Management method and system for coping with nursing rehabilitation service

Abstract

The invention discloses a management method and system for coping with nursing rehabilitation service, and relates to the technical field of nursing management. The method comprises the following steps: collecting and maintaining personal information of all users; health assessment is conducted on the target user regularly, and a rehabilitation state data set is obtained; the technical key points are as follows: the daily average nursing duration fine adjustment operation when the nursing grade reaches the limit is constructed, and the Barthel index, the PEI value and the ideal range deviation degree of the physical state evaluation value are introduced, so that the whole scheme can flexibly adjust the nursing duration to adapt to the rehabilitation trend change on the premise that the nursing grade is not changed or cannot be continuously adjusted, and the rehabilitation effect is improved. On one hand, personalized nursing resource configuration is carried out according to functional state differences, service flexibility is enhanced while nursing grade stability is maintained, on the other hand, the nursing disjunction phenomenon caused by grade limitation is avoided, and optimal management operation on nursing operation is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of nursing management, and in particular to a management method and system for nursing rehabilitation services. Background Art

[0002] Nursing management refers to the systematic planning, organization, direction and control of nursing resources in a healthcare environment to ensure the provision of high-quality patient care services; it involves the formulation of nursing policies, process optimization, quality improvement, risk management, and personnel training and development; existing technologies such as electronic health records, mobile nursing applications, remote monitoring systems and data analysis tools are revolutionizing the way nursing management is done, making the nursing process more efficient and accurate, and better meeting the personalized needs of patients or users.

[0003] Some existing nursing and rehabilitation service systems suffer from widespread issues such as simplistic evaluation, rigid regulatory mechanisms, and irrational resource allocation. Traditional solutions often employ fixed care levels and unified assessment criteria, making it difficult to dynamically respond to changes in the user's or patient's rehabilitation progress, leading to wasted nursing resources or insufficient care, and failing to effectively balance the two. For example, some systems set care levels based solely on the initial condition and fail to adjust them based on recovery trends or make inaccurate adjustments, resulting in overestimation or underestimation of nursing needs. Furthermore, most systems lack quantitative considerations for elderly or special patient populations, resulting in one-sided nursing performance assessment methods that ignore the differences in rehabilitation outcomes and the increasing difficulty of care at different stages. For example, patients over 70 years old require more intensive care due to declining physical function, but existing technologies fail to prioritize actual age in assessments. Simply considering this factor is insufficient and can affect the effectiveness of nursing incentive mechanisms. Furthermore, when care levels reach their limits, traditional methods are unable to flexibly adjust and control them. They lack a compensation mechanism based on deviations from ideal functional status, leading to service disjointedness and, to a certain extent, reducing the flexibility and precision of nursing management. Summary of the Invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions:

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

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

[0007] Regularly conduct health assessments on target users, obtain and generate comprehensive rehabilitation valuation scores based on rehabilitation status data sets, and calculate the rehabilitation progress percentage according to the set assessment cycle to evaluate the progress of rehabilitation effects;

[0008] Based on the target user's rehabilitation status dataset, a rehabilitation plan recommendation system based on the knowledge graph is configured. When a target health problem is detected, the best rehabilitation plan is retrieved from the knowledge graph and the recommended action is completed;

[0009] The effectiveness of rehabilitation services at different rehabilitation progress percentages was comprehensively evaluated over time. An improved multi-dimensional evaluation model was used to input nursing variables and output the estimated effectiveness of rehabilitation services for target users equipped with nursing staff. This model was used to measure the overall service quality at the current stage.

[0010] The target user's age is retrieved from personal information, and a correction model is constructed. The positive correction coefficient is calibrated based on the age range, and the product of the positive correction coefficient and the estimated rehabilitation service effect is used as the revised estimated rehabilitation service effect;

[0011] Detect whether the target user meets the set rehabilitation goals; if not, send an adjustment signal and provide feedback: perform secondary optimization adjustments on the given recommended actions; if so, trigger the fluctuation judgment response mechanism: judge whether the change in the revised rehabilitation service effect valuation is within the expected fluctuation range under the previous and subsequent evaluation cycles; if so, do not take any response action for the time being; if not, continue to trigger the secondary response adjustment sub-mechanism: judge whether the revised rehabilitation service effect valuation is rising or falling, and execute the nursing level adjustment strategy to adjust the pre-built nursing level classification standards.

[0012] Furthermore, personal information shall include at least: basic information, health status, medical history, family and social support;

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

[0014] Furthermore, the complex state data set includes at least: a Barthel index, a PEI value, and a physical state assessment value;

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

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

[0017] Standardization processing: Use linear interpolation method to convert each physiological index into a standard score;

[0018] Comprehensive calculation: Based on the standard score corresponding to each physiological indicator, cumulative average processing is performed to generate the target user's physical condition assessment value PSS.

[0019] Furthermore, when generating a comprehensive rehabilitation valuation score, the Barthel index, PEI value, and physical condition assessment value are weighted and summed to obtain a comprehensive rehabilitation valuation score. The process for calculating the rehabilitation progress percentage is as follows:

[0020] Set an evaluation cycle: conduct evaluation once a month;

[0021] Record each score: After each assessment, record the Barthel index, PEI value, and physical status assessment value, and calculate the comprehensive rehabilitation valuation score; Calculate the rehabilitation progress percentage: Generate the rehabilitation progress percentage based on the current comprehensive rehabilitation valuation score and the initial comprehensive rehabilitation valuation score.

[0022] Furthermore, the nursing variables include at least: a rehabilitation progress factor, a non-standard operation score, and a satisfaction score; wherein the rehabilitation progress factor is a result obtained after calibration processing of the rehabilitation progress percentage based on a pre-built rule engine; the rule engine divides the rehabilitation progress percentage into at least three stages, and when the rehabilitation progress percentage Rpe>40%, 40%≥Rpe≥10%, and Rpe<10%, the rehabilitation progress factors are 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 assessment strategy;

[0024] The content of the nursing operation compliance assessment strategy is as follows: count the frequency of nursing operations that do not meet standard specifications in the previous assessment period, and convert the frequency into a non-standard operation score F_norm through normalization;

[0025] The satisfaction score is obtained by scoring the target users' satisfaction questionnaire on nursing services.

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

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

[0028] Furthermore, the pre-built nursing level classification standards are adjusted as follows:

[0029] Construct a recovery trend scoring function: Where, T total represents the comprehensive index of trend change, T(X) represents the trend change factor of indicator X, and indicator X at least includes: the revised valuation of rehabilitation service effect Eg ad , Barthel index Ba, PEI value Pe and physical condition assessment value PSS; w1, w2, w3 and w4 are weight coefficients, ranging from 0 to 1; when the corresponding index X is less than the previous index X0 and the corresponding threshold mol X When the cumulative value of the corresponding indicator X is greater than the previous indicator X0 and the corresponding threshold value mol X When the cumulative value is , it means that the indicator X has risen significantly, so the trend change factor of the indicator X is: -1; when other conditions occur, the trend change factor of the indicator X is: 0.

[0030] Furthermore, based on the results of the rehabilitation trend scoring function, the nursing level adjustment decision function is run:

[0031] ; Where ΔL represents the level of adjustment currently required by the target user, wol represents the preset standard threshold, and T total <-wol means the overall trend is getting worse, T total >wol indicates the overall trend is positive;

[0032] Monitor the results of the care level adjustment strategy if:

[0033] When the overall trend is positive and the current nursing level is level 3 care, the nursing time is adjusted according to the degree to which the indicators deviate from the ideal values to generate the change in the average daily nursing time; among them, the degree to which the indicators deviate from the ideal values is the degree to which the Barthel index Ba, PEI value Pe and physical condition assessment value PSS deviate from their ideal range values.

[0034] A management system for providing nursing and rehabilitation services, the system comprising:

[0035] Information collection module: collects and maintains all users’ personal information;

[0036] Evaluation and comparison module: Regularly conduct health assessments on target users, obtain and generate comprehensive rehabilitation valuation scores based on rehabilitation status data sets, and calculate the rehabilitation progress percentage according to the set evaluation cycle to evaluate the progress of rehabilitation effects;

[0037] Intelligent recommendation module: Based on the target user's rehabilitation status dataset, a rehabilitation plan recommendation system based on the knowledge graph is configured. When a target health problem is detected, the optimal rehabilitation plan is retrieved from the knowledge graph and the recommended action is completed;

[0038] Service Determination Module: This module comprehensively evaluates the effectiveness of rehabilitation services at different stages of rehabilitation progress according to time series. It uses an improved multi-dimensional evaluation model that inputs nursing variables and outputs an estimated value of the rehabilitation service effectiveness of the target user with nursing staff, which is used to measure the overall service quality at the current stage.

[0039] Result correction module: retrieve the target user's age from personal information, build a correction model, calibrate the positive correction coefficient based on the age range, and use the product of the positive correction coefficient and the estimated rehabilitation service effect as the corrected rehabilitation service effect estimate;

[0040] Adjustment management module: detects whether the target user meets the set rehabilitation goals; if not, an adjustment signal is issued, and feedback is given: secondary optimization adjustment is performed on the given recommended actions; if so, a fluctuation determination response mechanism is triggered: determines whether the change in the revised rehabilitation service effect valuation is within the expected fluctuation range under the previous and subsequent evaluation cycles; if so, no response action is taken for the time being; if not, the secondary response adjustment sub-mechanism is triggered: determines whether the revised rehabilitation service effect valuation is rising or falling, and executes the nursing level adjustment strategy to adjust the pre-built nursing level classification standards.

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

[0042] (1) By using the percentage of rehabilitation progress for the first correction and introducing the age of the target user for the second correction, this plan not only takes into account the rehabilitation stage of the target user, but also fully reflects the reality that the care of elderly users is more difficult, realizes the differentiated evaluation of the rehabilitation effects at different stages, and can more effectively and accurately reflect the work value of nursing staff, thereby improving the fairness of subsequent nursing performance evaluation;

[0043] (2) By adopting dynamic hierarchical regulation and a trend scoring function based on multidimensional indicators, this solution can judge in real time whether the overall rehabilitation trend of the target user is improving or deteriorating based on the changing trend of the target user's Barthel index, PEI value, physical condition assessment value, and rehabilitation service effect valuation. On the one hand, it can achieve dynamic adjustment of the nursing level, avoid the problem of resource waste or insufficient care caused by fixed nursing operations, and complete the dynamic balance operation. On the other hand, without changing the configuration of nursing staff, it improves the quality of nursing services and makes nursing resources more reasonably allocated.

[0044] (3) By constructing a fine-tuning operation for the average daily nursing time when the nursing level has reached its limit, and continuing to introduce the ideal range deviation degree of the Barthel index, PEI value and physical condition assessment value, the overall plan can flexibly adjust the nursing time to adapt to the changes in rehabilitation trends under the premise that the nursing level remains unchanged or cannot be adjusted further, thus realizing "fine-grained resource regulation under the premise of unchanged level", solving the problem of "inelasticity" of traditional nursing level, on the one hand, realizing personalized nursing resource allocation according to functional status differences, maintaining the stability of nursing level while enhancing service flexibility, and on the other hand, avoiding the nursing disconnection caused by level restrictions, completing the optimized management of nursing operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a schematic diagram of the overall process of a management method for nursing and rehabilitation services in the present invention. DETAILED DESCRIPTION

[0046] The following will provide a clear and complete description of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0047] Example 1:

[0048] See also Figure 1 This embodiment provides a management method for nursing and rehabilitation services. During the period of elderly care, this method manages the elderly's needs for integrated medical, nursing, and rehabilitation services and the factors affecting them. The demand for high-quality, personalized medical services is particularly urgent. Based on this information, the solution provided in this embodiment designs the medical care management system, aiming to improve service quality, optimize resource allocation, and enhance the quality of life of the elderly.

[0049] The specific steps of this management approach to nursing and rehabilitation services are as follows:

[0050] S1. Collect and maintain personal information of all users;

[0051] Personal information includes basic information (such as name, age, and gender), health status, medical history, and family and social support. Personal information is maintained by implementing data security measures to ensure its privacy and security. These measures include using encryption technology to protect data transmission and storage, setting access control permissions, regularly backing up data, and establishing an audit log mechanism to prevent information leakage, tampering, or unauthorized use.

[0052] During user management, a corresponding user ID needs to be assigned to facilitate subsequent online operations. The user ID uniquely identifies each user. Basic information includes: name, age, and gender; health status: record current physical and mental health status; past medical history: list past medical history and treatment in detail; family and social support: understand the user's social resources and support network.

[0053] S2. Regularly conduct health assessments on target users, obtain and generate comprehensive rehabilitation valuation scores based on rehabilitation status data sets, and calculate the rehabilitation progress percentage according to the set assessment cycle to evaluate the progress of rehabilitation effects;

[0054] Among them, the rehabilitation status data set includes: Barthel index, PEI value and physical status assessment value;

[0055] The Barthel Index is used to assess target users, such as elderly individuals, in their ability to perform basic activities of daily living, including eating, bathing, dressing, and moving. The Barthel Index is positively correlated with the degree of daily living ability and is assessed using the Barthel Index Rating Scale. The PEI value is used to assess the target user's individual self-evaluation level, including self-esteem and self-confidence, reflecting the target user's psychological state and confidence in their own recovery. The PEI value is positively correlated with the degree of psychological state and is assessed using the Personal Evaluation Questionnaire (PEI).

[0056] The physical condition assessment value is used to evaluate the target user's physical health through physiological indicators, including blood pressure, blood sugar, heart rate, and body mass index (BMI). The process of obtaining the physical condition assessment is as follows:

[0057] S2.1. Screening indicators: Select physiological indicators related to the target user's disease;

[0058] For example: blood pressure of patients with hypertension, blood sugar of patients with diabetes, etc. However, in the actual screening process, if the target user is an elderly patient, their blood pressure, blood sugar, heart rate and body mass index (BMI) must all be screened out;

[0059] S2.2, Standardization: Convert each physiological indicator into a standard score to facilitate comparison and comprehensive evaluation;

[0060] Conversions are calculated based on: ;

[0061] In the formula, sf represents the standard score corresponding to the physiological indicator. For physiological indicators that exceed the normal range, the standard score is set to 0. This has the advantage of being more consistent with clinical judgment, avoiding misjudging abnormally high values as "good", and improving the accuracy and practicality of the overall scoring system; if represents the meaning of "if", xr, Lu, and Ld represent the actual measured value (such as blood pressure, blood sugar, heart rate, and body mass index (BMI), the lower limit of the normal reference value for the physiological indicator, and the upper limit of the normal reference value, respectively; in the above formula, under the condition of Lu < xr < Ld, the standard score is calculated using linear interpolation. After processing, all physiological indicators are unified into the interval [0, 1], which facilitates subsequent weighted averaging or comprehensive evaluation;

[0062] S2.3. Comprehensive Calculation: Based on the standard score corresponding to each physiological indicator, perform cumulative mean processing to generate the target user's physical condition assessment value. The formula is as follows: ;

[0063] Where PSS represents the physical status assessment value, n represents the number of physiological indicators involved in the assessment, 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 assessments, the solution proposed in this embodiment can automatically collect and analyze user or patient data. This process 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 assessment mechanism. By adopting this technical solution that combines real-time monitoring and dynamic assessment, accurate grasp of the health status of the target user is achieved, achieving the effect of timely response to changes in the target user, and at the same time solving the problem of untimely intervention caused by information lag in traditional nursing plans.

[0065] Then, when generating the comprehensive recovery estimate score:

[0066] The Barthel index, PEI value, and physical status assessment value are weighted and summed to obtain a comprehensive rehabilitation valuation score. Weight allocation involves assigning different weights based on the importance of each type of data in the rehabilitation status dataset, ensuring that the cumulative weight value is 1.

[0067] The process for calculating the recovery progress percentage is as follows:

[0068] S2.4. Set an evaluation cycle: for example, conduct an evaluation once a month (the specific cycle can be determined based on needs);

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

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

[0071] Where Rpe represents the percentage of rehabilitation progress, Com and Com_0 represent the current comprehensive rehabilitation valuation score and the initial comprehensive rehabilitation valuation score, respectively.

[0072] S3. Based on the target user's rehabilitation status dataset, a rehabilitation plan recommendation system based on the knowledge graph is configured, namely the Knowledge Graph + Recommendation System. When a target health problem is detected, the optimal rehabilitation plan is retrieved from the graph and the recommended action is completed;

[0073] The knowledge graph-based rehabilitation plan recommendation system mentioned above is an intelligent, personalized, and semantically driven rehabilitation decision-making tool. Its core principles are:

[0074] First, a knowledge graph is constructed that includes entities such as diseases, symptoms, rehabilitation methods, drugs, and evaluation indicators, as well as their relationships, 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 therapeutic relationship between "unsteady gait" and "balance training." After receiving the target user's rehabilitation status dataset, the system automatically identifies the current target health issues, such as "high blood sugar + mild cognitive impairment" or "low mood + reduced social interaction."

[0075] Subsequently, the recommendation system performs semantic reasoning and path matching in the knowledge graph to retrieve the rehabilitation plan combination that best matches the health status and recommends it based on priority. For example:

[0076] If "high blood sugar + mild cognitive impairment" is detected, the recommendation is: low-sugar diet + cognitive training course;

[0077] If "depressed mood + reduced social interaction" is detected, the following recommendations are made: social activities + psychological counseling courses;

[0078] If "unstable gait + decreased lower limb muscle strength" is detected, the following are recommended: balance training + strength training courses;

[0079] The advantages of this knowledge graph-based rehabilitation plan recommendation system are: on the one hand, it realizes comprehensive analysis of multiple factors; on the other hand, it improves the professionalism, explainability, and personalization of rehabilitation plans, effectively supporting clinical decision-making and rehabilitation management automation. This part is a conventional technical means, so it will not be further described or explained here.

[0080] In addition, after the above-mentioned recommendation system automatically generates personalized recommended actions, the relevant plans for the rehabilitation program combination need to be updated regularly to adapt to the rehabilitation progress of some elderly people, thereby enhancing the adaptability of the overall program.

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

[0082] S4. Comprehensively evaluate the effectiveness of rehabilitation services at different rehabilitation progress percentages based on time series. Use an improved multi-dimensional evaluation model that inputs nursing variables and outputs the estimated effectiveness of rehabilitation services for target users equipped with nursing staff, which is used to measure the overall service quality at the current stage.

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

[0084] Specifically, the recovery progress factor is the result of a calibration process based on the recovery progress percentage using a pre-built rule engine. The aforementioned rule engine divides the recovery progress percentage into three stages and sets a different recovery progress factor for each stage.

[0085] High progress stage (Rpe>40%): indicates significant rehabilitation effect and high factor calibration;

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

[0087] Low progression stage (Rpe < 10%): indicates poor rehabilitation effect and low factor calibration;

[0088] The corresponding piecewise function is: Wherein, W(Rpe) represents the function for calculating the rehabilitation progress factor at the stage corresponding to the rehabilitation progress percentage, and the value of Q is (0, 1], which represents the rehabilitation progress factor under the corresponding conditions. In this embodiment, the value of Q is 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 recovery progress percentage Rpe is a negative number;

[0090] The non-standard operation score is obtained based on the nursing operation compliance assessment strategy. The frequency of nursing operations that do not meet standard specifications in the previous cycle is counted (for example, 3 times / day). 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: ; In the formula, F_norm represents the non-standard operation score, ranging from [0, 1]. The larger the score, the better the standardization. F represents the frequency of non-standard nursing operations during the statistical period. It should be noted that whether the nursing operations are compliant can be obtained through the supporting video surveillance system. Specifically, the video surveillance system can be used to record the nursing operation process, and the operation behavior can be analyzed using computer vision and machine learning algorithms. The non-compliant operations can be automatically identified and marked by comparing with the standard operation specifications.

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

[0092] The operation process of the improved multi-dimensional evaluation model is as follows: based on the input nursing variables, a comprehensive evaluation function is executed: Where Eg represents the valuation of rehabilitation service effect, α and β are weight coefficients, representing the importance ratio of nursing operation compliance (i.e., non-standard operation score) and patient satisfaction (i.e., satisfaction score), respectively, and both range from [0, 1]. The logic explanation is that the non-standard operation score and satisfaction score are comprehensively considered by weighted summation, and the rehabilitation progress factor determined by the rehabilitation progress percentage is dynamically corrected and adjusted to ensure the rationality and accuracy of the valuation of rehabilitation service effect at different rehabilitation stages.

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

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

[0095] When the age range is under 70 years old, the positive correction coefficient is calibrated to R; when the age range is between 70 and 80 years old, the positive correction coefficient is calibrated to 1.2R; when the age range is over 80 years old, the positive correction coefficient is calibrated to 1.5R; among them, the value of R is greater than 0; in this embodiment, the value is 1; the positive correction coefficient indicates that: under the same nursing service quality, the nursing difficulty of elderly patients is higher, so the valuation of their rehabilitation service effect should be appropriately magnified, so that the work intensity and service value of nursing staff can be more fairly reflected.

[0096] By using the percentage of rehabilitation progress for the first correction and introducing the age of the target user for the second correction, this plan not only takes into account the rehabilitation stage of the target user, but also fully reflects the reality that the care of elderly users is more difficult. It realizes differentiated evaluation of rehabilitation effects at different stages, and can more effectively and accurately reflect the work value of nursing staff, thereby improving the fairness of subsequent nursing performance evaluation.

[0097] S6. Continuously observe changes in the revised rehabilitation service effect estimates under different evaluations to detect whether the target users meet the set rehabilitation goals (i.e., compare whether the revised rehabilitation service effect estimates exceed the preset target estimates);

[0098] If not, an adjustment signal is sent and fed back to S3 to perform secondary optimization adjustments on the given recommended action, that is, to retrieve the best rehabilitation plan from the atlas again; if so, the fluctuation judgment response mechanism is triggered: it is judged whether the change range of the revised rehabilitation service effect valuation is within the expected fluctuation range during the previous and subsequent evaluation cycles; if so, it indicates that it is normal, and no response action is taken for the time being; if not, the secondary response adjustment sub-mechanism is triggered: it is judged whether the revised rehabilitation service effect valuation is an increase or decrease, and the nursing level adjustment strategy is executed to adjust the pre-built nursing level classification standard;

[0099] The pre-built nursing level classification standards are shown in the following table:

[0100] Table 1: Standard examples of nursing levels, average daily nursing hours, and nursing content:

[0101]

[0102] From the above table, we can see that the lower the nursing level, the shorter the average daily nursing time;

[0103] At the same time, for the average daily nursing time, its specific value can be adjusted or set according to needs; the initial nursing level of the target user can be initially set independently according to the patient's condition, and then rationally adjusted through the management method designed in this plan.

[0104] Then, when implementing the nursing grade adjustment strategy, the content of adjusting the pre-built nursing grade classification standard is to construct a rehabilitation trend scoring function: Where, T total It represents the comprehensive index of trend change, T(X), which represents the trend change factor of index X. The index X in the brackets covers the revised rehabilitation service effect estimation Eg in the above formula. ad , Barthel index Ba, PEI value Pe and physical condition assessment value PSS; the value of each T(X) is: ;

[0105] In the formula, when the corresponding index X is less than the previous index X0 and the corresponding threshold mol X When the cumulative value of the corresponding indicator X is greater than the previous indicator X0 and the corresponding threshold mol X When the cumulative value of , it means that the indicator X has increased significantly, so the trend change factor of indicator X is: -1 (need to reduce the nursing level and balance nursing resources); when other situations occur, the trend change factor of indicator X is: 0 (no change or adjustment); w1, w2, w3 and w4 are weight coefficients, ranging from 0 to 1;

[0106] It should be noted that the weight coefficient is determined using the coefficient of variation method, which is a method of assigning weights to each indicator based on the degree of variation between the current value of each evaluation indicator and the target value. If the numerical difference of an indicator is large, it can clearly distinguish the evaluated objects, indicating that the indicator has rich discrimination information, and thus the indicator should be given a larger weight. Conversely, if the numerical difference of each evaluated object on a certain indicator is small, then the ability of this indicator to distinguish the evaluated objects is weak, and thus the indicator should be given a smaller weight. This method directly uses the information contained in each indicator to calculate the weight of the indicator, and therefore is objective.

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

[0108] Where ΔL represents the target user's current adjustment level, wol represents the preset standard threshold, and 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 getting worse, so the care level needs to be adjusted to a higher level. For example, if the original target user's care level is level 2, when the overall trend is detected to be worsening, it is necessary to adjust it to level 1, increase the average daily care time, and enhance the service content.total >wol indicates that the overall trend is positive, so the nursing level needs to be adjusted to a later level to save nursing resources to a certain extent.

[0109] By adopting dynamic hierarchical regulation and a trend scoring function based on multidimensional indicators, this solution can judge in real time whether the overall rehabilitation trend of the target user is improving or deteriorating based on the changing trends of the target user's Barthel index, PEI value, physical condition assessment value, and rehabilitation service effect valuation. On the one hand, it can achieve dynamic adjustment of nursing levels, avoid resource waste or insufficient care caused by fixed nursing operations, and complete dynamic balancing operations. On the other hand, without changing the configuration of nursing staff, it improves the quality of nursing services, enables a more reasonable allocation of nursing resources, and improves nursing efficiency.

[0110] Based on the results of the implementation of the care level adjustment strategy, if the results show:

[0111] When the overall trend is positive and the current nursing level is level 3, it means that no further downgrade or upgrade is possible, and the nursing duration is adjusted according to the degree to which the indicators deviate from the ideal values. The degree to which the indicators deviate from the ideal values refers to the degree to which the Barthel index Ba, PEI value Pe, and physical condition assessment value PSS deviate from their ideal range values. The ideal range value represents the lowest ideal value to the highest ideal value. The specific data is set according to actual needs and will not be elaborated on here.

[0112] If you need to upgrade but you are already at the highest level (i.e. nursing level L=1):

[0113] ;

[0114] Where ΔTr represents the change in the average daily nursing time, in hours / day, indicating the amount of nursing time that needs to be increased or decreased; for example, if 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 Indicates the lowest ideal value of Barthel index Ba, Pe low Indicates the lowest ideal value of PEI value Pe, PSS low Indicates the lowest ideal value of the physical condition assessment value PSS. b1, b2, and b3 are weight coefficients, ranging from 0 to 1. If an extreme case occurs and the calculated result ΔTr is less than 0, then according to the established constraints, the ΔTr in this extreme case can be directly changed to 1, that is, the original 4 hours / day is changed to 5 hours / day.

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

[0116] ;

[0117] In the formula, Ba high Indicates the highest ideal value of Barthel index Ba, Pe high Indicates the highest ideal value of PEI value Pe, PSS high Indicates the highest ideal value of the physical condition assessment value PSS. b1, b2, and b3 are weight coefficients, ranging from 0 to 1. If an extreme case occurs and the result is not less than 0, then the same as above, ΔTr can be directly changed to -1. No further explanation is given here.

[0118] Effect description: The implementation of the above-mentioned nursing level adjustment strategy, on the one hand, achieved the response to changes in rehabilitation trends by fine-tuning the nursing duration when the nursing level could not be raised or lowered; on the other hand, it embodied the principle of personalized intervention, that is, dynamically adjusting the input of nursing resources according to the differences in individual functional status, avoiding both excessive and insufficient care.

[0119] The above scheme realizes the fine-tuning operation of the average daily nursing time when the nursing level has reached the limit, and introduces the ideal range deviation degree of the Barthel index, PEI value and physical condition assessment value. The overall scheme can flexibly adjust the nursing time to adapt to the changes in rehabilitation trends under the premise that the nursing level remains unchanged or cannot be adjusted further, realizing "fine-grained resource regulation under the premise of immutable level" and solving the problem of "inelasticity" of traditional nursing level. On the one hand, it realizes personalized nursing resource allocation according to functional status differences, maintains the stability of nursing level while enhancing service flexibility. On the other hand, it avoids the disconnection of nursing caused by level restrictions and completes the optimization management operation of nursing operations.

[0120] Example 2:

[0121] Based on Example 1, this embodiment further provides a management system for providing nursing and rehabilitation services, the system comprising:

[0122] Information collection module: collects and maintains all users’ personal information;

[0123] Evaluation and comparison module: Regularly conduct health assessments on target users, obtain and generate comprehensive rehabilitation valuation scores based on rehabilitation status data sets, and calculate the rehabilitation progress percentage according to the set evaluation cycle to evaluate the progress of rehabilitation effects;

[0124] Intelligent recommendation module: Based on the target user's rehabilitation status dataset, a rehabilitation plan recommendation system based on the knowledge graph is configured. When a target health problem is detected, the optimal rehabilitation plan is retrieved from the knowledge graph and the recommended action is completed;

[0125] Service Determination Module: This module comprehensively evaluates the effectiveness of rehabilitation services at different stages of rehabilitation progress according to time series. It uses an improved multi-dimensional evaluation model that inputs nursing variables and outputs an estimated value of the rehabilitation service effectiveness of the target user with nursing staff, which is used to measure the overall service quality at the current stage.

[0126] Result correction module: retrieve the target user's age from personal information, build a correction model, calibrate the positive correction coefficient based on the age range, and use the product of the positive correction coefficient and the estimated rehabilitation service effect as the corrected rehabilitation service effect estimate;

[0127] Adjustment management module: detects whether the target user meets the set rehabilitation goals; if not, an adjustment signal is issued, and feedback is given: secondary optimization adjustment is performed on the given recommended actions; if so, a fluctuation determination response mechanism is triggered: determines whether the change in the revised rehabilitation service effect valuation is within the expected fluctuation range under the previous and subsequent evaluation cycles; if so, no response action is taken for the time being; if not, the secondary response adjustment sub-mechanism is triggered: determines whether the revised rehabilitation service effect valuation is rising or falling, and executes the nursing level adjustment strategy to adjust the pre-built nursing level classification standards.

[0128] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0129] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0130] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A management method for nursing and rehabilitation services, the method comprising: Collect and maintain personal information about all users; Regularly conduct health assessments on target users, obtain and generate comprehensive rehabilitation valuation scores based on rehabilitation status data sets, and calculate the rehabilitation progress percentage according to the set assessment cycle to evaluate the progress of rehabilitation effects; Based on the target user's rehabilitation status dataset, a rehabilitation plan recommendation system based on the knowledge graph is configured. When a target health problem is detected, the best rehabilitation plan is retrieved from the knowledge graph and the recommended action is completed. The characteristics are: The effectiveness of rehabilitation services at different rehabilitation progress percentages was comprehensively evaluated over time. An improved multi-dimensional evaluation model was used to input nursing variables and output the estimated effectiveness of rehabilitation services for target users equipped with nursing staff. This model was used to measure the overall service quality at the current stage. The target user's age is retrieved from personal information, and a correction model is constructed. The positive correction coefficient is calibrated based on the age range, and the product of the positive correction coefficient and the estimated rehabilitation service effect is used as the revised estimated rehabilitation service effect; Detect whether the target user meets the set rehabilitation goals; if not, send an adjustment signal and provide feedback: perform secondary optimization adjustments on the given recommended actions; if so, trigger the fluctuation judgment response mechanism: judge whether the change in the revised rehabilitation service effect valuation is within the expected fluctuation range under the previous and subsequent evaluation cycles; if so, do not take any response action for the time being; if not, continue to trigger the secondary response adjustment sub-mechanism: judge whether the revised rehabilitation service effect valuation is rising or falling, and execute the nursing level adjustment strategy to adjust the pre-built nursing level classification standards.

2. A management method for nursing and rehabilitation services according to claim 1, characterized in that: Personal information shall at least include: basic information, health status, medical history, family and social support; The basic information includes at least: name, age and gender.

3. A management method for nursing and rehabilitation services according to claim 1, characterized in that: The rehabilitation status data set includes at least: Barthel index, PEI value and physical status assessment value; The physical condition evaluation value is to evaluate the physical health of the target user through physiological indicators, which include at least: blood pressure, blood sugar, heart rate and body mass index (BMI). The process of obtaining the physical condition evaluation is as follows: Screening indicators: Select physiological indicators related to the target user's disease; Standardization processing: Use linear interpolation method to convert each physiological index into a standard score; Comprehensive calculation: Based on the standard score corresponding to each physiological indicator, cumulative average processing is performed to generate the target user's physical condition assessment value PSS.

4. A management method for nursing and rehabilitation services according to claim 3, characterized in that: When generating a comprehensive rehabilitation estimate score, the Barthel Index, PEI value, and physical condition assessment value are weighted and summed to obtain a comprehensive rehabilitation estimate score. The process for calculating the rehabilitation progress percentage is as follows: Set an evaluation cycle: conduct evaluation once a month; Record each score: After each assessment, record the Barthel index, PEI value, and physical status assessment value, and calculate the comprehensive rehabilitation valuation score; Calculate the recovery progress percentage: Generate the recovery progress percentage based on the current comprehensive recovery valuation score and the initial comprehensive recovery valuation score.

5. A management method for nursing and rehabilitation services according to claim 1, characterized in that: Nursing variables include at least: rehabilitation progress factor, non-standard operation score and satisfaction score; wherein, the rehabilitation progress factor is the result obtained after completing the calibration processing of the rehabilitation progress percentage based on the pre-built rule engine; the rule engine divides the rehabilitation progress percentage into at least three stages, when the rehabilitation progress percentage Rpe>40%, when 40%≥Rpe≥10% and when Rpe<10%, the rehabilitation progress factors are 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 assessment strategy; The content of the nursing operation compliance assessment strategy is as follows: count the frequency of nursing operations that do not meet standard specifications in the previous assessment period, and convert the frequency into a non-standard operation score F_norm through normalization; The satisfaction score is obtained by scoring the target users' satisfaction questionnaire on nursing services.

6. A management method for nursing and rehabilitation services according to claim 5, characterized in that: The operation process of the improved multi-dimensional evaluation model is as follows: based on the input nursing variables, a comprehensive evaluation function is executed: the non-standard operation score F_norm and the normalized satisfaction score Sz are weightedly summed, and the sum result is corrected by the rehabilitation progress factor to produce the rehabilitation service effect valuation Eg.

7. A management method for nursing and rehabilitation services according to claim 1, characterized in that: The pre-built nursing level classification content includes at least: when the nursing level is level one nursing, the average daily 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 average daily nursing time is 3 hours / day, and the service content is: partial assistance + functional training; when the nursing level is level three nursing, the average daily nursing time is 2 hours / day, and the service content is: self-management + regular inspections.

8. A management method for nursing and rehabilitation services according to claim 7, characterized in that: Adjustments to the pre-built care level classification criteria include: Construct a recovery trend scoring function: Where, T total represents the comprehensive index of trend change, T(X) represents the trend change factor of indicator X, and indicator X at least includes: the revised valuation of rehabilitation service effect Eg ad , Barthel index Ba, PEI value Pe and physical condition assessment value PSS; w1, w2, w3 and w4 are weight coefficients, ranging from 0 to 1; when the corresponding index X is less than the previous index X0 and the corresponding threshold mol X When the cumulative value of the corresponding indicator X is greater than the previous indicator X0 and the corresponding threshold value mol X When the cumulative value is , it means that the indicator X has risen significantly, so the trend change factor of the indicator X is: -1; when other conditions occur, the trend change factor of the indicator X is:

0.

9. A management method for nursing and rehabilitation services according to claim 8, characterized in that: Based on the results of the rehabilitation trend scoring function, run the care level adjustment decision function: ; Where ΔL represents the level of adjustment currently required by the target user, wol represents the preset standard threshold, and T total <-wol means the overall trend is getting worse, T total >wol indicates the overall trend is positive; Monitor the results of the care level adjustment strategy if: When the overall trend is positive and the current nursing level is level 3 care, the nursing time is adjusted according to the degree to which the indicators deviate from the ideal values to generate the change in the average daily nursing time; among them, the degree to which the indicators deviate from the ideal values is the degree to which the Barthel index Ba, PEI value Pe and physical condition assessment value PSS deviate from their ideal range values.

10. A management system for providing nursing and rehabilitation services, the system comprising: Information collection module: collects and maintains all users’ personal information; Evaluation and comparison module: Regularly conduct health assessments on target users, obtain and generate comprehensive rehabilitation valuation scores based on rehabilitation status data sets, and calculate the rehabilitation progress percentage according to the set evaluation cycle to evaluate the progress of rehabilitation effects; Intelligent recommendation module: Based on the target user's rehabilitation status dataset, a rehabilitation plan recommendation system based on the knowledge graph is configured. When a target health problem is detected, the optimal rehabilitation plan is retrieved from the knowledge graph and the recommended action is completed; It is characterized by: further comprising: Service Determination Module: This module comprehensively evaluates the effectiveness of rehabilitation services at different stages of rehabilitation progress according to time series. It uses an improved multi-dimensional evaluation model that inputs nursing variables and outputs an estimated value of the rehabilitation service effectiveness of the target user with nursing staff, which is used to measure the overall service quality at the current stage. Result correction module: retrieve the target user's age from personal information, build a correction model, calibrate the positive correction coefficient based on the age range, and use the product of the positive correction coefficient and the estimated rehabilitation service effect as the corrected rehabilitation service effect estimate; Adjustment management module: detects whether the target user meets the set rehabilitation goals; if not, an adjustment signal is issued, and feedback is given: secondary optimization adjustment is performed on the given recommended actions; if so, a fluctuation determination response mechanism is triggered: determines whether the change in the revised rehabilitation service effect valuation is within the expected fluctuation range under the previous and subsequent evaluation cycles; if so, no response action is taken for the time being; if not, the secondary response adjustment sub-mechanism is triggered: determines whether the revised rehabilitation service effect valuation is rising or falling, and executes the nursing level adjustment strategy to adjust the pre-built nursing level classification standards.

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