Internet nursing service evaluation system based on Kano model

Abstract

The invention relates to the technical field of service quality evaluation, and discloses an internet nursing service evaluation system based on a Kano model, which comprises a nursing data module and a service evaluation module, the system is in network connection with a database through a nursing data module, obtains medical record data, nursing records and satisfaction questionnaires of all patients, classifies the medical record data, the nursing records and the satisfaction questionnaires to form a data set, a service evaluation module analyzes the basic frequency of nursing services needed by each patient and the actually accepted nursing frequency, and finally obtains the nursing service according to the questionnaire data set. The service evaluation module is used for analyzing the change trend of the patient on article preparation satisfaction, service technology satisfaction and nursing plan satisfaction, generating a corresponding fluctuation data set and comprehensively analyzing patient service experience, and the service evaluation module is used for training to generate a Kano model which is used for evaluating nursing services and marking priority levels required by the patient; a nursing service management platform can be helped to fully understand medical requirements of different patient groups, and the efficient nursing service quality is good.

Description

Technical Field

[0001] The present invention relates to the technical field of service quality evaluation, and in particular to an Internet nursing service evaluation system based on a Kano model. Background Art

[0002] The Internet nursing service evaluation system is to objectively and comprehensively evaluate the quality of "Internet + nursing service" through scientific and standardized methods to promote the improvement and continuous improvement of service quality. The Internet nursing service evaluation system is usually used in clinical nursing, community nursing, chronic disease management and other fields. In the field of community nursing, patients are inconvenient to move, and the service location is usually at the patient's home. Therefore, higher requirements are placed on the preparation of items and technical requirements of nursing staff. The evaluation content of the Internet nursing service evaluation system usually covers multiple dimensions, such as patient satisfaction, professional skills of nursing staff, service attitude, response speed, information transparency, security, etc. The opinions and suggestions of patients, nursing staff and relevant managers are collected by designing questionnaires to understand their views and needs on "Internet + nursing service". The collected data are analyzed using statistical methods to evaluate the achievement of various indicators and the overall service quality. Only by comprehensively analyzing the needs of patients can the service quality be better improved.

[0003] At present, the traditional Internet nursing service evaluation system lacks in-depth analysis capabilities, and it is difficult to promptly discover the reasons why patients resist nursing services. When the traditional Internet nursing service evaluation system sorts patient needs, it lacks unified standards to determine priorities and fails to fully consider the medical needs of different patient groups. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the existing technology, the present invention provides an Internet nursing service evaluation system based on the Kano model, which has the advantages of comprehensive analysis of patient service experience, efficient nursing service quality, etc., and solves the problems that the traditional Internet nursing service evaluation system lacks in-depth analysis capabilities and lacks unified standards to determine demand priorities.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solutions: an Internet nursing service evaluation system based on the Kano model, comprising a nursing data module and a service evaluation module;

[0008] The nursing data module is composed of a patient data unit, a service data unit and a questionnaire data unit. The patient data set collects the patient data set through a network connection database, and the patient data set includes the medical record data of all patients. The service data unit collects the service data set through a network connection database, and the service data set includes the nursing records of all patients. The questionnaire data unit collects the questionnaire data set through a network connection database, and the questionnaire data set includes the satisfaction questionnaires of all patients. The nursing data module transmits the patient data set, the service data set and the questionnaire data set to the service evaluation module through the network.

[0009] The service evaluation module consists of a basic analysis unit, a quality analysis unit and an evaluation management unit. The basic analysis unit analyzes the basic frequency Jcpl of nursing services required by each patient and the actual nursing frequency Hlpl based on the patient data set and the service data set, and transmits them to the evaluation management unit through the network. The quality analysis unit analyzes the changing trends of the patient's satisfaction with item preparation, service technology and nursing plan based on the questionnaire data set, generates a corresponding fluctuation data group Bdsj, and transmits it to the evaluation management unit through the network. The evaluation management unit is set with a fixed range of scoring thresholds PFY, and then combines the basic frequency Jcpl, nursing frequency Hlpl and fluctuation data group Bdsj to judge the patient's satisfaction with the nursing service process and nursing plan, and mark the priority of the patient's needs. The evaluation management unit trains and generates a Kano model based on the patient data set, service data set and questionnaire data set, which is used to evaluate nursing services and mark the priority of patient needs.

[0010] Preferably, the expression of the patient data set is {H1 t 、H2 t 、H3 t , ..., Hz t}, H1 t to Hz t These are the medical records of the first to zth patients, including the patient's name, age, disease, medication list, home address and mobile phone number. t represents the duration of the patient's illness.

[0011] Preferably, the expression of the service data set is {F1 d 、F2 d 、F3 d ,...,Fz d}, F1 d To Fz d These are the nursing records of the first to zth patients, respectively. The nursing records include a list of items, nursing staff, and nursing content. d represents the time point of the nursing service.

[0012] Preferably, the expression of the questionnaire data set is {W1 s 、W2 s 、W3 s , ..., Wz s}, W1 s To Wz s are the satisfaction questionnaires for the first to zth patients respectively. The satisfaction questionnaires include patients' satisfaction scores on item preparation, service technology and nursing plan. s represents the time point when the patient submits the satisfaction questionnaire.

[0013] Preferably, the basic frequency Jcpl calculation process is as follows:

[0014] Extract the medical record data of the i-th patient in the patient data set and mark it as Hi t ;

[0015] Hi t The patient's disease is labeled as JI i , Hi t The patient age in the i ;

[0016] Jcpl=αJI i +βt+γNL i

[0017] In the formula, Jcpl represents the basic frequency, α represents the conversion coefficient for the patient's disease, β represents the conversion coefficient for the patient's illness duration, and γ represents the conversion coefficient for the patient's age. α, β, and γ are all constants, and α+β+γ=1, αJI i +βt+γNL i It refers to the basic frequency of nursing services obtained by comprehensively analyzing the patient's disease, illness duration and age within a unit of time.

[0018] Preferably, the nursing frequency Hlpl calculation process is as follows:

[0019] Extract the nursing records of the i-th patient in the service data set and mark the total number of times in the i-th patient's nursing records as ZC i ;

[0020]

[0021] In the formula, Hlpl represents the nursing frequency, Δd represents the interval between the first and last nursing service received by the i-th patient. represents the actual nursing frequency of the i-th patient.

[0022] Preferably, the calculation process of the fluctuation data set Bdsj is as follows:

[0023] Extract the satisfaction questionnaire of the uth patient in the questionnaire dataset and mark it as to are the satisfaction questionnaires of the i-th patient from the first time to the x-th time, and s represents the time point when the patient submitted the satisfaction questionnaire; to The satisfaction score of the i-th patient on the item preparation is counted and marked as {ZB1, ZB2, ZB3, ..., ZB x}, ZB1 to ZB x The satisfaction scores of the i-th patient on the item preparation from the first time to the x-th time are counted, and the satisfaction score of the i-th patient on the service technology is counted and marked as {JS1, JS2, JS3, ..., JS x}, JS1 to JS x The satisfaction scores of the i-th patient on the service technology from the first time to the x-th time are counted, and the satisfaction scores of the i-th patient on the nursing plan are counted and marked as {JH1, JH2, JH3, ..., JH x}, JH1 to JH x are the satisfaction scores of the i-th patient with the nursing plan from the first to the x-th time;

[0024]

[0025] In the formula, Bdsj represents the fluctuation data group, represents the average satisfaction score of the i-th patient on the item preparation represents the average satisfaction score of the i-th patient on the service technology represents the average satisfaction score of the i-th patient with the nursing plan ZB u represents the satisfaction score of the i-th patient on the preparation of items for the u-th time, According to the variance formula, the obtained variance value is the fluctuation index of the item preparation satisfaction score, JS v represents the satisfaction score of the i-th patient on the service technology for the vth time, According to the variance formula, the variance value obtained is the fluctuation index of the service technology satisfaction score, JH k represents the satisfaction score of the i-th patient with the nursing plan for the kth time, It means that according to the variance formula, the variance value obtained is the fluctuation index of the nursing plan satisfaction score.

[0026] Preferably, when any value of the fluctuation data set Bdsj is lower than the scoring threshold PFY, it indicates that the patient is dissatisfied with the nursing service process, and the priority level of the patient's needs is marked as level one.

[0027] Preferably, when all values ​​in the fluctuation data set Bdsj are included in the scoring threshold PFY, but the nursing frequency Hlpl is lower than the basic frequency Jcpl, it means that the patient is not satisfied with the nursing plan at the current time point, and the priority level of the patient's needs is marked as level two.

[0028] Preferably, the Kano model training process is as follows:

[0029] Based on the patient dataset, service dataset and questionnaire dataset, The medical records, nursing records and satisfaction questionnaires of patients were used as training sets. The medical records, nursing records and satisfaction questionnaires of 10 patients constituted the test set;

[0030] According to the training set, the Kano model is trained to generate the corresponding basic frequency Jcpl, nursing frequency Hlpl and fluctuation data group Bdsj, to judge the patient's satisfaction with the nursing service process and nursing plan, and to mark the priority of the patient's needs;

[0031] Based on the test set, test the accuracy of the Kano model in marking the priority level of patient needs ZQl, and the number of tests is The number of times the Kano model correctly marks the priority level of patient needs is y, and the accuracy ZQl of the Kano model is calculated as follows:

[0032]

[0033] If the accuracy ZQl of the Kano model is greater than or equal to 0.9, it means that the Kano model training at the current time point is qualified;

[0034] If the accuracy ZQl of the Kano model is less than 0.9, it means that the Kano model training at the current time point is unqualified, and the training set and test set will continue to be used for training until the accuracy ZQl of the Kano model is greater than or equal to 0.9.

[0035] Compared with the prior art, the present invention provides an Internet nursing service evaluation system based on the Kano model, which has the following beneficial effects:

[0036] 1. The present invention obtains the medical records, nursing records and satisfaction questionnaires of all patients through the nursing data module network connection database, and classifies them into patient data set, service data set and questionnaire data set. The service evaluation module analyzes the basic frequency Jcpl of nursing services required by each patient and the actual nursing frequency Hlpl received according to the patient data set and the service data set, and then analyzes the changing trends of the patient's satisfaction with item preparation, service technology satisfaction and nursing plan satisfaction according to the questionnaire data set, generates the corresponding fluctuation data group Bdsj, and comprehensively analyzes the patient's service experience. The larger the fluctuation index of a single aspect, the more unstable the patient's service experience in that aspect, which intuitively reflects the reasons for the patient's resistance to nursing services.

[0037] 2. The present invention sets a fixed range of scoring thresholds PFY through the service evaluation module, and then combines the basic frequency Jcpl, the nursing frequency Hlpl and the fluctuation data group Bdsj to judge the patient's satisfaction with the nursing service process and the nursing plan, and then trains and generates a Kano model to evaluate nursing services and mark the priority of patient needs. It can help the nursing service management platform fully understand the medical needs of different patient groups and provide efficient nursing services of good quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Because the traditional Internet nursing service evaluation system lacks in-depth analysis capabilities, it is difficult to timely discover the reasons why patients resist nursing services. When the traditional Internet nursing service evaluation system is based on patient needs, it lacks a unified standard to determine the priority and fails to fully consider the medical needs of different patient groups. Therefore, an Internet nursing service evaluation system based on the Kano model is provided. Please refer to Figure 1 ,The system includes a nursing data module and a service evaluation module;

[0041] The nursing data module consists of patient data unit, service data unit and questionnaire data unit. The patient data set is collected through the network connection database. The patient data set includes the medical records of all patients. The expression of the patient data set is {H1 t 、H2 t 、H3t , ..., Hz t}, H1 t to Hz t These are the medical records of the first to zth patients, including the patient's name, age, disease, medication list, home address and mobile phone number. t represents the duration of the patient's illness. Comprehensive collection of the patient's medical records is conducive to the rapid classification of patient groups. Patients with different diseases require service personnel with different nursing experience.

[0042] The service data unit collects the service data set through the network connection database. The service data set includes the nursing records of all patients. The expression of the service data set is {F1 d 、F2 d 、F3 d ,...,Fz d}, F1 d To Fz d These are the nursing records of the first to the zth patients, respectively. The nursing records include a list of items, nursing staff, and nursing content. d represents the time point of nursing services. Nursing records are an important data source for evaluating and improving the quality of nursing services, and are helpful for timely discovering problems and deficiencies in the nursing process.

[0043] The questionnaire data unit collects the questionnaire data set through the network connection database. The questionnaire data set includes all patients' satisfaction questionnaires. The expression of the questionnaire data set is {W1 s 、W2 s 、W3 s , ..., Wz s}, W1 s To Wz s These are the satisfaction questionnaires for the first to zth patients, respectively. The satisfaction questionnaires include the patients' satisfaction scores on item preparation, service technology, and nursing plans. s represents the time point when the patient submits the satisfaction questionnaire. The questionnaire directly reflects the patient's service experience, which helps to optimize the nursing plan and thus improve the satisfaction and effectiveness of nursing services.

[0044] The nursing data module transmits the patient data set, service data set and questionnaire data set to the service evaluation module through the network; the service evaluation module consists of a basic analysis unit, a quality analysis unit and an evaluation management unit. The basic analysis unit analyzes the basic frequency Jcpl of nursing services required by each patient and the actual frequency Hlpl of nursing services received based on the patient data set and the service data set, and transmits them to the evaluation management unit through the network. The calculation process is as follows:

[0045] Extract the medical record data of the i-th patient in the patient data set and mark it as Hi t ;

[0046] Hi t The patient's disease is labeled as JI i , Hi t The patient age in the i ;

[0047] Jcpl=αJI i +βt+γNL i

[0048] In the formula, Jcpl represents the basic frequency, α represents the conversion coefficient for the patient's disease. In actual application, the basic frequency is converted and calculated according to the severity of the patient's disease, β represents the conversion coefficient for the patient's illness duration, and γ represents the conversion coefficient for the patient's age. α, β and γ are all constants, and α+β+γ=1, αJI i +βt+γNL i It indicates the basic frequency of nursing services obtained by comprehensively analyzing the patient's disease, duration of illness and age per unit time;

[0049] Extract the nursing records of the i-th patient in the service data set and mark the total number of times in the i-th patient's nursing records as ZC i ;

[0050]

[0051] In the formula, Hlpl represents the nursing frequency, Δd represents the interval between the first and last nursing service received by the i-th patient. represents the actual nursing frequency of the i-th patient;

[0052] The quality analysis unit analyzes the changing trends of patients' satisfaction with item preparation, service technology, and nursing plan based on the questionnaire data set, generates the corresponding fluctuation data group Bdsj, and transmits it to the evaluation management unit through the network. The calculation process is as follows:

[0053] Extract the satisfaction questionnaire of the i-th patient in the questionnaire dataset and mark it as to are the satisfaction questionnaires of the i-th patient from the first time to the x-th time, and s represents the time point when the patient submitted the satisfaction questionnaire; to The satisfaction score of the i-th patient on the item preparation is counted and marked as {ZB1, ZB2, ZB3, ..., ZB x}, ZB1 to ZB x The satisfaction scores of the i-th patient on the item preparation from the first time to the x-th time are counted, and the satisfaction score of the i-th patient on the service technology is counted and marked as {JS1, JS2, JS3, ..., JS x}, JS1 to JS x The satisfaction scores of the i-th patient on the service technology from the first time to the x-th time are counted, and the satisfaction scores of the i-th patient on the nursing plan are counted and marked as {JH1, JH2, JH3, ..., JH x}, JH1 to JH x are the satisfaction scores of the i-th patient with the nursing plan from the first to the x-th time;

[0054]

[0055] In the formula, Bdsj represents the fluctuation data group, represents the average satisfaction score of the i-th patient on the item preparation represents the average satisfaction score of the i-th patient on the service technology represents the average satisfaction score of the i-th patient with the nursing plan ZB u represents the satisfaction score of the i-th patient on the preparation of items for the u-th time, According to the variance formula, the obtained variance value is the fluctuation index of the item preparation satisfaction score, JS v represents the satisfaction score of the i-th patient on the service technology for the vth time, According to the variance formula, the variance value obtained is the fluctuation index of the service technology satisfaction score, JH k represents the satisfaction score of the i-th patient with the nursing plan for the kth time, According to the variance formula, the variance value obtained is the fluctuation index of the nursing plan satisfaction score. The patient service experience is comprehensively analyzed. The larger the fluctuation index of a single aspect, the more unstable the patient's service experience in that aspect is, which directly reflects the reasons for the patient's resistance to nursing services.

[0056] The evaluation management unit is set with a fixed range of scoring threshold PEY, and then combined with the basic frequency Jcpl, nursing frequency Hlpl and fluctuation data group Bdsj, it determines the patient's satisfaction with the nursing service process and nursing plan, and marks the priority of the patient's needs. When any value in the fluctuation data group Bdsj is lower than the scoring threshold PFY, it means that the patient is dissatisfied with the nursing service process, and the priority of the patient's needs is marked as level one. Level one patients have the highest priority and need to be revisited as soon as possible to solve after-sales problems. When all values ​​in the fluctuation data group Bdsj are included in the scoring threshold PFY, but the nursing frequency Hlpl is lower than the basic frequency Jcpl, it means that the patient is dissatisfied with the nursing plan at the current time point, and the priority of the patient's needs is marked as level two. Level two patients need targeted care from management personnel, active communication and adjustment of nursing plans, and efficient nursing service quality.

[0057] The evaluation management unit trains and generates a Kano model based on the patient data set, service data set, and questionnaire data set to evaluate nursing services and mark the priority of patient needs. The training process is as follows:

[0058] Based on the patient dataset, service dataset and questionnaire dataset, The medical records, nursing records and satisfaction questionnaires of patients were used as training sets. The medical records, nursing records and satisfaction questionnaires of 10 patients constituted the test set;

[0059] According to the training set, the Kano model is trained to generate the corresponding basic frequency Jcpl, nursing frequency Hlpl and fluctuation data group Bdsj, to judge the patient's satisfaction with the nursing service process and nursing plan, and to mark the priority of the patient's needs;

[0060] Based on the test set, test the accuracy of the Kano model in marking the priority level of patient needs ZQl, and the number of tests is The number of times the Kano model correctly marks the priority level of patient needs is y, and the accuracy ZQl of the Kano model is calculated as follows:

[0061]

[0062] If the accuracy ZQl of the Kano model is greater than or equal to 0.9, it means that the Kano model training at the current time point is qualified;

[0063] If the accuracy ZQl of the Kano model is less than 0.9, it means that the Kano model training at the current time point is unqualified. Continue to use the training set and test set for training until the accuracy ZQl of the Kano model is greater than or equal to 0.9. The Kano model with high accuracy ZQl can help the nursing service management platform fully understand the medical needs of different patient groups.

[0064] Example 1: In this experiment, a patient with chronic kidney disease was selected as the experimental subject. According to statistics, the severity of the patient's condition was in stage G3, with mild to moderate decline in renal function, a disease duration of 10 months, and a patient age of 62 years old. The conversion coefficient for the patient's disease was 0.5, the conversion coefficient for the patient's disease duration was 0.2, and the conversion coefficient for the patient's age was 0.3. The basic frequency Jcpl calculation formula of the patient is as follows:

[0065] Jcpl=αJIi i +βt+γNL i =0.5×3+0.2×10+0.3×62=22.1

[0066] In the formula, Jcpl represents the basic frequency, α, β and γ are all constants, and 0.5+0.2+0.3=1. Within one month, the basic frequency of nursing services for the patient should be 22.1 times.

[0067] Example 2: In this experiment, patients with chronic kidney disease were selected as experimental subjects. According to statistics, there were 3 satisfaction questionnaires reported by the patient. In the first satisfaction questionnaire, the item preparation score was 4, the service technology score was 3, and the nursing plan score was 5. In the second satisfaction questionnaire, the item preparation score was 4, the service technology score was 2, and the nursing plan score was 4. In the third satisfaction questionnaire, the item preparation score was 4, the service technology score was 5, and the nursing plan score was 5. The calculation formula of the patient's fluctuation data group Bssj is as follows:

[0068]

[0069]

[0070] In the formula, Bdsj represents the fluctuating data group, and 4 represents the average satisfaction score of the patient for the preparation of items. 3 represents the average satisfaction score of the patient on the service technology 5 represents the average satisfaction score of the patient with the nursing plan According to the variance formula, 0 is the fluctuation index of the item preparation satisfaction score, 1.7 is the fluctuation index of the service technology satisfaction score, and 0.3 is the fluctuation index of the nursing plan satisfaction score.

[0071] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Internet nursing service evaluation system based on Kano model, characterized by: Includes nursing data module and service evaluation module: The nursing data module is composed of a patient data unit, a service data unit and a questionnaire data unit. The patient data set collects the patient data set through a network connection database, and the patient data set includes the medical record data of all patients. The service data unit collects the service data set through a network connection database, and the service data set includes the nursing records of all patients. The questionnaire data unit collects the questionnaire data set through a network connection database, and the questionnaire data set includes the satisfaction questionnaires of all patients. The nursing data module transmits the patient data set, the service data set and the questionnaire data set to the service evaluation module through the network. The service evaluation module consists of a basic analysis unit, a quality analysis unit and an evaluation management unit. The basic analysis unit analyzes the basic frequency Jcpl of nursing services required by each patient and the actual nursing frequency Hlpl based on the patient data set and the service data set, and transmits them to the evaluation management unit through the network. The quality analysis unit analyzes the changing trends of the patient's satisfaction with item preparation, service technology and nursing plan based on the questionnaire data set, generates a corresponding fluctuation data group Bdsj, and transmits it to the evaluation management unit through the network. The evaluation management unit is set with a fixed range of scoring thresholds PFY, and then combines the basic frequency Jcpl, nursing frequency Hlpl and fluctuation data group Bdsj to judge the patient's satisfaction with the nursing service process and nursing plan, and mark the priority of the patient's needs. The evaluation management unit trains and generates a Kano model based on the patient data set, service data set and questionnaire data set, which is used to evaluate nursing services and mark the priority of patient needs.

2. The Internet nursing service evaluation system based on the Kano model according to claim 1 is characterized by: The expression of the patient data set is {H1 t 、H2 t 、H3 t , …, Hz t }, H1 t to Hz t These are the medical records of the first to zth patients, including the patient's name, age, disease, medication list, home address and mobile phone number. t represents the duration of the patient's illness.

3. The Internet nursing service evaluation system based on the Kano model according to claim 2 is characterized in that: The expression of the service data set is {F1 d 、F2 d 、F3 d ,…,Fz d }, F1 d To Fz d These are the nursing records of the first to zth patients, respectively. The nursing records include a list of items, nursing staff, and nursing content. d represents the time point of the nursing service.

4. The Internet nursing service evaluation system based on the Kano model according to claim 3 is characterized by: The expression of the questionnaire data set is {W1 s 、W2 s 、W3 s ,…,Wz s }, W1 s To Wz s are the satisfaction questionnaires for the first to zth patients respectively. The satisfaction questionnaires include patients' satisfaction scores on item preparation, service technology and nursing plan. s represents the time point when the patient submits the satisfaction questionnaire.

5. The Internet nursing service evaluation system based on the Kano model according to claim 4 is characterized in that: The basic frequency Jcpl calculation process is as follows: Extract the medical record data of the i-th patient in the patient data set and mark it as Hi t ; Hi t The patient's disease is labeled as JI i , Hi t The patient age in the i ; Jcpl=αJI i +βt+γNL i In the formula, Jcpl represents the basic frequency, α represents the conversion coefficient for the patient's disease, β represents the conversion coefficient for the patient's illness duration, and γ represents the conversion coefficient for the patient's age. α, β, and γ are all constants, and α+β+γ=1, αJI i +βt+yNL i It refers to the basic frequency of nursing services obtained by comprehensively analyzing the patient's disease, illness duration and age within a unit of time.

6. The Internet nursing service evaluation system based on the Kano model according to claim 5 is characterized in that: The calculation process of the nursing frequency Hlpl is as follows: Extract the nursing records of the i-th patient in the service data set and mark the total number of times in the i-th patient's nursing records as ZC i ; In the formula, Hlpl represents the nursing frequency, Δd represents the interval between the first and last nursing service received by the i-th patient. represents the actual nursing frequency of the i-th patient.

7. The Internet nursing service evaluation system based on the Kano model according to claim 6 is characterized in that: The calculation process of the fluctuation data group Bdsj is as follows: Extract the satisfaction questionnaire of the i-th patient in the questionnaire dataset and mark it as to are the satisfaction questionnaires of the i-th patient from the first time to the x-th time, and s represents the time point when the patient submitted the satisfaction questionnaire; to The satisfaction score of the i-th patient on the item preparation is counted and marked as {ZB1, ZB2, ZB3, …, ZB x }, ZB1 to ZB x The satisfaction scores of the i-th patient on the item preparation from the first time to the x-th time are counted, and the satisfaction score of the i-th patient on the service technology is counted and marked as {JS1, JS2, JS3, …, JS x }, JS1 to JS x The satisfaction scores of the i-th patient on the service technology from the first time to the x-th time are counted, and the satisfaction scores of the i-th patient on the nursing plan are counted and marked as {JH1, JH2, JH3, …, JH x }, JH1 to JH x are the satisfaction scores of the i-th patient with the nursing plan from the first to the x-th time; In the formula, Bdsj represents the fluctuation data group, represents the average satisfaction score of the i-th patient on the item preparation represents the average satisfaction score of the i-th patient on the service technology represents the average satisfaction score of the i-th patient with the nursing plan ZB u represents the satisfaction score of the i-th patient on the preparation of items for the u-th time, According to the variance formula, the obtained variance value is the fluctuation index of the item preparation satisfaction score, JS v represents the satisfaction score of the i-th patient on the service technology for the vth time, According to the variance formula, the variance value obtained is the fluctuation index of the service technology satisfaction score, JH k represents the satisfaction score of the i-th patient with the nursing plan for the kth time, It means that according to the variance formula, the variance value obtained is the fluctuation index of the nursing plan satisfaction score.

8. The Internet nursing service evaluation system based on the Kano model according to claim 7 is characterized in that: When any value of the fluctuation data set Bdsj is lower than the scoring threshold PFY, it means that the patient is dissatisfied with the nursing service process, and the priority level of the patient's needs is marked as level one.

9. The Internet nursing service evaluation system based on the Kano model according to claim 8 is characterized in that: When all values ​​in the fluctuation data set Bdsj are included in the scoring threshold PFY, but the nursing frequency Hlpl is lower than the basic frequency Jcpl, it means that the patient is not satisfied with the nursing plan at the current time point, and the priority level of the patient's needs is marked as level two.

10. The Internet nursing service evaluation system based on the Kano model according to claim 9 is characterized in that: The Kano model training process is as follows: Based on the patient dataset, service dataset and questionnaire dataset, The medical records, nursing records and satisfaction questionnaires of patients were used as training sets. The medical records, nursing records and satisfaction questionnaires of 10 patients constituted the test set; According to the training set, the Kano model is trained to generate the corresponding basic frequency Jcpl, nursing frequency Hlpl and fluctuation data group Bdsj, to judge the patient's satisfaction with the nursing service process and nursing plan, and to mark the priority of the patient's needs; Based on the test set, test the accuracy of the Kano model in marking the priority level of patient needs ZQl, and the number of tests is The number of times the Kano model correctly marks the priority level of patient needs is y, and the accuracy ZQl of the Kano model is calculated as follows: If the accuracy ZQl of the Kano model is greater than or equal to 0.9, it means that the Kano model training at the current time point is qualified; If the accuracy ZQl of the Kano model is less than 0.9, it means that the Kano model training at the current time point is unqualified, and the training set and test set will continue to be used for training until the accuracy ZQl of the Kano model is greater than or equal to 0.9.

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