obtain a first match degree.

[0099] In the disclosed embodiment, key social media touchpoints are selected based on the target communication strategy. Metrics such as the communicator's number of followers, interaction rate, and exposure are collected from each social media touchpoint. These metrics are used to assign a score to the communicator to determine social media influence. Scoring criteria may include: the larger the communicator's fan base, the higher the score; the more frequent the fan interaction, the higher the score; and the more times the content is displayed, the higher the score.

[0100] In an embodiment of the present disclosure, all content (posts, articles, videos, etc.) published in the past period of time is extracted from the communicator's social media account. These contents are analyzed, and keywords related to the target disease are extracted, and scores are performed based on the results of the matching between the target disease and the keywords to obtain a second degree of match. The scoring criteria may include: content relevance, that is, whether the content directly discusses the target disease and its treatment methods; content quality, that is, whether the content is scientific and authoritative; audience feedback, that is, whether the content is well received and supported by the audience. In an embodiment of the present disclosure, characteristic information (age, gender, geographic location, interests and hobbies, etc.) of the audience is extracted from the communicator's social media account. The characteristics of the communicator's audience group are compared with the population attributes of the target circle, and the third degree of match is calculated.

[0101] In the disclosed embodiment, the form of the content published by the communicator (articles, videos, pictures, live broadcasts, etc.) is extracted from the communicator's social media account. The communicator's content carrier form is compared with the topic carrier form in the target communication strategy to calculate a fourth matching degree.

[0102] In the disclosed embodiment, a communicator's match score is determined based on the first match, social media influence, second match, third match, and fourth match. This includes determining weights for the first match, social media influence, second match, third match, and fourth match based on the business objective of patient education and communication, and determining the communicator's match score based on the first match, social media influence, second match, third match, and fourth match and their weights. Business objectives include increasing brand awareness, improving patient treatment compliance, and the like.

[0103] Taking the business goal of increasing brand awareness as an example, the weights of social media influence, first matching degree, second matching degree, fourth matching degree, and third matching degree decrease in sequence. Taking the business goal of improving patient treatment compliance as an example, the weights of first matching degree, social media influence, second matching degree, third matching degree, and fourth matching degree decrease in sequence. In the disclosed embodiment, communicators whose matching scores are greater than a preset score can be determined as candidate communicators. Alternatively, communicators whose matching scores rank in the top N are determined as candidate communicators. Where N is a positive integer.

[0104] S404: The device obtains potential risk data of each candidate disseminator.

[0105] S405 : The device selects target communicators from the candidate communicators based on the potential risk data of each candidate communicator.

[0106] In the disclosed embodiment, candidate communicators are checked for compliance issues or negative feedback in their past published content to ensure that the selected communicators can not only effectively convey patient education information but also effectively avoid potential risks. Ultimately, based on these comprehensive evaluation results, candidate communicators that best meet the requirements of the target disease and target communication strategy are screened from the communicator database and selected as target communicators.

[0107] In step S406 , the device obtains preset evaluation indicators from social media, and evaluates the effect of patient education and communication on the target disease based on the evaluation indicators.

[0108] In some embodiments, obtaining preset evaluation indicators from social media and evaluating the effectiveness of patient education communication for the target disease based on the evaluation indicators may include: obtaining communication content data related to the target disease and related drugs from social media; determining a communication effectiveness indicator based on the communication content data; calculating a mindset change indicator based on the communication content data; and evaluating the effectiveness of patient education communication for the target disease based on the communication effectiveness indicator and the mindset change indicator. Here, the mindset change indicator is an evaluation indicator used to assess the long-term impact of patient education communication on the audience's cognition of the target disease, and the communication effectiveness indicator is an evaluation indicator used to assess the immediate communication effect of the patient education content.

[0109] By capturing communication content data related to target diseases and related medications from social media and determining communication effectiveness indicators based on this content data, the immediate communication effects of patient education content can be assessed in real time, ensuring the effectiveness and reach of communication activities. Simultaneously, by calculating mindset change indicators based on the same communication content data, we can deeply assess the long-term impact of patient education on audience cognition of the target disease, helping brands understand the effectiveness of communication activities in changing patient attitudes and behaviors. Combining communication effectiveness indicators with mindset change indicators allows for a comprehensive assessment of the effectiveness of patient education communication for target diseases, providing not only immediate communication feedback but also tracking long-term cognitive changes, thereby providing a scientific basis for optimizing future communication strategies.

[0110] Combine Figure 5 As shown, the embodiment of the present disclosure provides another patient education communication method, which includes:

[0111] In step S501 , the device performs cluster analysis on social media data to obtain hot topics of the target disease.

[0112] S502: The device determines a target circle associated with the target disease and a target communication strategy for the target circle based on topic hotspots and a pre-built disease user circle library.

[0113] S503: The device screens target spreaders according to the target disease and the target spread strategy.

[0114] S504: The device obtains dissemination content data related to the target disease and related drugs in social media.

[0115] S505, the device determines a communication effectiveness index based on the communication content data.

[0116] In the disclosed embodiments, the communication effectiveness index is used to evaluate the immediate communication effectiveness of patient education content. Specifically, the communication content data is extracted from the buzz, interaction, exposure, and sentiment related to the target disease and related drugs; the buzz, interaction, exposure, and sentiment are then integrated to obtain the communication effectiveness index.

[0117] Each post in the dissemination content data hit by the keyword is recorded as a corresponding voice. For example, the social media voice of "hypertension" is the total number of posts on the social media platform that mention the keyword "hypertension" in all dissemination content data. Interaction volume refers to the sum of interactive actions that netizens can perform under each post. The specific form of interaction varies depending on the platform. Typical interactive behaviors include "comments", "forwards" and "likes". Exposure refers to the number of times the dissemination content data is seen on the social media platform. It may be reflected in indicators such as "reading volume" and "play volume" on different platforms. Emotionality refers to the emotional expression tendency of the dissemination content data, such as positive, negative, and neutral.

[0118] In the disclosed embodiment, each sub-indicator (volume, interaction, exposure, and sentiment) can be standardized to make them comparable; for example, each sub-indicator can be converted into a standard score with a mean of 0 and a standard deviation of 1. Then, weights are assigned based on the importance of each indicator. The weights can be determined based on historical data or expert opinions. For example, for some brands, interaction may be more important than exposure, so a higher weight can be assigned. Finally, the standardized indicators are weighted and summed according to their weights to obtain the final communication effectiveness indicator.

[0119] By extracting the volume, interaction, exposure, and sentiment related to the target disease and related drugs from the communication content data, we can fully capture the immediate dissemination effect of patient education content on social media; then, we integrate these multi-dimensional data to generate a comprehensive communication effectiveness indicator, which can intuitively evaluate the actual influence and audience response of each communication content.

[0120] S506: The device collects mental change indicators based on the dissemination content data.

[0121] In this disclosed embodiment, the mindset change index is used to assess the long-term impact of patient education on the audience's understanding of the target disease. Specifically, the communication content data is analyzed to identify the changing trends in opinions regarding the target disease and related medications, the feedback attitudes towards the educational content, and the tendency of cognitive opinion changes. The mindset change index is then integrated with these trends, the feedback attitudes towards the educational content, and the tendency of cognitive opinion changes.

[0122] In an embodiment of the present disclosure, natural language processing technology is used to perform a time series analysis of discussion content to identify how the public's views on target diseases and related drugs change over time. For example, by analyzing the frequency and sentiment of keywords within a specific time period, it is possible to understand whether the public's attitude towards a new drug is gradually becoming positive or negative. Through in-depth analysis of user comments and interactive behaviors, the audience's acceptance of and feedback on patient education content can be evaluated. Specifically, users' specific feedback on educational content can be identified, such as whether they think the content is useful, whether it is easy to understand, and whether it has changed their cognition. By tracking users' discussion content over a long period of time, it is possible to identify whether their cognitive concepts about target diseases and related drugs have changed significantly. For example, some users may initially be skeptical about a certain treatment, but over time, their views become more positive or trusting.

[0123] After completing the three analyses above, the next step is to integrate these results to generate a comprehensive mindset change index. First, each indicator is standardized to make them comparable. For example, opinion change trends, feedback attitudes, and cognitive opinion change tendencies can be converted into standardized scores with a mean of 0 and a standard deviation of 1. Then, weights are assigned to each indicator based on its importance. Weights can be determined based on historical data, expert opinion, or actual business needs. For example, for some brands, cognitive opinion changes may be more important than short-term feedback attitudes and therefore warrant a higher weight. Finally, the standardized indicators are weighted and summed according to their weights to produce the final mindset change index.

[0124] By analyzing the communication content data to identify trends in opinions regarding target diseases and related drugs, feedback attitudes toward educational content, and the tendency of cognitive opinion changes, it is possible to comprehensively assess the impact of patient education communication on the audience's long-term cognition and attitudes. This approach, through in-depth analysis of large amounts of social media discussion data, identifies how patients' views on specific diseases and related drugs have evolved over time, their acceptance of and feedback on educational content, and whether their cognitive perspectives have undergone positive changes. These analyzed opinion trends, feedback attitudes toward educational content, and cognitive opinion change tendencies are then integrated to generate a comprehensive mindset change index, which can accurately assess the effectiveness of patient education activities in changing patient attitudes and behaviors.

[0125] S507, the device evaluates the effect of patient education communication on the target disease based on the communication effectiveness index and the mind change index.

[0126] In some embodiments, the communication effectiveness index before patient education and communication can be obtained, and this communication effectiveness index can be used as an evaluation benchmark. The communication effectiveness index after patient education and communication can be continuously tracked, and the communication effectiveness index can be compared with the evaluation benchmark to obtain the communication effectiveness change result, which can be used to evaluate the patient education and communication effect for the target disease. In some embodiments, the communication effectiveness index in the early, middle and late stages of a specific social media activity can be tracked, and the communication effectiveness index in the early, middle and late stages can be compared to obtain the communication effectiveness change result, which can be used to evaluate the patient education and communication effect for the target disease. Here, the communication effectiveness change result and the mental change index can be combined to evaluate the patient education and communication effect for the target disease.

[0127] In the disclosed embodiment, relevant optimization effect evaluation can also be performed on some auxiliary means of patient education and communication (such as social media search engine optimization) to help brands determine whether these optimization means have achieved the expected results.

[0128] Combine Figure 6 As shown, an embodiment of the present disclosure provides a patient education communication device 600 , which includes a data analysis module 601 , a strategy determination module 602 , a communicator determination module 603 and an effect evaluation module 604 .

[0129] The data analysis module 601 is configured to perform cluster analysis on social media data to obtain hot topics for the target disease. The strategy determination module 602 is configured to determine the target circle associated with the target disease and the target communication strategy for the target circle based on the hot topics and the pre-built disease user circle library. The communicator determination module 603 is configured to screen the target communicators according to the target disease and the target communication strategy. The target communicators are used to be entrusted to carry out patient education and communication on the target disease on social media. The effect evaluation module 604 is configured to obtain preset evaluation indicators in social media and evaluate the effect of patient education and communication on the target disease based on the evaluation indicators.

[0130] The patient education communication device 600 provided in the embodiment of the present disclosure first collects and analyzes massive patient discussion data on social media platforms, performs cluster analysis on the data, and identifies the core hot topics of the target disease, thereby breaking through the traditional small sample limitation, dynamically tracking the latest discussion trends, and ensuring that the analysis results are synchronized with the current market environment; then, the hot topics obtained by the cluster analysis are associated and matched with the pre-built disease user circle library, and interest circles with a high correlation with the target disease are screened out, and customized communication strategies are formulated based on the characteristics of the circle population, shortening the strategy generation cycle and avoiding the separation of various links; then, according to the target disease and communication strategy, professional matching communicators are screened out, automated screening reduces manual research costs, accurate matching improves communication conversion rate, and real-time tracking of communication effects is carried out to adjust resource allocation in a timely manner; finally, multi-dimensional evaluation indicators are set to quantify the communication effect, provide data-driven effect attribution analysis, and contribute to the improvement and improvement of subsequent communication strategies. The above solution systematically solves the shortcomings of patient education methods of related technologies in terms of sample size, timeliness, cost and effect tracking through social media big data cluster analysis, precise matching of interest circles, dynamic screening of communicators and closed-loop effect evaluation. It can complete patient education communication in a quick and efficient manner, and provides core technical support for pharmaceutical companies to enhance their competitiveness in the market.

[0131] In some embodiments, the data analysis module 601 is configured to:

[0132] Identify discussion data related to the target disease in social media data;

[0133] Cluster analysis is performed on the discussion data to obtain hot topics of the target disease, where the hot topics include patient demand information and cognitive information about the target disease and related drugs.

[0134] In some embodiments, the policy determination module 602 is configured to:

[0135] Cross-analyze hot topics and pre-built disease user circle databases to identify target circles with the highest correlation with the target disease;

[0136] Based on the population attributes, content preferences and cross-discussion characteristics of the target circle and the disease, a targeted communication strategy for the target circle is generated.

[0137] In some embodiments, the propagator determination module 603 is configured to:

[0138] Screen candidate communicators matching the target disease and target communication strategy from the communicator database;

[0139] Obtaining data on the potential risk of each candidate spreader;

[0140] Based on the potential risk data of each candidate communicator, target communicators are screened out from the candidate communicators.

[0141] In some embodiments, the effect evaluation module 604 is configured to:

[0142] Obtain data on dissemination content related to target diseases and related drugs in social media;

[0143] Determining a communication effectiveness index based on the communication content data, wherein the communication effectiveness index is an evaluation index used to evaluate the immediate communication effect of the patient education content;

[0144] Mindset change indicators are calculated based on the communication content data. The mindset change indicators are used to evaluate the long-term impact of patient education communication on the audience's cognition of the target disease.

[0145] Evaluate the effectiveness of patient education communication for target diseases based on communication effectiveness indicators and mindset change indicators.

[0146] In some embodiments, the effect evaluation module 604 is configured to:

[0147] Extract the volume, interaction, exposure, and sentiment related to the target disease and related drugs from the communication content data;

[0148] The volume of voice, interaction, exposure and emotion are integrated to obtain the communication effectiveness index.

[0149] In some embodiments, the effect evaluation module 604 is configured to:

[0150] Analyze the changing trends of opinions on target diseases and related drugs, feedback attitudes on educational content, and changes in cognitive opinions from the communication content data;

[0151] The trend of opinion change, attitude towards feedback on educational content and tendency of cognitive opinion change are integrated to obtain the index of mental change.

[0152] Combine Figure 7As shown, an embodiment of the present disclosure provides an electronic device 700, which includes a processor 701 and a memory 702. Optionally, the electronic device 700 may further include a communication interface 703 and a bus 704. The processor 701, the communication interface 703, and the memory 702 may communicate with each other through the bus 704. The communication interface 703 may be used for information transmission. The processor 701 may call the logic instructions in the memory 702 to execute the patient education communication method of the above embodiment.

[0153] In addition, the logic instructions in the memory 702 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0154] Memory 702, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of the present disclosure. Processor 701 executes the program instructions / modules stored in memory 702 to perform functional applications and data processing, thereby implementing the patient education and dissemination methods in the above-mentioned embodiments.

[0155] The memory 702 may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal device. Furthermore, the memory 702 may include high-speed random access memory and non-volatile memory.

[0156] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above-mentioned patient education dissemination method.

[0157] The technical solutions of the embodiments of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present disclosure. The aforementioned storage medium may be a non-transitory storage medium, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, among other media capable of storing program code.

[0158] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible variations. Unless explicitly required, individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to also include plural forms. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variations "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups of these. In the absence of further restrictions, an element defined by the sentence "comprising a..." does not exclude the presence of other identical elements in the process, method or device that includes the element. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments can be referenced to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can be found in the description of the method part.

[0159] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. The technicians will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0160] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units can be merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, and can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of the present disclosure may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0161] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architectures, functions and operations of the systems, methods and computer program products according to the embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of the code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or action, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A patient education communication method, characterized in that: include: Perform cluster analysis on social media data to obtain hot topics of target diseases; Based on hot topics and a pre-built disease user circle database, identify target circles associated with the target disease and target communication strategies for these circles; Screen target communicators based on the target disease and target communication strategy. Target communicators are commissioned to conduct patient education and communication on social media for the target disease. Obtain preset evaluation indicators in social media and evaluate the effectiveness of patient education communication for target diseases based on the evaluation indicators.

2. The patient education communication method according to claim 1, characterized in that: Cluster analysis is performed on social media data to obtain hot topics for the target disease, including: Identify discussion data related to the target disease in social media data; Cluster analysis is performed on the discussion data to obtain hot topics of the target disease, where the hot topics include patient demand information and cognitive information about the target disease and related drugs.

3. The patient education communication method according to claim 1, characterized in that: Based on hot topics and a pre-built disease user community database, target communities associated with the target disease and targeted communication strategies for these communities are identified, including: Cross-analyze hot topics and pre-built disease user circle databases to identify target circles with the highest correlation with the target disease; Based on the population attributes, content preferences and cross-discussion characteristics of the target circle and the disease, a targeted communication strategy for the target circle is generated.

4. The patient education communication method according to claim 1, characterized in that: Screening of target communicators based on target disease and target communication strategy, including: Screen candidate communicators matching the target disease and target communication strategy from the communicator database; Obtaining data on the potential risk of each candidate spreader; Based on the potential risk data of each candidate communicator, target communicators are screened out from the candidate communicators.

5. The patient education communication method according to claim 1, characterized in that: Obtain preset evaluation indicators in social media and evaluate the effectiveness of patient education communication for target diseases based on the evaluation indicators, including: Obtain data on dissemination content related to target diseases and related drugs in social media; Determining a communication effectiveness index based on the communication content data, wherein the communication effectiveness index is an evaluation index used to evaluate the immediate communication effect of the patient education content; Mindset change indicators are calculated based on the communication content data. The mindset change indicators are used to evaluate the long-term impact of patient education communication on the audience's cognition of the target disease. Evaluate the effectiveness of patient education communication for target diseases based on communication effectiveness indicators and mindset change indicators.

6. The patient education communication method according to claim 5, characterized in that: Determine communication effectiveness indicators based on communication content data, including: Extract the volume, interaction, exposure, and sentiment related to the target disease and related drugs from the communication content data; The volume of voice, interaction, exposure and emotion are integrated to obtain the communication effectiveness index.

7. The patient education communication method according to claim 5, characterized in that: Based on communication effectiveness indicators and mindset change indicators, including: Analyze the changing trends of opinions on target diseases and related drugs, feedback attitudes on educational content, and changes in cognitive opinions from the communication content data; The trend of opinion change, attitude towards feedback on educational content and tendency of cognitive opinion change are integrated to obtain the index of mental change.

8. A patient education communication device, characterized in that: include: The data analysis module is configured to perform cluster analysis on social media data to obtain hot topics of the target disease; A strategy determination module is configured to determine target circles associated with the target disease and a targeted communication strategy for the target circles based on topic hotspots and a pre-built disease user circle library; a communicator determination module, configured to screen target communicators according to the target disease and the target communication strategy, wherein the target communicators are commissioned to carry out patient education communication on the target disease on social media; The effect evaluation module is configured to obtain preset evaluation indicators in social media and evaluate the effect of patient education communication on the target disease based on the evaluation indicators.

9. An electronic device comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the patient education dissemination method according to any one of claims 1 to 7 when executing the program instructions.

10. A storage medium, characterized in that: The storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the patient education and communication method according to any one of claims 1 to 7 is executed.

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