Electronic medical record recording method and system

Abstract

The invention relates to a recording method and system of an electronic medical record, and aims to comprehensively and systematically collect health information of a patient through diversified input terminals, improve information input efficiency, ensure information integrity and promote team cooperation. The system comprises a medical professional terminal, a patient direct related terminal and other patient related terminals, supports information input in various forms of pictures, characters, videos, audios and the like, and covers various input devices such as portable devices, professional examination instruments and the like. And the information storage module ensures accurate homing of the data and supports cross-mechanism data integration and sharing. The system also has the functions of electronic medical record automatic generation, treatment tracking, symptom and sign extraction, intelligent analysis and early warning and the like, provides efficient and accurate information support for medical services, optimizes medical resource configuration, and enhances medical experience of patients. The method is suitable for modern medical management, and particularly has remarkable advantages in the aspect of improving the intelligence and integration level of an electronic medical record system.

Description

TECHNICAL FIELD

[0001] The present application relates to a recording method of electronic medical records, aiming to comprehensively and systematically collect and record patients' health information through diversified input terminals, improve information input efficiency, ensure information integrity, and promote team collaboration. BACKGROUND

[0002] In the field of medical informatization, electronic medical record systems, as an important tool for modern medical management, have been widely used. However, traditional medical record recording methods often have problems such as incomplete information input, scattered data storage, and low query efficiency, which cannot meet the efficient and accurate needs of modern medical information management. With the continuous expansion of medical business and the development of information technology, electronic medical record systems have gradually replaced paper medical records and become the mainstream of medical information management.

[0003] However, existing electronic medical record systems still face many challenges in actual application. First, the input terminal is relatively single, mainly relying on manual input by medical professionals, lacking the participation of patients and their families, and other relevant personnel, resulting in limited information sources and possible omissions. Second, the information format is not unified, and the data format between different medical institutions and different systems is different, making it difficult to integrate and share information. In addition, the lack of intelligent recognition capability is also a major pain point of existing systems, and the recognition and processing of unstructured data (such as text description, pictures, videos, etc.) are still insufficient, affecting the accuracy and integrity of the information.

[0004] More importantly, the sharing and integration of medical records across medical institutions still face technical obstacles. When patients visit different medical institutions, their health records are often stored in the internal systems of each institution, making it difficult for doctors to access the complete health records of patients during treatment, which undoubtedly increases the difficulty of treatment decision-making and reduces the efficiency and quality of medical services.

[0005] Therefore, in view of the many problems existing in the current electronic medical record system, the development of an electronic medical record recording method that can comprehensively and systematically collect patients' health information, support diversified input terminals and intelligent recognition, realize cross-institutional data integration and sharing, and provide intelligent analysis and early warning functions, is of great significance to improve the level of medical services, optimize the allocation of medical resources, and enhance the patient experience. SUMMARY

[0006] A recording method of electronic medical records, characterized in that it comprises the following steps:

[0007] Step 1: Information input

[0008] Through diversified input terminals, comprehensive and systematic collection and recording of patients' health information. The input terminals are specifically divided into the following three categories:

[0009] Medical Professional End: Composed of physicians, nurses, medical technicians, and medical authorized personnel, specifically including:

[0010] Physicians: Covering 120 emergency personnel, emergency department physicians, outpatient physicians, inpatient physicians, and other types of physicians who directly contact patients;

[0011] Nurses: Including 120 emergency nurses, emergency department nurses, outpatient nurses, inpatient nurses, and other types of nurses who directly contact patients;

[0012] Medical Technicians: Involving medical laboratory personnel, medical imaging personnel, pathological diagnosis personnel, and other personnel in the field of professional technology;

[0013] Medical Authorized Personnel: Interns, postgraduate physicians, intern nurses, medical assistants, and other medical-related personnel who are formally authorized to enter health information;

[0014] Patient Directly Related End: Composed of patients, patient family members, and patient authorized personnel, among which:

[0015] Patients: Have the right to directly participate in the entry and update of health information;

[0016] Patient Family Members and Patient Authorized Personnel: After obtaining the explicit authorization of the patient, they can enter or verify health information on behalf of the patient;

[0017] Other Related End of Patients: Including traffic police, firefighters, neighbors, patient companions, and passers-by, etc. These people may provide valuable information related to the patient's health information in specific situations;

[0018] The specific situations include:

[0019] Traffic Accidents or Emergencies: When patients encounter traffic accidents or other emergencies, traffic police or firefighters may be the first to arrive at the scene. They can provide information about the specific circumstances of the accident, the patient's preliminary injury description, and on-site first aid measures, etc. These information is crucial for subsequent medical treatment and medical records;

[0020] Sudden Illness or Accidents: When patients suffer from sudden illness (such as heart attack, stroke, etc.) or encounter other accidents (such as falling, drowning, etc.), neighbors, companions, or passers-by at the scene may have witnessed the event and provided timely assistance. They can provide detailed information about the patient's condition before the onset of the disease, the patient's performance at the time of the onset, and the first aid measures taken, which helps doctors more accurately judge the condition and develop treatment plans;

[0021] Long-term care or rehabilitation process: For patients who need long-term care or rehabilitation, their family members, caregivers or community workers may observe changes in the patient's health status such as diet, sleep, activity ability, etc. during daily care. These information is important for evaluating the patient's rehabilitation progress and adjusting the treatment plan;

[0022] Workplace accident: If the patient is injured in an accident at work, colleagues, superiors or safety management personnel may provide detailed information about the cause, process and patient's injury of the accident. These information helps to determine the work injury recognition and compensation, and also provides important clues for medical treatment;

[0023] Social activities or public places: In some social activities or public places, if the patient has health problems (such as syncope, allergic reaction, etc.), people around may provide timely help and record the relevant circumstances. These information is very helpful for doctors to understand the patient's onset environment and inducement.

[0024] Step two: information storage

[0025] The entered patient health information is accurately saved to the corresponding module or location of the electronic medical record system, ensuring the integrity, accuracy and traceability of the information.

[0026] Further, the information entry method is divided into two modes: regular entry and designated entry;

[0027] I. The regular entry mode includes automatic recognition entry and manual selection entry:

[0028] 1) The automatic recognition entry:

[0029] Step 1: Information submission: the entry end (including but not limited to medical professional end, patient directly related end, patient other related end) is responsible for entering the patient's health information;

[0030] The health information specifically includes but is not limited to:

[0031] Patient basic information: such as name, gender, age, contact information, ID number, medical insurance number, etc. for patient identification and contact basic information;

[0032] Medical history record: including current medical history, past medical history, family medical history, allergy history, operation history, hospitalization history, etc. for evaluating the patient's health status and potential risks;

[0033] The current medical history includes: onset time and condition: the specific time of the first symptom; onset mode (acute, chronic, subacute); symptoms and severity at onset;

[0034] Main symptoms and their characteristics: nature, location, duration, frequency of onset of main symptoms; factors that alleviate or exacerbate symptoms; accompanying symptoms: other symptoms that occur simultaneously or subsequently with the main symptoms; these symptoms may reveal the nature, location, or complications of the disease; evolution and progression of the disease: changes in the patient's condition from the onset to the present; aggravation, alleviation, disappearance of symptoms, or appearance of new symptoms; time points of these changes and possible triggers; etiology and triggers: etiology: the underlying cause, presumed or confirmed, that leads to the occurrence of the disease. This can include genetic factors, infections, environmental factors, lifestyle factors, etc.; triggers: factors that trigger or exacerbate symptoms of the disease. For example, certain foods, drugs, stress events, climate changes, etc. can act as triggers;

[0035] Diagnosis and treatment history: diagnosis and treatment measures received by the patient since the onset of the disease;

[0036] Visits to other medical institutions, prescribed drugs, treatment surgeries, etc.; the effectiveness of these treatments, and whether there are adverse reactions or complications;

[0037] General condition: the patient's current mental state, appetite, sleep, bowel and bladder conditions; weight changes and other systemic symptoms related to the disease;

[0038] Physical examination information: vital sign data such as height, weight, blood pressure, heart rate, body temperature, and abnormal findings recorded by the doctor during physical examination;

[0039] Test results: including laboratory tests (such as blood tests, urine tests, biochemical tests, etc.) and imaging tests (such as X-rays, CT, MRI, etc.) results, which usually contain numerical data and image materials;

[0040] Diagnosis information: the preliminary diagnosis or final diagnosis made by the doctor based on the patient's medical history, physical examination, and test results;

[0041] Treatment plan: the treatment plan developed by the doctor for the patient, including drug treatment, physical therapy, surgical treatment, etc., as well as treatment precautions and follow-up plans during treatment;

[0042] Other relevant information: such as the patient's lifestyle, eating habits, occupational exposure history, vaccination history, etc., which may have important implications for diagnosis and treatment.

[0043] Step 2: Intelligent recognition: the system uses a pre-established electronic medical record knowledge base to intelligently recognize the health information content submitted by the input end;

[0044] The electronic medical record knowledge base content includes: electronic medical record basic framework: defines the overall structure and module division of electronic medical record, such as patient basic information, medical history record, physical examination, examination result, diagnosis information, treatment plan, etc. Each module has detailed data field and coding rule to ensure standardized storage of information.

[0045] Disease diagnosis knowledge: it includes the names of common diseases at home and abroad, diagnostic criteria and coding (such as ICD-10, ICD-11, etc.); It contains the diagnosis basis of clinical symptoms, signs, laboratory examination indexes, imaging examination characteristics, etc. of diseases; Provide differential diagnosis information to help doctors distinguish similar diseases.

[0046] Treatment and examination items:

[0047] Listed are common treatment methods and surgical operations, including indications, contraindications, operation steps, expected effects, etc. Various examination items such as laboratory examination, imaging examination, special examination, etc. and their normal values and abnormal interpretation are included. Provide coding rules for treatment items and examination items to facilitate data management and statistical analysis.

[0048] Drug information: contains information such as drug name, dosage form, usage and dosage, indications, contraindications, adverse reactions, drug interactions, etc. Provide drug classification and coding rules to facilitate doctors to quickly select when prescribing.

[0049] Patient information template: a standardized patient information input template is designed, including basic information (such as name, gender, age, contact information, etc.), family history, past medical history, allergy history, etc. The template contains data verification rules to ensure the accuracy and completeness of the input information.

[0050] Medical terminology and abbreviation library: it includes the explanation and definition of medical terms, abbreviations and symbols commonly used in medical field. Provide Chinese and English contrast of terms to facilitate international exchange and cooperation.

[0051] Clinical guidelines and consensus: it contains clinical guidelines, consensus documents and expert recommendations published by authoritative institutions at home and abroad. The diagnostic criteria, treatment plans, examination items and other information involved in the guidelines and consensus will be integrated into the knowledge base to provide scientific basis for doctors.

[0052] Data quality and privacy protection rules: define the quality standards and privacy protection requirements for data entry, storage, use and sharing. Ensure the accuracy, integrity, availability and security of electronic medical record data.

[0053] The following are the specific steps and technical points of implementing intelligent recognition function:

[0054] 1. Construction of electronic medical record knowledge base

[0055] Knowledge base content: Same as the electronic medical record knowledge base content mentioned above;

[0056] Data encoding and standardization: Encode all information to ensure its uniqueness and standardization; set data fields and formats to ensure consistency of information;

[0057] 2. Development of intelligent recognition algorithm

[0058] Natural language processing (NLP): Use NLP technology to analyze health information submitted by the input end and extract key information points; NLP algorithms need to be trained to understand medical terminology, abbreviations and common expressions;

[0059] Pattern matching and rule engine: Use the information in the knowledge base to build pattern matching rules; when new information is submitted, the rule engine matches it with the patterns in the knowledge base;

[0060] Machine learning algorithm: Apply machine learning algorithms such as classification, clustering, regression, etc. to improve the accuracy and generalization ability of recognition; continuously optimize algorithm models through training data;

[0061] 3. Implementation process of intelligent recognition

[0062] Information submission: The input end submits health information, which can be in the form of text, numerical value or image, etc.;

[0063] Preprocessing: Preprocess the submitted information, such as denoising, word segmentation, standardization, etc.;

[0064] Intelligent recognition: NLP algorithm analyzes information and extracts key information points; rule engine matches the extracted information with the patterns in the knowledge base; machine learning algorithm verifies and optimizes the matching results;

[0065] Result output: The system automatically matches health information to the corresponding module or location of the electronic medical record according to the recognition results; for information that cannot be recognized, the system saves it to the "unrecognized data unit" and triggers a prompt for manual review;

[0066] 4. System optimization and iteration

[0067] Manual review and feedback: Manually review the unrecognized data to ensure the accuracy and completeness of the information; the review results are used to optimize the knowledge base and algorithm model;

[0068] Continuous learning and updating: The system regularly updates the knowledge base, including new diseases, treatment methods and examination items, etc.; through continuous learning, the intelligent recognition algorithm is continuously optimized to improve the accuracy and efficiency of recognition;

[0069] Step 3: Data saving and review:

[0070] 3.1 Automatic saving: successfully identified health data will be automatically saved to the corresponding module or location, ensuring the accuracy of the information and the correctness of the location;

[0071] 3.2 Unidentified data processing: for health data that cannot be identified, the system will temporarily save it to the "unidentified data unit" and automatically trigger a prompt to inform the relevant personnel to conduct manual review and identification. After manual identification, these data will be correctly classified and saved, and at the same time, the knowledge base will be further improved to better handle similar information in the future;

[0072] 2) The manual selection entry:

[0073] Step 1: Information module selection:

[0074] The entry end user carefully selects the module corresponding to the health information to be entered from the pre-set, structured document module according to actual needs. These pre-set modules cover patient basic information, medical history records, physical examination, examination results, diagnosis information, treatment plans, and other aspects, ensuring the comprehensiveness and systematicness of the information;

[0075] Step 2: Information entry and verification:

[0076] After selecting the module, the entry end user needs to enter the patient's health information one by one according to the entry requirements and format of the module;

[0077] Step 3: Information upload and automatic distribution:

[0078] After completing the information entry, the entry end user uploads the recorded information to the database of the electronic medical record system. After receiving the uploaded information, the system will automatically distribute it to the corresponding module or location according to the type and attribute of the information. This process ensures the orderly storage and convenient retrieval of information;

[0079] Two, the specified entry mode: including medical end specified patient direct related end entry and system specified entry end entry:

[0080] 1) The medical end specified patient direct related end entry:

[0081] Step 1: The medical end (physicians, nurses, etc.) selects the health information content that needs to be obtained from the patient direct related end (patients, patient family members and authorized personnel) from the electronic medical record system according to the needs of diagnosis and treatment;

[0082] Step 2: The system sends a push notification to the patient direct related end, clearly informing the specific health information content that needs to be entered;

[0083] Step 3: The patient directly related end enters the corresponding health information according to the push content;

[0084] Step 4: The medical end real-time views the health information entered by the patient directly related end, confirms that it is correct, and saves it to the electronic medical record system to ensure the integrity and accuracy of the information;

[0085] 2) The system specifies the entry end to enter:

[0086] Step 1: According to the system preset rules or trigger conditions, the system automatically identifies the electronic medical record to be completed;

[0087] Step 2: The system further analyzes the electronic medical record to be completed and the electronic medical record completed in the current period to determine the required health information;

[0088] Step 3: The system intelligently judges the health information that can be provided by each entry end (medical professional end, patient directly related end, and patient other related end), and sends these required health information to the corresponding entry end;

[0089] Step 4: The entry end enters the required health information according to the system prompt, and the system automatically stores it to the electronic medical record system to ensure the timeliness and accuracy of the information.

[0090] Further, the entry form of the health information includes picture form, text form, video form, audio / voice form:

[0091] The picture form: used to record the skin and soft tissue disease state of the patient, including but not limited to eczema, dermatitis, urticaria, and other skin diseases, bruises, contusions, crush injuries, burns, frostbite, and other soft tissue injuries, as well as fractures, joint dislocations, muscle strains, and other musculoskeletal diseases. In addition, the picture form is also suitable for recording the contrast before and after surgery, as well as the color and nature of physiological samples such as vomit, stool, and sputum. These pictures should have high definition to facilitate doctors to make accurate disease assessment;

[0092] The text form: as the basis of medical record, the text form is used to record the patient's disease, medical history, diagnosis results, treatment plan, medical advice, follow-up records, and other information in detail. The text record should be accurate, clear, and follow the medical terminology standard to ensure the accuracy and readability of the information;

[0093] The video form: for recording the dynamic condition of the patient, including but not limited to respiratory conditions, symptoms of seizures, symptoms of Parkinson's disease, hemiplegia, aphasia, sensory disturbance and other symptoms of patients with cerebrovascular disease, and surgical operation process, wound recovery, etc. The video recording should contain time stamp, patient identification and other key information to facilitate subsequent retrieval and analysis. Video recording provides an intuitive observation method for doctors, which helps to develop and adjust treatment plan.

[0094] Audio / speech form: for recording the abnormal sound of the patient's cough, breathing sound, heart sound, etc. and the whole process of doctor-patient communication. Audio / speech recording provides an important auxiliary means for doctors to diagnose respiratory system diseases, cardiovascular system diseases, etc.

[0095] Further, the input device of the health information includes portable devices, computers, professional examination, testing instruments and equipment:

[0096] The portable device: including but not limited to smart phones, tablets (pad) and other mobile devices with photo, video and audio recording functions. These devices should support high-definition photo, video and audio recording functions, and have enough storage space. At the same time, professional medical applications or software should be installed to facilitate the uploading of collected health information to the electronic medical record system. Portable devices are convenient for patients and medical staff to record information at any time and anywhere, improving the flexibility and convenience of information input;

[0097] The computer: as a fixed workstation, the computer should be installed with electronic medical record management software, supporting text editing, picture processing, video playing, audio analysis and other complex tasks. The information input on the computer should be more detailed and comprehensive to facilitate the in-depth analysis and diagnosis of the doctor;

[0098] The professional examination, testing instruments and equipment: including but not limited to electronic stethoscope, electronic thermometer, electronic pulse meter, electronic sphygmomanometer, respiratory detector, pulse oximeter and other medical professional equipment. These devices should support Bluetooth, Wi-Fi and other wireless transmission methods to upload the collected physiological data to the electronic medical record system. At the same time, these devices should have accuracy and reliability to ensure the accuracy and reliability of the data.

[0099] In addition, patients can also purchase and use these devices, and then upload the collected data to the electronic medical record system through portable devices or computers.

[0100] The specific uploading method of the professional examination, testing instruments and equipment includes but is not limited to the following methods:

[0101] 1. Wireless direct upload

[0102] Bluetooth transmission: Many modern medical professional devices support Bluetooth functionality. By establishing a Bluetooth connection with a portable device such as a smartphone or tablet, the device can directly send the collected physiological data to the portable device, and then the user can upload the data to the electronic medical record system through the medical application or software installed on the portable device;

[0103] Wi-Fi transmission: Some high-end medical professional devices support Wi-Fi functionality and can directly connect to the Wi-Fi network at home or in medical institutions. The data collected by the device can be directly uploaded to the electronic medical record system through Wi-Fi, or first uploaded to an intermediate server, and then the server imports the data into the electronic medical record system;

[0104] 2. Data interface upload

[0105] USB interface: Many medical professional devices are equipped with USB interfaces, allowing users to connect the device to a computer through a USB cable. Once connected, the data in the device can be exported to the computer through specific software or drivers, and then uploaded to the electronic medical record management software on the computer side;

[0106] 3. Special software / application upload

[0107] Device companion software: Many medical professional devices are equipped with special software or applications for device configuration, data viewing and uploading. Users can upload the data in the device to the electronic medical record system through these software or applications, which usually have direct interfaces or data exchange protocols with the electronic medical record system;

[0108] Third-party applications: Some third-party applications may support data import and upload functions for multiple medical professional devices. Users can import the data in the device into these third-party applications, and then upload the data to the electronic medical record system through the application. This method needs to ensure the data compatibility and security between the third-party application and the electronic medical record system;

[0109] 4. Cloud service upload

[0110] Device cloud service: Some high-end medical professional devices may provide cloud service functions, allowing users to upload the data in the device to the cloud service of the device manufacturer. Users can access the cloud service through a portable device or computer, and then export the data from the cloud service and upload it to the electronic medical record system. Third-party cloud service: Users can also choose to use third-party cloud services to store and upload data in the device. This method requires users to ensure the security of the cloud service and the protection of data privacy.

[0111] Further, the information storage, the method comprises the following steps:

[0112] Step 1: Document structure standardization and information entry system construction

[0113] Document structure design: Following the application level grading evaluation standard of electronic medical record system, a modular document structure containing patient's whole cycle health information is designed. Especially for physical examination information such as visual examination, palpation, percussion, auscultation, etc., detailed multimedia storage modules are designed to support the storage of multiple data formats such as pictures, videos, and audio;

[0114] The document structure design

[0115] Modular design

[0116] Patient basic information module: Contains key information such as name, gender, age, contact information, ID number, medical insurance number, etc., used for patient identification and contact.

[0117] Medical history module:

[0118] Present illness sub-module: Records information such as onset time, onset mode, main symptoms, accompanying symptoms, disease evolution, cause and inducement, diagnosis and treatment history, etc.

[0119] Past medical history sub-module: Records the patient's past disease history, operation history, hospitalization history, etc.

[0120] Family medical history sub-module: Records the incidence of related diseases in the patient's family.

[0121] Allergy history sub-module: Records the patient's allergic reactions to specific drugs, food or substances.

[0122] Physical examination module:

[0123] Vital signs sub-module: Records basic information such as height, weight, blood pressure, heart rate, body temperature, etc.

[0124] Detailed examination sub-module: Design multimedia storage area, support multiple formats such as pictures, videos, audio, etc., for recording visual examination, palpation, percussion, auscultation, etc. Detailed examination results.

[0125] Laboratory examination result module:

[0126] Laboratory sub-module: Integrates the results of blood routine, urine routine, biochemical examination, etc. Laboratory examination. At the same time, support the entry of multimedia information, such as scanned copies or pictures of test reports.

[0127] Examination sub-module: Integrates the results of X-ray, CT, MRI and other imaging examinations and other special examinations, providing storage functions of numerical data and image data. This sub-module also supports the entry of multimedia information such as scanned copies, pictures or videos of examination reports. Through detailed fields and data structures, the accuracy and traceability of examination results are ensured.

[0128] Diagnosis Information Module: Records the preliminary diagnosis or final diagnosis made by the doctor based on the medical history, physical examination and test results, including diagnosis name, diagnosis code (such as ICD-10, ICD-11, etc.) and other information.

[0129] Treatment Plan Module: Detailed records of treatment plan, including drug treatment (drug name, dosage, medication time, etc.), physical therapy, surgical treatment, etc., as well as precautions during treatment, follow-up plan and expected effect. At the same time, support the entry of multimedia information, such as scanned copies or pictures of treatment plan.

[0130] Other Related Information Module: Records the patient's lifestyle, eating habits, occupational exposure history, vaccination history and other information that may have an important impact on diagnosis and treatment. These information helps doctors have a more comprehensive understanding of the patient's condition, so as to develop a more appropriate treatment plan.

[0131] Unique Identifier Assignment: Assign a unique identifier to each category of health information, and accurately associate it to the corresponding multimedia storage area according to the information category, to ensure the orderliness and traceability of the data;

[0132] Integration of Diverse Entry Ends: Integrate medical professional ends (covering physicians, nurses, medical technicians and authorized medical personnel), patient directly related ends (patients, family members and authorized representatives) and other related ends of patients (such as traffic police, firefighters, witnesses, etc.), to realize the all-round and multi-channel collection of health information;

[0133] Step 2: Information Storage and Multimedia Data Association

[0134] Health Information Storage: Accurately map the entered patient health information to the predetermined modules of electronic medical record, to ensure the accurate placement of information;

[0135] Physical Examination Data Association: Physical examination information needs to be accurately linked to the corresponding multimedia storage table according to its category (visual examination, palpation, percussion, auscultation, pulse diagnosis, etc.), to strengthen the completeness and historical traceability of data;

[0136] In the recording method of electronic medical record, the association of physical examination data is a key link, which ensures the completeness, accuracy and traceability of physical examination information. The following is a detailed description of the specific methods and steps of physical examination data association:

[0137] I. Classification of Physical Examination Data

[0138] Physical examination information needs to be classified in detail according to its category, such as visual examination, palpation, percussion, auscultation, pulse diagnosis, etc. These classifications are helpful for subsequent information entry, storage and retrieval;

[0139] II. Unique Identifier Assignment

[0140] A unique identifier is assigned to each type of physical examination information, which is used to uniquely identify each physical examination record in the system. These identifiers should be able to accurately associate with the corresponding multimedia storage area, so that the relevant information can be quickly found and accessed when needed;

[0141] III. Multimedia Storage Table Design

[0142] A special multimedia storage table is designed to store multimedia information in physical examination, such as pictures, videos, audio, etc. These storage tables not only save the original data, but also contain text summaries for subsequent clinical analysis and scientific research applications. The text summary can be a brief description of the multimedia information or the extraction of key information;

[0143] IV. Data Association and Linking

[0144] Information entry: During the physical examination process, medical personnel use standardized entry interface and process to enter information into the system. These information include text description, multimedia data, etc;

[0145] Automatic association: The system automatically associates the entered physical examination information to the corresponding multimedia storage table according to the unique identifier and the type of physical examination information. For example, the information of visual examination will be associated to the multimedia storage table of visual examination, and the information of auscultation will be associated to the multimedia storage table of auscultation;

[0146] Manual adjustment: On the basis of automatic association, medical personnel can also make manual adjustment according to needs to ensure the accuracy and completeness of information.

[0147] Multimedia and text data coexist: Multimedia storage table not only saves the original data (pictures, videos, audio), but also contains text summary of multimedia information, which complement each other, and facilitate subsequent clinical analysis and scientific research applications;

[0148] The specific methods and steps of the text summary of multimedia information are as follows:

[0149] I. Definition and purpose of text summary

[0150] Text summary is a brief and accurate overview of the content of multimedia information (such as pictures, videos, audio). Its main purpose is to help users quickly understand the content without directly viewing the multimedia file;

[0151] II. Generation method of text summary

[0152] Manual generation:

[0153] Medical staff can manually write a text summary when entering multimedia information. This method requires medical staff to have certain writing skills and accurate understanding of multimedia content;

[0154] Automatic generation:

[0155] Using natural language processing (NLP) technology, algorithms can be developed to automatically analyze multimedia content and generate text summaries. For example, for pictures, key elements and scenes in the image can be identified; for videos and audios, key dialogues or sound features can be extracted and converted into text form; three, the inclusion method of text summary

[0156] Add a summary field in the multimedia storage table:

[0157] When designing a multimedia storage table, a field specifically for storing text summaries can be added. Whenever new multimedia information is entered, the field needs to be filled in at the same time;

[0158] Associated storage with multimedia information:

[0159] Ensure that the text summary is stored in association with the corresponding multimedia information in the system. In this way, when viewing multimedia information, its corresponding text summary can be easily found;

[0160] Provide summary viewing function:

[0161] On the user interface of the electronic medical record system, provide a text summary viewing function. Users can quickly view the text summary of multimedia information by clicking or hovering, etc;

[0162] Step 3: Device and data synchronization and user permission management

[0163] Device data automatic integration: support real-time or scheduled uploading of data provided by medical institutions and self-provided medical devices (electronic stethoscope, thermometer, pulse meter, sphygmomanometer, respiratory detector, blood glucose meter, etc.), realize seamless connection of health monitoring data;

[0164] Multi-role collaborative access: medical professionals, patients and other related parties can access the same electronic medical record system, but access permissions and scope strictly follow the user role allocation principle to ensure information security and privacy protection;

[0165] Data entry and operation record: allow different users to collaboratively enter data in the same module, while the system automatically records the history track of each operation to ensure data accuracy and responsibility traceability.

[0166] Further, an electronic medical record automatic generation method, characterized by comprising the following steps:

[0167] Step 1: Selection and creation of electronic medical record

[0168] 1.1 Manual selection and creation: Medical professionals manually select and create corresponding electronic medical record templates according to the specific medical needs of patients and the writing specifications of electronic medical records management;

[0169] 1.2 Automatic identification and creation: The system automatically identifies the required electronic medical records according to the system's preset rules or trigger conditions, and the system automatically creates corresponding electronic medical record templates;

[0170] 1.3 Automatic identification and manual selection and creation: The system automatically identifies the required electronic medical records according to the system's preset rules or trigger conditions, and medical professionals select and create electronic medical record templates;

[0171] Step 2: Acquisition of health information and data filling;

[0172] 2.1 Determination of health information needs: The system automatically determines the health information required to be collected according to the type and writing specifications of the created electronic medical record template, including but not limited to patient basic information, symptoms, physical examination, diagnosis information, treatment plan, examination, examination results, etc.;

[0173] A method for determining health information needs in an electronic medical record automatic generation method, comprising the following steps:

[0174] Step A: Electronic medical record template type identification: The system first identifies and determines the type of the created electronic medical record template;

[0175] Step B: Writing specification acquisition: According to the type of the electronic medical record template, the system acquires the corresponding electronic medical record writing specification;

[0176] Step C: Health information needs determination: The system automatically analyzes and determines the health information required to be collected according to the acquired writing specification, including but not limited to patient basic information, symptoms, physical examination, diagnosis information, treatment plan, examination, examination results, etc.;

[0177] Step D: Information needs list generation: The system generates a health information needs list, which details all the health information items required to be collected, for subsequent data collection and filling process.

[0178] 2.2 Multi-channel health information collection: Medical professionals, patients and other related parties collect health information and mark the data source;

[0179] 2.3 Integration and verification of data: the system will integrate the data collected from different channels and strictly verify it according to the electronic medical record writing specification to ensure the completeness, accuracy and consistency of the data; for missing, incorrect or inconsistent data, the system will automatically prompt the relevant entry end to supplement, correct or verify;

[0180] For missing, incorrect or inconsistent data, the system will automatically prompt the relevant entry end to supplement, correct or verify the specific method as follows:

[0181] 2.3.1 Data completeness check:

[0182] The system first checks whether the data collected from various channels is complete. For example, for patient basic information, the system will check whether it contains key fields such as name, gender, age, contact information, etc.; for present illness history, the system will check whether it contains onset time and cause, main symptom description, accompanying symptom record, disease development and evolution, diagnosis and treatment history, general condition, etc.; for diagnosis information, the system will check whether it contains diagnosis name, diagnosis date, etc.;

[0183] If the data is missing, the system will immediately generate a prompt message indicating the missing data item and send it to the corresponding entry end (such as the medical professional end or the patient end);

[0184] 2.3.2 Data accuracy verification:

[0185] The system will use built-in verification rules or algorithms to verify the accuracy of the collected data. For example, the system will check whether the patient's age is reasonable (such as whether it is a positive number and whether it is within a reasonable range), whether the diagnosis name conforms to the medical terminology specification, etc.;

[0186] If the data is found to be incorrect, the system will generate an error prompt message detailing the incorrect data item and its problem, and send it to the corresponding entry end for correction;

[0187] 2.3.3 Data consistency check:

[0188] The system will check the consistency of the same data collected from multiple channels. For example, for a patient's name and age, the system may collect them from the medical professional end and the patient end respectively, at which time the system will compare them to ensure consistency between the two channels; if the data is found to be inconsistent, the system will generate an inconsistency prompt message indicating which data items are inconsistent and send it to all relevant entry ends for verification and unification; Prompt information sending and feedback mechanism: the system will send prompt information to the corresponding entry end through various means such as SMS and system notification; the entry end needs to supplement, correct or verify the data according to the prompt content and resubmit the updated data to the system;

[0189] The system will recheck the updated data to ensure that the data meets the requirements of integrity, accuracy and consistency.

[0190] Step 3: Generation, review and preservation of electronic medical record

[0191] The system automatically generates an electronic medical record based on the integrated data and the preset electronic medical record template;

[0192] The generated electronic medical record needs to be reviewed and confirmed by medical professionals to ensure that it meets medical standards and quality requirements;

[0193] After the review is passed, the system safely saves the electronic medical record to the electronic medical record management system, and provides efficient query and access functions, so that medical professionals can view, update and share patient electronic medical record information at any time; At the same time, the system takes appropriate encryption and access control mechanisms to ensure the security and privacy protection of electronic medical record information.

[0194] Further, according to the system preset rules or trigger conditions, the system automatically identifies the required completed electronic medical record, including the following steps: Step 1.2.1: Time information acquisition: The system acquires real-time time information as the basis for electronic medical record identification;

[0195] Step 1.2.2: Intelligent identification of required completed electronic medical record

[0196] Time point-based electronic medical record identification: The system automatically identifies the required completed electronic medical record at the current time point according to medical standards and hospital internal regulations, such as patient admission, which should complete the admission conversation record, admission record and first medical record;

[0197] Electronic medical record identification based on medical order information: The system analyzes the medical order content and identifies the required completed electronic medical record according to the key information in the medical order;

[0198] Electronic medical record identification based on test and examination results: The system monitors test and examination results in real time, and automatically identifies the corresponding required completed electronic medical record for abnormal or critical value results; For example, if a critical value is identified, a critical value record should be written and recorded in the electronic medical record;

[0199] Electronic medical record identification based on consultation information: After receiving the consultation opinion, the system identifies the corresponding required completed electronic medical record according to the consultation opinion;

[0200] Electronic medical record identification based on billing items: The system automatically identifies the required completed electronic medical record according to the billing items; For example, when billing operations and treatments are performed, the corresponding operation and treatment electronic medical record should be completed;

[0201] Electronic medical record identification based on surgery end time: After identifying the completion of surgery, the system should automatically prompt the need to complete the surgery record, the first postoperative progress note, etc. according to the time node specified by the hospital. For example, the surgery record should be completed within 24 hours after the surgery is completed, and the first postoperative progress note should be completed within 6 hours after the surgery;

[0202] Specific methods to identify the completion of surgery:

[0203] Operating room information system (ORIS) integration:

[0204] Through integration with the ORIS system, the electronic medical record system can obtain the end time of the surgery in real time, thereby triggering the need for subsequent medical record recording; Anesthesia record system synchronization:

[0205] When the surgery is over, the anesthesia record system will usually update the end time of the surgery or mark that the surgery has been completed. The electronic medical record system can synchronize with the anesthesia record system to obtain information about the completion of the surgery;

[0206] Manual confirmation by medical staff:

[0207] In some cases, there may be no automated system integration to track the status of the surgery in real time. At this time, the system can be designed with an interface or function that allows medical staff involved in the surgery (such as the lead surgeon, anesthesiologist, or operating room nurse) to manually confirm the completion of the surgery after the surgery is over;

[0208] Analysis of device usage records:

[0209] Medical devices used during surgery (such as surgical instruments, anesthesia machines, etc.) may generate usage records;

[0210] The system can analyze the usage records of these devices, and when it detects that a particular device has not been used for a period of time (assuming it is the idle time after the surgery is completed), it may infer that the surgery has been completed. However, this method may not be accurate, as the device may still be used for other purposes after the surgery; Real-time video monitoring and A1 analysis:

[0211] In some advanced hospital environments, the operating room may be equipped with high-definition cameras for real-time monitoring of the surgery;

[0212] By applying artificial intelligence (AI) technology, the system can analyze the operating room video to identify signs of the end of the surgery (such as medical staff leaving the operating room, surgical instruments being packed up, etc.), thereby automatically determining the completion of the surgery.

[0213] Based on the identification of pre-set associated electronic medical records: The system determines other medical records that need to be completed according to the pre-set association rules. For example, the operation consent is associated with the preoperative summary and preoperative discussion record. When the operation consent is created, the system should also prompt the creation of the preoperative summary and preoperative discussion record.

[0214] Specific steps and methods based on the identification of pre-set associated electronic medical records:

[0215] 1. Define association rules:

[0216] First, the system administrator or medical expert needs to define the association rules between medical records. These rules can be based on medical processes, hospital regulations, regulatory requirements, and other factors. For example:

[0217] Operation consent is associated with preoperative summary and preoperative discussion record;

[0218] Blood transfusion treatment record needs to be associated with blood transfusion consent and post-transfusion evaluation record, etc.

[0219] Diagnosis record of specific diseases needs to be associated with corresponding treatment plan, follow-up record, etc.

[0220] 2. Configure association logic:

[0221] After defining the association rules, the system administrator needs to configure the corresponding association logic in the electronic medical record system. This usually involves setting trigger conditions, types and quantities of associated medical records, and operations after association (such as prompting creation, automatic filling of information, etc.);

[0222] 3. Real-time monitoring of medical record creation and update:

[0223] The electronic medical record system needs to monitor the creation and update of medical records in real time. When new medical records are created or existing medical records are updated, the system should be able to automatically detect and identify these changes;

[0224] 4. Trigger associated medical record identification:

[0225] Once the changes in medical records that meet the pre-set association rules are monitored, the system should automatically trigger the identification mechanism of associated medical records. This usually involves the following steps:

[0226] Identify associated medical records: The system identifies other medical records associated with the current medical record according to the pre-set association rules;

[0227] Determine the status of medical records: The system checks the status of associated medical records to determine whether to prompt medical staff to create or update these medical records;

[0228] Electronic medical record identification based on other medical data: the system continuously monitors various data during medical treatment, including information at each link of treatment, examination, etc.; when the system detects that a certain medical process (such as treatment) has been completed, it will automatically trigger the corresponding medical record identification mechanism. Identify the treatment records required by medical staff to ensure the completeness and accuracy of the medical record;

[0229] Steps and methods of electronic medical record identification based on other medical data:

[0230] Step 1: The system continuously monitors

[0231] The system deeply integrates multiple key information systems within the hospital, including but not limited to laboratory information system (LIS), radiology information system (RIS), and operating room information system (ORIS). Through these integrated interfaces, the system can capture and monitor comprehensive information of patients in treatment, examination and other medical links in real time. These information covers laboratory examination results, imaging diagnosis reports, specific progress and status of surgery, etc., providing a solid data foundation for subsequent medical record identification and generation;

[0232] Step 2: Automatically trigger the medical record identification process

[0233] When the system accurately monitors the completion of a specific medical process (such as a certain treatment or a specific examination), it will automatically activate the corresponding medical record identification and processing mechanism according to the pre-set intelligent rules or algorithms. For example, once the system detects the completion of blood transfusion, it will immediately trigger the identification and generation requirement of blood transfusion process record;

[0234] Step 3: Intelligent identification and prompt of medical record completion

[0235] Once the medical record identification mechanism is activated, the system will use its intelligent algorithm to quickly identify the medical record closely related to the current medical process and carefully check the completion status of these medical records. For the medical records that have not been filled in, the system will immediately send clear prompt information to the relevant medical staff through various communication means, such as system internal instant notification, SMS reminder or email, etc. These prompts aim to guide medical staff to complete the required medical record in a timely and accurate manner, so as to ensure the completeness, timeliness and accuracy of the medical record.

[0236] Step 1.2.3: The system synchronously updates the status information of the completed medical record;

[0237] Step 1.2.4: The system intelligently judges the electronic medical record to be completed according to the identified required completed electronic medical record and the current completed medical record status.

[0238] Further, an electronic medical record identification based on medical order information, characterized in that the electronic medical record to be completed is identified from the medical order; comprising the following steps:

[0239] Step S1: obtaining the medical order information of the patient;

[0240] Step S2: identifying at least the following entity types by keyword extraction on the medical order information:

[0241] criticality keywords (such as critical, critical);

[0242] surgery / operation keywords (such as surgery / operation name);

[0243] drug keywords (such as drug name, dosage, route of administration);

[0244] inspection / inspection keywords (such as inspection item, inspection item);

[0245] nursing / special instruction keywords (such as fasting requirement, body position restriction);

[0246] Step S3: identifying the electronic medical record to be completed according to the type and content of the extracted keywords, specifically including:

[0247] based on criticality keywords (such as critical, critical): identify the need to complete the critical and critical notification and the electronic medical record containing the reason for the medical order;

[0248] based on surgery / operation keywords: identify the need to complete the surgery / operation risk notification and the electronic medical record containing the reason for the medical order;

[0249] based on drug keywords: identify the need to complete the electronic medical record containing the reason for using the drug and the dosage and route of administration;

[0250] based on inspection / inspection keywords: identify the need to complete the electronic medical record containing the reason for ordering the inspection / inspection;

[0251] based on nursing / special instruction keywords: identify the need to complete the electronic medical record containing the reason for the nursing / special instruction.

[0252] Further, an electronic medical record system for medical exception records, characterized in that it comprises:

[0253] an exception record detection and reminder module: for detecting abnormal records generated in the medical process, including but not limited to inspection, inspection data and results collected by instruments and equipment, and triggering a reminder signal when an abnormal record is detected;

[0254] Electronic medical record retrieval and analysis module: in response to the prompt signal, this module will automatically search for relevant abnormal records in the electronic medical record system. If the system electronic medical record does not record the abnormality or the analysis process of the medical staff is missing, the module will send detailed prompts to the medical staff through the preset communication mode;

[0255] Abnormal record processing detection module: this module is responsible for monitoring whether the medical staff has taken corresponding handling measures according to the analysis results. If the system detects that the abnormal record has not been handled: will automatically send a processing prompt to the medical staff;

[0256] Abnormal record tracking module: further includes:

[0257] Review observation time acquisition sub-module: according to the type and severity of the abnormal record, automatically set and manage the review and observation time of the indicators that need to be tracked;

[0258] Medical record tracking sub-module: used to track review results and check whether these results have been accurately and timely recorded in the electronic medical record;

[0259] Prompting sub-module: when the review and observation time arrives, send a reminder to the medical staff through the preset communication mode to ensure timely review and recording;

[0260] Cyclic tracking sub-module: according to the clinical needs, continuously perform cyclic tracking until the abnormal record is properly handled, and ensure that the processing process and results have been completely recorded in the electronic medical record;

[0261] Electronic medical record automatic generation module: when the abnormal record is confirmed and handled, this module automatically integrates the abnormal record and its processing process, results and other information to generate a standardized electronic medical record.

[0262] Further, an electronic medical record symptom recording method, characterized in that it comprises the following steps:

[0263] Step 1: entry and preliminary verification of symptom information

[0264] The system receives the patient's preliminary symptom information from the entry end and performs preliminary verification. The verification content includes the correctness of the information format, whether it contains garbled codes, missing fields, and whether there are obvious logical errors. This step ensures the preliminary integrity and accuracy of the information, laying a foundation for subsequent processing;

[0265] Step 2: retrieval, intelligent updating and supplementing of symptom records

[0266] New symptom record creation: If a symptom record for the patient does not exist in the system, the system will automatically create a new record based on a pre-set, structured symptom record template. The template covers key information fields such as symptom nature, specific location, duration, intensity / severity, evolution trend, triggering or aggravating factors, etc. The entry end needs to supplement the description information that may be missing in step 1 to ensure the completeness and standardization of the record;

[0267] Intelligent display and addition of historical records: If a symptom record for the patient already exists in the system, the system will automatically search and intelligently display the historical symptom records in chronological order. Users can intuitively compare historical and current symptoms, input complete information of the current symptoms after referring to the historical records, and realize dynamic updating of symptoms;

[0268] Step 3: Standardization and completeness of symptom information

[0269] The system performs deep standardization processing on the received symptom information to ensure the use of unified medical terminology, measurement units, and format specifications. At the same time, it performs deep completeness checking to check whether the information contains all necessary fields and verifies the logical coherence and medical reasonableness of the information. If the information is incomplete or contains errors, the system will issue clear and explicit prompts to the user through the entry end, requiring the user to supplement or correct the information until the information meets the standards of completeness, accuracy, and reasonableness;

[0270] Step 4: Safe storage and efficient management of symptom records

[0271] The system safely and efficiently stores the symptom records that have passed standardization and completeness checking into the electronic medical record, using advanced encryption technology to protect patient privacy. At the same time, it provides powerful data management functions, supporting quick retrieval and screening based on time range, symptom type, keywords, etc. Users can also export, print, or share data as needed to meet diverse needs;

[0272] Step 5: Intuitive display and convenient interaction of symptom records

[0273] The system provides an intuitive and easy-to-use symptom record display interface based on user needs. The interface displays the change history of symptoms in a clear timeline, while highlighting key information fields such as symptom nature, location, etc. The system supports multiple display forms such as charts and lists to facilitate user understanding and analysis of symptom changes. In addition, it provides convenient interaction functions such as clicking on the timeline points to view detailed symptom records, editing or adding new symptom information, etc., to improve user experience.

[0274] Further, a method for mutual detection and improvement of electronic medical record in an electronic medical record system, characterized in that the method comprises:

[0275] I. Construction of medical record dataset:

[0276] In the electronic medical record system, the following information is received, integrated and stored to form a comprehensive and systematic medical record dataset: patient's medical history information, physical examination (physical examination) information, examination and test results, and diagnosis information and treatment information;

[0277] II. Function setting of diagnosis basis detection module:

[0278] Establish a diagnosis basis detection module, which has the following functions:

[0279] Automatic abnormal data retrieval: can automatically retrieve the medical history, physical examination, examination and test results in the medical record dataset, and accurately identify the abnormal data therein;

[0280] Diagnosis information matching and verification: for each abnormal data, determine whether there is corresponding diagnosis information;

[0281] The method and steps for implementing diagnosis information matching and verification are as follows:

[0282] Data preparation and preprocessing:

[0283] Extract a comprehensive medical record dataset from the electronic medical record system, including but not limited to patient's medical history information, physical examination information, examination and test results, and diagnosis information and treatment information;

[0284] Abnormal data identification and classification:

[0285] Use the automatic abnormal data retrieval function to identify abnormal data in the medical record dataset;

[0286] According to the pre-set threshold standard, classify the abnormal data to distinguish between significant abnormal data and slight abnormal data. Significant abnormal data refers to data that deviates significantly from the normal range, while slight abnormal data refers to data that deviates only slightly from the normal value;

[0287] Diagnosis information matching strategy development:

[0288] For significant abnormal data, develop a strategy for automatically matching diagnosis information. This strategy should be able to efficiently retrieve diagnosis information in the medical record dataset and determine whether there is diagnosis corresponding to the significant abnormal data;

[0289] For slight abnormal data, you can choose not to perform automatic matching, or provide an option for doctors to decide whether to match. Doctors can decide whether to match these slight abnormal data with diagnosis information based on clinical experience and patient conditions;

[0290] Matching algorithm implementation and optimization:

[0291] Develop and implement matching algorithms that can quickly and accurately match corresponding diagnostic information based on the type and characteristics of abnormal data.

[0292] Optimize the matching algorithm to improve efficiency and accuracy. This includes but is not limited to adjusting algorithm parameters, optimizing feature selection, etc.

[0293] Matching result verification and feedback:

[0294] Verify the matching results to ensure consistency between the matched diagnostic information and abnormal data.

[0295] If the matching results are inaccurate or questionable, the system should be able to automatically mark and remind the doctor to further review or adjust.

[0296] Doctor review and confirmation:

[0297] Submit the matching results to the doctor for review. The doctor can confirm or adjust the matching results based on their professional knowledge and clinical experience.

[0298] If the doctor finds that the matching results are unreasonable or incomplete during the review process, they can manually modify or supplement the diagnostic information.

[0299] Perfecting medical records and reminders:

[0300] Perfect the electronic medical record based on the doctor's review and matching results. Ensure that each diagnosis has sufficient diagnostic basis as support, and each abnormal data can be accurately associated with the corresponding diagnostic information.

[0301] Establish a reminder mechanism to automatically send clear and specific reminders to the doctor when finding abnormal data without associated diagnosis or diagnostic information without recording abnormalities, guiding the doctor to perfect the electronic medical record.

[0302] Continuous monitoring and improvement:

[0303] Regularly monitor and evaluate the process of diagnostic information matching and verification, and continuously improve and optimize the matching strategy, algorithm and reminder mechanism according to the actual situation.

[0304] Assessment of the sufficiency of diagnostic basis: For each diagnostic information, verify the sufficiency of its diagnostic basis, which can include text, pictures, videos, audio and other forms. At the same time, check the history, physical examination, examination and test results cited in the diagnostic information to ensure the consistency of abnormal data and diagnostic information;

[0305] The implementation of the sufficiency assessment of diagnostic basis is a crucial step in the electronic medical record system, aiming to ensure that each diagnosis has reliable and sufficient basis. The following is a detailed implementation process of this step:

[0306] I. Preparation Phase

[0307] Data Collection: Extract relevant medical history, physical examination (physical examination), examination and test results, and diagnosis information from the electronic medical record system; ensure that the collected data is comprehensive, accurate and up-to-date;

[0308] Define evaluation criteria: According to medical expertise and clinical guidelines, develop evaluation criteria for the sufficiency of diagnostic basis. These criteria may include the number, quality, source, and relevance of diagnostic basis;

[0309] II. Evaluation Phase

[0310] Automatic abnormal data retrieval: Use the automatic abnormal data retrieval function in the electronic medical record system to identify abnormal data in the medical record data set. These abnormal data may include test results beyond the normal range, abnormal physical signs, etc.;

[0311] Diagnosis information matching and verification: For each abnormal data, check if there is corresponding diagnosis information. If there is diagnosis information, further verify the consistency between diagnosis information and abnormal data;

[0312] Sufficiency assessment of diagnostic basis:

[0313] Check the number of diagnostic basis: Ensure that each diagnosis has sufficient number of basis to support;

[0314] Evaluate the quality of diagnostic basis: Check if the basis comes from reliable medical resources, such as professional guidelines, authoritative literature, etc.;

[0315] Analyze the form of diagnostic basis: Consider various forms of basis such as text, pictures, videos, audio, etc., and evaluate their support for diagnosis;

[0316] Check the consistency of diagnostic basis: Ensure that the medical history, physical examination, examination and test results cited in the diagnosis information are consistent with the abnormal data;

[0317] Record evaluation results:

[0318] Record the evaluation results in the electronic medical record system for subsequent analysis and improvement;

[0319] If the diagnostic basis is insufficient or inconsistent, it should be marked and the doctor should be reminded to further review or supplement;

[0320] III. Subsequent Processing Phase

[0321] Doctor Review: Submit the assessment results to the doctor for review to ensure the accuracy and reasonableness of the assessment; the doctor can adjust or supplement the diagnosis according to the assessment results;

[0322] Medical Record Perfection: Improve electronic medical record based on assessment results and doctor's review opinions; ensure that each diagnosis has sufficient diagnostic basis as support, and each abnormal data can be accurately associated with the corresponding diagnostic information;

[0323] Continuous Monitoring and Improvement: Regularly monitor and evaluate the sufficiency of the diagnosis basis assessment process; continuously improve and optimize the evaluation criteria, process and method according to actual conditions;

[0324] Three, intelligent recommendation module of diagnosis corresponding to result abnormalities:

[0325] Establish an intelligent recommendation module of diagnosis corresponding to result abnormalities, which can intelligently analyze and recommend or prompt possible diagnosis options for doctors according to the identified abnormal data, and display relevant diagnostic basis. After the doctor confirms the diagnosis, the module can automatically associate the diagnostic information with the corresponding abnormal data;

[0326] One of the implementation schemes of the intelligent recommendation module of diagnosis corresponding to result abnormalities is as follows:

[0327] 1. Data preprocessing and feature extraction

[0328] Data cleaning: Clean up the medical history, physical examination, examination and test results in the medical record data set, remove noise and irrelevant information, and ensure the accuracy and consistency of the data;

[0329] Feature extraction: Extract key features from the cleaned data, which may include numerical indicators (such as blood glucose value, blood pressure value, etc.), categorical indicators (such as positive / negative results), and text descriptions (such as medical history description, physical examination findings, etc.);

[0330] 2. Build a diagnosis knowledge base

[0331] Integrate professional guidelines and literature: Collect and integrate professional guidelines, clinical pathways, and the latest research literature in the medical field to form a diagnosis knowledge base;

[0332] Structured knowledge representation: Represent the information in the diagnosis knowledge base in a structured form, such as ontology, rule set or decision tree, etc., to facilitate computer understanding and processing;

[0333] 3. Development of intelligent recommendation algorithm

[0334] Machine Learning Model Training: Utilize historical medical record data to train one or more machine learning models (such as decision trees, random forests, support vector machines, neural networks, etc.) that can predict possible diagnoses based on input features (abnormal data);

[0335] Model Optimization and Validation: Continuously optimize model performance through cross-validation, feature selection, parameter tuning, and other methods to ensure accuracy and generalization ability;

[0336] Diagnosis Basis Display: When recommending a diagnosis, extract relevant diagnosis basis from the diagnosis knowledge base based on the diagnosis probability or confidence output by the model, and display it to the doctor in a clear and intuitive way;

[0337] 4. Diagnosis Information and Abnormal Data Association

[0338] Doctor Confirmation of Diagnosis: The doctor confirms the final diagnosis based on the diagnosis options and diagnosis basis provided by the intelligent recommendation module, combined with their professional knowledge and clinical experience;

[0339] Automatic Association: Once the doctor confirms the diagnosis, the system automatically associates the diagnosis information with the corresponding abnormal data and updates the medical record data set;

[0340] Record Improvement Reminder: If the doctor does not make a diagnosis for a certain abnormal data, the system should be able to intelligently detect and remind the doctor to improve the corresponding electronic medical record;

[0341] 5. System Integration and Testing

[0342] Module Integration: Integrate the intelligent recommendation module with other modules of the electronic medical record system (such as medical record data set construction module, diagnosis basis detection module, etc.) to ensure data flow and functional coordination between modules.

[0343] Four, Medical Record Improvement and Reminder Mechanism:

[0344] Establish a reminder and improvement module with the following functions:

[0345] Intelligent detection of potential problems in medical record data sets, such as unassociated abnormal data or unrecorded abnormal diagnosis information;

[0346] When problems are found, automatically send clear and specific reminders to the doctor to guide the doctor to improve the electronic medical record. Ensure that each diagnosis has sufficient diagnostic basis as support, and each abnormal data can be accurately associated with the corresponding diagnosis information, thereby improving the quality and completeness of medical record.

[0347] Further, a method for ensuring the completeness of diagnosis and treatment records in an electronic medical record system, characterized in that the method comprises:

[0348] I. Construction of Medical Record Dataset:

[0349] In the electronic medical record system, the following information is received, integrated, and stored to form a comprehensive and systematic medical record dataset: patient's medical history information, physical examination (physical examination) information, various examination and test results, and diagnosis information and treatment information;

[0350] II. Verification module of diagnosis and treatment logical relationship:

[0351] Establish a diagnosis and treatment detection module, which focuses on verifying the logical relationship between diagnosis and treatment, and the specific functions include:

[0352] Automatically retrieve the medical record dataset and match the diagnosis information with the treatment records to ensure the corresponding relationship between them;

[0353] The method of automatically retrieving the medical record dataset and matching the diagnosis information with the treatment records to ensure the corresponding relationship between them can be divided into the following key steps and technical points:

[0354] I. Data preparation and standardization

[0355] Data extraction: Extract the complete medical record data of the patient from the electronic medical record system, including diagnosis information, treatment records, medical history, physical examination, examination results, etc.; Ensure that the extracted data is comprehensive, accurate, and contains enough information for subsequent analysis and matching;

[0356] Data standardization: Standardize the coding of diagnosis information, such as using ICD-10 or ICD-11 international disease classification coding;

[0357] Standardize the coding of treatment measures in treatment records, such as using CPT (Current Procedural Terminology) or similar coding systems;

[0358] II. Matching logic and algorithm design

[0359] Timeline matching: Check if the timeline of the treatment records matches the timeline of the diagnosis information. Usually, treatment should be performed after diagnosis; Verify the time sequence relationship between diagnosis and treatment through time stamp or date information;

[0360] Diagnosis and treatment relationship establishment: Based on clinical guidelines, expert consensus and medical knowledge base, establish the expected relationship between diagnosis and treatment measures; This can be achieved by creating a diagnosis-treatment mapping table or rule base;

[0361] Automated Matching Algorithm: Rule-based Matching: Design a series of rules to match diagnoses and treatments. These rules can be based on the correspondence of diagnostic codes and treatment codes, or based on specific clinical logic;

[0362] Machine Learning Algorithm: Use machine learning techniques to train models to identify complex relationships between diagnoses and treatment measures. This can be done by analyzing large amounts of medical record data to learn potential matching patterns;

[0363] Three, Matching Process and Verification

[0364] Data Preprocessing: Before matching, preprocess the data such as cleaning, deduplication, standardization, etc. to ensure data quality;

[0365] Matching Execution: Apply automated matching algorithms to match diagnoses and treatment records; Set matching thresholds or confidence levels to determine the accuracy of matching;

[0366] Result Verification: Manually review the matching results, especially for complex or unusual cases; Establish a feedback mechanism to allow doctors to challenge or suggest the matching results, and adjust the algorithm according to the feedback;

[0367] Four, System Optimization and Iteration

[0368] Data Analysis and Mining: Regularly analyze and mine medical record data to discover new diagnostic and treatment relationships; Use these new findings to update the matching algorithm and rule base;

[0369] System Update and Iteration: Based on data analysis results and doctor feedback, continuously optimize the electronic medical record system; Improve the accuracy and efficiency of the diagnosis and treatment detection module, and ensure the completeness, accuracy and consistency of medical record records;

[0370] Analyze diagnostic information to assess whether the patient needs treatment and the necessity and urgency of treatment;

[0371] The steps and methods of analyzing diagnostic information to assess whether the patient needs treatment and the necessity and urgency of treatment are:

[0372] I. Analyze diagnostic information

[0373] Data extraction and integration: Extract patient's medical history information, physical examination information, examination and test results, etc. from medical record data set;

[0374] Integrate these information into a clear diagnosis overview for subsequent analysis;

[0375] Diagnosis standardization: Use standardized diagnostic codes (such as ICD-10, ICD-11) to encode the extracted diagnostic information;

[0376] Disease assessment: Based on the patient's medical history, physical examination results and examination results, assess the severity and complexity of the disease; identify possible complications or comorbidities;

[0377] II. Assessment of treatment needs

[0378] Treatment guideline matching: Match the patient's diagnosis information with existing clinical guidelines and expert consensus; identify the recommended treatment methods and strategies in the guidelines;

[0379] Patient risk assessment: Analyze the patient's age, gender, medical history, current health status and other factors; assess the potential risks and benefits of the patient receiving treatment;

[0380] Symptom and quality of life assessment: Assess the severity of the patient's symptoms and their impact on quality of life; identify symptoms that may cause significant distress or dysfunction to the patient;

[0381] III. Determine the necessity and urgency of treatment

[0382] Treatment priority ranking: Based on the severity of the disease, the recommendations of the treatment guidelines and the results of the patient's risk assessment; prioritize the treatment, determine which treatment is urgent and which is secondary;

[0383] Urgency assessment: Analyze the speed of disease progression and potential consequences; determine whether treatment needs to be performed immediately to slow down disease progression or prevent the occurrence of complications;

[0384] Patient wishes and expectations: Consider the patient's personal wishes, expectations and treatment preferences; ensure that the treatment plan meets both medical standards and respects the patient's autonomy.

[0385] Verify whether the treatment basis provided in the treatment record is sufficient and reasonable, including but not limited to clinical guidelines, expert consensus, patient-specific conditions, etc.;

[0386] Check the matching degree of specific treatment measures described in the treatment record with the diagnosis information, to ensure the targeting and effectiveness of the treatment;

[0387] The matching degree of the specific treatment measures described in the treatment record with the diagnosis information is a key step in the electronic medical record system to ensure the completeness, accuracy and consistency of diagnosis and treatment records. Here are the specific methods to achieve this function:

[0388] I. Data preparation and integration

[0389] Extracting key information: Extracting patients' diagnosis information from the medical record dataset, including primary diagnosis, secondary diagnosis, diagnosis date, etc.; extracting specific measures in treatment records, such as drug treatment, surgical treatment, physical therapy, etc., as well as treatment start and end dates, treatment purposes, etc.

[0390] Standardization: Standardize the coding of diagnoses and treatment measures, such as using ICD (International Classification of Diseases) to code diagnoses and using CPT (Current Procedure Terminology) or similar coding systems to code treatment measures;

[0391] II. Matching logic design

[0392] Timeline matching: Check if the timeline of treatment measures matches the timeline of diagnosis information. For example, after diagnosis, appropriate treatment measures should follow;

[0393] Diagnosis and treatment relationship: Establish the expected relationship between diagnoses and treatment measures based on clinical guidelines and expert consensus; for example, certain specific diagnoses usually correspond to specific treatment plans;

[0394] Treatment measure targeting: Analyze whether the treatment measures are directly aimed at the problems mentioned in the diagnosis information; for example, for hypertension diagnosis, treatment measures should include antihypertensive drugs or lifestyle adjustments, etc.;

[0395] III. Automatic matching algorithm

[0396] Rule-based matching: Design a series of rules for matching diagnoses and treatment measures; rules can be based on the correspondence between diagnosis coding and treatment coding, or based on specific clinical logic;

[0397] Machine learning algorithm: Use machine learning techniques to train models to identify complex relationships between diagnoses and treatment measures; this can be achieved by analyzing a large number of medical records data, learning the potential patterns between diagnoses and treatment measures;

[0398] IV. Verification and feedback of matching results

[0399] Manual review: Manually review the results of automated matching to ensure accuracy; manual review is particularly important for complex or unusual cases;

[0400] Feedback mechanism: Establish a feedback mechanism to allow doctors to challenge or suggest the matching results; these feedbacks can be used to improve the matching algorithm and rules, and improve the accuracy and efficiency of matching;

[0401] V. Continuous optimization and iteration

[0402] Data analysis and mining: Regular analysis and mining of medical record data to discover new diagnostic and treatment relationships; these new findings can be used to update matching algorithms and rules;

[0403] System updates and iterations: Based on data analysis results and physician feedback, continuously optimize the electronic medical record system; improve the accuracy and efficiency of the diagnosis and treatment detection module, and ensure the completeness, accuracy and consistency of medical record records.

[0404] Ensure that all key information about diagnosis and treatment is accurately and completely recorded in the electronic medical record, including but not limited to whether there is treatment, whether treatment is needed, the basis for treatment and specific treatment measures, etc.

[0405] Three, reminder and improvement mechanism

[0406] Establish a reminder and improvement module that can intelligently detect potential problems in medical record data sets, such as:

[0407] Diagnosis without recording treatment information;

[0408] Treatment records not associated with diagnosis information;

[0409] When the above problems are found, automatically send reminders to doctors. Doctors supplement and improve medical records in a timely manner based on reminders to ensure the completeness, accuracy and consistency of medical records;

[0410] Four, continuous optimization of the system

[0411] Based on the actual use of feedback from doctors and in-depth analysis of medical record data, continuously optimize the electronic medical record system, and continuously improve the accuracy and efficiency of the diagnosis and treatment detection module to ensure the completeness, accuracy and consistency of diagnosis and treatment records in the electronic medical record.

[0412] Further, a treatment tracking electronic medical record method, characterized in that the method comprises the following steps in sequence:

[0413] (I) Construction of treatment project database

[0414] In the electronic medical record system, a comprehensive, accurate and real-time updated treatment project database is constructed to store and manage all treatment project information received by patients. The information includes but is not limited to: detailed records of operations and operations (such as operation and operation name, time, site, doctor, etc.), comprehensive information of drug use (such as drug name, specification, dosage, use frequency, start and end date, etc.), detailed records of consumable use (such as consumable type, use site, use duration, etc.), and other key information related to treatment;

[0415] (II) Dynamic tracking of treatment projects

[0416] Utilizing the electronic medical record system, the surgical procedures, drug usage, and consumable usage of patients are recorded and tracked in real-time. The specific tracking contents include:

[0417] Surgical and procedure tracking: Record key information of surgeries and procedures, and continuously monitor recovery, complications, and surgical site infections, etc. after surgery to evaluate treatment effectiveness;

[0418] Drug usage tracking: Record detailed information of drug usage, and continuously evaluate key indicators such as antibacterial effect, drug resistance, side effects, etc. of the drugs;

[0419] Consumable usage tracking: Record the usage of consumables, and track the treatment effect of consumables, such as treatment purposes, observed effects, etc.

[0420] (Three) Establishing an Effect Record and Analysis Module

[0421] An effect record and analysis module is established in the electronic medical record system to track and analyze each treatment project in detail. The module should have the following functions:

[0422] Tracking reminders: Based on the status of the participants of the treatment project (such as patients and medical personnel), the system automatically analyzes and sends reminders to relevant medical personnel and patients, including but not limited to treatment progress reminders, drug usage reminders, examination result viewing reminders, etc.

[0423] To achieve the automatic tracking reminder function based on the participants of the treatment project, the following steps are taken:

[0424] 1. Data integration and participant identification

[0425] Data integration: First, ensure that all necessary patient treatment information is stored in the electronic medical record system, including detailed records of surgeries, drug usage, and consumable usage. At the same time, the system should record the basic information of the participants, such as contact information (mobile phone, email, etc.).

[0426] Participant identification: According to the participants of the treatment project (patients and medical personnel), the system should be able to automatically identify and classify these participants for subsequent reminders.

[0427] 2. Setting reminder rules and conditions

[0428] Rule setting: According to the treatment process and clinical guidelines, set reminder rules for different treatment stages. For example, regular check-ups of the wound within one week after surgery, adjustment of the dosage or review of the drug usage at a certain stage, etc.

[0429] Condition judgment: The system should be able to judge whether these rules are triggered in real-time or periodically. For example, when the drug usage record shows that the patient is about to finish the current course of drugs, trigger the drug usage reminder;

[0430] 3. Reminder content generation and sending

[0431] Content generation: According to the triggered reminder rules, the system automatically generates corresponding reminder content. Contains necessary information, such as reminder type, treatment items, specific operations or inspection requirements, etc.;

[0432] Sending method: The system should support multiple sending methods, such as SMS, email, APP push, etc., in order to meet the needs of different participants. At the same time, the system should record the sending status to ensure that the reminder information can be accurately delivered;

[0433] 4. Intelligent optimization and adjustment

[0434] Machine learning: Using machine learning technology, the system can analyze historical reminder data and user feedback, and continuously optimize reminder rules and sending strategies. For example, according to the patient's medication habits and reactions, adjust the frequency and time of drug use reminders;

[0435] User feedback: The system should provide a user feedback mechanism to allow participants to evaluate and suggest the received reminders. These feedbacks can be used to improve the performance and user experience of the reminder system;

[0436] Record reminders: Participants who remind treatment items should record treatment information in electronic medical records in a timely manner;

[0437] Results display: Use a variety of multimedia forms (such as text, pictures, videos, audio, etc.) to record and display treatment effects, so that medical personnel and patients can intuitively and clearly understand the treatment situation;

[0438] (Four) Implement a cycle tracking mechanism

[0439] According to the analysis results of treatment effects, the system automatically determines whether to perform electronic medical record tracking on patients again. Through this mechanism, ensure the continuity and integrity of treatment, and form a closed loop of cycle tracking;

[0440] In order to realize the automatic judgment of the system according to the analysis results of treatment effects whether to perform electronic medical record tracking on patients again, we can take the following specific methods to realize the automatic judgment of the system:

[0441] I. Define the treatment effect evaluation system

[0442] Determine key evaluation indicators: Based on clinical guidelines and expert consensus, determine key evaluation indicators directly related to treatment effects; These indicators include physiological parameters (such as blood pressure, blood glucose), biochemical indicators (such as liver and kidney function), imaging results, improvement of patient symptoms and signs;

[0443] Setting evaluation criteria and thresholds: Set reasonable evaluation criteria and thresholds for each key evaluation indicator; these criteria and thresholds should be determined based on historical data, clinical experience and expert judgment;

[0444] II. Building a treatment effect analysis model

[0445] Data collection and preprocessing: Collect patient treatment data from the electronic medical record system, including physiological parameters, examination results, medication records, etc.; clean, integrate and preprocess the data to ensure the accuracy and consistency of the data;

[0446] Feature selection and extraction: Extract features related to treatment effect from preprocessed data; these features may include numerical values, trends, fluctuations, etc.

[0447] Model training and validation: Use machine learning algorithms (such as decision trees, random forests, neural networks, etc.) to train a treatment effect analysis model; use historical data to train and validate the model to ensure its accuracy and reliability;

[0448] III. Implementing automatic judgment logic

[0449] Real-time data input: Input real-time treatment data of patients into the treatment effect analysis model;

[0450] Model prediction and evaluation: Use the trained model to predict and evaluate the treatment effect of patients; according to the prediction results and the set evaluation criteria, judge whether the treatment effect meets the expectations;

[0451] Automatic judgment and decision: If the treatment effect does not meet the expectations (i.e. the key evaluation indicators exceed the set thresholds), the system automatically judges that the patient needs to be tracked again in the electronic medical record; the system can generate a tracking task and assign it to the corresponding medical personnel;

[0452] IV. Circular tracking and feedback mechanism

[0453] Tracking task execution: Medical personnel perform re-tracking and evaluation of patients according to the tracking task assigned by the system; record the tracking results in the electronic medical record system and update the data required by the treatment effect analysis model;

[0454] Model optimization and update: Based on new tracking results and clinical data, optimize and update the treatment effect analysis model;

[0455] Circular tracking closed loop: Through continuous tracking, evaluation and feedback, a circular tracking closed loop is formed; ensure the continuity and integrity of treatment, improve medical quality and patient satisfaction.

[0456] (V) Establishing a treatment tracking module system

[0457] In the electronic medical record system, an independent tracking module is established for each treatment item. These modules should include patient tracking functions and medical personnel tracking functions, allowing patients and medical personnel to freely view, edit and supplement the electronic medical record of the treatment within the authorized scope.

[0458] Further, a method for extracting symptoms and signs in an electronic medical record is used to accurately extract and display a specific symptom and sign and its changes over time, covering various types of data such as text, pictures, videos and audio. The specific steps are as follows:

[0459] I. Define symptoms and signs and time range

[0460] Select symptoms and signs: According to clinical needs or research goals, specify the specific symptoms and signs that need to be extracted in the electronic medical record system;

[0461] Set time frame: According to the monitoring or analysis needs of symptoms and signs, set a clear time range for screening and extracting relevant records;

[0462] II. Retrieve and obtain electronic medical record

[0463] Data retrieval: Use the retrieval tools of the electronic medical record system to quickly retrieve all relevant medical records according to the selected symptoms and signs and time range;

[0464] Screening and sorting: Carefully screen the retrieved medical records to ensure that the extracted information is closely related to the required symptoms and signs, and orderly arrange these information;

[0465] III. Extraction of symptoms and signs data

[0466] Symptoms and signs extraction:

[0467] Text description: Extract detailed descriptions of symptoms and signs from medical records, including the nature, location, size, color, shape, and accompanying symptoms of symptoms and signs;

[0468] Picture extraction: For symptoms and signs that can be visually displayed through pictures, such as skin tumors, pigmented nevi, and pigment spots, extract the corresponding picture data from the medical records;

[0469] Video and audio extraction: Extract video or audio data containing symptoms and signs in medical records, such as videos of patients describing symptoms and signs, and audio of doctors examining;

[0470] IV. Presentation of symptoms and signs

[0471] Presentation mode selection: Select the appropriate presentation mode based on the characteristics of the symptoms and signs and the type of extracted information;

[0472] Text presentation: Structure and organize the extracted textual descriptions to form a clear report of symptoms and signs;

[0473] Picture presentation: Arrange the extracted picture information in chronological order or by symptom and sign type to form an intuitive picture display;

[0474] Video and audio presentation: Edit and organize the extracted video and audio information to form multimedia display materials;

[0475] Time range annotation: Clearly mark the time range of each symptom and sign or information when presenting symptoms and signs;

[0476] Five, information viewing and utilization

[0477] Viewing function: Provide convenient viewing functions to allow doctors or researchers to view extracted symptom and sign information at any time, including text, pictures, videos and audio;

[0478] Analysis and utilization: Use the extracted symptom and sign information for further analysis and research, such as symptom and sign trend analysis, disease diagnosis assistance, treatment effect evaluation, etc.

[0479] Further, a national electronic medical record system characterized by comprising:

[0480] System integration and data synchronization module:

[0481] The system includes a national electronic medical record cloud server as the core data processing center, which is seamlessly connected with each medical institution electronic medical record server;

[0482] The national electronic medical record cloud server and each medical institution electronic medical record server use an efficient data synchronization mechanism to ensure real-time synchronization and updating of patient health information;

[0483] The system supports cross-institutional data integration, allowing medical professionals to query and access complete patient health records nationwide;

[0484] Patient health information comprehensive management module:

[0485] The system provides comprehensive patient health information management functions, including but not limited to medical record, diagnosis information, test results, treatment plan, medication record, etc.;

[0486] The system can automatically integrate health information from medical professionals, patients and other related parties to generate a comprehensive patient health profile;

[0487] 1. Data Interface Standardization and Integration

[0488] Developing Data Exchange Standards: Collaborate with various medical institutions, patient terminals, and other related systems (such as traffic police systems) to develop unified data exchange standards and formats, ensuring accurate and efficient data transmission.

[0489] API Interface Development: Develop API interfaces for medical professional terminals, patient terminals, and other endpoints, allowing these endpoints to send or request data from the electronic medical record system according to agreed formats and standards.

[0490] 2. Data Extraction and Synchronization

[0491] Scheduled Extraction: The system can set up scheduled tasks to periodically extract the latest health information from various endpoints.

[0492] Real-time Synchronization: For data that needs real-time updates, such as emergency records and urgent examination results, real-time synchronization mechanisms can be used to ensure timely updates to the system.

[0493] 3. Data Cleaning and Integration

[0494] Data Cleaning: Pre-process the extracted data, including removing duplicate data, correcting errors, and filling in missing data, to ensure data accuracy and completeness.

[0495] Data Integration: Integrate the cleaned data according to key fields such as patient ID to generate comprehensive patient health records. During integration, pay attention to data timing and relevance to ensure the coherence and accuracy of health records.

[0496] 4. Data Storage and Management

[0497] Efficient Storage: Use high-performance databases and storage technologies to ensure efficient storage and retrieval of large-scale data.

[0498] Data Security Management: Strengthen data encryption, access control, and other security measures to protect patient privacy and data security.

[0499] 5. Intelligent Analysis and Early Warning

[0500] Intelligent Analysis: Use big data analysis and machine learning techniques to deeply mine and analyze patient health information, discovering potential health problems and risks.

[0501] Early Warning Function: Based on analysis results, send early warning information to medical professionals and patients, reminding them to pay attention to health problems or take necessary medical measures.

[0502] 6. User Interface and Interaction

[0503] User-friendly interface: Provide an intuitive and easy-to-use interface for patients and medical professionals to query, manage, and update health information.

[0504] Interactive functions: Add interactive functions such as online consultations, appointment registration, etc., to improve user experience and satisfaction.

[0505] 7. Continuous maintenance and upgrade

[0506] System monitoring: Real-time monitoring of the system to timely discover and solve potential problems and faults.

[0507] Regular upgrades: According to business needs and technological development, regularly upgrade and expand the system's functions to ensure its advanced nature and usability.

[0508] The system supports intelligent analysis and early warning functions based on patient health information, such as disease risk assessment, drug interaction detection, etc.

[0509] To implement the nationwide electronic medical record system to support intelligent analysis and early warning functions based on patient health information, such as disease risk assessment, drug interaction detection, etc., follow these steps:

[0510] 1. Data preprocessing and cleaning

[0511] Data integration: First, ensure that the health information collected from medical professionals, patients, and other related parties has been integrated into the nationwide electronic medical record system, forming a comprehensive patient health profile.

[0512] Data cleaning: Clean the collected data to remove duplicate, incorrect, or inconsistent information, ensuring data accuracy and completeness.

[0513] 2. Intelligent analysis model development

[0514] Algorithm selection: According to specific analysis needs, select appropriate algorithms and models. For example, for disease risk assessment, machine learning algorithms such as decision trees, random forests, neural networks, etc. can be used to train models; for drug interaction detection, known drug interaction databases and rules can be used for matching analysis.

[0515] Model training: Use historical health data to train algorithm models to accurately identify and analyze patient health information.

[0516] Model verification and optimization: Verify the model through cross-validation, A / B testing, etc. to ensure its accuracy and reliability. Optimize the model based on verification results to improve analysis effectiveness.

[0517] 3. Early warning function implementation

[0518] Threshold Setting: Based on the results of disease risk assessment and drug interaction detection, reasonable warning thresholds are set. When a patient's health information reaches or exceeds these thresholds, the system will trigger a warning.

[0519] Warning Notification: The system should support multiple warning notification methods such as SMS, email, APP push, etc., to ensure that medical professionals and patients can receive timely warning information.

[0520] Warning Processing: Provide a convenient warning processing interface for medical professionals, allowing them to view warning details, patient health information, and recommended processing measures, and record processing results and feedback.

[0521] 4. System Integration and Testing

[0522] System Integration: Integrate intelligent analysis and warning functions into the national electronic medical record system, ensuring compatibility and collaboration with other modules such as data access permission and security control modules, system performance and scalability modules, etc.

[0523] System Testing: Conduct comprehensive testing on the integrated system, including functional testing, performance testing, security testing, etc., to ensure system stability and reliability.

[0524] 5. Continuous Optimization and Update

[0525] Data Update: Regularly update and analyze the health data and algorithm library required by the model to maintain the accuracy and timeliness of the model.

[0526] User Feedback: Collect feedback from medical professionals and patients to continuously optimize and improve intelligent analysis and warning functions.

[0527] Technology Upgrade: Focus on the latest technology and algorithm development, and apply new technologies to the system in a timely manner to improve the accuracy and efficiency of intelligent analysis and warning.

[0528] Data Access Permission and Security Control Module:

[0529] The system implements strict data access permission management to ensure that only authorized medical professionals, patients and their authorized personnel can access corresponding patient health information;

[0530] The system provides patient data access permission management functions, allowing patients to set and control access permissions to their health information independently;

[0531] System Performance and Scalability Module:

[0532] The national electronic medical record cloud server and the electronic medical record server of the medical institutions both use high-performance computing and storage technology to ensure the stability and response speed of the system under high concurrency access and large data processing.

[0533] The system design supports modular expansion, facilitating function upgrade and expansion according to business needs and technological development.

[0534] The system has the ability to interface with other systems (such as the traffic police system) to enter additional patient health information through other related patient terminals.

[0535] Further, an electronic medical record recording and management system is used to realize the recording, storage, automatic generation, treatment tracking and symptom extraction of electronic medical records. The system includes:

[0536] Information input module: used to collect and record patient health information comprehensively and systematically through medical professional terminals, patient direct related terminals and patient other related terminals;

[0537] Information storage module: used to accurately save the entered patient health information to the corresponding module or location of the electronic medical record system, ensuring the integrity, accuracy and traceability of the information;

[0538] Electronic medical record automatic generation module: used to automatically identify the required completed electronic medical record according to the system preset rules or trigger conditions, and automatically fill in and generate the electronic medical record according to the obtained health information;

[0539] Treatment tracking module: used to record and track the operation, drug use and consumable use of the patient in real time, and set up an effect recording and analysis module to provide treatment progress reminders, drug use reminders and other functions;

[0540] Symptom extraction module: used to accurately extract and display a specific symptom and its changes over time from the electronic medical record, covering various types of data such as text, pictures, videos and audio;

[0541] Data synchronization and access control module: used to ensure data synchronization between the electronic medical record servers of various medical institutions and the national electronic medical record cloud server, and to implement strict data access permission management;

[0542] Intelligent analysis and early warning module: used to deeply mine and analyze patient health information, discover potential health problems and risks, and provide disease risk assessment, drug interaction detection and other functions. DETAILED DESCRIPTION

[0543] A specific embodiment of a method for recording electronic medical records:

[0544] In a busy urban hospital, a patient named Li Ming was urgently sent to the emergency department due to a traffic accident. Here is a specific example of using diverse entry terminals to record Li Ming's health information:

[0545] Step 1: Information Entry

[0546] Medical Professional Terminal Entry: 120 Emergency Medical Technician Entry:

[0547] When the 120 ambulance arrived at the scene of the accident, the emergency medical technician quickly assessed Li Ming and entered his basic information (such as name, age, gender), accident time, preliminary injury description, and emergency measures taken through a mobile application;

[0548] Emergency Department Physician Entry:

[0549] After Li Ming arrived at the emergency department, the emergency department physician immediately conducted a comprehensive physical examination and recorded the patient's vital signs (such as blood pressure, heart rate, respiratory rate), consciousness state, wound condition, etc. At the same time, the physician also developed a preliminary treatment plan based on the examination results and preliminary diagnosis, and entered these information into the electronic medical record system;

[0550] Emergency Department Nurse Entry:

[0551] Under the guidance of the physician, the emergency department nurse performed various nursing operations for Li Ming, such as establishing intravenous access, administering medication, etc., and entered these nursing records and medication use information into the electronic medical record;

[0552] Medical Laboratory and Imaging Personnel Entry:

[0553] According to the physician's orders, Li Ming underwent blood tests and X-ray examination. The medical laboratory personnel entered the blood test results into the system, while the medical imaging personnel uploaded the X-ray film and diagnosis report to the electronic medical record system;

[0554] Patient Directly Related Terminal Entry

[0555] During treatment in the emergency department, Li Ming was conscious and could operate the patient terminal interface of the electronic medical record system himself. He updated his allergy history and past medical history through the system, which was crucial for the physician to develop subsequent treatment plans;

[0556] If Li Ming was unconscious, he could not operate the patient terminal interface of the electronic medical record system to enter information. However, in this case, Li Ming's family members or authorized personnel (such as accompanying friends and relatives) entered the patient's allergy history, past medical history, and other key information on behalf of the patient;

[0557] Other Related Terminal Entry of Patient

[0558] When handling traffic accidents, traffic police enter the specific location, time, and information about the vehicles and personnel involved in the accident through the temporary entry interface provided by the hospital. This information provides important clues about the accident context, helping to assess the patient's injury and prognosis and subsequent insurance claims;

[0559] Step two: Information storage

[0560] All patient health information collected through various entry points, including emergency records, physical examination results, treatment plans, nursing records, test results, imaging reports, and patient self-entered information, is accurately saved to the corresponding modules or locations of the electronic medical record system. The system ensures the integrity and traceability of the information through timestamps and unique identifiers.

[0561] Other related entries by patients (traffic police information entry) can also

[0562] Traffic police on-site handling:

[0563] Traffic police quickly handle traffic accidents at the scene, collecting key data such as the specific location, time, and information about the vehicles and personnel involved in the accident; information entry into the traffic police system:

[0564] Traffic police enter this information into the traffic police system through dedicated law enforcement equipment or mobile applications. The system performs preliminary verification and sorting of the entered information;

[0565] Information synchronization to the electronic medical record system:

[0566] A safe and efficient data exchange interface is established between the traffic police system and the hospital's electronic medical record system. When the traffic police complete the accident information entry in the system and confirm that it is correct, this information is automatically or through a trigger mechanism synchronized to the hospital's electronic medical record system;

[0567] During synchronization, the electronic medical record system will re-verify the received information to ensure data accuracy and completeness. At the same time, the system assigns a unique identifier and timestamp to each synchronized information for subsequent tracking and auditing;

[0568] Hospital receives and audits information:

[0569] After the electronic medical record system receives the synchronized accident information, it is automatically saved to the corresponding module or location. Hospital staff (such as emergency department physicians or medical record management personnel) can view this information when needed to understand the patient's accident context;

[0570] If the hospital finds that the synchronized information is incorrect or incomplete, it can communicate with the traffic police department through the pre-set feedback mechanism to request correction or additional information.

[0571] Example 2

[0572] In a serious fire accident in a residential area, patient Zhang Hua was unfortunately injured during the escape process and was then urgently sent to the hospital for treatment. During the fire rescue and treatment process, the electronic medical record method played a key role, especially in the input and integration of firefighter information, showing its efficient and comprehensive advantages. The following is a detailed description of this process, including the input of firefighter information, the connection with the fire system, and the synchronous input in the electronic medical record system;

[0573] I. Information input and integration process

[0574] 1. Medical professional input

[0575] 120 Emergency personnel input: After the ambulance arrived at the scene, emergency personnel quickly assessed Zhang Hua and entered basic information, preliminary injury description, and emergency measures taken through a mobile application;

[0576] Emergency physician and nurse input: After Zhang Hua arrived at the emergency department, the physician conducted a comprehensive physical examination, recorded vital signs, consciousness status, burn situation, etc., and developed a treatment plan; the nurse recorded nursing operations and drug use information;

[0577] Medical laboratory and imaging personnel input: According to the doctor's order, Zhang Hua received necessary tests and examinations, and the relevant results were input into the electronic medical record system by medical laboratory and imaging personnel;

[0578] 2. Firefighter input

[0579] At the fire scene, firefighters not only rescue, but also record key information, which is important for assessing patient injury and prognosis;

[0580] Basic information input: Record fire time, location, fire size, and main burning materials;

[0581] Patient escape path and state input: Detailed record of Zhang Hua's escape path, whether through a larger fire area, and state during escape (such as difficulty breathing, burns, etc.);

[0582] Fire scene environment input: Describe smoke density, temperature and heat radiation, building structure and safety conditions, etc. to assess the possible harm to the patient;

[0583] Other related information input: Record rescue process, use of special equipment or tools, and other injured persons at the fire scene;

[0584] 3. Connection with fire system and synchronous input

[0585] To achieve seamless integration of information, after the firefighter enters the above information into the fire system, these information is automatically synchronized to the electronic medical record system through the preset interface. This process ensures the timeliness, accuracy and completeness of the information, avoiding errors and delays that may be caused by manual entry; Information synchronization mechanism: a data exchange protocol is established between the fire system and the electronic medical record system to realize real-time synchronization of information;

[0586] Data verification and integration: during the synchronization process, the electronic medical record system verifies the data to ensure the accuracy and consistency of the information. Subsequently, these information is integrated into Zhang Hua's medical record, forming a complete medical file;

[0587] 4. Patient directly related end and other related end entry

[0588] Patient directly related end: due to Zhang Hua's serious injury, he cannot enter the information by himself. But the patient's family members arrive at the hospital after the patient's authorized personnel function to enter the allergic history, past medical history and other key information on behalf of the patient;

[0589] Patient other related end: neighbors and other personnel provide basic information about Zhang Hua and his behavior state in the fire, which helps the hospital to quickly contact the family members and understand the patient's preliminary situation;

[0590] II. Information storage and utilization

[0591] All information collected through diversified entry ends, including first aid records, physical examination results, treatment plans, nursing records, test results, image reports and on-site information provided by firefighters, are accurately saved to the corresponding modules or locations of the electronic medical record system.

[0592] Application of automatic identification in information entry in medical information management system

[0593] Scenario background:

[0594] Mr. Li, 50 years old, recently went to a large general hospital for treatment due to persistent chest pain and difficulty breathing. In order to efficiently and accurately collect and process Mr. Li's health information in order to develop a personalized treatment plan for him, the hospital decides to use an advanced automatic identification entry system to optimize the information entry process.

[0595] Information entry process:

[0596] Step 1: Information submission

[0597] Medical professional end: The doctor quickly enters Mr. Li's basic information, such as name, gender, age, contact information, ID number, and other key data into the electronic medical record system. At the same time, the nurse uses intelligent devices to quickly collect Mr. Li's admission physical examination results, including height, weight, blood pressure, heart rate, and other vital sign data, and uploads these data to the system in real time.

[0598] Patient direct correlation end: Mr. Li's family members fill in the medical history questionnaire in detail through the health management APP provided by the hospital, and upload multiple materials. The questionnaire content covers the onset time, onset mode, main symptoms and their characteristics, accompanying symptoms, disease evolution and progression, etiology and predisposing factors, and other present illness information. In addition, the family members also upload Mr. Li's electrocardiogram, blood test results, and an upload record of uncertain specific content (may be the results of a special examination, the patient's self-reported illness record or other related documents) in other medical institutions.

[0599] Step 2: Intelligent identification

[0600] The system uses advanced natural language processing, image recognition, and machine learning techniques, combined with a pre-established electronic medical record knowledge base, to intelligently identify and preprocess the health information submitted by the medical professional end and the patient direct correlation end. The system successfully identifies Mr. Li's basic information, physical examination results, most of the medical history records, and key values and abnormal indicators in the electrocardiogram and blood test results.

[0601] For the upload record of uncertain specific content, since the system cannot directly identify its content and format, it is temporarily classified as "unknown type upload record" and saved to the "to-be-audited data unit" together with other incompletely identified data.

[0602] Step 3: Data saving, auditing and feedback Automatic saving: successfully identified health data is saved to the corresponding modules of the electronic medical record system, such as "patient basic information", "physical examination", "test results", etc., ensuring the completeness and traceability of the information.

[0603] To-be-audited data processing: For the "unknown type upload record" and other to-be-audited data (such as detailed descriptions or special symbols in part of the medical history records) that the system cannot completely identify, the system temporarily saves them to the "to-be-audited data unit" and automatically triggers a prompt to inform the doctor to conduct manual auditing.

[0604] The doctor carefully reviews the data under audit, confirms the key information in the medical history record, and identifies the specific content of the "unknown type upload record" (such as the results of a special examination or the patient's self-reported illness record). The audited data is correctly classified and saved to the corresponding module. At the same time, the doctor further improves the electronic medical record knowledge base based on the findings during the audit process to improve the system's ability to identify similar information in the future.

[0605] The system also provides a real-time feedback mechanism, allowing doctors and family members to communicate information entry at any time during the audit process to ensure the accuracy and completeness of the information. In addition, the system can automatically adjust the recognition algorithm based on the doctor's feedback to continuously optimize the recognition effect.

[0606] Manual selection entry in information entry

[0607] Scenario background:

[0608] Ms. Zhang, 45 years old, recently went to a large general hospital for treatment due to repeated fever and cough symptoms. In order to comprehensively and systematically collect and process Ms. Zhang's health information, the hospital decides to use the manual selection entry method in the conventional entry mode to optimize the information entry process.

[0609] Information entry process:

[0610] Step one: information module selection

[0611] Medical professional side: The doctor carefully selects the modules corresponding to the health information to be entered from the pre-set, structured document modules in the electronic medical record system according to Ms. Zhang's condition and treatment needs. The doctor first selects the "patient basic information" module to enter Ms. Zhang's name, gender, age, contact information, and other key data. Then, the doctor selects the "medical history record" module to record Ms. Zhang's onset time, onset mode, main symptoms and characteristics, accompanying symptoms, and other present illness information. In addition, the doctor also reserves the "test results" and "treatment plan" modules for subsequent entry of related examination data and treatment plans.

[0612] Patient direct related side: Ms. Zhang's family members also enter the manual selection entry interface through the health management APP provided by the hospital. The family members select the "patient basic information" to supplement and improve (such as medical insurance number, emergency contact, etc.), and select the "past medical history" and "allergy history" sub-modules in the "medical history record" module to enter Ms. Zhang's past medical history and known allergic drug information.

[0613] Step two: information entry and verification

[0614] Medical professional side: After selecting the module, the doctor enters Ms. Zhang's health information one by one according to the entry requirements and format of the module. For example, in the "medical history record" module, the doctor describes Ms. Zhang's onset time (such as "fever symptoms appeared a week ago"), onset mode (such as "acute onset"), main symptoms and their characteristics (such as "high fever, body temperature up to 39.5°C, accompanied by cough and sputum"), accompanying symptoms (such as "weakness, loss of appetite"), etc. During the entry process, the system provides data format verification and mandatory item verification guidance to ensure the accuracy and completeness of the information.

[0615] Patient direct correlation side: After selecting the module, the family member also supplements and perfects Ms. Zhang's health information one by one according to the corresponding entry requirements and format. For example, in the "patient basic information" module, the family member enters Ms. Zhang's medical insurance number and emergency contact information. In the "medical history record" module, the family member describes Ms. Zhang's past medical history (such as "has had bronchitis") and allergy history (such as "allergic to penicillin"). During the entry process, the system also provides necessary entry guidance and verification rules.

[0616] Step three: information upload and automatic allocation

[0617] After completing the information entry, the users of the medical professional side and the patient direct correlation side will upload the recorded information to the database of the electronic medical record system. After receiving the uploaded information, the system will automatically allocate it to the corresponding module or location according to the type and attributes of the information. For example, Ms. Zhang's basic information is allocated to the "patient basic information" module, the medical history record is allocated to the "medical history record" module, and the subsequent examination data and treatment plan will be allocated to the "examination results" and "treatment plan" modules respectively. This process ensures the orderly storage and convenient retrieval of information. Information entry by the medical side to specify the patient direct correlation side:

[0618] Background: Dr. Zhang is an internal medicine physician who needs to understand the allergy history information of a patient named Li Hua when formulating a treatment plan for him. Since allergy history is crucial for avoiding potential drug reactions, Dr. Zhang decides to specify the patient direct correlation side (i.e. Li Hua himself or his family member) to enter this information through the electronic medical record system;

[0619] Steps:

[0620] Medical side selects information content:

[0621] Dr. Zhang logs into the electronic medical record system and views the details of Li Hua's medical record.

[0622] In the "Allergy History" section, Dr. Zhang notices that the information is incomplete, so he decides to assign Li Hua or his family members to supplement this information through the system. Dr. Zhang selects "Allergy History" as the information content that needs to be obtained directly from the patient's related end in the system;

[0623] The system sends a push notification:

[0624] The electronic medical record system automatically generates a push notification with the content: "Dear Mr. / Ms. Li Hua, in order to more accurately develop your treatment plan, we need to understand your allergy history information. Please click on the following link or scan the QR code to enter the input interface and fill in the relevant information according to your actual situation."

[0625] The system sends this notification to Li Hua's mobile phone through SMS and APP push;

[0626] Patient directly related end enters information:

[0627] After receiving the push notification, Li Hua clicks on the link and enters the input interface;

[0628] In the interface, Li Hua sees detailed inquiries about allergy history, such as "Are you allergic to any drugs?" and "Do you have a history of food allergies?"

[0629] Li Hua answers these questions one by one according to his actual situation and submits the information.

[0630] Medical end confirms and saves information:

[0631] Dr. Zhang sees Li Hua's submitted allergy history information in the electronic medical record system in real time.

[0632] He carefully checks the information and confirms that it is correct, then clicks the save button.

[0633] The system automatically updates Li Hua's allergy history information to his electronic medical record and marks it as verified.

[0634] Specific implementation example: System assignment of input end in information input

[0635] Background: A large general hospital introduces an advanced electronic medical record system to improve the completeness and accuracy of electronic medical records. The system has intelligent recognition, automatic allocation, and assignment of input functions, which can greatly improve the efficiency of medical information input and data quality. The following is a specific implementation example of system assignment of input end.

[0636] Step 1: The system automatically identifies the electronic medical record to be completed

[0637] Trigger Condition: The system is pre-set with a rule to automatically check unfinished electronic medical records at 4 PM every day.

[0638] Execution Process: At the set time, the system automatically scans the electronic medical record system and identifies all unfinished electronic medical records.

[0639] Identification Result: The system identifies a patient named Zhang San whose electronic medical record is missing the "postoperative recovery" course record.

[0640] Step 2: Determine the required health information

[0641] Analysis Process: The system further analyzes Zhang San's electronic medical record and finds that the health information that needs to be supplemented includes "operation time", "operation method", "postoperative symptoms", "postoperative examination results", etc.

[0642] Information List: The system generates an information list detailing the required supplementary health information and its corresponding electronic medical record modules.

[0643] Step 3: Intelligent judgment and sending information to the corresponding entry end

[0644] Judgment Process: The system intelligently analyzes the health information that each entry end (medical professional end, patient directly related end, and other related patient end) can provide.

[0645] Medical Professional End: Can provide "operation time", "operation method" and other medical professional information.

[0646] Patient Directly Related End: Can provide "postoperative symptoms" and other subjective information of patients.

[0647] (No patient other related end involved in this example)

[0648] Send Information: The system sends push notifications to the medical professional end and the patient directly related end respectively, clearly informing the specific health information content that needs to be entered.

[0649] Step 4: Entry end enters information and automatically stores it into the electronic medical record system

[0650] Medical Professional End Entry:

[0651] The entry personnel selects the "operation time" and "operation method" modules from the electronic medical record system according to the system prompt.

[0652] Enter the specific operation time and operation method of Zhang San's patient.

[0653] The system automatically checks the accuracy and completeness of the entered information.

[0654] Patient Directly Related End Entry:

[0655] Patient Zhang San or his family members log in to the electronic medical record system based on system push notifications.

[0656] In the "Postoperative Symptoms" module, the postoperative recovery of patient Zhang San is recorded, such as pain level, wound healing, etc.

[0657] The system also performs automatic verification.

[0658] Automatic storage:

[0659] After receiving the information entered by the medical professional end and the patient directly related end, the system automatically performs data verification and cleaning.

[0660] After verification, the system stores the information in the corresponding module of the electronic medical record system. The system updates the electronic medical record of patient Zhang San in real time, ensuring the timeliness and accuracy of the information.

[0661] The following is an example of information storage implementation, combining the steps and modular design described earlier:

[0662] Patient information storage implementation

[0663] Background: Patient Mr. Zhang, male, 45 years old, came to the hospital for persistent chest pain. The doctor needs to conduct detailed medical history inquiry, physical examination and necessary laboratory tests, and enter all information into the electronic medical record system.

[0664] Step 1: Standardization of document structure and construction of information entry system

[0665] Document structure design:

[0666] According to the hierarchical evaluation standard of electronic medical record system application level, design a modular document structure containing patient's whole cycle health information.

[0667] Determine each module, such as patient basic information module, medical history record module, physical examination module, laboratory test result module, diagnosis information module, treatment plan module, etc.

[0668] Information entry system construction:

[0669] Assign a unique identifier to Mr. Zhang's health information to ensure data organization and traceability.

[0670] Integrate the entry interface and process of the medical professional end (doctor, nurse) and the patient directly related end (Mr. Zhang and his family members).

[0671] Step 2: Information storage and multimedia data association

[0672] Health information storage:

[0673] Patient Basic Information Module: Enter Mr. Zhang's name, gender, age, contact information, ID number, medical insurance number, and other key information.

[0674] Medical History Recording Module:

[0675] Current Medical History Submodule: Record Mr. Zhang's onset time, onset mode, main symptoms (persistent chest pain), accompanying symptoms, disease evolution, cause and inducement, and treatment history.

[0676] Past Medical History Submodule: Record Mr. Zhang's past medical history, such as a 5-year history of hypertension.

[0677] Family Medical History Submodule: Record Mr. Zhang's family history of heart disease.

[0678] Allergy History Submodule: Record Mr. Zhang's allergic reaction to penicillin.

[0679] Physical Examination Module:

[0680] Vital Signs Submodule: Record Mr. Zhang's height, weight, blood pressure (elevated), heart rate, and body temperature.

[0681] Detailed Examination Submodule: Use an electronic stethoscope to record Mr. Zhang's heart auscultation audio and take a chest X-ray as multimedia information storage. These multimedia information are linked to the physical examination record through a unique identifier.

[0682] Laboratory Test Results Module:

[0683] Laboratory Test Submodule: Enter Mr. Zhang's blood test, urine test, and biochemical test results, and upload scanned copies of laboratory test reports.

[0684] Examination Submodule: Integrate Mr. Zhang's electrocardiogram and chest X-ray results, and provide storage functions for numerical data and image data.

[0685] Data Association and Integration:

[0686] Ensure that multimedia information in physical examination (such as heart auscultation audio and chest X-ray) can be accurately linked to the corresponding multimedia storage table.

[0687] The multimedia storage table not only saves the original data, but also contains a text summary, such as "heart auscultation audio shows a fast heart rate with a murmur; chest X-ray shows a slightly enlarged heart."

[0688] Step 3: Device and data synchronization and user permission management

[0689] Device Data Automatic Integration:

[0690] Mr. Zhang uses his own electronic blood pressure monitor to measure his blood pressure and uploads the data in real time to the electronic medical record system, ensuring seamless integration of health monitoring data.

[0691] Multi-role collaborative access:

[0692] The doctor accesses Mr. Zhang's electronic medical record through the medical professional terminal to make a diagnosis and develop a treatment plan.

[0693] Mr. Zhang and his family access some medical record information through the patient direct related terminal to understand the patient's condition and treatment progress.

[0694] Data entry and operation record:

[0695] Doctors and nurses collaboratively enter data within their respective permissions, and the system automatically records the historical track of each operation, such as "2023-05-15 10:00, Doctor A enters ECG results."

[0696] Results

[0697] Through the above steps, Mr. Zhang's health information is fully and accurately entered into the electronic medical record system, and multimedia data association and storage are achieved. Different users access medical record information according to role allocation principles, ensuring information security and privacy protection. At the same time, automatic integration of device data and retention of operation records improve data accuracy and traceability.

[0698] Specific implementation example of electronic medical record automatic generation method Background: A large third-grade hospital decides to use an electronic medical record automatic generation system to improve medical work efficiency and ensure the accuracy and completeness of medical record information. The system combines manual selection and creation, automatic recognition and creation, multi-channel health information collection, data integration and verification, and electronic medical record generation, review and preservation, aiming to optimize medical record writing process and improve medical quality.

[0699] Implementation steps

[0700] Step 1: Selection and creation of electronic medical record

[0701] Manual selection and creation:

[0702] Dr. Zhang of the cardiovascular department sees a new patient and manually selects and creates a cardiovascular department-specific electronic medical record template in the system according to the patient's specific condition and electronic medical record management writing specifications.

[0703] Automatic recognition and creation:

[0704] The system recognizes that the patient needs an ECG examination according to the preset rules and automatically creates an ECG examination electronic medical record template.

[0705] The system identifies that the patient needs blood tests and provides multiple blood test templates for Dr. Zhang to choose from. Dr. Zhang selects the templates for routine blood tests and biochemical tests based on the patient's specific needs.

[0706] Step 2: Acquisition of health information and data filling

[0707] Determination of health information needs:

[0708] The system identifies the type of cardiovascular medicine electronic medical record template and obtains the corresponding writing specifications. According to the writing specifications, the system determines the health information that needs to be collected, including patient basic information, symptom description, physical examination, diagnosis information, treatment plan, electrocardiogram test results, blood test results, etc.

[0709] The system generates a health information requirement list, detailing all the information items that need to be collected.

[0710] Multi-channel collection of health information:

[0711] Dr. Zhang enters the patient's basic information, symptom description, and physical examination information through the medical professional terminal.

[0712] The patient enters his own allergy history and past medical history through the patient direct related terminal.

[0713] The electrocardiogram room uploads the electrocardiogram test results through the patient other related terminal.

[0714] Data integration and verification:

[0715] The system integrates the data collected from different channels and conducts strict verification.

[0716] In the data integrity check, the system finds that the contact information in the patient's basic information is missing, and immediately generates a prompt message to Dr. Zhang, who then supplements the contact information.

[0717] In the data accuracy verification, the system finds that the patient's age is filled in as "150 years old", which is obviously unreasonable, so it generates an error prompt message, and Dr. Zhang corrects it to the correct age after verification.

[0718] In the data consistency verification, the system finds that the patient's name is inconsistent between the medical professional terminal and the patient terminal, and generates an inconsistency prompt message. Dr. Zhang and the patient verify and unify the name.

[0719] Step 3: Generation, review and saving of electronic medical record

[0720] Based on the integrated data and the preset electronic medical record template, the system automatically generates an electronic medical record containing patient basic information, symptom description, physical examination, diagnosis information, treatment plan, electrocardiogram results, and blood test results.

[0721] Review and confirmation of electronic medical record:

[0722] Dr. Zhang reviews the generated electronic medical record and confirms that it meets medical standards and quality requirements.

[0723] After passing the review, Dr. Zhang confirms the electronic medical record in the system.

[0724] Saving and querying of electronic medical record:

[0725] The system safely saves the electronic medical record to the electronic medical record management system.

[0726] Dr. Zhang and other medical professionals can query and access patient electronic medical record information at any time through the system for subsequent diagnosis and treatment.

[0727] Security and privacy protection:

[0728] The system adopts appropriate encryption and access control mechanisms to ensure the security and privacy protection of electronic medical record information.

[0729] Only authorized medical professionals can access patient electronic medical record information.

[0730] According to the system's preset rules or trigger conditions, the system automatically identifies the specific implementation cases of the electronic medical record required to be completed.

[0731] Case implementation steps

[0732] Step 1.2.1: Time information acquisition

[0733] The system obtains real-time time information through the hospital's internal time server to ensure the accuracy of the time stamp of the medical record generation.

[0734] Step 1.2.2: Intelligent identification of electronic medical record required to be completed

[0735] Time-based electronic medical record identification:

[0736] When patient Ms. Li was admitted, the system automatically identified and prompted the medical staff to complete the admission conversation record, admission record, and first medical record. The admission record and admission conversation record were completed within 24 hours after admission, and the first medical record should be completed within 8 hours of the patient's admission. Electronic medical record identification based on doctor's order information:

[0737] The doctor prescribed blood routine and urine routine for Ms. Li. After the system analyzed the doctor's order, it automatically identified and prompted the medical staff to complete the corresponding test application form, and after the test result came out, it prompted to complete the medical record of the test result.

[0738] Electronic medical record identification based on test results:

[0739] The blood routine result of Ms. Li showed that the white blood cell count was abnormal, and the system automatically identified and prompted the medical staff to complete the critical value record, and detailed the result and subsequent processing measures in the electronic medical record.

[0740] Electronic medical record identification based on consultation information:

[0741] Ms. Li needed to consult the cardiology department due to her complex condition. After the system received the consultation opinion, it automatically identified and prompted the medical staff to complete the corresponding medical record according to the consultation opinion, and detailed the consultation process and the corresponding processing measures of the consultant's opinion.

[0742] Electronic medical record identification based on billing items:

[0743] Ms. Li received infusion therapy, and the system automatically identified and prompted the medical staff to complete the electronic medical record of infusion therapy based on the billing items, including the drug, dose, time, and other information of the infusion.

[0744] Electronic medical record identification based on surgery end time:

[0745] Ms. Li underwent cholecystectomy. The operating room information system (ORIS) synchronously transmitted the surgery end time to the electronic medical record system. According to the time node specified by the hospital, the system automatically prompted the medical staff to complete the surgery record, postoperative first medical record, etc.

[0746] During this process, the system also synchronously obtained the surgery end information through the anesthesia record system, and through the manual confirmation function of the medical staff, the need for surgery record was verified again after the lead surgeon confirmed the completion of the surgery.

[0747] Electronic medical record identification based on pre-set association:

[0748] The system administrator defined the association rules of the surgery consent form, preoperative summary, and preoperative discussion record. When Ms. Li's surgery consent form was created, the system simultaneously prompted to create the preoperative summary and preoperative discussion record.

[0749] The system monitors the creation and update of these medical records in real time. Once it detects a change in a medical record that meets the pre-set association rules, it automatically triggers the identification mechanism for associated medical records.

[0750] Step 1.2.3: Completed medical record status synchronization

[0751] The system synchronizes and updates the status information of completed medical records in real time. For example, when the medical staff completes Ms. Li's admission record, the system immediately updates the status of this medical record to "completed" and removes it from the list of pending medical records.

[0752] Step 1.2.4: Intelligent judgment of pending medical records

[0753] The system intelligently judges the pending electronic medical records based on the identified required completed electronic medical records and the current completed medical record status. For example, after Ms. Li's surgery record is completed, the system determines that the first postoperative medical record is still pending and prompts the medical staff to complete it in a timely manner.

[0754] Electronic medical record identification based on other medical data

[0755] The system deeply integrates the hospital's internal laboratory information system (LIS), radiology information system (RIS), etc., to capture and monitor Ms. Li's comprehensive information in medical treatment, examination, and other medical links in real time.

[0756] When the system detects that Ms. Li's CT examination is completed, it automatically triggers the identification and generation of the CT examination report. The system uses intelligent algorithms to quickly identify medical records closely related to the CT examination and check the completion status of these medical records. For medical records that have not been completed, the system prompts the medical staff to complete them in a timely manner through internal notifications.

[0757] A specific example of electronic medical record identification based on medical order information

[0758] Patient background: Patient Zhang, male, 65 years old, admitted for treatment of acute appendicitis.

[0759] Medical order information:

[0760] "Patient Zhang, scheduled for appendectomy under general anesthesia tomorrow morning at 9 am, fasting for 8 hours before surgery, and lying flat for 6 hours after surgery."

[0761] "Give patient ceftriaxone sodium 2g, once a day, intravenous infusion, to prevent infection."

[0762] "Perform blood routine and urine routine examination on the second day after surgery to assess patient's recovery."

[0763] Keyword extraction and medical record identification:

[0764] Step S1: Obtain the patient's order information: the system obtains the above-mentioned order information of patient Zhang from the doctor's workstation or electronic medical record system.

[0765] Step S2: Keyword extraction:

[0766] Severity of illness keywords: none (the patient did not mention severe or critical illness)

[0767] Operation / operation keywords: appendectomy

[0768] Drug keywords: ceftriaxone sodium, 2g, once a day, intravenous drip

[0769] Examination / inspection keywords: blood routine, urine routine

[0770] Nursing / special instruction keywords: preoperative fasting for 8 hours, postoperative supine for 6 hours

[0771] Step S3: Medical record identification:

[0772] Based on the operation / operation keywords:

[0773] Identify the need to complete the "appendectomy risk notification", and record the operation reason (acute appendicitis).

[0774] Identify the need to complete the preoperative preparation medical record, including "preoperative summary", "preoperative discussion record", etc., and record the operation plan and related information. Based on the drug keywords:

[0775] Identify the need to complete the "ceftriaxone sodium use record", and record the medication reason (to prevent infection), dose (2g), administration route (intravenous drip) and frequency (once a day).

[0776] Based on the examination / inspection keywords:

[0777] Identify the need to complete the "blood routine examination application form" and "urine routine examination application form", and record the examination reason (to evaluate the patient's recovery).

[0778] Based on the nursing / special instruction keywords:

[0779] Identify the need to complete the "preoperative nursing record", and record the nursing operation and reason of preoperative fasting for 8 hours.

[0780] Identify the need to complete the "postoperative nursing record", and record the nursing operation and reason of postoperative supine for 6 hours, as well as other postoperative nursing needs.

[0781] System operation:

[0782] According to the above identification results, the system automatically generates or prompts medical staff to fill in the corresponding electronic medical record.

[0783] For medical records that require patient or family signature (such as surgical risk notification), the system can generate an electronic version of the signature page and send it to the patient or family member's mobile device through the hospital's internal system for electronic signature, or print it out for the patient or family member to sign and then scan and upload to the system. The system synchronously and real-time updates the status information of the completed medical record, ensuring the completeness and accuracy of the medical record.

[0784] The following is an example of the implementation process of the medical abnormality record electronic medical record system:

[0785] Patient Background

[0786] Patient Name: Mr. Wang Age: 56 Gender: Male Admission Diagnosis: Suspected diabetes, need to perform blood glucose monitoring and related examinations

[0787] Abnormality Record Detection and Reminder Module Scenario: Mr. Wang underwent routine blood glucose monitoring after admission. The blood glucose monitoring results showed that his fasting blood glucose value was much higher than the normal range, reaching the diagnostic criteria for diabetes.

[0788] Process: The abnormality record detection and reminder module received and analyzed the blood glucose monitoring data in real-time. When it detected the abnormality in Mr. Wang's blood glucose value, the module immediately triggered a reminder signal and marked the abnormal record as important.

[0789] Electronic Medical Record Retrieval and Analysis Module Response: After receiving the reminder signal, the electronic medical record retrieval and analysis module automatically searched the electronic medical record system for blood glucose monitoring records related to Mr. Wang. The system found that although the blood glucose monitoring results were recorded, there was a lack of further analysis and diagnosis opinions from the doctor.

[0790] Operation: The module sent a detailed reminder to Mr. Wang's attending physician through the hospital's internal communication system, reminding the doctor to conduct in-depth analysis of the blood glucose monitoring results and consider whether further examinations or adjustments to the treatment plan are needed.

[0791] Abnormality Record Processing Detection Module Doctor Operation: After receiving the reminder, the doctor analyzed Mr. Wang's blood glucose monitoring results in detail and preliminarily diagnosed "Type 2 diabetes". Subsequently, the doctor developed a detailed treatment plan and arranged for further glycosylated hemoglobin testing to confirm the diagnosis.

[0792] Monitoring: The abnormality record processing detection module detected that the doctor had processed the abnormal record and recorded the analysis and processing opinions. Therefore, the module did not send additional processing reminders to the doctor.

[0793] Abnormality Record Tracking Module

[0794] Review observation time acquisition submodule: Based on the doctor's preliminary diagnosis and follow-up examination plan, the module automatically sets the review time for glycosylated hemoglobin testing and manages the blood glucose indicators that need to be tracked.

[0795] Medical record tracking submodule: When the review time arrives, the module automatically tracks Mr. Wang's glycosylated hemoglobin test results and checks whether these results have been accurately and timely recorded in the electronic medical record.

[0796] Reminding submodule: Before the review time, the module sends a reminder to the doctor through a short message, ensuring that the doctor can arrange Mr. Wang's review on time. Loop tracking submodule: After receiving the reminder, the doctor arranges glycosylated hemoglobin testing and updates the electronic medical record. The module continues to loop track Mr. Wang's blood glucose indicators and glycosylated hemoglobin results until the abnormal record is properly handled and ensures that the handling process and results are recorded in the electronic medical record.

[0797] Electronic medical record automatic generation module operation: When Mr. Wang's abnormal record is confirmed and handled (i.e., the doctor analyzes the glycosylated hemoglobin test results and adjusts the treatment plan), the electronic medical record automatic generation module automatically integrates the abnormal record (including blood glucose monitoring results, doctor's analysis and diagnosis opinions, glycosylated hemoglobin test results, etc.) and its handling process, results, etc. Information is integrated to generate a standardized electronic medical record.

[0798] Results

[0799] Through the electronic medical record system of medical abnormal records, Mr. Wang's suspected diabetes was timely and effectively managed and tracked. The system not only improves the doctor's work efficiency, but also ensures the completeness, accuracy and timeliness of the medical record. This provides strong support for Mr. Wang's subsequent treatment and helps to continuously improve the quality of medical care.

[0800] Application of electronic medical record symptom recording method in chronic obstructive pulmonary disease (COPD) management

[0801] Patient background: Patient name: Zhao Min, age: 72 years old, gender: female, department: respiratory medicine, chief complaint: long-term smoking history, cough and sputum have worsened in the past year, activity tolerance has decreased significantly, and respiratory difficulty has occurred recently, especially when climbing stairs or walking quickly.

[0802] Step implementation details

[0803] Step 1: Entry and preliminary verification of symptom information: Zhao Min visits the respiratory medicine clinic, and the doctor inputs her initial symptom information, including a long history of smoking, worsening cough and sputum (for nearly a year), decreased exercise tolerance, and dyspnea (especially when climbing stairs or walking quickly), through the hospital's electronic medical record system input terminal.

[0804] Preliminary verification: After the system receives this symptom information, it immediately performs preliminary verification to check whether the information format is correct, whether there are garbled codes, missing fields, or obvious logical errors. The verification result shows that the information format is correct and the content is complete, and the preliminary verification is passed.

[0805] Step 2: Retrieval, intelligent update, and supplement of symptom records

[0806] New symptom record: Since Zhao Min is visiting the hospital for the first time, there is no symptom record for her in the system. The system automatically creates a new record based on the pre-set symptom record template, which includes key information fields such as symptom nature (cough, sputum, dyspnea), duration (nearly a year), activity impact (decreased exercise tolerance), and smoking history.

[0807] Information supplement: The doctor supplements the specific characteristics of cough and sputum (cough is persistent dry cough, sputum is white mucous sputum, and the amount is moderate) and the degree of dyspnea (mild to moderate, aggravated after activity) according to Zhao Min's detailed description, and inquires whether Zhao Min has other COPD-related symptoms such as wheezing and chest tightness. At the same time, the doctor also records Zhao Min's smoking duration and daily smoking amount, as well as whether she has other underlying diseases such as hypertension and coronary heart disease.

[0808] Step 3: Standardization and depth verification of symptom information completeness

[0809] Standardization processing: The system performs in-depth standardization processing on Zhao Min's symptom information, such as describing "decreased exercise tolerance" as "decreased exercise capacity", and using uniform measurement units (such as years for smoking history and cigarettes per day for daily smoking amount).

[0810] Depth verification of completeness: The system performs completeness verification to confirm that the information contains all necessary fields and verifies the logical coherence and medical reasonableness of the information. The verification result shows that the information is complete, accurate, and reasonable, but the system still reminds the doctor to confirm whether Zhao Min has undergone lung function tests, chest CT, blood biochemistry, and other related examinations, and whether she has used bronchodilators, inhaled corticosteroids, and other COPD treatment drugs to ensure the comprehensiveness of the record.

[0811] Step 4: Secure Storage and Efficient Management of Symptom Records The system securely stores the symptom records into the electronic medical record after standardization and integrity verification. Advanced encryption technology is used to ensure that Zhao Min's symptom records are not illegally accessed or tampered with.

[0812] Efficient Management: The system provides powerful data management functions. Doctors can quickly retrieve and filter Zhao Min's symptom records by various conditions such as time range (e.g., the past year), symptom type (e.g., cough, sputum, difficulty breathing, etc.), keywords (e.g., COPD, smoking history), etc. In addition, doctors can export symptom records in Excel or PDF format for subsequent analysis and report writing, and share with other medical team members or experts during consultation.

[0813] Step 5: Intuitive Display and Convenient Interaction of Symptom Records Intuitive Display: The system provides an intuitive and easy-to-use symptom record display interface for doctors. The interface displays Zhao Min's COPD symptom changes in a clear timeline, including the onset time, frequency, and accompanying symptoms of cough, sputum, and difficulty breathing. At the same time, it highlights key information fields such as symptom nature, duration, and activity impact.

[0814] Convenient Interaction: The system supports multiple display forms such as charts and lists, making it easy for doctors to quickly understand and analyze symptom changes. In this example, the doctor chooses a timeline display form and can view symptom record details for the corresponding date by clicking on different points on the timeline. At the same time, doctors can also directly edit or add new symptom information on the display interface, such as Zhao Min's lung function test results, chest CT reports, drug treatment plans, and effect evaluations. In addition, the system provides printing and sharing functions to facilitate doctors to share symptom records with Zhao Min herself or her family members, as well as for teaching, research, or academic exchange purposes.

[0815] Example of Zhao Min's Re-visit

[0816] Background Introduction

[0817] Patient Zhao Min, female, 72 years old, has been treated for chronic obstructive pulmonary disease (COPD) multiple times. This time, she hopes to record her latest symptom changes and hopes that the doctor can refer to her past symptom records to provide more accurate treatment recommendations.

[0818] Implementation Steps

[0819] Step 1: Entry and Preliminary Verification of Symptom Information

[0820] When Zhao Min visits the doctor, the doctor inputs her initial symptom information through the hospital's electronic medical record system input terminal, including increased cough, increased sputum volume, and deepened difficulty in breathing. After receiving this information, the system immediately performs preliminary verification to check whether the information format is correct, whether it contains garbled characters, missing fields, and whether there are obvious logical errors. The verification result shows that the information format is correct, the content is complete, and the preliminary verification is passed.

[0821] Step 2: Retrieval, intelligent display, and addition of symptom records

[0822] Intelligent display of historical records: Since Zhao Min is a regular customer of the hospital, there are multiple symptom records of her in the system. The system automatically retrieves and intelligently displays her past symptom records in chronological order according to her visit ID. These records are presented in a clear timeline, including the date of each visit, main symptoms, accompanying symptoms, treatment plans, and effects, etc.

[0823] Addition of symptom records: The doctor refers to Zhao Min's historical symptom records and compares the current symptoms, finding that her cough and sputum symptoms have worsened, and the degree of difficulty in breathing has also deepened. Therefore, the doctor inputs Zhao Min's complete symptom information into the system, including the nature of the cough (from persistent dry cough to paroxysmal cough), the color and volume of sputum (from white mucus sputum to yellow pus sputum, with increased volume), and the degree of difficulty in breathing (from mild to moderate to moderate to severe). The system seamlessly connects these newly added symptom records with the historical records, achieving dynamic updating of symptoms.

[0824] Step 3: Standardization and depth verification of symptom information

[0825] The system performs deep standardization processing on Zhao Min's newly added symptom information, ensuring the use of unified medical terminology, measurement units, and format specifications. At the same time, it performs depth verification of completeness, checking whether the information contains all necessary fields and verifying the logical coherence and medical reasonableness of the information. The verification result shows that the information is complete, accurate, and reasonable, conforming to medical standards.

[0826] Step 4: Safe storage and efficient management of symptom records

[0827] The system safely and efficiently stores the symptom records that have been standardized and verified for completeness in the electronic medical record. Advanced encryption technology is used to protect patient privacy, ensuring that Zhao Min's symptom records cannot be accessed or tampered with illegally. At the same time, the system provides powerful data management functions, supporting fast retrieval and filtering according to time range, symptom type, keywords, and other conditions. The doctor can export, print, or share Zhao Min's symptom records as needed, providing strong support for subsequent diagnosis and treatment work.

[0828] Step 5: Intuitive display and convenient interaction of symptom records

[0829] The system provides a user-friendly and intuitive interface for the doctor to display the symptom records. The interface displays the changes in Zhao Min's COPD symptoms in a clear timeline, including the onset time, frequency, and changes in accompanying symptoms of symptoms such as cough, sputum, and difficulty breathing. At the same time, it highlights key information fields such as the nature and location of the symptoms. The system supports multiple display forms such as charts and lists, making it easy for doctors to quickly understand and analyze symptom changes. In addition, it provides convenient interaction functions such as clicking on the points on the timeline to view detailed symptom records, editing or adding new symptom information, etc. Doctors can easily view Zhao Min's historical symptom records and compare them with current symptoms to develop more accurate treatment plans for her.

[0830] The following is a specific example of a method for diagnosing and detecting abnormal results in the electronic medical record system described above to improve medical record records:

[0831] Patient background: Mr. Wang, 60 years old, has been to the hospital for treatment due to recent persistent chest pain, shortness of breath, and other symptoms.

[0832] Specific implementation steps

[0833] I. Construction of medical history information: Record Mr. Wang's medical history, including a 10-year history of hypertension, a 5-year history of diabetes, and no history of smoking.

[0834] Physical examination information: Record Mr. Wang's vital signs, including blood pressure, heart rate, respiratory rate, and chest pain location, nature, duration, and other physical examination information.

[0835] Examination and test results: Record ECG, blood biochemical tests (such as myocardial enzyme spectrum, blood glucose, blood lipids, etc.), chest X-ray, etc. Among them, the ECG result shows that the ST segment is significantly depressed, suggesting that there may be myocardial ischemia; blood biochemical tests show that the myocardial enzyme spectrum is elevated, further supporting the diagnosis of myocardial ischemia.

[0836] Preliminary diagnosis: Based on the medical history, physical examination and examination results, the doctor preliminarily diagnosed "suspected coronary heart disease".

[0837] II. Function setting of the diagnosis basis detection module Automatic abnormal data retrieval: The system automatically retrieves the ST segment depression of ECG and the elevated myocardial enzyme spectrum as abnormal data.

[0838] Diagnosis information matching and verification: The system checks that there is a preliminary diagnosis of "suspected coronary heart disease" corresponding to the abnormal data, and verifies the consistency of the diagnosis information and the abnormal data.

[0839] Sufficiency evaluation of diagnostic basis: The system evaluated the sufficiency of the diagnostic basis, including the history of hypertension and diabetes (high-risk factors for coronary heart disease) in the medical history information, the chest pain symptom (consistent with the symptoms of coronary heart disease) in the physical examination, and the ST segment depression and elevated myocardial enzyme spectrum in the electrocardiogram (direct evidence). The system considered that the diagnostic basis was sufficient, but recommended further coronary angiography for definitive diagnosis.

[0840] III. Intelligent recommendation of corresponding diagnosis based on abnormal results: Based on the abnormal data (ST segment depression in electrocardiogram and elevated myocardial enzyme spectrum), the system intelligently recommended "coronary heart disease" as a possible diagnosis option and displayed the relevant diagnostic basis, including the results of electrocardiogram and blood biochemical tests.

[0841] Doctor's confirmation and association: The doctor reviewed the intelligently recommended diagnosis and basis, combined with his own professional knowledge and clinical experience, confirmed the diagnosis of "coronary heart disease", and agreed that the system automatically associated the diagnosis information with the corresponding abnormal data. At the same time, the doctor decided to further arrange coronary angiography for definitive diagnosis.

[0842] IV. Perfection of medical record and reminder mechanism

[0843] Intelligent detection of potential problems: During the process of perfecting the medical record, the system intelligently detected that although the abnormal data (ST segment depression in electrocardiogram and elevated myocardial enzyme spectrum) associated with the diagnosis had been recorded, the results of coronary angiography had not been recorded.

[0844] Remind the doctor: The system automatically reminds the doctor that the results of coronary angiography have not been recorded and suggests that the doctor arrange the examination as soon as possible and supplement the record.

[0845] Doctor perfects medical record: The doctor arranges coronary angiography examination according to the system's reminder, and supplements the examination results (such as the degree of coronary artery stenosis) to the medical record. At this point, the medical record is complete and accurate, and each diagnosis has sufficient diagnostic basis as support, and each abnormal data is precisely associated with the corresponding diagnosis information.

[0846] Implementation effect

[0847] Through the above method, the electronic medical record system not only realizes the mutual detection of diagnosis and abnormal results, but also perfects the medical record, improves the quality and integrity of the medical record. At the same time, the application of intelligent recommendation module and reminder mechanism also greatly improves the work efficiency and accuracy of the doctor. Mr. Wang's medical record is now more detailed and accurate, providing strong support for subsequent treatment and follow-up.

[0848] Method embodiment for ensuring the completeness of diagnosis and treatment records

[0849] I. Construction of Medical Record Dataset

[0850] Mr. Li visited the hospital due to sudden chest pain. The hospital's electronic medical record system quickly received and integrated his medical record information, forming a comprehensive and systematic medical record dataset. This dataset includes:

[0851] History information: Records Mr. Li's chief complaint (sudden chest pain lasting more than half an hour), past medical history (hypertension, hyperlipidemia), family history (father died of heart disease), etc.

[0852] Physical examination information: Detailed records of Mr. Li's vital signs (low blood pressure, rapid heart rate, irregular heart rhythm), and cardiopulmonary auscultation results (low and dull heart sound, with murmur).

[0853] Test and examination results: ECG results show that the ST segment is significantly elevated, and the CK-MB and TnI in the myocardial enzyme spectrum examination are significantly elevated, indicating acute myocardial infarction.

[0854] Diagnosis information: The doctor diagnosed Mr. Li as "acute ST segment elevation myocardial infarction" based on the history, physical examination, and examination results.

[0855] Treatment information: The doctor immediately gave Mr. Li aspirin anti-platelet, clopidogrel anticoagulant therapy, and arranged emergency coronary intervention (PCI) and stent implantation to restore coronary blood flow.

[0856] II. Verification module of diagnosis and treatment logic relationship

[0857] The diagnosis and treatment detection module in the electronic medical record system strictly verifies the logical relationship of Mr. Li's diagnosis and treatment records:

[0858] Automatic retrieval and matching: The system automatically retrieves the medical record dataset and successfully matches the diagnosis information of "acute ST segment elevation myocardial infarction" with the treatment records of aspirin anti-platelet, clopidogrel anticoagulant therapy, and emergency coronary intervention (PCI) and stent implantation, ensuring the correspondence between diagnosis and treatment.

[0859] Treatment necessity and urgency assessment: The system analyzes Mr. Li's diagnosis information, considering that he has acute myocardial infarction, and the ECG and myocardial enzyme spectrum examination results support the diagnosis. The assessment believes that treatment is necessary and urgent. Aspirin and clopidogrel can quickly resist platelets and anticoagulants to prevent further thrombus formation, while PCI and stent implantation are key treatment measures to restore coronary blood flow and save dying myocardium.

[0860] Treatment basis verification: The system verified the treatment basis provided in the treatment record, including domestic and international treatment guidelines for acute myocardial infarction, expert consensus, and Mr. Li's specific circumstances (such as age, gender, medical history, ECG and myocardial enzyme test results, etc.). All treatment measures meet the current medical practice standards and fully consider the individual differences of the patient.

[0861] Treatment measure matching check: The system checked the matching degree of the specific treatment measures described in the treatment record and the diagnosis information. Aspirin and clopidogrel anti-platelet, anticoagulant therapy, and PCI and stent implantation therapy are all aimed at the pathophysiological process of acute myocardial infarction, and are highly matched with the diagnosis information of "acute ST segment elevation myocardial infarction", ensuring the targeting and effectiveness of treatment.

[0862] Key information record completeness check: The system checked whether all key information about diagnosis and treatment was recorded in the medical record, including diagnosis basis, treatment necessity, treatment basis, specific treatment measures, treatment time, treatment results, etc. All information is accurately and completely recorded in the electronic medical record, ensuring the completeness, accuracy and consistency of the medical record.

[0863] III. Reminder and improvement mechanism

[0864] During the construction of the medical record data set and the verification of the logical relationship between diagnosis and treatment, the system not only automatically detects and ensures the completeness of Mr. Li's medical record, but also further improves the quality of the medical record through the reminder and improvement mechanism.

[0865] System detection and reminder: During Mr. Li's anti-platelet and anticoagulant therapy with aspirin and clopidogrel, the system found that the treatment record did not include observations of drug side effects during the medical record data completeness check. Therefore, the system automatically sends a reminder to the doctor responsible for Mr. Li's treatment, asking the doctor to supplement the record of Mr. Li's reaction to the two drugs, including whether there is a tendency to bleed, allergic reaction or other discomfort symptoms.

[0866] Doctor response and improvement: After receiving the reminder, the doctor immediately reviewed Mr. Li's treatment process and inquired in detail about Mr. Li's feelings about the drugs. After confirmation, Mr. Li did not have any drug side effects. The doctor then entered the electronic medical record system and supplemented the record of drug side effect observations.

[0867] In addition, the system also has the ability to detect other potential problems. For example, if the system detects that a diagnosis has no corresponding treatment record, it will remind the doctor to supplement the treatment information; if the system detects that a treatment record is not associated with the diagnosis information, it will remind the doctor to confirm and associate the correct diagnosis information. Through these reminder mechanisms, the system ensures the completeness, accuracy and consistency of the medical record.

[0868] IV. Continuous Optimization of the System

[0869] The hospital regularly collects feedback from doctors on their actual usage and conducts in-depth analysis of medical record data to continuously optimize the electronic medical record system. For example, doctors may suggest adding new examination items or treatment methods, or provide suggestions for improving the friendliness of the system interface. The system developers will optimize the algorithms and improve the interface of the diagnosis and treatment detection module based on these feedbacks to improve the accuracy and user experience of the system.

[0870] At the same time, with the continuous progress of medical technology and the update of clinical guidelines, the system will also regularly update its built-in treatment basis library and diagnosis rule library to ensure that the completeness, accuracy and consistency of the diagnosis and treatment records in the electronic medical record always meet the current medical practice standards.

[0871] Through the above specific examples, Mr. Li's acute myocardial infarction diagnosis and treatment records are comprehensively, systematically and accurately managed, ensuring the completeness, accuracy and consistency of the diagnosis and treatment records. At the same time, the continuous optimization of the system will provide more efficient and convenient tools for future medical record management.

[0872] Specific implementation case: A treatment tracking electronic medical record method for lung cancer patients

[0873] Patient basic information: Name: Mr. Wang, age: 65 years old, gender: male, admission diagnosis: primary lung cancer (T3N1M0, stage IIIA)

[0874] I. Construction of treatment item database

[0875] In Mr. Wang's electronic medical record system, a comprehensive and real-time updated treatment item database is constructed. This database records all the treatment item information received by Mr. Wang, including but not limited to:

[0876] Operation record: lobectomy (right upper lobe), operation time, location, main surgeon, etc.

[0877] Drug use record: name, specification, dosage, frequency of use, start and end date of chemotherapy drugs (such as cisplatin, gemcitabine).

[0878] Consumable use record: types, use location, use duration of chest drainage tube, suture line, etc.

[0879] Other treatment information: radiotherapy plan, use of targeted therapy drugs, etc.

[0880] II. Dynamic tracking of treatment items

[0881] Operation and procedure tracking: Key information about Mr. Wang's lobectomy surgery was recorded, and his recovery was continuously monitored, including wound healing, lung function recovery, and the presence of complications (such as lung infection, pleural effusion).

[0882] Drug usage tracking: The use of chemotherapy drugs was meticulously recorded, and their antibacterial effects (although chemotherapy drugs do not involve antibacterial activity, this refers to monitoring their killing effect on tumor cells), drug resistance (observing whether the tumor develops resistance to chemotherapy drugs), and side effects (such as nausea, vomiting, and bone marrow suppression) were continuously evaluated.

[0883] Consumable usage tracking: The use of chest drainage tubes was recorded, tracking the nature, quantity, and duration of the drainage fluid, as well as the healing of sutures.

[0884] Three, Establish the Effect Record and Analysis Module

[0885] In the electronic medical record system, an effect record and analysis module was established for Mr. Wang. The functions of this module include:

[0886] Tracking reminders: The system automatically sends treatment progress reminders to Mr. Wang and the medical team, such as chemotherapy cycle reminders and radiotherapy plan execution reminders.

[0887] Record reminders: Remind medical personnel to timely record Mr. Wang's treatment information (such as post-chemotherapy blood routine and liver and kidney function test results) in the electronic medical record.

[0888] Results display: The treatment effects of Mr. Wang were recorded in the form of text and pictures, such as the comparison of CT images before and after chemotherapy, which directly shows the changes in tumor size.

[0889] Four, Implement the Cycle Tracking Mechanism

[0890] Based on the analysis of Mr. Wang's treatment effects, the system automatically determines whether further electronic medical record tracking is needed. For example, after several cycles of chemotherapy, the system automatically determines whether to adjust the chemotherapy regimen or proceed to the next treatment (such as radiotherapy) based on Mr. Wang's tumor size reduction and physical condition. Through this mechanism, the continuity and integrity of Mr. Wang's treatment are ensured.

[0891] Five, Establish the Treatment Tracking Module System

[0892] In the electronic medical record system, an independent tracking module was established for each treatment item of Mr. Wang. These modules contain patient tracking functions and medical personnel tracking functions. Mr. Wang can view his own treatment records within the authorized scope to understand the treatment progress and effects. Medical personnel can track Mr. Wang's treatment in real time through these modules to make more accurate diagnoses and treatment decisions.

[0893] Through the application of this treatment tracking electronic medical record recording method, Mr. Wang's treatment process is comprehensively, accurately and real-time recorded and tracked, ensuring the continuity and integrity of the treatment, improving the medical quality and efficiency. At the same time, it also provides Mr. Wang with a more convenient and intuitive information query method, improving patient satisfaction and medical experience.

[0894] Specific embodiment: A method for extracting symptoms and signs in electronic medical records, extracting and analyzing the changes in symptoms and signs of foot ulcers in a diabetic patient

[0895] I. Define symptoms and signs and time range

[0896] Select symptoms and signs: In this case, the symptom to be extracted is "foot ulcer". This is a common complication of diabetic patients, and its monitoring and analysis are crucial for assessing disease progression and treatment effectiveness;

[0897] Set time frame: Assume the patient was diagnosed with diabetes on January 1st of this year and has been experiencing foot ulcer symptoms since April. Therefore, the time range is set from January 1st of this year to the current date (assuming December 31st), but the focus is on the changes in symptoms and signs from April to December;

[0898] II. Retrieve and obtain electronic medical records

[0899] Data retrieval: Use the search function of the electronic medical record system, input "foot ulcer" and "diabetes" as keywords, and set the time range from January 1st to December 31st. The system retrieves all relevant medical records, including outpatient records, inpatient records, examination reports, etc.;

[0900] Screening and sorting: Screen the retrieved medical records to ensure that all records are directly related to foot ulcers. Sort these records by date of visit for subsequent analysis;

[0901] III. Extraction of symptoms and signs data

[0902] Symptoms and signs extraction:

[0903] Text description: Extract detailed descriptions of foot ulcers in medical records, such as ulcer location, size, color, shape, whether accompanied by infection, pain level, etc.;

[0904] Picture extraction: Extract photos of foot ulcers from medical records, which record the changes in ulcers from the initial stage to the healing process;

[0905] Video and audio extraction: Although this case may contain less video data, audio recordings of the doctor's examination of the patient's foot can be extracted to understand the doctor's assessment and recommendations;

[0906] IV. Presentation of Symptoms and Signs

[0907] Presentation method selection:

[0908] Textual presentation: The extracted textual descriptions are organized into a structured report, detailing the changes in the ulcers at different time points.

[0909] Image presentation: The extracted image data is arranged in chronological order to form a timeline display of ulcer changes.

[0910] Video and audio presentation: Although the video data is limited in this example, the audio data can be compiled into audio files for doctors or researchers to listen to.

[0911] Time range annotation: When presenting changes in ulcers, clearly annotate the time points of each image or text description to clearly show the progression of the ulcer;

[0912] V. Access to and Use of Data

[0913] Viewing function: Provides convenient online viewing function, allowing doctors or researchers to access these symptom and sign data at any time for detailed viewing and analysis;

[0914] Analysis and Utilization:

[0915] Trend analysis: By analyzing the changes in ulcers at different time points, the effectiveness of the treatment plan can be evaluated;

[0916] Disease diagnosis assistance: These symptoms and signs can serve as a basis for auxiliary diagnosis, helping doctors to more accurately judge the patient's condition; Treatment effect evaluation: By comparing the changes in ulcers before and after treatment, the efficacy of the treatment plan can be evaluated, providing a basis for adjusting the treatment plan.

[0917] The following is an example of the application of the national electronic medical record system in the precision treatment of Mr. Wang's cardiovascular disease.

[0918] Patient basic information: Name: Mr. Wang, Age: 72, Gender: Male

[0919] Chief complaint: Frequent chest tightness, shortness of breath, and palpitations recently, occasionally accompanied by mild chest pain.

[0920] Past medical history: Hypertension (10-year history), type 2 diabetes (5-year history), mild dyslipidemia. Case background: Mr. Wang is a retired teacher who has long suffered from hypertension and diabetes and usually relies on the community hospital for chronic disease management. Recently, Mr. Wang felt that his physical condition had declined significantly, especially his heart discomfort, which gradually worsened. Therefore, he decided to go to the city hospital with several old friends for further examination.

[0921] Case implementation process:

[0922] Information entry and integration:

[0923] Medical professional end:

[0924] Grandpa Wang first went to the community hospital. The doctor queried his past medical history, including previous electrocardiograms, echocardiograms, and blood biochemistry test results, through the national electronic medical record system.

[0925] The community doctor conducted a preliminary physical examination on Grandpa Wang and entered new examination data and symptom descriptions into the system.

[0926] Grandpa Wang was then transferred to a municipal hospital. The cardiovascular specialist obtained Grandpa Wang's complete health record through the system and conducted further specialized examinations, such as coronary CTA and dynamic electrocardiogram. The examination results were also entered into the system.

[0927] Patient direct correlation end:

[0928] Grandpa Wang entered his daily monitoring data such as blood pressure, blood sugar, and heart rate through the patient end function of the system.

[0929] Grandpa Wang's children obtained authorization through the system and could view and update his health information.

[0930] Patient companion end:

[0931] On the way to the hospital, Grandpa Wang suddenly felt his chest pain intensifying. His friend accompanying him quickly contacted the emergency center and described Grandpa Wang's symptoms and current situation.

[0932] After the emergency personnel arrived on the scene, the friend accompanying Grandpa Wang entered his current symptoms, past medical history, observations during the emergency process (such as Grandpa Wang's consciousness, breathing, etc.), and emergency measures (such as cardiopulmonary resuscitation, oxygen administration, etc.) into the system through the patient companion end of the national electronic medical record system. These information provided important references for emergency personnel and key evidence for subsequent medical treatment.

[0933] The emergency personnel also entered the preliminary examination results (such as electrocardiogram, blood sugar, etc.) into the system through the medical professional end to ensure the completeness and accuracy of the information.

[0934] Information storage and synchronization: All of Grandpa Wang's health information, including information from the medical professional end, patient direct correlation end, and patient companion end, were accurately saved to the national electronic medical record cloud server and synchronized in real-time with all electronic medical record servers of medical institutions he had previously visited. This ensured that Grandpa Wang's health information was complete, accurate, and traceable at any time.

[0935] Patient Health Information Integration: The system automatically integrates Mr. Wang's health information from different sources to generate a comprehensive patient health profile. This profile includes Mr. Wang's medical records, diagnosis information, test results, treatment plans, medication records, and other comprehensive information. Based on this profile and the latest test results, the cardiovascular specialist diagnoses Mr. Wang's condition and develops a personalized treatment plan and prevention plan.

[0936] Intelligent Analysis and Early Warning: The system conducts intelligent analysis based on Mr. Wang's health information, predicts his future cardiovascular disease risks such as myocardial infarction and heart failure, and provides personalized prevention recommendations. The system also detects potential interaction risks in Mr. Wang's current medication to ensure medication safety.

[0937] Data Access Rights and Security Control: The system implements strict data access rights management to ensure that only authorized medical professionals, Mr. Wang himself, and his children can access his health information. In addition, the system uses encryption technology to ensure security during data transmission and storage.

[0938] Treatment Results: With the support of the national electronic medical record system, Mr. Wang's cardiovascular disease has been treated in a timely and effective manner. Doctors can comprehensively and accurately understand his health status and past medical history, develop personalized treatment plans and prevention plans for him. At the same time, Mr. Wang can easily view and manage his own health information, improving his health awareness and self-management ability. With the support of the national electronic medical record system, Mr. Wang's cardiovascular disease has been effectively controlled, and his quality of life has been significantly improved.

[0939] This example further demonstrates the advantages of the national electronic medical record system in improving medical service efficiency and quality, promoting medical resource sharing and optimal utilization, and enhancing patient health information management and security. In particular, the information entry function of the patient's accompanying person in emergency situations provides valuable reference information for doctors, saving valuable time for patient treatment.

[0940] A detailed implementation case of an electronic medical record system in the process of fire rescue and treatment, taking patient Zhanghua as an example, fully demonstrates the specific functions and collaboration mechanisms of each module, characterized in that the system application includes:

[0941] I. Information entry module

[0942] Medical professional end:

[0943] 120 First-aid personnel quickly enter Zhang Hua's basic information (name, age, gender, contact information, ID number) and preliminary injury description (such as burn location, degree, and consciousness state) at the fire scene through the mobile application.

[0944] Upon arrival at the hospital, emergency department physicians and nurses further record vital signs (blood pressure, heart rate, respiratory rate, body temperature), burn assessment (burn area, depth, location), preliminary treatment plan (such as fluid replacement, pain relief, debridement), and nursing operations (such as establishing intravenous access, wound dressing) in detail.

[0945] Other relevant information about the patient:

[0946] Firefighters enter key information at the fire scene through the dedicated law enforcement equipment or mobile application of the fire department, including the time and location of the fire, the size of the fire, the main burning material, Zhang Hua's escape route, the rescue process, and on-site first aid measures (such as fire extinguishing, moving away from the fire, and preliminary wound treatment).

[0947] II. Information Storage Module

[0948] All patient health information entered through the medical professional end and the patient's other relevant end, including first aid records, physical examination results, treatment plans, nursing records, test and examination results, etc., are accurately saved to the corresponding module or location of the information storage module.

[0949] The information storage module ensures the integrity, accuracy, and traceability of the data, recording the source, entry time, and modification history of each piece of information through time stamps and unique identifiers.

[0950] III. Electronic Medical Record Automatic Generation Module

[0951] System default rules: According to hospital internal regulations and medical standards, the system automatically identifies the type of electronic medical record that Zhang Hua needs to complete upon admission (such as admission record, first course record).

[0952] Automatic filling generation: Based on the entered health information, the system automatically fills in the electronic medical record, including patient basic information, medical history record, physical examination result, preliminary diagnosis, treatment plan, etc.

[0953] IV. Treatment Tracking Module Real-time Recording: The treatment tracking module records the surgical operations (such as debridement, skin grafting) received by Zhang Hua, the use of drugs (such as antibiotics, painkillers, and fluid replacement), and the use of consumables (such as burn dressings and bandages) in real time.

[0954] Effect Record and Analysis: An effect record and analysis module is established to record the changes in key indicators during treatment (such as wound healing, infection indicators, and pain scores), and to provide treatment progress reminders (such as dressing change time, review time) and medication reminders (such as antibiotic use period, pain medication use frequency).

[0955] Five, Accurate Extraction of Symptom Signs Module: The symptom signs extraction module accurately extracts Zhanghua's burn site symptom signs information from the electronic medical record, including wound size, color, exudate, and pain level.

[0956] Diversified Display: Through various forms such as text description, pictures (wound photos), videos (wound change records), and audio (patient's self-reported pain experience), the symptom signs and their changes over time are visually displayed.

[0957] Six, Data Synchronization and Access Control Module: The data synchronization and access control module ensures that Zhanghua's health information in all medical institutions nationwide is synchronized to the national electronic medical record cloud server in real time, realizing cross-institutional data sharing.

[0958] Access Control: Strict data access permission management is implemented to ensure that only authorized medical professionals, Zhanghua, and his authorized family members can access the corresponding health information. At the same time, patient self-determination permission setting function is provided, allowing Zhanghua to control the access permission of his health information through the system.

[0959] Seven, Intelligent Analysis and Early Warning Module: The intelligent analysis and early warning module conducts in-depth mining and analysis of Zhanghua's health information, predicting potential complication risks (such as infection, shock, and multiple organ dysfunction syndrome).

[0960] Early Warning Function: Based on the analysis results, the system sends early warning information to the medical team in a timely manner, reminding them to pay attention to potential health problems or take necessary medical measures. At the same time, disease risk assessment, drug interaction detection, and other functions are provided to provide scientific basis for treatment decisions.

[0961] In summary, the electronic medical record record and management system provides comprehensive, accurate, and timely information support for Zhanghua's fire rescue and treatment process through the close cooperation and efficient operation of various modules, significantly improving the efficiency and quality of medical treatment.

Claims

1. A method for recording electronic medical records, characterized in that, Includes the following steps: Step 1: Information Entry Through diverse data entry terminals, patients' health information is collected and recorded comprehensively and systematically. These data entry terminals are specifically categorized into the following three types: The medical professional side consists of physicians, nurses, medical technicians, and authorized medical personnel, specifically including: Physicians: This includes 120 emergency medical personnel, emergency room physicians, outpatient physicians, inpatient physicians, and other physicians who have direct contact with patients; Nurses include emergency room nurses, outpatient nurses, inpatient nurses, and other nurses who have direct contact with patients. Medical technicians: Personnel in professional and technical fields such as medical laboratory technicians, medical imaging technicians, and pathology diagnostic technicians; Authorized medical personnel: interns, visiting physicians, intern nurses, medical assistants, and other officially authorized medical personnel who can input health information; The patient's direct stakeholders consist of the patient, the patient's family, and authorized personnel, including: Patients: I have the right to directly participate in the entry and updating of my health information; Patient's family members and authorized personnel: With the patient's explicit authorization, they may enter or verify health information on their behalf; Other relevant parties to the patient include traffic police, firefighters, neighbors, patients' companions, and passersby. These individuals may provide valuable information related to the patient's health in specific situations. Step Two: Information Storage The entered patient health information is accurately saved to the corresponding module or location in the electronic medical record system to ensure the integrity, accuracy and traceability of the information.

2. The electronic medical record recording method according to claim 1, wherein the information entry method is further divided into two modes: routine entry and designated entry; I. The standard data entry modes include automatic recognition entry and manual selection entry: 1) The automatic recognition and input: Step 1: Information Submission: The data entry terminals (including but not limited to medical professionals, patients directly related to the patient, and other relevant patient terminals) are responsible for entering the patient's health information; Step 2: Intelligent Recognition: The system uses a pre-established electronic medical record knowledge base to intelligently recognize the health information submitted by the input terminal; Step 3: Data storage and verification: 3.1 Automatic Saving: Successfully identified health data will be automatically saved to the corresponding module or location to ensure the accuracy of the information and the correctness of the location; 3.2 Unidentified Data Processing: For unidentified health data, the system temporarily saves it to the "Unidentified Data Unit" and automatically triggers a prompt to notify relevant personnel for manual review and identification. After manual identification, this data will be correctly classified and saved. Simultaneously, the knowledge base will be further improved to better handle similar information in the future. 2) Manual selection and input: Step 1: Information Module Selection: Users at the data entry end carefully select the modules corresponding to the health information to be entered from a preset, structured document module set according to their actual needs. These preset modules cover multiple aspects such as basic patient information, medical history records, physical examination, examination results, diagnostic information, and treatment plans, ensuring the comprehensiveness and systematic nature of the information. Step Two: Information Entry and Verification After selecting a module, the user on the data entry end needs to enter the patient's health information one by one according to the data entry requirements and format of that module; Step 3: Information Upload and Automatic Allocation After completing the data entry, the user uploads the information to the electronic medical record system's database. Upon receiving the uploaded information, the system automatically assigns it to the appropriate module or location based on its type and attributes. This process ensures orderly storage and convenient retrieval of information. II. The designated data entry modes include data entry from the medical end directly related to the patient and data entry from the system-designated entry end. 1) The medical terminal specifies the patient's directly related terminal entry: Step 1: The medical staff (doctors, nurses, etc.) select the health information content that needs to be obtained from the patient's directly related parties (patient, patient's family members, and authorized personnel) from the electronic medical record system according to the needs of diagnosis and treatment; Step 2: The system sends a push notification to the patient's directly relevant end, clearly informing them of the specific health information that needs to be entered; Step 3: The patient's directly related end enters the corresponding health information based on the push notification content; Step 4: The medical staff can view the health information entered by the patient in real time, and after confirming that it is correct, save it to the electronic medical record system to ensure the integrity and accuracy of the information; 2) The system specifies the input terminal for data entry: Step 1: Based on the system's preset rules or triggering conditions, the system automatically identifies the electronic medical record that needs to be completed; Step 2: The system further analyzes the electronic medical records that have been completed and the electronic medical records that need to be completed in the current period to determine the required health information; Step 3: The system intelligently determines the health information that each input terminal (medical professional terminal, patient-related terminal, and other patient-related terminals) can provide, and sends the required health information to the corresponding input terminal; Step 4: The data entry terminal enters the required health information according to the system prompts, and the system automatically stores it into the electronic medical record system to ensure the timeliness and accuracy of the information.

3. According to claim 1, a method for recording electronic medical records, wherein the health information is entered in the form of images, text, video, or audio / voice: The images are used to record the patient's skin and soft tissue conditions, including but not limited to skin diseases such as eczema, dermatitis, and urticaria; soft tissue injuries such as abrasions, contusions, crush injuries, burns, and frostbite; and musculoskeletal disorders such as fractures, joint dislocations, and muscle strains. In addition, the images are suitable for recording before-and-after comparisons of surgical procedures, as well as the color and characteristics of physiological samples such as vomit, stool, and sputum. These images should be of high resolution to facilitate accurate assessment of the patient's condition by the physician. The written form serves as the foundation of medical records, used to record in detail the patient's condition, medical history, diagnosis, treatment plan, medical orders, follow-up records, and other information. Written records should be accurate, clear, and adhere to standardized medical terminology to ensure accuracy and readability. The video format is used to record the patient's dynamic condition, including but not limited to breathing, symptoms during epileptic seizures, the evolution of Parkinson's disease symptoms, changes in symptoms such as hemiplegia, aphasia, and sensory disturbances in patients with cerebrovascular diseases, as well as surgical procedures and wound healing. Audio / voice recording: Used to record abnormal sounds such as the patient's cough, breath sounds, and heart sounds, as well as the entire process of doctor-patient communication. Audio / voice recording provides an important auxiliary tool for doctors to diagnose respiratory and cardiovascular diseases.

4. According to claim 1, a method for recording electronic medical records, wherein the health information input device includes a portable device, a computer, professional examination and testing instruments and equipment: The portable devices mentioned include, but are not limited to, smartphones, tablets, and other mobile devices with photo, video, and audio recording functions. These devices should support high-definition photo, video, and audio recording functions and have sufficient storage space. They should also have professional medical applications or software installed to facilitate the direct uploading of collected health information to the electronic medical record system. Portable devices allow patients and medical staff to record medical information anytime, anywhere, improving the flexibility and convenience of information entry. The computer, serving as a fixed workstation, should be equipped with electronic medical record management software that supports complex tasks such as text editing, image processing, video playback, and audio analysis. Information entered on the computer should be more detailed and comprehensive to facilitate in-depth analysis and diagnosis by doctors. The professional examination and testing instruments and equipment mentioned include, but are not limited to, electronic stethoscopes, electronic thermometers, electronic pulse oximeters, electronic blood pressure monitors, respiration analyzers, pulse oximeters, and other medical professional equipment. These devices should support wireless transmission methods such as Bluetooth and Wi-Fi to upload the collected physiological data to the electronic medical record system. Furthermore, these devices should possess accuracy and reliability to ensure the accuracy and credibility of the data.

5. According to claim 1, a method for recording electronic medical records, wherein the information storage method comprises the following steps: Step 1: Document Structure Standardization and Information Entry System Construction Document structure design: Following the evaluation standards for the application level of electronic medical record systems, a modular document structure containing the patient's health information throughout the entire life cycle is designed. Specifically for physical examination information, such as inspection, palpation, percussion, and auscultation, a detailed multimedia storage module is designed to support the storage of various data formats such as images, videos, and audio. Unique Identifier Assignment: Assign a unique identifier to each type of health information and accurately link it to the corresponding multimedia storage area based on the information category to ensure the organization and traceability of the data; Diverse data entry integration: Integrating medical professionals (including physicians, nurses, medical technicians and authorized medical personnel), patients directly related to the data entry (patients, family members and authorized representatives), and other patients related to the data entry (such as traffic police, firefighters, witnesses, etc.) to achieve comprehensive and multi-channel collection of health information; Step 2: Information storage and multimedia data association Health information storage: Accurately map the entered patient health information to the designated modules of the electronic medical record to ensure the accurate storage of information; Physical examination data association: Physical examination information needs to be accurately linked to the corresponding multimedia storage table according to its category (inspection, palpation, percussion, auscultation, pulse diagnosis, etc.) to enhance the integrity of the data and the ability to trace its history. Multimedia and text data coexist: The multimedia storage table not only saves the original data (images, videos, audio), but also includes a text summary of the multimedia information. The two complement each other, which facilitates subsequent clinical analysis and scientific research applications. Step 3: Device and data synchronization and user access control Automatic integration of device data: Supports real-time or scheduled uploading of data from medical devices provided by medical institutions and those provided by patients (electronic stethoscopes, thermometers, pulse oximeters, blood pressure monitors, respiration meters, blood glucose meters, etc.), achieving seamless integration of health monitoring data; Multi-role collaborative access: Medical professionals, patients directly related to the system, and other related parties can all access the same electronic medical record system, but access permissions and scope strictly follow the user role allocation principle to ensure information security and privacy protection; Data entry and operation record: Allows different users to collaboratively enter data within the same module, while the system automatically records the historical trajectory of each operation to ensure data accuracy and traceability of responsibility.

6. A method for automatically generating electronic medical records, characterized in that, Includes the following steps: Step 1: Selection and Creation of Electronic Medical Records 1.1 Manual Selection and Creation: Medical professionals manually select and create corresponding electronic medical record templates based on the patient's specific treatment needs and the electronic medical record management and writing standards; 1.2 Automatic Identification and Creation: Based on the system's preset rules or triggering conditions, the system automatically identifies the electronic medical record to be completed and automatically creates the corresponding electronic medical record template; 1.3 Automatic identification and manual selection creation: Based on the system's preset rules or triggering conditions, the system automatically identifies the electronic medical records that need to be completed, and medical professionals select from them to create electronic medical record templates; Step 2: Obtaining and populating health information; 2.1 Determination of Health Information Needs: The system automatically determines the health information to be collected based on the type and writing specifications of the created electronic medical record template, including but not limited to patient basic information, symptoms, physical examination, diagnostic information, treatment plan, examination, and examination results; 2.2 Collection of health information from multiple channels: Health information is collected from medical professionals, patients' directly related parties, and other relevant parties, and the data source is indicated. 2.3 Data Integration and Verification: The system will integrate data collected from different channels and conduct strict verification in accordance with electronic medical record writing standards to ensure the integrity, accuracy and consistency of the data; For missing, incorrect, or inconsistent data, the system will automatically prompt the relevant data entry end to supplement, correct, or verify it; Step 3: Generation, review, and storage of electronic medical records The system automatically generates electronic medical records based on the integrated data and preset electronic medical record templates; The generated electronic medical records must be reviewed and confirmed by medical professionals to ensure that they meet medical standards and quality requirements; Once approved, the system securely stores the electronic medical record in the electronic medical record management system and provides efficient query and access functions so that medical professionals can view, update, and share patients' electronic medical record information at any time. At the same time, the system adopts appropriate encryption and access control mechanisms to ensure the security and privacy protection of electronic medical record information.

7. According to claims 2 and 6, based on preset rules or triggering conditions, the system automatically identifies the electronic medical record to be completed, including the following steps: Step 1.2.1: Time Information Acquisition: The system acquires the current time information in real time, which serves as the basis for electronic medical record recognition; Step 1.2.2: Required intelligent recognition of electronic medical records: Time-based electronic medical record recognition: The system automatically identifies the electronic medical records that need to be completed at the current time point according to medical standards and hospital internal regulations, such as the admission interview record, admission record and initial medical record record that should be completed when the patient is admitted. Electronic medical record recognition based on medical order information: The system parses the content of medical orders and identifies the electronic medical record to be completed based on the key information in the medical orders; Electronic medical record identification based on test and examination results: The system monitors test and examination results in real time. For abnormal or critical values, it automatically identifies the corresponding electronic medical record that needs to be completed. If a critical value is identified, a critical value record should be written and recorded in the electronic medical record. Electronic medical record recognition based on consultation information: After receiving consultation opinions, the system identifies the corresponding electronic medical records that need to be completed based on the consultation opinions; Electronic medical record recognition based on accounting items: The system automatically identifies the electronic medical record that needs to be completed based on the accounting item; for example, when accounting operations and treatments are performed, the corresponding electronic medical record records for the operations and treatments should be completed accordingly. Electronic medical record recognition based on surgery completion time: Upon recognizing the completion of surgery, the system should automatically prompt for the completion of surgical records, the first postoperative progress note, etc., according to the time nodes stipulated by the hospital. For example, the surgical record should be completed within 24 hours after the surgery, and the first postoperative progress note should be completed within 6 hours after the surgery. Identification based on pre-defined associated electronic medical records: The system determines other medical records that need to be completed according to pre-defined association rules. For example, a surgical consent form is associated with a preoperative summary and a preoperative discussion record. When a surgical consent form is created, the system should simultaneously prompt for the creation of a preoperative summary and a preoperative discussion record. Electronic medical record recognition based on other medical data: The system continuously monitors various data during the medical process, including information from each stage of treatment and examination; when the system detects that a medical process (such as treatment) has been completed, it automatically triggers the corresponding medical record recognition mechanism. This identifies the treatment records required by medical staff, ensuring the completeness and accuracy of medical records. Step 1.2.3: The system has completed the real-time synchronization and updating of the status information of completed medical records; Step 1.2.4: The intelligent medical record judgment system for pending completion intelligently judges the electronic medical records to be completed based on the identified electronic medical records that need to be completed and the current status of completed medical records.

8. An electronic medical record recognition method based on medical order information, characterized in that, The process of identifying the electronic medical records that need to be completed from medical orders; Includes the following steps: Step S1: Obtain the patient's medical orders; Step S2: By extracting keywords from the medical order information, identify at least the following entity types: Keywords indicating the severity of the illness (e.g., severe illness, critical illness); Surgical / procedure related keywords (such as the name of the surgery / procedure); Drug-related keywords (such as drug name, dosage, and route of administration); Inspection / testing keywords (such as inspection items, test items); Nursing / Special Instructions Keywords (such as fasting requirements, postural restrictions); Step S3: Based on the type and content of the extracted keywords, identify the electronic medical record to be completed, specifically including: Based on keywords indicating the severity of the illness (such as serious illness, critical illness): Identify electronic medical records that require the completion of serious illness or critical illness notification forms and the reasons for issuing this medical order; Based on surgical / procedural keywords: Identify electronic medical records that require completion of surgical / procedural risk disclosure forms and the reasons for issuing this medical order; Based on medication-related keywords: Identify electronic medical records that need to be completed, including the reasons for using the drug, dosage, and route of administration; Based on examination / testing keywords: Identify electronic medical records that require order placement and include the reason for requesting the examination / testing; Based on nursing / special instructions keywords: Identify electronic medical records that require the issuance of the reason for the nursing / special instruction.

9. An electronic medical record system for recording medical abnormalities, characterized in that, include: Abnormal Record Detection and Alert Module: Used to detect abnormal records generated during medical procedures, including but not limited to examination and test data, as well as results collected by instruments and equipment. When an abnormal record is detected, an alert signal is triggered. Electronic Medical Record Retrieval and Analysis Module: Upon responding to an alert signal, this module will automatically search for relevant abnormal records in the electronic medical record system. If the abnormality is not recorded in the system's electronic medical records or the medical staff's analysis process is missing, the module will send detailed prompts to the medical staff through a preset communication method. Anomaly Record Handling and Detection Module: This module monitors whether medical staff have taken appropriate measures based on the analysis results. If the system detects an anomaly record that has not been processed, it will automatically send a processing prompt to the medical staff. The anomaly log tracking module further includes: The review and observation time acquisition submodule automatically sets and manages the review and observation time for indicators that need to be tracked based on the type and severity of abnormal records. The medical record tracking submodule is used to track the results of follow-up examinations and check whether these results have been accurately and timely recorded in the electronic medical record. The reminder submodule sends reminders to medical staff via a preset communication method when the follow-up examination and observation time arrives, ensuring that the follow-up examination and recording are carried out on time; Cyclic Tracking Submodule: Based on clinical needs, continuous cyclic tracking is performed until abnormal records are properly handled, and the handling process and results are fully recorded in the electronic medical record; Electronic medical record automatic generation module: After an abnormal record is confirmed and processed, this module automatically integrates the abnormal record, its processing process, results and other information to generate a standardized electronic medical record.

10. A method for recording symptoms in electronic medical records, characterized by the following steps: Step 1: Input and preliminary verification of symptom information The system receives preliminary symptom information from the input terminal and performs initial verification. Verification includes checking the format of the information, whether it contains garbled characters, missing fields, and obvious logical errors. This step ensures the preliminary completeness and accuracy of the information, laying the foundation for subsequent processing. Step 2: Retrieval, intelligent updating, and supplementation of symptom records Create a new symptom record: If no symptom record for this patient exists in the system, the system will automatically create a new record based on a pre-set, well-structured symptom record template. The template covers key information fields such as symptom nature, specific location, duration, intensity / severity, evolution trend, and triggering or aggravating factors. The data entry end needs to supplement and improve any descriptive information that may be missing in step 1 to ensure the comprehensiveness and standardization of the record; Intelligent display and addition of historical records: If the system already contains symptom records for the patient, it will automatically retrieve and intelligently display the historical symptom records in chronological order. Users can intuitively compare historical and current symptoms, and after referring to the historical records, input complete information about the current symptoms to achieve dynamic symptom updates; Step 3: In-depth verification of the standardization and completeness of symptom information The system performs in-depth standardization on the received symptom information to ensure the use of consistent medical terminology, units of measurement, and formatting standards. Simultaneously, it conducts in-depth integrity checks, verifying that the information includes all necessary fields and confirming its logical coherence and medical rationale. If the information is incomplete or contains errors, the system will issue clear and explicit prompts to the user through the input terminal, requesting the user to supplement or correct the information until it meets the standards of completeness, accuracy, and reasonableness. Step 4: Secure storage and efficient management of symptom records The system securely and efficiently stores standardized and integrity-verified symptom records into electronic medical records, using advanced encryption technology to protect patient privacy. It also offers powerful data management features, supporting quick searching and filtering based on various criteria such as time range, symptom type, and keywords. Users can also export, print, or share data as needed to meet diverse requirements. Step 5: Intuitive display and convenient interaction of symptom records The system provides an intuitive and user-friendly symptom record display interface based on user needs. The interface presents the symptom progression in a clear timeline format, highlighting key information fields such as the nature and location of the symptoms. The system supports various display formats, including charts and lists, facilitating quick understanding and analysis of symptom changes. In addition, it provides convenient interactive functions, such as clicking on points on the timeline to view detailed symptom records, edit or add new symptom information, etc., to improve the user experience.

11. A method for mutual detection of diagnoses and abnormal results and for improving electronic medical record records in an electronic medical record system, characterized in that, The method includes: I. Construction of the medical record dataset: In an electronic medical record system, the following information is received, integrated, and stored to form a comprehensive and systematic medical record dataset: the patient's medical history information, physical examination information, results of various examinations and tests, as well as diagnostic and treatment information; II. Diagnostic basis and detection module function settings: A diagnostic criteria testing module is established, which has the following functions: Automatic abnormal data retrieval: It can automatically retrieve medical history, physical examination, examination and test results in medical record datasets and accurately identify abnormal data; Diagnostic information matching and verification: For each abnormal data, determine whether there is corresponding diagnostic information; Assessment of the sufficiency of diagnostic evidence: For each diagnostic piece of information, verify the sufficiency of its diagnostic evidence, which may include various forms such as text, images, videos, and audio. Simultaneously, verify the medical history, physical examination, tests, and laboratory results cited in the diagnostic information to ensure consistency between abnormal data and the diagnostic information; III. Intelligent Recommendation Module for Diagnosing Abnormal Results: An intelligent diagnostic recommendation module for abnormal results is established. This module can intelligently analyze and recommend or suggest possible diagnostic options to doctors based on the identified abnormal data, while displaying relevant diagnostic evidence. After the doctor confirms the diagnosis, the module can automatically associate the diagnostic information with the corresponding abnormal data. IV. Mechanism for Improving and Reminding Patients Regarding Medical Records: A reminder and improvement module has the following functions: Intelligent detection of potential problems in medical record datasets, such as abnormal data that is not associated with a diagnosis or abnormal diagnostic information that is not recorded; When a problem is detected, the system automatically sends clear and specific reminders to the doctor, guiding them to improve electronic medical records. This ensures that every diagnosis is supported by sufficient diagnostic evidence, and that every abnormal data point is accurately linked to the corresponding diagnostic information, thereby improving the quality and completeness of medical records.

12. A method for ensuring the integrity of diagnostic and treatment records in an electronic medical record system, characterized in that, The method includes: I. Construction of the medical record dataset: In an electronic medical record system, the following information is received, integrated, and stored to form a comprehensive and systematic medical record dataset: the patient's medical history information, physical examination information, results of various examinations and tests, as well as diagnostic and treatment information; II. Validation module for the logical relationship between diagnosis and treatment: A diagnostic and treatment testing module has been established. This module focuses on verifying the logical relationship between diagnosis and treatment, and its specific functions include: Automatically retrieve medical record datasets, match diagnostic information with treatment records, and ensure the correspondence between the two; Analyze diagnostic information to assess whether the patient needs treatment, and the necessity and urgency of such treatment; Verify whether the treatment basis provided in the treatment record is sufficient and reasonable, including but not limited to clinical guidelines, expert consensus, and the patient's specific condition; Verify the matching degree between the specific treatment measures described in the treatment records and the diagnostic information to ensure the targetedness and effectiveness of the treatment; Ensure that all key information regarding diagnosis and treatment is accurately and completely recorded in electronic medical records, including but not limited to whether treatment has been administered, whether treatment is necessary, the basis for treatment, and specific treatment measures. III. Reminder and Improvement Mechanism A reminder and improvement module has been established, which can intelligently detect potential problems in the medical record dataset, such as: Diagnosis for which treatment information was not recorded; Treatment records not associated with diagnostic information; When the above problems are detected, an automatic reminder is sent to the doctor. Based on the reminder, the doctor promptly supplements and improves the medical records to ensure their completeness, accuracy, and consistency. IV. Continuous System Optimization Based on feedback from doctors and in-depth analysis of medical record data, we continuously optimize the electronic medical record system and improve the accuracy and efficiency of the diagnostic, treatment, and testing modules to ensure the integrity, accuracy, and consistency of diagnostic and treatment records in the electronic medical record.

13. A method for recording electronic medical records for treatment tracking, characterized in that, The method includes the following steps in sequence: (I) Constructing a treatment program database In the electronic medical record system, a comprehensive, accurate, and real-time updated treatment item database is constructed to store and manage information on all treatment items received by the patient. This information includes, but is not limited to: detailed records of surgeries and procedures (such as surgery and procedure name, time, site, doctor, etc.), comprehensive information on medication use (such as medication name, specifications, dosage, frequency of use, start and end dates, etc.), detailed records of consumable use (such as consumable type, site of use, duration of use, etc.), and other key information related to treatment. (II) Dynamic tracking of treatment programs The electronic medical record system is used to record and track patients' surgical procedures, medication use, and consumable usage in real time. Specific tracking content includes: Surgical and procedural tracking: Record key information about surgeries and procedures, and continuously monitor postoperative recovery, complications, and surgical site infections to assess treatment effectiveness; Drug usage tracking: Record detailed information on drug use and continuously evaluate key indicators such as antibacterial efficacy, drug resistance, and side effects; Consumable usage tracking: Record the usage of consumables and track their therapeutic effects, such as treatment objectives and observed results; (III) Establishing an effect recording and analysis module An efficacy recording and analysis module should be established in the electronic medical record system to track, record, and analyze each treatment item in detail; this module should have the following functions: Tracking and Reminders: Based on the status of participants in the treatment program (such as patients and medical staff), the system automatically analyzes and sends reminders to relevant medical staff and patients, including but not limited to treatment progress reminders, medication usage reminders, and test result viewing reminders; Record reminders: Remind participants of treatment programs to promptly record their treatment progress in their electronic medical records; Results presentation: The treatment effects are recorded and presented using various multimedia formats (such as text, pictures, videos, audio, etc.) so that medical staff and patients can understand the treatment situation intuitively and clearly. (iv) Implement a cyclical tracking mechanism Based on the analysis of treatment effectiveness, the system automatically determines whether further follow-up electronic medical record entries are needed for the patient. This mechanism ensures the continuity and integrity of treatment, forming a closed loop of cyclical follow-up. (V) Establish a treatment tracking module system In the electronic medical record system, an independent tracking module should be established for each treatment item. These modules should include patient tracking and healthcare personnel tracking functions, allowing patients and healthcare personnel to freely view, edit, and supplement electronic medical record records of treatment within their authorized scope.

14. A method for extracting symptoms and signs from electronic medical records, used to accurately extract and display a specific symptom or sign and its changes over time from electronic medical records, while covering multiple data types such as text, images, video, and audio. The specific steps are as follows: I. Clearly define the symptoms, signs, and time frame. Selecting symptoms and signs: Based on clinical needs or research objectives, identify the specific symptoms and signs that need to be extracted in the electronic medical record system; Set a time frame: Based on the monitoring or analysis needs of symptoms and signs, set a clear time range for screening and extracting relevant records; II. Retrieving and Obtaining Electronic Medical Records Data retrieval: Using the retrieval tools of the electronic medical record system, all relevant medical records can be quickly retrieved based on the selected symptoms, signs, and time range; Screening and organization: The retrieved medical records are carefully screened to ensure that the extracted information is closely related to the required symptoms and signs, and this information is organized in an orderly manner; III. Extraction of Symptom and Sign Data Symptom and sign extraction: Textual description: Extract detailed descriptions of symptoms and signs from medical records, including the nature, location, size, color, shape, and accompanying symptoms of the symptoms and signs; Image extraction: For symptoms and signs that can be visually displayed through images, such as skin tumors, moles, and pigmented spots, relevant image data are extracted from medical records. Video and audio extraction: Extract video or audio data containing symptoms and signs from medical records, such as videos of patients describing their symptoms and signs, and audio recordings of doctors' examinations. IV. Presentation of Symptoms and Signs Presentation method selection: Select an appropriate presentation method based on the characteristics of the symptoms and signs and the type of data extracted; Textual presentation: The extracted textual descriptions are structured and organized to form a clear report of symptoms and signs; Image presentation: The extracted image data is arranged according to time sequence or symptom and sign type to form an intuitive image display; Video and audio presentation: The extracted video and audio materials are edited and organized to form multimedia presentation materials; Time range labeling: When presenting symptoms and signs, clearly label the time range for each symptom, sign, or data. V. Access to and Use of Data Viewing Function: Provides convenient viewing functions, allowing doctors or researchers to view the extracted symptom and sign data at any time, including text, images, videos, and audio; Analysis and utilization: The extracted symptom and sign data are used for further analysis and research, such as analysis of symptom and sign change trends, disease diagnosis assistance, and treatment effect evaluation.

15. A nationwide electronic medical record system, characterized in that... include: System integration and data synchronization module: The system includes a national electronic medical record cloud server, which serves as the core data processing center and is seamlessly connected to the electronic medical record servers of various medical institutions. The national electronic medical record cloud server and the electronic medical record servers of various medical institutions adopt an efficient data synchronization mechanism to ensure the real-time synchronization and updating of patients' health information. The system supports data integration across healthcare institutions, allowing healthcare professionals to query and access patients' complete health records nationwide; Patient Health Information Integrated Management Module: The system provides comprehensive patient health information management functions, including but not limited to medical records, diagnostic information, examination results, treatment plans, medication records, etc. The system can automatically integrate health information from medical professionals, patients' direct stakeholders, and other relevant stakeholders to generate comprehensive patient health records. The system supports intelligent analysis and early warning functions based on patient health information, such as disease risk assessment and drug interaction detection. Data access permission and security control module: The system implements strict data access permission management to ensure that only authorized medical professionals, patients, and their authorized personnel can access the relevant patient health information; The system provides patient data access permission management functions, allowing patients to independently set and control access permissions to their health information; System performance and scalability module: Both the national electronic medical record cloud server and the electronic medical record server of medical institutions adopt high-performance computing and storage technologies to ensure the stability and response speed of the system under high-concurrency access and big data processing. The system design supports modular expansion, facilitating functional upgrades and expansions based on business needs and technological advancements. The system has the ability to interface with other systems (such as traffic police systems) to input additional patient health information through other relevant patient terminals.

16. An electronic medical record recording and management system for realizing the recording, storage, automatic generation, treatment tracking, and symptom and sign extraction of electronic medical records, the system comprising: Information entry module: Used to comprehensively and systematically collect and record patients' health information through various entry points, including medical professional terminals, patient-related terminals, and other related terminals. Information storage module: Used to accurately save the entered patient health information to the corresponding module or location in the electronic medical record system, ensuring the integrity, accuracy and traceability of the information; Electronic medical record automatic generation module: It is used to automatically identify the electronic medical record to be completed according to the system's preset rules or trigger conditions, and automatically fill in and generate the electronic medical record based on the obtained health information; Treatment tracking module: This module records and tracks the surgical procedures, medications, and consumables used by patients in real time. It also includes an effect recording and analysis module, providing functions such as treatment progress reminders and medication usage reminders. Symptom and Sign Extraction Module: Used to accurately extract and display specific symptoms and signs and their changes over time from electronic medical records, covering various data types such as text, images, videos, and audio. Data synchronization and access control module: used to ensure data synchronization between electronic medical record servers of medical institutions across the country and the national electronic medical record cloud server, and to implement strict data access permission management; Intelligent Analysis and Early Warning Module: Used for in-depth mining and analysis of patient health information, to discover potential health problems and risks, and to provide functions such as disease risk assessment and drug interaction detection.