Hysteroscopic surgery whole-process information management system

Abstract

The invention discloses a hysteroscopic surgery whole-process information management system, and relates to the technical field of hysteroscopic surgery. Comprising an information registration module, a pre-operation evaluation module, a scheme recommendation module, an intra-operation collaboration module, a post-operation management module, a follow-up management module, a data security module, a consumable management module, a doctor-patient interaction module and a scientific research analysis module, and all the modules interact in real time through a data bus to form an evaluation-execution-management-scientific research closed loop. And the information management efficiency and the medical quality are obviously improved. According to the system, through a machine learning algorithm of the preoperative evaluation module, the age, medical history and laboratory indexes of a patient can be automatically analyzed, the risk probability of bleeding, infection and the like in the operation can be predicted, a personalized preparation scheme including preoperative medication and fasting time can be generated, and the scheme recommendation module supports automatic matching of an operation style and an instrument list. A standardized operation process is generated in combination with historical operation data, and the decision-making difficulty of novice doctors is reduced.

Description

Technical Field

[0001] This invention relates to the field of hysteroscopic surgery technology, specifically to a hysteroscopic surgery full-process information management system. Background Technology

[0002] Hysteroscopic surgery refers to minimally invasive surgery. A hysteroscope is an advanced device for diagnosing and treating diseases within the uterine cavity. It allows for clear observation of various changes within the uterine cavity, enabling accurate diagnosis. Currently, hysteroscopic surgeries generally rely on manual registration for pre-operative, intra-operative, and post-operative information management. This requires highly skilled and qualified personnel, but information management is inconvenient and inefficient.

[0003] The invention disclosed in CN116130054A is a hysteroscopic surgery full-process information management system, method, equipment, and storage medium. The system includes: an information registration module for storing basic patient information and patient details; a procedure recommendation module for generating corresponding surgical procedures and intraoperative operation steps based on preoperative diagnosis, or for manually inputting templates; an intraoperative image acquisition module for acquiring intraoperative images and marking their locations; a postoperative diagnosis module for providing postoperative diagnosis based on the intraoperative situation; a postoperative reminder module for providing standardized reminders for postoperative medication; a pathology report module for recording and entering pathology results; and a postoperative follow-up module for sending follow-up reminders at regular intervals.

[0004] However, the existing hysteroscopic surgery end-to-end information management system's information registration module only mentions storing patient information but lacks intelligent verification mechanisms, such as data integrity verification or logical consistency checks. This may result in manual input errors going undetected, affecting the accuracy of medical records. While the intraoperative image acquisition module mentions light filtering, it lacks real-time integration with anesthesia monitoring and surgical guidance, failing to dynamically highlight the location of key anatomical structures or operational steps, thus impacting surgical precision. The postoperative follow-up module only supports timed reminders and lacks a dynamic assessment mechanism based on patient recovery data, making personalized rehabilitation management difficult. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a hysteroscopic surgery process information management system, which solves the existing problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a hysteroscopic surgery full-process information management system, comprising:

[0007] Information registration module: used to collect and store patients' basic information, medical history and preoperative examination data, and generate standardized medical record files;

[0008] Preoperative assessment module: Based on artificial intelligence algorithms, analyze patient medical records to generate surgical risk assessment reports and personalized preoperative preparation plans;

[0009] The recommended procedure module automatically matches surgical procedures, operation steps, and instrument lists based on preoperative diagnosis results, and supports doctors to customize templates.

[0010] Intraoperative collaboration module: integrates real-time hysteroscopic image acquisition, pathological location marking, and anesthesia depth monitoring functions, and supports real-time data sharing among multiple departments;

[0011] Postoperative management module: Automatically generates postoperative diagnostic reports, medication reminders, and rehabilitation plans, and connects to the pathology testing system to obtain reports;

[0012] Follow-up management module: Automatically triggers follow-up reminders based on time nodes, and supports patient symptom self-assessment and remote doctor evaluation;

[0013] Data security module: Blockchain technology is used to encrypt and store all surgical data to ensure that the data is tamper-proof and traceable.

[0014] Preferably, the information registration module includes:

[0015] Information Acquisition Unit: Acquires patient information through HIS system integration, mobile questionnaires, or manual data entry;

[0016] Intelligent verification unit: Automatically verifies the integrity and logical consistency of input data and marks abnormal data;

[0017] Template Management Unit: Generates standardized information collection templates based on disease type, and supports custom field configuration.

[0018] Preferably, the preoperative assessment module includes:

[0019] Risk prediction model: Based on machine learning algorithms, analyze patient age, medical history, and laboratory indicators to predict the probability of intraoperative bleeding, infection, uterine perforation, and fatal complications such as TURP and air embolism.

[0020] Solution generation unit: Recommends preoperative medication, fasting time and blood preparation plan based on risk level, and generates a visual assessment report.

[0021] Preferably, the intraoperative collaboration module includes:

[0022] Image processing unit: Adaptive filtering algorithm is used to eliminate the interference of intraoperative fluid accumulation and bleeding on images, and supports real-time transmission of 4K high-definition images;

[0023] Anesthesia monitoring unit: synchronously collects anesthesia machine data, displays the patient's vital signs curve in real time, and sets abnormal value warning thresholds;

[0024] Operation guidance unit: Dynamically prompts operation steps according to the surgical plan and marks the location of key anatomical structures.

[0025] Preferably, the postoperative management module includes:

[0026] Diagnostic report generation unit: Automatically generates structured diagnostic reports based on intraoperative images and pathology results, and supports voice input correction;

[0027] Intelligent medication reminder unit: Generates a medication calendar based on doctor's orders, pushes medication time and dosage via SMS and APP, and records medication feedback;

[0028] Rehabilitation assessment unit: Regularly pushes out rehabilitation questionnaires, adjusts rehabilitation plans based on patient feedback, and connects with smart devices to collect exercise and sleep data.

[0029] Preferably, the follow-up management module includes:

[0030] Smart reminder unit: Automatically sends reminder notifications N days before the follow-up date, supporting multiple channels such as phone, SMS, and WeChat;

[0031] Remote assessment unit: Patients upload pictures of symptoms and test reports via mobile devices, and doctors provide follow-up recommendations online;

[0032] Data statistics unit: Automatically analyzes follow-up data, generates disease prognosis trend reports, and supports the export of scientific research data.

[0033] Preferably, the data security module includes:

[0034] Blockchain-based evidence storage unit: Stores key information such as surgical informed consent forms, imaging data, and pathology reports on the blockchain using hash values.

[0035] Access control unit: Assigns access permissions based on roles, records all data operation logs, and supports operation traceability and auditing;

[0036] Encrypted transmission unit: Employs SSL / TLS protocol to ensure data transmission security and prevent middleware attacks.

[0037] Preferably, the consumables management module is included:

[0038] Real-time tracking of surgical instruments and consumables usage, and automatic generation of consumable consumption lists;

[0039] It integrates with the inventory management system to provide early warnings of low inventory consumables and supports automatic approval of purchase requests.

[0040] Preferably, a doctor-patient interaction module is also included:

[0041] Provide a patient-side app that supports checking surgery progress, leaving doctor messages, and accessing health education materials;

[0042] The doctor's side integrates instant messaging functionality, supporting multidisciplinary consultation message push and collaborative recording.

[0043] Preferably, it also includes a scientific research analysis module:

[0044] A research database is built based on anonymized medical record data, supporting custom queue filtering and statistical analysis;

[0045] It automatically generates research reports, connects to academic paper submission systems, and assists in the translation of clinical research findings.

[0046] Beneficial effects

[0047] This invention provides an information management system for the entire process of hysteroscopic surgery. Compared with existing technologies, it has the following advantages:

[0048] 1. This hysteroscopic surgery full-process information management system can automatically analyze the patient's age, medical history, and laboratory indicators through the machine learning algorithm of the preoperative assessment module, predict the probability of risks such as intraoperative bleeding and infection, and generate a personalized preparation plan that includes preoperative medication and fasting time. The plan recommendation module supports automatic matching of surgical procedures and instrument lists, and generates standardized operating procedures by combining historical surgical data, reducing the decision-making difficulty for novice doctors.

[0049] 2. This hysteroscopic surgery end-to-end information management system integrates real-time 4K image acquisition, pathological location marking, and anesthesia depth monitoring through an intraoperative collaboration module. Adaptive filtering algorithms eliminate interference from fluid accumulation and bleeding, ensuring image clarity. Simultaneously, multiple departments can share patient vital sign data in real time through the system. Automatic alerts are triggered when anesthesia parameters are abnormal, shortening the time required to handle anomalies. The data security module uses blockchain technology to store hash values ​​of key information such as informed consent forms and pathology reports on the blockchain. Combined with role-based access control, this ensures data is tamper-proof and traceable, meeting medical data compliance requirements. Furthermore, the consumables management module tracks instrument usage in real time, automatically generates a consumption list and connects to the inventory system. Low inventory triggers procurement alerts, reducing manual inventory errors and improving consumables management efficiency. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the system architecture of the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] See also Figure 1 The present invention provides the following two technical solutions:

[0053] The first implementation method is a hysteroscopic surgery full-process information management system, which realizes full-process digital management through modular design. It includes an information registration module, a preoperative assessment module, a plan recommendation module, an intraoperative collaboration module, a postoperative management module, a follow-up management module, a data security module, a consumables management module, a doctor-patient interaction module, and a scientific research analysis module. The modules interact in real time through a data bus to form a closed loop of "assessment-execution-management-scientific research", which significantly improves information management efficiency and medical quality.

[0054] The information registration module is used to achieve standardized collection and verification of patient information, including:

[0055] Information Acquisition Unit: Acquires patient information through HIS system integration, mobile questionnaires, or manual data entry. Patients fill out medical history questionnaires via mobile APP, which supports voice input and file upload.

[0056] Intelligent verification unit: Automatically verifies the integrity and logical consistency of input data and marks abnormal data;

[0057] Template Management Unit: Generates standardized information collection templates based on disease type, and supports custom field configuration.

[0058] The preoperative assessment module uses AI algorithms to generate personalized surgical risk assessment and preparation plans, including:

[0059] Risk prediction model: Based on machine learning algorithms, the model analyzes patient age, medical history, and laboratory indicators to predict the probability of intraoperative bleeding, infection, uterine perforation, and fatal complications such as TURP and air embolism. The risk prediction model is trained using a random forest algorithm.

[0060] Solution generation unit: Recommends preoperative medication, fasting time and blood preparation plan based on risk level, and generates a visual assessment report, including risk factor weight analysis.

[0061] The intraoperative collaboration module is used to improve the precision of surgical procedures and the efficiency of multidisciplinary collaboration, including:

[0062] Image processing unit: Adaptive filtering algorithm is used to eliminate the interference of intraoperative fluid accumulation and bleeding on images, and supports real-time transmission of 4K high-definition images to the teaching terminal for marking pathological locations;

[0063] Anesthesia monitoring unit: synchronously collects anesthesia machine data, displays the patient's vital signs curve in real time, and sets abnormal value warning thresholds;

[0064] Operation guidance unit: Dynamically prompts operation steps according to the surgical plan and marks the location of key anatomical structures.

[0065] The data security module is used to ensure the integrity, confidentiality, and traceability of medical data, including:

[0066] Blockchain Evidence Storage Unit: Hash values ​​of key information such as surgical informed consent forms, imaging data, and pathology reports are stored on the blockchain. Data consensus among multiple institutions is achieved through consortium blockchain technology to ensure that the data is tamper-proof.

[0067] Access control unit: Assigns access permissions based on roles, records all data operation logs, and supports operation traceability and auditing;

[0068] Encrypted transmission unit: Data is stored using the AES-256 algorithm, and the transport layer uses the SSL / TLS protocol to ensure data transmission security and prevent middleware attacks.

[0069] The research analysis module is used to extract value from clinical data and support research and teaching, including:

[0070] Anonymized data pool automatically removes patient privacy information and generates anonymized medical record data, supporting the filtering of research cohorts by disease type, surgical method, and other dimensions;

[0071] The statistical analysis engine has built-in statistical tools such as t-tests and survival analysis, automatically generates trend charts, and connects to academic platforms such as PubMed and CNKI, supporting one-click submission of research reports.

[0072] The consumables management module uses RFID tags to track the location of medical devices, automatically generates a consumables list after surgery, connects to the hospital's ERP system, and automatically triggers a purchase request when inventory is low.

[0073] The doctor-patient interaction module allows patients to receive real-time updates on their surgery progress via the app, doctors to send rehabilitation guidance videos through the app, and patients to upload symptom images for online consultation.

[0074] Second implementation method: Example

[0075] Taking a hysteroscopic surgery at a top-tier hospital as an example, the system operation procedure is as follows:

[0076] Preoperative stage:

[0077] Patients fill out a medical history questionnaire through a mobile app, and the information registration module automatically generates standardized medical records (including symptom descriptions and ultrasound results);

[0078] The preoperative assessment module analyzed the data and predicted the intraoperative bleeding risk to be "moderate" for patients with a BMI > 28, recommending that 200 mL of blood be prepared before the operation.

[0079] Intraoperative phase:

[0080] The intraoperative collaborative module acquires hysteroscopic images in real time, automatically filters out interference from intrauterine fluid accumulation, and clearly displays the location of the polyp (12mm in diameter);

[0081] The anesthesia monitoring unit detected that the patient's blood oxygen saturation dropped to 92% and immediately sent an alert to the surgeon. After adjusting the ventilation parameters, the oxygen saturation returned to normal.

[0082] Postoperative stage:

[0083] The postoperative management module automatically generates a progestin medication plan based on the intraoperative pathology results (endometrial polyps) and reminds patients to take the medication daily via SMS.

[0084] The follow-up management module triggers a follow-up reminder 3 months after surgery. Patients upload ultrasound reports through the APP, and doctors remotely assess whether there is a recurrence.

[0085] Data security and scientific research:

[0086] All surgical data (including images and pathology reports) is stored on the blockchain to ensure traceability for judicial purposes;

[0087] The research analysis module analyzed data from 1,000 patients with endometrial polyps and found that the use of the Mirena IUD after surgery could reduce the recurrence rate by 35%. The relevant research was published in the Chinese Journal of Obstetrics and Gynecology.

[0088] This invention integrates functional modular innovation with cutting-edge technology to construct an intelligent management system covering the entire process of hysteroscopic surgery, which significantly improves medical safety, efficiency and scientific research value, and has broad clinical application prospects.

[0089] Furthermore, all content not described in detail in this specification is existing technology known to those skilled in the art, and the model parameters of each electrical appliance are not specifically limited; conventional equipment can be used.

[0090] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0091] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A hysteroscopic surgery full-process information management system, characterized in that, include: Information registration module: used to collect and store patients' basic information, medical history and preoperative examination data, and generate standardized medical record files; Preoperative assessment module: Based on artificial intelligence algorithms, analyze patient medical records to generate surgical risk assessment reports and personalized preoperative preparation plans; The recommended procedure module automatically matches surgical procedures, operation steps, and instrument lists based on preoperative diagnosis results, and supports doctors to customize templates. Intraoperative collaboration module: integrates real-time hysteroscopic image acquisition, pathological location marking, and anesthesia depth monitoring functions, and supports real-time data sharing among multiple departments; Postoperative management module: Automatically generates postoperative diagnostic reports, medication reminders, and rehabilitation plans, and connects to the pathology testing system to obtain reports; Follow-up management module: Automatically triggers follow-up reminders based on time nodes, and supports patient symptom self-assessment and remote doctor evaluation; Data security module: Blockchain technology is used to encrypt and store all surgical data to ensure that the data is tamper-proof and traceable.

2. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The information registration module includes: Information Acquisition Unit: Acquires patient information through HIS system integration, mobile questionnaires, or manual data entry; Intelligent verification unit: Automatically verifies the integrity and logical consistency of input data and marks abnormal data; Template Management Unit: Generates standardized information collection templates based on disease type, and supports custom field configuration.

3. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The preoperative assessment module includes: Risk prediction model: Based on machine learning algorithms, this model analyzes patient age, medical history, and laboratory indicators to predict the probability of intraoperative bleeding, infection, uterine perforation, and fatal complications such as TURP and air embolism. Solution generation unit: Recommends preoperative medication, fasting time and blood preparation plan based on risk level, and generates a visual assessment report.

4. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The intraoperative collaboration module includes: Image processing unit: Adaptive filtering algorithm is used to eliminate the interference of intraoperative fluid accumulation and bleeding on images, and supports real-time transmission of 4K high-definition images; Anesthesia monitoring unit: synchronously collects anesthesia machine data, displays the patient's vital signs curve in real time, and sets abnormal value warning thresholds; Operation guidance unit: Dynamically prompts operation steps according to the surgical plan and marks the location of key anatomical structures.

5. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The postoperative management module includes: Diagnostic report generation unit: Automatically generates structured diagnostic reports based on intraoperative images and pathology results, and supports voice input correction; Intelligent medication reminder unit: Generates a medication calendar based on doctor's orders, pushes medication time and dosage via SMS and APP, and records medication feedback; Rehabilitation assessment unit: Regularly pushes out rehabilitation questionnaires, adjusts rehabilitation plans based on patient feedback, and connects with smart devices to collect exercise and sleep data.

6. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The follow-up management module includes: Smart reminder unit: Automatically sends reminder notifications N days before the follow-up date, supporting multiple channels such as phone, SMS, and WeChat; Remote assessment unit: Patients upload pictures of symptoms and test reports via mobile devices, and doctors provide follow-up recommendations online; Data statistics unit: Automatically analyzes follow-up data, generates disease prognosis trend reports, and supports the export of scientific research data.

7. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The data security module includes: Blockchain-based evidence storage unit: Stores key information such as surgical informed consent forms, imaging data, and pathology reports on the blockchain using hash values. Access control unit: Assigns access permissions based on roles, records all data operation logs, and supports operation traceability and auditing; Encrypted transmission unit: Employs SSL / TLS protocol to ensure data transmission security and prevent middleware attacks.

8. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: The system includes a consumables management module: Real-time tracking of surgical instruments and consumables usage, and automatic generation of consumable consumption lists; It integrates with the inventory management system to provide early warnings of low inventory consumables and supports automatic approval of purchase requests.

9. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: It also includes a doctor-patient interaction module: Provide a patient-side app that supports checking surgery progress, leaving doctor messages, and accessing health education materials; The doctor's side integrates instant messaging functionality, supporting multidisciplinary consultation message push and collaborative recording.

10. The hysteroscopic surgery full-process information management system according to claim 1, characterized in that: It also includes a scientific research analysis module: A research database is built based on anonymized medical record data, supporting custom queue filtering and statistical analysis; It automatically generates research reports, connects to academic paper submission systems, and assists in the translation of clinical research findings.

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