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CN-121983265-A - Medical equipment management system

CN121983265ACN 121983265 ACN121983265 ACN 121983265ACN-121983265-A

Abstract

The invention relates to the technical field of medical instrument information management and maintenance and guarantee, and discloses a medical equipment management system which comprises a basic information management module, a dynamic monitoring module, a dynamic computing module and an intelligent decision and resource control module. The system firstly builds a multidimensional attribute model containing clinical risk indexes, calculates accumulated equivalent damage degree of equipment based on real-time working condition data by utilizing a nonlinear damage model, monitors inventory state and purchasing period of spare parts, dynamically generates a floating maintenance threshold by combining the clinical risk indexes, and automatically executes soft locking operation on associated spare parts when the accumulated equivalent damage degree meets early warning conditions. According to the invention, the physical loss of the equipment can be accurately estimated, the maintenance time can be adaptively adjusted according to the state of the supply chain, the buffer time is reserved in advance in the inventory shortage or high risk scene, the intelligent optimal configuration of medical maintenance resources is realized, and the unplanned shutdown risk of the equipment is effectively reduced.

Inventors

  • SONG KUIWU

Assignees

  • 上海枫登医疗科技有限公司

Dates

Publication Date
20260505
Application Date
20260126

Claims (10)

  1. 1. A medical device management system, comprising: a base information management module configured to store static attributes and clinical risk indices of the medical device; The dynamic monitoring and calculating module is configured to collect working condition data of the medical equipment in the running process and calculate the accumulated equivalent damage degree of the medical equipment based on a nonlinear damage model; an intelligent decision and resource control module configured to monitor real-time inventory status and procurement cycles of spare parts associated with the medical device and dynamically generate a floating maintenance threshold in combination with the clinical risk index; The intelligent decision and resource control module is further configured to compare the accumulated equivalent damage degree with the floating maintenance threshold, and execute the resource locking operation for the spare part when the accumulated equivalent damage degree meets the early warning condition set based on the floating maintenance threshold.
  2. 2. The medical device management system of claim 1, wherein the base information management module further comprises a risk assessment sub-module configured to quantitatively generate the clinical risk index according to a preset weighting rule that performs a numerical calculation based on the department attributes, life support dependencies, and device redundancy backup status of the medical device.
  3. 3. The medical device management system of claim 1, wherein the dynamic monitoring and computing module comprises a damage calculation engine configured to calculate the cumulative equivalent damage level by a nonlinear operating condition weighting algorithm that converts the ratio of the collected average operating load to the nominal standard load into damage increments per unit time by introducing a nonlinear damage factor.
  4. 4. A medical device management system according to claim 3 wherein the computing logic of the damage computation engine executing the cumulative equivalent damage degree comprises: dividing the running time of the device into successive time windows; Calculating, for each time window, a ratio of an average operating load within the window to the nominal standard load; Carrying out exponential operation on the ratio by utilizing the nonlinear damage factor to obtain a load acceleration effect coefficient; Multiplying the load acceleration effect coefficient by the corresponding time window duration to obtain a damage increment in the window; and summing the damage increment of all the time windows to obtain the accumulated equivalent damage degree.
  5. 5. The medical device management system of claim 1, wherein the intelligent decision and resource control module comprises an inventory monitoring unit configured to calculate spare part scarcity coefficients; When the real-time stock quantity of the spare parts is greater than or equal to a preset safety stock water level, setting the spare part scarcity coefficient as a reference value; When the real-time inventory quantity of the spare parts is smaller than the safety inventory water level, the inventory monitoring unit calculates a spare part scarcity coefficient which is larger than the reference value based on the ratio of the average purchasing lead time of the spare parts to the reference purchasing period.
  6. 6. The medical device management system of claim 5, wherein the logic of the inventory monitoring unit to calculate the spare part scarcity coefficient when the real-time inventory quantity is less than the safety inventory level comprises: acquiring the average purchasing lead time of the spare parts; Calculating the ratio of the average purchasing lead time to the standard purchasing period; And adding the ratio to a value of 1, and taking the obtained sum as the spare part scarcity coefficient.
  7. 7. The medical device management system of claim 1, wherein the intelligent decision and resource control module comprises a threshold generation unit configured to construct a risk and inventory coupling based attenuation model; The attenuation model is used for reducing the floating maintenance threshold according to a logarithmic attenuation law under the condition that the clinical risk index is increased or the spare part scarcity coefficient is increased so as to reserve a safe buffer period corresponding to purchase delay before the equipment reaches the maximum physical life.
  8. 8. The medical device management system of claim 1, wherein the logic of the threshold generation unit to calculate the floating maintenance threshold comprises: Calculating a product of the clinical risk index and the spare part scarcity coefficient; Performing natural logarithm operation on the product, and multiplying an operation result by a preset threshold sensitivity coefficient to obtain an attenuation factor; Calculating a difference of the value 1 minus the attenuation factor; And multiplying the difference value by the design maximum life of the key parts of the equipment to obtain the floating maintenance threshold value.
  9. 9. The medical device management system of claim 1, wherein the intelligent decision and resource control module comprises a resource locking unit configured to: setting an early warning judgment factor smaller than 1; when the accumulated equivalent damage degree is monitored to reach the product of the floating maintenance threshold value and the early warning judgment factor, judging that the early warning condition is met; And modifying the state identification field of the spare part from an available state to a soft locking state in a database, and binding the spare part with the unique identification code of the medical equipment.
  10. 10. A medical device management method applied to a medical device management system according to any one of claims 1 to 9, comprising the steps of: Constructing a multidimensional attribute data model of the medical equipment, wherein the model comprises static attributes and clinical risk indexes of the equipment; Collecting working condition data of the medical equipment in the operation process, and calculating the accumulated equivalent damage degree of the medical equipment based on a nonlinear damage model; Monitoring real-time inventory status and purchasing period of spare parts associated with the medical equipment, and dynamically generating a floating maintenance threshold value by combining the clinical risk index; And comparing the accumulated equivalent damage degree with the floating maintenance threshold, and executing the resource locking operation for the spare part when the accumulated equivalent damage degree meets the early warning condition set based on the floating maintenance threshold.

Description

Medical equipment management system Technical Field The invention relates to the technical field of medical instrument information management and maintenance guarantee, in particular to a medical equipment management system. Background With the rapid development of modern medical technology, medical equipment has become a core element for developing clinical diagnosis and treatment activities, and the operation reliability of the medical equipment is directly related to the medical quality and the patient safety. At present, medical institutions mainly adopt preventive maintenance strategies based on fixed periods, namely, maintenance plans are formulated strictly according to time intervals recommended by equipment manufacturers. In the prior art, some medical institutions began to introduce digital tools, such as using OM04IB information base for device archive registration, or using low code development platforms (e.g., sails, jian Daoyun, h3yun, etc.) to build simple device management applications. However, most of these current applications only implement the function of "paperless recording", i.e. static storage and presentation of information through simple form entry and spreadsheets. The shallow application based on the universal tool ignores the working condition load difference of the equipment in actual clinical application, and lacks the capability of deep quantitative analysis of the physical loss of the equipment. The system often cannot sense whether the equipment is in a high-load link state or a low-frequency standby state, so that the high-load equipment has burst faults due to overrun of accumulated damage before a preset maintenance period arrives. In addition, existing medical equipment maintenance management systems are often mutually split with supply chain inventory management systems, and maintenance decisions are often only based on the physical state of the equipment itself, without fully considering the real-time availability of key spare parts and the logistics timeliness of the supply chain. Under the condition that spare part stock is at a low water level or the purchasing lead time is long, if the system still mechanically triggers the maintenance request according to the fixed physical life threshold, the system is extremely easy to stop for a long time due to the shortage of spare parts when equipment fails or parts need to be replaced, and the continuity of clinical service is seriously affected. More importantly, the prior art lacks a cross-dimension resource intelligent locking mechanism, when the scarce spare parts face multi-equipment competition, the scarce spare parts cannot be distributed preferentially according to the clinical risk level of the equipment, and the conventional maintenance of the low-risk equipment is difficult to prevent from occupying the critical final inventory. Therefore, how to implement intelligent optimal configuration of medical maintenance resources by an intelligent decision algorithm and a working condition damage model of implantation depth based on a general low-code development platform and a standard information base is a problem which needs to be solved in the field. Disclosure of Invention The application aims to provide a medical equipment management system, which aims to solve the problems that equipment maintenance is delayed or excessive due to neglect of actual working condition load difference in the existing maintenance mode, the risk of waiting for material shutdown is caused by unaccounted for supply chain state, and scarce maintenance resources cannot be matched and locked preferentially according to clinical risks. The first aspect of the invention provides a medical equipment management system, which comprises a basic information management module, a dynamic monitoring and calculating module and an intelligent decision and resource control module. The basic information management module is used for constructing a data base of the medical equipment and storing static attributes and clinical risk indexes of the equipment. The clinical risk index is a quantitative index reflecting the importance degree of the equipment in clinical business, and is calculated and generated through a preset weighting rule according to parameters such as the attribute of a department to which the equipment belongs, the dependency on life support, whether a redundant backup state exists or not and the like. The dynamic monitoring and calculating module is used for acquiring equipment operation data in real time and quantifying the physical loss of the equipment. Specifically, the module collects working condition data of the medical equipment in the operation process, and a nonlinear damage model is adopted to calculate accumulated equivalent damage degree. In order to overcome the defect that the traditional time length method cannot reflect the influence of high-load operation on the service life acceleration loss of equipment, the module e