Method and system for use management of icu equipment

Abstract

The invention relates to an icu equipment use management method and system. The method comprises the following steps: generating a corresponding unique digital identifier according to warehousing information of equipment; taking the unique digital identifier as basic identifier information of equipment full-life-cycle management; obtaining an equipment dynamic grading result; constructing an equipment-personnel-post three-dimensional permission matrix based on the dynamic grading result of the equipment and the qualification information of the operator; on the basis of the unique digital identifier, the dynamic grading result and the data of the three-dimensional permission matrix, generating an equipment-adaptive maintenance scheduling instruction; performing maintenance scheduling on the equipment in response to an adaptive maintenance scheduling instruction of the equipment, obtaining a deviation value of generated abnormal maintenance data and equipment operation parameters, and triggering a multi-level fault early warning signal for the fault equipment; and generating a maintenance resource allocation scheme for the fault equipment based on the fault early warning signal and preset supplier historical service data. According to the invention, the efficiency and precision of use management of the icu equipment can be improved.

Description

Technical Field

[0001] The present invention relates to the field of information management technology, and in particular to a method, system, electronic device and non-transitory computer-readable storage medium for managing the use of ICU equipment. Background Art

[0002] Nowadays, the ICU department of a hospital is usually equipped with a large number of key medical equipment, such as ECG monitors, ventilators, micro pumps, bronchoscopes, defibrillators, etc.

[0003] However, existing methods for managing ICU equipment usage have numerous shortcomings. They lack automatic maintenance reminders, continuous tracking of equipment status, and risk warning mechanisms. This is particularly true for equipment that requires frequent repairs within the warranty period or has a high failure rate outside of warranty. Furthermore, there is a lack of an assessment mechanism for those responsible for repairs and maintenance, hindering both efficient and safe equipment management. Summary of the Invention

[0004] The present invention addresses the technical problems existing in the prior art and provides a method, system, electronic device and non-transitory computer-readable storage medium for managing device usage.

[0005] The technical solution of the present invention to solve the above technical problems is as follows: The present invention provides a method for managing the use of ICU equipment, the method comprising: Generate a corresponding unique digital identifier based on the device's storage information; use the unique digital identifier as the basic identification information for the device's full life cycle management; Based on the unique digital identifier and the real-time operating parameters of the device, dynamically grading the device risk to obtain a dynamic grading result of the device; Based on the dynamic classification results of the equipment and the qualification information of the operators, a three-dimensional permission matrix of equipment-personnel-position is constructed to limit the use rights of high-risk equipment; Generate equipment adaptive maintenance scheduling instructions based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; Perform maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment, obtain the deviation value between the generated abnormal maintenance data and the equipment operating parameters, and trigger multi-level fault warning signals for the faulty equipment; Based on the fault warning signal and preset supplier historical service data, a maintenance resource deployment plan for the faulty equipment is generated.

[0006] Optionally, generating a corresponding unique digital identifier based on the storage information of the device includes: Collect basic information about the device; the basic information includes device model, serial number, manufacturer information, purchase date, price, and warranty period; Building a structured digital device archive based on the basic information; By generating a corresponding QR code and RFID electronic tag, the digital device file is bound to the device entity to obtain the binding information of the device; The binding information is mapped and registered with the device management platform to generate the unique digital identifier used for subsequent life cycle management of the device.

[0007] Optionally, the dynamically grading the risk of the device based on the unique digital identifier and the real-time operating parameters of the device to obtain a dynamic risk grading result of the device includes: Real-time collection of operating parameters of the equipment; the operating parameters include operating time, startup frequency, load status and abnormal alarm data; Cleaning, standardizing, and feature extracting the operating parameters to obtain processed operating parameters; Based on the set risk assessment model, weighted scoring is performed on the processed operating parameters to obtain corresponding scoring results; According to the scoring results, each of the devices is divided into low risk, medium risk, high risk and extremely high risk levels, and the division results are used as the dynamic classification results.

[0008] Optionally, the three-dimensional authority matrix of equipment-personnel-position is constructed based on the dynamic classification results of the equipment and the qualification information of the operators, including: Obtain the scope of responsibilities and operating authority levels corresponding to each position; Read the operator's qualification information based on the scope of responsibilities and the level of operation authority; the qualification information includes training records, assessment results, certification level and violation records; Correlating and matching the dynamic classification result of the equipment with the position information and qualification information of the operator to obtain a matching result; The three-dimensional permission matrix is ​​constructed based on the matching results, and permission boundary conditions are set to limit unauthorized operations.

[0009] Optionally, generating a device adaptive maintenance scheduling instruction based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix includes: Collecting statistics on the key information of the equipment; the key information includes usage frequency, cumulative operating time, load intensity and number of historical failures; Setting a basic maintenance cycle based on the dynamic classification results of the equipment, and determining the priority of the equipment for maintenance scheduling in combination with the critical information of the equipment; Obtain the current department workload and maintenance resource scheduling information; According to the priority, the workload of the current department and the scheduling information of the maintenance resources, a corresponding maintenance time window and the maintenance scheduling instruction are generated through a scheduling algorithm.

[0010] Optionally, performing maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment and obtaining a deviation value between the generated abnormal maintenance data and the equipment operating parameter includes: Execute the maintenance scheduling instructions and simultaneously record the equipment operating status and key parameters during maintenance execution; Collecting the response behavior of the equipment during maintenance; the response behavior includes performance recovery curve, control feedback index and operation deviation; The response behavior is compared and analyzed with the operating parameters of the equipment before maintenance, and the deviation value is calculated.

[0011] Optionally, triggering a multi-level fault warning signal for a faulty device includes: Determining the severity of the fault of the faulty device based on the deviation value; When the deviation value exceeds the preset fault threshold, a yellow, orange, red or emergency warning signal is triggered according to the threshold range; The fault level, occurrence frequency, risk category and possible impact scope associated with the warning signal form a structured warning event; The structured warning events are pushed to the corresponding equipment responsible person, technical supervisor and ICU management system.

[0012] Optionally, generating a maintenance resource allocation plan for the faulty equipment based on the fault warning signal and preset supplier historical service data includes: Calling the manufacturer's service history data corresponding to the device; the manufacturer's service history data includes average response time, repair success rate, parts replacement record and service attitude score; Obtain currently available maintenance resources; these include in-hospital maintenance engineers, manufacturer technical support, and third-party maintenance organizations; Prioritizing the manufacturer's service history data and the maintenance resources based on a service capability scoring model to obtain a ranking result; According to the ranking results and the current maintenance urgency of the faulty equipment, a maintenance resource allocation plan for the faulty equipment is generated, and tasks are automatically assigned and notifications are issued.

[0013] Optionally, the method further includes: Periodically collecting core performance parameters of the device and calculating the performance degradation trend of the device based on historical benchmark data; Based on the performance degradation trend, maintenance frequency, and maintenance cost, the remaining service life and economic applicability of the equipment are evaluated to obtain corresponding evaluation results; Based on the evaluation results, an equipment update recommendation report is generated, including the reasons for the update, alternative equipment recommendations, and budget assessment.

[0014] The present invention also provides a system for managing the use of ICU equipment, the system comprising: An identification generation module is used to generate a corresponding unique digital identification according to the storage information of the device; and use the unique digital identification as the basic identification information for the full life cycle management of the device; A risk grading module, configured to dynamically grade the risk of the device based on the unique digital identifier and the real-time operating parameters of the device, and obtain a dynamic risk grading result of the device; The permission matrix module is used to construct a three-dimensional permission matrix of equipment-personnel-position based on the dynamic classification results of the equipment and the qualification information of the operators, so as to limit the use rights of high-risk equipment; A maintenance scheduling module, configured to generate adaptive maintenance scheduling instructions for the equipment based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; A fault warning module is used to perform maintenance scheduling on the equipment in response to the equipment's adaptive maintenance scheduling instructions, obtain the deviation between the generated abnormal maintenance data and the equipment's operating parameters, and trigger a multi-level fault warning signal for the faulty equipment; The maintenance allocation module is used to generate a maintenance resource allocation plan for the faulty equipment based on the fault warning signal and preset supplier historical service data.

[0015] In addition, to achieve the above objectives, the present invention also proposes an electronic device, comprising: a memory for storing computer software programs; a processor for reading and executing the computer software programs, thereby implementing a method for managing the use of an ICU device as described above.

[0016] In addition, to achieve the above-mentioned purpose, the present invention also proposes a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by a processor, it implements a method for managing the use of an ICU device as described above.

[0017] The beneficial effects of the present invention are: (1) The present invention uses a unique digital identifier (digital passport) to conduct closed-loop tracking management of the entire process of equipment from storage, use, maintenance to update, significantly improving the traceability of equipment information and management accuracy.

[0018] (2) The present invention combines the dynamic assessment of equipment operation risks with the qualification information of medical staff to construct a three-dimensional authority matrix, realizing hierarchical authorization and precise use control of high-risk equipment, significantly reducing the risks of operational errors and safety accidents.

[0019] (3) The present invention dynamically generates maintenance scheduling instructions by analyzing equipment type, load, usage frequency and clinical pressure, thereby improving the scientific nature and timeliness of maintenance work and effectively avoiding the phenomenon of "over-maintenance" or "under-maintenance". BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flowchart of a method for managing the use of ICU equipment provided by the present invention; Figure 2 A schematic diagram of the structure of an ICU equipment use management system provided by the present invention; Figure 3 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention; Figure 4 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0022] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0023] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or illustration". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0024] See also Figure 1 , provides a flowchart of a method for managing the use of ICU equipment of the present invention, comprising the following steps: Step 201: Generate a corresponding unique digital identifier based on the device's storage information.

[0025] The unique digital identifier is used as the basic identification information for the entire life cycle management of the device.

[0026] In some embodiments, step 201 may include: Collect basic information about the device; the basic information includes device model, serial number, manufacturer information, purchase date, price, and warranty period; Building a structured digital device archive based on the basic information; By generating a corresponding QR code and RFID electronic tag, the digital device file is bound to the device entity to obtain the binding information of the device; The binding information is mapped and registered with the device management platform to generate the unique digital identifier used for subsequent life cycle management of the device.

[0027] Specifically, during the ICU equipment warehousing phase, basic equipment information is collected and recorded for subsequent identification and management. This basic information includes at least: equipment model, unique serial number, manufacturer information (manufacturer name, contact information), purchase date, purchase price, warranty period, and service level information.

[0028] Based on the basic information collected above, a structured data model is constructed to form a digital device profile unique to the device. This digital profile can be encapsulated using data structures such as JSON / XML, which is scalable and system-compatible, making it easy to connect with other systems (such as HIS and material management systems).

[0029] To physically bind digital files to physical devices, the system automatically generates a QR code (for manual identification and scanning) and an RFID tag (for automatic radio frequency identification and rapid inventory) corresponding to the device file. These QR codes and RFID tags are printed or embedded into the device itself, forming the device's binding information.

[0030] This binding information can be uploaded to the device intelligent management platform, where it is mapped to the device profile and registered, generating a unique digital identifier (Digital UID) for the device. This digital identifier is non-repeatable and traceable throughout its lifecycle, serving as a unified identification entry for all subsequent operations (such as tiered assessments, permission authorization, maintenance scheduling, risk warnings, and update decisions).

[0031] Through the above steps, the present invention can establish a unique digital identity for each ICU medical device, realize the binding of digital archives and physical devices, ensure the consistency of data and traceability of operations in device management, build a basic information framework for the management of the entire life cycle of the device, and provide data support for subsequent dynamic classification, authority control and intelligent maintenance modules.

[0032] Step 202: Based on the unique digital identifier and the real-time operating parameters of the device, dynamically classify the device risk to obtain a dynamic device classification result.

[0033] In some embodiments, step 202 may include: Real-time collection of operating parameters of the equipment; the operating parameters include operating time, startup frequency, load status and abnormal alarm data; Cleaning, standardizing, and feature extracting the operating parameters to obtain processed operating parameters; Based on the set risk assessment model, weighted scoring is performed on the processed operating parameters to obtain corresponding scoring results; According to the scoring results, each of the devices is divided into low risk, medium risk, high risk and extremely high risk levels, and the division results are used as the dynamic classification results.

[0034] Specifically, the device's operating parameters during actual use can be collected in real time through built-in or external IoT acquisition terminals (such as temperature sensors, current sensors, operation recording modules, control interfaces, etc.). These operating parameters include at least: operating time: the continuous operating time from the device's startup to the current time, and the cumulative operating time; startup frequency: the number of times the device is started per unit time; load status: the power load, current, voltage, or other data related to the device's operating intensity during operation; abnormal alarm data: alarm event information from the device's self-diagnostic system or external safety system, including fault code, alarm level, and occurrence frequency. The above-mentioned collected data is uploaded to the central server through the edge computing node or is bound to the device's unique digital identifier.

[0035] The collected operating parameters may be subjected to data preprocessing, the processing including: Missing value filling: use interpolation, mean value or model prediction method to fill missing data; Outlier identification and elimination: Eliminate abnormally high / low values ​​caused by sensor failure or miscommunication; Time window normalization: standardize the parameters according to a unified time unit (such as hours or days); Feature extraction processing: Extract trend characteristics (such as fluctuation amplitude and change slope), stability indicators (such as standard deviation), and key event counts. This generates structured and standardized post-processing operating parameters as input for risk modeling.

[0036] A preset risk assessment model (which can be a weighted scoring model, a decision tree model, or a machine learning model) can be called to perform a weighted score on the post-processing operating parameters of each device. The model assigns preset weights to different parameters, such as the operating time weight. ; Start frequency weight ; Load state stability weight ; Abnormal alarm frequency weight ; The comprehensive score result is calculated by the following general expression:

[0037] in, is the equipment operation risk score, is the normalized running time, is the frequency of starts per unit time, is the load status score, It is the abnormal alarm score.

[0038] The risk score result can be compared with the set multi-level risk threshold to classify the current risk level of the device. The risk level classification rules may include the following criteria: Low Risk: Score Medium risk: ; High risk: ; Very high risk: .

[0039] in The risk score threshold set for the system supports dynamic adjustment.

[0040] Ultimately, the risk level of each device can be used as its current dynamic classification result and stored in the device digital file for subsequent management decision-making processes such as authority control, maintenance scheduling and early warning response.

[0041] In summary, this invention achieves objective, quantitative analysis of the actual operating status of equipment through real-time collection and multi-dimensional processing of operational data. The introduction of a standardized scoring system and multi-level risk grading strategy not only improves the accuracy of equipment risk identification but also enhances the foresight and operability of equipment management, effectively supporting subsequent intelligent maintenance, permission setting, and emergency response processes.

[0042] Step 203: Based on the dynamic classification results of the equipment and the qualification information of the operators, a three-dimensional permission matrix of equipment-personnel-position is constructed to limit the use authority of high-risk equipment.

[0043] In some embodiments, step 203 may include: Obtain the scope of responsibilities and operating authority levels corresponding to each position; Read the operator's qualification information based on the scope of responsibilities and the level of operation authority; the qualification information includes training records, assessment results, certification level and violation records; Correlating and matching the dynamic classification result of the equipment with the position information and qualification information of the operator to obtain a matching result; The three-dimensional permission matrix is ​​constructed based on the matching results, and permission boundary conditions are set to limit unauthorized operations.

[0044] Specifically, the scope of responsibilities and operating authority levels corresponding to each operating position in the medical institution can be obtained. Among them: the scope of responsibilities is used to define the functional boundaries of the position in the management of medical equipment use, such as "primary use", "daily maintenance of equipment", "technical support debugging", "system security review", etc. The operating authority level is used to indicate the permission level of each position in equipment operation, and is set according to the grading principle from low to high, such as P1 (read-only permission), P2 (operation permission), P3 (maintenance permission), P4 (administrator permission), etc. Position responsibilities and authority levels can be preset and imported by the hospital personnel system or ICU management platform, or they can be manually configured and entered.

[0045] Based on job responsibilities and permission level requirements, the corresponding operator's qualification information can be retrieved. This qualification information includes but is not limited to: training records (including the equipment-related training courses the person has completed and the completion time); assessment results (including theoretical and practical exam scores, pass status, and rating); certification levels (such as manufacturer authorization certification and professional qualification level); and violation records (including historical violations and disciplinary actions during use). This qualification information can be obtained from the medical personnel information management platform, training system, log tracing module, etc.

[0046] The current dynamic classification results of the equipment (such as low risk, medium risk, high risk, and very high risk) can be cross-correlated and matched with the operator's job information and qualification information. The matching logic may include: If the device is classified as high-risk or above, a matching person with a high-level permission level (e.g., P3 or above), who has passed the assessment and has no violation record, must be found. If the job description does not include the device category, the person is considered unmatched. If the training record is expired or the certification is invalid, the operation permission will be downgraded or locked. The matching result can be marked as "operation allowed," "operation restricted," or "operation prohibited."

[0047] Based on the matching results, a three-dimensional permission matrix can be constructed. This matrix uses "device ID - position number - person ID" as the coordinate axes, establishing a permission mapping relationship for each entity operation scenario. The values ​​in the matrix represent the executable operation permission level, forming a three-dimensional restriction rule for device, position, and person.

[0048] Based on the three-dimensional permission matrix, boundary control conditions can be set to limit unauthorized or unauthorized operations. Specifically, when the system detects that a person attempts to operate a device that does not match their permission, it will automatically issue an alarm and deny the operation; the system supports dynamic generation of authorization and approval processes based on the permission matrix; all unauthorized attempts will be recorded and included in the violation audit module.

[0049] In summary, this solution achieves precise permission management for ICU medical equipment by constructing a three-dimensional permission matrix of equipment, position, and personnel, and setting fine-grained boundary condition controls. This effectively prevents unauthorized personnel from misoperating high-risk equipment, thereby reducing human risk and improving the safety and standardization of ICU operations. Furthermore, this mechanism supports dynamic updates and audit tracking, and has good maintainability and scalability.

[0050] Step 204: Generate equipment adaptive maintenance scheduling instructions based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix.

[0051] In some embodiments, step 204 may include: Collecting statistics on the key information of the equipment; the key information includes usage frequency, cumulative operating time, load intensity and number of historical failures; Setting a basic maintenance cycle based on the dynamic classification results of the equipment, and determining the priority of the equipment for maintenance scheduling in combination with the critical information of the equipment; Obtain the current department workload and maintenance resource scheduling information; According to the priority, the workload of the current department and the scheduling information of the maintenance resources, a corresponding maintenance time window and the maintenance scheduling instruction are generated through a scheduling algorithm.

[0052] Specifically, key information about the device can be collected, including but not limited to: usage frequency (the number of times the device is started or used within a specific time period); cumulative operating time (the total cumulative operating time of the device, reflecting the degree of wear and tear); load intensity (the load conditions during device operation, such as peak load and average load); and historical failure counts (the number of historical failures recorded on the device, reflecting the device's health). This key information is derived from real-time data collection by the device's sensor module and the device maintenance history database.

[0053] Based on the dynamic risk grading results of the equipment, basic maintenance cycles can be set for the equipment, for example, longer maintenance cycles for low-risk equipment and shorter maintenance cycles for high-risk equipment. The maintenance scheduling priority of the equipment is calculated based on its criticality information. This priority is determined by comprehensively considering the equipment's importance, usage intensity, and failure risk, ensuring that key equipment receives priority maintenance.

[0054] The current clinical workload of the department can be obtained, including bed occupancy, medical staffing status, and surgical schedules. At the same time, the maintenance team's schedule information and available maintenance resources can be obtained as scheduling constraints.

[0055] By combining maintenance priorities, department workload, and maintenance resource scheduling, scheduling algorithms (such as weighted priority queues or optimization models) can generate appropriate maintenance time windows and generate corresponding maintenance scheduling instructions. These scheduling instructions clearly define the equipment to be maintained, the time period, the maintenance content, and the responsible personnel, ensuring that maintenance activities can be carried out smoothly without affecting clinical work.

[0056] In summary, by statistically analyzing critical equipment information and combining it with the department's real-time workload and maintenance resource conditions, this solution achieves dynamic self-adaptation of equipment maintenance scheduling, significantly improves maintenance efficiency, avoids the risk of maintenance interfering with clinical work, and ensures that the equipment's health status continues to meet the high-standard clinical needs of the ICU.

[0057] Step 205: Perform maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment, obtain the deviation value between the generated abnormal maintenance data and the equipment operating parameters, and trigger a multi-level fault warning signal for the faulty equipment.

[0058] In some embodiments, step 205 may include: Execute the maintenance scheduling instructions and simultaneously record the equipment operating status and key parameters during maintenance execution; Collecting the response behavior of the equipment during maintenance; the response behavior includes performance recovery curve, control feedback index and operation deviation; The response behavior is compared and analyzed with the operating parameters of the equipment before maintenance, and the deviation value is calculated.

[0059] Specifically, according to the adaptive maintenance scheduling instructions issued by the maintenance management module, the system or maintenance personnel can initiate corresponding maintenance operations. Specific operations include: Perform scheduled maintenance operations on the equipment as required by the instructions, such as testing, calibration, parts replacement, software upgrades, etc.; During maintenance, real-time equipment status information is collected. This information includes, but is not limited to, power consumption, key sensor readings (temperature, pressure, flow), system error codes and alarms, maintenance operation timelines, and process parameters. This data is simultaneously recorded on the equipment management platform, ensuring transparency and traceability of the maintenance process.

[0060] During the maintenance process, the device's response to maintenance operations is continuously monitored. The following response behavior indicators can be collected: Performance recovery curve: By comparing the core performance parameters of the equipment before and after maintenance (such as output stability and work efficiency), the performance of the equipment is depicted as the maintenance progresses. Control feedback indicators: Collect feedback signals from the equipment control system to evaluate the response rate and stability of the control link to maintenance actions; Operational Deviation: This records deviations between equipment behavior and expected operating parameters during maintenance, including adjustment errors, response delays, etc. This response behavior data can be collected directly through sensors or obtained through input and feedback from maintenance personnel.

[0061] The collected maintenance response behavior data can be compared and analyzed with the equipment operating parameters before maintenance. The specific steps are as follows: Select key operating parameters before maintenance as benchmark values, such as average load, startup frequency, and failure rate; Calculate the degree of deviation between maintenance response data and baseline values ​​using statistical analysis methods (such as mean difference analysis, variance calculation, etc.); Quantify the deviation value indicator to reflect the equipment maintenance effect and the existence of abnormal conditions. If the deviation value exceeds the preset threshold, it may indicate insufficient maintenance or potential failure risks.

[0062] Through the above comparative analysis, the system can dynamically evaluate the effectiveness of maintenance and assist in subsequent fault diagnosis and maintenance strategy optimization.

[0063] In summary, this invention, by synchronously recording equipment status and response behavior during maintenance and comparing pre- and post-maintenance parameters, enables real-time and objective evaluation of maintenance effectiveness, effectively identifying potential anomalies and improving maintenance accuracy and equipment reliability. Furthermore, it provides data support for intelligent equipment maintenance, promoting scientific and automated maintenance decision-making.

[0064] In some embodiments, step 205 may further include: Determining the severity of the fault of the faulty device based on the deviation value; When the deviation value exceeds the preset fault threshold, a yellow, orange, red or emergency warning signal is triggered according to the threshold range; The fault level, occurrence frequency, risk category and possible impact scope associated with the warning signal form a structured warning event; The structured warning events are pushed to the corresponding equipment responsible person, technical supervisor and ICU management system.

[0065] Specifically, the deviation values ​​of equipment operating parameters obtained during the maintenance process can be judged using a preset fault threshold model in combination with the equipment type and historical operating data. The fault threshold model sets multiple intervals corresponding to different fault severity levels, such as: Slight deviation range: the deviation value is within the normal range and no warning is required; Yellow warning zone: The deviation value exceeds the primary threshold, indicating potential risks; Orange warning zone: The deviation value significantly exceeds the threshold and requires close monitoring and timely processing; Red warning range: The deviation value is extremely high, and the equipment may be at risk of serious failure; Emergency warning range: The deviation value far exceeds the threshold, and the safety of equipment operation is directly threatened.

[0066] When the deviation value enters each warning interval, the system automatically triggers the corresponding level of warning signal: the yellow warning signal is used for early risk reminder; the orange warning signal prompts the need to accelerate maintenance response; the red warning signal requires emergency processing and starts the fault isolation process; the emergency warning signal immediately notifies all relevant personnel to prevent safety accidents.

[0067] The system can associate and organize warning signals with the following information to form a structured warning event data package: equipment failure level (yellow, orange, red, emergency); historical frequency statistics of the failure level; risk category of equipment failure, such as safety risk, functional risk, impact on use, etc.; the scope of possible impact of the failure, including clinical application impact, patient safety impact and equipment network impact, etc.

[0068] Structured warning events can be automatically pushed to relevant responsible parties, including but not limited to: equipment owners, ensuring immediate on-site response; technical supervisors, arranging maintenance and technical support; and the ICU management system, enabling centralized management and tracking of warning information. Warning push supports multiple communication channels, including mobile app notifications, SMS, email, and system pop-up prompts, ensuring timely and accurate information dissemination.

[0069] Through the above-mentioned implementation, the present invention achieves scientific and quantitative judgment of equipment maintenance anomalies and multi-level intelligent early warning, significantly improving the timeliness and pertinence of fault response, ensuring the safe operation of ICU medical equipment and the continuity of clinical application. Furthermore, the digital management of structured early warning events facilitates subsequent analysis and improvement, enhancing the intelligence level of the equipment management system.

[0070] Step 206: Generate a maintenance resource deployment plan for the faulty equipment based on the fault warning signal and preset supplier historical service data.

[0071] In some embodiments, step 206 may include: Calling the manufacturer's service history data corresponding to the device; the manufacturer's service history data includes average response time, repair success rate, parts replacement record and service attitude score; Obtain currently available maintenance resources; these include in-hospital maintenance engineers, manufacturer technical support, and third-party maintenance organizations; Prioritizing the manufacturer's service history data and the maintenance resources based on a service capability scoring model to obtain a ranking result; According to the ranking results and the current maintenance urgency of the faulty equipment, a maintenance resource allocation plan for the faulty equipment is generated, and tasks are automatically assigned and notifications are issued.

[0072] Specifically, the historical service records of the device manufacturer can be retrieved from the maintenance service database. The data includes but is not limited to: Average response time: the average time it takes for a manufacturer to respond to a maintenance request; Repair success rate: the proportion of problems that were successfully solved in the manufacturer's historical repair cases; Parts replacement records: the number and types of key parts replaced by the manufacturer during the maintenance process; Service attitude rating: A comprehensive evaluation of the manufacturer's service attitude based on user feedback and a rating system.

[0073] The system can query the currently available maintenance resource library, and the resource categories include: In-hospital maintenance engineer: an in-house technical staff member of the hospital who is qualified in equipment maintenance; Manufacturer technical support: professional technicians dispatched by the manufacturer or remote support services; Third-party maintenance organization: a contracted external maintenance service team or cooperative organization.

[0074] Based on a service capability scoring model, a comprehensive score is generated for retrieved manufacturer historical service data and current maintenance resources. Factors considered include: manufacturer and maintenance personnel response speed and maintenance efficiency; repair success rate and quality assurance; maintenance cost and resource availability; manufacturer service reputation and customer satisfaction. Based on the comprehensive score, maintenance resources are prioritized to form a preferred list of maintenance resources.

[0075] Based on the current maintenance urgency of the equipment (such as red or emergency warning level), the system can generate a maintenance resource allocation plan for the faulty equipment based on the priority sorting results; the allocation plan clearly defines key information such as the responsible party for maintenance, estimated maintenance time and required accessories; the system automatically issues maintenance task notifications to the assigned maintenance personnel or team, and simultaneously updates the maintenance scheduling status; it supports multi-channel notifications, such as mobile phone text messages, emails and system messages, to ensure timely response to maintenance tasks.

[0076] Through the above-mentioned implementation, the present invention achieves scientific assessment and intelligent allocation of maintenance resources, improving the efficiency and quality of maintenance responses, minimizing the impact of equipment failures on ICU clinical work, and ensuring efficient and orderly equipment maintenance. Furthermore, the dynamic integration of historical data and real-time resource status makes maintenance management more intelligent and precise.

[0077] In some embodiments, the method of the present application may further include: Periodically collecting core performance parameters of the device and calculating the performance degradation trend of the device based on historical benchmark data; Based on the performance degradation trend, maintenance frequency, and maintenance cost, the remaining service life and economic applicability of the equipment are evaluated to obtain corresponding evaluation results; Based on the evaluation results, an equipment update recommendation report is generated, including the reasons for the update, alternative equipment recommendations, and budget assessment.

[0078] Specifically, the system can automatically collect key performance indicators of the equipment according to preset time intervals or usage cycles. The performance parameters include but are not limited to equipment output efficiency, response time, failure rate, accuracy indicators and energy consumption levels; the collected data is compared with the equipment's historical benchmark data, and the benchmark data comes from the equipment's initial performance test results and long-term operation statistics.

[0079] Based on historical benchmark data and currently collected performance parameters, time series analysis, regression models, or machine learning algorithms can be used to calculate the device performance degradation curve over time; identify the key nodes and rates of performance degradation, and form a performance degradation trend model.

[0080] The remaining service life of the equipment can be evaluated by comprehensively considering the performance degradation trend, equipment maintenance frequency and cumulative maintenance cost, applying life prediction models and cost-benefit analysis models; analyzing the economic benefits of continuing to use the equipment and replacing it, and judging whether the equipment has the economic rationale to continue to serve.

[0081] Based on the assessment results, a device update recommendation report can be automatically generated containing the following content: Update reasons: Key drivers such as performance degradation, failure risk, and increased maintenance costs; Alternative device recommendations: Recommend alternative device models and configurations that meet clinical needs based on market research and historical usage data; Budget assessment: New equipment purchase budget and cost savings forecast from replacement.

[0082] Through the above methods, the present invention can ensure that the ICU equipment management system can scientifically predict equipment performance changes, reasonably arrange equipment update plans, improve the use efficiency of medical equipment, and ensure clinical safety and economy.

[0083] See also Figure 2 , Figure 2 This is a structural diagram of a system for managing the use of ICU equipment provided by the present invention.

[0084] like Figure 2 As shown, an ICU equipment usage management system proposed in an embodiment of the present invention includes: The identification generation module 301 is used to generate a corresponding unique digital identification according to the storage information of the device; and use the unique digital identification as the basic identification information for the full life cycle management of the device; The risk classification module 302 is configured to perform dynamic risk classification on the device based on the unique digital identifier and the real-time operating parameters of the device to obtain a dynamic classification result of the device; The permission matrix module 303 is used to construct a three-dimensional permission matrix of equipment-personnel-position based on the dynamic classification results of the equipment and the qualification information of the operators, so as to limit the use rights of high-risk equipment; A maintenance scheduling module 304 is configured to generate a maintenance scheduling instruction for the equipment based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; A fault warning module 305 is configured to perform maintenance scheduling on the equipment in response to the equipment's adaptive maintenance scheduling instruction, obtain deviations between the generated abnormal maintenance data and the equipment's operating parameters, and trigger multi-level fault warning signals for the faulty equipment; The maintenance allocation module 306 is configured to generate a maintenance resource allocation plan for the faulty equipment based on the fault warning signal and preset supplier historical service data.

[0085] See also Figure 3 , Figure 3 Schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented: Generate a corresponding unique digital identifier based on the device's storage information; use the unique digital identifier as the basic identification information for the device's full life cycle management; Based on the unique digital identifier and the real-time operating parameters of the device, dynamically grading the device risk to obtain a dynamic grading result of the device; Based on the dynamic classification results of the equipment and the qualification information of the operators, a three-dimensional permission matrix of equipment-personnel-position is constructed to limit the use rights of high-risk equipment; Generate equipment adaptive maintenance scheduling instructions based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; Perform maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment, obtain the deviation value between the generated abnormal maintenance data and the equipment operating parameters, and trigger multi-level fault warning signals for the faulty equipment; Based on the fault warning signal and preset supplier historical service data, a maintenance resource deployment plan for the faulty equipment is generated.

[0086] See also Figure 4 , Figure 4 Schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 4As shown, this embodiment provides a computer-readable storage medium 500 on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented: Generate a corresponding unique digital identifier based on the device's storage information; use the unique digital identifier as the basic identification information for the device's full life cycle management; Based on the unique digital identifier and the real-time operating parameters of the device, dynamically grading the device risk to obtain a dynamic grading result of the device; Based on the dynamic classification results of the equipment and the qualification information of the operators, a three-dimensional permission matrix of equipment-personnel-position is constructed to limit the use rights of high-risk equipment; Generate equipment adaptive maintenance scheduling instructions based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; Perform maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment, obtain the deviation value between the generated abnormal maintenance data and the equipment operating parameters, and trigger multi-level fault warning signals for the faulty equipment; Based on the fault warning signal and preset supplier historical service data, a maintenance resource deployment plan for the faulty equipment is generated.

[0087] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0088] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1A system that specifies the functions of a box or boxes.

[0090] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system that is implemented in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0092] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0093] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for managing the use of ICU equipment, characterized in that: The method comprises: Generate a corresponding unique digital identifier based on the device's storage information; use the unique digital identifier as the basic identification information for the device's full life cycle management; Based on the unique digital identifier and the real-time operating parameters of the device, dynamically grading the device risk to obtain a dynamic grading result of the device; Based on the dynamic classification results of the equipment and the qualification information of the operators, a three-dimensional permission matrix of equipment-personnel-position is constructed to limit the use rights of high-risk equipment; Generate equipment adaptive maintenance scheduling instructions based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; Perform maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment, obtain the deviation value between the generated abnormal maintenance data and the equipment operating parameters, and trigger multi-level fault warning signals for the faulty equipment; Based on the fault warning signal and preset supplier historical service data, a maintenance resource deployment plan for the faulty equipment is generated.

2. The method for managing the use of ICU equipment according to claim 1, characterized in that: Generating a corresponding unique digital identifier based on the storage information of the device includes: Collect basic information about the device; the basic information includes device model, serial number, manufacturer information, purchase date, price, and warranty period; Building a structured digital device archive based on the basic information; By generating a corresponding QR code and RFID electronic tag, the digital device file is bound to the device entity to obtain the binding information of the device; The binding information is mapped and registered with the device management platform to generate the unique digital identifier used for subsequent life cycle management of the device.

3. The method for managing the use of ICU equipment according to claim 2, characterized in that: The dynamically grading the risk of the device based on the unique digital identifier and the real-time operating parameters of the device to obtain a dynamic grading result of the device includes: Real-time collection of operating parameters of the equipment; the operating parameters include operating time, startup frequency, load status and abnormal alarm data; Cleaning, standardizing, and feature extracting the operating parameters to obtain processed operating parameters; Based on the set risk assessment model, weighted scoring is performed on the processed operating parameters to obtain corresponding scoring results; According to the scoring results, each of the devices is divided into low risk, medium risk, high risk and extremely high risk levels, and the division results are used as the dynamic classification results.

4. The method for managing the use of ICU equipment according to claim 3, characterized in that: The three-dimensional authority matrix of equipment-personnel-position is constructed based on the dynamic classification results of the equipment and the qualification information of the operators, including: Obtain the scope of responsibilities and operating authority levels corresponding to each position; Read the operator's qualification information based on the scope of responsibilities and the level of operation authority; the qualification information includes training records, assessment results, certification level and violation records; Correlating and matching the dynamic classification result of the equipment with the position information and qualification information of the operator to obtain a matching result; The three-dimensional permission matrix is ​​constructed based on the matching results, and permission boundary conditions are set to limit unauthorized operations.

5. The method for managing the use of ICU equipment according to claim 4, characterized in that: The generating of equipment adaptive maintenance scheduling instructions based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix includes: Collecting statistics on the key information of the equipment; the key information includes usage frequency, cumulative operating time, load intensity and number of historical failures; Setting a basic maintenance cycle based on the dynamic classification results of the equipment, and determining the priority of the equipment for maintenance scheduling in combination with the critical information of the equipment; Obtain the current department workload and maintenance resource scheduling information; According to the priority, the workload of the current department and the scheduling information of the maintenance resources, a corresponding maintenance time window and the maintenance scheduling instruction are generated through a scheduling algorithm.

6. The method for managing the use of ICU equipment according to claim 5, characterized in that: The step of performing maintenance scheduling on the equipment in response to the adaptive maintenance scheduling instruction of the equipment and obtaining a deviation value between the generated abnormal maintenance data and the equipment operating parameter includes: Execute the maintenance scheduling instructions and simultaneously record the equipment operating status and key parameters during maintenance execution; Collecting the response behavior of the equipment during maintenance; the response behavior includes performance recovery curve, control feedback index and operation deviation; The response behavior is compared and analyzed with the operating parameters of the equipment before maintenance, and the deviation value is calculated.

7. The method for managing the use of ICU equipment according to claim 6, characterized in that: The triggering of multi-level fault warning signals for faulty equipment includes: Determining the severity of the fault of the faulty device based on the deviation value; When the deviation value exceeds the preset fault threshold, a yellow, orange, red or emergency warning signal is triggered according to the threshold range; The fault level, occurrence frequency, risk category and possible impact scope associated with the warning signal form a structured warning event; The structured warning events are pushed to the corresponding equipment responsible person, technical supervisor and ICU management system.

8. The method for managing the use of ICU equipment according to claim 7, characterized in that: Generating a maintenance resource allocation plan for the faulty equipment based on the fault warning signal and preset supplier historical service data includes: Calling the manufacturer's service history data corresponding to the device; the manufacturer's service history data includes average response time, repair success rate, parts replacement record and service attitude score; Obtain currently available maintenance resources; these include in-hospital maintenance engineers, manufacturer technical support, and third-party maintenance organizations; Prioritizing the manufacturer's service history data and the maintenance resources based on a service capability scoring model to obtain a ranking result; According to the ranking results and the current maintenance urgency of the faulty equipment, a maintenance resource allocation plan for the faulty equipment is generated, and tasks are automatically assigned and notifications are issued.

9. The method for managing the use of ICU equipment according to claim 8, characterized in that: The method further comprises: Periodically collecting core performance parameters of the device and calculating the performance degradation trend of the device based on historical benchmark data; Based on the performance degradation trend, maintenance frequency, and maintenance cost, the remaining service life and economic applicability of the equipment are evaluated to obtain corresponding evaluation results; Based on the evaluation results, an equipment update recommendation report is generated, including the reasons for the update, alternative equipment recommendations, and budget assessment.

10. A system for managing the use of ICU equipment, characterized in that: The system comprises: An identification generation module is used to generate a corresponding unique digital identification according to the storage information of the device; and use the unique digital identification as the basic identification information for the full life cycle management of the device; A risk grading module, configured to dynamically grade the risk of the device based on the unique digital identifier and the real-time operating parameters of the device, and obtain a dynamic risk grading result of the device; The permission matrix module is used to construct a three-dimensional permission matrix of equipment-personnel-position based on the dynamic classification results of the equipment and the qualification information of the operators, so as to limit the use rights of high-risk equipment; A maintenance scheduling module, configured to generate adaptive maintenance scheduling instructions for the equipment based on the unique digital identifier, the dynamic classification result, and the data of the three-dimensional authority matrix; A fault warning module is used to perform maintenance scheduling on the equipment in response to the equipment's adaptive maintenance scheduling instructions, obtain the deviation between the generated abnormal maintenance data and the equipment's operating parameters, and trigger a multi-level fault warning signal for the faulty equipment; The maintenance allocation module is used to generate a maintenance resource allocation plan for the faulty equipment based on the fault warning signal and preset supplier historical service data.

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