Intelligent nursing plan assessment method

Abstract

The invention discloses an intelligent nursing plan assessment method, and relates to the technical field of nursing plan assessment, and the method comprises the steps: obtaining the nursing plan assessment data of a patient, namely the personal physiological state data of the patient and the nursing service quality data, carrying out the preprocessing of the nursing plan assessment data, and obtaining a nursing plan assessment sequence; according to the intelligent nursing plan assessment method, the effectiveness and applicability of the current nursing plan of the patient can be assessed more accurately by collecting and analyzing the personal physiological state index data and the nursing service quality index data of the patient and calculating the nursing plan matching coefficient, the physiological state change of the patient is considered, and the accuracy of the nursing plan assessment is improved. In addition, quality factors of nursing services are integrated, the nursing plan can be dynamically adjusted by periodically updating the physiological data and service quality data of the patient, it is ensured that the nursing plan is always matched with the actual demand of the patient, the treatment effect and life quality of the patient can be improved, and unnecessary medical resource waste is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of nursing plan evaluation, in particular to an intelligent nursing plan evaluation method. Background Art

[0002] With the rapid development of information technology, especially the increasing maturity of technologies such as cloud computing, big data, and artificial intelligence, the field of medical care has ushered in an era of informatization and intelligence. Smart nursing is an inevitable product of the medical care field in the context of the information and intelligent era. It integrates advanced technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence, and provides a new model and means for nursing services. As an important part of smart nursing, intelligent nursing plan evaluation methods can realize rapid processing and analysis of medical data, provide medical staff with accurate disease prediction and personalized treatment recommendations, and optimize nursing processes and service models.

[0003] In the existing technology, patients have individual differences and their own disease characteristics. It is difficult to formulate personalized nursing plans according to patient needs, and it is difficult to dynamically adjust nursing plans according to changes in patient conditions. Therefore, how to integrate the patient's personal physiological state with the quality of nursing services, and then formulate and adjust the patient's nursing plan, is the problem we need to solve. To this end, an intelligent nursing plan evaluation method is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent nursing plan evaluation method, comprising the following steps:

[0005] Step 1: Obtain the patient's nursing plan evaluation data, which are the patient's personal physiological state data and nursing service quality data, and pre-process the nursing plan evaluation data to obtain a nursing plan evaluation sequence;

[0006] Step 2: Perform feature analysis based on the nursing plan evaluation sequence, extract evaluation features related to the patient's personal physiological state and nursing service quality, and analyze the change trend of the patient's personal physiological state and nursing service quality relative to the standard threshold;

[0007] Step 3: Combine historical nursing plan evaluation data to train the nursing plan evaluation model, and then use the model to predict the patient's nursing needs and effects;

[0008] Step 4: Based on the prediction results of the nursing plan evaluation model, combined with the analysis results of the patient's personal physiological state and the change trend of nursing service quality relative to the standard threshold, the nursing plan matching coefficient is obtained to analyze the matching degree of the patient's current nursing plan;

[0009] Step 5: Use the matching degree analysis results of the current nursing plan to re-formulate or dynamically adjust the patient's nursing plan to match the patient's current physiological state.

[0010] Preferably, in step 1, the process of obtaining the nursing plan evaluation sequence includes:

[0011] Collect the patient's historical nursing plan evaluation data and current nursing plan evaluation data, where the nursing plan evaluation data includes the patient's personal physiological status data and nursing service quality data. The patient's personal physiological status data comes from medical equipment (monitors, blood glucose meters, etc.) and patient self-monitoring records, and the nursing service quality data comes from nursing staff's records, patient feedback, and data from the nursing quality monitoring system;

[0012] Preprocess the collected nursing plan evaluation data. The preprocessing stage is divided into data cleaning and data standardization processes. Data cleaning is used to remove duplicate data to ensure that each data point is unique, correct erroneous data with obvious input errors or outliers, and process missing data by interpolation, mean substitution or deletion of missing data points. Data from different sources and dimensions are converted into a unified standard format for subsequent analysis. For continuous variables, normalization is performed to convert them into values ​​between 0 and 1. The preprocessed patient personal physiological status data and nursing service quality data are integrated to form a complete nursing plan evaluation data set to ensure the integrity and consistency of the data set for subsequent analysis.

[0013] The data are sorted into time series according to their timestamps. For each time point, the corresponding physiological status indicators and nursing service quality indicator data are clearly identified to form a nursing plan evaluation sequence.

[0014] Preferably, the physiological status indicators include vital signs, disease symptoms, nutritional metabolism and patient emotional state, wherein vital signs include body temperature, heart rate, respiratory rate, blood pressure, etc., disease symptoms include pain, cough, dyspnea, etc., nutritional metabolism includes body weight, nutritional intake, water and electrolyte balance, etc., and patient emotional state includes anxiety, depression, fear, etc.;

[0015] The nursing service quality indicators include nursing frequency, nursing environment and patient satisfaction, among which the nursing environment includes ward cleanliness, noise level, temperature and humidity, etc.

[0016] Preferably, in step 2, the analysis process of the change trend of the patient's personal physiological state and nursing service quality relative to the standard threshold value includes:

[0017] Combine the nursing plan evaluation sequence with medical guidelines and industry standards to set standard thresholds for patient personal physiological status indicators and nursing service quality indicators. The standard thresholds are used to evaluate the patient's status and the quality of nursing services.

[0018] Conduct feature analysis on the patient's personal physiological status indicators, extract assessment features of vital signs, disease symptoms, nutritional metabolism, and the patient's emotional state, and score each assessment feature of the patient's personal physiological status indicators to obtain vital signs scores, disease symptom scores, nutritional metabolism scores, and patient emotional state scores;

[0019] Conduct feature analysis on nursing service quality indicators, extract evaluation features of nursing frequency, nursing environment and patient satisfaction, and score each evaluation feature of nursing service quality indicators to obtain nursing environment scores and patient satisfaction scores;

[0020] Based on the scoring results of each evaluation feature of the patient's personal physiological state index, the standard scoring threshold of each evaluation feature is determined in combination with the preset standard threshold of the patient's personal physiological state index, the physiological state trend index is calculated, and the change trend of the patient's personal physiological state relative to the standard threshold is analyzed;

[0021] Based on the scoring results of each evaluation feature of the nursing service quality indicators, the standard scoring threshold of each evaluation feature is determined in combination with the preset standard threshold of the nursing service quality indicators, the nursing quality trend index is calculated, and the changing trend of nursing service quality relative to the standard threshold is analyzed.

[0022] Preferably, the expression of the physiological state trend index is:

[0023] ;

[0024] in, is the physiological state trend index, It is The actual score of each patient's personal physiological state assessment feature reflects the patient's current physiological state. It is Standard scoring thresholds for the assessment characteristics of a patient's personal physiological state are set based on medical guidelines and industry standards to assess the quality of the patient's condition. is the total number of characteristics of the patient's individual physiological state assessment, The value range is , where 0 means that the patient's physiological state fully meets the standard threshold, that is, the patient is in an excellent state;

[0025] The expression of the nursing quality trend index is:

[0026] ;

[0027] in, is the nursing quality trend index, is the actual frequency of care, is the preset standard threshold of nursing frequency, is the nursing environment score, is the preset nursing environment standard scoring threshold, is the patient satisfaction score, is the preset patient satisfaction standard score threshold, are weight coefficients, corresponding to the relative importance of nursing frequency, nursing environment, and patient satisfaction in the overall score, and , The value range is , where 0 means that the patient's nursing service quality fully meets the standard threshold, that is, the nursing service quality is excellent.

[0028] Preferably, in step 3, the training process of the nursing plan evaluation model includes:

[0029] Collect relevant nursing plan evaluation data from historical nursing plans, and extract evaluation characteristics of vital signs, disease symptoms, nutritional metabolism, and patient emotional state, as well as evaluation characteristics of nursing frequency, nursing environment, and patient satisfaction;

[0030] Based on the extracted evaluation features combined with the neural network model, the nursing plan evaluation model is trained, and the model is optimized by adjusting the model parameters and using cross-validation and other methods to improve its prediction performance. A part of the original data set is divided as a validation set, and the validation set is used to predict the model, and the accuracy, recall, F1 score and other evaluation indicators are calculated to evaluate the performance of the model. According to the validation results, the model is adjusted and optimized as necessary to improve its generalization ability.

[0031] Deploy the trained nursing plan evaluation model, input the nursing plan evaluation data of the current patient into the nursing plan evaluation model, and evaluate the patient's nursing effect.

[0032] Preferably, in step 4, the analysis process of the degree of matching of the patient's current nursing plan includes:

[0033] Extract the nursing plan evaluation data of a fixed-length evaluation cycle, and calculate the physiological state trend index and nursing quality trend index respectively based on the patient's personal physiological state index data and nursing service quality index data;

[0034] Based on the patient care effect prediction results output by the nursing plan evaluation model, the weights of the physiological state trend index and the nursing quality trend index are determined in combination with the patient's specific conditions and nursing goals;

[0035] Combine the physiological state trend index, nursing quality trend index and their respective weights, merge the physiological state trend index and nursing quality trend index to obtain the nursing plan matching coefficient, and analyze the matching degree between the patient's current nursing plan and its actual needs and nursing service quality;

[0036] A benchmark threshold of the nursing plan matching coefficient is preset, and the nursing plan matching coefficient is compared with the benchmark threshold to determine the matching degree of the patient's current nursing plan, wherein the benchmark threshold is divided into a first benchmark threshold and a second benchmark threshold, and the first benchmark threshold and the second benchmark threshold are used to determine the standards for re-formulating and dynamically adjusting the nursing plan.

[0037] Preferably, the calculation expression of the nursing plan matching coefficient is:

[0038] ;

[0039] in, is the care plan matching coefficient, It is a physiological state trend index, which reflects the changing trend of the patient's personal physiological state relative to the standard threshold. It is a nursing quality trend index, which reflects the changing trend of nursing service quality relative to the standard threshold. and are the weights of the physiological status trend index and the nursing quality trend index, respectively, and , The value range is , where the closer the value is to 0, the lower the degree of match between the nursing plan and the patient's actual needs and nursing service quality; the larger the value, the higher the degree of match.

[0040] Preferably, in step 5, the criteria for re-establishing or dynamically adjusting the patient's nursing plan are:

[0041] If the result of the nursing plan matching coefficient exceeds the first benchmark threshold, it means that the matching degree between the current nursing plan and the actual needs and nursing service quality meets the expected needs and no adjustment is required;

[0042] If the result of the nursing plan matching coefficient is lower than the first benchmark threshold and exceeds the second benchmark threshold, it means that the current nursing plan has a low degree of match with the actual needs and nursing service quality, deviates from the expected goal, and needs to be dynamically adjusted;

[0043] If the result of the care plan matching coefficient is lower than the second benchmark threshold, the care plan needs to be reformulated.

[0044] Preferably, in step 5, the process of re-formulating or dynamically adjusting the nursing plan includes:

[0045] The calculated nursing plan matching coefficient is used to evaluate the matching degree between the patient's current nursing plan and his / her actual needs and nursing service quality, and the deviation trend of the nursing plan matching coefficient relative to the benchmark threshold is analyzed;

[0046] Based on the matching analysis results of the nursing plan matching coefficient relative to the first benchmark threshold and the second benchmark threshold, clarify the response measures of the nursing plan;

[0047] According to the analysis results of the matching degree, determine the direction of re-formulating or dynamically adjusting the nursing plan. If the physiological state trend index is low, it is necessary to increase the monitoring and intervention measures of specific physiological indicators. If the nursing quality trend index is low, it is necessary to improve the quality of nursing services or change the nursing strategy. For the case of a low physiological state trend index, the nursing frequency can be increased, the drug dosage can be adjusted, and the patient's psychological counseling can be strengthened. For the case of a low nursing quality trend index, the nursing process can be optimized, the professional level of nursing staff can be improved, and the nursing environment can be improved.

[0048] Based on the reformulated or adjusted nursing plan, develop detailed implementation steps and timetables to ensure that all nursing staff understand and are familiar with the new nursing plan, provide care for patients in accordance with the new nursing plan, and closely monitor changes in the patient's physiological state and improvements in the quality of nursing services.

[0049] The present invention provides an intelligent nursing plan evaluation method, which has the following beneficial effects:

[0050] 1. This intelligent nursing plan evaluation method can more accurately evaluate the effectiveness and applicability of the patient's current nursing plan by collecting and analyzing the patient's personal physiological state indicator data, nursing service quality indicator data, and calculating the nursing plan matching coefficient. It not only takes into account the patient's physiological state changes, but also integrates the quality factors of nursing services. By regularly updating the patient's physiological data and service quality data, the nursing plan can be dynamically adjusted to ensure that it always matches the patient's actual needs, which helps to improve the patient's treatment effect and quality of life and reduce unnecessary waste of medical resources.

[0051] 2. This intelligent nursing plan evaluation method can plan the use of nursing resources in advance by analyzing the patient's nursing needs and effects. When the nursing plan matching coefficient deviates from the preset benchmark threshold, the nursing staff can make necessary adjustments or re-formulate the nursing plan, which helps the nursing staff to respond and adjust the nursing plan in time and reasonably allocate nursing resources, thereby avoiding resource shortages or waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A method flow chart of an intelligent nursing plan evaluation method of the present invention;

[0053] Figure 2 The present invention is a flowchart for analyzing the changing trend of the individual physiological state of the patient and the quality of nursing services relative to the standard threshold value;

[0054] Figure 3 The flowchart of the analysis of the matching degree of the patient's current nursing plan according to the present invention. DETAILED DESCRIPTION

[0055] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0056] The first embodiment, as Figure 1 , Figure 2 As shown, the present invention provides a technical solution: an intelligent nursing plan evaluation method, comprising the following steps:

[0057] Step 1: Obtain the patient's nursing plan evaluation data, which are the patient's personal physiological state data and nursing service quality data, and pre-process the nursing plan evaluation data to obtain the nursing plan evaluation sequence, collect the patient's historical nursing plan evaluation data and current nursing plan evaluation data, where the nursing plan evaluation data includes the patient's personal physiological state data and nursing service quality data. The patient's personal physiological state data comes from medical equipment (monitors, blood glucose meters, etc.) and patient self-monitoring records. The nursing service quality data comes from the nursing staff's records, patient feedback, and the data of the nursing quality monitoring system. Pre-process the collected nursing plan evaluation data. The pre-processing stage is divided into data cleaning and data standardization processes. Through data cleaning Remove duplicate data to ensure that each data point is unique, correct erroneous data with obvious input errors or outliers, handle missing data by interpolation, mean substitution or deletion of missing data points, convert data from different sources and dimensions into a unified standard format for subsequent analysis, normalize continuous variables and convert them to values ​​between 0 and 1, and integrate the pre-processed patient personal physiological status data and nursing service quality data to form a complete nursing plan evaluation data set, ensure the integrity and consistency of the data set for subsequent analysis, sort the data into a time series according to the timestamp of the data, and for each time point, clarify the corresponding physiological status indicators and nursing service quality indicator data to form a nursing plan evaluation sequence;

[0058] Among them, physiological status indicators include vital signs, disease symptoms, nutritional metabolism and patient emotional state. Among them, vital signs include body temperature, heart rate, respiratory rate, blood pressure, etc., disease symptoms include pain, cough, dyspnea, etc., nutritional metabolism includes weight, nutritional intake, water and electrolyte balance, etc., and patient emotional state includes anxiety, depression, fear, etc.;

[0059] Nursing service quality indicators include nursing frequency, nursing environment and patient satisfaction. The nursing environment includes ward cleanliness, noise level, temperature and humidity, etc.

[0060] Step 2: Perform feature analysis based on the nursing plan evaluation sequence, extract evaluation features related to the patient's personal physiological state and nursing service quality, analyze the changing trends of the patient's personal physiological state and nursing service quality relative to the standard threshold, and combine the nursing plan evaluation sequence with medical guidelines and industry standards to set standard thresholds for the patient's personal physiological state indicators and nursing service quality indicators. The standard thresholds are used to evaluate the patient's condition and the quality of nursing services. Perform feature analysis on the patient's personal physiological state indicators, extract evaluation features of vital signs, disease symptoms, nutritional metabolism, and the patient's emotional state, and score each evaluation feature of the patient's personal physiological state indicators to obtain vital signs scores, disease symptom scores, nutritional metabolism scores, and patient emotional state scores. The nursing service quality indicators are characterized by analyzing the nursing frequency, nursing environment and patient satisfaction, and the evaluation characteristics of the nursing service quality indicators are extracted, and the evaluation characteristics of the nursing service quality indicators are scored to obtain the nursing environment score and the patient satisfaction score. Based on the scoring results of each evaluation characteristic of the patient's personal physiological state indicator, the standard scoring threshold of each evaluation characteristic is determined in combination with the preset standard threshold of the patient's personal physiological state indicator, the physiological state trend index is calculated, and the change trend of the patient's personal physiological state relative to the standard threshold is analyzed. Based on the scoring results of each evaluation characteristic of the nursing service quality indicator, the standard scoring threshold of each evaluation characteristic is determined in combination with the preset standard threshold of the nursing service quality indicator, the nursing quality trend index is calculated, and the change trend of the nursing service quality relative to the standard threshold is analyzed;

[0061] Furthermore, the expression of the physiological state trend index is:

[0062] ;

[0063] in, is the physiological state trend index, It is The actual score of each patient's personal physiological state assessment feature reflects the patient's current physiological state. It is Standard scoring thresholds for the assessment characteristics of a patient's personal physiological state are set based on medical guidelines and industry standards to assess the quality of the patient's condition. is the total number of characteristics of the patient's individual physiological state assessment, The value range of , where 0 means that the patient's physiological state fully meets the standard threshold, that is, the patient is in an excellent state. The increase in the value indicates that the deviation between the patient's physiological state and the standard threshold is greater, that is, the worse the patient's condition is. Close to or equal to hour, A smaller value indicates that the patient is in good condition. and When the deviation increases, An increase in the value indicates a worsening of the patient's condition;

[0064] The expression of nursing quality trend index is:

[0065] ;

[0066] in, is the nursing quality trend index, is the actual frequency of care, is the preset standard threshold of nursing frequency, is the nursing environment score, is the preset nursing environment standard scoring threshold, is the patient satisfaction score, is the preset patient satisfaction standard score threshold, are weight coefficients, corresponding to the relative importance of nursing frequency, nursing environment, and patient satisfaction in the overall score, and , The value range is , where 0 means that the patient's nursing service quality fully meets the standard threshold, that is, the nursing service quality is excellent. The increase in the value indicates that the greater the deviation of the patient's nursing service quality from the standard threshold, that is, the worse the nursing service quality. Close to or equal to hour, A smaller value indicates good nursing service quality; when the deviation of the score from the standard threshold increases, An increase in the value indicates a deterioration in the quality of nursing services;

[0067] Step 3: Train the nursing plan evaluation model in combination with historical nursing plan evaluation data, and then use the model to predict the patient's nursing needs and effects. Collect relevant nursing plan evaluation data from historical nursing plans, and extract evaluation features of vital signs, disease symptoms, nutritional metabolism, and patient emotional state, as well as evaluation features of nursing frequency, nursing environment, and patient satisfaction. Based on the extracted evaluation features and combined with the neural network model, train the nursing plan evaluation model, and optimize the model by adjusting the model parameters and using cross-validation and other methods to improve its prediction performance. Separate a part of the original data set as a validation set, use the validation set to predict the model, and calculate evaluation indicators such as accuracy, recall, and F1 score to evaluate the performance of the model. According to the verification results, make necessary adjustments and optimizations to the model to improve its generalization ability, deploy the trained nursing plan evaluation model, input the nursing plan evaluation data of the current patient into the nursing plan evaluation model, and evaluate the patient's nursing effect.

[0068] Step 4: Based on the prediction results of the nursing plan evaluation model, combined with the analysis results of the patient's personal physiological state and the change trend of nursing service quality relative to the standard threshold, the nursing plan matching coefficient is obtained to analyze the matching degree of the patient's current nursing plan;

[0069] Step 5: Use the matching degree analysis results of the current nursing plan to re-formulate or dynamically adjust the patient's nursing plan to match the patient's current physiological state.

[0070] The second embodiment is based on the first embodiment. Figure 3 As shown, in step 4, the analysis process of the patient's current care plan matching degree includes:

[0071] Extract nursing plan evaluation data of a fixed-length evaluation cycle, calculate the physiological state trend index and the nursing quality trend index respectively according to the patient's personal physiological state indicator data and nursing service quality indicator data, determine the weights of the physiological state trend index and the nursing quality trend index based on the patient's nursing effect prediction results output by the nursing plan evaluation model, combine the patient's specific situation and nursing goals, combine the physiological state trend index, the nursing quality trend index and the determined respective weights, combine the physiological state trend index and the nursing quality trend index to obtain the nursing plan matching coefficient, analyze the matching degree between the patient's current nursing plan and its actual needs and nursing service quality, preset a benchmark threshold of the nursing plan matching coefficient, compare the nursing plan matching coefficient with the benchmark threshold, and judge the matching degree of the patient's current nursing plan, wherein the benchmark threshold is divided into a first benchmark threshold and a second benchmark threshold, and the first benchmark threshold and the second benchmark threshold are used to determine the standard for re-formulating and dynamically adjusting the nursing plan;

[0072] Furthermore, the calculation expression of the nursing plan matching coefficient is:

[0073] ;

[0074] in, is the care plan matching coefficient, It is a physiological state trend index, which reflects the changing trend of the patient's personal physiological state relative to the standard threshold. It is a nursing quality trend index, which reflects the changing trend of nursing service quality relative to the standard threshold. and are the weights of the physiological status trend index and the nursing quality trend index, respectively, and , The value range is , where the closer the value is to 0, the lower the matching degree between the nursing plan and the actual needs of the patient and the quality of nursing services; the larger the value is, the higher the matching degree is. and When both are close to 1, it means that the patient's physiological state and nursing service quality are close to the ideal state. A larger value indicates a better match. or When any value in is far away from 1, it means that the corresponding matching degree decreases. A decreasing value indicates a lower matching degree;

[0075] In step 5, the criteria for re-developing or dynamically adjusting the patient's care plan are:

[0076] If the result of the nursing plan matching coefficient exceeds the first benchmark threshold, it means that the matching degree between the current nursing plan and the actual needs and nursing service quality meets the expected needs and no adjustment is required;

[0077] If the result of the nursing plan matching coefficient is lower than the first benchmark threshold and exceeds the second benchmark threshold, it means that the current nursing plan has a low degree of match with the actual needs and nursing service quality, deviates from the expected goal, and needs to be dynamically adjusted;

[0078] If the result of the care plan matching coefficient is lower than the second benchmark threshold, the care plan needs to be reformulated;

[0079] In addition, in step 5, the process of re-formulating or dynamically adjusting the care plan includes:

[0080] The calculated nursing plan matching coefficient is used to evaluate the degree of match between the patient's current nursing plan and its actual needs and the quality of nursing services. The deviation trend of the nursing plan matching coefficient relative to the benchmark threshold is analyzed. Based on the matching analysis results of the nursing plan matching coefficient relative to the first benchmark threshold and the second benchmark threshold, the response measures of the nursing plan are clarified. According to the analysis results of the matching degree, the direction of re-formulating or dynamically adjusting the nursing plan is determined. If the physiological state trend index is low, it is necessary to increase the monitoring and intervention measures of specific physiological indicators. If the nursing quality trend index is low, it is necessary to improve the quality of nursing services or change the nursing strategy. For the case of a low physiological state trend index, the nursing frequency can be increased, the drug dosage can be adjusted, and the patient's psychological counseling can be strengthened. For the case of a low nursing quality trend index, the nursing process can be optimized, the professional level of nursing staff can be improved, and the nursing environment can be improved. According to the re-formulated or adjusted nursing plan, detailed implementation steps and timetables are formulated to ensure that all nursing staff understand and are familiar with the new nursing plan, provide care for patients according to the new nursing plan, and closely monitor the changes in the patient's physiological state and the improvement of the quality of nursing services.

[0081] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. An intelligent nursing plan evaluation method, characterized in that: The following steps are involved: Step 1: Obtain the patient's nursing plan evaluation data, which are the patient's personal physiological state data and nursing service quality data, and pre-process the nursing plan evaluation data to obtain a nursing plan evaluation sequence; Step 2: Perform feature analysis based on the nursing plan evaluation sequence, extract evaluation features related to the patient's personal physiological state and nursing service quality, and analyze the change trend of the patient's personal physiological state and nursing service quality relative to the standard threshold; Step 3: Combine historical nursing plan evaluation data to train the nursing plan evaluation model, and then use the model to predict the patient's nursing needs and effects; Step 4: Based on the prediction results of the nursing plan evaluation model, combined with the analysis results of the patient's personal physiological state and the change trend of nursing service quality relative to the standard threshold, the nursing plan matching coefficient is obtained to analyze the matching degree of the patient's current nursing plan; Step 5: Use the matching degree analysis results of the current nursing plan to re-formulate or dynamically adjust the patient's nursing plan to match the patient's current physiological state.

2. An intelligent nursing plan evaluation method according to claim 1, characterized in that: In step 1, the process of obtaining the nursing plan evaluation sequence includes: Collect the patient's historical nursing plan evaluation data and current nursing plan evaluation data, wherein the nursing plan evaluation data includes the patient's personal physiological status data and nursing service quality data; Preprocess the collected nursing plan evaluation data. The preprocessing stage is divided into data cleaning and data standardization processes, and integrates the preprocessed patient's personal physiological status data and nursing service quality data to form a complete nursing plan evaluation data set; The data are sorted into time series according to their timestamps. For each time point, the corresponding physiological status indicators and nursing service quality indicator data are clearly identified to form a nursing plan evaluation sequence.

3. An intelligent nursing plan evaluation method according to claim 2, characterized in that: The physiological status indicators include vital signs, disease symptoms, nutritional metabolism and patient emotional state, wherein vital signs include body temperature, heart rate, respiratory rate and blood pressure, disease symptoms include pain, cough and dyspnea, nutritional metabolism includes body weight, nutritional intake and water and electrolyte balance, and patient emotional state includes anxiety, depression and fear; The nursing service quality indicators include nursing frequency, nursing environment and patient satisfaction, among which the nursing environment includes ward cleanliness, noise level, temperature and humidity.

4. An intelligent nursing plan evaluation method according to claim 3, characterized in that: In step 2, the analysis process of the change trend of the patient's personal physiological state and nursing service quality relative to the standard threshold value includes: Combine the nursing plan assessment sequence with medical guidelines and industry standards to set standard thresholds for patient personal physiological status indicators and nursing service quality indicators; Conduct feature analysis on the patient's personal physiological status indicators, extract assessment features of vital signs, disease symptoms, nutritional metabolism, and the patient's emotional state, and score each assessment feature of the patient's personal physiological status indicators to obtain vital signs scores, disease symptom scores, nutritional metabolism scores, and patient emotional state scores; Conduct feature analysis on nursing service quality indicators, extract evaluation features of nursing frequency, nursing environment and patient satisfaction, and score each evaluation feature of nursing service quality indicators to obtain nursing environment scores and patient satisfaction scores; Based on the scoring results of each evaluation feature of the patient's personal physiological state index, the standard scoring threshold of each evaluation feature is determined in combination with the preset standard threshold of the patient's personal physiological state index, the physiological state trend index is calculated, and the change trend of the patient's personal physiological state relative to the standard threshold is analyzed; Based on the scoring results of each evaluation feature of the nursing service quality indicators, the standard scoring threshold of each evaluation feature is determined in combination with the preset standard threshold of the nursing service quality indicators, the nursing quality trend index is calculated, and the changing trend of nursing service quality relative to the standard threshold is analyzed.

5. An intelligent nursing plan evaluation method according to claim 4, characterized in that: The expression of the physiological state trend index is: ； in, is the physiological state trend index, It is The actual score value of the patient's personal physiological status assessment characteristics, It is Standard scoring thresholds for assessing characteristics of individual patient physiological states, is the total number of characteristics of the patient's individual physiological state assessment; The expression of the nursing quality trend index is: ； in, is the nursing quality trend index, is the actual frequency of care, is the preset standard threshold of nursing frequency, is the nursing environment score, is the preset nursing environment standard scoring threshold, is the patient satisfaction score, is the preset patient satisfaction standard score threshold, is the weight coefficient, and .

6. An intelligent nursing plan evaluation method according to claim 5, characterized in that: In step 3, the training process of the nursing plan evaluation model includes: Collect relevant nursing plan evaluation data from historical nursing plans, and extract evaluation characteristics of vital signs, disease symptoms, nutritional metabolism, and patient emotional state, as well as evaluation characteristics of nursing frequency, nursing environment, and patient satisfaction; Based on the extracted evaluation features combined with the neural network model, the nursing plan evaluation model is trained and optimized to improve its prediction performance. A part of the original data set is divided as a validation set, and the model is predicted using the validation set to evaluate the performance of the model. According to the validation results, the model is adjusted and optimized. Deploy the trained nursing plan evaluation model, input the nursing plan evaluation data of the current patient into the nursing plan evaluation model, and evaluate the patient's nursing effect.

7. An intelligent nursing plan evaluation method according to claim 6, characterized in that: In step 4, the analysis process of the degree of matching of the patient's current nursing plan includes: Extract the nursing plan evaluation data of a fixed-length evaluation cycle, and calculate the physiological state trend index and nursing quality trend index respectively based on the patient's personal physiological state index data and nursing service quality index data; Based on the patient care effect prediction results output by the nursing plan evaluation model, the weights of the physiological state trend index and the nursing quality trend index are determined in combination with the patient's specific conditions and nursing goals; Combine the physiological state trend index, nursing quality trend index and their respective weights, merge the physiological state trend index and nursing quality trend index to obtain the nursing plan matching coefficient, and analyze the matching degree between the patient's current nursing plan and its actual needs and nursing service quality; A benchmark threshold of the nursing plan matching coefficient is preset, and the nursing plan matching coefficient is compared with the benchmark threshold to determine the matching degree of the patient's current nursing plan, wherein the benchmark threshold is divided into a first benchmark threshold and a second benchmark threshold, and the first benchmark threshold and the second benchmark threshold are used to determine the standards for re-formulating and dynamically adjusting the nursing plan.

8. An intelligent nursing plan evaluation method according to claim 7, characterized in that: The calculation expression of the nursing plan matching coefficient is: ； in, is the care plan matching coefficient, is the physiological state trend index, is the nursing quality trend index, and are the weights of the physiological status trend index and the nursing quality trend index, respectively, and .

9. An intelligent nursing plan evaluation method according to claim 8, characterized in that: In step 5, the criteria for re-establishing or dynamically adjusting the patient's care plan are: If the result of the nursing plan matching coefficient exceeds the first benchmark threshold, it means that the matching degree between the current nursing plan and the actual needs and nursing service quality meets the expected needs and no adjustment is required; If the result of the nursing plan matching coefficient is lower than the first benchmark threshold and exceeds the second benchmark threshold, it means that the current nursing plan has a low degree of match with the actual needs and nursing service quality, deviates from the expected goal, and needs to be dynamically adjusted; If the result of the care plan matching coefficient is lower than the second benchmark threshold, the care plan needs to be reformulated.

10. An intelligent nursing plan evaluation method according to claim 9, characterized in that: In step 5, the process of re-formulating or dynamically adjusting the nursing plan includes: The calculated nursing plan matching coefficient is used to evaluate the matching degree between the patient's current nursing plan and his / her actual needs and nursing service quality, and the deviation trend of the nursing plan matching coefficient relative to the benchmark threshold is analyzed; Based on the matching analysis results of the nursing plan matching coefficient relative to the first benchmark threshold and the second benchmark threshold, clarify the response measures of the nursing plan; According to the analysis results of the matching degree, determine the direction of re-formulating or dynamically adjusting the nursing plan; Based on the reformulated or adjusted nursing plan, develop detailed implementation steps and timetables, provide care for patients according to the new nursing plan, and monitor changes in the patient's physiological state and improvements in the quality of nursing services.

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