Information storage management method and system for hospital disinfection supply center

Abstract

The present invention relates to the field of data processing technology, and specifically to an information storage management method and system for a hospital disinfection supply center, including: obtaining the weight change degree and defect degree of medical dressings; constructing multiple two-dimensional coordinate systems to obtain a number of data points; clustering the data points to obtain clusters, and obtaining evaluation indicators of the disinfection effect of each cluster; according to the weight change degree of the data points in the clusters, obtaining evaluation indicators of the disinfection effect of clusters and clusters, and obtaining the disinfection effectiveness of each data point in each two-dimensional coordinate system; according to the disinfection effectiveness of the same data point in different two-dimensional coordinate systems and the position of a data point in the clusters in different two-dimensional coordinate systems, obtaining the disinfection effect of each data point, obtaining lossless compression areas and lossy compression areas, and compressing. The present invention aims to solve the problem of low storage efficiency when storing the disinfection quality of disinfected equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an information storage management method and system for a hospital disinfection supply center. Background Art

[0002] The hospital disinfection supply center is responsible for the cleaning, disinfection, sterilization, storage, and distribution of reusable diagnostic and treatment equipment, medical accessories, and other items in various departments, and is responsible for the supply of sterile items. It is the core of hospital infection control. If the quality of disinfection supply does not meet the standards, it will cause hospital infection and endanger the life and health of patients and medical staff. In the actual disinfection process, there may be unqualified situations such as wet bags and occupational exposure.

[0003] When using a pressure steam sterilizer to sterilize medical items, the sterilization ability of the instrument may decline with the length of time it is used, that is, the sterilization ability of different locations inside the instrument may be inconsistent, resulting in too low sterilization ability in a certain area. At this time, setting the same value for the storage method of sterilization quality for all sterilized items will lead to information loss, which in turn causes medical accidents. Summary of the invention

[0004] The invention provides an information storage management method and system for a hospital disinfection supply center to solve the existing problems.

[0005] The information storage management method and system of a hospital disinfection supply center of the present invention adopts the following technical solutions:

[0006] The present invention proposes an information storage management method for a hospital disinfection supply center, the method comprising the following steps:

[0007] sterilizing multiple batches of medical dressings using a pressure steam sterilizer to obtain weight change degrees and defect degrees of the medical dressings; constructing multiple two-dimensional coordinate systems, mapping the weight change degrees and defect degrees of the same batch of medical dressings into the same two-dimensional coordinate system, and obtaining a number of data points in each two-dimensional coordinate system;

[0008] Clustering the data points in each two-dimensional coordinate system to obtain clusters in each two-dimensional coordinate system; obtaining the degree of outliers of each cluster in each two-dimensional coordinate system according to the distribution of the clusters in each two-dimensional coordinate system, the number of data points contained in each cluster, and the distribution of the data points; combining the weight change degree and defect degree of the cluster center point in each cluster in each two-dimensional coordinate system to obtain an evaluation index of the disinfection effect of each cluster in each two-dimensional coordinate system;

[0009] The clustering result is corrected according to the weight change degree of each data point to obtain the clustering cluster in each two-dimensional coordinate system, and then the evaluation index of the disinfection effect of each clustering cluster is obtained; according to the difference between the evaluation index of the disinfection effect of the clustering cluster in each two-dimensional coordinate system and the evaluation index of the disinfection effect of the class cluster, the disinfection effectiveness of each data point in each two-dimensional coordinate system is obtained, and then the number of times each data point is a data point that fails the disinfection is obtained;

[0010] According to the disinfection effectiveness of the same data point in different two-dimensional coordinate systems and the position of a data point in the clusters in different two-dimensional coordinate systems, the volatility of each data point is obtained; combined with the number of times each data point is a data point that fails disinfection, the disinfection effect of each data point is obtained, and then the lossless compression area and the lossy compression area are obtained and compressed.

[0011] Furthermore, the method of constructing multiple two-dimensional coordinate systems, mapping the weight change degree and defect degree of the same batch of medical dressings into the same two-dimensional coordinate system, and obtaining a number of data points in each two-dimensional coordinate system includes the following specific methods:

[0012] structure A two-dimensional coordinate system is obtained in which the horizontal axis is the weight change degree and the vertical axis is the defect degree, and the weight change degree and the defect degree of the same batch of medical dressings are mapped into the same two-dimensional coordinate system, and multiple data points are obtained in each two-dimensional coordinate system;

[0013] Among them, a data point in each two-dimensional coordinate system corresponds to an area in the pressure steam sterilizer; the same data point in different two-dimensional coordinate systems corresponds to the same area in the pressure steam sterilizer.

[0014] Furthermore, the data points in each two-dimensional coordinate system are clustered to obtain clusters in each two-dimensional coordinate system, including the following specific methods:

[0015] The Euclidean distance between different data points in each two-dimensional coordinate system is set as the distance metric, and the number of clusters is set using Clustering algorithm clusters the data points in each two-dimensional coordinate system into several clusters.

[0016] Furthermore, the degree of outlier of each cluster in each two-dimensional coordinate system is obtained according to the distribution of clusters in each two-dimensional coordinate system, the number of data points contained in each cluster, and the distribution of data points, including the specific method of:

[0017] The first The cluster with the most data points in the two-dimensional coordinate system is recorded as Representative clusters;

[0018] According to The clusters in the two-dimensional coordinate system and the The specific calculation formula for the degree of outlier of each cluster is as follows:

[0019] ;

[0020] In the formula, Indicates In the two-dimensional coordinate system The degree of outliers of a cluster, Represents the number of data points contained in the two-dimensional coordinate system. Indicates In the two-dimensional coordinate system The number of data points contained in each cluster. Indicates In the two-dimensional coordinate system The cluster center of the cluster is The Euclidean distance between the cluster centers representing the clusters, Indicates All data points in the cluster to The average Euclidean distance between the cluster centers of the clusters.

[0021] Furthermore, the specific method for obtaining the evaluation index of the disinfection effect of each cluster in each two-dimensional coordinate system includes:

[0022] ;

[0023] In the formula, Indicates In the two-dimensional coordinate system Evaluation index of disinfection effect of each cluster, Indicates In the two-dimensional coordinate system The degree of outliers of a cluster, Indicates In the two-dimensional coordinate system The defect degree of the cluster center of each cluster, Indicates In the two-dimensional coordinate system The degree of weight change of the cluster center points within a cluster, To avoid hyperparameters with denominators equal to zero.

[0024] Furthermore, the clustering result is corrected according to the weight change degree of each data point to obtain the clustering clusters in each two-dimensional coordinate system, and then the evaluation index of the disinfection effect of each clustering cluster is obtained, including the specific method of:

[0025] The data points with a weight change greater than 0.03 are recorded as the data points corresponding to the medical dressings that failed the disinfection;

[0026] In the Remove the data points corresponding to the medical dressings that fail to be disinfected from each cluster in the two-dimensional coordinate system to obtain four new clusters; In the two-dimensional coordinate system The cluster obtained by removing the data points corresponding to the medical dressings that failed to be disinfected is recorded as In the two-dimensional coordinate system clusters; and obtain the evaluation index of the disinfection effect of each cluster in the two-dimensional coordinate system.

[0027] Furthermore, the disinfection effectiveness of each data point in each two-dimensional coordinate system is obtained according to the difference between the evaluation index of the disinfection effect of the cluster in each two-dimensional coordinate system and the evaluation index of the disinfection effect of the class cluster, and then the number of times each data point is a data point that fails disinfection is obtained, including the specific method of:

[0028] ;

[0029] In the formula, Indicates In the two-dimensional coordinate system The disinfection effectiveness of the clusters, Indicates In the two-dimensional coordinate system Evaluation index of disinfection effect of each cluster, Indicates In the two-dimensional coordinate system The evaluation index of the disinfection effect of clusters is Indicates The mean of the evaluation index of the disinfection effect of all clusters in a two-dimensional coordinate system, Indicates The maximum value of the evaluation index of the disinfection effect of all clusters in a two-dimensional coordinate system, Represents the sigmoid function;

[0030] Order The disinfection effectiveness of the data point corresponding to the medical dressing that fails to be disinfected in the two-dimensional coordinate system is 0. The disinfection effectiveness of each cluster in a two-dimensional coordinate system is the disinfection effectiveness of all data points in the cluster;

[0031] Preset validity threshold , the disinfection effectiveness is less than the effectiveness threshold The data points are recorded as data points that fail disinfection;

[0032] The disinfection effectiveness level is greater than or equal to the effectiveness level threshold The data points are recorded as qualified disinfection data points;

[0033] The number of times the same data point in all two-dimensional coordinate systems is recorded as a data point that fails disinfection is recorded as the number of times the data point is recorded as a data point that fails disinfection.

[0034] Furthermore, the volatility of each data point is obtained according to the disinfection effectiveness of the same data point in different two-dimensional coordinate systems and the position of a data point in the cluster in different two-dimensional coordinate systems, including the specific method of:

[0035] In each two-dimensional coordinate system The disinfection effectiveness of the data point is taken as the elements in the valid set of data points, and obtain the A valid set of data points;

[0036] All the two-dimensional coordinate systems The maximum Euclidean distance between a data point and the cluster center point of its cluster is recorded as Maximum distance;

[0037] All the two-dimensional coordinate systems The mean of the Euclidean distances between a data point and the cluster center of its cluster is denoted as The specific calculation formula for obtaining the volatility of each data point is as follows:

[0038] ;

[0039] In the formula, Indicates The volatility of the data points, Indicates The variance of all data points in the valid set of data points, Indicates The maximum distance, Indicates The average distance.

[0040] Furthermore, the disinfection effect of each data point is obtained, and then the lossless compression area and the lossy compression area are obtained and compressed, including the specific method of:

[0041] ;

[0042] In the formula, Indicates The disinfection effect of each data point is Indicates The volatility of the data points, Indicates The mean of all elements in the valid set of data points, represents the mean of all elements in the valid set of all data points, Indicates batch, Indicates data points is the number of data points that failed disinfection. Represents the sigmoid function;

[0043] Preset effect threshold , the area corresponding to the data points whose disinfection effect is less than the effect threshold is recorded as the area with unqualified disinfection effect; the area corresponding to the data points whose disinfection effect is greater than or equal to the effect threshold is recorded as the area with qualified disinfection effect;

[0044] Lossless compression of the disinfection quality of medical dressings in areas where the disinfection effect is unsatisfactory;

[0045] The average of the disinfection qualities of all medical dressings in the area with qualified disinfection effect is recorded as the final disinfection quality of the medical dressings in the area with qualified disinfection effect; according to the final disinfection quality of the medical dressings in the area with qualified disinfection effect, the medical dressings in the area with qualified disinfection effect are lossily compressed.

[0046] The present invention also proposes an information storage management system for a hospital disinfection supply center, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the above method.

[0047] The technical solution of the present invention has the following beneficial effects: when storing the disinfection quality of disinfected articles, based on the characteristics that different areas of unqualified disinfection have different disinfection qualities for the articles, while different areas of qualified disinfection have relatively similar disinfection qualities for the articles, the evaluation index of the disinfection effect of the cluster where the data points of the medical dressings that fail to be disinfected are located is smaller than the evaluation index of the disinfection effect of the cluster where the data points of the medical dressings that fail to be disinfected are located; based on the characteristics that the evaluation index of the disinfection effect of the cluster where the data points corresponding to some medical dressings are located is greatly affected by the data points corresponding to the medical dressings that fail to be disinfected due to the influence of the irregular use of the disinfection equipment, the disinfection effectiveness of the data points of the medical dressings affected by the standard degree of use of the equipment is smaller than the disinfection effectiveness of the data points of the medical dressings that are not affected by the standard degree of use of the equipment and have better disinfection effects; based on the characteristics that the possibility of irregular use of the disinfection equipment is low, the volatility of the data points of the medical dressings affected by the standard degree of use of the equipment is larger, so that the disinfection effect of each data point is more accurate; the lossless compression area and the lossy compression area are more accurate; and the compression efficiency is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 The present invention is a flowchart of the steps of an information storage management method for a hospital disinfection supply center. DETAILED DESCRIPTION

[0050] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the information storage management method and system of a hospital disinfection supply center proposed according to the present invention, its specific implementation method, structure, characteristics and effects thereof as follows. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0051] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0052] The following is a detailed description of the information storage management method and system for a hospital disinfection supply center provided by the present invention in conjunction with the accompanying drawings.

[0053] See also Figure 1 , which shows a flowchart of a method for information storage management of a hospital disinfection supply center provided by an embodiment of the present invention, the method comprising the following steps:

[0054] Step S001: sterilize multiple batches of medical dressings using a pressure steam sterilizer to obtain the weight change degree and defect degree of the medical dressings; construct multiple two-dimensional coordinate systems, map the weight change degree and defect degree of the same batch of medical dressings into the same two-dimensional coordinate system, and obtain a number of data points in each two-dimensional coordinate system.

[0055] This embodiment stores the disinfection effect of the disinfected articles, thereby obtaining the results of multiple disinfection of the same type of articles by the disinfection equipment, and obtaining the weight change degree and defect degree of each medical dressing. A two-dimensional coordinate system is constructed, and each medical dressing is mapped to the two-dimensional coordinate system according to the weight change degree and defect degree of each medical dressing.

[0056] Specifically, a high-precision electronic scale is used to obtain the weight of the medical dressing to be sterilized. A pressure steam sterilizer is used to sterilize the medical dressing to be sterilized, and a high-precision electronic scale is used to obtain the weight of the sterilized medical dressing. The number of medical dressings to be sterilized in a batch refers to the number of medical dressings that can be sterilized after opening the pressure steam sterilizer once. Indicates the preset batch. In this embodiment, the preset batch , this is used as an example for description, and other values ​​may be set in other implementations. Use a camera to obtain an image of the sterilized medical dressing. Use semantic segmentation to obtain the dirty area and damaged area in the sterilized medical dressing image, and obtain the area of ​​the dirty area and damaged area in each sterilized medical dressing image. The ratio of the sum of the areas of the dirty area and the damaged area in each sterilized medical dressing image to the area of ​​the medical dressing image is recorded as the defect degree of the medical dressing. Among them, when placing the medical dressing to be sterilized in a pressure steam sterilizer, avoid placing the medical dressing to be sterilized too tightly, too densely, or overlapping and squeezing. Among them, performing semantic segmentation on the image to obtain the damaged area and the dirty area in the image is a well-known technology, which will not be repeated in this embodiment.

[0057] Further, Bite The first medical dressing to be sterilized is recorded as the first Bite A sterilized medical dressing. Bhd. The weight of the sterilized medical dressing minus the weight of the Bhd. The weight of the first medical dressing to be sterilized is recorded as Bhd. The weight change of the first medical dressing. Bite The weight change of the first medical dressing is similar to that of the second Bhd. The ratio of the weight of the medical dressing to be sterilized is recorded as Bhd. The weight change degree of each medical dressing is measured, wherein each medical dressing corresponds to an area in the steam sterilizer.

[0058] Furthermore, the structure A two-dimensional coordinate system is obtained in which the horizontal axis is the weight change degree and the vertical axis is the defect degree. The weight change degree and defect degree of the same batch of medical dressings are mapped to the same two-dimensional coordinate system, and multiple data points are obtained in each two-dimensional coordinate system. The medical dressings in the batch are mapped to the In a two-dimensional coordinate system, each medical dressing corresponds to an area in the pressure steam sterilizer. That is, each data point in a two-dimensional coordinate system corresponds to an area in the pressure steam sterilizer. And the same data point in different two-dimensional coordinate systems corresponds to the same area in the pressure steam sterilizer. That is, the first data point in different batches corresponds to the same area in the pressure steam sterilizer. Each medical dressing corresponds to the first area.

[0059] At this point, the required data is obtained.

[0060] Step S002: Cluster the data points in each two-dimensional coordinate system to obtain clusters in each two-dimensional coordinate system; obtain the degree of outliers of each cluster in each two-dimensional coordinate system based on the distribution of clusters in each two-dimensional coordinate system, the number of data points contained in each cluster, and the distribution of data points; combine the weight change degree and defect degree of the cluster center point in each cluster in each two-dimensional coordinate system to obtain an evaluation index of the disinfection effect of each cluster in each two-dimensional coordinate system.

[0061] It should be noted that when using a pressure steam sterilizer to sterilize medical dressings, the disinfection effect of medical dressings placed in some locations in the steam sterilizer does not meet national standards due to aging of the equipment. Due to improper operation, the disinfection effect of medical dressings placed in some locations in the steam sterilizer exceeds the national standard, but the disinfection effect is not ideal. Therefore, the areas in the pressure steam sterilizer where the disinfection effect does not meet the standard and the areas where the disinfection effect is not ideal are obtained, and the disinfection effect of the items in these two areas is losslessly compressed. The area with an ideal disinfection effect is obtained, and the disinfection effect of the items in the area with an ideal disinfection effect is losslessly compressed.

[0062] It should be further explained that when obtaining the areas where the disinfection effect does not meet the standard, the areas where the disinfection effect is not ideal, and the areas where the disinfection effect is ideal. Ideally, the pressure steam sterilizer can perform consistent and efficient disinfection at different locations, so that the disinfection effect of the medical dressings in the areas where the disinfection effect is ideal is relatively similar. Therefore, the data points in each two-dimensional coordinate system are clustered.

[0063] It should be further explained that after disinfection, a medical dressing may face four situations, namely, the weight change before and after disinfection is small but the area of ​​the defect area is large, the weight change before and after disinfection is large but the area of ​​the defect area is small, the weight change before and after disinfection is large and the area of ​​the defect area is large, and the weight change before and after disinfection is small and the area of ​​the defect area is small. Therefore, the number of clusters is set to 4 during clustering.

[0064] It should be further explained that, ideally, the pressure steam sterilizer can sterilize different positions with the same degree of efficiency, so that the degree of outliers of each cluster reflects the sterilization effect of the corresponding position of the data point in each cluster. Therefore, the degree of outliers of each cluster is calculated.

[0065] It is further necessary to explain that when calculating the degree of outliers of each cluster, the distribution of data points in each cluster reflects the degree of aggregation of data points in the cluster; the number of data points in each cluster reflects the similarity between the data points in the cluster and the overall data points; the distance between each cluster and other clusters reflects the difference between the data points in each cluster and the data points in other clusters. Therefore, the degree of outliers of each cluster is calculated based on the number of data points in each cluster, the distance between each cluster and other clusters, and the distribution of data points in each cluster.

[0066] Specifically, the Euclidean distance between different data points in each two-dimensional coordinate system is set as the distance metric, and the number of clusters is set as Set the value to 4 and use Clustering algorithm, clustering the data points in each two-dimensional coordinate system into four clusters. The cluster with the most data points in the two-dimensional coordinate system is recorded as Representative clusters. The clusters in the two-dimensional coordinate system and the The specific calculation formula for the degree of outlier of each cluster is as follows:

[0067] ;

[0068] In the formula, Indicates In the two-dimensional coordinate system The degree of outliers of a cluster, Represents the number of data points contained in the two-dimensional coordinate system. Indicates In the two-dimensional coordinate system The number of data points contained in each cluster, Indicates In the two-dimensional coordinate system The cluster center of the cluster is The Euclidean distance between the cluster centers representing the clusters, Indicates All data points in the cluster to The average Euclidean distance between the cluster centers of the clusters.

[0069] It should be noted that The larger the value, the In the two-dimensional coordinate system Each data point in a cluster is quite different from other data points, which further illustrates that In the two-dimensional coordinate system The greater the degree of outlier of a cluster; The larger the value of, the more it means; The larger the value, the In the two-dimensional coordinate system There are fewer data points in each cluster that are similar to each other, which further illustrates that In the two-dimensional coordinate system The greater the degree of outlier of a cluster; The larger the value, the In the two-dimensional coordinate system The data points in the cluster are quite different from the majority of data points, which further illustrates that In the two-dimensional coordinate system The greater the degree of outlier of a cluster.

[0070] At this point, the outlier degree of each cluster in each two-dimensional coordinate system is obtained.

[0071] It should be further explained that when calculating the evaluation index of the disinfection effect of each cluster, since the horizontal and vertical coordinates of each data point in each cluster reflect the disinfection effect of the position corresponding to each data point in each cluster, the evaluation index of the disinfection effect of each cluster is calculated according to the degree of outliers of each cluster and the horizontal and vertical coordinates of the cluster center point in each cluster.

[0072] Specifically, the specific calculation formula for the evaluation index of the disinfection effect of each cluster in each two-dimensional coordinate system is as follows:

[0073] ;

[0074] In the formula, Indicates In the two-dimensional coordinate system Evaluation index of disinfection effect of each cluster, Indicates In the two-dimensional coordinate system The degree of outliers of a cluster, Indicates In the two-dimensional coordinate system The defect degree of the cluster center of each cluster, Indicates In the two-dimensional coordinate system The degree of weight change of the cluster center points within a cluster, To avoid hyperparameters with a denominator of 0, this embodiment uses Give a narrative.

[0075] It should be noted that The larger the value, the In the two-dimensional coordinate system The greater the difference in disinfection effect of the locations corresponding to the data points in the clusters, the greater the difference in disinfection effect of the locations corresponding to the data points in the clusters. In the two-dimensional coordinate system The disinfection effect of the location corresponding to the data point in each cluster is poor; The larger the value, the In the two-dimensional coordinate system The disinfection effect of the locations corresponding to the data points in each cluster is poor.

[0076] So far, we have obtained Evaluation index of disinfection effect of each cluster.

[0077] Step S003: Correct the clustering result according to the weight change degree of each data point to obtain the clustering clusters in each two-dimensional coordinate system, and then obtain the evaluation index of the disinfection effect of each clustering cluster; according to the difference between the evaluation index of the disinfection effect of the clustering cluster in each two-dimensional coordinate system and the evaluation index of the disinfection effect of the class cluster, obtain the disinfection effectiveness of each data point in each two-dimensional coordinate system, and then obtain the number of times each data point is a data point that fails the disinfection.

[0078] It should be noted that when using a pressure steam sterilizer to sterilize medical dressings, the disinfection effect of medical dressings placed in some areas may deteriorate due to improper operation, which may cause some data points with unqualified disinfection effects and data points with unsatisfactory disinfection effects to be clustered into one cluster during the clustering process, thereby deteriorating the disinfection effect of the cluster. In order to eliminate the influence of accidental factors on the disinfection effect of each area, the data points with unqualified disinfection effects should be removed from each cluster to obtain the effectiveness of the disinfection effect of each data point.

[0079] Specifically, the data point with a weight change greater than 0.03 is recorded as the data point corresponding to the medical dressing that fails to pass the disinfection test. 0.03 is obtained according to the provisions of GB8599. Remove the data points corresponding to the medical dressings that fail to meet the disinfection standards from each cluster in the two-dimensional coordinate system to obtain four new clusters. In the two-dimensional coordinate system The cluster obtained by removing the data points corresponding to the medical dressings that failed to be disinfected is recorded as In the two-dimensional coordinate system Clusters are formed. According to the method for obtaining the evaluation index of the disinfection effect of each cluster, the evaluation index of the disinfection effect of each cluster in the two-dimensional coordinate system is obtained. Among them, if there is no data point in a cluster, the evaluation index of the disinfection effect of the cluster is 0. The evaluation index of the disinfection effect of each cluster in a two-dimensional coordinate system is obtained, and the specific calculation formula for the disinfection effectiveness of each cluster is as follows:

[0080] ;

[0081] In the formula, Indicates In the two-dimensional coordinate system The disinfection effectiveness of the clusters, Indicates In the two-dimensional coordinate system Evaluation index of disinfection effect of each cluster, Indicates In the two-dimensional coordinate system The evaluation index of the disinfection effect of clusters is Indicates The mean of the evaluation index of the disinfection effect of all clusters in a two-dimensional coordinate system, Indicates The maximum value of the evaluation index of the disinfection effect of all clusters in a two-dimensional coordinate system, represents a sigmoid function, which is used for normalization processing in this embodiment.

[0082] It should be noted that The larger the value, the The first The greater the impact of the unqualified points in a cluster on the evaluation index of the disinfection effect of the cluster, the greater the impact of the unqualified points in the cluster on the evaluation index of the disinfection effect of the cluster, which further explains the The first The greater the difference between the data points in the cluster and the data points corresponding to the medical dressings that fail to be disinfected, the greater the difference between the data points in the cluster and the data points corresponding to the medical dressings that fail to be disinfected. The first The better the disinfection effect of the data points in the clusters; The larger the value, the The first The greater the impact of the unqualified points in a cluster on the evaluation index of the disinfection effect of the cluster, the greater the impact of the unqualified points in the cluster on the evaluation index of the disinfection effect of the cluster, which further explains the The first The better the disinfection effect is, the smaller the number of data points in each cluster.

[0083] Furthermore, The disinfection effectiveness of the data point corresponding to the medical dressing that fails to be disinfected in the two-dimensional coordinate system is 0. The disinfection effectiveness of each cluster in a two-dimensional coordinate system is the disinfection effectiveness of all data points in the cluster. Preset effectiveness threshold , the disinfection effectiveness is less than the effectiveness threshold The data points with a disinfection effectiveness greater than or equal to the effectiveness threshold are recorded as data points with disinfection effectiveness greater than or equal to the effectiveness threshold. The number of times the same data point in all two-dimensional coordinate systems is recorded as a data point that fails to be disinfected is recorded as the number of times the data point is a data point that fails to be disinfected.

[0084] At this point, the data points that pass the disinfection and the data points that fail the disinfection are obtained in each two-dimensional coordinate system.

[0085] Step S004: According to the disinfection effectiveness of the same data point in different two-dimensional coordinate systems and the position of a data point in the clusters in different two-dimensional coordinate systems, the volatility of each data point is obtained; combined with the number of times each data point is a data point that fails disinfection, the disinfection effect of each data point is obtained, and then the lossless compression area and the lossy compression area are obtained, and compression is performed.

[0086] It should be noted that when sterilizing medical dressings by pressure steam sterilizer, due to improper operation, the corresponding data points of medical dressings in some areas may be unqualified for disinfection in some times and qualified for disinfection in other times. That is, the data points affected by accidental factors have strong volatility, so the volatility of each data point is calculated, and according to the volatility of each data point, the possibility that the area where the medical dressing corresponding to each data point is located is the area where the disinfection fails is obtained.

[0087] Specifically, the first The disinfection effectiveness of the data point is taken as the elements in the valid set of data points, and obtain the The valid set of data points. The maximum Euclidean distance between a data point and the cluster center point of its cluster is recorded as The maximum distance. The mean of the Euclidean distances between a data point and the cluster center of its cluster is denoted as The average distance.

[0088] Furthermore, the specific calculation formula for obtaining the volatility of each data point is as follows:

[0089] ;

[0090] In the formula, Indicates The volatility of the data points, Indicates The variance of all data points in the valid set of data points, Indicates The maximum distance, Indicates The average distance.

[0091] It should be noted that The larger the value, the The volatility of the elements in the effective set of data points is strong. The larger the value, the The positions of the data points in different two-dimensional coordinate systems vary greatly, further explaining that The greater the volatility of the data points.

[0092] At this point, the volatility of each data point is obtained.

[0093] Furthermore, the specific calculation formula for obtaining the disinfection effect of each data point is as follows:

[0094] ;

[0095] In the formula, Indicates The disinfection effect of each data point is Indicates The volatility of the data points, Indicates The mean of all elements in the valid set of data points, represents the mean of all elements in the valid set of all data points, Indicates batch, Indicates data points is the number of data points that failed disinfection. represents a sigmoid function, which is used for normalization processing in this embodiment.

[0096] It should be noted that The larger the value of The more times the data points are qualified for disinfection, the more it indicates that The stronger the disinfection effect of each data point; The larger the value of The disinfection effectiveness of each data point is less.

[0097] Specifically, preset effect threshold , the area corresponding to the data points with disinfection effect less than the effect threshold is recorded as the area with unqualified disinfection effect; the area corresponding to the data points with disinfection effect greater than or equal to the effect threshold is recorded as the area with qualified disinfection effect. Indicates the preset effect threshold. In this embodiment, , this is used as an example for description, and other values ​​may be set in other implementation modes.

[0098] Furthermore, the disinfection quality of the medical dressings in the area with unqualified disinfection effect is losslessly compressed. The average of the disinfection quality of all medical dressings in the area with qualified disinfection effect is recorded as the final disinfection quality of the medical dressings in the area with qualified disinfection effect. According to the final disinfection quality of the medical dressings in the area with better disinfection effect, the medical dressings in the area with better disinfection effect are lossily compressed.

[0099] At this point, this embodiment is completed.

[0100] Another embodiment of the present invention provides an information storage management system for a hospital disinfection supply center, the system comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the above method steps S001 to S004 are implemented.

[0101] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An information storage management method for a hospital disinfection supply center, characterized in that: The method comprises the following steps: sterilizing multiple batches of medical dressings using a pressure steam sterilizer to obtain weight change degrees and defect degrees of the medical dressings; constructing multiple two-dimensional coordinate systems, mapping the weight change degrees and defect degrees of the same batch of medical dressings into the same two-dimensional coordinate system, and obtaining a number of data points in each two-dimensional coordinate system; Clustering the data points in each two-dimensional coordinate system to obtain clusters in each two-dimensional coordinate system; obtaining the degree of outliers of each cluster in each two-dimensional coordinate system according to the distribution of the clusters in each two-dimensional coordinate system, the number of data points contained in each cluster, and the distribution of the data points; combining the weight change degree and defect degree of the cluster center point in each cluster in each two-dimensional coordinate system to obtain an evaluation index of the disinfection effect of each cluster in each two-dimensional coordinate system; The clustering result is corrected according to the weight change degree of each data point to obtain the clustering cluster in each two-dimensional coordinate system, and then the evaluation index of the disinfection effect of each clustering cluster is obtained; according to the difference between the evaluation index of the disinfection effect of the clustering cluster in each two-dimensional coordinate system and the evaluation index of the disinfection effect of the class cluster, the disinfection effectiveness of each data point in each two-dimensional coordinate system is obtained, and then the number of times each data point is a data point that fails the disinfection is obtained; According to the disinfection effectiveness of the same data point in different two-dimensional coordinate systems and the position of a data point in the clusters in different two-dimensional coordinate systems, the volatility of each data point is obtained; combined with the number of times each data point is a data point that fails disinfection, the disinfection effect of each data point is obtained, and then the lossless compression area and the lossy compression area are obtained, and compression is performed; The method of obtaining the degree of outlier of each cluster in each two-dimensional coordinate system according to the distribution of clusters in each two-dimensional coordinate system, the number of data points contained in each cluster and the distribution of data points includes the following specific methods: The first The cluster with the most data points in the two-dimensional coordinate system is recorded as Representative clusters; According to The clusters in the two-dimensional coordinate system and the The specific calculation formula for the degree of outlier of each cluster is as follows: ； In the formula, Indicates In the two-dimensional coordinate system The degree of outliers of a cluster, Represents the number of data points contained in the two-dimensional coordinate system. Indicates In the two-dimensional coordinate system The number of data points contained in each cluster, Indicates In the two-dimensional coordinate system The cluster center of the cluster is The Euclidean distance between the cluster centers representing the clusters, Indicates All data points in the cluster to The average Euclidean distance between the cluster centers of each cluster; The specific method for obtaining the evaluation index of the disinfection effect of each cluster in each two-dimensional coordinate system includes: ； In the formula, Indicates In the two-dimensional coordinate system Evaluation index of disinfection effect of each cluster, Indicates In the two-dimensional coordinate system The degree of outliers of a cluster, Indicates In the two-dimensional coordinate system The defect degree of the cluster center of each cluster, Indicates In the two-dimensional coordinate system The degree of weight change of the cluster center points within a cluster, To avoid hyperparameters with a denominator of 0; The clustering result is corrected according to the weight change degree of each data point to obtain the clustering clusters in each two-dimensional coordinate system, and then the evaluation index of the disinfection effect of each clustering cluster is obtained, including the specific method of: The data points with a weight change greater than 0.03 are recorded as the data points corresponding to the medical dressings that failed the disinfection; In the Remove the data points corresponding to the medical dressings that fail to be disinfected from each cluster in the two-dimensional coordinate system to obtain four new clusters; In the two-dimensional coordinate system The cluster obtained by removing the data points corresponding to the medical dressings that failed to be disinfected is recorded as In the two-dimensional coordinate system clusters; obtain the evaluation index of the disinfection effect of each cluster in the two-dimensional coordinate system; The method of obtaining the disinfection effectiveness of each data point in each two-dimensional coordinate system according to the difference between the evaluation index of the disinfection effect of the cluster and the evaluation index of the disinfection effect of the class cluster in each two-dimensional coordinate system, and then obtaining the number of times each data point is a data point that fails the disinfection, includes the following specific methods: ； In the formula, Indicates In the two-dimensional coordinate system The disinfection effectiveness of the clusters, Indicates In the two-dimensional coordinate system Evaluation index of disinfection effect of each cluster, Indicates In the two-dimensional coordinate system The evaluation index of the disinfection effect of clusters is Indicates The mean of the evaluation index of the disinfection effect of all clusters in a two-dimensional coordinate system, Indicates The maximum value of the evaluation index of the disinfection effect of all clusters in a two-dimensional coordinate system, Represents the sigmoid function; Order The disinfection effectiveness of the data point corresponding to the medical dressing that fails to be disinfected in the two-dimensional coordinate system is 0. The disinfection effectiveness of each cluster in a two-dimensional coordinate system is the disinfection effectiveness of all data points in the cluster; Preset validity threshold , the disinfection effectiveness is less than the effectiveness threshold The data points are recorded as data points that fail disinfection; The disinfection effectiveness level is greater than or equal to the effectiveness level threshold The data points are recorded as qualified disinfection data points; The number of times the same data point in all two-dimensional coordinate systems is recorded as a data point that fails disinfection is recorded as the number of times the data point is a data point that fails disinfection.

2. The information storage management method of a hospital disinfection supply center according to claim 1, characterized in that: The method of constructing multiple two-dimensional coordinate systems, mapping the weight change degree and defect degree of the same batch of medical dressings into the same two-dimensional coordinate system, and obtaining a number of data points in each two-dimensional coordinate system includes: structure A two-dimensional coordinate system is obtained in which the horizontal axis is the weight change degree and the vertical axis is the defect degree, and the weight change degree and defect degree of the same batch of medical dressings are mapped into the same two-dimensional coordinate system, and multiple data points are obtained in each two-dimensional coordinate system; Among them, a data point in each two-dimensional coordinate system corresponds to an area in the pressure steam sterilizer; the same data point in different two-dimensional coordinate systems corresponds to the same area in the pressure steam sterilizer.

3. The information storage management method of a hospital disinfection supply center according to claim 1, characterized in that: The specific method of clustering the data points in each two-dimensional coordinate system to obtain the clusters in each two-dimensional coordinate system includes: The Euclidean distance between different data points in each two-dimensional coordinate system is set as the distance metric, and the number of clusters is set using Clustering algorithm clusters the data points in each two-dimensional coordinate system into several clusters.

4. The information storage management method of a hospital disinfection supply center according to claim 1, characterized in that: The volatility of each data point is obtained according to the disinfection effectiveness of the same data point in different two-dimensional coordinate systems and the position of a data point in the cluster in different two-dimensional coordinate systems, including the specific method of: In each two-dimensional coordinate system The disinfection effectiveness of the data point is taken as the elements in the valid set of data points, and obtain the A valid set of data points; All the two-dimensional coordinate systems The maximum Euclidean distance between a data point and the cluster center point of its cluster is recorded as Maximum distance; All the two-dimensional coordinate systems The mean of the Euclidean distances between a data point and the cluster center of its cluster is denoted as The specific calculation formula for obtaining the volatility of each data point is as follows: ； In the formula, Indicates The volatility of the data points, Indicates The variance of all data points in the valid set of data points, Indicates The maximum distance, Indicates The average distance.

5. The information storage management method of a hospital disinfection supply center according to claim 4, characterized in that: The disinfection effect of each data point is obtained, and then the lossless compression area and the lossy compression area are obtained and compressed, including the specific method of: ； In the formula, Indicates The disinfection effect of each data point is Indicates The volatility of the data points, Indicates The mean of all elements in the valid set of data points, represents the mean of all elements in the valid set of all data points, Indicates batch, Indicates data points is the number of data points that failed disinfection. Represents the sigmoid function; Preset effect threshold , the area corresponding to the data points whose disinfection effect is less than the effect threshold is recorded as the area with unqualified disinfection effect; the area corresponding to the data points whose disinfection effect is greater than or equal to the effect threshold is recorded as the area with qualified disinfection effect; Lossless compression of the disinfection quality of medical dressings in areas where the disinfection effect is unsatisfactory; The average of the disinfection qualities of all medical dressings in the area with qualified disinfection effect is recorded as the final disinfection quality of the medical dressings in the area with qualified disinfection effect; According to the final disinfection quality of the medical dressing in the area with qualified disinfection effect, lossy compression is performed on the medical dressing in the area with qualified disinfection effect.

6. An information storage management system for a hospital disinfection supply center, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the information storage management method for a hospital disinfection supply center as described in any one of claims 1-5 are implemented.

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