Nursing recommendation method and system for self-management education of lower limb DVT patient

Abstract

The invention discloses a nursing recommendation method and system for self-management education of lower limb DVT patients, and belongs to the technical field of nursing recommendation. After the patient is authorized, basic nursing data of the patient is collected, and a compliance data set of the patient is constructed; calling behavior feedback data of the patient from a nursing monitoring system, and constructing an interactive feedback data set; calculating a medication compliance score of the patient and a medication compliance score mean value; based on the interactive feedback data set of the patient, calculating an interactive feedback score of the patient, calculating a medication compliance-interactive feedback joint response score of the patient, and analyzing and judging the joint response score similarity between different patients; according to the method, the threshold value is preset, the similarity and the self-management state between the patients are analyzed and judged, and nursing recommendation and dynamic management are carried out, so that a nursing intervention optimization path caused by human strategy is realized, the self-management ability of the patients is improved, and the waste of nursing resources is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of nursing recommendation, and in particular to a nursing recommendation method and system for self-management education of patients with lower limb deep vein thrombosis (DVT). Background Art

[0002] During the treatment and rehabilitation of patients with lower extremity deep vein thrombosis (DVT), enhancing patients' self-management abilities and improving the compliance and effectiveness of nursing interventions have become important research areas in current clinical nursing. With the rapid development of internet healthcare and mobile health technologies, self-management education and personalized nursing recommendations have gradually become new tools to assist in chronic disease management. In particular, in the context of long-term DVT management, the medical community is increasingly prioritizing ongoing behavioral intervention and health education guidance for patients, aiming to achieve comprehensive synergy between medication adherence and daily behaviors, thereby reducing the risk of recurrence and improving quality of life. Existing research primarily focuses on patient classification and intervention based on questionnaires, regular follow-up, or static models. However, this generally lacks the full utilization of dynamic patient feedback data, making it difficult to achieve continuous, personalized, and intelligent nursing decision support. Furthermore, current systems and methods for interactive feedback behavior modeling, compliance analysis, and multidimensional data fusion still suffer from issues such as crude modeling mechanisms, delayed response assessment, and limited accuracy in nursing intervention recommendations.

[0003] In the existing technology, most self-management care methods have failed to form a closed-loop mechanism between high-frequency sampling, real-time scoring and refined recommendations. They often rely on subjective feedback from patients or manual judgment by nurses, and cannot meet the actual needs of DVT patients whose compliance changes frequently and whose self-management abilities vary greatly. Although some studies have attempted to introduce data-driven models to analyze patient compliance behavior, most of them are based on single indicators (such as medication frequency and behavioral check-ins), lack a multi-factor comprehensive scoring mechanism, and it is difficult to reveal the nonlinear relationship between patient behavioral responses and nursing effectiveness. In addition, the individual differences in nursing responses among patients have not been effectively explored, and it is impossible to form a group portrait and a recommendation mechanism based on similarity. Summary of the Invention

[0004] The purpose of the present invention is to provide a nursing recommendation method and system for self-management education of patients with lower limb DVT, so as to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A nursing recommendation method for self-management education of patients with lower limb DVT includes the following steps: Step S1: After authorization by the patient, basic nursing data of the patient is collected and a compliance data set of the patient is constructed; behavioral feedback data of the patient is retrieved from the nursing monitoring system and an interactive feedback data set is constructed on a daily basis; Step S2: Based on the patient compliance data set, the patient's medication compliance score is calculated; based on the medication compliance score, the mean of the patient's medication compliance score is calculated; Step S3: Based on the patient's interactive feedback data set, the patient's interactive feedback score is calculated; based on the interactive feedback score and the mean of the medication compliance score, the patient's medication compliance-interactive feedback joint response score is calculated; Step S4: Based on the patient's medication compliance-interactive feedback joint response score, the similarity of the joint response scores between different patients is analyzed and determined; a threshold is preset, the similarity and self-management status between patients are analyzed and determined, and nursing recommendations and dynamic management are performed.

[0007] As a preferred embodiment of the nursing recommendation method for self-management education of patients with lower limb DVT described in the present invention, after authorization by the patient, basic nursing data of the patient is collected using a daily nursing questionnaire, wherein the basic nursing data includes the patient's punch-in record data, medication frequency, actual medication time data, and planned medication time data; based on the medication frequency data, the punch-in record data, actual medication time data, and planned medication time data are aligned and normalized to construct the patient's compliance data set, and the compliance data set corresponding to the patient's i-th medication is recorded as ADS i ={CI i ,ATD i ,STD i}, where CI i Indicates the patient's check-in record data corresponding to the i-th medication, ATD i Indicates the actual medication time data corresponding to the patient's medication for the i-th time, STD i represents the planned medication time data corresponding to the patient's medication for the i-th time;

[0008] The patient's behavioral feedback data on the empowerment education nursing program is retrieved from the nursing monitoring system. The behavioral feedback data includes response speed data and questionnaire feedback completeness data. The behavioral feedback data is collected and normalized on a daily basis to construct an interactive feedback dataset. The patient's interactive feedback dataset on day j is recorded as IF j ={RS j ,CP j}, where RS j Represents the patient's response rate data on day j, CP j Represents the completeness data of the patient on day j.

[0009] As a preferred solution of the nursing recommendation method for self-management education of patients with lower limb DVT according to the present invention, based on the patient's compliance dataset ADS corresponding to the i-th medication i ={CI i ,ATD i ,STD i}, calculate the patient's medication compliance score at the time of medication i, the calculation formula is as follows:

[0010]

[0011] Among them, MAS i represents the patient's medication compliance score at the time of medication i, α represents the influencing factor corresponding to the preset punch-in record data, β represents the preset medication time influencing factor, max() represents the maximum value function, and γ represents the preset maximum acceptable medication time deviation;

[0012] It should be noted that the punch card record CI i Directly reflects the patient's active management awareness of medication behavior, quantified by binary or continuous values ​​(missing the clock in is 0, and clocking in on time is 1). i -STD i |, when the actual medication time exceeds γ, A score of 0 reflects the critical value of medication time compliance. Combining the clock-in rate and time deviation, a comprehensive score is formed to distinguish the behavioral differences between "missed doses" and "late doses but not exceeding the threshold." Convert the patient's "execution frequency" and "time accuracy" of medication into calculable values, for example: clocking in on time and the time deviation is less than 10 minutes: the score is close to 1 (high compliance). Missing the clock-in or the time deviation is greater than 30 minutes: the score is significantly reduced (low compliance). Provide a detailed assessment of a single medication for the subsequent calculation of the daily average, and identify fluctuations in the patient's daily compliance (such as regularity on weekdays and slackness on weekends).

[0013] Based on the patient's medication compliance score MAS at the time of medication i i , calculate the mean medication compliance score of the patient when taking all the medications on the jth day, the calculation formula is: in, represents the mean medication compliance score of the patient when taking all the medications on the jth day, and I represents the total number of times the patient takes the medication in one day.

[0014] As a preferred solution of the nursing recommendation method for self-management education of patients with lower limb DVT according to the present invention, based on the patient's interactive feedback data set IF on day j, j ={RS j ,CP j}, calculate the patient's interactive feedback score on day j, and the calculation formula is as follows:

[0015]

[0016] Among them, IFC j represents the patient's interactive feedback score on day j, δ represents the preset feedback adjustment factor, RS max Indicates the preset maximum acceptable response speed;

[0017] It should be noted that in this formula The segment means converting "longer time taken" into "lower score", for example: RS j 30 minutes (RS max =60), the score for this part is 1-30 / 60=0.5. The higher the questionnaire omission rate, the higher the CP j The lower the score, the more it directly reflects the patient's participation in the educational content. This formula can quantify the quality of patients' feedback on nursing education, RS j Reflects the patients' "attention to the educational content" (such as timely completion of the questionnaire is considered positive); CP j Reflects the "depth of understanding" (such as missing key questions, indicating that the student did not read the questionnaire carefully). For example, completing the questionnaire in a timely and complete manner: the score is close to 1 (high participation); exceeding the time limit and having a high rate of missing answers: the score is below 0.5 (low participation).

[0018] Based on the patient's interactive feedback score IFC on day j j and the mean medication compliance score of the patient when taking all medications on day j Calculate the patient's medication compliance-interactive feedback joint response score on day j using the following formula:

[0019]

[0020] Among them, SMS j represents the patient's medication compliance-interactive feedback joint response score on day j, and ε represents the preset system constant.

[0021] As a preferred embodiment of the nursing recommendation method for self-management education of patients with lower limb DVT according to the present invention, based on the patient's medication compliance-interactive feedback joint response score SMS on day j j , judge the patient's self-management status on day j, as follows:

[0022] Analyze and determine the similarity of the joint response scores between different patients. Specifically, calculate the difference in the medication adherence-interactive feedback joint response scores of different patients on day j, preset a difference threshold, and if the difference in the medication adherence-interactive feedback joint response scores of different patients on day j is less than the difference threshold, then it is determined that there is similarity between the patients;

[0023] The threshold of the joint response score is preset. If the medication compliance-interactive feedback joint response score SMS of the a-th patient on the j-th day is j If the a-th patient's medication compliance-interactive feedback joint response score SMS on day j is greater than or equal to the joint response score threshold, it is determined that the a-th patient is in a high response cooperation state on day j. j If the score is less than the joint response score threshold, the a-th patient is determined to be in a low response and cooperation state on day j, and the a-th patient is determined to have a high self-management risk on day j. The empowerment education and nursing plans of the remaining patients whose self-management states are high response and cooperation and similar to that of the a-th patient are obtained, and a recommendation is made to the a-th patient;

[0024] Let j = j + 1, monitor the patient's medication compliance - interactive feedback joint response score in real time and conduct dynamic management.

[0025] A nursing recommendation system for self-management education of patients with lower limb DVT, comprising: a data acquisition and set construction module, a medication compliance score and mean calculation module, a feedback score and response score calculation module, and a similarity calculation and analysis recommendation module;

[0026] The data acquisition and collection construction module: after the patient's authorization, collects the patient's basic nursing data and constructs the patient's compliance data set; retrieves the patient's behavioral feedback data from the nursing monitoring system and constructs an interactive feedback data set on a daily basis;

[0027] The medication compliance score and mean calculation module calculates the patient's medication compliance score based on the patient compliance data set; and calculates the patient's medication compliance score mean based on the medication compliance score;

[0028] The feedback score and response score calculation module: calculates the patient's interactive feedback score based on the patient's interactive feedback data set; calculates the patient's medication compliance-interactive feedback combined response score based on the average of the interactive feedback score and the medication compliance score;

[0029] The similarity calculation and analysis recommendation module: based on the patient's medication compliance-interactive feedback joint response score, analyzes and determines the similarity of the joint response scores between different patients; presets a threshold, analyzes and determines the similarity and self-management status between patients, and makes nursing recommendations and dynamic management.

[0030] Furthermore, the data acquisition and set construction module includes a data acquisition and set construction unit;

[0031] The data acquisition and collection construction unit: after the patient's authorization, uses a daily care questionnaire to collect the patient's basic care data, and the basic care data includes the patient's punch-in record data, number of medication times, actual medication time data and planned medication time data; based on the number of medication times data, the punch-in record data, actual medication time data and planned medication time data are aligned and normalized to construct the patient's compliance data set; the patient's behavioral feedback data on the empowerment education nursing program is retrieved from the nursing monitoring system, and the behavioral feedback data includes response speed data and questionnaire feedback completeness data; the behavioral feedback data is collected and normalized on a daily basis to construct an interactive feedback data set.

[0032] Furthermore, the medication compliance scoring and mean calculation module includes a medication compliance scoring and mean calculation unit;

[0033] The medication compliance score and mean calculation unit calculates the patient's medication compliance score at the i-th medication based on the compliance data set corresponding to the patient's i-th medication; and calculates the mean of the patient's medication compliance scores for all medications taken within the j-th day based on the patient's medication compliance score at the i-th medication.

[0034] Furthermore, the feedback score and response score calculation module includes a feedback score calculation unit and a response score calculation unit;

[0035] The feedback score calculation unit calculates the patient's interactive feedback score on day j based on the patient's interactive feedback data set on day j;

[0036] The response score calculation unit calculates the patient's medication compliance-interactive feedback combined response score on day j based on the patient's interactive feedback score on day j and the average of the patient's medication compliance scores when taking all medications on day j.

[0037] Furthermore, the similarity calculation and analysis recommendation module includes a similarity calculation unit and an analysis recommendation unit;

[0038] The similarity calculation unit analyzes and determines the similarity of the combined response scores between different patients based on the combined response scores of medication compliance and interactive feedback of the patients on day j, specifically by calculating the difference between the combined response scores of medication compliance and interactive feedback of different patients on day j, and presetting a difference threshold. If the difference between the combined response scores of medication compliance and interactive feedback of different patients on day j is less than the difference threshold, it is determined that there is similarity between the patients;

[0039] The analysis and recommendation unit: presets a joint response score threshold, and if the medication compliance-interactive feedback joint response score of the a-th patient on the j-th day is greater than or equal to the joint response score threshold, then the a-th patient is determined to be in a high response and cooperation state on the j-th day; if the medication compliance-interactive feedback joint response score of the a-th patient on the j-th day is less than the joint response score threshold, then the a-th patient is determined to be in a low response and cooperation state on the j-th day, and the self-management risk of the a-th patient on the j-th day is determined to be high, obtains the empowerment education and nursing plans of other patients whose self-management states are in a high response and cooperation state and are similar to that of the a-th patient, and recommends them to the a-th patient;

[0040] Let j = j + 1, monitor the patient's medication compliance - interactive feedback joint response score in real time and conduct dynamic management.

[0041] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in the nursing recommendation method and system for self-management education of patients with lower limb DVT provided by the present invention, by collecting the patient's basic nursing data and constructing a compliance data set, and extracting interactive feedback data from the nursing monitoring system to form an interactive feedback data set, a comprehensive perception of the patient's daily behavior and feedback is achieved, providing a data basis for subsequent analysis. Based on the compliance data set, the patient's medication compliance score and its mean are calculated to accurately quantify the patient's medication behavior, so that a scientific evaluation of their daily management behavior can be made. The patient's interactive feedback score is further calculated, and the mean of the medication compliance score is integrated to construct a joint response score to form a quantitative indicator of the patient's comprehensive response ability, so that the system can accurately identify the patient's overall cooperation status. By comparing the similarity of the joint response scores between different patients and combining the set threshold to judge the patient's self-management status, intelligent matching and individualized push of nursing recommendations are achieved, and real-time management can be performed according to the dynamic changes in the score. The present invention not only realizes patient behavior perception, behavior evaluation and individual characteristic classification, but also realizes the optimization path of nursing intervention based on individual needs, ultimately effectively improving the self-management ability of DVT patients, reducing the waste of nursing resources, and improving the efficiency of chronic disease management and prognosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0043] Figure 1 Schematic diagram of the steps of the nursing recommendation method for self-management education of patients with lower limb DVT according to the present invention;

[0044] Figure 2 It is a structural schematic diagram of the nursing recommendation system for self-management education of patients with lower limb DVT according to the present invention. DETAILED DESCRIPTION

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0046] See also Figure 1 In this embodiment 1, a nursing recommendation method for self-management education of patients with lower limb DVT is provided, the method comprising the following steps:

[0047] Step S1: After the patient's authorization, the patient's basic nursing data is collected and the patient's compliance data set is constructed; the patient's behavioral feedback data is retrieved from the nursing monitoring system, and an interactive feedback data set is constructed on a daily basis.

[0048] Specifically, after authorization by the patient, the daily care questionnaire is used to collect the patient's basic care data, which includes the patient's punch-in record data, medication frequency, actual medication time data, and planned medication time data; based on the medication frequency data, the punch-in record data, actual medication time data, and planned medication time data are aligned and normalized to construct the patient's compliance data set, and the patient's compliance data set corresponding to the i-th medication is recorded as ADS i ={CI i ,ATD i ,STD i}, where CI i Indicates the patient's check-in record data corresponding to the i-th medication, ATD i Indicates the actual medication time data corresponding to the patient's medication for the i-th time, STD i represents the planned medication time data corresponding to the patient's medication for the i-th time;

[0049] Furthermore, the patient's behavioral feedback data on the empowerment education nursing program is retrieved from the nursing monitoring system. The behavioral feedback data includes response speed data and questionnaire feedback completeness data. The behavioral feedback data is collected and normalized on a daily basis to construct an interactive feedback dataset. The patient's interactive feedback dataset on day j is recorded as IF j ={RS j ,CP j}, where RS j Represents the patient's response rate data on day j, CP j Represents the completeness data of the patient on day j.

[0050] Step S2: Calculate the patient's medication compliance score based on the patient compliance data set; and calculate the mean of the patient's medication compliance score based on the medication compliance score.

[0051] Specifically, based on the patient's compliance dataset ADS corresponding to the i-th medication i ={CI i ,ATD i ,STD i}, calculate the patient's medication compliance score at the time of medication i, the calculation formula is as follows:

[0052]

[0053] Among them, MAS i represents the patient's medication compliance score at the time of medication i, α represents the influencing factor corresponding to the preset punch-in record data, β represents the preset medication time influencing factor, max() represents the maximum value function, and γ represents the preset maximum acceptable medication time deviation;

[0054] In the present invention, the formula integrates the punch-in record (CI i ) and time deviation, distinguishing “active missed service” (CI i =0) and “passive delayed service” (CI i =1 but with large time deviation); DVT patients need to take medication strictly on time to prevent recurrence of thrombosis. This design can accurately identify patients who are "occasionally late but generally regular" (e.g., there are still some scores when the time deviation is <γ), avoid misjudgment as "low compliance", and Set a "tolerance boundary" for medication time. When the deviation is within the threshold, points will be deducted proportionally. When the deviation exceeds the threshold, it will be directly reset to zero.

[0055] Furthermore, based on the patient's medication compliance score MAS at the time of medication i i , calculate the mean medication compliance score of the patient when taking all the medications on the jth day, the calculation formula is: in, represents the mean medication compliance score of the patient when taking all the medications on the jth day, and I represents the total number of times the patient takes the medication in one day.

[0056] Step S3: Based on the patient's interactive feedback data set, the patient's interactive feedback score is calculated; based on the interactive feedback score and the mean of the medication compliance score, the patient's medication compliance-interactive feedback joint response score is calculated.

[0057] Specifically, based on the patient's interactive feedback dataset on day j IF j ={RS j ,CP j}, calculate the patient's interactive feedback score on day j, and the calculation formula is as follows:

[0058]

[0059] Among them, IFC j represents the patient's interactive feedback score on day j, δ represents the preset feedback adjustment factor, RS max Indicates the preset maximum acceptable response speed;

[0060] Furthermore, based on the patient's interactive feedback score IFC on day j j and the mean medication compliance score of the patient when taking all medications on day j Calculate the patient's medication compliance-interactive feedback joint response score on day j using the following formula:

[0061]

[0062] Among them, SMS j represents the patient's medication compliance-interactive feedback joint response score on day j, and ε represents the preset system constant.

[0063] In this paper, this formula, a variation of the harmonic mean, is often used to reflect the combined performance of two values, particularly when one is significantly low. It effectively reflects the overall deviation and distinguishes between "good medication use but poor education" (needing improved education) and "good education but poor medication use" (needing optimized medication reminders), avoiding a one-size-fits-all approach. For patients who regularly take medication and actively participate in education, their regimen can be recommended as a "benchmark."

[0064] Step S4: Based on the patient's medication compliance-interactive feedback joint response score, analyze and determine the similarity of the joint response scores between different patients; preset thresholds, analyze and determine the similarity and self-management status between patients, and make nursing recommendations and dynamic management.

[0065] Specifically, based on the patient's medication compliance on day j - interactive feedback joint response score SMS j , judge the patient's self-management status on day j, as follows:

[0066] Analyze and determine the similarity of the joint response scores between different patients. Specifically, calculate the difference in the medication adherence-interactive feedback joint response scores of different patients on day j, preset a difference threshold, and if the difference in the medication adherence-interactive feedback joint response scores of different patients on day j is less than the difference threshold, then it is determined that there is similarity between the patients;

[0067] Furthermore, a threshold value of the combined response score is preset. If the medication compliance-interaction feedback combined response score SMS of the ath patient on the jth day isj If the a-th patient's medication compliance-interactive feedback joint response score SMS on day j is greater than or equal to the joint response score threshold, it is determined that the a-th patient is in a high response cooperation state on day j. j If the score is less than the joint response score threshold, the a-th patient is determined to be in a low response and cooperation state on day j, and the a-th patient is determined to have a high self-management risk on day j. The empowerment education and nursing plans of the remaining patients whose self-management states are high response and cooperation and similar to that of the a-th patient are obtained, and a recommendation is made to the a-th patient;

[0068] Let j = j + 1, monitor the patient's medication compliance - interactive feedback joint response score in real time and conduct dynamic management.

[0069] See also Figure 2 ,In this embodiment 2: a nursing recommendation system for self-management education of patients with lower limb DVT is provided, the system comprising: a data acquisition and set construction module, a medication compliance score and mean calculation module, a feedback score and response score calculation module, and a similarity calculation and analysis recommendation module;

[0070] The data acquisition and collection construction module: after the patient's authorization, collects the patient's basic nursing data and constructs the patient's compliance data set; retrieves the patient's behavioral feedback data from the nursing monitoring system and constructs an interactive feedback data set on a daily basis;

[0071] The medication compliance score and mean calculation module calculates the patient's medication compliance score based on the patient compliance data set; and calculates the patient's medication compliance score mean based on the medication compliance score;

[0072] The feedback score and response score calculation module: calculates the patient's interactive feedback score based on the patient's interactive feedback data set; calculates the patient's medication compliance-interactive feedback combined response score based on the average of the interactive feedback score and the medication compliance score;

[0073] The similarity calculation and analysis recommendation module: based on the patient's medication compliance-interactive feedback joint response score, analyzes and determines the similarity of the joint response scores between different patients; presets a threshold, analyzes and determines the similarity and self-management status between patients, and makes nursing recommendations and dynamic management.

[0074] Furthermore, the data acquisition and set construction module includes a data acquisition and set construction unit;

[0075] The data acquisition and collection construction unit: after the patient's authorization, uses a daily care questionnaire to collect the patient's basic care data, and the basic care data includes the patient's punch-in record data, number of medication times, actual medication time data and planned medication time data; based on the number of medication times data, the punch-in record data, actual medication time data and planned medication time data are aligned and normalized to construct the patient's compliance data set; the patient's behavioral feedback data on the empowerment education nursing program is retrieved from the nursing monitoring system, and the behavioral feedback data includes response speed data and questionnaire feedback completeness data; the behavioral feedback data is collected and normalized on a daily basis to construct an interactive feedback data set.

[0076] Furthermore, the medication compliance scoring and mean calculation module includes a medication compliance scoring and mean calculation unit;

[0077] The medication compliance score and mean calculation unit calculates the patient's medication compliance score at the i-th medication based on the compliance data set corresponding to the patient's i-th medication; and calculates the mean of the patient's medication compliance scores for all medications taken within the j-th day based on the patient's medication compliance score at the i-th medication.

[0078] Furthermore, the feedback score and response score calculation module includes a feedback score calculation unit and a response score calculation unit;

[0079] The feedback score calculation unit calculates the patient's interactive feedback score on day j based on the patient's interactive feedback data set on day j;

[0080] The response score calculation unit calculates the patient's medication compliance-interactive feedback combined response score on day j based on the patient's interactive feedback score on day j and the average of the patient's medication compliance scores when taking all medications on day j.

[0081] Furthermore, the similarity calculation and analysis recommendation module includes a similarity calculation unit and an analysis recommendation unit;

[0082] The similarity calculation unit analyzes and determines the similarity of the combined response scores between different patients based on the combined response scores of medication compliance and interactive feedback of the patients on day j, specifically by calculating the difference between the combined response scores of medication compliance and interactive feedback of different patients on day j, and presetting a difference threshold. If the difference between the combined response scores of medication compliance and interactive feedback of different patients on day j is less than the difference threshold, it is determined that there is similarity between the patients;

[0083] The analysis and recommendation unit: presets a joint response score threshold, and if the medication compliance-interactive feedback joint response score of the a-th patient on the j-th day is greater than or equal to the joint response score threshold, then the a-th patient is determined to be in a high response and cooperation state on the j-th day; if the medication compliance-interactive feedback joint response score of the a-th patient on the j-th day is less than the joint response score threshold, then the a-th patient is determined to be in a low response and cooperation state on the j-th day, and the self-management risk of the a-th patient on the j-th day is determined to be high, obtains the empowerment education and nursing plans of other patients whose self-management states are in a high response and cooperation state and are similar to that of the a-th patient, and recommends them to the a-th patient;

[0084] Let j = j + 1, monitor the patient's medication compliance - interactive feedback joint response score in real time and conduct dynamic management.

[0085] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0086] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A recommended nursing method for self-management education of patients with lower limb DVT, characterized by: The method comprises the following steps: Step S1: After the patient's authorization, the patient's basic nursing data is collected and the patient's compliance data set is constructed; the patient's behavioral feedback data is retrieved from the nursing monitoring system and an interactive feedback data set is constructed on a daily basis; Step S2: calculating the patient's medication compliance score based on the patient compliance data set; and calculating the mean of the patient's medication compliance score based on the medication compliance score; Step S3: Calculating the patient's interactive feedback score based on the patient's interactive feedback data set; calculating the patient's medication adherence-interactive feedback joint response score based on the average of the interactive feedback score and the medication adherence score; Step S4: Based on the patient's medication compliance-interactive feedback joint response score, analyze and determine the similarity of the joint response scores between different patients; preset thresholds, analyze and determine the similarity and self-management status between patients, and make nursing recommendations and dynamic management.

2. The nursing recommendation method for self-management education of patients with lower limb DVT according to claim 1, characterized in that: The specific implementation process of step S1 includes: After the patient's authorization, the daily care questionnaire is used to collect the patient's basic care data, which includes the patient's punch-in record data, medication frequency, actual medication time data, and planned medication time data; based on the medication frequency data, the punch-in record data, actual medication time data, and planned medication time data are aligned and normalized to construct the patient's compliance data set, and the patient's compliance data set corresponding to the i-th medication is recorded as ADS i ={CI i ,ATD i ,STD i }, where CI i Indicates the patient's check-in record data corresponding to the i-th medication, ATD i Indicates the actual medication time data corresponding to the patient's medication for the i-th time, STD i represents the planned medication time data corresponding to the patient's medication for the i-th time; The patient's behavioral feedback data on the empowerment education nursing program is retrieved from the nursing monitoring system. The behavioral feedback data includes response speed data and questionnaire feedback completeness data. The behavioral feedback data is collected and normalized on a daily basis to construct an interactive feedback dataset. The patient's interactive feedback dataset on day j is recorded as IF j ={RS j ,CP j }, where RS j Represents the patient's response rate data on day j, CP j Represents the completeness data of the patient on day j.

3. The nursing recommendation method for self-management education of patients with lower limb DVT according to claim 2, characterized in that: The specific implementation process of step S2 includes: Based on the patient's compliance dataset ADS corresponding to the i-th medication i ={CI i ,ATD i ,STD i }, calculate the patient's medication compliance score at the time of medication i, the calculation formula is as follows: Among them, MAS i represents the patient's medication compliance score at the time of medication i, α represents the influencing factor corresponding to the preset punch-in record data, β represents the preset medication time influencing factor, max() represents the maximum value function, and γ represents the preset maximum acceptable medication time deviation; Based on the patient's medication compliance score MAS at the time of medication i i , calculate the mean medication compliance score of the patient when taking all the medications on the jth day, the calculation formula is: in, represents the mean medication compliance score of the patient when taking all the medications on the jth day, and I represents the total number of times the patient takes the medication in one day.

4. The nursing recommendation method for self-management education of patients with lower limb DVT according to claim 1, characterized in that: The specific implementation process of step S3 includes: Based on the patient's interactive feedback dataset on day j j ={RS j ,CP j }, calculate the patient's interactive feedback score on day j, and the calculation formula is as follows: Among them, IFC j represents the patient's interactive feedback score on day j, δ represents the preset feedback adjustment factor, RS max Indicates the preset maximum acceptable response speed; Based on the patient's interactive feedback score IFC on day j j and the mean medication compliance score of the patient when taking all medications on day j Calculate the patient's medication compliance-interactive feedback joint response score on day j using the following formula: Among them, SMS j represents the patient's medication compliance-interactive feedback joint response score on day j, and ε represents the preset system constant.

5. The nursing recommendation method for self-management education of patients with lower limb DVT according to claim 4, characterized in that: The specific implementation process of step S4 includes: Based on the patient's medication compliance on day j - interactive feedback joint response score SMS j , judge the patient's self-management status on day j, as follows: Analyze and determine the similarity of the joint response scores between different patients. Specifically, calculate the difference in the medication adherence-interactive feedback joint response scores of different patients on day j, preset a difference threshold, and if the difference in the medication adherence-interactive feedback joint response scores of different patients on day j is less than the difference threshold, then it is determined that there is similarity between the patients; The threshold of the joint response score is preset. If the medication compliance-interactive feedback joint response score SMS of the ath patient on the jth day is j If the a-th patient's medication compliance-interactive feedback joint response score SMS on day j is greater than or equal to the joint response score threshold, it is determined that the a-th patient is in a high response cooperation state on day j. j If the score is less than the joint response score threshold, the a-th patient is determined to be in a low response and cooperation state on day j, and the a-th patient is determined to have a high self-management risk on day j. The empowerment education and nursing plans of the remaining patients whose self-management states are high response and cooperation and similar to that of the a-th patient are obtained, and a recommendation is made to the a-th patient; Let j = j + 1, monitor the patient's medication compliance - interactive feedback joint response score in real time and conduct dynamic management.

6. A nursing recommendation system for self-management education of patients with lower limb DVT, which implements the nursing recommendation method for self-management education of patients with lower limb DVT according to any one of claims 1 to 5, characterized in that: The system includes: a data acquisition and set construction module, a medication compliance score and mean calculation module, a feedback score and response score calculation module, and a similarity calculation and analysis recommendation module; The data acquisition and collection construction module: after the patient's authorization, collects the patient's basic nursing data and constructs the patient's compliance data set; retrieves the patient's behavioral feedback data from the nursing monitoring system and constructs an interactive feedback data set on a daily basis; The medication compliance score and mean calculation module calculates the patient's medication compliance score based on the patient compliance data set; and calculates the patient's medication compliance score mean based on the medication compliance score; The feedback score and response score calculation module: calculates the patient's interactive feedback score based on the patient's interactive feedback data set; calculates the patient's medication compliance-interactive feedback combined response score based on the average of the interactive feedback score and the medication compliance score; The similarity calculation and analysis recommendation module: based on the patient's medication compliance-interactive feedback joint response score, analyzes and determines the similarity of the joint response scores between different patients; presets a threshold, analyzes and determines the similarity and self-management status between patients, and makes nursing recommendations and dynamic management.

7. The nursing recommendation system for self-management education of patients with lower limb DVT according to claim 6, characterized in that: The data acquisition and set construction module includes a data acquisition and set construction unit; The data acquisition and collection construction unit: after authorization by the patient, uses a daily care questionnaire to collect the patient's basic care data, the basic care data including the patient's punch-in record data, medication frequency, actual medication time data and planned medication time data; Based on the medication frequency data, the punch-in record data, actual medication time data, and planned medication time data are aligned and normalized to construct a patient compliance dataset; the patient's behavioral feedback data on the empowerment education nursing program is retrieved from the nursing monitoring system, and the behavioral feedback data includes response speed data and questionnaire feedback completeness data; The behavioral feedback data is collected and normalized on a daily basis to construct an interactive feedback dataset.

8. The nursing recommendation system for self-management education of patients with lower limb DVT according to claim 7, characterized in that: The medication compliance scoring and mean calculation module includes a medication compliance scoring and mean calculation unit; The medication compliance score and mean calculation unit calculates the medication compliance score of the patient at the i-th medication based on the compliance data set corresponding to the patient's i-th medication; Based on the patient's medication compliance score when taking the medication for the i-th time, the mean medication compliance score of the patient when taking all medications on the j-th day was calculated.

9. The nursing recommendation system for self-management education of patients with lower limb DVT according to claim 8, characterized in that: The feedback score and response score calculation module includes a feedback score calculation unit and a response score calculation unit; The feedback score calculation unit calculates the patient's interactive feedback score on day j based on the patient's interactive feedback data set on day j; The response score calculation unit calculates the patient's medication compliance-interactive feedback combined response score on day j based on the patient's interactive feedback score on day j and the average of the patient's medication compliance scores when taking all medications on day j.

10. The nursing recommendation system for self-management education of patients with lower limb DVT according to claim 9, characterized in that: The similarity calculation and analysis recommendation module includes a similarity calculation unit and an analysis recommendation unit; The similarity calculation unit analyzes and determines the similarity of the combined response scores between different patients based on the combined response scores of medication compliance and interactive feedback of the patients on day j, specifically by calculating the difference between the combined response scores of medication compliance and interactive feedback of different patients on day j, and presetting a difference threshold. If the difference between the combined response scores of medication compliance and interactive feedback of different patients on day j is less than the difference threshold, it is determined that there is similarity between the patients; The analysis and recommendation unit: presets a joint response score threshold, and if the medication compliance-interactive feedback joint response score of the a-th patient on the j-th day is greater than or equal to the joint response score threshold, then the a-th patient is determined to be in a high response and cooperation state on the j-th day; if the medication compliance-interactive feedback joint response score of the a-th patient on the j-th day is less than the joint response score threshold, then the a-th patient is determined to be in a low response and cooperation state on the j-th day, and the self-management risk of the a-th patient on the j-th day is determined to be high, obtains the empowerment education and nursing plans of other patients whose self-management states are in a high response and cooperation state and are similar to that of the a-th patient, and recommends them to the a-th patient; Let j = j + 1, monitor the patient's medication compliance - interactive feedback joint response score in real time and conduct dynamic management.

Images