Ear-nose-throat clinical nursing decision-making system based on vital signs of patient

Abstract

The invention discloses an ear-nose-throat clinical nursing decision-making system based on vital signs of a patient, and relates to the technical field of ear-nose-throat clinical nursing. The nursing decision-making system comprises a nursing database construction module, a data acquisition module, a vital sign analysis module, an illness state early warning module, a nursing decision-making support module, a personalized nursing scheme generation module and a nursing scheme execution tracking module, all the modules are connected through electric signals, and the nursing database construction module is connected with the data acquisition module. And acquiring nursing data and nursing rule specifications. According to the ear-nose-throat clinical nursing decision-making system based on the vital signs of the patient, by comprehensively analyzing the vital sign data, the medical history information, the allergy history and the like of the patient, a nursing plan meeting the actual needs of the patient is generated, so that the pertinence and effectiveness of nursing can be improved, the individual needs of different patients can be met, and the patient experience is improved. Therefore, symptoms of patients are relieved, and life quality is improved.

Description

Technical Field

[0001] The invention relates to the technical field of ENT clinical nursing, and in particular to an ENT clinical nursing decision-making system based on patient vital signs. Background Art

[0002] Vital sign monitoring refers to the monitoring and recording of human physiological indicators through various technical means to obtain information about the individual's health status. Vital signs include heart rate, pulse, blood pressure, respiration, blood oxygen, etc., which are important indicators for judging the severity and criticality of the patient's condition. Otolaryngology patients have some particularities. For example, the incidence of diseases such as deafness, snoring, vocal cord polyps, esophageal foreign bodies and tracheal foreign bodies varies among people of different genders and ages, and these differences are often related to the patient's vital signs. Therefore, the nursing work of the otolaryngology department needs to be more meticulous and comprehensive. With the rapid development of science and technology, the emergence and widespread application of various vital sign monitoring equipment have enabled medical staff to obtain patients' vital sign data more conveniently and accurately.

[0003] Since there are large individual differences among patients with ENT diseases, there are certain differences in physiological status and disease severity, which not only affects the interpretation of vital signs data, but also interferes with the formulation of nursing decisions, and thus affects the implementation of nursing strategies for patients with ENT diseases. Therefore, how to comprehensively evaluate the impact of physiological status and disease severity to improve the accuracy of nursing decision-making is the problem we need to solve. To this end, this paper proposes an ENT clinical nursing decision-making system based on patients' vital signs. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: an ENT clinical nursing decision system based on the patient's vital signs, the nursing decision system comprising a nursing database construction module, a data acquisition module, a vital sign analysis module, a disease warning module, a nursing decision support module, a personalized nursing plan generation module and a nursing plan execution tracking module, wherein the modules are connected by electrical signals;

[0005] The nursing database construction module obtains nursing data and nursing rule specifications, structures the nursing data to a minimum, assigns weight values ​​according to the correlation between the nursing data, stores the nursing data in a tree data structure, forms a nursing database, and provides a standardized and structured nursing knowledge foundation for the system, facilitating subsequent nursing decision-making and knowledge reasoning;

[0006] The data acquisition module is used to collect the patient's vital signs data and personal information data, and pre-process the collected vital signs data and personal information data, and ensure the accuracy and real-time nature of the data through high-precision sensors and medical equipment, so as to provide basic data support for subsequent data analysis and nursing decisions;

[0007] The vital signs analysis module monitors the patient's vital signs data and analyzes any abnormalities, which helps medical staff take timely intervention measures to prevent the condition from worsening;

[0008] The disease warning module analyzes the patient's physiological state based on the patient's vital signs data, makes a preliminary assessment of the patient's condition, identifies the severity of the condition and potential risks, provides key information for nursing decision-making, and helps medical staff take appropriate nursing measures in a timely manner;

[0009] The nursing decision support module, based on the nursing database and combined with the patient's condition warning results, generates nursing questions and nursing measures to provide nursing decision suggestions, improve the accuracy and scientificity of nursing decisions, and reduce nursing risks;

[0010] The personalized nursing plan generation module generates a personalized nursing plan based on the individual differences of the patient and the disease warning results, and formulates highly adaptable nursing measures based on the patient's age, physiological structure and disease severity, so as to improve the nursing effect and promote the patient's recovery;

[0011] The nursing plan execution tracking module guides nursing staff to implement the nursing plan and tracks the effects of nursing measures to ensure that the nursing measures are correctly implemented and to adjust the nursing plan in a timely manner to adapt to changes in the patient's condition.

[0012] Preferably, in the nursing database construction module, the process of forming the nursing database includes:

[0013] Identify the nursing problems that the database aims to solve by improving nursing quality, and determine the type and scope of nursing data required, including basic patient information, nursing operation records, and nursing effect evaluation;

[0014] Design the logical and physical structure of the database according to the characteristics and needs of nursing data, determine the relationship between fields, records, tables and databases, as well as the storage method and access path of data;

[0015] Collect the nursing data of patients with historical ENT diseases and the data related to nursing rules and regulations, and decompose the collected data into basic database units, namely fields and records. The nursing data of patients with historical ENT diseases come from the hospital information system, nursing records and patient medical records, and the data related to nursing rules and regulations come from literature and operation guidelines in the nursing field.

[0016] According to the correlation between the data, a weight value is assigned to each data item, and a storage scheme for the tree data structure is designed to define the nodes and establish the parent-child relationship. The processed nursing data is then stored in the database according to the tree structure to form a nursing database.

[0017] Preferably, in the data collection module, the process of collecting vital sign data and personal information data includes:

[0018] Start the data acquisition module, connect sensors and medical equipment, enter the patient's personal information data, and collect the patient's vital signs data through sensors and medical equipment. Sensors include blood pressure cuffs, blood oxygen probes, ECG leads, and temperature probes, etc. Medical equipment includes monitors and electrocardiographs, etc. Vital signs data include heart rate, blood pressure, blood oxygen saturation, and body temperature, etc.;

[0019] Perform pre-processing operations such as data cleaning and format conversion on the collected vital signs data and personal information data, and integrate the pre-processed vital signs data and personal information data to form a complete patient data record, ensuring that each record contains the patient's basic information and corresponding vital signs data;

[0020] The preprocessed data is stored in the data warehouse and transmitted to the remote server in real time.

[0021] Preferably, in the vital signs analysis module, the abnormal situation analysis process includes:

[0022] Preset standard thresholds for each vital sign data, and use the vital sign analysis module to receive the patient's vital sign data of heart rate, blood pressure, blood oxygen saturation and body temperature from a remote server;

[0023] comparing the received vital sign data with their respective standard thresholds and calculating a deviation score for each vital sign data;

[0024] The deviation scores obtained are comprehensively calculated to calculate the abnormal sign recognition index, analyze the abnormalities of the vital sign data, and identify the abnormal sign index based on the abnormal sign;

[0025] Analyze the calculated abnormal sign identification index to determine whether there is an abnormal situation.

[0026] Preferably, the calculation formula of the abnormal sign identification index is:

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] in, It is the abnormal sign recognition index. is the deviation score of the heart rate, is the deviation score of blood pressure, is the deviation score of blood oxygen saturation, is the deviation score of body temperature, is the weight of the heart rate, is the actual heart rate value, is a normal heart rate value. This is the normal range of heart rate. is the weight of blood pressure, is the actual blood pressure value, is the normal blood pressure value. This is the normal range of blood pressure. is the weight of blood oxygen saturation, is the actual blood oxygen saturation value, is the normal blood oxygen saturation value. This is the normal range of blood oxygen saturation. is the weight of body temperature, is the actual body temperature value, is the normal body temperature. This is the normal range of body temperature. The value range is between 0 and 1.

[0033] Preferably, in the condition warning module, the patient condition assessment process includes:

[0034] Analyze the patient's physiological state based on the collected patient's vital signs data, compare and analyze the patient's vital signs data, and analyze the deviation of the patient's vital signs, which are divided into single deviation, two deviations, and three or more deviations;

[0035] According to the deviation of the patient's vital signs, identify whether there are abnormal signs, analyze the severity of the abnormal signs, and divide them into low warning level, medium warning level and high warning level based on the deviation status of the patient's vital signs. Among them, a single deviation corresponds to a low warning level, two deviations correspond to a medium warning level, and three or more deviations correspond to a high warning level;

[0036] By combining the abnormal sign recognition index with the divided warning levels, the corresponding warning threshold is matched for each warning level, and according to the determined warning level, a warning signal is automatically issued to assist medical staff in determining the severity of the patient's condition.

[0037] Preferably, the plurality of warning levels correspond to the plurality of warning thresholds one by one, wherein the warning thresholds include an upper threshold and a lower threshold, and the corresponding relationship between the warning level and the warning threshold is as follows:

[0038] Low warning level ;

[0039] Medium warning level ;

[0040] High alert level ;

[0041] in, It is the abnormal sign recognition index. is the upper threshold of the low warning level and the lower threshold of the medium warning level. is the upper threshold of the medium warning level and the lower threshold of the high warning level. , .

[0042] Preferably, in the nursing decision support module, the generation process of nursing questions and nursing measures includes:

[0043] Comprehensively collect patients’ vital signs, medical history, and allergy information data from medical devices and electronic medical record systems, and conduct in-depth analysis of patients’ data to assess their current physiological status, severity of illness, and potential risks;

[0044] The nursing decision support module calls on the professional knowledge and past experience in the nursing database, compares them with the patient's assessment results, and logically infers the assessment results based on the cases, guidelines and research results in the nursing database, identifies existing nursing problems, and preliminarily proposes corresponding nursing measures;

[0045] The system classifies and organizes the nursing problems obtained by reasoning to ensure that each problem is clear and generates specific solutions and operation steps for each nursing problem.

[0046] Preferably, in the personalized nursing plan generating module, the process of generating the personalized nursing plan includes:

[0047] Based on the generated nursing problems and nursing measures, combined with the professional knowledge and past experience in the nursing database, develop personalized nursing measures for patients, including medication management, diet adjustment, exercise management and psychological support;

[0048] Assess the patient's medication needs based on the patient's disease type, severity of illness, and allergy history. Combine the professional knowledge and past experience in the nursing database to develop a personalized medication management plan for the patient, including the type of medication, dosage, and medication schedule, and identify the side effects, interactions, and contraindications of the medication to ensure medication safety;

[0049] Analyze the patient's nutritional intake, eating habits and preferences through nutritional assessment tools, develop a personalized diet plan based on the patient's nutritional needs and disease characteristics, including food types, intake and cooking methods, and provide diet-related health knowledge to patients and their families;

[0050] Through exercise capacity assessment, we analyze the patient's physical condition, exercise habits and endurance level, develop a personalized exercise plan based on the patient's exercise capacity and disease characteristics, including exercise type, intensity and time, and provide patients with exercise-related health guidance;

[0051] Analyze the patient's mental state, emotional changes and coping style through psychological assessment tools, and provide personalized psychological support services, including psychological counseling and psychological counseling, based on the patient's psychological needs;

[0052] Arrange various nursing measures in chronological order and logical relationship to form clear nursing steps, ensure that each step has clear goals and operation methods, list the required materials according to the nursing steps, ensure that the type, quantity and quality of the materials meet the patient's needs and nursing standards, and determine the execution time and frequency of various nursing measures according to the patient's specific situation and nursing needs, to ensure that the nursing measures can be completed on time, in quantity and with quality;

[0053] Integrate the various nursing measures developed into a complete nursing plan, and record the nursing plan in the patient's electronic medical record.

[0054] Preferably, in the nursing plan execution tracking module, the nursing plan execution process includes:

[0055] Nursing staff shall implement various nursing measures step by step according to the time sequence and logical relationship of the nursing plan. During the implementation process, they shall strictly abide by the operating specifications to ensure the safety and comfort of the patients. When implementing each nursing measure, they shall record in detail the implementation of the nursing measure, the patient's response and changes;

[0056] Regularly monitor the patient's vital signs and condition changes, record and evaluate them, pay close attention to the patient's response and comfort, promptly detect and handle abnormal conditions, and evaluate the effectiveness of nursing measures based on nursing goals and evaluation criteria;

[0057] Conduct detailed analysis of the evaluation results to identify the strengths and weaknesses of the nursing measures, determine whether the nursing plan needs to be adjusted based on the patient's condition and needs, and make corresponding adjustments to the nursing plan based on the evaluation results and the patient's needs. The adjustments include modifying the nursing goals, changing the nursing measures, and adjusting the execution time and frequency;

[0058] Integrate the implementation of the nursing plan, nursing effectiveness evaluation and patient feedback into a report and record it in the patient's electronic medical record to ensure the continuity and traceability of information.

[0059] The present invention provides an ENT clinical nursing decision-making system based on the patient's vital signs. It has the following beneficial effects:

[0060] 1. This ENT clinical nursing decision system based on the patient's vital signs generates a nursing plan that meets the patient's actual needs by comprehensively analyzing the patient's vital signs data, medical history information, allergy history, etc. It can not only improve the pertinence and effectiveness of nursing, but also meet the personalized needs of different patients, thereby alleviating patients' symptoms and improving their quality of life.

[0061] 2. This ENT clinical nursing decision system based on the patient's vital signs generates personalized nursing plans according to the individual differences of the patients and the results of disease warning, formulates highly adaptable nursing measures, improves nursing effects, and promotes patient recovery, so as to better meet the needs of patients, improve nursing satisfaction and rehabilitation effects, and by providing real-time vital signs monitoring and data analysis, patients can have a clearer understanding of their own health status and changes in their condition, so that they can participate more actively in the nursing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A module diagram of an ENT clinical nursing decision-making system based on patient vital signs of the present invention;

[0063] Figure 2 It is a flow chart of analyzing abnormal situations of the present invention;

[0064] Figure 3 The present invention is a flow chart for evaluating the patient's condition. DETAILED DESCRIPTION

[0065] 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.

[0066] The first embodiment, as Figure 1 , Figure 2 As shown, the present invention provides a technical solution: an ENT clinical nursing decision system based on the patient's vital signs, the nursing decision system includes a nursing database construction module, a data acquisition module, a vital sign analysis module, a disease warning module, a nursing decision support module, a personalized nursing plan generation module and a nursing plan execution tracking module, wherein the modules are connected by electrical signals;

[0067] The nursing database construction module obtains nursing data and nursing rule specifications, minimizes the structure of nursing data, assigns weight values ​​according to the correlation between nursing data, uses a tree data structure to store nursing data, and forms a nursing database, providing the system with a standardized and structured nursing knowledge base to facilitate subsequent nursing decisions and knowledge reasoning, clearly improving nursing quality as the nursing problem to be solved by the database, and determining the required nursing data type and scope, including patient basic information, nursing operation records, and nursing effect evaluation. Among them, patient basic information includes patient ID, name, age, gender, contact number, address, allergy history, and previous medical history of ear, nose, and throat related diseases. Nursing operation records include nursing operation ID, patient ID, operation date and time, operation type (cleaning, dressing change, medication, etc.), operation site (nasal cavity, throat, etc.), operator name, and description of operation results. Nursing effect evaluation includes evaluation ID, patient ID, evaluation date and Time, evaluation indicators (pain level, recovery speed, patient satisfaction, etc.), evaluation results (numerical scores, text descriptions, etc.) and the names of the evaluators. According to the characteristics and needs of nursing data, the logical and physical structures of the database are designed, and the relationships between fields, records, tables and databases, as well as the storage methods and access paths of data are determined. Nursing data of patients with historical ENT diseases and relevant data of nursing rules and regulations are collected, and the collected data are decomposed into basic database units, namely fields and records. The nursing data of patients with historical ENT diseases are derived from hospital information systems, nursing records and patient medical records, and the relevant data of nursing rules and regulations are derived from literature and operation guidelines in the field of nursing. According to the correlation between the data, weight values ​​are assigned to each data item, and a storage scheme for a tree data structure is designed to define nodes and establish parent-child relationships. The processed nursing data is then stored in the database according to the tree structure to form a nursing database.

[0068] The data acquisition module is used to collect the patient's vital signs data and personal information data, and pre-process the collected vital signs data and personal information data. Through high-precision sensors and medical equipment, the accuracy and real-time nature of the data are ensured, and basic data support is provided for subsequent data analysis and nursing decisions. The data acquisition module is started, and sensors and medical equipment are connected to input the patient's personal information data. The patient's vital signs data are collected through sensors and medical equipment. Among them, sensors include blood pressure cuffs, blood oxygen probes, ECG leads and temperature probes, etc. Medical equipment includes monitors and electrocardiographs, etc. Vital signs data include heart rate, blood pressure, blood oxygen saturation and body temperature, etc. The collected vital signs data and personal information data are pre-processed by data cleaning and format conversion. The collected vital signs data and personal information data are cleaned by data cleaning to remove duplicate, erroneous, invalid or abnormal data, and the collected data are converted into a format suitable for database storage and subsequent analysis. The analog signal output by the sensor is converted into a digital signal, and encoded and standardized. The pre-processed vital signs data and personal information data are integrated to form a complete patient data record, ensuring that each record contains the patient's basic information and corresponding vital signs data, and the pre-processed data is stored in the data warehouse and transmitted to the remote server in real time;

[0069] The vital signs analysis module monitors the patient's vital signs data and analyzes any abnormalities, which helps medical staff to take timely intervention measures to prevent the condition from worsening, presets standard thresholds for each vital sign data, and uses the vital signs analysis module to receive the patient's heart rate, blood pressure, blood oxygen saturation, and body temperature vital signs data from a remote server, compares the received vital signs data with their respective standard thresholds, calculates the deviation score of each vital sign data, comprehensively calculates the deviation score, calculates the abnormal sign recognition index, analyzes the abnormalities of the vital signs data, and determines whether there are any abnormalities based on the calculated abnormal sign recognition index;

[0070] Furthermore, the calculation formula of the abnormal sign recognition index is:

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] in, It is the abnormal sign recognition index. is the deviation score of the heart rate, is the deviation score of blood pressure, is the deviation score of blood oxygen saturation, is the deviation score of body temperature, is the weight of the heart rate, is the actual heart rate value, is a normal heart rate value. This is the normal range of heart rate. is the weight of blood pressure, is the actual blood pressure value, is the normal blood pressure value. This is the normal range of blood pressure. is the weight of blood oxygen saturation, is the actual blood oxygen saturation value, is the normal blood oxygen saturation value. This is the normal range of blood oxygen saturation. is the weight of body temperature, is the actual body temperature value, is the normal body temperature. This is the normal range of body temperature. The value range is between 0 and 1. When it is close to 0, it means that the patient's vital signs are within the normal range. When it is close to 1, it means that the patient's vital signs data have multiple deviations from the normal range, requiring immediate attention and intervention;

[0077] The disease warning module analyzes the patient's physiological state based on the patient's vital signs data, conducts a preliminary assessment of the patient's condition, identifies the severity of the condition and potential risks, provides key information for nursing decisions, and helps medical staff take appropriate nursing measures in a timely manner;

[0078] The nursing decision support module is based on the nursing database and combines the patient's condition warning results to generate nursing questions and nursing measures to provide nursing decision suggestions, improve the accuracy and scientificity of nursing decisions, and reduce nursing risks;

[0079] The personalized nursing plan generation module generates personalized nursing plans based on the individual differences of patients and the results of disease warning. It comprehensively considers the age, physiological structure and severity of the disease of the patients, formulates highly adaptable nursing measures, improves nursing effects and promotes patient recovery.

[0080] The nursing plan execution tracking module guides nursing staff to implement nursing plans and track the effectiveness of nursing measures to ensure that nursing measures are correctly implemented and adjust nursing plans in time to adapt to changes in patient conditions.

[0081] The second embodiment is based on the first embodiment. Figure 3 As shown, in the condition warning module, the patient's condition assessment process includes:

[0082] Analyze the physiological state of the patient based on the collected vital signs data of the patient, compare and analyze the vital signs data of the patient, analyze the deviation of the patient's vital signs, which are divided into single deviation, two deviations, and three or more deviations. According to the deviation of the patient's vital signs, identify whether there are abnormal signs, analyze the severity of the abnormal signs, and divide them into low warning level, medium warning level and high warning level based on the deviation status of the patient's vital signs. Among them, single deviation corresponds to low warning level, two deviations correspond to medium warning level, and three or more deviations correspond to high warning level. Combine the abnormal sign recognition index with the divided warning level, match the corresponding warning threshold for each warning level, and automatically issue a warning signal according to the determined warning level to assist medical staff in determining the severity of the patient's condition;

[0083] Furthermore, multiple warning levels correspond to multiple warning thresholds one by one, wherein the warning threshold includes an upper threshold and a lower threshold. The corresponding relationship between the warning level and the warning threshold is as follows:

[0084] Low warning level ;

[0085] Medium warning level ;

[0086] High alert level ;

[0087] in, It is the abnormal sign recognition index. is the upper threshold of the low warning level and the lower threshold of the medium warning level. is the upper threshold of the medium warning level and the lower threshold of the high warning level. , ;

[0088] In the nursing decision support module, the generation process of nursing problems and nursing measures includes:

[0089] Comprehensively collect patients' vital signs, medical history and allergy information data from medical equipment and electronic medical record systems, and conduct in-depth analysis of patients' data to assess their current physiological status, severity of illness and potential risks. The nursing decision support module calls on the professional knowledge and past experience in the nursing database to compare with the patient's assessment results. Based on the cases, guidelines and research results in the nursing database, the module conducts logical reasoning on the assessment results, identifies existing nursing problems, and preliminarily proposes corresponding nursing measures. The system classifies and organizes the nursing problems obtained by reasoning to ensure that each problem is clear and specific. For each nursing problem, it generates specific solutions and operation steps.

[0090] In the personalized care plan generation module, the generation process of the personalized care plan includes:

[0091] Based on the generated nursing questions and nursing measures, combined with the professional knowledge and past experience in the nursing database, develop personalized nursing measures for patients, including medication management, diet conditioning, exercise management and psychological support. According to the patient's disease type, disease severity and allergy history information, assess their medication needs. Combined with the professional knowledge and past experience in the nursing database, develop personalized medication management plans for patients, including drug types, dosages and medication times, clarify the side effects, interactions and contraindications of drugs, ensure medication safety, analyze patients' nutritional intake, eating habits and preferences through nutritional assessment tools, develop personalized diet plans based on patients' nutritional needs and disease characteristics, including food types, intake and cooking methods, and provide patients and their families with diet-related health knowledge. Through exercise ability assessment, analyze patients' physical conditions, exercise habits and endurance levels, and Based on the patient's exercise ability and disease characteristics, develop a personalized exercise plan, including exercise type, intensity and time, provide exercise-related health guidance to patients, analyze the patient's psychological state, emotional changes and coping methods through psychological assessment tools, and provide personalized psychological support services according to the patient's psychological needs, including psychological counseling and psychological counseling, arrange various nursing measures in chronological order and logical relationship, form clear nursing steps, ensure that each step has a clear goal and operation method, list the required materials according to the nursing steps, ensure that the type, quantity and quality of the materials meet the patient's needs and nursing standards, and determine the execution time and frequency of various nursing measures according to the patient's specific situation and nursing needs, ensure that the nursing measures can be completed on time, in quantity and according to quality, integrate the formulated various nursing measures to form a complete nursing plan, and record the nursing plan in the patient's electronic medical record;

[0092] In the nursing plan execution tracking module, the nursing plan execution process includes:

[0093] Nursing staff shall implement various nursing measures step by step according to the chronological sequence and logical relationship of the nursing plan. During the implementation process, they shall strictly abide by the operating specifications to ensure the safety and comfort of the patients. When implementing each nursing measure, they shall record in detail the implementation of the nursing measures, the patients' reactions and changes, regularly monitor the patients' vital signs and changes in their condition, record and evaluate them, pay close attention to the patients' reactions and comfort, promptly discover and deal with abnormal situations, and evaluate the effectiveness of the nursing measures according to the nursing goals and evaluation criteria. They shall conduct a detailed analysis of the evaluation results to find out the advantages and disadvantages of the nursing measures, determine whether the nursing plan needs to be adjusted according to the patients' conditions and needs, and make corresponding adjustments to the nursing plan according to the evaluation results and the patients' needs. The adjustments include modifying the nursing goals, changing the nursing measures, adjusting the execution time and frequency, integrating the implementation of the nursing plan, the evaluation of the nursing effectiveness and the patients' feedback into a report, and recording it in the patients' electronic medical records to ensure the continuity and traceability of the information.

[0094] 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 ENT clinical nursing decision system based on patient vital signs, characterized in that: The nursing decision system includes a nursing database construction module, a data acquisition module, a vital sign analysis module, a disease warning module, a nursing decision support module, a personalized nursing plan generation module and a nursing plan execution tracking module, wherein the modules are connected by electrical signals; The nursing database construction module acquires nursing data and nursing rule specifications, stores the nursing data in a tree data structure, and forms a nursing database; The data collection module is used to collect the patient's vital signs data and personal information data, and pre-process the collected vital signs data and personal information data; The vital signs analysis module monitors the patient's vital signs data and analyzes any abnormalities; The disease warning module analyzes the patient's physiological state based on the patient's vital signs data, makes a preliminary assessment of the patient's disease condition, and identifies the severity of the disease and potential risks; The nursing decision support module generates nursing questions and nursing measures based on the nursing database and in combination with the patient's condition warning results; The personalized nursing plan generation module generates a personalized nursing plan based on individual differences of patients and disease warning results; The nursing plan execution tracking module guides nursing staff to implement the nursing plan and tracks the effects of nursing measures.

2. The ENT clinical nursing decision system based on patient vital signs according to claim 1, characterized in that: In the nursing database construction module, the formation process of the nursing database includes: Identify the nursing problems that the database aims to solve by improving nursing quality, and determine the type and scope of nursing data required, including basic patient information, nursing operation records, and nursing effect evaluation; Design the logical and physical structure of the database according to the characteristics and needs of nursing data, determine the relationship between fields, records, tables and databases, as well as the storage method and access path of data; Collect the nursing data of patients with historical ENT diseases and the data related to nursing rules and regulations, and decompose the collected data into basic database units, namely fields and records. The nursing data of patients with historical ENT diseases come from the hospital information system, nursing records and patient medical records, and the data related to nursing rules and regulations come from literature and operation guidelines in the nursing field. According to the correlation between the data, a weight value is assigned to each data item, and a storage scheme for the tree data structure is designed to define the nodes and establish the parent-child relationship. The processed nursing data is then stored in the database according to the tree structure to form a nursing database.

3. The ENT clinical nursing decision system based on patient vital signs according to claim 2 is characterized by: In the data collection module, the process of collecting vital sign data and personal information data includes: Start the data collection module, connect sensors and medical equipment, input the patient's personal information data, and collect the patient's vital signs data through sensors and medical equipment; Perform pre-processing operations such as data cleaning and format conversion on the collected vital signs data and personal information data, and integrate the pre-processed vital signs data and personal information data to form a complete patient data record; The preprocessed data is stored in the data warehouse and transmitted to the remote server in real time.

4. The ENT clinical nursing decision system based on patient vital signs according to claim 3 is characterized by: In the vital signs analysis module, the abnormal situation analysis process includes: Preset standard thresholds for each vital sign data, and use the vital sign analysis module to receive the patient's vital sign data of heart rate, blood pressure, blood oxygen saturation and body temperature from a remote server; comparing the received vital sign data with their respective standard thresholds and calculating a deviation score for each vital sign data; The deviation scores obtained are comprehensively calculated to calculate the abnormal sign recognition index, analyze the abnormalities of the vital sign data, and identify the abnormal sign index based on the abnormal sign; Analyze the calculated abnormal sign identification index to determine whether there is an abnormal situation.

5. The ENT clinical nursing decision system based on patient vital signs according to claim 4 is characterized by: The calculation formula of the abnormal sign identification index is: ； ； ； ； ； in, It is the abnormal sign recognition index. is the deviation score of the heart rate, is the deviation score of blood pressure, is the deviation score of blood oxygen saturation, is the deviation score of body temperature, is the weight of the heart rate, is the actual heart rate value, is a normal heart rate value. This is the normal range of heart rate. is the weight of blood pressure, is the actual blood pressure value, is the normal blood pressure value. This is the normal range of blood pressure. is the weight of blood oxygen saturation, is the actual blood oxygen saturation value, is the normal blood oxygen saturation value. This is the normal range of blood oxygen saturation. is the weight of body temperature, is the actual body temperature value, is the normal body temperature. This is the normal range of body temperature.

6. The ENT clinical nursing decision system based on patient vital signs according to claim 5, characterized in that: In the condition warning module, the patient's condition assessment process includes: Analyze the patient's physiological state based on the collected patient's vital signs data, compare and analyze the patient's vital signs data, and analyze the deviation of the patient's vital signs, which are divided into single deviation, two deviations, and three or more deviations; According to the deviation of the patient's vital signs, identify whether there are abnormal signs, analyze the severity of the abnormal signs, and divide them into low warning level, medium warning level and high warning level based on the deviation status of the patient's vital signs. Among them, a single deviation corresponds to a low warning level, two deviations correspond to a medium warning level, and three or more deviations correspond to a high warning level; By combining the abnormal sign recognition index with the divided warning levels, the corresponding warning threshold is matched for each warning level, and according to the determined warning level, a warning signal is automatically issued to assist medical staff in determining the severity of the patient's condition.

7. The ENT clinical nursing decision system based on patient vital signs according to claim 6, characterized in that: The plurality of warning levels correspond to the plurality of warning thresholds one by one, wherein the warning threshold includes an upper threshold and a lower threshold. The corresponding relationship between the warning level and the warning threshold is as follows: Low warning level ; Medium warning level ; High alert level ; in, is the abnormal sign recognition index, which is the upper threshold of the low warning level and the lower threshold of the medium warning level. is the upper threshold of the medium warning level and the lower threshold of the high warning level. , .

8. The ENT clinical nursing decision system based on patient vital signs according to claim 7, characterized in that: In the nursing decision support module, the generation process of nursing questions and nursing measures includes: Comprehensively collect patients’ vital signs, medical history, and allergy information data from medical devices and electronic medical record systems, and conduct in-depth analysis of patients’ data to assess their current physiological status, severity of illness, and potential risks; The nursing decision support module calls on the professional knowledge and past experience in the nursing database, compares them with the patient's assessment results, and logically infers the assessment results based on the cases, guidelines and research results in the nursing database, identifies existing nursing problems, and preliminarily proposes corresponding nursing measures; The system classifies and organizes the nursing problems obtained by reasoning, and generates specific solutions and operation steps for each nursing problem.

9. The ENT clinical nursing decision system based on patient vital signs according to claim 8, characterized in that: In the personalized nursing plan generation module, the generation process of the personalized nursing plan includes: Based on the generated nursing problems and nursing measures, combined with the professional knowledge and past experience in the nursing database, develop personalized nursing measures for patients, including medication management, diet adjustment, exercise management and psychological support; Assess the patient's medication needs based on the type of disease, severity of the disease, and allergy history. Combine the professional knowledge and past experience in the nursing database to develop a personalized medication management plan for the patient, including the type of medication, dosage, and medication schedule, and identify the side effects, interactions, and contraindications of the medication; Through nutritional assessment tools, we analyze the patient's nutritional intake, eating habits and preferences, and develop a personalized diet plan based on the patient's nutritional needs and disease characteristics, including food types, intake and cooking methods; Through exercise capacity assessment, we analyze the patient's physical condition, exercise habits and endurance level, and develop a personalized exercise plan based on the patient's exercise capacity and disease characteristics, including exercise type, intensity and time; Analyze the patient's mental state, emotional changes and coping style through psychological assessment tools, and provide personalized psychological support services, including psychological counseling and psychological counseling, based on the patient's psychological needs; Arrange various nursing measures in chronological order and logical relationship to form clear nursing steps. According to the nursing steps, list the required materials, and determine the execution time and frequency of various nursing measures according to the patient's specific situation and nursing needs; Integrate the various nursing measures developed into a complete nursing plan, and record the nursing plan in the patient's electronic medical record.

10. The ENT clinical nursing decision system based on patient vital signs according to claim 9, characterized in that: In the nursing plan execution tracking module, the nursing plan execution process includes: Nursing staff shall implement various nursing measures step by step according to the time sequence and logical relationship of the nursing plan, and record the implementation of each nursing measure, the patient's response and changes in detail when implementing each nursing measure; Regularly monitor the patient's vital signs and condition changes, record and evaluate them, pay close attention to the patient's response and comfort, identify and handle abnormal conditions, and evaluate the effectiveness of nursing measures based on nursing goals and evaluation criteria; Conduct detailed analysis of the evaluation results to identify the strengths and weaknesses of the nursing measures, determine whether the nursing plan needs to be adjusted based on the patient's condition and needs, and make corresponding adjustments to the nursing plan based on the evaluation results and the patient's needs. The adjustments include modifying the nursing goals, changing the nursing measures, and adjusting the execution time and frequency; Integrate the implementation of the nursing plan, the evaluation of nursing effectiveness and the patient's feedback into a report and record it in the patient's electronic medical record.

Images