Surgery auxiliary service supervision system

Abstract

The invention discloses a surgical auxiliary service supervision system, which relates to the field of service supervision and comprises a surgical auxiliary supervision platform which is provided with a service management module, a risk prediction module, a surgical monitoring module, an auxiliary analysis module and a surgical management module. The service management module is used for obtaining patient medical record information, service medical record information and historical service supervision information, and constructing a data storage model according to the obtained information; the risk prediction model is used for performing risk prediction according to the information in the data storage model to obtain risk assessment data; the operation monitoring module obtains operation monitoring data according to the risk assessment data; the auxiliary analysis module sets auxiliary monitoring evaluation standard data corresponding to the operation process according to the data storage model, and obtains corresponding auxiliary analysis data according to evaluation analysis; the operation management module is used for generating operation response data according to the auxiliary analysis data; according to the invention, the accuracy of the service supervision process is improved to a certain extent.

Description

Technical Field

[0001] The present invention relates to the technical field of service supervision, and particularly to a surgical assistance service supervision system. Background Art

[0002] With the aggravation of population aging and the continuous progress of medical technology, the number of patients requiring surgical treatment is increasing continuously; nowadays, patients have higher expectations for the quality and safety of medical services. They not only focus on the quality and effect of surgeries, but also have more requirements for the experience and service quality during the surgical process. Therefore, a complete supervision system is needed to standardize surgical assistance services and ensure that patients can obtain high-quality medical services.

[0003] It is difficult to conduct focused, personalized, and flexible auxiliary monitoring according to the different usage habits and technical proficiency levels of each medical staff and the different medical record information corresponding to each patient, thus affecting the accuracy of auxiliary supervision services and the data supervision efficiency during the surgical process. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcoming of insufficient accuracy of supervision services in the prior art, and to propose a surgical assistance service supervision system.

[0005] In order to achieve the above purpose, the present invention adopts the following technical scheme: A surgical assistance service supervision system includes a surgical assistance supervision platform, and a service management module, a risk prediction module, a surgical monitoring module, an auxiliary analysis module, and a surgical management module are arranged in the surgical assistance supervision platform; The service management module is used to obtain the patient medical record information corresponding to the patient, the service case information corresponding to the corresponding medical staff, and the historical service supervision information, set a data storage model associated with the surgical process according to the historical service supervision information, and store the obtained patient medical record information and service case information into the corresponding data storage model; The risk prediction model is used to perform risk prediction analysis on the surgical process according to the corresponding patient medical record information and service case information in the data storage model, and obtain risk assessment data in the surgical process; The surgical monitoring module is used to dynamically adjust the surgical monitoring process according to the surgical process and the corresponding risk assessment data, and obtain corresponding surgical monitoring data; The auxiliary analysis module is used to set auxiliary monitoring evaluation standard data corresponding to the surgical process according to the data storage model, and evaluate and analyze the corresponding surgical monitoring data according to the corresponding auxiliary monitoring evaluation standard data, and obtain auxiliary analysis data corresponding to the corresponding patient; The surgical management module is used to generate surgical response data for the surgical process of the corresponding patient according to the corresponding auxiliary analysis data, and feedback the obtained surgical response data to the corresponding medical staff.

[0006] The above technical solution further includes: The process of obtaining the patient medical record information corresponding to the patient, the service case information corresponding to the corresponding medical staff, and the historical service supervision information includes: A patient collection unit, a medical staff collection unit, and a historical collection unit are set in the service management module; The patient collection unit is provided with a patient input port, a medical staff input port, and a device input port, which are respectively used for the patient, the medical staff, and the corresponding medical device to input the corresponding patient information, and mark the input patient information as the corresponding patient medical record information; The medical staff collection unit is used to collect the service case information corresponding to the services of the corresponding medical staff, and the service case information is the service process case information of the corresponding patient involved in the work of the corresponding medical staff; The historical collection unit is used to collect the historical service supervision information in the surgical assistance supervision platform, and the historical service supervision information includes the patient medical record information, service case information, surgical monitoring data, auxiliary analysis data, and surgical response data corresponding to the patient.

[0007] Further, the process of setting the data storage model associated with the surgical process according to the historical service supervision information includes: Obtain the historical service supervision information, set the surgical service supervision data set according to the historical service supervision information, extract the key features of the surgical service monitoring data set, obtain the corresponding key indicators, and construct the surgical operation process framework according to the obtained key indicators. The surgical operation process framework includes the corresponding surgical process nodes and the corresponding surgical monitoring data; Set the patient control data set and the medical staff control data set according to the corresponding surgical process nodes in the surgical operation process framework and the corresponding patient medical record information and service medical record information respectively; Analyze and process the obtained patient control data set and medical staff control data set respectively, and perform correlation analysis on the corresponding patient control data set and medical staff control data set based on the data mining algorithm to obtain the correlation data between the corresponding parameters and the surgical process nodes; Construct a data storage model according to the correlation data corresponding to each patient control data set and medical staff control data set; map and store the obtained patient medical record information and service case information to the corresponding positions in the data storage model respectively.

[0008] Further, the process of obtaining the risk assessment data in the surgical process includes: Obtain the patient medical record information and service case information of the corresponding surgery stored in the data storage model, and sequentially perform risk assessment on the patient medical record information and service case information associated in the corresponding surgery process nodes according to the corresponding surgery operation process framework; Preset the key parameters corresponding to the corresponding surgery operation process, construct a risk assessment model based on the relevance data between the corresponding patient medical record information and service case information in the data storage model and the corresponding associated parameters, and obtain the influence coefficients of the key parameters corresponding to different patient medical record information and service case information based on the risk assessment model; Integrate the influence coefficients of each key parameter corresponding to the corresponding surgery process node to obtain the process risk assessment data of the corresponding surgery process node; Mark the process risk assessment data corresponding to each surgery process node in the surgery process in sequence to obtain the risk assessment data in the corresponding surgery process.

[0009] Further, the process of obtaining the corresponding surgery monitoring data includes: Obtain the risk assessment data corresponding to each surgery process node in the surgery process; Set multiple surgical service monitoring devices, and the surgical service monitoring devices are respectively used to obtain the surgical monitoring data corresponding to the corresponding surgery process node, and the corresponding surgical service monitoring device presets a corresponding monitoring standard parameter table according to the corresponding process risk assessment data; Compare and analyze the process risk assessment data corresponding to the corresponding surgery process node with the monitoring standard parameter table corresponding to the corresponding surgical service monitoring device, obtain the monitoring standard parameters corresponding to the corresponding surgical service monitoring device, dynamically adjust the monitoring process of the surgical service monitoring device according to the corresponding monitoring standard parameters, and obtain the surgical monitoring data corresponding to the corresponding surgery process node according to the dynamic adjustment result.

[0010] Further, the process of setting the auxiliary monitoring and evaluation standard data corresponding to the surgery process according to the data storage model includes: Obtain the patient medical record information, service case information corresponding in the data storage model, and the surgical monitoring data obtained in the corresponding surgery process node; Preset the initial auxiliary evaluation data corresponding to the corresponding surgery process node, and perform preliminary correction processing on the initial auxiliary evaluation data according to the relevance data between the patient medical record information and service case information and the corresponding surgery process node to obtain the corresponding associated auxiliary evaluation data; Perform a correlation analysis on the impact of the surgical monitoring data corresponding to each surgical process node within the surgical operation process framework on the next surgical process node. Set corresponding adjacent data sets for the surgical monitoring data and associated auxiliary evaluation data corresponding to adjacent surgical process nodes, analyze and process the adjacent data sets, and construct an adjacent association model; Input the surgical monitoring data corresponding to the corresponding surgical process node and the corresponding associated auxiliary evaluation parameters into the adjacent association model, and output the auxiliary monitoring and evaluation standard data corresponding to the next surgical process node.

[0011] Furthermore, the process of obtaining the auxiliary analysis data corresponding to the corresponding patient includes: Compare and analyze the surgical monitoring data of the corresponding surgical process node during the surgical process of the corresponding patient and medical staff with the corresponding auxiliary monitoring and evaluation standard data to obtain the evaluation deviation data corresponding to the corresponding surgical process node; Conduct an auxiliary evaluation analysis on the obtained evaluation deviation data, preset deviation standard data. If the evaluation deviation data meets the deviation standard data, no auxiliary warning information is generated; otherwise, auxiliary warning information is generated; Evaluate and analyze the corresponding surgical monitoring data based on the auxiliary warning information, obtain the characteristic data corresponding to the corresponding surgical monitoring data and the corresponding time information, and construct an index visualization curve based on the corresponding time information and the characteristic data of the surgical monitoring data; Preset a surgical error data repository corresponding to the corresponding surgical process node. The surgical error data repository stores an error index comparison curve of possible error operation results for the corresponding surgical process node. Compare and analyze the index visualization curve with the corresponding error index comparison curve in the surgical error data repository, and obtain the auxiliary analysis data corresponding to the corresponding surgical process node according to the matching result.

[0012] Furthermore, obtain the matching result of the corresponding error operation result according to the auxiliary analysis data, obtain the surgical response data corresponding to the corresponding surgical process node according to the corresponding error operation result, and feedback the surgical response data to the corresponding medical staff.

[0013] The present invention has the following beneficial effects: 0. In the present invention, by constructing a data storage model related to the surgical process based on the patient's medical record information, the service case information corresponding to the medical staff, and the corresponding historical service supervision information, storing the data associated with the surgical monitoring process through the data storage model, thereby improving the efficiency in the data analysis process; 1. In the present invention, by predicting and analyzing the risks of the patient's surgical process, risk assessment data for different surgical processes is obtained. According to the corresponding risk assessment data, the surgical monitoring process is dynamically adjusted, and corresponding surgical monitoring data is obtained based on the dynamic adjustment results. Thus, relatively accurate surgical monitoring data is obtained to a certain extent, avoiding waste of resources and improving the accuracy in the supervision process of surgical assistance services. 2. In the present invention, by using the surgical monitoring data obtained during the surgical process to dynamically adjust the monitoring and evaluation standard data of subsequent surgical process nodes, the error brought by a single evaluation index in the supervision process of surgical assistance services is avoided. By making personalized adjustments to the monitoring process according to the patient medical record information corresponding to different patients and the service case information corresponding to medical staff, the accuracy in the supervision service process is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic structural diagram of a surgical assistance service supervision system proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0016] Embodiment 1 As Figure 1 shown, a surgical assistance service supervision system proposed by the present invention includes a surgical assistance supervision platform, and a service management module, a risk prediction module, a surgical monitoring module, an auxiliary analysis module, and a surgical management module are arranged in the surgical assistance supervision platform; In this embodiment, the surgical assistance supervision platform is used to conduct a full-process supervision and analysis of the service process of corresponding medical staff before and during the surgical operation on the patient, so as to improve the safety of the patient's surgery and provide a better service experience for the patient. Its specific implementation process includes: The service management module is used to obtain the patient medical record information corresponding to the patient, the service case information corresponding to the corresponding medical staff, and the historical service supervision information, set a data storage model associated with the surgical process according to the historical service supervision information, and store the obtained patient medical record information and service case information into the corresponding data storage model. Its specific implementation process includes: Set a patient collection unit, a medical staff collection unit, a historical collection unit, and a collection management unit; The patient collection unit is used to obtain the patient medical record information corresponding to the corresponding patient, and is provided with a patient input port, a medical staff input port, and a device input port, where: The patient input port is used to obtain the basic identity information of the corresponding patient, the patient's self-reported information, the patient's medical history and allergy history information, etc.; The medical staff input port is used for the corresponding medical staff to perform status description and analysis on the status of the corresponding patient, and input the medical staff description information and medical diagnosis information corresponding to the corresponding patient according to the status description and analysis results; The device input port is used for the corresponding medical detection devices and medical monitoring devices to monitor and detect the physical condition and surgical process of the corresponding patient, and obtain the device monitoring information corresponding to the corresponding patient; Mark the basic identity information of the patient, the patient's self-reported information, the patient's medical history and allergy history information, the medical staff description information, the medical diagnosis information, and the device monitoring information obtained from the patient input port, the medical staff input port, and the device input port respectively according to the corresponding collection and input time, generate electronic medical record information, and integrate the electronic medical record information according to the mark processing result to obtain the patient medical record information corresponding to the patient. The patient medical record information is medical data information reflecting the physical state of the corresponding patient; The medical staff collection unit is used to collect the service case information corresponding to the corresponding medical staff, set a corresponding medical staff account for the corresponding medical staff, and obtain the patient medical record information related to the medical staff according to the corresponding medical staff account; Extract the information from the patient medical record information related to the medical staff account to obtain the medical staff service information associated with the corresponding medical staff account, mark the obtained medical staff service information according to the source of the corresponding patient medical record information, and set the service case information corresponding to the corresponding medical staff account for each mark processing result. The service case information is the service case process information of the corresponding patient involved in the daily work of the corresponding medical staff; The historical collection unit is used to collect the historical service supervision information in the surgical assistance supervision platform. The historical service supervision information includes the patient medical record information, service case information, surgical monitoring data, auxiliary analysis data, and surgical response data corresponding to the patient, that is, the historical service supervision information is the full-process historical data of the corresponding patient in the surgical assistance service supervision; The collection management unit is used to analyze and process the obtained data information and set a corresponding data storage model. The process includes: Obtain the historical patient medical record information corresponding to the corresponding department type in the surgical assistance supervision platform, and divide the process according to the surgical process corresponding to the historical patient medical record information of the corresponding department; Set the obtained historical patient medical record information as the surgical service supervision data set, extract key features from the surgical service monitoring data set, obtain the corresponding diagnosis information and treatment plan in the patient medical record information, obtain the corresponding surgical type, obtain the corresponding key indicators according to the corresponding surgical type, and construct a surgical operation process framework based on the obtained key indicators. The surgical operation process framework includes corresponding surgical process nodes and corresponding surgical monitoring data, and the surgical process nodes correspond to the corresponding key indicators; Set up a patient control data set and a medical staff control data set according to the corresponding surgical process nodes in the surgical operation process framework and the corresponding patient medical record information and service medical record information respectively; The patient control data set includes the comparison relationships between various types of data information in the corresponding patient medical record information and the surgical monitoring data corresponding to the corresponding surgical process nodes; The medical staff control data set includes the comparison relationships between various types of data information in the corresponding medical staff's corresponding service case information and the surgical monitoring data corresponding to the corresponding surgical process nodes; Analyze and process the obtained patient control data set and medical staff control data set respectively, and conduct association analysis on the corresponding patient control data set and medical staff control data set based on the data mining algorithm to obtain the correlation data between the corresponding parameters and the surgical process nodes. The process includes: Obtain the data types and monitoring types in the corresponding control data set, and mark them as and respectively, where i is the type of corresponding data type and j is the type of corresponding monitoring type; Obtain the probability data and that simultaneously contain and in the control data set, as well as the occurrence frequency data The corresponding correlation data is marked as , where: , and are the correlation evaluation coefficients corresponding to the corresponding data type and monitoring type; Evaluate the obtained correlation data, preset the control correlation data threshold, compare and analyze the correlation data with the control correlation data threshold. If it meets the standard, set the corresponding data type and monitoring type as the correlation control, otherwise do not set it as the correlation control; Construct a data storage model based on the correlation control relationships of the correlation data corresponding to each patient control data set and medical staff control data set, connect the corresponding data types and monitoring types, and set corresponding data storage spaces at the corresponding positions according to the connection relationships; map and store the obtained patient medical record information and service case information to the corresponding positions in the data storage model respectively.

[0017] The risk prediction model is used to perform risk prediction analysis on the surgical process according to the corresponding patient medical record information and service case information in the data storage model, and obtain risk assessment data in the surgical process. Its specific implementation process includes: Obtain the patient medical record information and service case information of the corresponding surgery stored in the data storage model, and perform risk assessment on the patient medical record information and service case information associated in the corresponding surgical process nodes in sequence according to the corresponding surgical operation process framework; Preset the key parameters corresponding to the corresponding surgical operation process , construct a risk assessment model according to the correlation data between the corresponding patient medical record information and service case information in the data storage model and the corresponding associated parameters, obtain the influence coefficients of the key parameters corresponding to different patient medical record information and service case information based on the risk assessment model, and mark them as ; Respectively set the correlation data of the associated parameters corresponding to the patient medical record information and service case information as , where n is the number of patient medical record information and service case information with corresponding associations; Integrate the influence coefficients of each key parameter corresponding to the corresponding surgical process node to obtain the process risk assessment data PR of the corresponding surgical process node, where: ; Mark the process risk assessment data corresponding to each surgical process node in the surgical process in sequence to obtain the risk assessment data in the corresponding surgical process.

[0018] The surgical monitoring module is used to dynamically adjust the surgical monitoring process according to the surgical process and the corresponding risk assessment data, and obtain the corresponding surgical monitoring data. Its specific implementation process includes: Obtain the risk assessment data corresponding to each surgical process node in the surgical process; Set multiple surgical service monitoring devices, and the surgical service monitoring devices are respectively used to obtain the surgical monitoring data corresponding to the corresponding surgical process nodes, where the surgical service monitoring devices include corresponding vital sign monitoring devices, surgical instrument use monitoring devices, airway management monitoring devices, and characteristic data monitoring devices, etc.; Preset a corresponding monitoring standard parameter table for the corresponding surgical service monitoring device according to the corresponding process risk assessment data. The monitoring standard parameter table is the parameters such as monitoring assessment and unit selection required for the monitoring accuracy corresponding to the corresponding surgical service monitoring device. Compare and analyze the process risk assessment data corresponding to the corresponding surgical process node with the monitoring standard parameter table corresponding to the corresponding surgical service monitoring device, obtain the monitoring standard parameters corresponding to the corresponding surgical service monitoring device, dynamically adjust the monitoring process of the surgical service monitoring device according to the corresponding monitoring standard parameters, and obtain the surgical monitoring data corresponding to the corresponding surgical process node according to the dynamic adjustment result.

[0019] The auxiliary analysis module is used to set the auxiliary monitoring assessment standard data corresponding to the surgical process according to the data storage model, and evaluate and analyze the corresponding surgical monitoring data according to the corresponding auxiliary monitoring assessment standard data to obtain the auxiliary analysis data corresponding to the corresponding patient. The specific implementation process includes: Obtain the patient medical record information, service case information corresponding in the data storage model, and the surgical monitoring data obtained in the corresponding surgical process node ; Preset the initial auxiliary assessment data corresponding to the corresponding surgical process node. The initial auxiliary assessment data includes the corresponding physiological auxiliary assessment data and cardiac monitoring auxiliary assessment data. Perform preliminary correction processing on the initial auxiliary assessment data according to the correlation data corresponding between the patient medical record information and service case information and the corresponding surgical process node to obtain the corresponding associated auxiliary assessment data , and the process includes: Obtain the corresponding correlation data , and mark the corresponding initial auxiliary assessment data as , where u is the corresponding surgical process node, v is the assessment type of the corresponding assessment data, and among them: , M is the sum of the corresponding data types with correlation data, m is the identification mark corresponding to i and j, is the preset correlation influence factor; Perform correlation analysis on the influence of the surgical monitoring data in each surgical process node within the surgical operation process framework on the next surgical process node, set the corresponding adjacent data set for the surgical monitoring data and associated auxiliary assessment data corresponding to the adjacent surgical process nodes, and perform analysis and processing on the adjacent data set to construct an adjacent correlation model. Input the surgical monitoring data corresponding to the corresponding surgical process node and the corresponding associated auxiliary assessment parameters into the adjacent correlation model, and output the auxiliary monitoring assessment standard data corresponding to the next surgical process node. Compare and analyze the surgical monitoring data of the corresponding surgical process nodes of the corresponding patients and medical staff with the corresponding auxiliary monitoring and evaluation standard data to obtain the evaluation deviation data corresponding to the corresponding surgical process nodes; Conduct auxiliary evaluation and analysis on the obtained evaluation deviation data, preset deviation standard data. If the evaluation deviation data meets the deviation standard data, no auxiliary warning information is generated; otherwise, auxiliary warning information is generated. Evaluate and analyze the surgical monitoring data of the corresponding coronary artery occlusion according to the auxiliary warning information to obtain the characteristic data and corresponding time information corresponding to the surgical monitoring data of the corresponding coronary artery occlusion, and construct an index visualization curve according to the corresponding time information and the characteristic data of the surgical monitoring data of the coronary artery occlusion. Preset a storage library for surgical error data of coronary artery occlusion corresponding to the corresponding surgical process nodes. The storage library for surgical error data of coronary artery occlusion stores error index comparison curves of possible error operation results corresponding to the corresponding surgical process nodes. Compare and analyze the index visualization curve with the corresponding error index comparison curve in the storage library for surgical error data of coronary artery occlusion, and obtain the auxiliary analysis data corresponding to the corresponding surgical process nodes according to the matching result.

[0020] The surgical management module is used to generate surgical response data for the surgical process of the corresponding patient according to the corresponding auxiliary analysis data, and feedback the obtained surgical response data to the corresponding medical staff. Its specific implementation process includes: Obtain the matching result of the corresponding error operation result according to the auxiliary analysis data, obtain the surgical response data corresponding to the corresponding surgical process node according to the corresponding error operation result, and feedback the surgical response data to the corresponding medical staff.

[0021] In the embodiment of the present invention, service monitoring and management can be carried out on the patients and medical staff corresponding to the coronary artery occlusion surgery. The index visualization curves corresponding to each error operation result set in the storage library for surgical error data of coronary artery occlusion are obtained from the historical data summary of professional medical staff in the historical surgical process. The accuracy of service supervision during the coronary artery occlusion surgery is improved through the surgical service supervision platform.

[0022] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A surgical assistance service supervision system, including a surgical assistance supervision platform, characterized in that, The surgical assistance supervision platform is provided with a service management module, a risk prediction module, a surgical monitoring module, an auxiliary analysis module and a surgical management module; The service management module is used to obtain the patient medical record information corresponding to the patient, the service case information corresponding to the corresponding medical staff, and the historical service supervision information, set a data storage model associated with the surgical process according to the historical service supervision information, and store the obtained patient medical record information and service case information into the corresponding data storage model; The risk prediction model is used to perform risk prediction analysis on the surgical process according to the corresponding patient medical record information and service case information in the data storage model, and obtain risk assessment data in the surgical process; The surgical monitoring module is used to dynamically adjust the surgical monitoring process according to the surgical process and the corresponding risk assessment data, and obtain corresponding surgical monitoring data; The auxiliary analysis module is used to set the auxiliary monitoring evaluation standard data corresponding to the surgical process according to the data storage model, and evaluate and analyze the corresponding surgical monitoring data according to the corresponding auxiliary monitoring evaluation standard data, and obtain the auxiliary analysis data corresponding to the corresponding patient; The surgical management module is used to generate surgical response data for the surgical process of the corresponding patient according to the corresponding auxiliary analysis data, and feedback the obtained surgical response data to the corresponding medical staff.

2. The surgical assistance service supervision system according to claim 1, wherein, The process of obtaining the patient medical record information corresponding to the patient, the service case information corresponding to the corresponding medical staff, and the historical service supervision information includes: A patient collection unit, a medical staff collection unit and a historical collection unit are provided in the service management module; The patient collection unit is provided with a patient input port, a medical staff input port and a device input port, which are respectively used for the patient, the medical staff and the corresponding medical device to input the corresponding patient information, and mark the input patient information as the corresponding patient medical record information; The medical staff collection unit is used to collect the service case information corresponding to the services of the corresponding medical staff, and the service case information is the service process case information of the corresponding patient involved in the work of the corresponding medical staff; The historical collection unit is used to collect the historical service supervision information in the surgical assistance supervision platform, and the historical service supervision information includes the patient medical record information, service case information, surgical monitoring data, auxiliary analysis data and surgical response data corresponding to the patient.

3. The surgical assistance service supervision system according to claim 2, characterized in that, The process of setting a data storage model associated with the surgical process according to the historical service supervision information includes: Obtain the historical service supervision information, set a surgical service supervision data set according to the historical service supervision information, extract key features from the surgical service monitoring data set, obtain corresponding key indicators, and construct a surgical operation process framework according to the obtained key indicators. The surgical operation process framework includes corresponding surgical process nodes and corresponding surgical monitoring data; Set a patient comparison data set and a medical staff comparison data set according to the corresponding surgical process nodes in the surgical operation process framework and the corresponding patient medical record information and service medical record information; The obtained patient control data set and medical staff control data set are respectively analyzed and processed. Association analysis is performed on the corresponding patient control data set and medical staff control data set based on a data mining algorithm to obtain the correlation data between the corresponding parameters and the surgical process nodes. A data storage model is constructed according to the correlation data corresponding to each patient control data set and medical staff control data set. The obtained patient medical record information and service case information are respectively mapped and stored at the corresponding positions in the data storage model.

4. The surgical assistance service supervision system according to claim 3, characterized in that, The process of obtaining the risk assessment data in the surgical process includes: Obtain the patient medical record information and service case information of the corresponding surgery stored in the data storage model, and perform risk assessment on the patient medical record information and service case information associated in the corresponding surgical process nodes in sequence according to the corresponding surgical operation process framework. Preset the key parameters corresponding to the corresponding surgical operation process. A risk assessment model is constructed according to the correlation data between the corresponding patient medical record information and service case information in the data storage model and the corresponding associated parameters. The influence coefficients of the key parameters corresponding to different patient medical record information and service case information are obtained based on the risk assessment model. Integrate the influence coefficients of each key parameter corresponding to the corresponding surgical process node to obtain the process risk assessment data of the corresponding surgical process node. Mark the process risk assessment data corresponding to each surgical process node in the surgical process in sequence to obtain the risk assessment data in the corresponding surgical process.

5. The surgical assistance service supervision system according to claim 4, characterized in that The process of obtaining the corresponding surgical monitoring data includes: Obtain the risk assessment data corresponding to each surgical process node in the surgical process. Set multiple surgical service monitoring devices. The surgical service monitoring devices are respectively used to obtain the surgical monitoring data corresponding to the corresponding surgical process nodes, and the corresponding surgical service monitoring devices are preset with corresponding monitoring standard parameter tables according to the corresponding process risk assessment data. Compare and analyze the process risk assessment data corresponding to the corresponding surgical process node with the monitoring standard parameter table corresponding to the corresponding surgical service monitoring device to obtain the monitoring standard parameters corresponding to the corresponding surgical service monitoring device. Dynamically adjust the monitoring process of the surgical service monitoring device according to the corresponding monitoring standard parameters, and obtain the surgical monitoring data corresponding to the corresponding surgical process node according to the dynamic adjustment result.

6. The surgical assistance service supervision system according to claim 5, wherein The process of setting the auxiliary monitoring and evaluation standard data corresponding to the surgical process according to the data storage model includes: Obtain the patient medical record information, service case information corresponding in the data storage model, and the surgical monitoring data obtained in the corresponding surgical process node. Preset the initial auxiliary evaluation data corresponding to the corresponding surgical process node, and perform preliminary correction processing on the initial auxiliary evaluation data according to the correlation data between the patient medical record information and service case information and the corresponding surgical process node to obtain the corresponding associated auxiliary evaluation data. Perform a correlation analysis on the impact of the surgical monitoring data corresponding to each surgical process node within the surgical operation process framework on the next surgical process node. Set corresponding adjacent data sets for the surgical monitoring data and associated auxiliary evaluation data corresponding to adjacent surgical process nodes, analyze and process the adjacent data sets, and construct an adjacent association model; Input the surgical monitoring data and corresponding associated auxiliary evaluation parameters corresponding to the corresponding surgical process node into the adjacent association model, and output the auxiliary monitoring and evaluation standard data corresponding to the next surgical process node.

7. The surgical assistance service supervision system according to claim 6, characterized in that, The process of obtaining the auxiliary analysis data corresponding to the corresponding patient includes: Compare and analyze the surgical monitoring data of the corresponding surgical process node during the surgical process of the corresponding patient and medical staff with the corresponding auxiliary monitoring and evaluation standard data to obtain the evaluation deviation data corresponding to the corresponding surgical process node; Perform an auxiliary evaluation analysis on the obtained evaluation deviation data, preset deviation standard data. If the evaluation deviation data meets the deviation standard data, no auxiliary warning information is generated; otherwise, auxiliary warning information is generated; Evaluate and analyze the corresponding surgical monitoring data according to the auxiliary warning information, obtain the characteristic data corresponding to the corresponding surgical monitoring data and the corresponding time information, and construct an index visualization curve based on the corresponding time information and the characteristic data of the surgical monitoring data; Preset a surgical error data repository corresponding to the corresponding surgical process node. The surgical error data repository stores an error index comparison curve of possible error operation results for the corresponding surgical process node. Compare and analyze the index visualization curve with the corresponding error index comparison curve in the surgical error data repository, and obtain the auxiliary analysis data corresponding to the corresponding surgical process node according to the matching result.

8. An operation assistance service supervision system according to claim 7, characterized in that, Obtain the matching result of the corresponding error operation result according to the auxiliary analysis data, obtain the surgical response data corresponding to the corresponding surgical process node according to the corresponding error operation result, and feedback the surgical response data to the corresponding medical staff.

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