Nursing decision scheme optimization analysis system based on artificial intelligence

Abstract

The invention discloses a nursing decision scheme optimization analysis system based on artificial intelligence, and relates to the technical field of data processing. The system comprises a nursing knowledge base module, a data acquisition and preprocessing module, a nursing scheme matching degree analysis module, a nursing demand prediction module, a nursing scheme optimization module and a nursing scheme monitoring feedback module. According to the nursing decision scheme optimization analysis system based on artificial intelligence, the medical history, the diagnosis result, the physiological parameter data and the real-time nursing record multi-source information of the patient are integrated, comprehensive and dynamic evaluation of the health condition of the patient is achieved, deep mining and analysis are conducted on the data, and therefore more accurate nursing decision suggestions are obtained; individual nursing schemes are provided according to individual differences of patients, pertinence and effectiveness of nursing measures are ensured, in addition, execution conditions of the nursing schemes are monitored in real time, deviation is found and corrected in time, and scientificity and accuracy of nursing decision making are further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an artificial intelligence-based nursing decision-making scheme optimization and analysis system. Background Art

[0002] In recent years, medical technology has made significant progress, and intelligent technology has gradually been applied to the medical field, especially nursing services. Through artificial intelligence technology and big data analysis technology, in-depth mining and analysis of patient information can be carried out, which can realize the monitoring and management of the entire nursing service process, provide strong support for nursing decision-making, and thus improve service quality and efficiency. In addition, intelligent technology can also assist nursing staff to complete part of the work, reduce their workload, and further improve patient satisfaction and medical experience.

[0003] Since there are differences in the conditions of different patients and the nursing needs at different treatment stages during the implementation of the nursing plan, it is necessary to optimize the implemented nursing plan and then adjust it as needed. However, when optimizing the nursing decision plan, it is difficult to accurately control the optimization nodes, which affects the quality of the nursing plan. Therefore, a nursing decision plan optimization analysis system based on artificial intelligence is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a nursing decision-making plan optimization and analysis system based on artificial intelligence, the system includes a nursing knowledge base module, a data acquisition and preprocessing module, a nursing plan matching degree analysis module, a nursing demand prediction module, a nursing plan optimization module and a nursing plan monitoring feedback module, wherein the modules are connected by electrical signals;

[0005] The nursing knowledge base module includes a knowledge base of disease information, the latest nursing knowledge, clinical operation guidelines, nursing needs and nursing advice data of the nursing program implementation object;

[0006] The data acquisition and preprocessing module is used to collect the patient's basic information, medical history, diagnosis results, and diversified data of physiological parameters, and perform preprocessing operations to ensure the accuracy and consistency of the data;

[0007] The nursing plan matching analysis module evaluates the patient's current status based on the pre-processed data and the nursing standards, including the rehabilitation progress and the stability of physiological indicators, analyzes the matching degree of the current nursing plan, and evaluates the deviation between the nursing plan and the current status, so as to help medical staff accurately understand the patient's status and provide a basis for formulating personalized nursing plans;

[0008] The nursing demand prediction module analyzes the patient's nursing needs, including medication needs, nursing frequency, and nursing type, based on the current nursing plan and current status, and plans nursing resources in advance to ensure the timeliness and effectiveness of nursing services;

[0009] The nursing plan optimization module adjusts and optimizes the nursing decision plan, including nursing goals, nursing measures, and nursing time, based on the patient status assessment and nursing needs analysis results, to improve the pertinence and effectiveness of the nursing plan and meet the needs of the patient;

[0010] The nursing plan monitoring and feedback module is used to monitor the implementation of the nursing plan and collect feedback information on the patient's recovery process to further optimize the nursing decision-making plan, ensure that the nursing plan is accurately implemented, and promptly discover and correct problems in the implementation process.

[0011] Preferably, the nursing knowledge base module includes a disease information unit, a nursing knowledge unit, a clinical operation guide unit, a nursing demand unit and a nursing suggestion unit;

[0012] Construct a nursing knowledge base framework, use disease information units to record the etiology, pathophysiological process, clinical manifestations, diagnostic criteria and treatment methods of the diseases to which the nursing program is applied, and use nursing knowledge units to regularly update the latest nursing research results, nursing techniques and nursing methods;

[0013] The clinical operation guide unit provides standard procedures, precautions and skills for various nursing operations, and extracts the patient's personal information in combination with the nursing needs unit. According to the patient's specific situation, the nursing needs are analyzed, and then the corresponding nursing suggestions and guidance are matched based on the patient's disease information and nursing needs.

[0014] Collect relevant literature from medical journals, nursing professional books, and clinical guidelines, organize them and enter them into the nursing knowledge base, use international nursing terminology to code nursing problems, and use a unified disease classification system to code diseases.

[0015] Preferably, in the data acquisition and preprocessing module, the data collection and preprocessing process includes:

[0016] Obtain the patient's basic information, medical history and diagnosis data through the medical records in the hospital information system, and use monitoring equipment (heart rate monitor, blood pressure monitor, etc.) to monitor and record the patient's physiological parameter data, including heart rate, blood pressure, blood sugar, body temperature, etc.;

[0017] Preprocess the collected data, including data cleaning and data conversion steps, and integrate the preprocessed data from different data sources to form a unified data set;

[0018] Verify the data in the data set, analyze the integrity, consistency and rationality of the data, ensure that all necessary data fields have been filled, evaluate the integrity of the data, verify whether the logical relationship between the data is reasonable, ensure the consistency of the data, check whether the data is within a reasonable range, ensure the rationality of the data, and store the verified data in the data warehouse for subsequent query and analysis.

[0019] Preferably, in the nursing plan matching degree analysis module, the nursing plan matching degree analysis process includes:

[0020] Extract the patient's current nursing plan and current status data from the preprocessed data to form the patient's health record, where the current nursing plan includes nursing goals, nursing measures, and nursing frequency;

[0021] Based on the patient's diagnosis, medical history, and current symptom status data, the patient's current rehabilitation progress and the stability of physiological indicators are evaluated to analyze the patient's physiological status trend, monitor the treatment response, the degree of symptom improvement, and any signs of functional recovery or disease deterioration. By monitoring the patient's physiological indicator data, its stability is evaluated. The stability of physiological indicators reflects the patient's overall health status and disease progression trend, helps predict the patient's future health status, and provides a basis for formulating and adjusting nursing plans;

[0022] Compare the patient's physiological status trend with the nursing benchmark goals in the nursing standards to analyze whether the current nursing plan meets the patient's actual needs. The nursing benchmark goals are set based on the patient's diagnosis, severity of the disease, and nursing needs;

[0023] Based on the patient's current status data, the actual nursing effect is scored, and the expected nursing effect is scored in combination with the target effect set by the nursing plan and the standard. According to the nursing benchmark target of the nursing plan, the acceptable deviation score is preset to define the acceptable deviation between the actual nursing effect and the expected nursing effect;

[0024] The plan deviation index is calculated by comparing the difference between the expected effect and the actual effect of the nursing plan, analyzing the degree of deviation between the current nursing plan and the actual needs of the patient, and quantitatively reflecting the matching degree between the nursing plan and the patient's condition.

[0025] Preferably, the calculation process of the scheme deviation index is:

[0026] Calculate whether the difference between the actual nursing effect score and the expected nursing effect score is within the acceptable deviation range, and analyze the relative difference between the actual nursing effect and the expected nursing effect. Combine the analysis to obtain the results of the deviation calculation and the difference calculation to obtain the relative difference function;

[0027] Calculate the relative size ratio between the actual nursing effect score and the expected nursing effect score, make weighted adjustments, analyze the relative size between the actual nursing effect and the expected nursing effect, and obtain the relative deviation function;

[0028] The relative difference function and the parts of the relative deviation function are combined to obtain the regimen deviation index, which quantifies the degree of deviation of the nursing regimen.

[0029] Preferably, the calculation formula of the scheme deviation index is:

[0030] ;

[0031] ;

[0032] ;

[0033] in, is the solution deviation index, is the relative difference function, is the relative deviation function, Score the actual nursing effect. Score the expected nursing effect. is the acceptable deviation score, is the adjustment factor, which is a positive integer. is a weight factor between 0 and 1, used to adjust the sensitivity of the formula. It should be noted that The value range is between 0 and 1. When , it means that the actual nursing effect is completely consistent with the expected nursing effect. When , it indicates that there is a significant deviation between the actual nursing effect and the expected nursing effect.

[0034] Preferably, in the nursing demand prediction module, the analysis process of patient nursing demand includes:

[0035] Extract the patient's basic information, medical history (including previous diseases, surgical history, etc.), diagnosis results and physiological parameter data from the hospital information system, combine the nursing plan with the analysis of the patient's actual physiological parameters and the expected values ​​in the nursing plan, and evaluate the effectiveness and adaptability of the current nursing plan. The greater the deviation, the more likely the nursing plan needs to be adjusted. Among them, basic information, medical history and diagnosis results are used to understand the patient's overall health status and potential risks, and physiological parameter data reflect the patient's current health status;

[0036] Analyze the patient's medication needs, including the type of medication, dosage, and frequency of administration, based on the patient's condition and treatment response; analyze the required frequency of care based on the patient's ability to take care of themselves and changes in their condition; and analyze the required type of care based on the patient's disease characteristics and care needs, including basic care (cleaning, turning over, etc.) and specialized care (wound care, rehabilitation training, etc.);

[0037] Based on the analysis results and the patient's nursing needs, plan nursing resources in advance, arrange nursing staff's work shifts, ensure that there are enough nursing staff to provide necessary nursing services, prepare the required medicines and medical devices according to the patient's medication needs and nursing plan, and ensure that they can be used immediately when needed, and formulate a personalized nursing plan based on the patient's specific situation and nursing needs, including specific nursing measures, schedules and responsible persons;

[0038] Based on the analysis results and the regimen deviation index, adjust the personalized care plan, including adjusting the drug dosage, changing the frequency or type of care to better meet the patient's needs, and regularly evaluate the patient's health status and monitor the implementation of the care plan to further optimize the care decision plan.

[0039] Preferably, in the nursing plan optimization module, the process of adjusting and optimizing the nursing decision plan includes:

[0040] Combine the patient's medical history, diagnostic results and physiological parameter data to conduct a comprehensive assessment of the patient's health status, including the severity of the patient's condition, the risk of potential complications and self-care ability, and adjust the care goals according to the patient's condition and treatment response to ensure that they match the patient's current health status;

[0041] Based on the calculation results of the scheme deviation index, three different deviation ranges are divided, namely slight deviation, moderate deviation and severe deviation, and corresponding deviation values ​​are set for each deviation range;

[0042] By using the numerical value of the plan deviation index and the determined deviation range, it is possible to determine whether the nursing plan needs to be adjusted and the extent of the adjustment, and then adjust and optimize the nursing decision plan.

[0043] Preferably, the numerical value of the scheme deviation index is obtained and the deviation value preset in the deviation range is matched with the three-level deviation range, which are respectively:

[0044] Slight deviations: ; Indicates that the nursing plan is basically consistent with the patient's needs and only requires minor adjustments;

[0045] Moderate Deviation: ; It means that there is a certain deviation between the nursing plan and the patient's needs, and appropriate adjustments are needed;

[0046] Serious deviations: ; It means that there is a large deviation between the nursing plan and the patient's needs and it needs to be adjusted significantly;

[0047] in, is the solution deviation index, is the lower threshold corresponding to moderate deviation and the upper threshold corresponding to slight deviation, is the lower threshold corresponding to severe deviation and the upper threshold corresponding to moderate deviation, , .

[0048] Preferably, in the nursing plan monitoring feedback module, the process of monitoring the nursing plan execution includes:

[0049] Through the hospital information system, monitor the implementation of each step of the nursing plan to ensure that the nursing measures are carried out as planned, and record various data during the nursing implementation process, including nursing time, implementation personnel, and patient response, compare the expected goals in the nursing plan with the actual implementation, and analyze whether there are deviations or omissions in the implementation process of the nursing staff;

[0050] Obtain feedback information on the patient's rehabilitation process by observing the patient's behavioral responses and changes in physiological parameters, and conduct a comprehensive analysis and evaluation of the nursing decision-making plan based on the nursing plan execution monitoring results and the patient's rehabilitation process feedback information, and evaluate the effectiveness, feasibility and patient satisfaction indicators of the nursing plan;

[0051] According to the analysis and evaluation results, the nursing decision plan is further revised, including the adjustment of nursing goals, nursing measures, and nursing time. The revised nursing decision plan is verified to ensure its effectiveness and feasibility in actual application, and the verified plan is implemented and its implementation is continuously monitored;

[0052] Record monitoring results, patient feedback, problem handling and plan adjustment information in detail in the patient's electronic health record, establish a continuous improvement mechanism, and regularly review and update the care plan.

[0053] The present invention provides a nursing decision-making scheme optimization analysis system based on artificial intelligence. It has the following beneficial effects:

[0054] 1. This artificial intelligence-based nursing decision-making optimization and analysis system integrates the patient's medical history, diagnostic results, physiological parameter data, and real-time nursing record multi-source information to achieve a comprehensive and dynamic assessment of the patient's health status, conduct in-depth mining and analysis of the data, and thus obtain more accurate nursing decision-making recommendations. It provides personalized nursing plans based on individual differences of patients to ensure the pertinence and effectiveness of nursing measures. In addition, it monitors the implementation of nursing plans in real time, promptly discovers and corrects deviations, and further improves the scientificity and accuracy of nursing decisions.

[0055] 2. This artificial intelligence-based nursing decision-making optimization and analysis system can achieve optimal allocation of nursing resources through intelligent management of nursing decision-making plans. It can analyze patients' future nursing needs, plan nursing staff's scheduling and task allocation in advance, and avoid idle and waste of resources. At the same time, it can also dynamically adjust nursing plans according to patients' real-time condition and nursing needs to ensure that patients receive timely and effective services when they need care most, which not only improves nursing efficiency, but also improves patient satisfaction and medical quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a structural module diagram of a nursing decision-making scheme optimization and analysis system based on artificial intelligence of the present invention;

[0057] Figure 2 This is a flow chart for analyzing the matching degree of the nursing plan of the present invention;

[0058] Figure 3 A flow chart for adjusting and optimizing the nursing decision-making scheme for the present invention. DETAILED DESCRIPTION

[0059] 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.

[0060] The first embodiment, as Figure 1 , Figure 2 As shown, the present invention provides a technical solution: a nursing decision-making plan optimization and analysis system based on artificial intelligence, the system includes a nursing knowledge base module, a data acquisition and preprocessing module, a nursing plan matching degree analysis module, a nursing demand prediction module, a nursing plan optimization module and a nursing plan monitoring feedback module, wherein the modules are connected by electrical signals;

[0061] The nursing knowledge base module contains the disease information, latest nursing knowledge, clinical operation guidelines, nursing needs and nursing advice data of the objects of nursing plan implementation. The nursing knowledge base module includes disease information unit, nursing knowledge unit, clinical operation guide unit, nursing needs unit and nursing advice unit. The nursing knowledge base framework is constructed. The disease information unit is used to record the etiology, pathophysiological process, clinical manifestations, diagnostic criteria and treatment methods of the diseases of the objects of nursing plan implementation. The nursing knowledge unit is used to regularly update the latest nursing research results, nursing technology and nursing methods. The clinical operation guide unit provides standard procedures, precautions and skills for various nursing operations. The nursing needs unit is combined to extract the patient's personal information. According to the patient's specific situation, the nursing needs are analyzed. Based on the patient's disease information and nursing needs, the corresponding nursing advice and guidance are matched. The relevant literature and materials of medical journals, nursing professional books and clinical guidelines are collected, sorted and entered into the nursing knowledge base, and international nursing terminology is used to encode nursing problems and a unified disease classification system is used to encode diseases.

[0062] The data acquisition and preprocessing module is used to collect the patient's basic information, medical history, diagnosis results, and diversified physiological parameter data, and perform preprocessing operations to ensure the accuracy and consistency of the data. The patient's basic information, medical history, and diagnosis result data are obtained through the medical records in the hospital information system, and monitoring equipment (heart rate monitors, sphygmomanometers, etc.) are used to monitor and record the patient's physiological parameter data, including heart rate, blood pressure, blood sugar, body temperature, etc. The collected data is preprocessed, including data cleaning and data conversion steps. Through data cleaning, missing values ​​are processed, noise values ​​are smoothed, and outliers are identified and processed. For missing data, deletion, mean filling, hot card filling and other methods can be used for processing. Through BIN method (binning), clustering method and other technologies, data with noise can be processed. Perform smoothing, identify and process through statistical methods (such as Z-score, IQR, etc.) or machine learning algorithms, convert data from different sources into a unified format through data conversion, and convert categorical data (such as gender, disease type) into numerical data for subsequent analysis and modeling, integrate pre-processed data from different data sources to form a unified data set, verify the data in the data set, analyze the integrity, consistency and rationality of the data, ensure that all necessary data fields have been filled, evaluate the integrity of the data, verify whether the logical relationship between the data is reasonable, ensure the consistency of the data, check whether the data is within a reasonable range, ensure the rationality of the data, and store the verified data in the data warehouse for subsequent query and analysis;

[0063] The nursing plan matching analysis module evaluates the patient's current status based on the pre-processed data and the nursing standards, including rehabilitation progress and stability of physiological indicators, analyzes the matching degree of the current nursing plan, and evaluates the deviation between the nursing plan and the current status, helping medical staff to accurately understand the patient's status and provide a basis for formulating personalized nursing plans. The patient's current nursing plan and current status data are extracted from the pre-processed data to form the patient's health record. The current nursing plan includes nursing goals, nursing measures, and nursing frequency. According to the patient's diagnosis, medical history, and current status data of symptoms, the patient's current rehabilitation progress and stability of physiological indicators are evaluated to analyze the patient's physiological state trend, monitor the treatment response, the degree of improvement of symptoms, and any signs of functional recovery or worsening of the disease. By monitoring the patient's physiological indicator data, its stability and the stability of physiological indicators are evaluated. It reflects the overall health status and disease progression trend of the patient, helps predict the patient's future health status, and provides a basis for formulating and adjusting the nursing plan. It compares the patient's physiological status trend with the nursing benchmark goals in the nursing standards to analyze whether the current nursing plan meets the patient's actual needs. The nursing benchmark goals are set according to the patient's diagnosis, disease severity and nursing needs. Based on the patient's current status data, the actual nursing effect is scored. In combination with the target effects set by the nursing plan and the standards, the expected nursing effect is scored. According to the nursing benchmark goals of the nursing plan, an acceptable deviation score is preset, and the acceptable deviation between the actual nursing effect and the expected nursing effect is defined. The difference between the expected effect and the actual effect of the nursing plan is compared to calculate the plan deviation index, analyze the degree of deviation between the current nursing plan and the patient's actual needs, and quantitatively reflect the matching degree between the nursing plan and the patient's status;

[0064] Furthermore, the calculation process of the solution deviation index is:

[0065] Calculate whether the difference between the actual nursing effect score and the expected nursing effect score is within the acceptable deviation range, and analyze the relative difference between the actual nursing effect and the expected nursing effect. Combine the analysis to obtain the results of the deviation calculation and the difference calculation to obtain the relative difference function. Calculate the relative size ratio between the actual nursing effect score and the expected nursing effect score, and make a weighted adjustment. Analyze the relative size between the actual nursing effect and the expected nursing effect to obtain the relative deviation function. Combine the relative difference function and the parts of the relative deviation function to obtain the program deviation index, and quantify the degree of deviation of the nursing program.

[0066] Furthermore, the calculation formula of the solution deviation index is:

[0067] ;

[0068] ;

[0069] ;

[0070] in, is the solution deviation index, is the relative difference function, is the relative deviation function, Score the actual nursing effect. Score the expected nursing effect. is the acceptable deviation score, is the adjustment factor, which is a positive integer. is a weight factor between 0 and 1, used to adjust the sensitivity of the formula. It should be noted that The value range is between 0 and 1. When , it means that the actual nursing effect is completely consistent with the expected nursing effect. When the actual nursing effect score is Very close to the expected nursing effect score hour, Close to 0, when the difference between the actual nursing effect score and the expected nursing effect score increases, Increase, when the actual effect is significantly lower than the expected effect, Close to 1;

[0071] Nursing demand prediction module: analyzes the patient's nursing needs, including medication needs, nursing frequency, and nursing type, based on the current nursing plan and current status, and plans nursing resources in advance to ensure the timeliness and effectiveness of nursing services;

[0072] The nursing plan optimization module adjusts and optimizes the nursing decision plan, including nursing goals, nursing measures, and nursing time, based on the patient status assessment and nursing needs analysis results, to improve the pertinence and effectiveness of the nursing plan and meet the needs of patients;

[0073] The nursing plan monitoring and feedback module is used to monitor the implementation of the nursing plan and collect feedback information on the patient's recovery process to further optimize the nursing decision-making plan, ensure that the nursing plan is accurately implemented, and promptly discover and correct problems in the implementation process.

[0074] The second embodiment is based on the first embodiment. Figure 3 As shown in the figure, in the nursing demand prediction module, the analysis process of patient nursing demand includes:

[0075] Extract the patient's basic information, medical history (including previous illnesses, surgical history, etc.), diagnosis results data and physiological parameter data from the hospital information system, combine the nursing plan with the analysis of the patient's actual physiological parameters and the expected values ​​in the nursing plan, and evaluate the effectiveness and adaptability of the current nursing plan. The greater the deviation, the more likely it is that the nursing plan may need to be adjusted. Among them, basic information, medical history and diagnosis results are used to understand the patient's overall health status and potential risks. Physiological parameter data reflects the patient's current health status. According to the patient's condition and treatment response, analyze the patient's drug needs, including drug types, dosages and frequency of administration. According to the patient's ability to take care of themselves and changes in their condition, analyze the required frequency of care. According to the patient's disease characteristics and nursing needs, analyze the required type of care, including basic care. According to the analysis results and the patient's care needs, plan nursing resources in advance, arrange the work shifts of nursing staff, ensure that there are enough nursing staff to provide necessary nursing services, prepare the required medicines and medical devices according to the patient's medication needs and care plan, and ensure that they can be used immediately when needed. According to the patient's specific situation and care needs, formulate a personalized care plan, including specific care measures, schedules and responsible persons. Based on the analysis results and the plan deviation index, adjust the personalized care plan, including adjusting the drug dosage, changing the frequency or type of care, to better meet the patient's needs, and regularly evaluate the patient's health status and monitor the implementation of the care plan to further optimize the care decision plan;

[0076] In the nursing plan optimization module, the process of adjusting and optimizing the nursing decision plan includes:

[0077] Combined with the patient's medical history, diagnosis results and physiological parameter data, a comprehensive assessment of the patient's health status is conducted, including an assessment of the severity of the patient's condition, the risk of potential complications and self-care ability. The nursing goals are adjusted according to the patient's condition and treatment response to ensure that they match the patient's current health status. Based on the calculation results of the program deviation index, three different deviation ranges are divided, namely slight deviation, moderate deviation and severe deviation, and corresponding deviation values ​​are set for each deviation range. Using the value of the program deviation index and the determined deviation range, it is clear whether the nursing plan needs to be adjusted and the degree of adjustment, and then the nursing decision plan is adjusted and optimized. For minor deviations, fine-tune the nursing goals to adapt to the patient's current condition, make small adjustments to the nursing measures, increase or decrease the frequency or intensity of certain nursing operations, and for moderate deviations, comprehensively review the nursing plan, including nursing goals, nursing measures, and nursing time, adjust the drug dosage, change the type of care, or add specific nursing operations to meet the patient's needs. For serious deviations, immediately make major adjustments to the nursing plan, including re-evaluating the patient's condition, adjusting the treatment plan, increasing the participation of professional nursing staff, and arranging nursing time according to the patient's biological clock and condition characteristics to ensure that the patient receives timely service when he needs care most;

[0078] Furthermore, the numerical value of the scheme deviation index is obtained and the deviation value preset in the deviation range is matched to the three-level deviation range, which are:

[0079] Slight deviations: ; Indicates that the nursing plan is basically consistent with the patient's needs and only requires minor adjustments;

[0080] Moderate Deviation: ; It means that there is a certain deviation between the nursing plan and the patient's needs, and appropriate adjustments are needed;

[0081] Serious deviations: ; It means that there is a large deviation between the nursing plan and the patient's needs and it needs to be adjusted significantly;

[0082] in, is the solution deviation index, is the lower threshold corresponding to moderate deviation and the upper threshold corresponding to slight deviation, is the lower threshold corresponding to severe deviation and the upper threshold corresponding to moderate deviation, , ;

[0083] In the nursing plan monitoring and feedback module, the process of monitoring the implementation of the nursing plan includes:

[0084] Through the hospital information system, monitor the implementation of each step of the nursing plan to ensure that the nursing measures are carried out as planned, and record various data in the nursing implementation process, including nursing time, executors, and patient reactions. Compare the expected goals in the nursing plan with the actual implementation, analyze whether there are deviations or omissions in the implementation process of nursing staff, obtain feedback information on the patient's rehabilitation process by observing the patient's behavioral reactions and changes in physiological parameters, and combine the results of nursing plan implementation monitoring and the feedback information on the patient's rehabilitation process to comprehensively analyze and evaluate the nursing decision plan, evaluate the effectiveness, feasibility and patient satisfaction indicators of the nursing plan, and further revise the nursing decision plan based on the analysis and evaluation results. The revisions include adjustments to nursing goals, nursing measures, and nursing time. Verify the revised nursing decision plan to ensure its effectiveness and feasibility in actual application, implement the verified plan, and continuously monitor its implementation. Record the monitoring results, patient feedback, problem handling, and plan adjustment information in detail in the patient's electronic health record, establish a continuous improvement mechanism, and regularly review and update the nursing plan.

[0085] 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. A nursing decision-making scheme optimization analysis system based on artificial intelligence, characterized in that: The system includes a nursing knowledge base module, a data acquisition and preprocessing module, a nursing plan matching degree analysis module, a nursing demand prediction module, a nursing plan optimization module, and a nursing plan monitoring feedback module, wherein the modules are connected by electrical signals; The nursing knowledge base module includes a knowledge base of disease information, the latest nursing knowledge, clinical operation guidelines, nursing needs and nursing advice data of the nursing program implementation object; The data acquisition and preprocessing module is used to collect the patient's basic information, medical history, diagnosis results, and diversified data of physiological parameters, and perform preprocessing operations; The nursing plan matching analysis module evaluates the patient's current status based on the preprocessed data and the nursing standards, analyzes the matching degree of the current nursing plan, and evaluates the deviation between the nursing plan and the current status; The nursing demand prediction module analyzes the patient's nursing needs based on the current nursing plan and current status; The nursing plan optimization module adjusts and optimizes the nursing decision plan based on the patient status assessment and nursing needs analysis results; The nursing plan monitoring and feedback module is used to monitor the implementation of the nursing plan and collect feedback information on the patient's rehabilitation process.

2. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 1 is characterized in that: The nursing knowledge base module includes a disease information unit, a nursing knowledge unit, a clinical operation guide unit, a nursing demand unit and a nursing suggestion unit; Construct a nursing knowledge base framework, use disease information units to record the etiology, pathophysiological process, clinical manifestations, diagnostic criteria and treatment methods of the diseases to which the nursing program is applied, and use nursing knowledge units to regularly update the latest nursing research results, nursing techniques and nursing methods; The clinical operation guide unit provides standard procedures, precautions and skills for various nursing operations, and extracts the patient's personal information in combination with the nursing needs unit. According to the patient's specific situation, the nursing needs are analyzed, and then the corresponding nursing suggestions and guidance are matched based on the patient's disease information and nursing needs. Collect relevant literature from medical journals, nursing professional books, and clinical guidelines, organize them and enter them into the nursing knowledge base, use international nursing terminology to code nursing problems, and use a unified disease classification system to code diseases.

3. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 2 is characterized in that: In the data acquisition and preprocessing module, the data collection and preprocessing process includes: Obtain the patient's basic information, medical history and diagnostic results data through the medical records in the hospital information system, and use monitoring equipment to monitor and record the patient's physiological parameter data; Preprocess the collected data, including data cleaning and data conversion steps, and integrate the preprocessed data from different data sources to form a unified data set; Verify the data in the data set, analyze the integrity, consistency and rationality of the data, evaluate the integrity of the data, verify the logical relationship between the data, and store the verified data in the data warehouse.

4. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 3 is characterized by: In the nursing plan matching degree analysis module, the nursing plan matching degree analysis process includes: Extract the patient's current nursing plan and current status data from the preprocessed data to form the patient's health record, where the current nursing plan includes nursing goals, nursing measures, and nursing frequency; Based on the patient's diagnosis, medical history, and current symptom data, the patient's current recovery progress and stability of physiological indicators are evaluated to analyze the patient's physiological state trend; Compare the patient's physiological status trend with the nursing benchmark goals in the nursing standards to analyze whether the current nursing plan meets the patient's actual needs. The nursing benchmark goals are set based on the patient's diagnosis, severity of the disease, and nursing needs; Based on the patient's current status data, the actual nursing effect is scored, and the expected nursing effect is scored in combination with the target effect set by the nursing plan and the standard. According to the nursing benchmark target of the nursing plan, the acceptable deviation score is preset to define the acceptable deviation between the actual nursing effect and the expected nursing effect; The plan deviation index is calculated by comparing the difference between the expected effect and the actual effect of the nursing plan, analyzing the degree of deviation between the current nursing plan and the actual needs of the patient, and quantitatively reflecting the matching degree between the nursing plan and the patient's condition.

5. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 4 is characterized in that: The calculation process of the scheme deviation index is: Calculate whether the difference between the actual nursing effect score and the expected nursing effect score is within the acceptable deviation range, and analyze the relative difference between the actual nursing effect and the expected nursing effect. Combine the analysis to obtain the results of the deviation calculation and the difference calculation to obtain the relative difference function; Calculate the relative size ratio between the actual nursing effect score and the expected nursing effect score, make weighted adjustments, analyze the relative size between the actual nursing effect and the expected nursing effect, and obtain the relative deviation function; The relative difference function and the parts of the relative deviation function are combined to obtain the regimen deviation index, which quantifies the degree of deviation of the nursing regimen.

6. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 5 is characterized in that: The calculation formula of the scheme deviation index is: ； ； ； in, is the solution deviation index, is the relative difference function, is the relative deviation function, Score the actual nursing effect. Score the expected nursing effect. is the acceptable deviation score, is the adjustment factor, which is a positive integer. is a weight factor between 0 and 1, used to adjust the sensitivity of the formula. It should be noted that The value range is between 0 and 1. When , it means that the actual nursing effect is completely consistent with the expected nursing effect. When , it indicates that there is a significant deviation between the actual nursing effect and the expected nursing effect.

7. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 6 is characterized in that: In the nursing demand prediction module, the analysis process of patient nursing demand includes: Extract the patient's basic information, medical history, diagnosis data and physiological parameter data from the hospital information system, combine the nursing plan with the analysis of the patient's actual physiological parameters and the expected values ​​in the nursing plan, and evaluate the effectiveness and adaptability of the current nursing plan; Analyze the patient's medication needs, including the type of medication, dosage, and frequency of administration, based on the patient's condition and treatment response; analyze the required frequency of care based on the patient's ability to take care of themselves and changes in their condition; and analyze the required type of care, including basic care and specialized care, based on the patient's disease characteristics and care needs; Based on the analysis results and the patient's nursing needs, plan nursing resources in advance, arrange the nursing staff's work shifts, prepare the necessary medicines and medical devices according to the patient's medication needs and nursing plan, and formulate a personalized nursing plan based on the patient's specific situation and nursing needs, including specific nursing measures, schedules and responsible persons; Based on the analysis results and the regimen deviation index, adjust the personalized care plan, including adjusting the medication dosage, changing the frequency or type of care, and regularly evaluate the patient's health status and monitor the implementation of the care plan to further optimize the care decision plan.

8. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 7 is characterized in that: In the nursing plan optimization module, the process of adjusting and optimizing the nursing decision plan includes: Combine the patient's medical history, diagnostic results and physiological parameter data to conduct a comprehensive assessment of the patient's health status, including the severity of the patient's condition, the risk of potential complications and self-care ability, and adjust the care goals according to the patient's condition and treatment response to ensure that they match the patient's current health status; Based on the calculation results of the scheme deviation index, three different deviation ranges are divided, namely slight deviation, moderate deviation and severe deviation, and corresponding deviation values ​​are set for each deviation range; By using the numerical value of the plan deviation index and the determined deviation range, it is possible to determine whether the nursing plan needs to be adjusted and the extent of the adjustment, and then adjust and optimize the nursing decision plan.

9. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 8, characterized in that: The numerical value of the scheme deviation index is obtained and the deviation value preset in the deviation range is matched with the three-level deviation range, which are: Slight deviations: ; Moderate Deviation: ; Serious deviations: ; in, is the solution deviation index, is the lower threshold corresponding to moderate deviation and the upper threshold corresponding to slight deviation, is the lower threshold corresponding to severe deviation and the upper threshold corresponding to moderate deviation, , .

10. The artificial intelligence-based nursing decision-making optimization analysis system according to claim 9, characterized in that: In the nursing plan monitoring feedback module, the process of monitoring the implementation of the nursing plan includes: Through the hospital information system, monitor the implementation of each step of the nursing plan and record various data during the nursing implementation process, including nursing time, implementation personnel, and patient response. Compare the expected goals in the nursing plan with the actual implementation status, and analyze whether there are deviations or omissions in the implementation process of the nursing staff; Obtain feedback information on the patient's rehabilitation process by observing the patient's behavioral responses and changes in physiological parameters, and conduct a comprehensive analysis and evaluation of the nursing decision-making plan based on the nursing plan execution monitoring results and the patient's rehabilitation process feedback information, and evaluate the effectiveness, feasibility and patient satisfaction indicators of the nursing plan; According to the analysis and evaluation results, the nursing decision plan is further revised, including the adjustment of nursing goals, nursing measures, and nursing time. The revised nursing decision plan is verified, implemented, and its implementation is continuously monitored; Record monitoring results, patient feedback, problem handling and plan adjustment information in the patient's electronic health record, establish a continuous improvement mechanism, and regularly review and update the care plan.

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