Medical consumable whole-process traceability and loss control method and system thereof

Abstract

The application discloses a medical consumable whole-process traceability and loss control method and system, relates to the technical field of intelligent medical informatization and supply chain control, and through a cargo identification system arranged in warehouses of various hospital areas, inherent attributes are collected with UDI as a core identifier, and dynamic flow data including temperature and humidity are recorded; a whole life cycle flow chain is constructed by fusing various hospital area flow records with UDI as a primary key; a remaining effective life index is obtained by using an expiration date dynamic attenuation model and combining temperature and humidity data to convert and correct a benchmark effective period; when the index is lower than a warning threshold, a consumable digestion capacity index is calculated based on current total effective inventory of each candidate hospital area and daily average consumption speed in a preset historical period, so that an optimal allocation destination is locked to control allocation and flow. The application breaks the information island of hospital areas, realizes intelligent scheduling based on real environment attenuation and dynamic supply and demand, and significantly reduces the expiration and scrap rate of consumables.

Description

Technical Field

[0001] This invention relates to the field of smart healthcare information technology and supply chain management, specifically to a method and system for full-process traceability and loss control of medical consumables. Background Technology

[0002] With the deepening of modern medical system reform, large medical groups or closely integrated urban medical groups are gradually becoming the main form of regional medical services. In such multi-hospital collaborative operation scenarios, high-value and medium-value medical consumables often need to be frequently transferred and shared between different hospitals or branches. The core purpose is to balance the inventory levels between hospitals and avoid the predicament of one hospital having stockpiled and expired inventory while another hospital faces stockouts and has to suspend surgeries.

[0003] However, the existing cross-hospital medical consumables logistics and supply chain management system has the following insurmountable technical shortcomings:

[0004] First, the independent systems across multiple hospital campuses easily create "information silos" and blind spots in expiration date management. Currently, each hospital campus often purchases and deploys its own independent consumable management system. When consumables are transferred from Campus A to Campus B, the system only performs a simple "outbound" processing in Campus A and an "inbound" processing in Campus B. Consumables lack a unified and continuous data view of "total inventory" and "total remaining shelf life" from the perspective of the entire group, detached from individual hospital campuses. Especially for consumables nearing their expiration date, frequent inter-regional transfers and multiple handovers can easily lead to them being forgotten in a corner of the warehouse due to information gaps and synchronization delays, ultimately resulting in expiration and disposal, causing a huge waste of medical resources.

[0005] Second, existing systems rely solely on the static expiration date at the factory, neglecting the accelerated degradation effect of the physical environment on the actual lifespan of consumables. Many high-value consumables are extremely sensitive to the temperature and humidity of the environment during storage and transportation. Existing consumable management systems use a rigid "calendar countdown" logic for expiration date warnings. This static management model cannot detect and quantify the "hidden deterioration" suffered by consumables during long-distance transfers between hospital campuses or under extreme conditions such as air conditioning malfunctions in a hospital's warehouse. This not only renders the system's warnings ineffective but may also lead to consumables with altered physicochemical properties entering clinical settings illegally, causing serious medical quality and safety incidents.

[0006] Third, existing inter-hospital allocation decisions heavily rely on manual experience or simple inventory warning lines, lacking a scientific quantitative matching mechanism. When a hospital discovers that consumables are nearing their expiration date and initiates an allocation, managers often blindly transfer them to other hospitals that appear to be short of stock. However, due to the failure to accurately calculate the "true consumption capacity" of the target hospital through algorithms, near-expiration consumables are frequently mistakenly allocated to hospitals with extremely slow daily consumption. This results in the consumables inevitably facing a second expiration after undergoing expensive secondary logistics transportation. This not only fails to save the consumables but also increases ineffective allocation logistics costs and human resource management costs.

[0007] Fourth, cross-campus transfers involve complex financial settlements and ownership transfers, and traditional system handover logs are easily tampered with. In multi-campus logistics chains, once consumables are found to be damaged or deteriorated, the lack of an immutable electronic handover and environmental traceability evidence chain makes it easy for each campus and logistics department to shirk responsibility. Summary of the Invention

[0008] The purpose of this invention is to provide a method and system for full-process traceability and loss control of medical consumables to solve the above-mentioned problems.

[0009] To achieve the above objectives, the present invention provides the following technical solution: a method for full-process traceability and loss control of medical consumables, comprising the following steps:

[0010] S1. By deploying a cargo identification system in warehouses across multiple hospital campuses, using the Unique Device Identifier (UDI) as the core identifier, the system collects the inherent attribute data of medical consumables in each hospital campus warehouse and records the dynamic circulation data of the medical consumables during the flow between and within hospital campuses; wherein, the dynamic circulation data includes temperature and humidity data of the storage environment.

[0011] S2. Based on the UDI as the unique primary key, the fragmented circulation records of each hospital warehouse are merged and integrated to construct the full life cycle circulation chain of the medical consumables;

[0012] S3. Using a preset consumable validity period dynamic decay model, the baseline validity period in the inherent attribute data is converted and corrected in combination with the temperature and humidity data of the storage environment, and the remaining effective life index of the medical consumable is calculated.

[0013] S4. When the remaining effective life index is lower than the preset cross-hospital warning threshold, an early warning is triggered, and the optimal allocation destination is calculated based on the inventory and consumption rate of the medical consumables in the current hospital warehouse and other hospital warehouses.

[0014] S5. Generate a list of allocation suggestions based on the optimal allocation destination to control the allocation and flow of medical consumables between warehouses in various hospital areas.

[0015] Furthermore, the goods identification system includes a medical consumables SPD system deployed in warehouses of various hospital campuses and a unified UDI barcode scanning node; the inherent attribute data includes production batch number, expiration date and sterilization batch; the dynamic circulation data also includes warehousing time, outbound time, transfer time, outbound warehouse identifier and inbound warehouse identifier.

[0016] Furthermore, based on the temperature and humidity data of the storage environment, the baseline validity period is adjusted and adjusted to calculate the remaining effective life index of the medical consumables, specifically including:

[0017] Based on the characteristics of the medical consumables, determine the corresponding environmental sensitivity factors;

[0018] The ambient temperature and humidity of the hospital warehouse where the medical consumables are located are acquired in real time or periodically, and it is determined whether the ambient temperature and humidity exceed the preset standard temperature and humidity range.

[0019] When the temperature and humidity exceed the standard temperature and humidity range, the temperature and humidity accelerated decay coefficient is calculated using the environmental sensitivity factor. The natural lifespan of the medical consumables in non-standard temperature and humidity environments is weighted and accumulated to obtain the corrected consumed lifespan.

[0020] The remaining effective life index is calculated based on the difference between the baseline effective life and the corrected consumed life.

[0021] Furthermore, based on the current inventory and consumption rate of the medical consumables in the hospital's warehouse and other hospital warehouses, the optimal allocation destination is calculated, specifically including:

[0022] Obtain the current inventory of the same type of medical consumables in the warehouses of each candidate hospital and the average consumption rate within a preset historical period;

[0023] Based on the ratio of the average consumption rate to the current inventory level, calculate the consumables digestibility index of each candidate hospital warehouse;

[0024] The hospital warehouse with the highest digestibility index and the conditions for receiving the supplies is identified as the optimal allocation destination, and medical consumables nearing their expiration date are prioritized for allocation to the hospital warehouse with the fastest consumption rate.

[0025] Furthermore, the method also includes:

[0026] An emergency warning is triggered when the remaining effective life index of the medical consumable is lower than a preset emergency threshold.

[0027] Automatically generate a "priority use" electronic tag, and push the electronic tag and the warning information together to the hospital warehouse where the medical consumable is currently located and the terminals of relevant clinical departments for prominent display.

[0028] Furthermore, the method also includes:

[0029] By combining the remaining effective life index, physical distribution, and allocation status of all medical consumables in the warehouses of each hospital area, a heat map of the shelf life of medical consumables across warehouses in the entire hospital area is dynamically generated.

[0030] The heatmap of the effective lifespan is divided into different color gradients to display the distribution and allocation trajectory of medical consumables in different remaining effective lifespan ranges.

[0031] Furthermore, constructing the entire lifecycle circulation chain of the aforementioned medical consumables also includes:

[0032] The handover confirmation data, barcode timestamps, and environmental temperature and humidity logs for each cross-campus warehouse transfer are hash-encrypted to form an immutable traceability node, achieving full-process anti-tampering auditing.

[0033] A medical consumable end-to-end traceability and loss control system includes:

[0034] The cargo identification system is deployed in warehouses across multiple hospital campuses. It uses the Unique Device Identifier (UDI) of Medical Devices as the core identifier to collect the inherent attribute data of medical consumables in each hospital campus warehouse and record the dynamic flow data of the medical consumables during the flow between and within hospital campuses. The dynamic flow data includes the temperature and humidity data of the storage environment.

[0035] The circulation chain construction module is used to merge and integrate the fragmented circulation records of each hospital warehouse based on the UDI as the unique primary key, and construct the full life cycle circulation chain of the medical consumables.

[0036] The shelf-life decay assessment module is used to calculate the remaining effective life index of the medical consumables by using a preset consumables shelf-life dynamic decay model, based on the baseline shelf-life in the inherent attribute data and combined with the temperature and humidity data of the storage environment.

[0037] The early warning and allocation decision module is used to trigger an early warning when the remaining effective life index is lower than the preset cross-hospital warning threshold, and to calculate the optimal allocation destination based on the inventory and consumption rate of the medical consumables in the current hospital warehouse and other hospital warehouses.

[0038] The control and management module is used to generate a list of allocation suggestions based on the optimal allocation destination, so as to control the allocation and flow of medical consumables between warehouses in various hospital areas.

[0039] Compared with existing technologies, the medical consumables full-process traceability and loss control method and system provided by this invention have the following beneficial effects:

[0040] First, it achieves seamless data integration and unified management across a complex supply chain system spanning multiple hospital campuses. This application innovatively uses the National Unique Device Identifier (NDI) as a universal language and unique primary key across systems, seamlessly integrating fragmented data on inbound and outbound shipments and transfers scattered across heterogeneous SPD systems in various hospital campuses. This breaks down traditional information silos between hospital campuses, providing group managers with a complete, uninterrupted lifecycle view of all consumables, completely eliminating blind spots in the management of near-expiry supplies caused by information asymmetry.

[0041] Secondly, a dynamic degradation assessment model for medical consumables' shelf life, more closely aligned with real-world physical environments, has been constructed, significantly enhancing the defenses against medical quality and safety issues. This application abandons the traditional, rigid, static "calendar expiration date" management model and creatively introduces accelerated degradation variables based on environmental temperature and humidity. The system can deduct from the baseline shelf life of consumables in real time based on abnormal environmental data captured by IoT sensors, accurately calculating the true "remaining effective life index." This technology effectively prevents substandard consumables that have "hidden expired" due to environmental anomalies from entering clinical settings, curbing the risk of medical accidents at the source.

[0042] Third, an intelligent allocation algorithm based on the consumables digestibility index was proposed, achieving optimal drip irrigation of inventory transfer and significantly reducing the consumables scrapping and loss rate. In the allocation decision-making process, this application no longer relies on manual experience or a single inventory base, but instead uses a formula to accurately characterize the real-time digestibility potential of each hospital area. By forcibly guiding near-expiry materials to the optimal destination of "empty storage capacity and high consumption," the probability of consumables being consumed within their expiration date is maximized, eliminating "secondary expiration" and ineffective logistics costs caused by blind allocation, and in turn optimizing the group's procurement plan, reducing duplicate capital occupation.

[0043] Fourth, a tiered interception and critical inventory penetration intervention mechanism has been established, improving end-of-pipe turnover efficiency. By setting emergency thresholds and automatically generating "priority use" electronic tags, the system can intelligently block ineffective cross-regional transfers of critically endangered consumables, instead sending system instructions directly to the final clinical department in the current hospital area for strong reminders, achieving rapid on-site salvage consumption of endangered materials with minimal time and logistical costs.

[0044] Fifth, it provides a multi-dimensional, dimensionality-reduced expiration date heatmap visualization tool, greatly improving the efficiency of macro-level decision-making. The system maps complex expiration date indices and geographical distributions into intuitive colors and trajectories, enabling group managers to locate areas of severe inventory backlog and high-risk obsolescence areas in seconds, providing an efficient command platform for macro-control and resource rebalancing of the supply chain.

[0045] Sixth, a hash encryption anti-tampering mechanism was introduced to ensure the credibility of inter-hospital transfer settlements. By using chain-hash encryption on the scanning timestamp, environmental temperature and humidity, and handover actions, a highly legally valid electronic evidence chain was formed, eliminating the possibility of unilateral tampering with the handover logs. This ensures clear and unambiguous ownership and responsibility transfers between hospitals, providing a solid technical guarantee for internal auditing and compliance supervision within the medical group. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0047] Figure 1 This is a schematic diagram of the overall method flow of the present invention;

[0048] Figure 2 This is a system module architecture diagram of the present invention. Detailed Implementation

[0049] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0050] Please see Figure 1 , 2 The method for full-process traceability and loss control of medical consumables includes the following steps:

[0051] S1. By deploying a cargo identification system in warehouses across multiple hospital campuses, using the Unique Device Identifier (UDI) as the core identifier, the system collects the inherent attribute data of medical consumables in each hospital campus warehouse and records the dynamic flow data of medical consumables during the flow between and within hospital campuses; among which, the dynamic flow data includes the temperature and humidity data of the storage environment.

[0052] S2. Based on UDI as the unique primary key, the fragmented circulation records of warehouses in various hospital areas are merged and integrated to build a full life cycle circulation chain for medical consumables;

[0053] S3. Using a preset dynamic decay model for consumable validity period, the baseline validity period is adjusted based on the baseline validity period in the inherent attribute data and the temperature and humidity data of the storage environment, and the remaining effective life index of medical consumables is calculated.

[0054] S4. When the remaining effective life index is lower than the preset cross-hospital warning threshold, an early warning is triggered, and the optimal allocation destination is calculated based on the inventory and consumption rate of the medical consumables in the current hospital warehouse and other hospital warehouses.

[0055] S5. Generate a list of allocation suggestions based on the optimal allocation destination to control the allocation and flow of medical consumables between warehouses in various hospital areas.

[0056] Specifically, the goods identification system consists of barcode scanning terminals and IoT gateways distributed at the entry and exit points of each campus; UDI is an international standard code that includes product identification and production identification. The system establishes a data table in the underlying database with the UDI string as the primary key, and concatenates and links time, space, and environmental data fragments uploaded independently by different campuses. The dynamic decay model for consumable shelf life is an algorithm function with multivariate inputs, breaking the limitations of traditional management based on static expiration dates. The calculation of the optimal allocation destination is achieved by comparing the real-time inventory and historical average daily consumption of each campus, using a heuristic algorithm to identify the warehouse node with the strongest digestion capacity.

[0057] This method employs a system architecture of distributed sensing and centralized computing. In the physical flow stage, when medical consumables pass through any hospital's physical checkpoints, the underlying hardware triggers a scanning action, sending a data packet carrying a UDI, timestamp, and spatial coordinates to the central data platform via an API interface. The data platform's streaming data processing engine intercepts these asynchronously arriving data packets, using the uniqueness of the UDI to concatenate them into a directed acyclic graph with a time series. Simultaneously, a background daemon process monitors the time-series data from environmental sensors in each warehouse in real time. Once environmental parameters fluctuate, the central processor incorporates the fluctuation duration and amplitude into a dynamic decay model, deducting the theoretical lifespan of the consumables in real time through integral calculations, and updating the "remaining effective lifespan index" field in the database. When this field value reaches a threshold set by the program, the system's rule engine is activated, automatically initiating concurrent queries to the inventory subsystems of each hospital, extracting the current inventory and consumption rate, executing a sorting algorithm to select the optimal allocation path, and finally issuing it to the logistics scheduling bus in the form of a system command stream.

[0058] It breaks down information silos between hospitals and realizes a unified expiration date view for consumables across the entire hospital. It upgrades the original passive management based on static dates to optimal scheduling based on real-world environmental degradation and dynamic supply and demand, significantly reducing expired waste.

[0059] The goods identification system includes a medical consumables SPD system deployed in warehouses of various hospital campuses and a unified UDI barcode scanning node; inherent attribute data includes production batch number, expiration date and sterilization batch; dynamic circulation data also includes warehousing time, outbound time, transfer time, outbound warehouse identifier and inbound warehouse identifier.

[0060] Specifically, the medical consumables SPD system is responsible for the refined instruction management of in-hospital material supply, processing, and distribution; the unified UDI barcode scanning node refers to the forced bypass access of a set of hardware and software acquisition nodes with a unified parsing protocol at the physical gateways of the existing heterogeneous systems in various hospital areas for inbound and outbound operations. Inherent attribute data is structured and extracted and written to the main data center when consumables first enter the medical group's central warehouse for acceptance; dynamic flow data is the record of status changes generated with each physical movement of consumables across regions or departments.

[0061] The data acquisition process relies on an event-driven mechanism. When an operator scans the barcodes of consumables at a unified UDI scanning node in any hospital area, the decoding chip of the scanning device converts the optical signal into a digital string. After the edge computing module of the SPD system captures this string, it immediately packages the current operation type, the current system time, and the MAC address or logical identifier of the current site into a standard JSON format message. Subsequently, this message is pushed to the message middleware through the intranet security link, thereby ensuring that the physical movement trajectory of all materials can be transformed into a high-precision spatiotemporal log of the digital world without any omissions, for upper-layer applications to subscribe to and consume.

[0062] This ensures absolute consistency in the granularity and format of data collection across the entire group, eliminating data gaps and ambiguities at the source, and providing a high-fidelity, standardized underlying data source for building a seamless, full-lifecycle workflow chain.

[0063] The baseline validity period is adjusted based on the temperature and humidity data of the storage environment to calculate the remaining effective life index of medical consumables, specifically including:

[0064] Based on the characteristics of medical consumables, determine the corresponding environmental sensitivity factors;

[0065] The ambient temperature and humidity of the hospital warehouse where medical consumables are located are obtained in real time or periodically to determine whether the ambient temperature and humidity exceed the preset standard temperature and humidity range.

[0066] When the temperature and humidity exceed the standard range, the temperature and humidity accelerated decay coefficient is calculated using the environmental sensitivity factor. The natural lifespan of medical consumables in non-standard temperature and humidity environments is weighted and accumulated to obtain the corrected consumed lifespan.

[0067] The remaining effective life index is calculated based on the difference between the baseline effective life and the revised consumed life.

[0068] Among them, the environmental sensitivity factor is a quantitative constant pre-calibrated based on the physicochemical parameters of the consumables at the factory or historical stability test data. The system obtains category information by parsing the UDI and retrieves the corresponding environmental sensitivity factor.

[0069] Temperature and humidity accelerate the decay coefficient The single expression is:

[0070]

[0071] Environmental sensitivity factor Actual ambient temperature, Standard storage temperature upper limit, Actual ambient relative humidity, Standard storage humidity limit;

[0072] Specifically, the revised formula for calculating spent lifetime is as follows:

[0073]

[0074] in, This is the corrected lifespan. This refers to the natural lifespan of medical consumables under non-standard temperature and humidity conditions. Temperature and humidity accelerate the degradation factor. The formula for calculating the remaining effective lifespan index is:

[0075]

[0076] in, The remaining effective lifespan index; This is the baseline validity period in the inherent attribute data of consumables.

[0077] A time-series state machine runs in the background of the system. Under normal circumstances, the lifespan of consumables deteriorates naturally over time. When the data reported by the IoT temperature and humidity probe via the MQTT protocol exceeds the upper and lower limits of the standard thresholds defined in the consumable database, the state machine enters an "abnormal accelerated decay" mode. The algorithm engine extracts the environmental sensitivity factor unique to the consumable and, combined with the excessive temperature and humidity difference, calculates the current acceleration rate in real time. The system uses calculus or discrete-time accumulation to calculate the time under harsh conditions. Multiply by a coefficient The equivalent lifetime of actual losses during this stage is calculated. Once the environment returns to normal, The value drops back to 1. Finally, the actual usable lifespan is obtained by subtracting the accumulated equivalent lifespan from the total factory lifespan.

[0078] A dynamic expiration model that closely resembles the physical world has been constructed, completely filling the blind spots of static date management, accurately identifying "hidden expired" consumables caused by environmental anomalies, preventing deteriorated consumables from entering clinical settings, and significantly improving medical quality and safety.

[0079] Based on the current inventory and consumption rate of medical consumables in the hospital's warehouse and other hospital warehouses, calculate the optimal allocation destination, specifically including:

[0080] Obtain the current inventory of the same type of medical consumables in the warehouses of each candidate hospital and the average consumption rate within a preset historical period;

[0081] Based on the ratio of average consumption rate to current inventory level, calculate the consumables digestibility index of each candidate hospital warehouse;

[0082] The hospital warehouse with the highest digestion capacity index and the conditions for receiving transfers is identified as the optimal transfer destination, and medical consumables nearing their expiration date are prioritized for transfer to the hospital warehouse with the fastest consumption rate.

[0083] Specifically, the system embeds a resource scheduling evaluation algorithm, defining the formula for calculating the digestion capacity index as follows:

[0084]

[0085] in, This refers to the index of consumables consumption capacity. The average daily consumption rate of the candidate hospital's warehouse within a preset historical period; This represents the current effective inventory of the same type of consumables in the candidate hospital's warehouse. A larger value indicates that the hospital area has "empty storage capacity and high consumption," meaning a greater potential for consuming near-expiry supplies. Considering that in actual operations, when a candidate hospital area runs out of this type of consumable inventory, it can cause calculation errors when dividing by zero in the algorithm, a minimal smoothing constant is introduced in the program implementation. To prevent errors, the formula is corrected as follows:

[0086]

[0087] Or set boundary bounce rules: when =0 and When >0, directly assign The value is the maximum value preset by the system.

[0088] Essentially, this step is a multi-objective optimization process based on heuristic rules. When the early warning module issues a transfer request, the scheduling engine initiates a global snapshot and instantly locks down the current effective inventory of consumables of the same specification across all hospital campuses via SQL aggregation queries. and the average daily consumption rate within the preset historical period. The microservice computing cluster computes its own computational power for each legitimate receiving node within the system. The value. Then, the engine calculates... The value array is sorted in descending order. After sorting, the system checks the constraints. If the conditions are met, the address of the first-ranked node is assigned to the "optimal allocation destination" variable; if constraints are present, the pointer moves down to evaluate the next best node until a match is found. Finally, the result is output to the control management module to generate a structured allocation order.

[0089] It enables data-driven intelligent allocation decisions, transforming the previously blind inventory transfer into precise allocation guided by "maximizing the probability of consumption," thus avoiding ineffective logistics costs and the occupation of duplicate procurement funds.

[0090] The method also includes:

[0091] An emergency warning is triggered when the remaining effective life index of medical consumables falls below a preset emergency threshold.

[0092] Automatically generate "priority use" electronic tags and push the electronic tags and early warning information to the hospital warehouse where the medical consumables are currently located and the terminals of relevant clinical departments for prominent display.

[0093] Specifically, the system sets tiered interception thresholds in its expiration date monitoring system, including the aforementioned "cross-hospital area early warning threshold" and the more stringent "emergency threshold" introduced in this step. The "priority use" electronic tag is a system control signal carrying a high-priority flag, which is interpreted on the front-end user interface as a red highlight, pop-up window, or flashing visual effect.

[0094] At the system's underlying level, this mechanism manifests as a high-priority interrupt response and message penetration technology. When the attenuation assessment module performs batch polling calculations, once it detects that the lifespan index of a consumable entity has fallen below the emergency threshold, it immediately exits the regular inter-hospital allocation calculation function branch and activates the emergency intervention service. The system no longer queries the status of other hospitals; instead, it directly pushes the consumable's UDI code and alarm level to the warehouse management dashboard where it is currently located and to the doctor's workstation screen in the corresponding department via a WebSocket long connection or RPC protocol. Logically, this forcibly places the batch of consumables at the head of the outbound queue, achieving mandatory overriding of the first-in, first-out (FIFO) mechanism.

[0095] It has achieved refined, hierarchical, and closed-loop management of the expiration dates of consumables. By blocking the ineffective cross-regional transfer of extremely near-expiration materials, the intervention actions directly penetrate and focus on the end-stage clinical use scenarios, achieving rapid turnover of critical inventory with minimal time cost.

[0096] The method also includes:

[0097] By combining the remaining effective life index, physical distribution, and allocation status of all medical consumables in the warehouses of each hospital area, a heat map of the shelf life of medical consumables across warehouses in the entire hospital area is dynamically generated.

[0098] Among them, the shelf life heatmap displays the distribution and allocation trajectory of medical consumables in different remaining effective life intervals according to different color gradients.

[0099] Specifically, the system front-end integrates a data visualization component library and a geographic information system engine or a self-developed two-dimensional topological map canvas of the campus. Discrete warehouse nodes are mapped to fixed coordinate points on the canvas, and massive expiration date indices are mapped to RGB color value parameters in a preset color palette.

[0100] The system employs data dimensionality reduction and multi-layer rendering techniques. The backend big data computing engine periodically executes batch processing tasks, performing multi-dimensional aggregation and dimensionality reduction on millions of existing consumable records according to dimensions such as hospital coordinate system, material category, and remaining expiration date, outputting a compact statistical feature matrix. Upon receiving this matrix, the frontend rendering engine uses Layer 1 to draw the hospital's geographical layout; Layer 2, based on the aggregated data, uses a Gaussian blur algorithm to generate halo color blocks with specific colors and radiation radii at corresponding coordinate points; Layer 3 reads recent transfer records and uses Bézier curves or dynamic particle flows with arrows to connect the sending and receiving locations. These three layers are superimposed and periodically refreshed and redrawn, presenting a dynamic interactive view on the administrator's large screen.

[0101] It provides the group's procurement center and materials management department with a holistic, visualized command platform, enabling managers to sift through complex data and pinpoint areas of severe inventory backlog and high-risk expired inventory in seconds, greatly improving the decision-making efficiency of the group's overall materials management.

[0102] When constructing the entire lifecycle circulation chain for medical consumables, it also includes:

[0103] The handover confirmation data, barcode timestamps, and environmental temperature and humidity logs for each cross-campus warehouse transfer are hash-encrypted to form an immutable traceability node, achieving full-process anti-tampering auditing.

[0104] Specifically, the handover confirmation data includes the employee ID, electronic signature, and acceptance status conclusion entered by the handover party and the receiving party on their mobile terminals. Hash encryption refers to the technique of converting plaintext input of arbitrary length into a fixed-length ciphertext string using a one-way hash algorithm.

[0105] The system incorporates a cryptographic anti-tampering mechanism. At the moment of each inter-campus handover and the click of "confirm," the system backend collects the five-tuple information of the current action as the plaintext payload. The cryptographic service module uses the SHA-256 algorithm to perform a joint operation on this payload along with the hash value of the previous transfer node, generating a unique digital digest belonging to the current transfer action. Subsequently, the system writes the original plaintext along with the generated digest into the audit table of the underlying distributed database. During subsequent traceability verification, the verification program only needs to re-hash the plaintext and compare it with the digest record. Any minor alteration to historical temperature and humidity, handover time, or signature data will cause a cascading change in the newly calculated hash value, immediately exposing the forgery during the comparison.

[0106] By establishing a robust data trust barrier, the high credibility and exclusivity of logs transferred and handed over across hospital campuses are ensured. This eliminates the possibility of post-transfer data tampering, clearly defines responsibilities, and provides a legally binding electronic chain of evidence for internal compliance audits within the medical group and for responding to external medical device regulatory agencies.

[0107] A medical consumable end-to-end traceability and loss control system includes:

[0108] The cargo identification system is deployed in warehouses across multiple hospital campuses. It uses the Unique Device Identifier (UDI) of Medical Devices as the core identifier to collect the inherent attribute data of medical consumables in each hospital campus warehouse and record the dynamic flow data of medical consumables during the flow between and within hospital campuses. The dynamic flow data includes the temperature and humidity data of the storage environment.

[0109] The circulation chain construction module is used to merge and integrate fragmented circulation records from warehouses in various hospital areas based on UDI as the unique primary key, and to build a full life cycle circulation chain for medical consumables.

[0110] The shelf-life assessment module is used to calculate the remaining effective life index of medical consumables by using a preset dynamic shelf-life decay model of consumables, based on the baseline shelf-life in the inherent attribute data and combined with the temperature and humidity data of the storage environment.

[0111] The early warning and allocation decision module is used to trigger an early warning when the remaining effective life index is lower than the preset cross-hospital warning threshold, and to calculate the optimal allocation destination based on the inventory and consumption rate of the medical consumables in the current hospital warehouse and other hospital warehouses.

[0112] The control and management module is used to generate a list of allocation suggestions based on the optimal allocation destination, so as to control the allocation and flow of medical consumables between warehouses in various hospital areas.

[0113] Specifically, the system adopts a B / S architecture and is deployed on the medical group's private cloud, with each module developed in a decoupled manner following the microservice design concept.

[0114] The system's operation relies on a layered data pipeline interaction. The underlying cargo identification system continuously pushes data to the system message bus via a RESTful API; the data flow chain construction module consumes bus data through an ETL toolchain, performs primary key alignment and dead zone cleaning, and then writes the normalized data to a relational database. Subsequently, the expiration assessment module, running as a timed batch processing computing cluster, pulls the latest status data and performs floating-point multiplication and addition operations to calculate the expiration period. When out-of-limit data is identified, the early warning and allocation decision module is activated via internal calls to perform C-value calculations and a graph search algorithm to match the best recipient. Finally, the control and management module captures the decision output, renders it as a visual list, and sends control signals to the execution systems of specific hospital areas via interface protocols.

[0115] By constructing a loosely coupled, highly cohesive integrated system architecture, the complex theoretical model was smoothly implemented into engineering applications, significantly improving the system's fault tolerance and horizontal scalability, and ensuring the system stability and real-time response of large-scale, high-concurrency medical consumables data flow processing throughout the hospital.

[0116] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned method for full-process traceability and loss control of medical consumables.

[0117] Specifically, the computing device can be a high-performance rack server cluster, blade server, or an elastic computing instance configured based on a public / private cloud, deployed in a healthcare group's data center. The processor includes a central processing unit, a general-purpose graphics processing unit, or an application-specific integrated circuit (ASIC). The memory includes high-speed random access memory for runtime data exchange and a non-volatile memory array for persistent storage.

[0118] At the physical level, the processor of a computer device communicates with the cache and main memory at high frequency via the system front-side bus. After the operating system boots up, it loads the compiled machine code binary file of the "Tracing and Loss Control System" program, which resides on the solid-state drive, into the RAM space and allocates memory addresses and system threads for it. The processor core prefetches instructions from RAM one by one according to the program counter, places them in the instruction register for decoding, calls the arithmetic logic unit to perform Boolean or floating-point operations on variables such as environmental degradation coefficients and consumption rate ratios reported by each hospital area, and finally writes the generated allocation target addresses and other results back to memory or outputs them to peripheral devices through the network interface card, driving the entire business logic closed-loop flow in a continuous cycle.

[0119] It provides a solid physical computing foundation and a high-throughput I / O operating environment for the entire technical solution, ensuring that the dynamic calculation of consumable expiration dates and the optimization process of supply and demand matching across the entire hospital can respond quickly within a short latency of milliseconds to seconds, meeting the stringent requirements of medical business continuity.

[0120] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for full-process traceability and loss control of medical consumables.

[0121] In practical industrial implementations, it can be a USB flash drive or portable hard drive used for packaging and distributing installation packages, a read-only memory or flash memory chip used for burning firmware, or a virtual storage volume used for cloud image deployment. The storage medium's sectors compactly encapsulate a high-level language compiled instruction set that implements the steps of the aforementioned multi-campus UDI fusion, temperature and humidity attenuation integral, and intelligent queuing scheduling algorithm.

[0122] During the deployment and execution process, when a device with the storage medium is connected to the target computer's standard physical interface or mounted as a mirror volume in a virtualization environment, the target computer's underlying BIOS / UEFI driver recognizes the file system of the medium, and the operating system reads the executable files in the medium cluster. Under the control of the bus read signal issued by the processor, the level states of the magnetic head, laser beam, or transistor in the storage medium are converted into digital electrical signals, and the instruction stream carrying the wear control logic is completely transferred to the motherboard's dynamic memory, where it is interpreted and executed by the processor, thus completing the physical reproduction of system functions on a remote machine.

[0123] This approach enables the commercial encapsulation of the solution from an abstract algorithm to a concrete software product, significantly reducing the deployment threshold in different medical institution network environments. It facilitates software version iteration and upgrades, offline secure backup, and rapid large-scale promotion, while effectively protecting the integrity of the program code.

[0124] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for full-process traceability and loss control of medical consumables, characterized in that, Includes the following steps: S1. By deploying a cargo identification system in warehouses across multiple hospital campuses, using the Unique Device Identifier (UDI) as the core identifier, the system collects the inherent attribute data of medical consumables in each hospital campus warehouse and records the dynamic circulation data of the medical consumables during the flow between and within hospital campuses; wherein, the dynamic circulation data includes temperature and humidity data of the storage environment. S2. Based on the UDI as the unique primary key, the fragmented circulation records of each hospital warehouse are merged and integrated to construct the full life cycle circulation chain of the medical consumables; S3. Using a preset consumable validity period dynamic decay model, the baseline validity period in the inherent attribute data is converted and corrected in combination with the temperature and humidity data of the storage environment, and the remaining effective life index of the medical consumable is calculated. S4. When the remaining effective life index is lower than the preset cross-hospital warning threshold, an early warning is triggered, and the optimal allocation destination is calculated based on the inventory and consumption rate of the medical consumables in the current hospital warehouse and other hospital warehouses. S5. Generate a list of allocation suggestions based on the optimal allocation destination to control the allocation and flow of medical consumables between warehouses in various hospital areas.

2. The method for full-process traceability and loss control of medical consumables according to claim 1, characterized in that, The cargo identification system includes a medical consumables SPD system deployed in warehouses of various hospital campuses and a unified UDI barcode scanning node; the inherent attribute data includes production batch number, expiration date and sterilization batch; the dynamic circulation data also includes warehousing time, outbound time, transfer time, outbound warehouse identifier and inbound warehouse identifier.

3. The method for full-process traceability and loss control of medical consumables according to claim 1, characterized in that, The baseline validity period is adjusted based on the temperature and humidity data of the storage environment to calculate the remaining effective life index of the medical consumables, specifically including: Based on the characteristics of the medical consumables, determine the corresponding environmental sensitivity factors; The ambient temperature and humidity of the hospital warehouse where the medical consumables are located are acquired in real time or periodically, and it is determined whether the ambient temperature and humidity exceed the preset standard temperature and humidity range. When the temperature and humidity exceed the standard temperature and humidity range, the temperature and humidity accelerated decay coefficient is calculated using the environmental sensitivity factor. The natural lifespan of the medical consumables in non-standard temperature and humidity environments is weighted and accumulated to obtain the corrected consumed lifespan. The remaining effective life index is calculated based on the difference between the baseline effective life and the corrected consumed life.

4. The method for full-process traceability and loss control of medical consumables according to claim 1, characterized in that, Based on the current inventory and consumption rate of the medical consumables in the hospital's warehouse and other hospital warehouses, the optimal allocation destination is calculated, specifically including: Obtain the current inventory of the same type of medical consumables in the warehouses of each candidate hospital and the average consumption rate within a preset historical period; Based on the ratio of the average consumption rate to the current inventory level, calculate the consumables digestibility index of each candidate hospital warehouse; The hospital warehouse with the highest digestibility index and the conditions for receiving the supplies is identified as the optimal allocation destination, and medical consumables nearing their expiration date are prioritized for allocation to the hospital warehouse with the fastest consumption rate.

5. The method for full-process traceability and loss control of medical consumables according to claim 1, characterized in that, The method further includes: An emergency warning is triggered when the remaining effective life index of the medical consumable is lower than a preset emergency threshold. Automatically generate a "priority use" electronic tag, and push the electronic tag and the warning information together to the hospital warehouse where the medical consumable is currently located and the terminals of relevant clinical departments for prominent display.

6. The method for full-process traceability and loss control of medical consumables according to claim 1, characterized in that, The method further includes: By combining the remaining effective life index, physical distribution, and allocation status of all medical consumables in the warehouses of each hospital area, a heat map of the shelf life of medical consumables across warehouses in the entire hospital area is dynamically generated. The heatmap of the effective lifespan is divided into different color gradients to display the distribution and allocation trajectory of medical consumables in different remaining effective lifespan ranges.

7. The method for full-process traceability and loss control of medical consumables according to claim 1, characterized in that, Constructing the entire lifecycle circulation chain of the aforementioned medical consumables also includes: The handover confirmation data, barcode timestamps, and environmental temperature and humidity logs for each cross-campus warehouse transfer are hash-encrypted to form an immutable traceability node, achieving full-process anti-tampering auditing.

8. A medical consumables full-process traceability and loss control system, characterized in that, include: The cargo identification system is deployed in warehouses across multiple hospital campuses. It uses the Unique Device Identifier (UDI) of Medical Devices as the core identifier to collect the inherent attribute data of medical consumables in each hospital campus warehouse and record the dynamic flow data of the medical consumables during the flow between and within hospital campuses. The dynamic flow data includes the temperature and humidity data of the storage environment. The circulation chain construction module is used to merge and integrate the fragmented circulation records of each hospital warehouse based on the UDI as the unique primary key, and construct the full life cycle circulation chain of the medical consumables. The shelf-life decay assessment module is used to calculate the remaining effective life index of the medical consumables by using a preset consumables shelf-life dynamic decay model, based on the baseline shelf-life in the inherent attribute data and combined with the temperature and humidity data of the storage environment. The early warning and allocation decision module is used to trigger an early warning when the remaining effective life index is lower than the preset cross-hospital warning threshold, and to calculate the optimal allocation destination based on the inventory and consumption rate of the medical consumables in the current hospital warehouse and other hospital warehouses. The control and management module is used to generate a list of allocation suggestions based on the optimal allocation destination, so as to control the allocation and flow of medical consumables between warehouses in various hospital areas.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the medical consumables full-process traceability and loss control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the medical consumables full-process traceability and loss control method as described in any one of claims 1 to 7.

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