Soft instrument whole-process cost accounting method and related equipment

Abstract

The invention discloses a soft instrument full-process cost accounting method and related equipment, relates to the field of medical instrument management, and realizes single-piece level unique identification by binding a flexible washable RFID tag for each soft instrument. Cleaning and disinfection, sterilization and quality inspection station data are collected in the third-party decontamination factory and are pushed to the in-hospital tracing platform in a JSON format through the edge gateway. Recording the temperature and the unsealing state by using an electronic seal in the transportation process; and in a hospital disinfection and supply center and a clinical department, the packaging, sterilization, warehousing, receiving and recycling information of the soft instruments is automatically recorded by scanning the RFID. And on the basis, a single-piece cost matrix is constructed, the cleaning cost, the sterilization cost, the transportation cost, the depreciation cost and the loss cost are comprehensively calculated, and an accurate single-piece cost result is output. According to the invention, traceability and accounting of the whole life cycle of the soft instrument are realized, and fine and auditable cost management of hospitals is supported.

Description

Technical Field

[0001] This specification relates to the field of medical device management; more specifically, this application relates to a method for full-process cost accounting of soft medical devices and related equipment. Background Technology

[0002] Soft medical devices (SMDs) are a type of wearable, foldable infection control supplies commonly used in operating rooms. These include surgical gowns, cleanroom garments (scrub suits), surgical drapes, surgical sheets, and instrument sheets. SMDs typically possess properties such as lint resistance, antibacterial properties, water resistance, breathability, and antistatic properties. They can be reused after multiple cleaning, disinfection, and sterilization processes, making them a key component of hospital surgical infection control systems.

[0003] Currently, most hospitals outsource the cleaning and disinfection of surgical instruments to third-party cleaning and disinfection plants. The hospital's Central Sterile Supply Department (CSSD) needs to regenerate the outsourced labels for the hospital's traceability system based on the third-party labels before proceeding with sterilization and distribution within the hospital. Furthermore, the lack of end-to-end, single-item-level tracking within the hospital leads to several practical problems: for example, if a surgical instrument is found missing during later inventory checks, it's impossible to pinpoint the exact stage at which the loss occurred. The lifespan, number of cycles, and wear and tear of surgical instruments cannot be monitored in real time, affecting the accuracy of hospital cost accounting. The data silos between third-party cleaning and disinfection plants and hospitals also result in a lack of information loops between cleaning, sterilization, and in-hospital use, making it difficult to establish a complete quality control chain.

[0004] Therefore, there is an urgent need for a method and system that can manage the entire process of software devices in a closed loop, so as to achieve single-item-level traceability and accurate cost management of the software device lifecycle. Summary of the Invention

[0005] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0006] Firstly, this application proposes a method for full-process cost accounting of software devices, including: Each soft medical device is bound to a flexible, washable RFID tag and written with a unique identification code, thus constructing a unified coding system that maps to the hospital's equipment identification dictionary; Data is collected at the cleaning, sterilization and quality inspection stations of the third-party cleaning and disinfection plant. The data is then encapsulated into JSON data via an edge gateway and pushed to the hospital's traceability platform via a cloud data exchange API. During the transportation of the aforementioned soft medical devices, electronic seals are used to record the transportation temperature and opening status. After the soft medical devices arrive at the hospital, the electronic seal data is read through a mobile terminal to complete the entry of transportation information into the database. In hospital disinfection supply centers and clinical departments, the entire process of packaging, warehousing, sterilization, distribution, use and recycling of the aforementioned soft medical devices is recorded based on the scanning of the aforementioned RFID tags. Based on the above-mentioned full-process flow information and workstation data, a single-piece cost matrix is ​​constructed, and the accurate cost accounting results of the soft equipment are output according to the single-piece processing cost, depreciation cost and loss cost.

[0007] In one feasible implementation, the above involves binding a flexible, washable RFID tag to each soft medical device and writing a unique identification code into it, constructing a unified coding system that maps to the hospital's equipment identification dictionary, including... Heat-resistant flexible RFID tags are used as the unique code carriers; A unique identification code is generated based on the structure of manufacturer code, product category code, serial number, and check digit; The aforementioned unique identifier is mapped to the hospital's DI dictionary to form a unified coding system.

[0008] In one feasible implementation, the aforementioned workstation data collected at the cleaning, sterilization, and quality inspection stations of the third-party decontamination plant, and the workstation data encapsulated into JSON data via an edge gateway and pushed to the hospital's traceability platform via a cloud data exchange API, includes: Write the cleaning and disinfection parameters and conductivity parameters at the cleaning station; Write the sterilization temperature, pressure, and FO value at the sterilization station; Write the ATP test results and visual inspection conclusions at the quality inspection station; The data written at each workstation is encapsulated into JSON via the aforementioned edge gateway and pushed to the cloud data exchange API via HTTPS. The hospital's traceability platform periodically retrieves the data and verifies its integrity based on hash verification.

[0009] In one feasible implementation, the aforementioned process of recording the entire flow of information regarding the packaging, warehousing, sterilization, distribution, use, and recycling of the aforementioned soft medical devices in hospital disinfection supply centers and clinical departments based on the scanning of the aforementioned RFID tags includes: Before packing, scan the above RFID tags and generate corresponding packing tags, and bind the name, quantity and identification code of the soft device to the packing record; The above-mentioned RFID tags are scanned during sterilization, warehousing, departmental requisition, intraoperative supplementation and postoperative recovery to generate hospital circulation records; When the tunnel boring machine detects a missing item in the package or detects an abnormal temperature exceeding 60°C, it automatically triggers an alarm and rejection logic.

[0010] In one feasible implementation, the above-mentioned construction of a unit cost matrix based on the above-mentioned full-process flow information and workstation data, and the output of accurate cost accounting results for the software device based on unit processing cost, depreciation cost, and loss cost, including: The cleaning cost is calculated based on the above workstation data and the above flow information. Sterilization costs With transportation costs ; Based on the original value of the soft device With the rated number of cycles Calculate depreciation costs; Calculate the loss cost based on the above recycling and damage records. ; According to the formula Calculate the total cost C of a single soft instrument and output accurate cost accounting results.

[0011] In one feasible implementation, the process of pushing workstation data from a third-party decontamination plant further includes: In the aforementioned edge gateway, a corresponding hash digest value is generated for each workstation data, and the hash digest value and the aforementioned JSON data are simultaneously pushed to the aforementioned cloud data exchange API. The hash digest value of the above-mentioned JSON data retrieved in the above-mentioned in-hospital traceability platform is recalculated and compared with the hash digest value pushed by the above-mentioned edge gateway; When the comparison results are inconsistent, the workstation data is automatically marked as risky data and the data audit process is triggered.

[0012] In one feasible implementation, the above-mentioned construction of the unit cost matrix further includes: Based on historical cleaning times, sterilization times, transportation distances, and recycling cycles, the cost factors in the above-mentioned unit cost matrix are dynamically weighted and updated. The machine learning model is used to fit the time-varying trends of the cleaning cost, sterilization cost, transportation cost, and loss cost, and the weights of the depreciation cost and loss cost are automatically adjusted. Based on the dynamically weighted and updated unit cost matrix described above, the time-sensitive soft device cost prediction results are output.

[0013] Secondly, this invention also proposes a full-process cost accounting system for software devices, comprising: The building unit is used to bind a flexible, washable RFID tag to each soft medical device and write a unique identification code into it, thus building a unified coding system that maps to the hospital's equipment identification dictionary; The push unit is used to collect station data at the cleaning, sterilization and quality inspection stations of third-party cleaning and disinfection plants, encapsulate the above station data into JSON data through the edge gateway and push it to the hospital's traceability platform through the cloud data exchange API; The reading unit is used to record the transport temperature and opening status using an electronic seal during the transport of the aforementioned soft medical devices, and to read the electronic seal data via a mobile terminal after the aforementioned soft medical devices arrive at the hospital to complete the entry of transport information into the database. The recording unit is used to record the entire process flow information of the above-mentioned soft medical devices, including packaging, warehousing, sterilization, distribution, use and recycling, based on the scanning of the above-mentioned RFID tags in the hospital's disinfection supply center and clinical departments. The output unit is used to construct a single-piece cost matrix based on the above-mentioned full-process flow information and the above-mentioned workstation data, and output the accurate cost accounting results of the software device according to the single-piece processing cost, depreciation cost and loss cost.

[0014] Thirdly, the present invention also proposes an electronic device, comprising: a memory and a processor, characterized in that the processor is used to execute a computer program stored in the memory to implement the steps of the software device full-process cost accounting method as described in any of the first aspects.

[0015] Fourthly, the present invention also proposes a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the software device full-process cost accounting method as described in any of the first aspects.

[0016] In summary, compared to the problems of insufficient traceability granularity, data fragmentation between in-hospital and out-of-hospital systems, and inability to accurately calculate costs in the background technologies, the full-process cost accounting method for soft medical devices provided by this invention has significant beneficial effects. Firstly, by binding a flexible, washable RFID tag to each soft medical device and establishing a unified coding system, this invention achieves unique identification of each soft medical device at the individual level from the third-party disinfection plant to each stage within the hospital. This overcomes the limitations of traditional systems that can only perform package-level management, enabling precise tracking of the usage trajectory of soft medical devices down to each cleaning, sterilization, distribution, and recycling operation. Secondly, this invention uploads cleaning, sterilization, and quality inspection data from the third-party disinfection plant to the cloud data exchange interface in real time via an edge gateway, and uses a hash digest verification mechanism to ensure data integrity. This constructs a trusted data chain from the plant to the hospital, solving the problems of inability to input plant data into the hospital system in real time and difficulty in verifying data authenticity in the traditional model. It achieves real-time visibility and tamper-proof management of out-of-hospital processed data. This invention monitors temperature and opening status during transportation using electronic seals, and combines this with RFID scanning activity from the hospital's sterilization supply center and clinical departments to automatically record the flow status of surgical instruments at each stage within the hospital. This establishes a fully automated recording mechanism for the entire hospital flow process, significantly reducing the probability of loss during surgical requisition, intraoperative addition, and postoperative retrieval, thus improving management efficiency and safety. Furthermore, this invention constructs a single-item cost matrix by integrating workstation data, transportation data, and intra-hospital flow data, and calculates cleaning costs, sterilization costs, transportation costs, depreciation costs, and loss costs item by item, generating precise cost accounting results at the single-item, single-session, and single-operation levels. This solves the problem of hospitals struggling to accurately calculate the true usage cost of surgical instruments in traditional management methods, providing a solid data foundation for hospital budget management, performance evaluation, and third-party settlement. In summary, this invention achieves closed-loop management of surgical instruments throughout their entire lifecycle—making them "identifiable, traceable, auditable, and accountable"—not only practically helping hospitals reduce loss rates and improve usage efficiency but also providing strong technical support for transparent and refined surgical cost operations.

[0017] Other advantages, objectives and features of this application will be apparent in part from the description which follows, and in part from what those skilled in the art will understand through study and practice of this application. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart illustrating a method for full-process cost accounting of soft devices provided in this application embodiment; Figure 2 A structural schematic diagram of a software device end-to-end cost accounting system provided in this application embodiment; Figure 3 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0019] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. The technical solutions of the embodiments of this application will now be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0020] Please see Figure 1 This is a flowchart illustrating a method for calculating the full-process cost of a software device, as provided in an embodiment of this application. Specifically, it may include: S110. Bind a flexible, washable RFID tag to each soft medical device and write a unique identification code into it to build a unified coding system that maps to the hospital's equipment identification dictionary; S120. Collect station data at the cleaning, sterilization and quality inspection stations of the third-party cleaning and disinfection plant, encapsulate the above station data into JSON data through the edge gateway and push it to the hospital's traceability platform through the cloud data exchange API. S130. During the transportation of the above-mentioned soft medical devices, electronic seals are used to record the transportation temperature and opening status, and after the above-mentioned soft medical devices arrive at the hospital, the electronic seal data is read through a mobile terminal to complete the entry of transportation information into the database. S140. In hospital disinfection supply centers and clinical departments, the entire process flow information of the above-mentioned soft medical devices, including packaging, warehousing, sterilization, distribution, use and recycling, is recorded based on the scanning of the above-mentioned RFID tags. S150. Based on the above-mentioned full-process flow information and the above-mentioned workstation data, construct a single-piece cost matrix, and output the accurate cost accounting results of the soft equipment according to the single-piece processing cost, depreciation cost and loss cost.

[0021] For example, in step S110, the present invention binds a flexible, washable RFID (Radio Frequency Identification) tag to each soft medical device and writes a unique identification code into the tag, enabling the soft medical device to be accurately identified throughout the entire process of pre-hospital disinfection, in-hospital circulation, and surgical use. By mapping the unique identification code to the hospital's internal equipment identification dictionary, the problem of inconsistent coding systems for soft medical devices from multiple manufacturers and batches is solved, laying the foundation for subsequent cross-platform data fusion.

[0022] In step S120, this invention deploys station readers at the cleaning, sterilization, and quality inspection stations of a third-party decontamination plant to collect key parameters in real time, such as cleaning time, conductivity, sterilization temperature, pressure, FO (F0 Value, F0 equivalent sterilization time) value, and ATP test results. The station data is then encapsulated in JSON format and uploaded to the cloud data exchange API (Application Programming Interface) via an edge gateway. This upload mechanism ensures that plant-side data can be continuously and stably acquired by the hospital's traceability platform, enabling real-time access and tamper-proof management of external data.

[0023] In step S130, the present invention records the temperature curve and opening status of the soft medical device during transportation using a disposable electronic seal. Once the soft medical device arrives at the hospital, staff use a mobile terminal to read the electronic seal data and complete the warehousing operation for the transportation information, thereby achieving visualized monitoring and closed-loop quality management of the transportation process.

[0024] Subsequently, in step S140, the present invention utilizes the existing RFID scanning capabilities of the hospital's sterilization supply center and clinical departments to automatically record the flow data of soft instruments at each stage within the hospital, including packing, sterilization, warehousing, departmental requisition, intraoperative addition, and postoperative retrieval. When the tunneling machine detects missing packing or abnormal seal temperature, it can immediately trigger an alarm, thereby significantly reducing the loss rate and handover risks.

[0025] In step S150, the present invention summarizes the above-mentioned workstation data, transportation information, and intra-hospital circulation data to construct a single-item cost matrix, and calculates the total cost of a single soft instrument based on cleaning costs, sterilization costs, transportation costs, depreciation costs, and loss costs. By outputting accurate cost accounting results, hospitals can manage costs by single surgery, by department, or by single item, achieving cost transparency, auditability, and accountability.

[0026] In summary, compared to the problems of insufficient traceability granularity, data fragmentation between in-hospital and out-of-hospital systems, and inability to accurately calculate costs in the background technologies, the full-process cost accounting method for soft medical devices provided by this invention has significant beneficial effects. Firstly, by binding a flexible, washable RFID tag to each soft medical device and establishing a unified coding system, this invention achieves unique identification of each soft medical device at the individual level from the third-party disinfection plant to each stage within the hospital. This overcomes the limitations of traditional systems that can only perform package-level management, enabling precise tracking of the usage trajectory of soft medical devices down to each cleaning, sterilization, distribution, and recycling operation. Secondly, this invention uploads cleaning, sterilization, and quality inspection data from the third-party disinfection plant to the cloud data exchange interface in real time via an edge gateway, and uses a hash digest verification mechanism to ensure data integrity. This constructs a trusted data chain from the plant to the hospital, solving the problems of inability to input plant data into the hospital system in real time and difficulty in verifying data authenticity in the traditional model. It achieves real-time visibility and tamper-proof management of out-of-hospital processed data. This invention monitors temperature and opening status during transportation using electronic seals, and combines this with RFID scanning activity from the hospital's sterilization supply center and clinical departments to automatically record the flow status of surgical instruments at each stage within the hospital. This establishes a fully automated recording mechanism for the entire hospital flow process, significantly reducing the probability of loss during surgical requisition, intraoperative addition, and postoperative retrieval, thus improving management efficiency and safety. Furthermore, this invention constructs a single-item cost matrix by integrating workstation data, transportation data, and intra-hospital flow data, and calculates cleaning costs, sterilization costs, transportation costs, depreciation costs, and loss costs item by item, generating precise cost accounting results at the single-item, single-session, and single-operation levels. This solves the problem of hospitals struggling to accurately calculate the true usage cost of surgical instruments in traditional management methods, providing a solid data foundation for hospital budget management, performance evaluation, and third-party settlement. In summary, this invention achieves closed-loop management of surgical instruments throughout their entire lifecycle—making them "identifiable, traceable, auditable, and accountable"—not only practically helping hospitals reduce loss rates and improve usage efficiency but also providing strong technical support for transparent and refined surgical cost operations.

[0027] In one feasible implementation, the above involves binding a flexible, washable RFID tag to each soft medical device and writing a unique identification code into it, constructing a unified coding system that maps to the hospital's equipment identification dictionary, including... Heat-resistant flexible RFID tags are used as the unique code carriers; A unique identification code is generated based on the structure of manufacturer code, product category code, serial number, and check digit; The aforementioned unique identifier is mapped to the hospital's DI dictionary to form a unified coding system.

[0028] For example, to ensure that each soft medical device can be uniquely identified when moving between the off-site disinfection plant and various departments within the hospital, this embodiment first binds a flexible, washable RFID tag to the soft medical device and writes a unique identification code into the tag. The RFID tag is made of heat-resistant flexible material, capable of withstanding high-temperature and high-humidity environments such as cleaning and sterilization, ensuring that the code remains stable and readable even after hundreds of disinfection cycles. This embodiment sequentially writes the manufacturer code, category code, serial number, and check code according to a preset coding structure, thereby forming a unique identification code, enabling unified management of soft medical devices from different production batches and different suppliers at the coding level.

[0029] To address the inconsistency in coding systems between the hospital and third-party factories, this embodiment further maps the aforementioned unique identification code to the hospital's internal DI (Device Identifier) ​​dictionary. This ensures a one-to-one correspondence between RFID tag codes and hospital equipment identifiers, thereby forming a unified coding system that can be identified across institutions and systems. Through this approach, this embodiment achieves the identification, tracking, and management of software devices throughout their entire lifecycle, providing a fundamental data carrier and reliable identifier for subsequent workstation data collection, intra-hospital circulation records, and cost accounting.

[0030] In one feasible implementation, the aforementioned workstation data collected at the cleaning, sterilization, and quality inspection stations of the third-party decontamination plant, and the workstation data encapsulated into JSON data via an edge gateway and pushed to the hospital's traceability platform via a cloud data exchange API, includes: Write the cleaning and disinfection parameters and conductivity parameters at the cleaning station; Write the sterilization temperature, pressure, and FO value at the sterilization station; Write the ATP test results and visual inspection conclusions at the quality inspection station; The data written at each workstation is encapsulated into JSON via the aforementioned edge gateway and pushed to the cloud data exchange API via HTTPS. The hospital's traceability platform periodically retrieves the data and verifies its integrity based on hash verification.

[0031] For example, to achieve quality transparency and data traceability for soft medical devices at the third-party disinfection plant stage, this embodiment deploys RFID readers and data acquisition devices linked to the PLC at key workstations such as cleaning, sterilization, and quality inspection. After the soft medical device completes the cleaning process, the system automatically writes parameters such as cleaning and disinfection, and conductivity, into its RFID tag or associated data record, and aggregates this data into a standardized record for that workstation. During sterilization, the system simultaneously collects sterilization temperature, pressure, and the FO value reflecting sterilization effectiveness, ensuring a complete process parameter trajectory for each soft medical device. Subsequently, at the quality inspection station, the system collects the ATP test results and manual visual inspection conclusions to ensure that the sterilization quality meets the requirements of the hospital and regulatory authorities.

[0032] The collected multi-dimensional workstation data will be uniformly processed by the edge gateway. The edge gateway will encapsulate the data into a JSON file according to a preset format and push it to the cloud data exchange API via the HTTPS channel to achieve real-time cloud uploading and secure transmission of factory data. Simultaneously, the institute's traceability platform will retrieve workstation data from the cloud interface at set intervals and perform hash digest comparisons on each JSON data entry to verify data integrity. If the verification result is abnormal, the system can automatically mark the record as risky data and trigger subsequent audit mechanisms.

[0033] This embodiment ensures that the data of soft instruments during the cleaning, sterilization and quality inspection stages are authentic, traceable and tamper-proof, providing a reliable data foundation for the hospital's subsequent internal circulation management and cost accounting.

[0034] In one feasible implementation, the aforementioned process of recording the entire flow of information regarding the packaging, warehousing, sterilization, distribution, use, and recycling of the aforementioned soft medical devices in hospital disinfection supply centers and clinical departments based on the scanning of the aforementioned RFID tags includes: Before packing, scan the above RFID tags and generate corresponding packing tags, and bind the name, quantity and identification code of the soft device to the packing record; The above-mentioned RFID tags are scanned during sterilization, warehousing, departmental requisition, intraoperative supplementation and postoperative recovery to generate hospital circulation records; When the tunnel boring machine detects a missing item in the package or detects an abnormal temperature exceeding 60°C, it automatically triggers an alarm and rejection logic.

[0035] For example, to achieve transparent management of soft medical devices throughout the entire process from entry to use and recycling within the hospital, this embodiment utilizes the existing RFID scanning scenarios in the hospital's Central Sterile Supply Department (CSSD) and clinical departments, using each scan as a trigger point to automatically record the flow status of the soft medical devices. Specifically, before the soft medical device enters the packing process, staff first scan its RFID tag. The system automatically generates a packing tag based on the unique identification code carried in the tag and binds the name, quantity, and identification code of the soft medical device to the corresponding packing record, ensuring that each packing has verifiable individual-level details.

[0036] Subsequently, at key stages such as sterilization, warehousing, departmental requisition, intraoperative addition, and postoperative waste disposal, simply scanning the RFID tag on the soft instrument will synchronously generate a corresponding circulation record, allowing the flow, status, and responsible person information of each soft instrument within the hospital to be updated in real time. For example, when a soft instrument is added to the operating room, scanning it can accurately record its usage time, the department using it, and the corresponding surgical schedule, realizing a chain of responsibility management where whoever scans the code is responsible.

[0037] Furthermore, this embodiment also uses intelligent identification devices such as tunnel boring machines to automatically check the integrity of the packing. When the tunnel boring machine detects that a single item is missing from the packing, the system will immediately light up a red light to indicate this and generate a missing item record in the background. When the system detects abnormalities such as a temperature exceeding 60°C recorded in the RFID tag or electronic seal, it will automatically trigger the rejection logic to prevent non-compliant items from entering the hospital's circulation process, ensuring infection control and medical quality and safety within the hospital.

[0038] Through the above methods, this embodiment achieves full-process visualization, supervision, and accountability for soft medical devices within the hospital, which significantly reduces the risk of loss and handover errors of soft medical devices, and provides reliable data support for subsequent cost accounting, usage efficiency analysis, and quality auditing.

[0039] In one feasible implementation, the above-mentioned construction of a unit cost matrix based on the above-mentioned full-process flow information and workstation data, and the output of accurate cost accounting results for the software device based on unit processing cost, depreciation cost, and loss cost, including: The cleaning cost is calculated based on the above workstation data and the above flow information. Sterilization costs With transportation costs ; Based on the original value of the soft device With the rated number of cycles Calculate depreciation costs; Calculate the loss cost based on the above recycling and damage records. ; According to the formula Calculate the total cost C of a single soft instrument and output accurate cost accounting results.

[0040] For example, in this embodiment, to achieve accurate cost accounting for soft medical devices throughout their entire lifecycle, this embodiment constructs a single-item cost matrix based on the aforementioned full-process flow information and workstation data, and calculates cleaning costs, sterilization costs, transportation costs, depreciation costs, and loss costs accordingly, thereby obtaining the total cost of the soft medical device. In specific implementation, firstly, based on the workstation data uploaded from the third-party cleaning and disinfection plant and the flow information such as packing, sterilization, use, and recycling within the hospital, the cleaning cost incurred by each soft medical device in the corresponding cycle is statistically analyzed. sterilization cost With transportation costs Subsequently, based on the original purchase value of the soft equipment... With respect to the rated number of reusable cycles of this soft device The original value is evenly distributed over the number of cycles to obtain the depreciation cost corresponding to each use. Furthermore, by statistically analyzing damage and loss records of soft devices during the recycling process, the loss costs associated with risk events can be calculated. It is used to reflect the unconventional wear and tear that occurs during the service life of soft devices.

[0041] After obtaining each cost factor, this embodiment follows the formula. The costs of each item are summed up to obtain the total cost of a single soft device. By outputting the total cost in a structured format, the system can provide hospitals with precise cost accounting results at the item, package, and even surgery level, enabling managers to clearly understand the true economic consumption of each soft instrument throughout the entire process. This embodiment not only achieves transparency and refinement in cost accounting but also provides accurate data for hospital cost control, surgical cost analysis, and performance evaluation of third-party disinfection services.

[0042] In one feasible implementation, the process of pushing workstation data from a third-party decontamination plant further includes: In the aforementioned edge gateway, a corresponding hash digest value is generated for each workstation data, and the hash digest value and the aforementioned JSON data are simultaneously pushed to the aforementioned cloud data exchange API. The hash digest value of the above-mentioned JSON data retrieved in the above-mentioned hospital traceability platform is recalculated and compared with the hash digest value pushed by the above-mentioned edge gateway. When the comparison results are inconsistent, the workstation data is automatically marked as risky data and the data audit process is triggered.

[0043] For example, to ensure the immutability and auditability of workstation data pushed from the third-party disinfection plant to the hospital's traceability platform, this embodiment introduces a hash verification mechanism between the edge gateway and the hospital's traceability platform to build a trusted data chain. Specifically, before each workstation (including cleaning, sterilization, and quality inspection workstations) in the third-party disinfection plant encapsulates the collected workstation data into a JSON file, the edge gateway calculates a corresponding hash digest value for each workstation data piece, generating a unique verification fingerprint for the data content through a hash algorithm. Subsequently, the edge gateway pushes the workstation JSON data and the corresponding hash digest value to the cloud data exchange API, ensuring that all workstation data has a data integrity identifier when leaving the plant.

[0044] After the internal traceability platform retrieves the workstation JSON data from the cloud interface, the system recalculates the hash digest value of the retrieved data based on the same hash algorithm and compares the calculated result with the hash digest value pushed by the factory. If they match, it means that the workstation data has not been modified during transmission and can be safely included in the internal circulation record and cost accounting system. If the comparison results are inconsistent, it means that the data may have been tampered with, lost fields, or abnormally modified. The system will automatically mark the workstation data as risk data and trigger subsequent data audit processes, such as manual review, workstation retransmission, or notification of a third-party factory to investigate anomalies.

[0045] By using the aforementioned dual-end verification mechanism—generating hash fingerprints before data is uploaded to the blockchain and recalculating and comparing the data after it is admitted to the hospital—this embodiment ensures the reliable transmission of workstation data from the factory to the hospital, significantly improving the data reliability, auditability, and security of the software medical device full-process traceability and cost accounting system, and further providing the hospital with strong data quality assurance.

[0046] In one feasible implementation, the above-mentioned construction of the unit cost matrix further includes: Based on historical cleaning times, sterilization times, transportation distances, and recycling cycles, the cost factors in the above-mentioned unit cost matrix are dynamically weighted and updated. The machine learning model is used to fit the time-varying trends of the cleaning cost, sterilization cost, transportation cost, and loss cost, and the weights of the depreciation cost and loss cost are automatically adjusted. Based on the dynamically weighted and updated unit cost matrix described above, the time-sensitive soft device cost prediction results are output.

[0047] For example, in order to enable the cost accounting of soft equipment to not only reflect the current actual consumption, but also to adapt to the changing trends of different time periods and realize the dynamic and predictive nature of costs, this embodiment further introduces a dynamic weighted update mechanism and a machine learning prediction mechanism on the basis of constructing a single-item cost matrix.

[0048] First, this embodiment dynamically updates the weighted average of each cost factor in the single-item cost matrix based on historical data accumulated during the long-term operation of soft medical devices, including key indicators such as cleaning frequency, sterilization frequency, transportation distance, and return cycle. For example, when the cleaning frequency of a certain type of soft medical device exceeds the rated level in actual use, the system automatically increases the weight of the cleaning cost for that type of soft medical device; when transportation distances or inter-hospital transfers are frequent, the weight of transportation costs will be adjusted accordingly. If the return cycle is stable and the loss rate is extremely low, the weight of loss costs will automatically decrease. Through the above methods, this embodiment enables the proportion of each cost factor in the matrix to adaptively reflect the actual usage status of the soft medical devices.

[0049] This embodiment utilizes a machine learning model to fit the time dynamics of multiple cost factors, such as cleaning costs, sterilization costs, transportation costs, and loss costs. For example, it analyzes the changing trends of cost factors through regression models, time series models, or lightweight predictive networks, thereby automatically adjusting the weights of depreciation costs and loss costs at different periods. In this way, the model can respond in real time when the aging rate of soft equipment accelerates, loss increases, or turnover efficiency changes, maintaining the time sensitivity and accuracy of the calculation results.

[0050] After completing the dynamic weighted update, this embodiment generates time-sensitive soft medical device cost forecasts based on the updated unit cost matrix, enabling hospitals to obtain relatively accurate cost estimates for different time windows in the future. For example, hospitals can know in advance that the cost of a certain type of soft medical device will show an upward trend in the next quarter, thereby enabling them to make procurement plans, adjust leasing, or optimize inventory management.

[0051] In summary, this embodiment transforms cost accounting from static results to dynamic predictions by introducing dynamic weighting driven by historical behavior and machine learning trend analysis. This enhances the system's adaptability to changes in clinical usage and provides hospitals with more forward-looking decision-making support for cost control, budget preparation, and refined operational management.

[0052] Secondly, this invention also proposes a full-process cost accounting system for software devices, such as... Figure 2 As shown, it includes: Unit 21 is used to bind a flexible washable RFID tag to each soft medical device and write a unique identification code, thereby building a unified coding system that maps to the hospital's equipment identification dictionary. Push unit 22 is used to collect station data at the cleaning, sterilization and quality inspection stations of third-party cleaning and disinfection plants, encapsulate the above station data into JSON data through the edge gateway and push it to the hospital traceability platform through the cloud data exchange API; The reading unit 23 is used to record the transport temperature and opening status using an electronic seal during the transport of the aforementioned soft medical device, and to read the electronic seal data through a mobile terminal after the aforementioned soft medical device arrives at the hospital to complete the entry of transport information into the database. Recording unit 24 is used to record the entire process flow information of the soft medical devices, including packaging, warehousing, sterilization, distribution, use and recycling, based on scanning the RFID tags in the hospital's disinfection supply center and clinical departments. Output unit 25 is used to construct a single-piece cost matrix based on the above-mentioned full-process flow information and the above-mentioned workstation data, and output the accurate cost accounting results of the software device according to the single-piece processing cost, depreciation cost and loss cost.

[0053] In one feasible implementation, a software device end-to-end cost accounting system can also perform any step of the method proposed in the first aspect.

[0054] Thirdly, the present invention also proposes an electronic device 300, such as... Figure 3 As shown, it includes a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, it implements the steps of the software device full-process cost accounting method as described in any of the first aspects.

[0055] Fourthly, the present invention also proposes a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the software device full-process cost accounting method as described in any one of the first aspects.

[0056] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0057] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations 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, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0059] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0060] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0061] This application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device performs the voice-based identity recognition process in the corresponding embodiment. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0062] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0063] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0064] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0065] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0066] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0067] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A soft instrument full-process cost accounting method, characterized in that, The application comprises the following steps: Binding a flexible washable RFID tag to each soft instrument and writing a unique identification code, and constructing a unified coding system mapped with the hospital equipment identification dictionary; Collecting data at the cleaning, disinfecting, sterilizing and quality inspection stations of the third-party cleaning factory, encapsulating the data into JSON data through an edge gateway, and pushing the data to the hospital traceability platform through a cloud data exchange API; Recording the transportation temperature and opening state using an electronic seal during the transportation of the soft instrument, and reading the electronic seal data through a mobile terminal when the soft instrument arrives at the hospital to complete the transportation information storage; Recording the full-process flow information of the soft instrument including packaging, storage, sterilization, distribution, use and recovery in the hospital disinfection supply center and clinical departments based on the scanning of the RFID tag; Constructing a single-piece cost matrix based on the full-process flow information and the station data, and outputting the accurate cost accounting result of the soft instrument according to the single-piece processing cost, depreciation cost and loss cost.

2. The soft instrument full-lot cost accounting method of claim 1, wherein, The application comprises the following steps: Using a heat-resistant flexible RFID tag as the unique code carrier; Generating a unique identification code according to the structure of the manufacturer code, category code, serial number and check code; Mapping the unique identification code to the hospital DI dictionary to form a unified coding system.

3. The soft instrument full-lot cost accounting method of claim 1, wherein, The application comprises the following steps: Writing the cleaning time, disinfection parameters and conductivity parameters at the cleaning station; Writing the sterilization temperature, pressure and FO value at the sterilization station; Writing the ATP detection result and visual inspection conclusion at the quality inspection station; Encapsulating the data written at each station into JSON through the edge gateway and pushing the data to the cloud data exchange API through HTTPS, and the hospital traceability platform pulls the data regularly and verifies the data integrity based on the hash check.

4. The soft instrument full-lot cost accounting method of claim 1, wherein, The application comprises the following steps: Scanning the RFID tag before packaging and generating a corresponding packaging label, and binding the soft instrument name, quantity and identification code to the packaging record; Scanning the RFID tag to generate hospital flow records at the sterilization, storage, department use, intraoperative addition and postoperative recovery stages; When the tunnel machine detects missing single-piece packaging or detects abnormal temperature exceeding 60℃, the alarm and rejection logic are automatically triggered.

5. The soft instrument full-lot cost accounting method of claim 1, wherein, The application comprises the following steps: According to the work station data and the flow transfer information, a cleaning cost is calculated , a sterilization cost and a transportation cost ​ According to the soft instrument original value With the rated number of cycles Calculate the depreciation cost; calculating a wear cost from the recovery record and the damage record ; The total cost C of the single soft instrument is calculated according to the formula and the accurate cost accounting result is output.

6. The soft instrument full-lot cost accounting method of claim 1, wherein, During the process of pushing the station data by the third-party cleaning factory, the application further comprises the following steps: In the edge gateway, a corresponding hash digest value is generated for each piece of station data, and the hash digest value is pushed to the cloud data exchange API at the same time as the JSON data; In the in-hospital traceability platform, the hash digest value of the pulled JSON data is recalculated and compared with the hash digest value pushed by the edge gateway; When the comparison result is inconsistent, the piece of station data is automatically marked as risk data and the data audit process is triggered.

7. The soft instrument full-lot cost accounting method of claim 1, wherein, The construction of the single-piece cost matrix also includes: Based on the historical cleaning times, sterilization times, transportation distances, and recycling periods, each cost factor in the single-piece cost matrix is dynamically weighted and updated; Through a machine learning model, the time variation trend of the cleaning cost, the sterilization cost, the transportation cost, and the loss cost is fitted, and the weights of the depreciation cost and the loss cost are automatically adjusted; According to the dynamically weighted and updated single-piece cost matrix, a time-sensitive soft instrument cost prediction result is output.

8. A soft instrument full-cycle cost accounting system, characterized by, It includes: A construction unit for binding a flexible washable RFID tag to each piece of soft instrument and writing a unique identification code, and constructing a unified coding system mapped with an in-hospital equipment identification dictionary; A pushing unit for collecting station data at the cleaning, sterilization, and quality inspection stations of a third-party decontamination factory, encapsulating the station data as JSON data through an edge gateway, and pushing the JSON data to an in-hospital traceability platform through a cloud data exchange API; A reading unit for recording transportation temperature and opening state using an electronic seal during the transportation of the soft instrument, and reading the electronic seal data through a mobile terminal when the soft instrument arrives at the hospital to complete the storage of transportation information; A recording unit for recording the full-process flow information of the soft instrument, including packaging, storage, sterilization, distribution, use, and recycling, based on the scanning of the RFID tag in the hospital disinfection supply center and clinical departments; An output unit for constructing a single-piece cost matrix based on the full-process flow information and the station data, and outputting the precise cost accounting result of the soft instrument according to the single-piece processing cost, depreciation cost, and loss cost.

9. An electronic device comprising: A memory and a processor, characterized in that the processor is used to implement the steps of the soft instrument full-process cost accounting method according to any one of claims 1-7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the soft instrument full-process cost accounting method according to any one of claims 1-7.

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