A medical item expiration date management system based on machine learning

Abstract

The present invention relates to the field of data processing technology, and provides a medical item expiration management system based on machine learning. The system includes: a data acquisition module for acquiring item information of medical items to be managed, as well as warehouse information of warehouses at various levels; a first calculation module for processing item information through a machine learning model to predict the usage and expiration turnover rate of medical items; a first strategy module for determining a collection strategy for medical items based on the usage and expiration turnover rate of medical items; a second strategy module for determining a distribution strategy for medical items based on the inventory of medical items in warehouses at various levels and the first expiration turnover rate; a first management module for ordering and collecting medical items according to the collection strategy; and a second management module for distributing medical items according to the distribution strategy. The present invention can improve the expiration management of medical items and the accuracy of the collection and procurement of medical items.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a medical item expiration date management system and electronic equipment based on machine learning. Background Art

[0002] In current medical supply management, most hospitals rely on manual record-keeping or simple spreadsheets to manage the inbound and outbound shipments and expiration dates of items. Typically, warehouse managers or medical staff are responsible for regularly checking inventory status and expiration dates, and using experience to determine when to restock or dispose of items approaching expiration.

[0003] However, manual inspection and record-keeping is not only inefficient but also prone to omissions and errors, making accurate expiration date management impossible, especially when dealing with large quantities of medical supplies. Furthermore, due to the lack of a systematic inventory forecasting mechanism, hospitals are often unable to rationally plan the procurement and allocation of supplies, leading to over-purchasing or shortages. Summary of the Invention

[0004] In response to the technical problems existing in the prior art, the present invention provides a medical product expiration date management system and electronic equipment based on machine learning that can improve the expiration date management of medical products and the accuracy of medical product collection and procurement.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] The present invention provides a medical product expiration date management system based on machine learning, the system comprising:

[0007] A data acquisition module is used to obtain the item information of the medical items to be managed and the warehouse information of warehouses at various levels;

[0008] A first computing module is configured to process the item information using a machine learning model to predict the usage and expiration turnover rate of the medical item;

[0009] A first strategy module is configured to determine a collection strategy for the medical supplies based on the usage and expiration turnover rate of the medical supplies;

[0010] a second strategy module, configured to determine a deployment strategy for the medical supplies based on the inventory levels of the medical supplies in the warehouses at each level and the first validity period turnover rates;

[0011] A first management module is used to order and collect the medical supplies according to the collection strategy;

[0012] The second management module is used to allocate the medical supplies according to the allocation strategy.

[0013] Furthermore, the first calculation module is specifically configured to:

[0014] Obtaining the current inventory of the medical item;

[0015] Obtain the average monthly usage, average quarterly usage and expiration date of the medical supplies;

[0016] Performing a weighted summation on the monthly average usage, quarterly average usage, and expiration date of the medical supplies to obtain a second processing result;

[0017] The expiration turnover rate of the medical item is determined according to the first processing result and the second processing result.

[0018] Furthermore, the system also includes an inventory upper and lower limit module for:

[0019] Get the value of the current month;

[0020] The upper and lower inventory limits of the medical supplies are determined based on the values ​​of the current month, as well as the monthly average usage and quarterly average usage of the medical supplies.

[0021] Furthermore, the inventory upper and lower limit module is also used to:

[0022] When the inventory of a first medical item exceeds the quarterly average usage of the first medical item, and the number of first medical items with a remaining validity period of less than 6 months accounts for more than 30% of the inventory of the first medical item, an inventory limit alarm is issued for the first medical item;

[0023] When the inventory quantity of a second medical item is less than the base number of the second medical item, an inventory lower limit alarm is issued for the second medical item; the base number of the second medical item is determined based on the average monthly usage, average quarterly usage and average annual usage of the second medical item.

[0024] Furthermore, the warehouses at each level include:

[0025] The third-level warehouse is set up in the ward and is used to realize the delivery and storage of goods in the entire ward;

[0026] The secondary warehouse is located in the ward treatment room. Items entering the secondary warehouse come from the tertiary warehouse, and items leaving the warehouse flow to the primary warehouse or are consumed.

[0027] The first-level warehouse is set up in the ward treatment vehicle and nursing vehicle. The incoming items of the first-level warehouse come from the second-level warehouse, and the outgoing items are used for consumption.

[0028] Furthermore, the first policy module is further specifically configured to:

[0029] Obtaining a first difference between an upper inventory limit and a current inventory level of the medical item;

[0030] The order quantity of the medical supplies in the delivery strategy is determined based on the values ​​of the current month, the first difference value, the monthly average usage and the expiration date turnover rate of the medical supplies.

[0031] Furthermore, the second policy module is specifically configured to:

[0032] Obtaining a first inventory quantity of the medical supplies in the primary warehouse, a second inventory quantity in the secondary warehouse, and a third inventory quantity in the tertiary warehouse;

[0033] Obtaining a first-expiration turnover rate of the medical supplies in the first-level warehouse, a second-expiration turnover rate in the second-level warehouse, and a third-expiration turnover rate in the third-level warehouse;

[0034] Determine the allocation priority of the medical supplies in the allocation strategy based on the first expiration turnover rate, the second expiration turnover rate, and the third expiration turnover rate, as well as the first inventory level, the second inventory level, and the third inventory level.

[0035] Furthermore, the system also includes a near expiration warning module, which is used to display warning prompt information in different colors according to the remaining expiration date of the medical item, wherein:

[0036] When it is determined that the remaining validity period of the medical item is within one month, a red warning message is displayed;

[0037] When it is determined that the remaining validity period of the medical item is within three months, an orange warning message will be displayed;

[0038] When it is determined that the remaining validity period of the medical item is within six months, a yellow warning prompt message is displayed.

[0039] Furthermore, the system also includes an item information update module, which is used to:

[0040] Obtaining the item consumption record of the medical items by scanning the code on a mobile PDA;

[0041] The inventory information of the medical supplies is automatically updated according to the consumption records of the medical supplies.

[0042] In addition, to achieve the above-mentioned purpose, the present invention also proposes an electronic device, comprising: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby realizing the functions of a medical product expiration management system based on machine learning as described above.

[0043] The beneficial effects of the present invention are:

[0044] (1) The present invention can realize the automated management of medical supplies information through data collection and standardized processing, reducing errors and omissions in manual records and improving management efficiency. At the same time, the mobile PDA terminal is used to perform item entry and exit operations, and inventory information is updated in real time to ensure the accuracy and timeliness of inventory data.

[0045] (2) This invention utilizes a machine learning model to predict item usage and turnover based on historical data and seasonal demand, dynamically adjusting the upper and lower limits of inventory. This model can adaptively adjust according to the characteristics of different departments, ensuring the rational allocation of inventory, reducing over-purchasing and material shortages, and improving the scientific nature of inventory management.

[0046] (3) The present invention can effectively track the expiration date of each item, giving priority to consuming items that are about to expire, thereby reducing waste. The near-expiration warning system can provide hierarchical reminders to management personnel, allowing them to promptly dispose of items that are about to expire, further improving the effectiveness of item use.

[0047] (4) Through the intelligent item collection algorithm and item allocation optimization mechanism, the present invention can automatically recommend order quantities and allocation priorities based on expiration dates, inventory status, and usage frequency, ensuring efficient and scientific use of items in warehouses at all levels and minimizing the risk of inventory backlogs and item expiration.

[0048] In summary, the present invention can not only improve the hospital's medical supplies management level, but also effectively reduce the supply costs and ensure the timeliness of supply and safety of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A scenario diagram of a medical item expiration date management system based on machine learning provided by the present invention;

[0050] Figure 2 A schematic diagram of the structure of a medical product expiration date management system based on machine learning provided by the present invention;

[0051] Figure 3 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0053] See also Figure 1 , Figure 1 This is a scenario diagram of a medical product expiration date management system based on machine learning provided by the present invention. Figure 1 As shown, the terminal and server are connected via a network, such as a wired or wireless network. Terminals include, but are not limited to, portable devices such as mobile phones and tablets installed with various network platform applications, as well as fixed devices such as computers, kiosks, and advertising machines. The server provides various business services to users, including service push servers and user recommendation servers.

[0054] It should be noted that Figure 1 The scenario diagram of a medical product expiration management system based on machine learning shown is only an example. The terminal, server, and application scenario described in the embodiment of the present invention are intended to more clearly illustrate the technical solution of the embodiment of the present invention, and do not generate any limitation on the technical solution provided by the embodiment of the present invention. Ordinary technicians in this field can know that with the evolution of the system and the emergence of new business scenarios, the technical solution provided by the embodiment of the present invention is also applicable to similar technical problems.

[0055] Among them, the terminal can be used to:

[0056] Obtain item information of medical items to be managed, as well as warehouse information of warehouses at all levels;

[0057] Processing the item information through a machine learning model to predict the usage and expiration turnover rate of the medical item;

[0058] Determine a collection strategy for the medical supplies based on the usage and expiration turnover rate of the medical supplies;

[0059] Determining a deployment strategy for the medical supplies based on the inventory levels and first-effectiveness turnover rates of the medical supplies in the warehouses at each level;

[0060] Ordering and collecting the medical supplies according to the collection strategy;

[0061] The medical supplies are dispensed according to the dispensing strategy.

[0062] See also Figure 2 , Figure 2This is a structural diagram of a medical product expiration date management system based on machine learning provided by the present invention.

[0063] like Figure 2 As shown, an embodiment of the present invention proposes a medical item expiration date management system based on machine learning, including: a data acquisition module 101, a first calculation module 102, a second calculation module 103, a first strategy module 104, a first management module 105 and a second management module 106.

[0064] In some embodiments, the data acquisition module 101 can be used to acquire item information of medical items to be managed, and warehouse information of warehouses at various levels.

[0065] In some embodiments, the item information of medical items may include basic item information, such as item ID: a unique identification code for each medical item, used to distinguish different items. This is the basis for data processing and analysis, ensuring that the system can accurately locate each item. Item name: the name of the medical item, which is convenient for medical staff to identify and query. For example, medicines, consumables, medical equipment, etc. Specification model: detailed specification or model information of the item (such as the dosage of the medicine, packaging specifications, etc.) to ensure that items of different specifications can be correctly managed and allocated.

[0066] In some embodiments, the item information of the medical item may also include item inventory information, item expiration information, item consumption information, item category and department information, and other auxiliary information.

[0067] In some embodiments, item inventory information may include current inventory levels: The system needs to record the real-time inventory quantity of each item in each warehouse to facilitate inventory management and item allocation. This data is typically dynamic, continuously updated as items are stored, shipped, and used. Upper and lower limits (UL) and lower limits (LL) are set by the system based on historical data and usage to ensure that inventory levels do not exceed reasonable limits and avoid overstocking or shortages.

[0068] In some embodiments, the expiration date information of an item may include the production date: the time when the item was produced, which is very important for expiration date management. The remaining validity period of the item can be deduced from the production date, thereby ensuring that the item is reasonably used before it expires. Expiration Date (EP): The expiration date of an item is the length of time it can be used. The system uses this data to manage the expiration date of the item, and combines inventory and consumption to ensure that expired items are handled in a timely manner. Expiration Date Turnover Rate (ECR): The expiration date turnover rate is an indicator calculated based on the usage, inventory and expiration date of the item, which is used to measure the turnover efficiency of the item during its validity period. Based on this value, the system will determine whether certain items need to be used first to avoid expiration waste.

[0069] It should be noted that the validity period in this application does not refer to the remaining validity period, but rather the production validity period of the item itself. This includes medicines, commonly used medical consumables, and the like, but does not include various diagnostic and treatment instruments, instruments, and items cleaned, disinfected, and sterilized by disinfection supply centers. Short-term validity period items refer to medical items with a validity period of less than one year, medium-term validity period items refer to medical items with a validity period of one to three years, and long-term validity period items refer to medical items with a validity period of more than three years.

[0070] In some embodiments, item consumption information may include Monthly Usage (MU): The average monthly usage of an item over a period of time. This data is used to predict future usage needs and help the system dynamically adjust inventory limits. Quarterly Usage (SU): The average usage calculated on a quarterly basis, used for longer-term inventory demand analysis. Yearly Usage (YU): The average usage of an item calculated on an annual basis, which helps analyze long-term consumption trends of an item.

[0071] In some embodiments, item category and department information can include: Item category: The system may categorize items based on their nature, such as medicine, consumables, and equipment. Items in different categories may have different management requirements. Usage department: The system records the department that each item is used in, such as internal medicine, surgery, or emergency. This helps manage items based on departmental needs and characteristics, especially when developing item collection strategies and inventory allocation.

[0072] In some embodiments, other auxiliary information may include price: the unit price of the item, which helps the system to manage costs and make item purchasing decisions. Storage conditions: Some medical items require special storage conditions (such as temperature, humidity, etc.). The system will record this information so that the items can be stored under the required conditions.

[0073] In some embodiments, the above item information can be acquired and entered into the system by manual entry, barcode scanning, or automatic docking. For small-scale medical institutions, initial data may be manually entered or imported into Excel spreadsheets. Barcode or QR code technology can be used to collect item information in real time and synchronize it into the system when items are put into storage, shipped out of storage, and taken inventory through PDAs or mobile terminal devices. For large hospitals, item information may be directly docked through the hospital information management system (HIS) or the drug supply chain system (such as ERP) and automatically imported into the inventory management system.

[0074] Understanding this, obtaining detailed information about medical supplies is crucial for subsequent expiration date management, inventory forecasting, allocation optimization, and intelligent ordering. Accurate and comprehensive information enables refined item management, preventing expiration, overstocking, and shortages. It also provides data support, enabling the system to perform intelligent forecasting and inventory optimization using machine learning models. Through expiration date management, dynamic inventory adjustments, and item allocation, the hospital's supply chain is ensured to operate efficiently and meet clinical needs.

[0075] In summary, obtaining medical product information is the first step in building an intelligent medical product expiration management system, providing a data foundation for subsequent intelligent management.

[0076] In some embodiments, each level of warehouse may include:

[0077] The third-level warehouse is set up in the ward and is used to realize the delivery and storage of goods in the entire ward;

[0078] The secondary warehouse is located in the ward treatment room. Items entering the secondary warehouse come from the tertiary warehouse, and items leaving the warehouse flow to the primary warehouse or are consumed.

[0079] The first-level warehouse is set up in the ward treatment vehicle and nursing vehicle. The incoming items of the first-level warehouse come from the second-level warehouse, and the outgoing items are used for consumption.

[0080] In some embodiments, the first computing module 102 can be used to process the item information through a machine learning model to predict the usage and expiration turnover rate of the medical item.

[0081] In some embodiments, data related to medical products can be obtained as input to the model. This data will serve as the basis for predicting product usage, including:

[0082] Historical usage data: including the monthly average usage (MU), quarterly average usage (SU), and annual average usage (YU) of items. These data reflect the historical consumption trend of items.

[0083] Inventory information: Current inventory quantity (I), upper inventory limit (UL) and lower inventory limit (LL), etc., used to guide forecast inventory management.

[0084] Expiration date information: The item's expiration date (EP), production date, and expiration date turnover rate (ECR) help the system dynamically adjust the predicted usage based on the item's expiration date.

[0085] Seasonality and departmental demand data: The demand for medical supplies may vary across seasons and departments, such as the increased demand for antiviral drugs during the flu season. These specific seasonal factors are also important inputs to the forecasting model.

[0086] In some embodiments, historical data can be used to train machine learning models to improve the accuracy of item usage predictions. By analyzing historical data, machine learning models can identify usage patterns and trends hidden in the data and make adaptive adjustments.

[0087] In some embodiments, after the machine learning model is trained, the system can predict future usage based on current item information. This step involves the model processing existing data to generate future item demand, typically based on a specific time period (e.g., a month, quarter, or year). The model can adjust future item usage forecasts based on seasonal fluctuations in historical data. For example, demand for antibiotics and antivirals may increase in winter, and the model can identify this pattern and increase predicted usage. Different departments have varying needs for items, and the model can predict future usage for specific items within a department based on historical usage. For example, the emergency department may require more disposable medical supplies, and the forecasting model can accurately estimate this based on historical data. By incorporating item expiration information, the model can avoid predicting usage beyond the item's expiration date. For example, items approaching their expiration date may need to be consumed in advance, and the model can adjust short-term usage forecasts based on expiration information to avoid waste. The system can dynamically adjust forecasts based on current inventory changes. For example, if the current inventory level of a particular item approaches a lower limit, the model will predict increased future demand and trigger automatic replenishment or allocation processes.

[0088] In some embodiments, forecast results can help the system dynamically adjust inventory limits to ensure inventory levels remain within reasonable ranges. For items with high usage, the system will increase the inventory limit based on forecasts; for items with low usage or decreasing demand, the system will reduce purchase quantities or lower the inventory limit. The system can automatically generate ordering recommendations based on future item demand and trigger replenishment based on real-time inventory status. For example, if the forecasted usage of an item is high and the inventory is nearing the lower limit, the system will automatically recommend a purchase and issue a replenishment request. By forecasting the demand for items across different departments or warehouses, the system can optimize the cross-warehouse allocation of items, ensuring that items are properly distributed across warehouses and avoiding inventory shortages or backlogs in certain warehouses. By forecasting the demand for items across different departments or warehouses, the system can optimize the cross-warehouse allocation of items, ensuring that items are properly distributed across warehouses and avoiding inventory shortages or backlogs in certain warehouses. For long-term procurement and budget planning in hospitals, the results of forecasting models can provide management with important data support, helping them formulate procurement plans for the coming months or years and optimize costs.

[0089] As the system continues to operate, new item usage data will be continuously fed into the machine learning model. The system continuously trains and optimizes the model based on this new data to improve forecast accuracy. For items with significant seasonal fluctuations or specialized departmental needs, the model can adaptively adjust to dynamically track changes in item demand, resulting in even more accurate forecasts.

[0090] This invention uses machine learning models to process medical supply information and predict usage, transforming supply management from traditional empirical judgment to data-driven intelligent prediction. By integrating multi-dimensional data such as historical usage data, inventory status, expiration date management, and seasonal demand, this process provides efficient and accurate decision-making for medical supply procurement, inventory management, and supply allocation. This not only significantly reduces supply waste and avoids inventory shortages, but also significantly improves the overall efficiency of hospital supply chain management.

[0091] In some embodiments, the first calculation module 102 may be specifically configured to:

[0092] Obtaining the current inventory of the medical item;

[0093] Obtain the average monthly usage, average quarterly usage and expiration date of the medical supplies;

[0094] Performing a weighted summation on the monthly average usage, quarterly average usage, and expiration date of the medical supplies to obtain a second processing result;

[0095] The expiration turnover rate of the medical item is determined according to the first processing result and the second processing result.

[0096] In some practical examples, the expiration turnover rate of medical items can be expressed as:

[0097]

[0098] Where ECR is the expiration turnover rate, I is the current inventory, MU is the average monthly usage, SU is the average quarterly usage, YU is the average annual usage, EP is the expiration date, and α, β, γ, and δ are the first, second, third, and fourth weights, respectively.

[0099] In practice, ECR stands for Expiration Date Turnover Rate, which reflects whether items are consumed before their expiration date. By calculating ECR, you can assess the turnover rate of inventory items and help determine whether accelerated consumption or inventory adjustments are needed to prevent expiration.

[0100] I is the current inventory, which refers to the actual inventory quantity of the item in the system at the current moment. The larger the inventory, the higher the turnover efficiency required in theory to consume it in time within the validity period. Therefore, I is used as the numerator to represent its positive impact on ECR.

[0101] MU stands for Monthly Average Usage, representing the average monthly consumption of an item over a period of time. Usage directly impacts the rate at which inventory is depleted. A higher monthly average usage indicates a higher turnover rate, so this term forms part of the denominator, reflecting the impact of usage frequency on expiration date management.

[0102] SU stands for Quarterly Average Usage, which is the average usage calculated on a quarterly basis over the past few months. Quarterly Average Usage reflects the usage trend of items over a longer period of time. It is multiplied by the square root of the expiration date to smooth out short-term fluctuations.

[0103] YU represents the average annual usage of an item over the past year, reflecting fluctuations in usage throughout the year. Using ln(YU × EP) logarithmically smoothes this value to stabilize its impact and avoid the undue influence of short-term outliers.

[0104] EP stands for the expiration date, which is the length of time from when an item enters storage until it expires, typically measured in months. The expiration date directly impacts the urgency of an item's consumption. The shorter the expiration date, the higher the turnover rate required to ensure items are consumed before they expire.

[0105] α, β, γ, and δ are the first weight, the second weight, the third weight, and the fourth weight, respectively.

[0106] Specifically, the numerator of α×I is composed of the current inventory level I and the weight α, which represents the impact of inventory level on turnover rate. A larger inventory level means a higher turnover efficiency is required to ensure that items are consumed within their validity period.

[0107] In β×MU×EP+γ×SU×EP+δ×ln(YU×EP), β×MU×EP represents the product of the average monthly usage and the validity period, reflecting the rate at which monthly usage consumes inventory. The weight β makes it adjustable.

[0108] The product of the quarterly average usage and the square root of the validity period is used to smooth short-term fluctuations, and the weight γ makes this part more flexible to the consumption patterns of different items.

[0109] δ×ln(YU×EP) is the logarithmic function of the average annual usage and the expiration date. The weight δ adjusts its impact on the long-term consumption trend, ensuring that the system can optimize inventory management based on usage data at different time scales.

[0110] It can be understood that the larger the ECR value, the higher the turnover rate of inventory items and the greater the probability that the items will be consumed in time within their validity period; the smaller the ECR value, the more likely the item is at risk of expiration or backlog, and managers need to take corresponding measures.

[0111] This invention can help hospitals and medical institutions accurately assess the effectiveness of item expiration management and dynamically adjust inventory strategies based on frequency of use, expiration date, and historical data, ensuring optimal item turnover and inventory optimization. By properly adjusting weight coefficients, the system can be adapted to the specific needs of different departments and items, reducing the risk of medical item expiration or shortages.

[0112] In some embodiments, the system of the present invention further includes an inventory upper and lower limit module for:

[0113] Get the value of the current month;

[0114] The upper and lower inventory limits of the medical supplies are determined based on the values ​​of the current month, as well as the monthly average usage and quarterly average usage of the medical supplies.

[0115] In some embodiments, the upper and lower inventory limits may be expressed as:

[0116]

[0117] Where UL is the upper limit of inventory, LL is the lower limit of inventory, MU is the average monthly usage, SU is the average quarterly usage, YU is the average annual usage, t is the value of the current month, μ, σ, λ, and ρ are the first, second, third, and fourth adjustment coefficients, respectively.

[0118] In practice, μ is a key factor used to adjust the overall inventory limit. This parameter allows us to adjust the inventory limit based on different item characteristics (such as importance and shelf life), allowing the system to adapt to different demand situations.

[0119] MU×3 represents high-frequency demand for an item in the short term (monthly). Demand for an item is typically stable over a month. Multiplying by 3 means the system tends to prepare three months of inventory reserves to cope with possible short-term fluctuations.

[0120] This is used to assess long-term (annual) demand for items. Incorporating average annual usage ensures the system has sufficient long-term inventory support. Taking a quarter is intended to balance short-term and long-term demand and avoid excessive long-term reserves.

[0121] Reflects seasonal fluctuations in inventory demand. t is an input parameter for seasonal adjustment based on monthly fluctuations. The value of t ranges from 1 to 12, corresponding to the 12 months of the year. This function is used to reflect seasonal fluctuations in demand for an item, with a 12-month period. The value of the sine function changes periodically throughout the year, simulating seasonal fluctuations in demand. For example, demand for pharmaceuticals surges in certain months (such as winter flu season), and the peaks of the sine function reflect this fluctuation. σ controls the magnitude of the seasonal fluctuation. Different items have different sensitivities to seasonal fluctuations, and the magnitude of the sine wave determines the extent to which the sine wave affects the inventory limit.

[0122] λ is similar to μ in that it adjusts the coefficient of the entire inventory floor. It controls the overall size of the inventory floor to ensure that the minimum inventory of different items meets actual demand and management requirements. Reflects medium-term demand. Taking into account quarterly fluctuations, a third of quarterly demand should be retained in the inventory floor to ensure that inventory will not be depleted due to fluctuations in a short period of time.

[0123] It is used to reflect long-term demand and smooth the demand throughout the year to ensure the rationality of long-term inventory reserves. Taking one-twelfth of the average annual demand is to prevent the inventory of items that have not been used for a long time from tying up too many resources.

[0124] Used to reflect seasonal changes in demand.

[0125] The present invention dynamically adjusts the inventory limit by combining the short-term (monthly), medium-term (quarterly) and long-term (annual) demand for items to cope with changes in usage frequency, and captures seasonal fluctuations through a sine function, making the inventory limit more flexible and in line with actual needs.

[0126] The fluctuation within a one-year cycle is the opposite of the sine function and is used to represent the impact of seasonal changes on the inventory floor. Its function is to simulate the decrease in seasonal demand and reduce the inventory floor to avoid over-replenishment.

[0127] ρ is used to control the impact of seasonal demand changes on the inventory floor. Different items have different sensitivities to seasonal changes, and the magnitude of ρ determines the magnitude of the cosine wave's adjustment to the inventory floor.

[0128] The present invention dynamically adjusts the upper and lower inventory limits by combining the short-term (monthly), medium-term (quarterly) and long-term (annual) demand for items to cope with changes in usage frequency, and captures seasonal fluctuations through a sine function, making the inventory limit more flexible and in line with actual needs.

[0129] In some embodiments, the inventory limit module is further configured to:

[0130] When the inventory of a first medical item exceeds the quarterly average usage of the first medical item, and the number of first medical items with a remaining validity period of less than 6 months accounts for more than 30% of the inventory of the first medical item, an inventory limit alarm is issued for the first medical item;

[0131] When the inventory quantity of a second medical item is less than the base number of the second medical item, an inventory lower limit alarm is issued for the second medical item; the base number of the second medical item is determined based on the average monthly usage, average quarterly usage and average annual usage of the second medical item.

[0132] In some embodiments, the first strategy module 103 may be configured to determine a collection strategy for the medical supplies based on the usage and expiration turnover rate of the medical supplies.

[0133] In some embodiments, the first policy module 103 is specifically configured to:

[0134] Obtaining a first difference between an upper inventory limit and a current inventory level of the medical item;

[0135] The order quantity of the medical supplies in the delivery strategy is determined based on the values ​​of the current month, the first difference value, the monthly average usage and the expiration date turnover rate of the medical supplies.

[0136] In some embodiments, the order quantity is expressed as:

[0137]

[0138] Among them, OQ is the order quantity, MU is the average monthly usage, UL is the inventory limit, I is the current inventory, ECR is the validity period turnover rate, ∈, ∈, and φ are the fifth, sixth, and seventh weights, respectively.

[0139] In the specific implementation, is a seasonal fluctuation correction term, which is used to adjust the order quantity to reflect seasonal changes in demand for items. It is corrected based on the sine function.

[0140] t is the numeric value of the current month (1-12) and is used to determine the current time's position in the year. The sine function has a 12-month period and simulates seasonal demand fluctuations. For example, demand for certain medical products may increase significantly during certain seasons (such as winter), and the sine function's fluctuations can accurately reflect these changes. ∈ is the adjustment factor, which controls the magnitude of seasonal fluctuations. Different products have different sensitivities to seasonal fluctuations, and the magnitude of ∈ determines the impact of seasonal fluctuations on order quantities. Using the sine function correction, order quantities can be dynamically adjusted, ensuring that orders are increased during peak demand seasons and reduced during off-seasons, thereby optimizing inventory levels.

[0141] ω is the fifth weight, used to adjust the first part of the formula, which determines the impact of average monthly usage on order quantity. This determines the influence of historical usage data on ordering decisions. By adjusting ω, the system can weight this part based on the importance of the item or other factors.

[0142] φ is the seventh weight, which adjusts the second part of the formula, which measures the impact of the difference between the inventory limit and the current inventory on the order quantity. This determines the degree to which the difference in inventory affects the order quantity. By adjusting φ, the system can determine whether to quickly reduce the order quantity when inventory approaches the limit.

[0143] This represents the base order quantity based on average monthly usage and seasonal fluctuations. By adjusting ω and ∈, the system can dynamically adjust the order quantity based on the item's historical usage frequency and seasonal demand changes, ensuring timely replenishment during peak seasons and reducing purchases during off-seasons.

[0144] This part further adjusts the order quantity based on the current inventory status and expiration turnover rate. By adjusting φ and ECR, the system can dynamically balance the order quantity with the inventory limit to avoid overstocking or shortage of items.

[0145] In the present invention, a larger OQ value indicates that more of the item needs to be ordered; a smaller OQ value indicates that the current inventory of the item is sufficient and no large-scale replenishment is required. This method combines multiple factors such as historical usage data, current inventory, inventory limit, and expiration date turnover rate to ensure that ordering decisions are both reasonable and flexible, thereby maximizing the efficiency of inventory management.

[0146] In some embodiments, the second strategy module 104 may be configured to determine a deployment strategy for the medical supplies based on the inventory levels and first validity period turnover rates of the medical supplies in the warehouses at each level.

[0147] In some embodiments, the second policy module 104 is specifically configured to:

[0148] Obtaining a first inventory quantity of the medical supplies in the primary warehouse, a second inventory quantity in the secondary warehouse, and a third inventory quantity in the tertiary warehouse;

[0149] Obtaining a first-expiration turnover rate of the medical supplies in the first-level warehouse, a second-expiration turnover rate in the second-level warehouse, and a third-expiration turnover rate in the third-level warehouse;

[0150] Determine the allocation priority of the medical supplies in the allocation strategy based on the first expiration turnover rate, the second expiration turnover rate, and the third expiration turnover rate, as well as the first inventory level, the second inventory level, and the third inventory level.

[0151] In some embodiments, the deployment priority can be expressed as:

[0152]

[0153] Among them, TP is the allocation priority, I1, I2, and I3 are the first inventory, second inventory, and third inventory, respectively; ECR1, ECR2, and ECR3 are the first validity period turnover rate, second validity period turnover rate, and third validity period turnover rate, respectively; ψ is the fifth adjustment coefficient.

[0154] Specifically, TP is the system's assigned allocation priority for an item across different warehouses. A higher value indicates the warehouse from which the item should be allocated and used first. By calculating allocation priorities, the system can effectively manage cross-warehouse allocations, prioritizing high-turnover items and those nearing expiration to avoid inventory backlogs and item expiration.

[0155] I1×ECR1+I2×ECR2+I3×ECR3 is the sum of the three warehouse inventory levels I1, I2, and I3 multiplied by their corresponding expiration turnover rates ECR1, ECR2, and ECR3, respectively. This represents the contribution of each warehouse's inventory items to overall turnover efficiency.

[0156] In some embodiments, I1 is the inventory level of the primary warehouse, which is usually the inventory of items in the ward treatment cart or nursing cart, which is directly used in the ward or clinical use. I2 is the inventory level of the secondary warehouse, which is usually the inventory in the ward treatment room, used as a ward reserve. I3 is the inventory level of the tertiary warehouse, which is usually the inventory of the ward warehouse, which is the long-term reserve for the entire ward. Inventory level is an important factor affecting the allocation priority. Items in small inventory warehouses (such as primary or secondary warehouses) are usually allocated first to maximize their utilization efficiency and reduce the risk of expiration.

[0157] A higher expiration turnover rate indicates that items in the warehouse are consumed more quickly, inventory turnover is faster, and the priority is higher. By multiplying inventory volume by the expiration turnover rate, the system can properly balance item usage efficiency and inventory levels, preventing low-turnover items from being stored for long periods of time.

[0158] I1+I2+I3 is the total inventory of the item across the primary, secondary, and tertiary warehouses. This total inventory serves as the denominator, normalizing the inventory contributions of each warehouse. This allows the system to prioritize the allocation of the entire inventory for the item, rather than focusing solely on a single warehouse. This normalization ensures balanced allocation of items across warehouses, preventing any one warehouse from overstocking or running out of inventory.

[0159] μ is the fifth adjustment coefficient, used to adjust the overall allocation priority weight. It controls the overall output scale of the formula, adapting the allocation priority value to specific management needs. By adjusting μ, the system can adjust the allocation strategy based on actual needs. For example, for highly consumable or expiration-sensitive items, a higher allocation priority may be required, so the value of ψ can be appropriately increased.

[0160] In some embodiments, the system of the present invention may further include a near expiration date warning module, which is configured to display warning information in different colors according to the remaining expiration date of the medical item, wherein:

[0161] When it is determined that the remaining validity period of the medical item is within one month, a red warning message is displayed;

[0162] When it is determined that the remaining validity period of the medical item is within three months, an orange warning message will be displayed;

[0163] When it is determined that the remaining validity period of the medical item is within six months, a yellow warning prompt message is displayed.

[0164] It can be understood that red, orange and yellow, arranged in descending order according to the degree of color eye-catchingness, can represent the severity of the remaining validity period in turn. The shorter the remaining validity period, the higher and more serious the corresponding warning level.

[0165] In some embodiments, the system of the present invention may further include an item information update module for:

[0166] Obtaining the item consumption record of the medical items by scanning the code on a mobile PDA;

[0167] The inventory information of the medical supplies is automatically updated according to the consumption records of the medical supplies.

[0168] Mobile PDAs (Personal Digital Assistants) are often equipped with barcode scanning capabilities. Each medical item has a unique barcode or QR code. Scanning this barcode with a PDA can quickly and accurately obtain relevant information about the item, such as its name, specifications, batch number, and expiration date.

[0169] When medical staff use medical items in clinical settings, they first scan the item's barcode with a PDA. The system automatically identifies the item and records the consumption. After scanning, the item's information is immediately transmitted to the management system, including the item's name, inventory number, production batch, expiration date, and other information. Information such as the time of consumption, the department using the item, and the operator is also recorded in the system. Based on the scan results, the system generates a real-time consumption record for the item, recording information such as the quantity used, the time it was shipped out, and the location of use. This data is used for subsequent inventory updates and analysis.

[0170] By scanning barcodes with a PDA, item consumption records reflect inventory usage in real time, avoiding delays or omissions caused by traditional manual record keeping. Each item's barcode is unique, ensuring accurate transmission of item information, eliminating the potential for manual record keeping errors, and improving inventory management accuracy. The system records each item's consumption information, including operator, location, and time of use, facilitating future traceability and statistical analysis of item usage.

[0171] In some embodiments, when an item has recorded its consumption behavior by scanning a code, the system will immediately adjust the inventory quantity of the corresponding item based on the consumption record. For example, if the original inventory of an item is 100 pieces and 5 pieces are used, the system will automatically update the inventory quantity of the item to 95 pieces. Medical items are usually distributed in different inventory levels (such as primary, secondary, and tertiary warehouses). Each item consumption record will accurately reflect the inventory changes of the item at the corresponding level. For example, if an item is consumed in a primary warehouse (treatment vehicle), the system will automatically update the inventory quantity of the primary warehouse. If an item is shipped from a warehouse (for example, transferred from a third-level warehouse to a primary warehouse), after recording the outbound information by scanning the code, the system will synchronously update the inventory data of the two warehouses to ensure that the circulation of the item is tracked globally.

[0172] After an item is shipped out or consumed, the system obtains the consumption record of the item, including the shipment quantity, shipping warehouse, using department and other information. The system automatically calculates the remaining inventory: Based on the consumption quantity of the item in the warehouse, the system automatically reduces the inventory of the corresponding warehouse. Expiration date management: When the system updates the inventory, it will also track the expiration date of the item. If a batch of items is about to expire, the system will trigger an expiration date warning to remind relevant personnel to give priority to the use of the item and reduce expiration waste. Adjustment of upper and lower limits of inventory: Based on the real-time changes in inventory, the system dynamically monitors whether the inventory of the item is lower than the lower limit or higher than the upper limit of inventory. If it is lower than the lower limit, a replenishment reminder will be issued. If it is higher than the upper limit, a prompt will be issued to reduce purchases.

[0173] Automated inventory updates eliminate the tedious steps of manual inventory adjustments, ensuring the real-time and accuracy of inventory information and significantly improving material management efficiency. The system's real-time inventory updates provide complete inventory visibility, allowing managers to monitor inventory status across warehouses and avoid overstocking or shortages. Based on real-time inventory data, the system can further generate replenishment suggestions, item allocation recommendations, and inventory reports, helping managers make more informed material procurement and scheduling decisions.

[0174] This invention uses a mobile PDA to scan a QR code to obtain consumption records of medical supplies and automatically updates inventory information based on these records, enabling real-time updates and automated management of inventory information. This approach not only improves the efficiency and accuracy of item usage and inventory updates, but also provides a data foundation for intelligent management functions such as dynamic inventory adjustments, expiration date management, and item allocation, ensuring more efficient and reliable use and management of medical supplies, and avoiding waste and shortages.

[0175] In some embodiments, the first management module 105 can be used to order and collect the medical supplies according to the collection strategy.

[0176] In some embodiments, when inventory falls below the system-set lower limit (LL), the system automatically issues a restocking reminder and calculates a reasonable order quantity based on an order quantity formula. If inventory approaches the upper limit (UL), the system reduces or suspends orders to avoid backlogs. Once the system determines that an order is needed, the relevant department can issue a purchase order directly to the supplier based on the system-generated ordering plan, ensuring timely delivery and timely replenishment of inventory.

[0177] In some embodiments, when medical staff collect items, they can scan a code with a PDA device to retrieve the item from the warehouse, record it in real time in the system, and automatically update inventory information. The system will automatically adjust inventory and allocate it based on actual usage.

[0178] Through the collection strategy of the present invention, the system can automatically evaluate the usage, inventory status and expiration date of the items, dynamically adjust the ordering and collection process, ensure the rational flow of items, inventory safety and expiration date management, and ultimately achieve efficient medical supply chain management.

[0179] In some embodiments, the second management module 106 can be used to allocate the medical supplies according to the allocation strategy.

[0180] In some embodiments, the allocation operation may mainly include the following scenarios: allocation from the tertiary warehouse to the primary warehouse and the secondary warehouse, allocation based on validity period priority, and allocation based on usage needs. In a specific implementation, the items in the primary warehouse (such as the ward treatment cart) are consumed quickly and have a high turnover rate because they are directly for clinical use. If the system detects that the inventory level in the primary warehouse is lower than the lower limit (LL), automatic allocation is triggered. The system calculates the priority of the item in the tertiary warehouse based on the inventory situation in the tertiary warehouse (long-term reserve) through the allocation priority formula. If the priority is high, a certain number of items will be allocated from the tertiary warehouse to the primary or secondary warehouse. After allocation, the system will update the inventory information of each warehouse, and adjust the inventory upper limit (UL) and lower limit (LL) values ​​to ensure the inventory balance of each warehouse.

[0181] The system can sort items in different warehouses based on their expiration date turnover rate (ECR), prioritizing those items that are about to expire or have a high turnover rate. For example, if an item in a tertiary warehouse is about to expire, the system will prioritize its allocation to a primary or secondary warehouse to ensure that it is used first in clinical practice and avoids expiration. In this case, the expiration date turnover rate (ECR) in the allocation priority formula has a greater impact on allocation decisions. For warehouses with lower turnover rates or larger inventory levels, the system will prioritize the removal of items to reduce inventory backlogs.

[0182] The system can predict the demand for specific items across different departments. For example, the emergency department may have a high demand for emergency medications. Based on this prediction, the system prioritizes the allocation of these items from the tertiary warehouse to the emergency department's secondary or primary warehouse. Allocation priorities are calculated based on warehouse inventory levels and expiration date management to ensure that high-demand items are prioritized and clinical needs are met.

[0183] Through the above methods, the system can monitor the inventory changes of each warehouse in real time and adjust the allocation strategy according to the inventory status of the warehouse. For example, if the inventory of a warehouse is about to fall below the lower limit, the system will allocate items from the upper warehouse in advance to replenish the inventory. When the expiration date of a batch of items is nearing the end, the system will prioritize allocating these items to warehouses with higher usage frequency to ensure that they are used first and reduce the risk of expiration. The adjustment coefficient ψ in the allocation priority formula can be adjusted according to the actual needs of the hospital. For example, for some items that are of high importance and urgently needed, the system can appropriately increase the value of ψ to increase the allocation priority of these items.

[0184] By allocating items based on each warehouse's inventory levels and expiration dates, the system prioritizes items that are about to expire or have high turnover rates, reducing waste and ensuring that items are fully utilized. Allocation strategies can rationally balance inventory levels across warehouses at all levels, avoiding backlogs or shortages of items in certain warehouses. Furthermore, by dynamically adjusting inventory limits, the system can optimize item procurement and allocation, reducing unnecessary inventory usage. Allocation strategies operate automatically, requiring no human intervention, significantly improving the efficiency and accuracy of item allocation and reducing the burden of manual management. By predicting changes in demand across departments, the system can flexibly adjust item allocation strategies to ensure that clinical needs are met in a timely manner.

[0185] This invention intelligently controls the flow of items between warehouses by leveraging multiple factors, including allocation priority formulas, inventory monitoring, and expiration date management. This strategy optimizes inventory management, ensuring the proper allocation and use of items, reducing expiration dates and inventory backlogs, while also improving item utilization efficiency and the ability to respond to clinical needs.

[0186] In summary, the present invention can not only improve the hospital's medical supplies management level, but also effectively reduce the supply costs and ensure the timeliness of supply and safety of use.

[0187] See also Figure 3 , Figure 3 Schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0188] Obtain item information of medical items to be managed, as well as warehouse information of warehouses at all levels;

[0189] Processing the item information through a machine learning model to predict the usage and expiration turnover rate of the medical item;

[0190] Determine a collection strategy for the medical supplies based on the usage and expiration turnover rate of the medical supplies;

[0191] Determining a deployment strategy for the medical supplies based on the inventory levels and first-effectiveness turnover rates of the medical supplies in the warehouses at each level;

[0192] Ordering and collecting the medical supplies according to the collection strategy;

[0193] The medical supplies are dispensed according to the dispensing strategy.

[0194] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0195] Those skilled in the art will appreciate that embodiments of the present invention may provide a system or computer program product. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware.

Claims

1. A medical product expiration date management system based on machine learning, characterized in that: The system comprises: A data acquisition module is used to obtain the item information of the medical items to be managed and the warehouse information of warehouses at various levels; The first computing module is configured to process the item information through a machine learning model to predict the usage and expiration turnover rate of the medical item, and is specifically configured to: obtain the current inventory of the medical item; obtain the monthly average usage, quarterly average usage, and expiration date of the medical item; perform weighted processing on the current inventory of the medical item to obtain a first processing result, and perform weighted sum processing on the monthly average usage, quarterly average usage, and expiration date of the medical item to obtain a second processing result; and determine the expiration turnover rate of the medical item based on the first processing result and the second processing result, wherein the expiration turnover rate of the medical item is expressed as: Where ECR is the expiration turnover rate, I is the current inventory, MU is the monthly average usage, SU is the quarterly average usage, YU is the annual average usage, EP is the expiration date, α, β, γ, and δ are the first, second, third, and fourth weights, respectively. A first strategy module is configured to determine a collection strategy for the medical supplies based on the usage and expiration turnover rate of the medical supplies; The second strategy module is used to determine the allocation strategy for the medical items based on the inventory and first expiration turnover rate of the medical items in the warehouses of each level, where the warehouses of each level include a first-level warehouse, a second-level warehouse, and a third-level warehouse, and is specifically used to: obtain the first inventory of the medical items in the first-level warehouse, the second inventory in the second-level warehouse, and the third inventory in the third-level warehouse; obtain the first expiration turnover rate of the medical items in the first-level warehouse, the second expiration turnover rate in the second-level warehouse, and the third expiration turnover rate in the third-level warehouse; and determine the allocation priority of the medical items in the allocation strategy based on the first expiration turnover rate, the second expiration turnover rate, and the third expiration turnover rate, as well as the first inventory, the second inventory, and the third inventory, where the allocation priority of the medical items is expressed as: Where TP is the allocation priority, I1, I2, and I3 are the first, second, and third inventory levels, respectively; ECR1, ECR2, and ECR3 are the first, second, and third validity period turnover rates, respectively; and ψ is the fifth adjustment coefficient. A first management module is used to order and collect the medical supplies according to the collection strategy; The second management module is used to allocate the medical supplies according to the allocation strategy.

2. The medical product expiration date management system based on machine learning according to claim 1, characterized in that: The system also includes an inventory upper and lower limit module for: Get the value of the current month; The upper and lower inventory limits of the medical supplies are determined based on the values ​​of the current month, as well as the monthly average usage and quarterly average usage of the medical supplies.

3. The medical product expiration date management system based on machine learning according to claim 2, characterized in that: The inventory upper and lower limit module is also used to: When the inventory of a first medical item exceeds the quarterly average usage of the first medical item, and the number of first medical items with a remaining validity period of less than 6 months accounts for more than 30% of the inventory of the first medical item, an inventory limit alarm is issued for the first medical item; When the inventory quantity of a second medical item is less than the base number of the second medical item, an inventory lower limit alarm is issued for the second medical item; the base number of the second medical item is determined based on the average monthly usage, average quarterly usage and average annual usage of the second medical item.

4. The medical product expiration date management system based on machine learning according to claim 3, characterized in that: The warehouses at each level include: The third-level warehouse is set up in the ward and is used to realize the delivery and storage of goods in the entire ward; The secondary warehouse is located in the ward treatment room. Items entering the secondary warehouse come from the tertiary warehouse, and items leaving the warehouse flow to the primary warehouse or are consumed. The first-level warehouse is set up in the ward treatment vehicle and nursing vehicle. The incoming items of the first-level warehouse come from the second-level warehouse, and the outgoing items are used for consumption.

5. The medical product expiration date management system based on machine learning according to claim 4 is characterized in that: The first strategy module is further specifically configured to: Obtaining a first difference between an upper inventory limit and a current inventory level of the medical item; The order quantity of the medical supplies in the delivery strategy is determined based on the values ​​of the current month, the first difference value, the monthly average usage and the expiration date turnover rate of the medical supplies.

6. The medical product expiration date management system based on machine learning according to claim 5, characterized in that: The system also includes a near expiration warning module, which is used to display warning prompt information in different colors according to the remaining expiration date of the medical item, wherein: When it is determined that the remaining validity period of the medical item is within one month, a red warning message is displayed; When it is determined that the remaining validity period of the medical item is within three months, an orange warning message will be displayed; When it is determined that the remaining validity period of the medical item is within six months, a yellow warning prompt message is displayed.

7. The medical item expiration date management system based on machine learning according to any one of claims 1 to 6, characterized in that: The system further includes an item information updating module, configured to: Obtaining the item consumption record of the medical items by scanning the code on a mobile PDA; The inventory information of the medical supplies is automatically updated according to the consumption records of the medical supplies.

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