Clinical intelligent monitoring method for preventing infection of orthopedic surgery site

Abstract

The invention discloses a clinical intelligent monitoring method for preventing infection of an orthopedic surgery site. The method comprises the following steps: (1) converting an orthopedic surgery video signal into analog video signal data of a human skeleton track subjected to desensitization processing in real time; (2) sequentially carrying out data distinguishing, data defining and data processing of endowing time and space position attributes in real time, and then forming a report form; (3) automatically packaging and encrypting the data and then transmitting the data to a database; (4) receiving and decrypting the encrypted data packet, and carrying out granulation disassembly, data standardization coding and data granulation recombination; (5) comparing the granulated and recombined real-time data with reference system data with the same coding standard in a database to obtain a heterogeneity value of the two data; and (6) converting and summarizing the dissimilarity values of the two to obtain an operation behavior score, judging whether an operation error exists or not, if so, displaying an operation error early warning and then ending the operation, otherwise, ending the operation.

Description

Technical Field

[0001] The invention relates to a clinical intelligent monitoring method for preventing infection at an orthopedic surgical site. Background Art

[0002] Surgical site infection (SSI) is a common and serious postoperative complication that poses a significant challenge to hospital infection prevention and control.

[0003] According to research published in the United States, surgical site infections occur in 2%-25% of surgical operations, and the risk of death in patients can increase by 2-11 times. It is estimated that about 750,000 surgical site infections occur in the United States each year. In addition to increasing morbidity and mortality, surgical site infections also prolong patient hospitalization and increase resource utilization costs. Surgical site infections cost the United States approximately $3.5 billion to $10 billion in healthcare costs each year. Since the Centers for Disease Control and Prevention (CDC) issued guidelines for the prevention of surgical site infections in 2017, several countries and societies have issued guidelines for the prevention of surgical site infections and published evidence-based practices to reduce the risk of surgical site infections. According to relevant statistics, the incidence of surgical site infections in orthopedic surgery is as high as 27.8%. This statistic highlights the urgency of taking effective preventive measures in the field of orthopedic surgery.

[0004] In order to improve the safety and patient satisfaction of orthopedic surgery, it is crucial to explore and implement innovative prevention strategies. Existing studies have shown that most surgical site infections are preventable by following evidence-based preventive measures. These measures mainly focus on managing risk factors throughout the entire surgical process, including but not limited to teamwork, surgical skills, standardization of surgical hand disinfection, aseptic operation, and operating room environmental control. Despite the existence of a series of preventive measures, existing technologies are insufficient in monitoring and evaluating the aseptic operation of medical staff. In particular, there is a lack of an effective method to record and quantify the impact of medical staff behavior on the surgical outcomes of orthopedic patients, which limits the evaluation of the implementation of preventive measures and the optimization of infection control strategies, and cannot evaluate the efficacy of the relevant nodes of the prevention of orthopedic surgical site infections.

[0005] Related studies have pointed out that the operating behaviors of medical staff, especially their technical habits in aseptic operation, have a direct impact on the incidence of surgical site infection. These behaviors are also closely related to key medical outcomes such as the success rate of surgical operations, the quality of life of patients, and survival rate.

[0006] The standardization and correctness of medical staff's surgical and dressing change operation behaviors, especially the establishment of new medical staff's operating habits, have a significant impact on reducing the incidence of orthopedic surgical site infection. However, there is no systematic study on medical staff's surgical and dressing change operation behaviors at home and abroad. Summary of the invention

[0007] Purpose of the invention: The present invention aims to improve the problems existing in the above-mentioned prior art, that is, the present invention discloses a clinical intelligent monitoring method for preventing orthopedic surgical site infection. The present invention combines the measurement system of Internet of Things technology, data communication technology, database technology and mathematical modeling tools, aiming to improve the standardization of aseptic operation behavior of medical staff, thereby effectively reducing the incidence of surgical site infection.

[0008] The present invention establishes a standard reference system, measures the operation behavior and forms a data index based on the relationship between the recorded operation behavior data and the reference system data, and provides a new index for effectively evaluating the behavior-based surgical site infection prevention node. This method not only provides a new perspective for the prevention of surgical site infection, but also provides a scientific basis for improving the standardization and safety of surgical operations.

[0009] Technical solution: A clinical intelligent monitoring method for preventing orthopedic surgical site infection, the steps are as follows:

[0010] Step (1), using an intelligent machine vision system to convert the orthopedic surgery video signal into analog video signal data of the human skeleton trajectory in real time, desensitizing the operation behavior of the video character acquisition object in the analog video signal data, realizing real-time video compression and simulation of the camera captured video, and then entering step (2);

[0011] (2) The desensitized analog video signal data is transmitted to the data processing module. According to the preset target requirements, the data processing module sequentially performs data differentiation, data definition, and real-time data processing of the desensitized analog video signal data, and then forms a report form in combination with the data with a feasible solution, so that the desensitized analog video signal data has the corresponding data fields required by the target, and then enters step (3);

[0012] (3) Automatically package the data processed in step (2), encrypt and transmit to the database, and then proceed to step (4);

[0013] (4) receiving and decrypting the encrypted data packet sent in step (3), and performing granular disassembly, data standardization encoding and data granular reorganization on the data packet in sequence according to the clinical analysis purpose, and then proceeding to step (5);

[0014] (5) Compare the real-time data reorganized by granulation in step (4) with the reference data with the same coding standard stored in the database in advance to obtain the difference value between the two, and then proceed to step (6);

[0015] (6) The difference values ​​of the two obtained in step (5) are converted and summarized into corresponding quantitative indicators, that is, the operation behavior score is obtained to determine whether there is an operation error. If there is an operation error, the operation error warning is displayed and the operation is terminated. If there is no operation error, the operation is terminated.

[0016] Furthermore, the intelligent machine vision system in step (1) includes a machine vision system, an AI system and a pattern recognition system.

[0017] Furthermore, in step (1), an intelligent machine vision system is used to monitor the detailed steps and time required for medical staff to perform surgical hand disinfection, wherein:

[0018] The intelligent machine vision system will evaluate whether the medical staff's hand disinfection process strictly follows the established hygiene standards. If any non-compliant operations are detected, the intelligent machine vision system will automatically send out a warning signal to prompt the medical staff to re-execute the hand hygiene process to ensure the safety of the operation.

[0019] Furthermore, in step (1):

[0020] A dedicated intelligent machine vision system is deployed at the entrance of the operating room. After the operation begins, the intelligent machine vision system will continuously monitor the entry and exit of medical staff. Once it detects that the flow of medical staff exceeds the preset threshold, the intelligent machine vision system will issue an early warning message to maintain the sterile environment of the operating room.

[0021] Furthermore, the preset threshold is 10 persons.

[0022] Furthermore, in step (1): based on the identity and duties of the medical staff, an intelligent machine vision system is used to monitor the position and range of activities of the medical staff in the operating room, wherein:

[0023] The surgeon and the instrument nurse are restricted to activities within the sterile area;

[0024] Circulating nurses and anesthesiologists should stay in the area surrounding the surgery and are strictly prohibited from crossing the sterile area;

[0025] Once it is discovered that the medical staff's standing position and range of activities do not comply with the standing rules, the intelligent machine vision system will issue a warning message.

[0026] Furthermore, in step (1):

[0027] A dedicated intelligent machine vision system is deployed at the entrance of the dressing room to identify the medical staff's information and check whether they are wearing masks, hats, and gloves correctly.

[0028] During the dressing change process, the intelligent machine vision system will monitor whether medical staff strictly follow aseptic operation and hand hygiene standards to ensure the safety and effectiveness of wound dressing changes;

[0029] If the intelligent machine vision system detects improper operation or violation of regulations, it will issue an early warning message to guide medical staff to take correct operating steps.

[0030] Furthermore, the data processing module in step (2) exists in the form of a mobile phone application.

[0031] Furthermore, in step (2), the data processing module also performs data cleaning on the desensitized analog video signal data before performing data differentiation, data definition, and real-time data processing of assigning time and spatial position attributes to the desensitized analog video signal data.

[0032] The present invention utilizes the newly developed "machine vision and AI pattern recognition technology" with Internet of Things function to automatically transmit the real-time remote data of medical staff at the corresponding time nodes specified in surgical hand disinfection, operating room personnel entry and exit, operating room position and activity range, and aseptic dressing change behavior to a predetermined database, and constructs a standard reference system for surgical hand disinfection of medical staff, operating room personnel entry and exit management, standard position and activity range, and aseptic dressing change operation. Through data granulation and granular reorganization and other means, the dataization and effective scoring of medical staff's operating behavior are realized, and effective indicators for corresponding diagnosis and treatment nodes for orthopedic surgical site infection prevention are constructed through behavioral research, and the aseptic operation behavior of medical staff and the operating room environment management are effectively standardized.

[0033] The database structure, cross-reference relationship between data, collection of key data, granular disassembly of data chain, granular reorganization and data coding in the present invention are finally formed by the inventor with the aseptic operation specification for preventing orthopedic surgical site infection as the core, and effectively integrating key technologies such as the Internet of Things, mobile communication, and data comparison reference. The core technology is the experience summary centered on aseptic technology and converted into computer network database language.

[0034] Beneficial effects: The clinical intelligent monitoring method for preventing orthopedic surgical site infection disclosed in the present invention has the following beneficial effects:

[0035] Through the technical solution of the present invention, the aseptic operation behaviors such as surgical hand disinfection and dressing change of medical personnel can be effectively regulated, which improves the scientificity and systematicness of surgical site infection prevention, thereby reducing the incidence of orthopedic surgical site infection and improving the patient's quality of life and medical safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The present invention discloses a flow chart of a clinical intelligent monitoring method for preventing orthopedic surgical site infection. DETAILED DESCRIPTION

[0037] The specific embodiments of the present invention are described in detail below.

[0038] The "range" disclosed in the present invention is defined in the form of a lower limit and an upper limit, and a given range is defined by selecting a lower limit and an upper limit, and the selected lower limit and upper limit define the boundaries of the particular range. The range defined in this way can be inclusive or exclusive of the end values, and can be arbitrarily combined, that is, any lower limit can be combined with any upper limit to form a range. For example, if a range of 10 to 50 is listed for a specific parameter, it is understood that the range of 10 to 40 and 20 to 50 is also expected. In addition, if the minimum range values ​​1 and 2 are listed, and if the maximum range values ​​3, 4 and 5 are listed, the following ranges can all be expected: 1 to 3, 1 to 4, 1 to 5, 2 to 3, 2 to 4 and 2 to 5. In this application, unless otherwise specified, the range of values ​​"a to b" represents an abbreviation of any real number combination between a and b, where a and b are both real numbers. For example, the range of values ​​"0 to 5" means that all real numbers between "0 to 5" have been fully listed in this article, and "0 to 5" is only an abbreviation of these numerical combinations.

[0039] If not otherwise specified, all embodiments and optional embodiments of the present application can be combined with each other to form a new technical solution.

[0040] Unless otherwise specified, all technical features and optional technical features of this application can be combined with each other to form a new technical solution.

[0041] If there is no special explanation, all steps of the present application can be performed sequentially or randomly, preferably sequentially. For example, the method includes steps (a) and (b), which means that the method may include steps (a) and (b) performed sequentially, or may include steps (b) and (a) performed sequentially. For example, the method may further include step (c), which means that step (c) may be added to the method in any order. For example, the method may include steps (a), (b) and (c), or may include steps (a), (c) and (b), or may include steps (c), (a) and (b), etc.

[0042] If there is no special explanation, the "include" and "comprising" mentioned in this application are open-ended or closed-ended. For example, the "include" and "comprising" may mean that other components not listed may also be included or only the listed components may be included or only the listed components may be included.

[0043] Unless otherwise specified, the reaction is carried out at room temperature and pressure.

[0044] Unless otherwise specified, all parts or percentages are by weight.

[0045] In the present invention, all substances used are known substances and can be purchased or synthesized by known methods.

[0046] In the present invention, the devices or equipment used are all conventional devices or equipment known in the art and are commercially available.

[0047] A clinical intelligent monitoring method for preventing orthopedic surgical site infection, the steps are as follows:

[0048] Step (1), using an intelligent machine vision system to convert the orthopedic surgery video signal into analog video signal data of the human skeleton trajectory in real time, desensitizing the operation behavior of the video character acquisition object in the analog video signal data, realizing real-time video compression and simulation of the camera captured video, and then entering step (2);

[0049] (2) The desensitized analog video signal data is transmitted to the data processing module. According to the preset target requirements, the data processing module sequentially performs data differentiation, data definition, and real-time data processing of the desensitized analog video signal data, and then forms a report form in combination with the data with a feasible solution, so that the desensitized analog video signal data has the corresponding data fields required by the target, and then enters step (3);

[0050] (3) Automatically package the data processed in step (2), encrypt and transmit to the database, and then proceed to step (4);

[0051] (4) receiving and decrypting the encrypted data packet sent in step (3), and performing granular disassembly, data standardization encoding and data granular reorganization on the data packet in sequence according to the clinical analysis purpose, and then proceeding to step (5);

[0052] (5) Compare the real-time data reorganized by granulation in step (4) with the reference data with the same coding standard stored in the database in advance to obtain the difference value between the two, and then proceed to step (6);

[0053] (6) The difference values ​​of the two obtained in step (5) are converted and summarized into corresponding quantitative indicators, that is, the operation behavior score is obtained to determine whether there is an operation error. If there is an operation error, the operation error warning is displayed and the operation is terminated. If there is no operation error, the operation is terminated.

[0054] Furthermore, the intelligent machine vision system in step (1) includes a machine vision system (MV system), an AI system and a pattern recognition system (PR system), that is, a machine vision and AI pattern recognition system (MVAIPR system).

[0055] Furthermore, in step (1), an intelligent machine vision system is used to monitor the detailed steps and time required for medical staff to perform surgical hand disinfection, wherein:

[0056] The intelligent machine vision system will evaluate whether the medical staff's hand disinfection process strictly follows the established hygiene standards. If any non-compliant operations are detected, the intelligent machine vision system will automatically send out a warning signal to prompt the medical staff to re-execute the hand hygiene process to ensure the safety of the operation.

[0057] Furthermore, in step (1):

[0058] A dedicated intelligent machine vision system is deployed at the entrance of the operating room. After the operation begins, the intelligent machine vision system will continuously monitor the entry and exit of medical staff. Once it detects that the flow of medical staff exceeds the preset threshold, the intelligent machine vision system will issue an early warning message to maintain the sterile environment of the operating room.

[0059] Furthermore, the preset threshold is 10 persons.

[0060] Furthermore, in step (1): based on the identity and duties of the medical staff, an intelligent machine vision system is used to monitor the position and range of activities of the medical staff in the operating room, wherein:

[0061] The surgeon and the instrument nurse are restricted to activities within the sterile area;

[0062] Circulating nurses and anesthesiologists should stay in the area surrounding the surgery and are strictly prohibited from crossing the sterile area;

[0063] Once it is found that the position and range of movement of medical staff do not comply with the position rules, the intelligent machine vision system will issue an early warning message. The intelligent machine vision system monitors the position in real time to ensure that all personnel comply with the prescribed position rules to avoid cross contamination.

[0064] Furthermore, in step (1):

[0065] A dedicated intelligent machine vision system is deployed at the entrance of the dressing room to identify the medical staff's information and check whether they are wearing masks, hats, and gloves correctly.

[0066] During the dressing change process, the intelligent machine vision system will monitor whether medical staff strictly follow aseptic operation and hand hygiene standards to ensure the safety and effectiveness of wound dressing changes;

[0067] If the intelligent machine vision system detects improper operation or violation of regulations, it will issue an early warning message to guide medical staff to take correct operating steps.

[0068] Furthermore, the data processing module in step (2) exists in the form of a mobile phone application (mobile phone App).

[0069] Furthermore, in step (2), the data processing module also performs data cleaning on the desensitized analog video signal data before performing data differentiation, data definition, and real-time data processing of assigning time and spatial position attributes to the desensitized analog video signal data.

[0070] The above describes the embodiments of the present invention in detail. However, the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of ordinary technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A clinical intelligent monitoring method for preventing orthopedic surgical site infection, characterized in that: Here are the steps: Step (1), using an intelligent machine vision system to convert the orthopedic surgery video signal into analog video signal data of the human skeleton trajectory in real time, desensitizing the operation behavior of the video character acquisition object in the analog video signal data, realizing real-time video compression and simulation of the camera captured video, and then entering step (2); (2) The desensitized analog video signal data is transmitted to the data processing module. According to the preset target requirements, the data processing module sequentially performs data differentiation, data definition, and real-time data processing of the desensitized analog video signal data, and then forms a report form in combination with the data with a feasible solution, so that the desensitized analog video signal data has the corresponding data fields required by the target, and then enters step (3); (3) Automatically package the data processed in step (2), encrypt and transmit to the database, and then proceed to step (4); (4) receiving and decrypting the encrypted data packet sent in step (3), and performing granular disassembly, data standardization encoding and data granular reorganization on the data packet in sequence according to the clinical analysis purpose, and then proceeding to step (5); (5) Compare the real-time data reorganized by granulation in step (4) with the reference data with the same coding standard stored in the database in advance to obtain the difference value between the two, and then proceed to step (6); (6) The difference values ​​of the two obtained in step (5) are converted and summarized into corresponding quantitative indicators, that is, the operation behavior score is obtained to determine whether there is an operation error. If there is an operation error, the operation error warning is displayed and the operation is terminated. If there is no operation error, the operation is terminated.

2. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: The intelligent machine vision system described in step (1) includes a machine vision system, an AI system and a pattern recognition system.

3. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: In step (1), an intelligent machine vision system is used to monitor the detailed steps and time required for medical staff to perform surgical hand disinfection, wherein: The intelligent machine vision system will evaluate whether the medical staff's hand disinfection process strictly follows the established hygiene standards. If any non-compliant operations are detected, the intelligent machine vision system will automatically send out a warning signal to prompt the medical staff to re-execute the hand hygiene process to ensure the safety of the operation.

4. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: In step (1): A dedicated intelligent machine vision system is deployed at the entrance of the operating room. After the operation begins, the intelligent machine vision system will continuously monitor the entry and exit of medical staff. Once it detects that the flow of medical staff exceeds the preset threshold, the intelligent machine vision system will issue an early warning message to maintain the sterile environment of the operating room.

5. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 4, characterized in that: The preset threshold is 10 persons.

6. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: In step (1): based on the identity and responsibilities of the medical staff, an intelligent machine vision system is used to monitor the position and range of activities of the medical staff in the operating room, wherein: The surgeon and the instrument nurse are restricted to activities within the sterile area; Circulating nurses and anesthesiologists should stay in the area surrounding the surgery and are strictly prohibited from crossing the sterile area; Once it is discovered that the medical staff's standing position and range of activities do not comply with the standing rules, the intelligent machine vision system will issue a warning message.

7. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: In step (1): A dedicated intelligent machine vision system is deployed at the entrance of the dressing room to identify the medical staff's information and check whether they are wearing masks, hats, and gloves correctly. During the dressing change process, the intelligent machine vision system will monitor whether medical staff strictly follow aseptic operation and hand hygiene standards to ensure the safety and effectiveness of wound dressing changes; If the intelligent machine vision system detects improper operation or violation of regulations, it will issue an early warning message to guide medical staff to take correct operating steps.

8. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: The data processing module of step (2) exists in the form of a mobile phone application.

9. A clinical intelligent monitoring method for preventing orthopedic surgical site infection as claimed in claim 1, characterized in that: In step (2), the data processing module performs data cleaning on the desensitized analog video signal data before performing data differentiation, data definition, and real-time data processing of assigning time and spatial location attributes to the desensitized analog video signal data.

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