Clinical department storehouse consumable intelligent management system

Abstract

The invention discloses an intelligent management system for clinical department storehouse consumables, relates to the technical field of hospital consumable management, and aims to solve the problems that a traditional consumable management mode often depends on manual recording and manual management, data omission and inaccuracy easily occur, the use condition of the consumables is difficult to track, the replenishment opportunity is likely to be inaccurate, and the use cost is low. According to the system, full-life-cycle tracking of consumables is realized through an RFID tag and a block chain recording module, the authenticity and integrity of data are ensured, the management risk caused by information asymmetry is reduced, the consumable inventory condition and consumable demand prediction are monitored in real time, and the medical service efficiency is improved. According to the technical scheme, the relation between the current inventory level and the safety inventory threshold value is automatically evaluated, early warning is given out, medical service efficiency reduction caused by insufficient inventory is avoided, the replenishment order is automatically generated and transmitted to related departments, the requirement for manual intervention is reduced, and the efficiency and accuracy of the whole replenishment process are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hospital consumables management, and in particular to an intelligent management system for clinical department warehouse consumables. Background Art

[0002] In the modern medical field, with the continuous advancement of technology, hospital management is gradually developing towards intelligence and digitalization, especially in supply chain management. As an important part of hospital material management, clinical department warehouses bear a large number of consumables management tasks. In the field of hospital consumables management technology, accurate management and real-time monitoring of consumables are crucial, involving the effective use and supply of various medical devices, drugs and consumables.

[0003] However, many hospitals are still facing many challenges in the management of consumables, which are mainly reflected in the poor information tracking and imperfect replenishment mechanism. The traditional consumables management method often relies on manual records and manual management, which is prone to data omissions and inaccuracies. This not only makes it difficult to track the use of consumables, but also may cause inaccurate replenishment timing, thus affecting the continuity and efficiency of medical services. These problems arise from the lack of attention to the real-time and accuracy of consumables data, which in turn leads to confusion in inventory management and waste of resources. For example, the lag in consumables usage records may cause inventory levels to fail to be updated in a timely manner, resulting in hospitals facing consumables shortages at critical moments, affecting the normal progress of medical work. At the same time, due to the inconsistency of data, hospitals may miss pricing during financial settlement, causing economic losses. These abnormal effects not only affect the hospital's operating efficiency, but also reduce the patient's service experience. Therefore, the introduction of blockchain tracking systems and intelligent replenishment mechanisms is particularly important, which can effectively solve these problems. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent management system for clinical department warehouse consumables, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent management system for clinical department warehouse consumables, including a data acquisition module, a blockchain recording module, a consumables data analysis module, a dynamic demand prediction module, a consumables inventory warning module and an intelligent replenishment module;

[0006] The data acquisition module is used to equip consumables with RFID tags, and use an RFID tag reader to collect consumable data, transmit the collected consumable data to a central data processing platform in real time through a wireless network, and pre-process the collected consumable data to construct a consumable data set;

[0007] The blockchain recording module is used to deploy blockchain nodes on the IT infrastructure of the hospital clinical department, integrate the blockchain platform with the hospital clinical department database and the RFID system, write smart contracts, encrypt the consumables data, generate a unique hash value, and store the encrypted consumables data on the blockchain platform;

[0008] The consumables data analysis module is used to obtain the consumables demand fluctuation coefficient CV based on the consumables data stored in the blockchain platform, and preset the consumables inventory service level coefficient Z, and obtain the consumables safety inventory AQ based on the consumables inventory service level coefficient Z and the consumables demand fluctuation coefficient CV;

[0009] The demand forecasting module is used to build a consumables demand forecasting model to obtain the consumables demand XQ at a future time point t. t ;

[0010] The inventory warning module is used to monitor the clinical department warehouse consumables data in real time, obtain the real-time consumables inventory KC, and compare and analyze the real-time consumables inventory KC with the consumables safety inventory AQ to evaluate the consumables inventory level;

[0011] The intelligent replenishment module is used to obtain the consumable replenishment quantity BH based on the real-time consumable inventory KC and the consumable demand XQ in the future predicted by the consumable demand prediction model, and transmit the consumable replenishment quantity BH to the blockchain platform, trigger the smart contract, generate a replenishment order, and send the replenishment order to the hospital consumable management department and suppliers to replenish the consumable inventory.

[0012] Preferably, the data acquisition module includes a consumables data acquisition unit and a data preprocessing unit;

[0013] The consumables data collection unit is used to install RFID readers at the consumables entry and exit ports and consumables use areas. When consumables are put into storage, RFID technology is used to generate unique RFID tags for consumables to record consumables information. A mobile RFID scanning device is used to scan the RFID tags on the consumables in the consumables use area in real time to obtain consumables use data. The wireless signal transmission device on the RFID reader is used to transmit the collected consumables use data to the hospital central data processing platform through a wireless network. The consumables information includes consumables ID, name and consumables validity period;

[0014] The data preprocessing unit is used to preprocess the consumables usage data transmitted to the hospital central data processing platform, including data cleaning, data conversion and data integration;

[0015] The data cleaning is used to check duplicate items in the consumables usage data, remove duplicate data with the same time and the same consumables ID, and standardize the consumables usage data, check whether there are missing values ​​in the consumables usage data, and fill in the missing values, wherein the missing values ​​include the consumables ID and the consumables quantity;

[0016] The data conversion is used to convert the timestamp in string format into a date and time object, and convert the consumables outbound and inbound data into a unified coding format, where "outbound" is 1 and "inbound" is 0;

[0017] The data integration is used to integrate the consumables usage data that has undergone data cleaning and data conversion into a consumables data set, and sort the data according to timestamps.

[0018] Preferably, the blockchain recording module includes a blockchain platform integration unit, a smart contract writing unit and a data encryption unit;

[0019] The blockchain platform integration unit is used to use Hyperledger Fabric as a blockchain platform, deploy Hyperledger Fabric nodes on the hospital IT infrastructure, build a blockchain network, connect the blockchain network with the hospital's clinical department consumables database and RFID system through an open API interface, use HTTP protocol requests to interact with the blockchain network, and upload the consumables data collected in real time by the Hyperledger Fabric node to the blockchain platform through the open API interface;

[0020] The hospital IT infrastructure includes hospital servers, network equipment, databases and medical terminal equipment;

[0021] The smart contract writing unit is used to write smart contracts using Java language, and install the written smart contracts to each Hyperledger Fabric node of the blockchain network. When the consumables data is uploaded to the blockchain platform through the blockchain network, the smart contract of the corresponding consumables is automatically generated according to the smart contract of the Hyperledger Fabric node. The smart contract includes the consumable ID, consumable usage time, usage quantity, user and using department.

[0022] Preferably, the data encryption unit is used to generate an asymmetric key according to an asymmetric encryption algorithm RSA, including a public key and a private key, and use the public key to asymmetrically encrypt the consumable data in the consumable data set to obtain the encrypted consumable data;

[0023] Hash processing is performed based on the encrypted consumables data to generate a unique hash value, and the encrypted consumables data and the hash value corresponding to the consumables data are transmitted to the blockchain platform through the HTTPS communication protocol through the smart contract interface of the Hyperledger Fabric node.

[0024] Preferably, the consumables data analysis module is used to obtain the average consumables demand D according to the consumables data in the preprocessed consumables data set. avg and the standard deviation of consumables demand σ, and based on the average consumables demand D avg The consumables demand fluctuation coefficient CV is obtained by using the consumables demand standard deviation σ, the consumables inventory service coefficient Z is preset, and the consumables safety stock threshold AQ is obtained based on the consumables inventory service coefficient Z and the consumables demand fluctuation coefficient CV;

[0025] The average demand for consumables D avg , the standard deviation of consumables demand σ and the consumables demand fluctuation coefficient CV are obtained as follows:

[0026]

[0027]

[0028]

[0029] Where D i is the consumables demand on the i-th day in the historical consumables data, n is the total number of days of consumables data collected, σ is the standard deviation of consumables demand, and D avg is the average demand for consumables;

[0030] The consumables safety inventory AQ is obtained in the following way:

[0031]

[0032] Where Z is the service coefficient of consumable inventory, D max It is the maximum demand for consumables.

[0033] Preferably, the demand forecasting module includes a model building unit and a demand forecasting unit;

[0034] The model building unit is used to build a consumable demand prediction model based on the weighted moving average method, set the input layer of the consumable demand prediction model to consumable data, and the output layer to the consumable demand quantity XQ at a future time point. Use historical consumable demand data as training data, input the consumable demand prediction model, obtain the consumable demand quantity XQ at a future time point, and use the root mean square error RMSE to adjust the consumable demand prediction model parameters. The historical consumable demand data is obtained from a hospital database.

[0035] Preferably, the demand prediction unit is used to input the real-time collected consumables data into the trained consumables demand prediction model according to the trained consumables demand prediction model to obtain the consumables demand XQ at the future time point t. t ;

[0036] The consumables demand XQ at the future time point t t The method of obtaining is:

[0037]

[0038] Where D i is the historical demand for consumables on the i-th day, ω i is the weight of the historical demand for consumables on the i-th day, n is the total number of days of consumables data collected, i = 1, 2, 3, ..., n.

[0039] Preferably, the inventory warning module is used to obtain the real-time consumable inventory KC based on the consumable data stored in the blockchain platform, compare and analyze the real-time consumable inventory KC with the consumable safety inventory AQ, and evaluate the consumable inventory level. The specific evaluation content is as follows:

[0040] If the real-time consumable inventory KC is greater than or equal to the consumable safety inventory AQ, that is, KC ≥ AQ, the consumable inventory is judged to be at a safe level, the consumable data is recorded, and a consumable in and out data report is generated and sent to the clinical department warehouse manager;

[0041] If the real-time consumables inventory KC is less than the consumables safety inventory AQ, that is, KC<AQ, the consumables inventory is judged to be at a dangerous level, the alarm mechanism is triggered, the consumables data is recorded and sent to the blockchain platform.

[0042] Preferably, the intelligent replenishment module includes a replenishment quantity analysis unit and a replenishment unit;

[0043] The replenishment quantity analysis unit is used to obtain the consumable replenishment quantity BH based on the real-time consumable inventory quantity KC and the consumable demand quantity XQ at a future time point obtained by the consumable demand prediction model when the real-time consumable inventory quantity KC is less than the consumable safety inventory quantity AQ, that is, KC<AQ, triggering the alarm mechanism, and transmit the obtained consumable replenishment quantity BH to the blockchain platform to trigger the smart contract;

[0044] The consumables replenishment quantity BH is obtained in the following manner:

[0045] BH=XQ-KC.

[0046] The replenishment unit is used to trigger the smart contract based on the consumables replenishment quantity BH received by the blockchain platform, formulate a consumables replenishment plan, automatically generate a replenishment order, and send the replenishment order to the hospital consumables management department and the consumables supplier until the hospital consumables management department and the consumables supplier respond.

[0047] The present invention provides an intelligent management system for clinical department warehouse consumables, which has the following beneficial effects:

[0048] (1) This system implements full tracking of the consumables usage process by equipping each consumable with an RFID tag and combining it with a blockchain recording module. All consumables usage records, replenishment requests, and expiration information are recorded in real time in the blockchain, ensuring the data is tamper-proof and transparent. This traceability effectively reduces the problem of missed pricing due to missing information, allowing hospitals to accurately grasp the usage of each consumable and ensure the accuracy of financial data.

[0049] (2) The inventory warning module in this system can obtain the inventory of consumables in a timely manner, compare it with the consumable safety inventory AQ, and automatically generate an inventory data report. When the real-time consumable inventory KC is less than the consumable safety inventory AQ, the system will trigger an alarm mechanism and notify relevant personnel to replenish the stock in a timely manner. This mechanism not only effectively prevents the problem of insufficient inventory, but also ensures the accuracy of inventory data, avoiding economic losses caused by recording errors or omissions.

[0050] (3) Through the dynamic demand forecasting module, the system can build a consumables demand forecasting model based on the historical consumables demand data and real-time collected data. Combined with machine learning technology, the system can predict the consumables demand at a future time point and optimize replenishment decisions accordingly. The intelligent replenishment module compares the real-time inventory with the predicted demand, automatically generates replenishment orders and triggers smart contracts, thus realizing an automated and intelligent replenishment process. This method reduces the errors that may be caused by manual operations, ensures the reasonable inventory and timely replenishment of consumables, and effectively solves the problem of mismatched consumables pricing. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The present invention is a block diagram of an intelligent management system for clinical department warehouse consumables. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example 1

[0054] See also Figure 1 , the present invention provides an intelligent management system for clinical department warehouse consumables, including a data acquisition module, a blockchain recording module, a consumables data analysis module, a demand forecasting module, an inventory warning module and an intelligent replenishment module;

[0055] The data acquisition module is used to equip consumables with RFID tags, and use an RFID tag reader to collect consumable data, transmit the collected consumable data to a central data processing platform in real time through a wireless network, and pre-process the collected consumable data to construct a consumable data set;

[0056] The blockchain recording module is used to deploy blockchain nodes on the IT infrastructure of the hospital clinical department, integrate the blockchain platform with the hospital clinical department database and the RFID system, write smart contracts, encrypt the consumables data, generate a unique hash value, and store the encrypted consumables data on the blockchain platform;

[0057] The consumables data analysis module is used to obtain the consumables demand fluctuation coefficient CV based on the consumables data stored in the blockchain platform, and preset the consumables inventory service level coefficient Z, and obtain the consumables safety inventory AQ based on the consumables inventory service level coefficient Z and the consumables demand fluctuation coefficient CV;

[0058] The demand forecasting module is used to build a consumables demand forecasting model to obtain the consumables demand XQ at a future time point t. t ;

[0059] The inventory warning module is used to monitor the clinical department warehouse consumables data in real time, obtain the real-time consumables inventory KC, and compare and analyze the real-time consumables inventory KC with the consumables safety inventory AQ to evaluate the consumables inventory level;

[0060] The intelligent replenishment module is used to obtain the consumable replenishment quantity BH based on the real-time consumable inventory KC and the consumable demand XQ in the future predicted by the consumable demand prediction model, and transmit the consumable replenishment quantity BH to the blockchain platform, trigger the smart contract, generate a replenishment order, and send the replenishment order to the hospital consumable management department and suppliers to replenish the consumable inventory.

[0061] In this embodiment, the whole life cycle tracking of consumables is realized through RFID tags and blockchain recording modules. Each consumable is recorded and stored in the blockchain in real time during the storage, use and replenishment process, ensuring the authenticity and integrity of the data. This transparency not only enhances the management personnel's grasp of the use of consumables, but also allows the use record of each consumable to be traced at any time, reducing the management risk caused by information asymmetry.

[0062] By real-time monitoring of consumables inventory and demand forecasts, the system can automatically evaluate the relationship between the current inventory level and the safety inventory threshold and issue early warnings in a timely manner. This efficient inventory management not only avoids clinical service interruptions caused by insufficient inventory, but also reduces resource waste caused by excessive inventory, ensuring that hospitals can reasonably allocate consumable resources. In addition, through an automated replenishment decision-making mechanism, replenishment orders are automatically generated and transmitted to relevant departments based on real-time inventory and demand forecast data. The automation of this process significantly reduces the need for manual intervention, reduces labor costs, reduces the occurrence of human errors, and improves the efficiency and accuracy of the entire replenishment process. Since all consumables usage records and replenishment information are securely stored in the blockchain, the hospital's financial settlement will be more accurate. The integrity and immutability of this information effectively reduce the risk of missed pricing, ensuring that hospitals can achieve financial transparency in consumables management and improve the efficiency of fund use.

[0063] Example 2

[0064] Please refer to Figure 1 ,Specifically: the data acquisition module includes a consumables data acquisition unit and a data preprocessing unit;

[0065] The consumables data collection unit is used to install RFID readers at the consumables entry and exit ports and consumables use areas. When consumables are put into storage, RFID technology is used to generate unique RFID tags for consumables to record consumables information. Mobile RFID scanning equipment is used to scan the RFID tags on consumables in real time in the consumables use area to obtain consumables use data. The wireless signal transmission device on the RFID reader is used to transmit the collected consumables use data to the hospital central data processing platform through a wireless network. The consumables information includes consumables ID, name and consumables validity period. The mobile RFID scanning equipment is used to facilitate real-time scanning of consumables in the operating room and record consumables use conditions.

[0066] The data preprocessing unit is used to preprocess the consumables usage data transmitted to the hospital central data processing platform, including data cleaning, data conversion and data integration;

[0067] The data cleaning is used to check duplicate items in the consumables usage data, remove duplicate data with the same time and the same consumables ID, and standardize the consumables usage data, check whether there are missing values ​​in the consumables usage data, and fill in the missing values, wherein the missing values ​​include the consumables ID and the consumables quantity;

[0068] The data conversion is used to convert the timestamp in string format into a date and time object, and convert the consumables outbound and inbound data into a unified coding form, where "outbound" is 1 and "inbound" is 0, to facilitate data analysis and calculation;

[0069] The data integration is used to integrate the consumables usage data that has undergone data cleaning and data conversion into a consumables data set, and sort it according to timestamps to ensure that the time sequence of the data is correct, so as to facilitate time series analysis, and generate a consumables data set for each consumable, including the total outbound quantity, total inbound quantity and current inventory quantity, to facilitate subsequent quick viewing and analysis of the data.

[0070] In this embodiment, by installing RFID readers, real-time and accurate consumables data recording is achieved at the consumables entry and exit ports and usage areas, which significantly improves the accuracy and real-time nature of data collection and reduces errors and delays caused by manual recording. At the same time, the data preprocessing unit removes duplicate records through cleaning, optimizes data quality, ensures the uniqueness of each record, and improves data reliability. The data conversion process unifies the data format, enhances data consistency, avoids confusion caused by inconsistent formats, and improves system efficiency. In addition, the filling of missing values ​​ensures the integrity of the data, provides more comprehensive information for subsequent analysis, and supports more accurate decision-making. The cleaned and converted data is integrated into an ordered data set, which is convenient for subsequent analysis and demand forecasting, optimizes the hospital's resource allocation, improves the hospital's operational efficiency, supports intelligent decision-making and automated management, and makes the consumables management process more efficient and intelligent.

[0071] Example 3

[0072] Please refer to Figure 1 ,Specifically: the blockchain recording module includes a blockchain platform integration unit, a smart contract writing unit and a data encryption unit;

[0073] The blockchain platform integration unit is used to use Hyperledger Fabric as a blockchain platform, deploy Hyperledger Fabric nodes on the hospital IT infrastructure, build a blockchain network, connect the blockchain network with the hospital's clinical department consumables database and RFID system through an open API interface, use HTTP protocol requests to interact with the blockchain network, and upload the consumables data collected in real time by the Hyperledger Fabric node to the blockchain platform through an open API interface. Hyperledger Fabric is an open source enterprise-level blockchain platform designed for transactions between organizations and can support private chains and permissioned chains. Its modular architecture allows developers to build blockchain applications according to specific needs, meeting the medical industry's strict requirements for data privacy and compliance;

[0074] The hospital IT infrastructure includes hospital servers, network equipment, databases and medical terminal equipment;

[0075] The smart contract writing unit is used to write a smart contract using the Java language, and install the written smart contract into each Hyperledger Fabric node of the blockchain network. When the consumables data is uploaded to the blockchain platform through the blockchain network, a smart contract corresponding to the consumables is automatically generated according to the smart contract of the Hyperledger Fabric node. The smart contract includes the consumable ID, consumable usage time, usage quantity, user and using department.

[0076] The data encryption unit is used to generate an asymmetric key according to an asymmetric encryption algorithm RSA, including a public key and a private key, and use the public key to asymmetrically encrypt the consumable data in the consumable data set to obtain the encrypted consumable data;

[0077] According to the encrypted consumables data, hash processing is performed to generate a unique hash value, and the encrypted consumables data and the hash value corresponding to the consumables data are transmitted to the blockchain platform through the HTTPS communication protocol through the smart contract interface of the Hyperledger Fabric node.

[0078] The hash processing refers to using the SHA-256 algorithm to obtain a hash value of a fixed length based on the encrypted consumable data. During the data transmission and storage process, after the recipient receives the data, it can perform hash processing on it and compare the hash value to confirm the integrity of the data.

[0079] In this embodiment, by integrating Hyperledger Fabric, a secure and transparent blockchain network is established for the hospital's consumables management. Through an open API interface, the clinical department consumables database is connected to the RFID system to achieve real-time data collection and upload, ensuring the immediacy and accuracy of the data. This real-time recording mechanism reduces the risk of data tampering and loss, and provides a reliable traceability mechanism for consumables management. In addition, the smart contract writing unit automatically generates smart contracts related to the use of consumables, including consumables ID, usage time, and usage quantity information, ensuring the transparency and traceability of the consumables usage process. This process not only simplifies contract management, but also reduces human errors and improves efficiency through automation. Finally, the asymmetric encryption algorithm RSA is used to encrypt the consumables data to protect the confidentiality and integrity of the data. The unique hash value generated by hash processing further ensures that the data cannot be tampered with in the blockchain. This series of encryption and hashing measures not only enhances the security of the system, but also provides effective protection for sensitive data for the hospital, so that the consumables management system maintains efficient operation capabilities while complying with data privacy and compliance, effectively improving the security, transparency and efficiency of hospital consumables management, and reducing management risks.

[0080] Example 4

[0081] Please refer to Figure 1 Specifically: the consumables data analysis module is used to obtain the average demand D of consumables based on the consumables data in the preprocessed consumables data set. avg and the standard deviation of consumables demand σ, and based on the average consumables demand D avg The consumables demand fluctuation coefficient CV is obtained by using the consumables demand standard deviation σ, the consumables inventory service coefficient Z is preset, and the consumables safety stock threshold AQ is obtained based on the consumables inventory service coefficient Z and the consumables demand fluctuation coefficient CV;

[0082] The average demand for consumables D avg , the standard deviation of consumables demand σ and the consumables demand fluctuation coefficient CV are obtained as follows:

[0083]

[0084]

[0085]

[0086] Where D i is the consumables demand on the i-th day in the historical consumables data, n is the total number of days of consumables data collected, σ is the standard deviation of consumables demand, and D avg is the average demand for consumables;

[0087] The consumables safety inventory AQ is obtained in the following way:

[0088]

[0089] Where Z is the service coefficient of consumable inventory, D max It is the maximum demand for consumables.

[0090] In this embodiment, by deeply analyzing the preprocessed consumables data set, the average demand for consumables D can be effectively obtained. avg and the standard deviation of demand σ, provide basic data for subsequent inventory management. Through these statistical indicators, the module can calculate the consumables demand fluctuation coefficient CV, thereby quantifying the stability of demand. This series of indicators provides hospitals with a clear understanding of changes in consumables demand and helps to formulate more reasonable inventory strategies. In addition, the preset inventory service coefficient Z combined with the calculation of the demand fluctuation coefficient can accurately derive the consumables safety inventory AQ, effectively reducing the risk of insufficient or excessive inventory. Through this data-driven approach, hospitals can maintain appropriate inventory levels in a dynamic demand environment, improve resource utilization efficiency, ensure the smooth progress of clinical work, and ultimately achieve consumables management and cost control.

[0091] Example 5

[0092] Please refer to Figure 1 ,Specifically: the demand forecasting module includes a model building unit and a demand forecasting unit;

[0093] The model building unit is used to build a consumable demand prediction model based on the weighted moving average method, set the input layer of the consumable demand prediction model to consumable data, and the output layer to the consumable demand quantity XQ at a future time point. Use historical consumable demand data as training data, input the consumable demand prediction model, obtain the consumable demand quantity XQ at a future time point, and use the root mean square error RMSE to adjust the consumable demand prediction model parameters. The historical consumable demand data is obtained from a hospital database.

[0094] The demand prediction unit is used to input the real-time collected consumables data into the trained consumables demand prediction model according to the trained consumables demand prediction model to obtain the consumables demand XQ at the future time point t t ;

[0095] The consumables demand XQ at the future time point t t The method of obtaining is:

[0096]

[0097] Where D i is the historical demand for consumables on the i-th day, ω i is the weight of the historical demand for consumables on the i-th day, n is the total number of days of consumables data collected, i = 1, 2, 3, ..., n.

[0098] In this embodiment, the accuracy of consumable demand forecasting can be effectively improved through the model building unit and the demand forecasting unit. The model building unit uses the weighted moving average method to train the forecasting model based on historical demand data, and clarifies the input layer and the output layer to realize the prediction of the consumable demand XQ at a future time point. The model parameters are adjusted by using the root mean square error RMSE to ensure the reliability and accuracy of the prediction results, so that the hospital can dynamically adjust the demand forecast based on real-time data, thereby more accurately predicting future consumable demand. In addition, the demand forecasting unit inputs the consumable data collected in real time into the trained model to provide timely demand forecasts and support quick-response replenishment decisions, which not only improves the hospital's resource management efficiency and reduces the risk of inventory shortages due to forecasting errors, but also optimizes the overall consumable management process to ensure the continuity and stability of medical services.

[0099] Example 6

[0100] Please refer to Figure 1Specifically: the inventory warning module is used to obtain the real-time consumable inventory KC based on the consumable data stored in the blockchain platform, compare and analyze the real-time consumable inventory KC with the consumable safety inventory AQ, and evaluate the consumable inventory level. The specific evaluation content is as follows:

[0101] If the real-time consumable inventory KC is greater than or equal to the consumable safety inventory AQ, that is, KC ≥ AQ, the consumable inventory is judged to be at a safe level, the consumable data is recorded, and a consumable in and out data report is generated and sent to the clinical department warehouse manager;

[0102] If the real-time consumables inventory KC is less than the consumables safety inventory AQ, that is, KC<AQ, the consumables inventory is judged to be at a dangerous level, the alarm mechanism is triggered, the consumables data is recorded and sent to the blockchain platform.

[0103] In this embodiment, by real-time monitoring of consumables data in the blockchain platform, the real-time consumables inventory KC is obtained, and it is compared and analyzed with the safety inventory AQ, the efficiency and safety of consumables management are improved. When the inventory KC is greater than or equal to the safety inventory AQ, the system can determine that the inventory is at a safe level, record the consumables data in time and generate a consumables in and out data report to ensure that the warehouse manager of the clinical department can grasp the inventory status of consumables in time to facilitate the allocation and use of resources. When the real-time inventory KC is lower than the safety inventory AQ, the system immediately triggers the alarm mechanism, records the data and sends it to the blockchain platform to ensure that relevant departments take prompt measures to avoid affecting medical services due to insufficient inventory. This dynamic monitoring and automatic early warning mechanism not only reduces the risks caused by improper inventory management, but also improves the hospital's response speed to the use of consumables and promotes overall operational efficiency.

[0104] Example 7

[0105] Please refer to Figure 1 ,Specifically: the intelligent replenishment module includes a replenishment quantity analysis unit and a replenishment unit;

[0106] The replenishment quantity analysis unit is used to obtain the consumable replenishment quantity BH based on the real-time consumable inventory quantity KC and the consumable demand quantity XQ at a future time point obtained by the consumable demand prediction model when the real-time consumable inventory quantity KC is less than the consumable safety inventory quantity AQ, that is, KC<AQ, triggering the alarm mechanism, and transmit the obtained consumable replenishment quantity BH to the blockchain platform to trigger the smart contract;

[0107] The consumables replenishment quantity BH is obtained in the following manner:

[0108] BH = XQ-KC;

[0109] The replenishment unit is used to trigger the smart contract based on the consumables replenishment quantity BH received by the blockchain platform, formulate a consumables replenishment plan, automatically generate a replenishment order, and send the replenishment order to the hospital consumables management department and the consumables supplier until the hospital consumables management department and the consumables supplier respond.

[0110] In this embodiment, the flexibility and efficiency of hospital consumables management are improved through the collaborative work of the replenishment quantity analysis unit and the replenishment unit. When the real-time inventory KC is lower than the safety inventory AQ, the system automatically triggers the alarm mechanism and uses the real-time inventory KC and the future demand XQ obtained by the demand forecasting model to calculate the required replenishment quantity BH. This process ensures the scientificity and timeliness of replenishment decisions and avoids the risk of insufficient inventory. Subsequently, the replenishment unit quickly triggers the smart contract based on the replenishment quantity BH received by the blockchain platform, formulates a detailed replenishment plan, and automatically generates a replenishment order, which is sent to the hospital's consumables management department and suppliers in a timely manner. This automated and real-time replenishment mechanism not only improves the response speed and reduces errors caused by human intervention, but also optimizes supply chain management, ensures the continuous availability of medical resources, and thus improves the efficiency and service quality of the hospital's overall operations.

[0111] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent management system for clinical department warehouse consumables, characterized by: Including data collection module, blockchain recording module, consumables data analysis module, demand forecasting module, inventory warning module and intelligent replenishment module; The data acquisition module is used to equip consumables with RFID tags, and use an RFID tag reader to collect consumable data, transmit the collected consumable data to a central data processing platform in real time through a wireless network, and pre-process the collected consumable data to construct a consumable data set; The blockchain recording module is used to deploy blockchain nodes on the IT infrastructure of the hospital clinical department, integrate the blockchain platform with the hospital clinical department database and the RFID system, write smart contracts, encrypt the consumables data, generate a unique hash value, and store the encrypted consumables data on the blockchain platform; The consumables data analysis module is used to obtain the consumables demand fluctuation coefficient CV based on the consumables data stored in the blockchain platform, and preset the consumables inventory service level coefficient Z, and obtain the consumables safety inventory AQ based on the consumables inventory service level coefficient Z and the consumables demand fluctuation coefficient CV; The demand forecasting module is used to build a consumables demand forecasting model to obtain the consumables demand XQ at a future time point t. t ; The inventory warning module is used to monitor the clinical department warehouse consumables data in real time, obtain the real-time consumables inventory KC, and compare and analyze the real-time consumables inventory KC with the consumables safety inventory AQ to evaluate the consumables inventory level; The intelligent replenishment module is used to obtain the consumable replenishment quantity BH based on the real-time consumable inventory KC and the consumable demand XQ in the future predicted by the consumable demand prediction model, and transmit the consumable replenishment quantity BH to the blockchain platform, trigger the smart contract, generate a replenishment order, and send the replenishment order to the hospital consumable management department and suppliers to replenish the consumable inventory.

2. According to claim 1, the intelligent management system for clinical department warehouse consumables is characterized by: The data acquisition module includes a consumables data acquisition unit and a data preprocessing unit; The consumables data collection unit is used to install RFID readers at the consumables entry and exit ports and consumables use areas. When consumables are put into storage, RFID technology is used to generate unique RFID tags for consumables to record consumables information. A mobile RFID scanning device is used to scan the RFID tags on the consumables in the consumables use area in real time to obtain consumables use data. The wireless signal transmission device on the RFID reader is used to transmit the collected consumables use data to the hospital central data processing platform through a wireless network. The consumables information includes consumables ID, name and consumables validity period; The data preprocessing unit is used to preprocess the consumables usage data transmitted to the hospital central data processing platform, including data cleaning, data conversion and data integration; The data cleaning is used to check duplicate items in the consumables usage data, remove duplicate data with the same time and the same consumables ID, and standardize the consumables usage data, check whether there are missing values ​​in the consumables usage data, and fill in the missing values, wherein the missing values ​​include the consumables ID and the consumables quantity; The data conversion is used to convert the timestamp in string format into a date and time object, and convert the consumables outbound and inbound data into a unified coding format, where "outbound" is 1 and "inbound" is 0; The data integration is used to integrate the consumables usage data that has undergone data cleaning and data conversion into a consumables data set, and sort the data according to timestamps.

3. According to claim 1, the intelligent management system for clinical department warehouse consumables is characterized by: The blockchain recording module includes a blockchain platform integration unit, a smart contract writing unit and a data encryption unit; The blockchain platform integration unit is used to use Hyperledger Fabric as a blockchain platform, deploy Hyperledger Fabric nodes on the hospital IT infrastructure, build a blockchain network, connect the blockchain network with the hospital's clinical department consumables database and RFID system through an open API interface, use HTTP protocol requests to interact with the blockchain network, and upload the consumables data collected in real time by the Hyperledger Fabric node to the blockchain platform through the open API interface; The hospital IT infrastructure includes hospital servers, network equipment, databases and medical terminal equipment; The smart contract writing unit is used to write a smart contract using the Java language, and install the written smart contract into each Hyperledger Fabric node of the blockchain network. When the consumables data is uploaded to the blockchain platform through the blockchain network, a smart contract corresponding to the consumables is automatically generated according to the smart contract of the Hyperledger Fabric node. The smart contract includes the consumable ID, consumable usage time, usage quantity, user and using department.

4. According to claim 3, the intelligent management system for clinical department warehouse consumables is characterized by: The data encryption unit is used to generate an asymmetric key according to an asymmetric encryption algorithm RSA, including a public key and a private key, and use the public key to asymmetrically encrypt the consumable data in the consumable data set to obtain the encrypted consumable data; Hash processing is performed based on the encrypted consumable data to generate a unique hash value, and the encrypted consumable data and the hash value corresponding to the consumable data are transmitted to the blockchain platform through the HTTPS communication protocol through the smart contract interface of the Hyperledger Fabric node.

5. According to claim 1, the intelligent management system for clinical department warehouse consumables is characterized by: The consumables data analysis module is used to obtain the average demand D of consumables based on the consumables data in the preprocessed consumables data set. avg and the standard deviation of consumables demand σ, and based on the average consumables demand D avg The consumables demand fluctuation coefficient CV is obtained by using the consumables demand standard deviation σ, the consumables inventory service coefficient Z is preset, and the consumables safety stock threshold AQ is obtained based on the consumables inventory service coefficient Z and the consumables demand fluctuation coefficient CV; The average demand for consumables D avg , the standard deviation of consumables demand σ and the consumables demand fluctuation coefficient CV are obtained as follows: Where D i is the consumables demand on the i-th day in the historical consumables data, n is the total number of days of consumables data collected, σ is the standard deviation of consumables demand, and D avg is the average demand for consumables; The consumables safety inventory AQ is obtained in the following way: Where Z is the service coefficient of consumable inventory, D max It is the maximum demand for consumables.

6. The intelligent management system for clinical department warehouse consumables according to claim 1, characterized in that: The demand forecasting module includes a model building unit and a demand forecasting unit; The model building unit is used to build a consumable demand prediction model based on the weighted moving average method, set the input layer of the consumable demand prediction model to consumable data, and the output layer to the consumable demand quantity XQ at a future time point. Use historical consumable demand data as training data, input the consumable demand prediction model, obtain the consumable demand quantity XQ at a future time point, and use the root mean square error RMSE to adjust the consumable demand prediction model parameters. The historical consumable demand data is obtained from a hospital database.

7. The intelligent management system for clinical department warehouse consumables according to claim 6, characterized in that: The demand prediction unit is used to input the real-time collected consumables data into the trained consumables demand prediction model according to the trained consumables demand prediction model to obtain the consumables demand XQ at the future time point t t ; The consumables demand XQ at the future time point t t The method of obtaining is: Where D i is the historical demand for consumables on the i-th day, ω i is the weight of the historical demand for consumables on the i-th day, n is the total number of days of consumables data collected, i = 1, 2, 3, ..., n.

8. The intelligent management system for clinical department warehouse consumables according to claim 1, characterized in that: The inventory warning module is used to obtain the real-time consumable inventory KC based on the consumable data stored in the blockchain platform, compare and analyze the real-time consumable inventory KC with the consumable safety inventory AQ, and evaluate the consumable inventory level. The specific evaluation contents are as follows: If the real-time consumable inventory KC is greater than or equal to the consumable safety inventory AQ, that is, KC ≥ AQ, the consumable inventory is judged to be at a safe level, the consumable data is recorded, and a consumable in and out data report is generated and sent to the clinical department warehouse manager; If the real-time consumables inventory KC is less than the consumables safety inventory AQ, that is, KC<AQ, the consumables inventory is judged to be at a dangerous level, the alarm mechanism is triggered, the consumables data is recorded and sent to the blockchain platform.

9. The intelligent management system for clinical department warehouse consumables according to claim 8, characterized in that: The intelligent replenishment module includes a replenishment quantity analysis unit and a replenishment unit; The replenishment quantity analysis unit is used to obtain the consumable replenishment quantity BH based on the real-time consumable inventory quantity KC and the consumable demand quantity XQ at a future time point obtained by the consumable demand prediction model when the real-time consumable inventory quantity KC is less than the consumable safety inventory quantity AQ, that is, KC<AQ, triggering the alarm mechanism, and transmit the obtained consumable replenishment quantity BH to the blockchain platform to trigger the smart contract; The consumables replenishment quantity BH is obtained in the following manner: BH=XQ-KC.

10. The intelligent management system for clinical department warehouse consumables according to claim 9, characterized in that: The replenishment unit is used to trigger the smart contract based on the consumables replenishment quantity BH received by the blockchain platform, formulate a consumables replenishment plan, automatically generate a replenishment order, and send the replenishment order to the hospital consumables management department and the consumables supplier until the hospital consumables management department and the consumables supplier respond.

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