A management method and system for nursing rehabilitation services

Abstract

The application discloses a kind of management methods and systems to cope with nursing rehabilitation service, it is related to nursing management technical field;The method includes the steps of: collecting and maintaining the personal information of all users;Regular health assessment is carried out to target user, and obtains rehabilitation state data set;Its technical points are: the daily nursing time length fine tuning operation when the nursing level has reached the limit is constructed, and the ideal range deviation degree of Barthel index, PEI value and body state evaluation value is introduced therein, so that the overall scheme can flexibly adjust the nursing time length under the premise that the nursing level is unchanged or cannot continue to adjust, to adapt to the rehabilitation trend change, on the one hand, individualized nursing resource allocation is realized according to functional state difference, while maintaining the stability of nursing level, enhance service flexibility, on the other hand, avoid the nursing disjointedness phenomenon caused by level limit, complete the optimization management operation of nursing operation.

Description

Technical Field

[0001] This invention relates to the field of nursing management technology, specifically to a management method and system for nursing rehabilitation services. Background Technology

[0002] Nursing management refers to the systematic planning, organization, guidance, and control of nursing resources in a healthcare setting to ensure the provision of high-quality patient care services. It involves aspects such as developing nursing policies, optimizing processes, improving quality, managing risks, and training and developing personnel. Existing technologies such as electronic health records, mobile nursing applications, remote monitoring systems, and data analytics tools are revolutionizing nursing management, making the nursing process more efficient, precise, and better able to meet the personalized needs of patients or users.

[0003] Existing nursing and rehabilitation service systems often suffer from problems such as simplistic assessment, rigid adjustment mechanisms, and irrational resource allocation. Traditional solutions often employ fixed nursing levels and uniform assessment standards, making it difficult to dynamically respond to changes in the rehabilitation progress of users or patients. This leads to wasted nursing resources or insufficient care, and fails to effectively balance the relationship between the two. For example, some systems only set nursing levels based on the initial condition, failing to adjust them according to the rehabilitation trend or adjusting them inaccurately, resulting in "overestimation" or "underestimation" of nursing needs. In addition, most systems lack quantitative consideration for elderly or special patient groups, and the nursing performance assessment methods are one-sided, ignoring the differences in rehabilitation effects at different stages and the increasing difficulty of nursing care. For example, patients over 70 years old require more refined care due to declining physical function, but current technology fails to take the actual age factor into account in the assessment. Simply considering this factor is insufficient, as it affects the effectiveness of nursing incentive mechanisms. At the same time, when the nursing level has reached its limit, traditional methods cannot make flexible adjustments and lack an ideal value compensation mechanism based on deviations from functional status, resulting in service disconnect and reducing the flexibility and accuracy of nursing management to some extent. Summary of the Invention

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A management approach for nursing rehabilitation services, the method comprising:

[0006] Collect and maintain all users' personal information;

[0007] Regularly conduct health assessments on target users, obtain and generate a comprehensive rehabilitation assessment score based on the rehabilitation status dataset, and calculate the percentage of rehabilitation progress according to the set assessment cycle to evaluate the progress of rehabilitation effectiveness.

[0008] According to the rehabilitation state data set of the target user, a rehabilitation scheme recommendation system based on a knowledge graph is configured, when a target health problem is detected, the best rehabilitation scheme is retrieved from the knowledge graph, and a recommendation action is completed;

[0009] According to the time sequence, the rehabilitation service effect in different rehabilitation progress percentage stages is comprehensively evaluated, an improved multi-dimensional evaluation model is used, nursing variables are input, and rehabilitation service effect evaluation of the target user under the equipped nursing personnel is output, which is used to measure the overall service quality in the current stage;

[0010] The age of the target user is obtained from the personal information, a correction model is constructed, a positive correction coefficient is calibrated based on the age range, and the product of the positive correction coefficient and the rehabilitation service effect evaluation is used as the corrected rehabilitation service effect evaluation;

[0011] Detect whether the target user meets the set rehabilitation target; if not, an adjustment signal is sent, and feedback is performed: the given recommended action is optimized and adjusted again; if yes, a fluctuation judgment response mechanism is triggered: whether the change amplitude of the corrected rehabilitation service effect evaluation in the front and back evaluation periods is within the expected fluctuation range is judged; if yes, no response action is performed; if not, a secondary response adjustment sub-mechanism is triggered: whether the corrected rehabilitation service effect evaluation is rising or falling is judged, and a nursing level adjustment strategy is executed, and the pre-constructed nursing level division standard is adjusted.

[0012] Further, the personal information at least includes: basic information, health status, medical history, family and social support situation;

[0013] The basic information at least includes: name, age and gender.

[0014] Further, the state data set at least includes: Barthel index, PEI value and physical state evaluation value;

[0015] The physical state evaluation value is used to evaluate the physical health status of the target user through physiological indicators, and the physiological indicators at least include: blood pressure, blood sugar, heart rate and body mass index BMI; the process of obtaining the physical state evaluation is as follows:

[0016] Screening indicators: select physiological indicators related to the target user's disease;

[0017] Standardization processing: using linear interpolation method, each physiological indicator is converted into a standard score;

[0018] Comprehensive calculation: according to the standard score corresponding to each physiological indicator, cumulative mean processing is performed to generate the physical state evaluation value PSS of the target user.

[0019] Further, when generating the comprehensive rehabilitation evaluation score: the Barthel index, the PEI value and the physical state evaluation value are weighted and summed to obtain the comprehensive rehabilitation evaluation score; the process of calculating the rehabilitation progress percentage is as follows:

[0020] Set the evaluation period: once a month;

[0021] Record each score: record the Barthel index, the PEI value and the physical state evaluation value after each evaluation, and calculate the comprehensive rehabilitation evaluation score; calculate the rehabilitation progress percentage: according to the current comprehensive rehabilitation evaluation score and the initial comprehensive rehabilitation evaluation score, generate the rehabilitation progress percentage.

[0022] Further, the nursing variables at least include: rehabilitation progress factor, non-standard operation score and satisfaction score; wherein the rehabilitation progress factor is based on the pre-constructed rule engine, and the result obtained after the rehabilitation progress percentage is calibrated; the rule engine divides the rehabilitation progress percentage into at least three stages, when the rehabilitation progress percentage Rpe>40%, 40%≥Rpe≥10% and Rpe<10%, the rehabilitation progress factor is 3Q, 2Q and Q respectively; the value of Q is (0, 1];

[0023] The non-standard operation score is obtained based on the nursing operation compliance evaluation strategy;

[0024] The content of the nursing operation compliance evaluation strategy is: statistics the frequency of the number of nursing operations that do not conform to the standard specification in the last evaluation period, and converts the frequency of the number into a non-standard operation score F_norm through normalization processing;

[0025] The satisfaction score is obtained by the target user's satisfaction questionnaire for nursing service.

[0026] Further, the running process of the improved multi-dimensional evaluation model is: based on the input nursing variables, execute the comprehensive evaluation function: the non-standard operation score F_norm and the normalized satisfaction score Sz are weighted and summed, and the sum result is corrected by the rehabilitation progress factor to produce the rehabilitation service effect evaluation Eg.

[0027] Further, the pre-constructed nursing level division content at least includes: when the nursing level is level one nursing, the daily average nursing time is at least 4 hours / day, and the service content is: life care + medical intervention; when the nursing level is level two nursing, the daily average nursing time is 3 hours / day, and the service content is: partial assistance + function training; when the nursing level is level three nursing, the daily average nursing time is 2 hours / day, and the service content is: self-management + regular inspection;

[0028] Further, the content of adjusting the pre-constructed nursing level classification standard is:

[0029] Constructing a rehabilitation trend score function: ; wherein, T total represents a comprehensive index of trend changes, T(X) represents a trend change factor of index X, and index X at least includes: the modified rehabilitation service effect evaluation Eg ad , the Barthel index Ba, the PEI value Pe, and the physical state assessment value PSS; w1, w2, w3, and w4 are all weight coefficients, and the value range is 0 to 1; when the cumulative value of the corresponding index X is less than the previous index X0 and the corresponding threshold mol X , it indicates that the index X has decreased significantly, so the trend change factor of the index X is +1; when the cumulative value of the corresponding index X is greater than the previous index X0 and the corresponding threshold mol X , it indicates that the index X has increased significantly, so the trend change factor of the index X is -1; when other conditions else occur, the trend change factor of the index X is 0.

[0030] Further, based on the result of the rehabilitation trend score function, a nursing level adjustment decision function is run:

[0031] ; wherein, ΔL represents the level currently required by the target user to adjust, wol represents a preset standard threshold, T total < -wol indicates that the overall trend is deteriorating, T total > wol indicates that the overall trend is good;

[0032] Implement the execution result of the monitoring nursing level adjustment strategy, if the result shows:

[0033] When the overall trend is good and the current nursing level is level three nursing, the nursing time is adjusted according to the degree of deviation of the index from the ideal value, to generate the change amount of daily nursing time; wherein, the degree of deviation of the index from the ideal value is the degree of deviation of the Barthel index Ba, the PEI value Pe, and the physical state assessment value PSS from the ideal range value.

[0034] A management system for coping with nursing rehabilitation services, the system comprises:

[0035] An information collection module: collects and maintains personal information of all users;

[0036] An evaluation comparison module: regularly evaluates the health of the target user, obtains and generates a comprehensive rehabilitation evaluation score according to the rehabilitation state data set, calculates the rehabilitation progress percentage according to the set evaluation period, and evaluates the progress state of the rehabilitation effect;

[0037] Intelligent recommendation module: according to the rehabilitation state data set of the target user, configure the rehabilitation scheme recommendation system based on the knowledge graph, when detecting the target health problem, retrieve the best rehabilitation scheme from the knowledge graph, and complete the recommended action;

[0038] Service determination module: according to the time sequence, comprehensively evaluate the rehabilitation service effect under different rehabilitation progress percentage stages, adopt an improved multi-dimensional evaluation model, input the nursing variables, and output the rehabilitation service effect evaluation value of the target user under the equipped nursing personnel, which is used to measure the overall service quality in the current stage;

[0039] Result correction module: the age of the target user is retrieved from the personal information, a correction model is constructed, a positive correction coefficient is calibrated based on the age range, and the product of the positive correction coefficient and the rehabilitation service effect evaluation value is taken as the corrected rehabilitation service effect evaluation value;

[0040] Adjustment management module: whether the target user meets the set rehabilitation target is detected; if not, an adjustment signal is sent, and feedback is performed: the recommended action is optimized and adjusted again; if yes, the fluctuation determination response mechanism is triggered: whether the change amplitude of the corrected rehabilitation service effect evaluation value in the front and back evaluation periods is within the expected fluctuation range is judged; if yes, no response action is performed; if not, the secondary response adjustment sub-mechanism is continued to be triggered: whether the corrected rehabilitation service effect evaluation value is increased or decreased is judged, and the nursing level adjustment strategy is executed, and the pre-constructed nursing level division standard is adjusted.

[0041] The application provides a management method and system for nursing rehabilitation service, which has the following beneficial effects:

[0042] (1) by adopting the rehabilitation progress percentage segmentation method for primary correction, and introducing the age of the target user for secondary correction, the present scheme not only considers the rehabilitation stage of the target user, but also fully reflects the reality that the nursing difficulty of the elderly user is higher, realizes the differential evaluation of the rehabilitation effect in different stages, and can more effectively and accurately reflect the work value of the nursing personnel, and improves the fairness of subsequent nursing performance evaluation;

[0043] (2) by adopting dynamic grading regulation and trend scoring function based on multi-dimensional indexes, the present scheme can judge whether the overall rehabilitation trend of the target user is good or deteriorating according to the change trend of the Barthel index, PEI value, body state evaluation value and rehabilitation service effect evaluation value, on the one hand, the dynamic rise and fall of the nursing level can be realized, the problem of resource waste or insufficient care caused by fixed nursing operation can be avoided, and dynamic balance operation can be completed, on the other hand, the nursing service quality is improved without changing the nursing personnel configuration, and the nursing resources are more reasonably allocated;

[0044] (3) By constructing the daily nursing time length fine-tuning operation when the nursing level has reached the limit, and continuously introducing the ideal range deviation degree of Barthel index, PEI value and body state evaluation value in it, the overall scheme can flexibly adjust the nursing time length under the premise that the nursing level is unchanged or cannot continue to adjust, to adapt to the rehabilitation trend change, realizes the "fine resource regulation under the premise of unchangeable level", solves the "inelasticity" problem of traditional nursing level, on the one hand, realizes the personalized nursing resource allocation according to the functional state difference, maintains the stability of the nursing level, at the same time, enhances the service flexibility, on the other hand, avoids the nursing disconnection phenomenon caused by the level limit, and completes the optimization management of nursing operation. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 It is a whole flow diagram of a kind of nursing rehabilitation service management method in the application. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0047] Embodiment 1:

[0048] Please refer to Figure 1 The embodiment provides a nursing rehabilitation service management method, which manages the needs of the elderly in medical care and rehabilitation integrated services and their influencing factors during the nursing of the elderly; the demand for high-quality and personalized medical services is particularly urgent; based on this information, the scheme provided in the embodiment designs a medical care management system to improve service quality, optimize resource allocation and improve the quality of life of the elderly;

[0049] The specific steps of the nursing rehabilitation service management method are as follows:

[0050] S1, collect and maintain the personal information of all users;

[0051] The personal information includes basic information (such as name, age and gender), health status, medical history, family and social support; the maintenance method of personal information is to implement data security measures to ensure the privacy and security of information; the implementation of data security measures includes: using encryption technology to protect data transmission and storage, setting access control, regularly backing up data, establishing audit log mechanism, preventing information leakage, tampering or illegal use;

[0052] For user management, a corresponding user ID needs to be assigned to facilitate subsequent online operations, and the user ID serves as a unique identifier for each user; basic information includes name, age, and gender; health status: records the current physical and mental health status; medical history: lists the past disease history and treatment in detail; family and social support: understands the user's social resources and support network.

[0053] S2, periodically assess the target user's health, obtain and generate a comprehensive rehabilitation evaluation score based on the rehabilitation status dataset, and calculate the rehabilitation progress percentage according to the set evaluation period to assess the progress of rehabilitation effect;

[0054] The rehabilitation status dataset includes the Barthel index, PEI value, and physical state evaluation value.

[0055] The Barthel index is used to assess the basic daily life activity ability of the target user, such as the elderly, including eating, bathing, dressing, and moving; the Barthel index is positively correlated with the degree of daily life ability, and the Barthel index assessment scale is used for evaluation; the PEI value is used to evaluate the individual self-evaluation level of the target user, including self-esteem and self-confidence, which can reflect the psychological state of the target user and their confidence in their own rehabilitation; the PEI value is positively correlated with the degree of psychological state, and the personal evaluation questionnaire, i.e., PEI, is used for evaluation.

[0056] The physical state evaluation value is evaluated by physiological indicators to assess the physical health status of the target user, including blood pressure, blood sugar, heart rate, and body mass index BMI, and the process of obtaining the physical state evaluation is as follows:

[0057] S2.1, screening indicators: selecting physiological indicators related to the target user's disease;

[0058] For example, blood pressure for hypertensive patients, blood sugar for diabetic patients, etc., but in the actual screening process, for the target user as an elderly patient, blood pressure, blood sugar, heart rate, and body mass index BMI all need to be screened out;

[0059] S2.2, standardization processing: converting each physiological indicator into a standard score for easy comparison and comprehensive evaluation;

[0060] The conversion calculation is based on: ;

[0061] In the formula, sf represents the standard score corresponding to the physiological index, and the standard score of the physiological index exceeding the normal range is set to 0, which has the advantages that it is more in line with clinical judgment, avoids misjudgment of an abnormally high value as “good”, and improves the accuracy and practicality of the overall scoring system; if represents the meaning of if, xr, Lu and Ld represent actual measurement values (such as blood pressure, blood sugar, heart rate and body mass index BMI) respectively, the lower limit of the normal reference value of the physiological index and the upper limit of the normal reference value; in the formula, under the condition that Lu < xr < Ld, the standard score is calculated using the linear interpolation method, so that all physiological indicators are unified into the interval [0, 1] after processing, which is convenient for subsequent weighted average or comprehensive evaluation;

[0062] S2.3, comprehensive calculation: according to the standard score corresponding to each physiological index, cumulative mean processing is performed to generate the body state evaluation value of the target user, and the formula is: ;

[0063] In the formula, PSS represents the body state evaluation value, n represents the number of physiological indicators participating in the evaluation, and sf i represents the standard score corresponding to the i-th physiological indicator, i = 1, 2,..., n; in this embodiment, since the physiological indicators include blood pressure, blood sugar, heart rate and body mass index BMI, the value of n is 4.

[0064] By implementing real-time health monitoring and regular health evaluation, the scheme proposed in this embodiment can automatically collect and analyze user or patient data, which not only ensures the accuracy and timeliness of the data, but also adjusts the rehabilitation plan according to the latest health status through a dynamic evaluation mechanism; by using this real-time monitoring and dynamic evaluation combined technical scheme, the health status of the target user is accurately grasped, the effect of timely responding to the changes of the target user is achieved, and the problem of not timely intervention caused by information lag in the traditional nursing scheme is solved.

[0065] Then, when generating the comprehensive rehabilitation evaluation score:

[0066] The Barthel index, PEI value and body state evaluation value are weighted and summed to obtain the comprehensive rehabilitation evaluation score; wherein the weight distribution: different weights are allocated according to the importance of various data in the rehabilitation state data set, and the weight cumulative value is 1.

[0067] The process of calculating the rehabilitation progress percentage is as follows:

[0068] S2.4, set the evaluation period: for example, evaluate once a month (the specific period can be determined according to the needs);

[0069] S2.5, Record each score: record the Barthel index, PEI value and physical status assessment value after each assessment, and calculate the comprehensive rehabilitation evaluation score;

[0070] S2.6, Calculate the progress percentage: ;

[0071] In the formula, Rpe represents the rehabilitation progress percentage, and Com and Com_0 represent the current comprehensive rehabilitation evaluation score and the initial comprehensive rehabilitation evaluation score, respectively.

[0072] S3, According to the rehabilitation state data set of the target user, configure a knowledge graph-based rehabilitation scheme recommendation system, namely Knowledge Graph + Recommendation System, retrieve the best rehabilitation scheme from the graph when the target health problem is detected, and complete the recommendation action;

[0073] The knowledge graph-based rehabilitation scheme recommendation system mentioned above is an intelligent, personalized and semantic-driven rehabilitation auxiliary decision-making tool; its core principle is:

[0074] First, a knowledge graph containing entities such as diseases, symptoms, rehabilitation methods, drugs, and evaluation indicators and their associated relationships is constructed to form a structured existing rehabilitation knowledge base; for example, there is an intervention relationship between "high blood pressure" and "low-salt diet", and there is a treatment association between "unsteady gait" and "balance training"; when receiving the rehabilitation state data set of the target user, it will automatically identify the current target health problem, such as "high blood sugar + mild cognitive impairment" or "low mood + reduced social interaction";

[0075] Subsequently, semantic reasoning and path matching are performed in the recommendation system knowledge graph to retrieve the most matched rehabilitation scheme combination for the health status, and the recommendation is sorted according to priority; for example:

[0076] Detecting "high blood sugar + mild cognitive impairment", recommending: low-sugar diet + cognitive training course;

[0077] Detecting "low mood + reduced social interaction", recommending: social activities + psychological counseling course;

[0078] Detecting "unsteady gait + lower limb muscle strength decline", recommending: balance training + strength training course;

[0079] The advantage of the knowledge graph-based rehabilitation scheme recommendation system is that it realizes multi-factor comprehensive analysis on the one hand and improves the professionalism, interpretability and individuality of the rehabilitation scheme on the other hand, effectively supporting clinical decision-making and rehabilitation management automation; this part is a conventional technical means, so it will not be described or explained here;

[0080] In addition, after the above-mentioned recommendation system automatically generates a personalized recommendation action, the related plan of the rehabilitation scheme combination needs to be updated regularly to adapt to the rehabilitation progress of part of the elderly, thereby enhancing the adaptability of the overall scheme.

[0081] In the above-mentioned scheme, a personalized rehabilitation plan is automatically generated according to the target user's rehabilitation state data set, and the best treatment scheme is provided through an intelligent recommendation system supported by a knowledge graph, and secondary adjustment or correction is completed in the subsequent scheme. This method not only takes into account the individual differences between different target users, but also can make the most appropriate recommendations for specific health problems; for example, for the case of "high blood sugar + mild cognitive impairment", low-sugar diet plus cognitive training courses are recommended; combined with the personalized rehabilitation plan and the intelligent recommendation system, highly customized rehabilitation guidance is achieved, which not only improves the effectiveness of treatment, but also solves the problem that the one-size-fits-all treatment scheme in the traditional scheme cannot meet the individual needs.

[0082] S4, according to the time sequence, comprehensively evaluate the rehabilitation service effect under different rehabilitation progress percentage stages, adopt an improved multi-dimensional evaluation model, input nursing variables, and output the rehabilitation service effect evaluation value of the target user under the equipped nursing personnel, for measuring the overall service quality in the current stage;

[0083] Among them, the nursing variables include: rehabilitation progress factor, non-standard operation score and satisfaction score;

[0084] Specifically, the rehabilitation progress factor is obtained after the pre-constructed rule engine is used to calibrate the rehabilitation progress percentage; the above-mentioned rule engine divides the rehabilitation progress percentage into three stages, and sets different rehabilitation progress factors for each stage;

[0085] High progress stage (Rpe>40%): indicating that the rehabilitation effect is significant, and the factor calibration is high;

[0086] Moderate progress stage (40%≥Rpe≥10%): indicating that the rehabilitation effect is general, and the factor calibration is moderate;

[0087] Low progress stage (Rpe<10%): indicating that the rehabilitation effect is poor, and the factor calibration is low;

[0088] The corresponding piecewise function is: In the formula, W(Rpe) represents a function of the rehabilitation progress factor corresponding to the rehabilitation progress percentage stage, Q takes a value of (0, 1], which represents the rehabilitation progress factor under the corresponding condition, and in this embodiment, Q takes a value of 0.5, so 2Q and 3Q are 1 and 1.5 respectively;

[0089] It should be noted that the above conditions also apply when the rehabilitation progress percentage Rpe is negative;

[0090] The non-standard operation score is obtained based on the nursing operation compliance evaluation strategy, and the frequency of non-compliance with the standard specification in the nursing operation in the last period (for example: 3 times / day) is counted. The higher the frequency, the worse the standardization of the corresponding nursing operation. The frequency is converted into a non-standard operation score through normalization processing: ; In the formula, F_norm represents the non-standard operation score, ranging from 0 to 1. The larger the score, the better the standardization. F represents the frequency of non-compliance with the standard specification in the nursing operation in the statistical period. It should be noted that whether the nursing operation is compliant can be obtained through a matching video monitoring system. Specifically, the video monitoring system can record the nursing operation process, analyze the operation behavior using computer vision and machine learning algorithms, and automatically identify and mark non-compliant operations by comparing standard operation specifications.

[0091] The satisfaction score is obtained by scoring the target user's satisfaction questionnaire for nursing services, which directly reflects the target user's subjective feelings about the nursing services. In this embodiment, the satisfaction score is Sz, ranging from 0 to 100 points.

[0092] The running process of the improved multi-dimensional evaluation model is as follows: based on the input nursing variables, execute the comprehensive evaluation function: ; In the formula, Eg represents the rehabilitation service effect evaluation, and both α and β are weight coefficients, representing the importance proportion of nursing operation compliance (i.e. non-standard operation score) and patient satisfaction (i.e. satisfaction score), respectively, with a value range of [0, 1]. Logically, the non-standard operation score and the satisfaction score are considered comprehensively through weighted summation, and the rehabilitation progress factor determined by the rehabilitation progress percentage is used for dynamic correction and adjustment, ensuring the rationality and accuracy of the rehabilitation service effect evaluation in different rehabilitation stages.

[0093] S5, retrieve the target user's age from the personal information, construct a correction model, and calibrate a positive correction coefficient based on the age range. The product of the positive correction coefficient and the rehabilitation service effect evaluation is used as the corrected rehabilitation service effect evaluation;

[0094] When calibrating the positive correction coefficient based on the age range:

[0095] When the age range is below 70 years old, the positive correction coefficient is calibrated as R; when the age range is between 70 years old and 80 years old, the positive correction coefficient is calibrated as 1.2R; when the age range is above 80 years old, the positive correction coefficient is calibrated as 1.5R; wherein the value of R is greater than 0; in this embodiment, the value is 1; the positive correction coefficient indicates that under the same quality of nursing service, the nursing difficulty of the elderly patient is higher, so the rehabilitation service effect evaluation should be appropriately magnified, which can more fairly reflect the working intensity and service value of the nursing staff.

[0096] By adopting the way of segmenting the percentage of rehabilitation progress for primary correction and introducing the age of the target user for secondary correction, the scheme not only considers the rehabilitation stage of the target user, but also fully reflects the reality that the nursing difficulty of the elderly user is higher, realizes the differential evaluation of the rehabilitation effect in different stages, and can more effectively and accurately reflect the working value of the nursing staff, and improves the fairness of subsequent nursing performance evaluation.

[0097] S6, continuously observe the change of the corrected rehabilitation service effect evaluation under different evaluations, and detect whether the target user meets the set rehabilitation target (i.e. whether the corrected rehabilitation service effect evaluation exceeds the preset target evaluation);

[0098] If not, an adjustment signal is sent to S3 for secondary optimization adjustment of the given recommended action, i.e. re-searching the best rehabilitation scheme from the atlas; if yes, a fluctuation judgment response mechanism is triggered: judging whether the change range of the corrected rehabilitation service effect evaluation under the front and back evaluation periods is within the expected fluctuation range; if yes, it means normal, and no response action is taken; if not, a secondary response adjustment sub-mechanism is continuously triggered: judging whether the corrected rehabilitation service effect evaluation is rising or falling, and executing a nursing level adjustment strategy to adjust the pre-constructed nursing level division standard;

[0099] Among them, the pre-constructed nursing level division standard refers to the following table:

[0100] Table 1: Standard examples of nursing level, daily average nursing time and nursing content:

[0101]

[0102] As can be seen from the above table, the later the nursing level, the less the daily average nursing time;

[0103] At the same time, the specific value of the daily average nursing time can be adjusted or set as needed; the initial nursing level of the target user can be preliminarily set by the patient's condition, and then adjusted reasonably by the management method designed in the scheme.

[0104] Then, when executing the nursing level adjustment strategy, the content of adjusting the pre-constructed nursing level division standard is to construct a rehabilitation trend scoring function: ; in the formula, T total represents the trend change comprehensive index, T(X) represents the trend change factor of index X, and the index X in the bracket covers the modified rehabilitation service effect evaluation Eg ad , Barthel index Ba, PEI value Pe, and physical state evaluation value PSS; the value of each T(X) is: ;

[0105] In the formula, when the corresponding index X < the index X0 of the last period and the cumulative value of the corresponding threshold mol X , it indicates that the index X has decreased significantly, so the trend change factor of the index X is +1 (the nursing level needs to be improved); when the corresponding index X > the index X0 of the last period and the cumulative value of the corresponding threshold mol X , it indicates that the index X has increased significantly, so the trend change factor of the index X is -1 (the nursing level needs to be reduced to balance the nursing resources); when else, the trend change factor of the index X is 0 (no change or adjustment); w1, w2, w3, and w4 are weight coefficients, and the value range is 0 to 1;

[0106] It should be noted that the weight coefficient is determined by the coefficient of variation method, which is a method of weighting each index according to the variation degree of the current value and the target value of each evaluation index; if the numerical difference of an index is large, it can clearly distinguish each evaluated object, indicating that the index has rich discrimination information, so the index should be given a larger weight; on the contrary, if the numerical difference of each evaluated object on an index is small, the index has weak ability to distinguish each evaluated object, so the index should be given a smaller weight; this method directly uses the information contained in each index, and the weight of the index is obtained by calculation, so it is objective;

[0107] Then, based on the result of the rehabilitation trend scoring function, the nursing level adjustment decision function is run:

[0108] ; in the formula, ΔL represents the level required to be adjusted by the target user currently, and wol represents a preset standard threshold; when the values of w1, w2, w3, and w4 are 0.4, 0.3, 0.2, and 0.1 respectively, the value of wol can be set to 0.3; T total -wol indicates that the overall trend is deteriorating, so the nursing level needs to be adjusted to the front; for example: the nursing level of the target user is originally secondary nursing, when the overall trend is detected to be deteriorating, then -1 is needed, so that it becomes primary nursing, increases the daily nursing time, and enhances the service content;total Wol indicates that the overall trend is good, so the nursing level needs to be adjusted backward to save nursing resources to a certain extent.

[0109] By adopting dynamic grading regulation and trend scoring function based on multi-dimensional indicators, the scheme can judge the overall rehabilitation trend of the target user according to the changes in Barthel index, PEI value, physical state evaluation value and rehabilitation service effect evaluation value, and determine whether it is good or deteriorating. On the one hand, it can realize the dynamic rise and fall of the nursing level, avoid the waste of resources or insufficient care caused by fixed nursing operation, complete the dynamic balance operation, on the other hand, it can improve the quality of nursing service without changing the nursing staff configuration, make the nursing resources more reasonably allocated, and improve the nursing efficiency.

[0110] Based on the execution result of the nursing level adjustment strategy, if the result shows:

[0111] When the overall trend is good and the current nursing level is level three, it means that it cannot be upgraded or downgraded, and the nursing time is adjusted according to the degree of deviation of the indicators from the ideal value; wherein, the degree of deviation of the indicators from the ideal value is the degree of deviation of Barthel index Ba, PEI value Pe and physical state evaluation value PSS from their ideal range value; wherein, the ideal range value means the lowest ideal value to the highest ideal value, which is set according to actual needs, and will not be described in detail here;

[0112] If it needs to be upgraded but is already the highest level (i.e. nursing level L = 1):

[0113] ;

[0114] In the formula, ΔTr represents the change amount of daily nursing time, the unit is: hour / day, which represents the nursing time that needs to be increased or decreased; for example, the original nursing time is 2 hours / day, when ΔTr = 1.5, the adjusted nursing time is 2 + 1.5 = 3.5 hours / day; Ba low represents the lowest ideal value of Barthel index Ba, Pe low represents the lowest ideal value of PEI value Pe, PSS low represents the lowest ideal value of physical state evaluation value PSS, b1, b2 and b3 are weight coefficients, the value range is 0 to 1; if an extreme case occurs so that the calculation result ΔTr is less than 0, then according to the established constraint condition, ΔTr in the extreme case is directly changed to 1, that is, the original 4 hours / day is changed to 5 hours / day;

[0115] If it needs to be downgraded but is already the lowest level (i.e. nursing level L = 3):

[0116] ;

[0117] Ba high represents the highest ideal value of the Barthel index Ba, Pe high represents the highest ideal value of the PEI value Pe, PSS high represents the highest ideal value of the physical state assessment value PSS, b1, b2 and b3 are weight coefficients, and the value range is 0 to 1; if an extreme case occurs, the result obtained is not less than 0, then ΔTr directly becomes -1, and here is not described in detail;

[0118] Effect description: the implementation of the above nursing level adjustment strategy realizes, on the one hand, that when the nursing level cannot be raised or lowered, the nursing duration is fine-tuned to respond to the rehabilitation trend change; on the other hand, it embodies the principle of individualized intervention, that is, dynamically adjusting the nursing resource input according to the individual functional state difference, which avoids both overcare and insufficient care.

[0119] The above scheme realizes the fine-tuning operation of the daily nursing duration when the nursing level has reached the limit, and introduces the ideal range deviation degree of the Barthel index, the PEI value and the physical state assessment value, so that the overall scheme can flexibly adjust the nursing duration under the premise that the nursing level is unchanged or cannot continue to be adjusted, to adapt to the rehabilitation trend change, realizes the "fine-tuned resource regulation under the premise of unchangeable level", solves the "inelasticity" problem of the traditional nursing level, on the one hand, realizes the individualized nursing resource allocation according to the functional state difference, maintains the stability of the nursing level, on the other hand, avoids the nursing disconnection phenomenon caused by the level limitation, and completes the optimized management operation of the nursing operation.

[0120] Embodiment 2:

[0121] Based on embodiment 1, the present embodiment further provides a management system for nursing rehabilitation service, which comprises:

[0122] An information collection module: collects and maintains the personal information of all users;

[0123] An evaluation comparison module: regularly evaluates the target user's health, obtains and generates a comprehensive rehabilitation evaluation score according to the rehabilitation state data set, and calculates the rehabilitation progress percentage according to the set evaluation period, which is used to evaluate the progress state of the rehabilitation effect;

[0124] An intelligent recommendation module: according to the rehabilitation state data set of the target user, a rehabilitation scheme recommendation system based on knowledge graph is configured, when the target health problem is detected, the best rehabilitation scheme is retrieved from the knowledge graph, and the recommendation action is completed;

[0125] Service determination module: according to time sequence, comprehensive evaluation of different rehabilitation progress percentage stage under the rehabilitation service effect, using an improved multi-dimensional evaluation model based on input nursing variables, output target user under the rehabilitation service effect evaluation of nursing staff equipped, for measuring the overall service quality in the current stage;

[0126] Result correction module: from the personal information to call the target user's age, build a correction model, based on the age range to determine the positive correction coefficient, the product of the positive correction coefficient and the rehabilitation service effect evaluation as the corrected rehabilitation service effect evaluation;

[0127] Adjustment management module: detect whether the target user meets the set rehabilitation goal; if not, send an adjustment signal, then feedback: secondary optimization adjustment to the recommended action; if yes, trigger the fluctuation determination response mechanism: judge whether the change amplitude of the corrected rehabilitation service effect evaluation in the front and back evaluation period is within the expected fluctuation range; if yes, do not respond temporarily; if not, continue to trigger the secondary response adjustment sub-mechanism: judge whether the corrected rehabilitation service effect evaluation is rising or falling, and execute the nursing level adjustment strategy to adjust the pre-constructed nursing level division standard.

[0128] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solutions.

[0129] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, which can be located in one place or distributed on multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiment according to actual needs.

[0130] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application.

Claims

1. A management method for coping with nursing rehabilitation services, the method comprising: collecting and maintaining personal information of all users; regularly performing health assessments on target users, obtaining and generating a comprehensive rehabilitation evaluation score based on a rehabilitation status dataset, calculating a rehabilitation progress percentage according to a set evaluation period, and using the rehabilitation progress percentage to evaluate the progress status of rehabilitation effects; configuring a rehabilitation scheme recommendation system based on a knowledge graph according to the rehabilitation status dataset of the target user, retrieving the best rehabilitation scheme from the knowledge graph when a target health problem is detected, and completing a recommendation action; characterized in that: according to a time sequence, the rehabilitation service effect in different rehabilitation progress percentage stages is comprehensively evaluated, an improved multi-dimensional evaluation model is used, nursing variables are input, and rehabilitation service effect evaluation of the target user under the equipped nursing staff is output to measure the overall service quality in the current stage; the running process of the improved multi-dimensional evaluation model is: executing a comprehensive evaluation function: weighting and summing a non-standard operation score F norm and a normalized satisfaction score Sz, and correcting the summing result by a rehabilitation progress factor; the age of the target user is retrieved from the personal information, a correction model is constructed, a positive correction coefficient is calibrated based on the age range, and the product of the positive correction coefficient and the rehabilitation service effect evaluation is used as the corrected rehabilitation service effect evaluation; detecting whether the target user meets the set rehabilitation goal; if not, an adjustment signal is sent, and feedback is performed: the recommended action is adjusted again; if yes, a fluctuation determination response mechanism is triggered: whether the change range of the modified rehabilitation service effect evaluation in the front and back evaluation periods is within the expected fluctuation range is determined; if yes, no response action is performed; if not, a secondary response adjustment sub-mechanism is continuously triggered: whether the modified rehabilitation service effect evaluation is rising or falling is determined, and a nursing level adjustment strategy is executed to adjust the pre-constructed nursing level division standard: a rehabilitation trend score function is constructed: ; wherein, Ttotal represents a trend change comprehensive index, T(X) represents a trend change factor of index X, and index X at least includes: the modified rehabilitation service effect evaluation Egad, the Barthel index Ba, the PEI value Pe, and the physical state evaluation value PSS; w1, w2, w3, and w4 are weight coefficients, and the value range is 0 to 1; when the corresponding index X < the cumulative value of the corresponding threshold molX and the last period index X0, it indicates that the index X significantly decreases, so the trend change factor of the index X is +1; when the corresponding index X > the cumulative value of the corresponding threshold molX and the last period index X0, it indicates that the index X significantly increases, so the trend change factor of the index X is -1; when other conditions else occur, so the trend change factor of the index X is 0; based on the result of the rehabilitation trend score function, a nursing level adjustment decision function is run: ; where ΔL represents the level of adjustment currently required by the target user, wol represents a preset standard threshold, Ttotal < -wol indicates that the overall trend is deteriorating, and Ttotal > wol indicates that the overall trend is improving. the implementation result of the monitoring nursing level adjustment strategy is displayed, if the result shows: when the overall trend is good and the current nursing level is tertiary nursing, the nursing time is adjusted according to the degree of deviation of the indicators from the ideal value to generate the change amount of the daily average nursing time; wherein the degree of deviation of the indicators from the ideal value is the degree of deviation of the Barthel index Ba, the PEI value Pe and the physical state evaluation value PSS from their ideal range values.

2. The management method for nursing rehabilitation services according to claim 1, characterized by: The personal information at least includes: basic information, health status, medical history, family and social support situation; wherein the basic information at least includes: name, age and gender.

3. The management method for nursing rehabilitation services according to claim 1, characterized in that: The rehabilitation status dataset at least includes: Barthel index, PEI value and physical state evaluation value; wherein the physical state evaluation value is evaluated by physiological indicators to evaluate the physical health status of the target user, and the physiological indicators at least include: blood pressure, blood sugar, heart rate and body mass index BMI; the process of obtaining the physical state evaluation is as follows: screening indicators: selecting physiological indicators related to the target user's disease; standardization processing: using linear interpolation method to convert each physiological indicator into standard score; comprehensive calculation: according to the standard score corresponding to each physiological indicator, cumulative mean processing is performed to generate the physical state evaluation value PSS of the target user.

4. The management method for nursing rehabilitation services according to claim 3, characterized in that: When generating the comprehensive rehabilitation evaluation score: the Barthel index, the PEI value and the physical state evaluation value are weighted and summed to obtain the comprehensive rehabilitation evaluation score; the process of calculating the rehabilitation progress percentage is as follows: setting the evaluation period: once a month; record the score each time: record the Barthel index, PEI value and physical state evaluation value after each evaluation, and calculate the comprehensive rehabilitation evaluation score; The percentage of rehabilitation progress is calculated based on the current comprehensive rehabilitation evaluation score and the initial comprehensive rehabilitation evaluation score.

5. The management method for nursing rehabilitation services according to claim 1, characterized in that: The nursing variables at least include: rehabilitation progress factor, non-standard operation score and satisfaction score; wherein the rehabilitation progress factor is obtained after the calibration processing of the rehabilitation progress percentage based on the pre-constructed rule engine; the rule engine divides the rehabilitation progress percentage into at least three stages, when the rehabilitation progress percentage Rpe>40%, 40%≥Rpe≥10% and Rpe<10%, the rehabilitation progress factor is 3Q, 2Q and Q respectively; the value of Q is (0, 1]; The non-standard operation score is obtained based on the nursing operation compliance evaluation strategy; The content of the nursing operation compliance evaluation strategy is: counting the frequency of the number of nursing operations that do not conform to the standard specification in the last evaluation period, and converting the frequency of the number into a non-standard operation score F_norm through normalization processing; The satisfaction score is obtained by scoring the satisfaction questionnaire of the target user for the nursing service.

6. The management method for nursing rehabilitation services according to claim 1, characterized in that: The pre-constructed nursing level division content at least includes: when the nursing level is first-class nursing, the daily average nursing time is at least 4 hours / day, and the service content is: life care + medical intervention; when the nursing level is second-class nursing, the daily average nursing time is 3 hours / day, and the service content is: partial assistance + functional training; when the nursing level is third-class nursing, the daily average nursing time is 2 hours / day, and the service content is: self-management + regular inspection.

7. A management system for nursing rehabilitation services, the system comprising: an information collection module: collecting and maintaining personal information of all users; an evaluation comparison module: regularly evaluating the health of the target user, obtaining and generating a comprehensive rehabilitation evaluation score based on the rehabilitation state data set, and calculating the rehabilitation progress percentage based on the set evaluation period to evaluate the progress of the rehabilitation effect; an intelligent recommendation module: configuring a rehabilitation scheme recommendation system based on a knowledge graph based on the rehabilitation state data set of the target user, retrieving the best rehabilitation scheme from the knowledge graph when detecting a target health problem, and completing the recommendation action; characterized in that it further comprises: a service determination module: according to the time sequence, comprehensively evaluating the rehabilitation service effect under different rehabilitation progress percentage stages, using an improved multi-dimensional evaluation model, inputting the nursing variables, and outputting the rehabilitation service effect evaluation of the target user under the equipped nursing personnel, which is used to measure the overall service quality in the current stage; the running process of the improved multi-dimensional evaluation model is: executing a comprehensive evaluation function: weighting and summing the non-standard operation score F_norm and the normalized satisfaction score Sz, and correcting the summing result by the rehabilitation progress factor; a result correction module: retrieving the age of the target user from the personal information, constructing a correction model, and marking a positive correction coefficient based on the age range, taking the product of the positive correction coefficient and the rehabilitation service effect evaluation as the corrected rehabilitation service effect evaluation; The adjustment management module detects whether the target user meets the set rehabilitation goal, and if not, sends an adjustment signal, and then performs feedback: secondary optimization adjustment is performed on the recommended action given; if yes, a fluctuation determination response mechanism is triggered: it is determined whether the change amplitude of the modified rehabilitation service effect evaluation in the front and back evaluation periods is within the expected fluctuation range; if yes, no response action is taken; if not, a secondary response adjustment sub-mechanism is continuously triggered: it is determined whether the modified rehabilitation service effect evaluation is rising or falling, and a nursing level adjustment strategy is executed to adjust the pre-constructed nursing level division standard: a rehabilitation trend score function is constructed: ; wherein, T total represents a trend change comprehensive index, T(X) represents a trend change factor of index X, and index X at least includes: the modified rehabilitation service effect evaluation Eg ad , the Barthel index Ba, the PEI value Pe, and the physical state evaluation value PSS; w1, w2, w3, and w4 are all weight coefficients, and the value range is 0 to 1; when the corresponding index X is less than the previous index X0 and the cumulative value of the corresponding threshold mol X , it indicates that the index X has decreased significantly, so the trend change factor of the index X is +1; when the corresponding index X is greater than the previous index X0 and the cumulative value of the corresponding threshold mol X , it indicates that the index X has increased significantly, so the trend change factor of the index X is -1; when other conditions else occur, the trend change factor of the index X is 0; based on the result of the rehabilitation trend score function, running the nursing level adjustment decision function: ; where, Delta L represents the level of adjustment currently required by the target user, wol represents a pre-set standard threshold, T total < -wol indicates that the overall trend is worsening, T total > wol indicates that the overall trend is improving; Implementing the monitoring of the execution result of the nursing level adjustment strategy, if the result shows: When the overall trend is good and the current nursing level is three, the nursing time is adjusted according to the degree of deviation of the indicators from the ideal value, so as to generate the change amount of the daily average nursing time; wherein, the degree of deviation of the indicators from the ideal value is the degree of deviation of the Barthel index Ba, the PEI value Pe and the physical state evaluation value PSS from the ideal range value.

Images