Patient doctor-seeing satisfaction evaluation system based on big data

Abstract

The invention discloses a patient medical satisfaction evaluation system based on big data, and relates to the technical field of big data analysis. The medical satisfaction evaluation system comprises a data acquisition and processing module, an evaluation index management module, a satisfaction questionnaire survey module, a multi-dimensional evaluation module, a satisfaction grading module and a service quality optimization module. According to the big data-based patient doctor-seeing satisfaction degree evaluation system, through real-time collection and analysis of patient satisfaction degree data including a medical quality evaluation index and a doctor-seeing experience evaluation index, registration waiting time, diagnosis and treatment waiting time and an endemic area environment score are monitored, service bottlenecks and patient dissatisfaction fields are rapidly identified, and the patient satisfaction degree evaluation efficiency is improved. The hospital can adjust resource distribution in time, the overall quality of medical services is evaluated through the patient complaint score and the doctor-patient communication transparency score, effective communication between doctors and patients is promoted, transparency is improved, and therefore the satisfaction degree and credibility of the patients for the medical services are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and in particular to a patient medical satisfaction evaluation system based on big data. Background Art

[0002] In the field of medical health, hospitals need to continuously improve service quality to attract and retain patients. Patient satisfaction is an important yardstick for measuring the quality of medical services and is also the key to the hospital's brand reputation and long-term development. With the continuous advancement of medical technology and the increasing awareness of people's health, patients' requirements for medical services are also increasing. In recent years, big data technology has developed rapidly and has been widely used in various fields. In the field of medical health, big data technology also plays an important role. Through big data analysis and mining, medical institutions can deeply understand patients' needs and preferences, optimize service processes, and provide more accurate and personalized medical services.

[0003] In the existing technology, medical satisfaction is often evaluated from a single dimension. However, the patient's medical process is a complex process, involving multiple aspects of the hospital's medical process. Satisfaction evaluation from a single dimension is difficult to accurately reflect the patient's satisfaction. Therefore, a patient medical satisfaction evaluation system based on big data is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a patient medical satisfaction evaluation system based on big data, the medical satisfaction evaluation system comprising a data collection and processing module, an evaluation index management module, a satisfaction questionnaire survey module, a multi-dimensional evaluation module, a satisfaction grading module and a service quality optimization module, wherein the modules are connected by electrical signals;

[0005] The data collection and processing module collects various data of patients during the medical treatment process, including basic information, medical records, treatment feedback, and online evaluations, to ensure the comprehensiveness and real-time nature of the data, provide a reliable basis for subsequent analysis and evaluation, and clean, organize and standardize the collected data to remove redundant and junk data, improve data quality, and ensure data accuracy and consistency;

[0006] The evaluation index management module specifies multiple evaluation indexes for evaluating medical satisfaction based on pre-processed patient medical data, and obtains relevant information of the evaluator and the evaluated. The evaluation indexes include medical quality evaluation indexes and medical experience evaluation indexes. The medical quality evaluation indexes include patient complaint scores and doctor-patient communication transparency scores. The medical experience evaluation indexes include registration waiting time, diagnosis and treatment waiting time, and ward environment scores.

[0007] The satisfaction questionnaire survey module uses an electronic questionnaire survey system to comprehensively evaluate multiple evaluation indicators of medical satisfaction and obtain the patient's scoring results on each evaluation indicator of the medical environment, thereby eliminating the cumbersome steps of traditional paper questionnaires and improving data collection efficiency and accuracy;

[0008] The multi-dimensional evaluation module combines the scoring results of multiple evaluation indicators to comprehensively evaluate the patient's medical satisfaction from multiple dimensions, analyze the patient's satisfaction trend, fully reflect the patient's various needs and opinions during the medical treatment process, and improve the accuracy and comprehensiveness of the evaluation;

[0009] The satisfaction grading module divides the patient's medical satisfaction into different satisfaction levels according to the results of the satisfaction analysis and the pre-set grading standards;

[0010] The service quality optimization module, based on the patient satisfaction evaluation results, uses big data technology to conduct real-time analysis of patient medical satisfaction, discover and handle patient dissatisfaction and complaints, improve the response speed and efficiency of medical services, and enhance patients' medical experience and satisfaction.

[0011] Preferably, in the data collection and processing module, the process of collecting patient medical treatment process data includes:

[0012] Use API interfaces and database connections to capture data from the hospital's electronic medical record system, patient information management system, online appointment system, feedback and evaluation system, and establish data transmission channels to transmit the collected data to the data warehouse of the medical satisfaction evaluation system;

[0013] Create table structures and fields for received data in the data warehouse, receive and store data from various data sources, and ensure data integrity and security;

[0014] Preprocess the raw data stored in the data warehouse, including data cleaning, data integration, and data normalization procedures, format the date, time and other fields, integrate data from different data sources to form a complete patient medical record, and establish indexes and relationship tables for quick query and association of data.

[0015] Preferably, in the evaluation index management module, the process of evaluation index management specifically includes:

[0016] Call the pre-processed patient medical data, clarify the evaluation indicators of medical satisfaction assessment, namely medical quality evaluation indicators and medical experience evaluation indicators, analyze the data source and type required for each evaluation indicator, and ensure the availability and integrity of the data. The medical quality evaluation indicators include patient complaint scores and doctor-patient communication transparency scores, and the medical experience evaluation indicators include registration waiting time, diagnosis and treatment waiting time, and ward environment scores;

[0017] Map the pre-processed patient medical data with the evaluation indicators, determine the corresponding relationship between each data field and the evaluation indicator, and mark the patient medical data associated with each evaluation indicator;

[0018] A standard evaluation threshold is preset for each evaluation indicator, which is compared with the marked evaluation indicator data to obtain the score results of each evaluation indicator. The calculated score results are stored in the data warehouse, and the abnormal change values ​​relative to the standard evaluation threshold are marked.

[0019] Preferably, in the satisfaction questionnaire survey module, the process of obtaining the scoring results of each evaluation indicator includes:

[0020] Design electronic questionnaires based on medical quality evaluation indicators (patient complaint scores, doctor-patient communication transparency scores) and medical experience evaluation indicators (registration waiting time, diagnosis and treatment waiting time, ward environment scores), ensure that the questionnaire questions are clear and concise, and easy for patients to understand and answer. Build an electronic questionnaire survey system, import the designed questionnaires into the system, and set up a questionnaire distribution and collection mechanism;

[0021] Electronic questionnaires are distributed to patients through SMS and WeChat official account channels. After the patient's consultation, the staff guides them to complete the questionnaire. The patient scores each evaluation indicator in the questionnaire based on his or her own medical experience;

[0022] Based on the relevant data of patient complaint scores and doctor-patient communication transparency scores, the medical quality evaluation index is calculated to analyze the changing trend of medical quality. Based on the relevant data of registration waiting time, diagnosis and treatment waiting time and ward environment scores, the medical experience evaluation index is calculated to analyze the changing trend of patients' medical experience.

[0023] The calculated medical quality evaluation index and medical experience evaluation index were analyzed to identify the strengths and weaknesses of hospital services, and to detect outliers with extremely low and high scores for further investigation.

[0024] Preferably, the expression of the medical quality evaluation index is:

[0025] ;

[0026] in, is the medical quality evaluation index. For the The weight of each medical quality evaluation indicator indicates the relative importance of the indicator in the overall evaluation, and reflects the relative importance of different evaluation indicators in the medical quality evaluation. For the The actual observed values ​​of the medical quality evaluation indicators, For the The benchmark value of a medical quality evaluation indicator indicates the standard value of the indicator. For the The maximum value of the medical quality evaluation index is used for standardization. It is the exponent of the exponential function, which is used to adjust the sensitivity of the formula. It is generally taken as a value greater than 1 to enhance the sensitivity to outliers. The value range of is 0 to 1. The closer the value is to 1, the higher the medical quality is, and the closer the value is to 0, the lower the medical quality is.

[0027] The expression of the medical experience evaluation index is:

[0028] ;

[0029] in, The medical experience evaluation index is For the The actual observed value of the medical experience evaluation index, For the The benchmark value of a medical experience evaluation indicator indicates the standard value of the indicator. For the The standard deviation of the medical experience evaluation index is used to measure the dispersion of the data and represents the variability of each medical experience evaluation index. The value range is 0 to 1. The closer the value is to 1, the better the medical experience is, and the closer the value is to 0, the worse the medical experience is.

[0030] Preferably, in the multi-dimensional evaluation module, the analysis process of patient satisfaction trend includes:

[0031] Integrate the relevant data of each evaluation indicator, assign corresponding weights according to the importance of each evaluation indicator to reflect its influence on the overall satisfaction, and standardize the collected data to ensure that the data of different indicators are comparable;

[0032] Combine the medical quality evaluation index and the medical experience evaluation index, as well as their respective weights, to calculate the satisfaction evaluation coefficient, and organize the calculated satisfaction evaluation coefficient to form time series data, which is then smoothed to eliminate the impact of random fluctuations, and then the changing trend of the satisfaction evaluation coefficient is analyzed;

[0033] Analyze the changing trends of patient satisfaction, identify abnormally high or low scores by comparing the satisfaction evaluation coefficients in different time periods, and further analyze to clarify the causes and influencing factors of changes in patient satisfaction.

[0034] Preferably, the expression of the satisfaction evaluation coefficient is:

[0035] ;

[0036] in, is the satisfaction evaluation coefficient, is the medical quality evaluation index. The medical experience evaluation index is is the benchmark value of the medical quality evaluation index. is the benchmark value of the medical experience evaluation index. is the weight of the medical quality evaluation index, is the weight of the medical experience evaluation index, The value range is from 0 to 1. The closer the value is to 1, the higher the patient satisfaction is, and the closer the value is to 0, the lower the patient satisfaction is.

[0037] Preferably, in the satisfaction rating module, the satisfaction rating classification process includes:

[0038] According to the numerical range of the satisfaction evaluation coefficient, a clear satisfaction grading standard is formulated, and different satisfaction levels are set, namely very satisfied, satisfied, average, dissatisfied, and very dissatisfied, and the corresponding evaluation threshold is matched for each satisfaction level;

[0039] The calculated satisfaction evaluation coefficient is compared with the evaluation threshold of each satisfaction level, and the patient's medical satisfaction is divided into corresponding satisfaction levels according to the comparison results;

[0040] The divided satisfaction levels are output to the system, and the satisfaction evaluation results of each patient are recorded to facilitate the hospital's subsequent tracking and analysis of patient satisfaction. Based on the satisfaction level classification results, a satisfaction evaluation report is generated and fed back to relevant departments so that services can be improved based on the reported information.

[0041] Preferably, the plurality of satisfaction levels and the plurality of evaluation thresholds satisfy the following relationship:

[0042] Very satisfied ;

[0043] satisfy ;

[0044] generally ;

[0045] Dissatisfied ;

[0046] Very dissatisfied ;

[0047] in, is the satisfaction evaluation coefficient, is the lower threshold corresponding to very satisfied and the upper threshold corresponding to satisfied, is the lower threshold corresponding to satisfaction and the upper threshold corresponding to general. is the lower threshold corresponding to the general and the upper threshold corresponding to the unsatisfactory, is the lower threshold corresponding to dissatisfaction and the upper threshold corresponding to very dissatisfaction, , , , .

[0048] Preferably, the service quality optimization module specifically includes:

[0049] Based on the collected patient satisfaction data after medical treatment, use big data technology to monitor and analyze the patient satisfaction evaluation results in real time, analyze the overall trend of patient satisfaction, the distribution of satisfaction in each dimension, and hot issues of dissatisfaction and complaints;

[0050] Based on real-time analysis results, patients’ dissatisfaction and complaints can be quickly identified, classified and marked for subsequent processing, and specific processing procedures can be developed for different types of dissatisfaction and complaints to ensure that the processing process is efficient, transparent and can quickly resolve patients’ problems;

[0051] Communicate with patients in a timely manner according to the processing procedures, clarify specific issues and needs, and take appropriate measures to deal with them according to the nature of the issues. Track the processing process to ensure that the issues are effectively resolved, provide feedback to patients on the processing results, and collect feedback from patients in order to further improve services;

[0052] Based on the results of the patient satisfaction analysis, we identify bottlenecks and deficiencies in the service process, optimize the service process, improve the response speed and efficiency of the service, and train medical staff to ensure that they can handle patients' problems and needs quickly and accurately.

[0053] The present invention provides a patient medical satisfaction evaluation system based on big data. It has the following beneficial effects:

[0054] 1. This patient medical satisfaction evaluation system based on big data collects and analyzes patient satisfaction data in real time, including the medical quality evaluation index and the medical experience evaluation index, monitors the registration waiting time, diagnosis and treatment waiting time and ward environment score, and quickly identifies service bottlenecks and areas of patient dissatisfaction, enabling hospitals to adjust resource allocation in a timely manner. It also evaluates the overall quality of medical services through patient complaint scores and doctor-patient communication transparency scores, promotes effective communication between doctors and patients, and improves transparency, thereby enhancing patients' satisfaction and trust in medical services.

[0055] 2. This patient medical satisfaction evaluation system based on big data, by comprehensively collecting patients' medical experience data, can enable hospitals to have a deep understanding of patients' needs, thereby providing more personalized and humane services, discovering and solving specific problems that affect patient satisfaction, helping to improve patients' medical experience, and enhancing patients' loyalty and satisfaction with the hospital, so as to provide patients with more personalized medical services, thereby improving treatment outcomes and patient satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a block diagram of a patient medical satisfaction evaluation system based on big data according to the present invention;

[0057] Figure 2 A flowchart for obtaining the scoring results of each evaluation index of the present invention;

[0058] Figure 3 The present invention is a flowchart for analyzing the patient satisfaction trend;

[0059] Figure 4 This is a flow chart for dividing the satisfaction levels of the present invention. DETAILED DESCRIPTION

[0060] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0061] The first embodiment, as Figure 1 , Figure 2As shown, the present invention provides a technical solution: a patient medical satisfaction evaluation system based on big data, the medical satisfaction evaluation system includes a data acquisition and processing module, an evaluation index management module, a satisfaction questionnaire survey module, a multi-dimensional evaluation module, a satisfaction grading module and a service quality optimization module, wherein the modules are connected by electrical signals;

[0062] The data collection and processing module collects various data of patients during the medical treatment process, including basic information, medical records, treatment feedback, and online evaluations, to ensure the comprehensiveness and real-time nature of the data, provide a reliable basis for subsequent analysis and evaluation, and clean, organize and standardize the collected data for pre-processing, remove redundant and junk data, improve data quality, ensure data accuracy and consistency, use API interfaces and database connections to capture data from the hospital's electronic medical record system, patient information management system, online appointment system, feedback and evaluation system, and establish a data transmission channel to transmit the collected data to the data warehouse of the medical satisfaction evaluation system, create table structures and fields for the received data in the data warehouse, receive and store data from various data sources, Ensure the integrity and security of data, pre-process the raw data stored in the data warehouse, including data cleaning, data integration and data normalization operations, in which unique identifiers (patient visit numbers) are used to identify and remove duplicate records, and obvious errors or inconsistent data, such as wrong dates, incomplete records, etc., are corrected, and data fields not related to business logic are deleted to reduce data redundancy and improve data quality. The data formats of different data sources are uniformly converted into a standard format for subsequent analysis and processing, and data encoding is standardized, and fields such as date and time are formatted. Data from different data sources are integrated to form a complete patient medical record, and indexes and relationship tables are established to quickly query and associate data;

[0063] The evaluation index management module, based on the pre-processed patient medical data, clarifies multiple evaluation indicators for medical satisfaction assessment, and realizes the acquisition of relevant information between the evaluator and the evaluated. Among them, the evaluation indicators include medical quality evaluation indicators and medical experience evaluation indicators. The medical quality evaluation indicators include patient complaint scores and doctor-patient communication transparency scores. The medical experience evaluation indicators include registration waiting time, diagnosis and treatment waiting time and ward environment scores. The pre-processed patient medical data is called to clarify the evaluation indicators for medical satisfaction assessment, which are medical quality evaluation indicators and medical experience evaluation indicators. The data source and type required for each evaluation indicator are analyzed to ensure the availability and integrity of the data. Among them, the medical quality evaluation indicators include patient complaint scores and doctor-patient communication transparency scores. The medical experience evaluation indicators include registration waiting time, diagnosis and treatment waiting time and ward environment score. The patient complaint score reflects the patient's dissatisfaction with the medical service process or the frequency of complaints. The patient complaint score is obtained by statistics and analysis of the content, number and handling of patient complaints to evaluate the overall quality of medical services and patient satisfaction. The doctor-patient communication transparency score reflects whether the communication between the doctor and the patient is clear and sufficient, and whether the doctor has explained the patient's condition and treatment plan in detail. High transparency helps to enhance patients' trust and satisfaction. Registration waiting time refers to the time required for patients to register and start treatment. A shorter registration waiting time can improve the patient's medical efficiency and reduce their anxiety during the waiting process. The waiting time for diagnosis and treatment refers to the time required for patients to enter the consulting room and the time required for the doctor to start the diagnosis and treatment during the diagnosis and treatment process. It reflects the timeliness and efficiency of medical services and is crucial to improving patient satisfaction. By scoring the ward environment (such as cleanliness, quietness, completeness of facilities, etc.), the hospital's performance in providing a comfortable medical environment is evaluated. The pre-processed patient medical data is mapped to the evaluation indicators, the correspondence between each data field and the evaluation indicator is determined, and the patient medical data associated with each evaluation indicator is marked. A standard evaluation threshold is preset for each evaluation indicator, which is compared with the marked evaluation indicator data to obtain the score results of each evaluation indicator, and the calculated score results are stored in the data warehouse. The relative standard evaluation threshold is compared with the Abnormal change values ​​are marked. For the patient complaint score, if the number of complaints per month is less than 5 times, it is within the normal range. If there are new concentrated complaints that seriously affect patients' medical treatment, it is marked as an abnormal change value. For the doctor-patient communication transparency score, an average score of 4 points or above (full score 5 points) is considered to have good communication transparency. A score below 3 points indicates that there is a lot of room for improvement and points need to be deducted. If there are many patients who report serious lack of communication, it is marked as an abnormal change value. For the registration waiting time, the registration waiting time during the morning peak on weekdays is normal within 30 minutes. If it exceeds 60 minutes, the score is low, which seriously affects the medical experience. The waiting time continues to increase and exceeds the reasonable fluctuation range, which is marked as an abnormal change value. For the diagnosis and treatment waiting time,The waiting time for adjacent patients to receive treatment is normal if it is within 15 minutes. If it exceeds 30 minutes, the score will be reduced. If there is an abnormal fluctuation in the waiting time (suddenly increasing or decreasing), it will be marked as an abnormal change value. For the ward environment score, the average patient score is 4 points (out of 5 points) or above, which means the environment is good. If it is lower, the score will be reduced. If there is a sudden drop in the ward environment score, it will be marked as an abnormal change value;

[0064] The satisfaction questionnaire survey module uses an electronic questionnaire survey system to integrate multiple evaluation indicators of medical satisfaction assessment, obtain patients' scoring results of various evaluation indicators of the medical environment, eliminate the cumbersome links of traditional paper questionnaires, and improve data collection efficiency and accuracy. According to medical quality evaluation indicators (patient complaint scores, doctor-patient communication transparency scores) and medical experience evaluation indicators (registration waiting time, diagnosis and treatment waiting time, ward environment scores), electronic questionnaires are designed to ensure that the questionnaire questions are clear and concise, easy for patients to understand and answer, and an electronic questionnaire survey system is built. The designed questionnaires are imported into the system, and a questionnaire distribution and collection mechanism is set up. The questionnaires are distributed to patients through SMS and WeChat public accounts. The electronic questionnaires were distributed to the patients. After the patients finished their medical treatment, the staff guided them to complete the questionnaires. The patients scored the evaluation indicators in the questionnaires according to their own medical experience. The medical quality evaluation index was calculated based on the relevant data of the patient complaint score and the doctor-patient communication transparency score, and the changing trend of medical quality was analyzed. The medical experience evaluation index was calculated based on the relevant data of the registration waiting time, the diagnosis and treatment waiting time, and the ward environment score, and the changing trend of the patients' medical experience was analyzed. The calculated medical quality evaluation index and medical experience evaluation index were analyzed to clarify the strengths and weaknesses of the hospital services, and the abnormal values ​​of extremely low and extremely high scores were detected for further investigation.

[0065] Furthermore, the expression of the medical quality evaluation index is:

[0066] ;

[0067] in, is the medical quality evaluation index. For the The weight of each medical quality evaluation indicator indicates the relative importance of the indicator in the overall evaluation, and reflects the relative importance of different evaluation indicators in the medical quality evaluation. For the The actual observed values ​​of the medical quality evaluation indicators, For the The benchmark value of a medical quality evaluation indicator indicates the standard value of the indicator. For the The maximum value of the medical quality evaluation index is used for standardization. It is the exponent of the exponential function, which is used to adjust the sensitivity of the formula. It is generally taken as a value greater than 1 to enhance the sensitivity to outliers. The value range of is 0 to 1. The closer the value is to 1, the higher the medical quality is, and the closer it is to 0, the lower the medical quality is. As the quality of medical services improves, will approach or exceed , resulting in an increase in the score. Much lower than Then the score will decrease, reflecting the decline in the quality of medical care;

[0068] The expression of medical experience evaluation index is:

[0069] ;

[0070] in, The medical experience evaluation index is For the The actual observed value of the medical experience evaluation index, For the The benchmark value of a medical experience evaluation indicator indicates the standard value of the indicator. For the The standard deviation of the medical experience evaluation index is used to measure the dispersion of the data and represents the variability of each medical experience evaluation index. The value range is 0 to 1. The closer the value is to 1, the better the medical experience is. The closer the value is to 0, the worse the medical experience is. Close to or better than the benchmark When , the summation term in the denominator will be smaller, making the entire score close to 1, reflecting a good medical experience. On the contrary, if the actual observed value is far from the benchmark value, the summation term will be larger, resulting in a lower score, reflecting a poor medical experience.

[0071] The multi-dimensional evaluation module combines the scoring results of multiple evaluation indicators to comprehensively evaluate the patient's medical satisfaction from multiple dimensions, analyze the patient's satisfaction trend, fully reflect the various needs and opinions of patients during the medical treatment process, and improve the accuracy and comprehensiveness of the evaluation;

[0072] The satisfaction grading module divides the patient's medical satisfaction into different satisfaction levels according to the results of the satisfaction analysis and the pre-set grading standards;

[0073] The service quality optimization module, based on the patient satisfaction evaluation results, uses big data technology to conduct real-time analysis of patient medical satisfaction, discover and handle patient dissatisfaction and complaints, improve the response speed and efficiency of medical services, and enhance patients' medical experience and satisfaction.

[0074] The second embodiment is based on the first embodiment. Figure 3 , Figure 4 As shown in the figure, in the multi-dimensional evaluation module, the analysis process of patient satisfaction trends includes:

[0075] Integrate the relevant data of each evaluation indicator, assign corresponding weights according to the importance of each evaluation indicator to reflect the influence in the overall satisfaction, and standardize the collected data to ensure that the data of different indicators are comparable. Combine the medical quality evaluation index and the medical experience evaluation index, as well as their respective weights, calculate the satisfaction evaluation coefficient, and organize the calculated satisfaction evaluation coefficient to form time series data. Smooth the time series data to eliminate the impact of random fluctuations, and then analyze the changing trend of the satisfaction evaluation coefficient and the changing trend of patient satisfaction. By comparing the satisfaction evaluation coefficients of different time periods, identify abnormally high or abnormally low scores, and further analyze and clarify the causes and influencing factors of changes in patient satisfaction.

[0076] Furthermore, the expression of the satisfaction evaluation coefficient is:

[0077] ;

[0078] in, is the satisfaction evaluation coefficient, is the medical quality evaluation index. The medical experience evaluation index is is the benchmark value of the medical quality evaluation index. is the benchmark value of the medical experience evaluation index. is the weight of the medical quality evaluation index, is the weight of the medical experience evaluation index, The value range is from 0 to 1. The closer the value is to 1, the higher the patient satisfaction is, and the closer the value is to 0, the lower the patient satisfaction is. and When both are higher than their baseline values, The value will be close to 1, indicating high patient satisfaction. or Below its baseline value, The value will decrease, indicating that the patient satisfaction is reduced. The use of exponential and logarithmic functions makes and When approaching the baseline value, It is more sensitive to changes and can more accurately reflect the changing trend of patient satisfaction;

[0079] In the satisfaction grading module, the satisfaction grading process includes:

[0080] According to the numerical range of the satisfaction evaluation coefficient, a clear satisfaction grading standard is formulated, and different satisfaction levels are set, namely very satisfied, satisfied, general, dissatisfied, and very dissatisfied. The corresponding evaluation threshold is matched for each satisfaction level, and the calculated satisfaction evaluation coefficient is compared with the evaluation threshold of each satisfaction level. According to the comparison results, the patient's medical satisfaction is divided into corresponding satisfaction levels, and the divided satisfaction levels are output to the system. The satisfaction evaluation results of each patient are recorded to facilitate the hospital's subsequent tracking and analysis of patient satisfaction. According to the satisfaction level division results, a satisfaction evaluation report is generated and fed back to the relevant departments so that services can be improved based on the information in the report;

[0081] Furthermore, the multiple satisfaction levels and the multiple evaluation thresholds satisfy the following relationship:

[0082] Very satisfied ;

[0083] satisfy ;

[0084] generally ;

[0085] Dissatisfied ;

[0086] Very dissatisfied ;

[0087] in, is the satisfaction evaluation coefficient, is the lower threshold corresponding to very satisfied and the upper threshold corresponding to satisfied, is the lower threshold corresponding to satisfaction and the upper threshold corresponding to general. is the lower threshold corresponding to the general and the upper threshold corresponding to the unsatisfactory, is the lower threshold corresponding to dissatisfaction and the upper threshold corresponding to very dissatisfaction, , , , ;

[0088] Service quality optimization module, including:

[0089] Based on the collected patient satisfaction data after medical treatment, big data technology is used to monitor and analyze the patient satisfaction evaluation results in real time, analyze the overall trend of patient satisfaction, the distribution of satisfaction in each dimension, and the hot issues of dissatisfaction and complaints. Based on the real-time analysis results, patients' dissatisfaction and complaints are quickly identified, classified and marked for subsequent processing, and specific processing procedures are formulated for different types of dissatisfaction and complaints to ensure that the processing procedures are efficient and transparent and can quickly solve patients' problems. According to the processing procedures, timely communication with patients is carried out to clarify specific problems and needs, and corresponding measures are taken to deal with them according to the nature of the problems. The processing process is tracked to ensure that the problems are effectively resolved, the processing results are fed back to patients, and feedback from patients is collected to further improve services. Based on the results of patient satisfaction analysis, bottlenecks and deficiencies in the service process are identified, the service process is optimized, the response speed and efficiency of the service are improved, and medical staff are trained to ensure that they can quickly and accurately handle patients' problems and needs.

[0090] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A patient medical satisfaction evaluation system based on big data, characterized in that: The medical satisfaction evaluation system includes a data collection and processing module, an evaluation index management module, a satisfaction questionnaire survey module, a multi-dimensional evaluation module, a satisfaction grading module and a service quality optimization module, wherein the modules are connected by electrical signals; The data collection and processing module collects various data of patients during the medical treatment process, including basic information, medical records, treatment feedback, and online evaluation; The evaluation index management module specifies multiple evaluation indexes for evaluating medical satisfaction based on the pre-processed patient medical data, wherein the evaluation indexes include medical quality evaluation indexes and medical experience evaluation indexes; The satisfaction questionnaire survey module uses an electronic questionnaire survey system to comprehensively evaluate multiple evaluation indicators of medical satisfaction and obtain the patient's scoring results for each evaluation indicator of the medical environment; The multi-dimensional evaluation module combines the scoring results of multiple evaluation indicators to comprehensively evaluate the patient's medical satisfaction from multiple dimensions and analyze the patient's satisfaction trend; The satisfaction grading module divides the patient's medical satisfaction into different satisfaction levels according to the results of the satisfaction analysis and the pre-set grading standards; The service quality optimization module uses big data technology to conduct real-time analysis of patient satisfaction with medical treatment based on patient satisfaction evaluation results.

2. According to the big data-based patient medical satisfaction evaluation system of claim 1, it is characterized by: In the data collection and processing module, the process of collecting patient medical treatment data includes: Use API interfaces and database connections to capture data from the hospital's electronic medical record system, patient information management system, online appointment system, feedback and evaluation system, and establish data transmission channels to transmit the collected data to the data warehouse of the medical satisfaction evaluation system; Create table structures and fields for received data in the data warehouse, receive and store data from various data sources; Preprocess the raw data stored in the data warehouse, including data cleaning, data integration, and data normalization procedures, format the date, time and other fields, and integrate data from different data sources to form a complete patient medical record.

3. According to the big data-based patient medical satisfaction evaluation system of claim 2, it is characterized by: In the evaluation index management module, the process of evaluation index management specifically includes: Call the pre-processed patient medical data, clarify the evaluation indicators of medical satisfaction assessment, namely medical quality evaluation indicators and medical experience evaluation indicators, and analyze the data sources and types required for each evaluation indicator. The medical quality evaluation indicators include patient complaint scores and doctor-patient communication transparency scores, and the medical experience evaluation indicators include registration waiting time, diagnosis and treatment waiting time, and ward environment scores; Map the pre-processed patient medical data with the evaluation indicators, determine the corresponding relationship between each data field and the evaluation indicator, and mark the patient medical data associated with each evaluation indicator; A standard evaluation threshold is preset for each evaluation indicator, which is compared with the marked evaluation indicator data to obtain the score results of each evaluation indicator. The calculated score results are stored in the data warehouse, and the abnormal change values ​​relative to the standard evaluation threshold are marked.

4. According to the big data-based patient medical satisfaction evaluation system of claim 3, it is characterized by: In the satisfaction questionnaire survey module, the process of obtaining the scoring results of each evaluation indicator includes: Design electronic questionnaires based on medical quality evaluation indicators and medical experience evaluation indicators, build an electronic questionnaire survey system, import the designed questionnaires into the system, and set up questionnaire distribution and collection mechanisms; Electronic questionnaires are distributed to patients through SMS and WeChat official account channels. After the patient's consultation, the staff guides them to complete the questionnaire. The patient scores each evaluation indicator in the questionnaire based on his or her own medical experience; Based on the relevant data of patient complaint scores and doctor-patient communication transparency scores, the medical quality evaluation index is calculated to analyze the changing trend of medical quality. Based on the relevant data of registration waiting time, diagnosis and treatment waiting time and ward environment scores, the medical experience evaluation index is calculated to analyze the changing trend of patients' medical experience. The calculated medical quality evaluation index and medical experience evaluation index were analyzed to identify the strengths and weaknesses of hospital services, and to detect outliers with extremely low and high scores for further investigation.

5. The patient medical satisfaction evaluation system based on big data according to claim 4 is characterized by: The expression of the medical quality evaluation index is: ； in, is the medical quality evaluation index. For the The weight of each medical quality evaluation indicator is For the The actual observed values ​​of the medical quality evaluation indicators, For the The benchmark values ​​of medical quality evaluation indicators are For the The maximum value of the medical quality evaluation index is used for standardization. is the exponent of the exponential function, The value range of is 0 to 1. The closer the value is to 1, the higher the medical quality is, and the closer the value is to 0, the lower the medical quality is. The expression of the medical experience evaluation index is: ； in, The medical experience evaluation index is For the The actual observed value of the medical experience evaluation index, For the The benchmark value of the medical experience evaluation index is For the The standard deviation of the medical experience evaluation index, The value range is 0 to 1. The closer the value is to 1, the better the medical experience.

6. The patient medical satisfaction evaluation system based on big data according to claim 5 is characterized by: In the multi-dimensional evaluation module, the analysis process of patient satisfaction trend includes: Integrate the relevant data of each evaluation indicator, assign corresponding weights according to the importance of each evaluation indicator, and standardize the collected data; Combine the medical quality evaluation index and the medical experience evaluation index, as well as their respective weights, to calculate the satisfaction evaluation coefficient, and then organize the calculated satisfaction evaluation coefficient to form time series data, smooth the time series data, and then analyze the change trend of the satisfaction evaluation coefficient; Analyze the changing trends of patient satisfaction, identify abnormally high or low scores by comparing the satisfaction evaluation coefficients in different time periods, and further analyze to clarify the causes and influencing factors of changes in patient satisfaction.

7. The patient medical satisfaction evaluation system based on big data according to claim 6 is characterized by: The expression of the satisfaction evaluation coefficient is: ； in, is the satisfaction evaluation coefficient, is the medical quality evaluation index. The medical experience evaluation index is is the benchmark value of the medical quality evaluation index. is the benchmark value of the medical experience evaluation index. is the weight of the medical quality evaluation index, is the weight of the medical experience evaluation index, The value range is from 0 to 1. The closer the value is to 1, the higher the patient satisfaction.

8. The patient medical satisfaction evaluation system based on big data according to claim 7 is characterized by: In the satisfaction grading module, the satisfaction grading process includes: According to the numerical range of the satisfaction evaluation coefficient, a clear satisfaction grading standard is formulated, and different satisfaction levels are set, namely very satisfied, satisfied, average, dissatisfied, and very dissatisfied, and the corresponding evaluation threshold is matched for each satisfaction level; The calculated satisfaction evaluation coefficient is compared with the evaluation threshold of each satisfaction level, and the patient's medical satisfaction is divided into corresponding satisfaction levels according to the comparison results; The divided satisfaction levels are output to the system, and the satisfaction evaluation results of each patient are recorded. According to the satisfaction level division results, a satisfaction evaluation report is generated and fed back to the relevant departments.

9. The patient medical satisfaction evaluation system based on big data according to claim 8 is characterized by: The plurality of satisfaction levels and the plurality of evaluation thresholds satisfy the following relationship: Very satisfied ; satisfy ; generally ; Dissatisfied ; Very dissatisfied ; in, is the satisfaction evaluation coefficient, is the lower threshold corresponding to very satisfied and the upper threshold corresponding to satisfied, is the lower threshold corresponding to satisfaction and the upper threshold corresponding to general. is the lower threshold corresponding to the general and the upper threshold corresponding to the unsatisfactory, is the lower threshold corresponding to dissatisfaction and the upper threshold corresponding to very dissatisfaction, , , , .

10. The patient medical satisfaction evaluation system based on big data according to claim 9 is characterized by: The service quality optimization module specifically includes: Based on the collected patient satisfaction data after medical treatment, use big data technology to monitor and analyze the patient satisfaction evaluation results in real time, analyze the overall trend of patient satisfaction, the distribution of satisfaction in each dimension, and hot issues of dissatisfaction and complaints; Based on real-time analysis results, identify patients’ dissatisfaction and complaints, classify and label them, and develop specific handling processes for different types of dissatisfaction and complaints; Communicate with patients according to the treatment process, clarify specific issues and needs, and take appropriate measures to deal with them according to the nature of the problems. Track the treatment process, feedback the treatment results to patients, and collect feedback from patients; Based on the results of patient satisfaction analysis, identify bottlenecks and deficiencies in the service process and optimize the service process.

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