Anesthesiology drug storage management method and system based on artificial intelligence

Abstract

The present invention belongs to the field of anesthesiology drug storage and involves data analysis technology. It is used to solve the problem that the anesthesiology drug storage management method and system in the prior art cannot perform processing decision analysis when the environment is abnormal. Specifically, it is an anesthesiology drug storage management system based on artificial intelligence, including a regional test module, a test evaluation module and a storage management module. The regional test module, the test evaluation module and the storage management module are communicatively connected in sequence; the regional test module is used to test and analyze the storage environment of the anesthesiology drug storage warehouse: the anesthesiology drug storage warehouse is divided into several storage areas, and the test coefficient Tc of the storage area within the test cycle is obtained; the test coefficient Tc of all storage areas is sent to the test evaluation module; the present invention can test and analyze the storage environment of the anesthesiology drug storage warehouse, and provide feedback on the environmental suitability of the storage area within the test cycle through the test coefficient.

Description

Technical Field

[0001] The present invention belongs to the field of anesthesiology drug storage and relates to data analysis technology, and specifically is an anesthesiology drug storage management system based on artificial intelligence. Background Art

[0002] To ensure the quality and stability of narcotic drugs, medical institutions need to provide a suitable storage environment; narcotic drugs should be stored in a dry, well-ventilated environment, avoid exposure to direct sunlight or strong light, and the storage area should avoid contamination of the drugs by harmful gases, dust and odors.

[0003] The anesthesiology drug storage management system in the prior art can only perform environmental monitoring of the anesthesia drug storage space, but cannot perform processing decision analysis when the environment is abnormal, nor can it perform layout optimization analysis of the anesthesia drug storage space based on the environmental monitoring parameters of the storage space, resulting in the overall storage status of the anesthesia drugs cannot be improved.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an anesthesiology drug storage management method and system based on artificial intelligence, which is used to solve the problem that the anesthesiology drug storage management system in the prior art cannot perform processing decision analysis when the environment is abnormal;

[0006] The technical problem to be solved by the present invention is: how to provide an anesthesia drug storage management method and system based on artificial intelligence that can perform processing decision analysis when the environment is abnormal.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The present invention provides an anesthesia drug storage management method based on artificial intelligence, the method comprising:

[0009] S110. Test and analyze the storage environment of the anesthesia department's drug storage warehouse, specifically:

[0010] The anesthesia drug storage bin is divided into several storage areas, each storage area is provided with an environmental adjustment mechanism; the parameters of each environmental adjustment mechanism are adjusted to the corresponding standard values; a test cycle is generated for each storage area; the storage environment of each storage area is tested respectively during the test cycle to obtain environmental test data of each storage area; and the test coefficient Tc of each storage area during the test cycle is obtained according to the environmental test data of each storage area;

[0011] S120, evaluating and analyzing the test coefficient Tc of the anesthesiology drug storage bin to obtain a standard adjustment value and a structural optimization value, and determining whether the storage environment of the anesthesiology drug storage bin meets the requirements based on the standard adjustment value and the structural optimization value;

[0012] S130. Manage and analyze the storage space for anesthesiology drugs.

[0013] Furthermore, the storage environment of each storage area is tested separately during the test cycle to obtain environmental test data of each storage area, specifically including:

[0014] Several test points are set in each storage area, and the air temperature value, air humidity value and air dust concentration value of each test point are obtained in real time during the test cycle as the environmental test data.

[0015] Further, the step of obtaining the test coefficient Tc of each storage area in the test cycle according to the environmental test data of each storage area specifically includes:

[0016] Calculate the temperature difference value Tdeviation according to the air temperature value of each storage area;

[0017] Calculate the humidity difference value H bias according to the air humidity value of each storage area;

[0018] Calculate the dust concentration value Dconcentration according to the air dust concentration value of each storage area;

[0019] The test coefficient Tc is calculated according to the temperature difference value Tb, humidity difference value Hb and ash concentration value Dc of each area during the test cycle. The specific calculation formula is:

[0020]

[0021] Among them, m1, m2, and m3 are all proportional coefficients, and m1>m2>m3>1.

[0022] Further, the temperature difference value T deviation is calculated according to the air temperature value of each storage area, specifically including:

[0023] Retrieve the standard temperature range of the anesthesia drug storage bin, and mark the average of the maximum and minimum values ​​of the standard temperature range as the temperature standard value;

[0024] The absolute value of the difference between the air temperature value at the test point and the temperature standard value is marked as the temperature difference value of the test point;

[0025] The maximum value of the temperature difference of all test points in the storage area during the test cycle is marked as the temperature difference value T deviation;

[0026] And / or, calculating the humidity difference value H bias according to the air humidity values ​​of each storage area, specifically including:

[0027] Retrieve the standard humidity range of the anesthesiology drug storage bin, and mark the average of the maximum and minimum values ​​of the standard humidity range as the humidity standard value;

[0028] The absolute value of the difference between the air humidity value at the test point and the humidity standard value is marked as the humidity difference value of the test point;

[0029] The maximum value of the humidity difference of all test points in the storage area during the test cycle is marked as the humidity difference value H bias;

[0030] And / or, calculating the dust concentration value Dconcentrate according to the air dust concentration value of each storage area, specifically including:

[0031] The maximum value of the air dust concentration values ​​at all test points in the storage area during the test cycle is marked as the dust concentration value Dconcentrate.

[0032] Furthermore, the test coefficients Tc of all storage areas are summed and averaged to obtain a standard adjustment value, and the test coefficients Tc of all storage areas are calculated by variance to obtain a structural optimization value.

[0033] Furthermore, the standard adjustment value and the structure optimization value are used to determine whether the storage environment of the anesthesia drug storage bin meets the requirements. Specifically, the standard adjustment value and the structure optimization value are compared with the preset standard adjustment threshold and the structure optimization threshold, respectively. The comparison process is as follows:

[0034] If the structural optimization value is greater than or equal to the structural optimization threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse does not meet the requirements, and a space optimization signal is generated and sent to the mobile phone terminal of the manager;

[0035] If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is greater than or equal to the standard adjustment threshold, it is determined that the drug storage environment of the anesthesia department's drug storage warehouse does not meet the requirements, and a standard adjustment signal is generated and sent to the mobile phone terminal of the administrator;

[0036] If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is less than the standard adjustment threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse meets the requirements, and the L1 storage areas with the smallest test coefficient Tc value are marked as high-quality areas, and the high-quality areas are stored and managed.

[0037] Furthermore, the management and analysis of the storage space for anesthesia drugs and the marking of special drugs in anesthesia drugs specifically include:

[0038] Special drugs are matched and stored with high-quality areas, and then the remaining anesthesia drugs other than special drugs are classified according to drug types and stored in various remaining storage areas other than the high-quality areas.

[0039] The present invention also provides an anesthesia drug storage management system based on artificial intelligence, comprising a regional test module, a test evaluation module and a storage management module, wherein the regional test module, the test evaluation module and the storage management module are sequentially connected in communication;

[0040] The regional test module is used to test and analyze the storage environment of the anesthesia drug storage warehouse: the anesthesia drug storage warehouse is divided into several storage areas, each storage area is provided with an environmental adjustment mechanism; the parameters of the environmental adjustment mechanism of the anesthesia drug storage warehouse are adjusted to the corresponding standard values; a test cycle is generated for each storage area, and the storage environment of each storage area is tested respectively during the test cycle to obtain environmental test data of each storage area; the test coefficient Tc of each storage area during the test cycle is obtained according to the environmental test data of each storage area; and the test coefficients Tc of all storage areas are sent to the test evaluation module;

[0041] The test evaluation module is used to evaluate and analyze the test coefficient Tc of the anesthesiology drug storage bin and obtain the standard adjustment value and the structural optimization value, and to determine whether the storage environment of the anesthesiology drug storage bin meets the requirements through the standard adjustment value and the structural optimization value;

[0042] The storage management module is used to manage and analyze the drug storage space of anesthesia drugs.

[0043] Furthermore, the regional test module is used to calculate the test coefficient Tc by: obtaining the temperature difference value Tb, humidity difference value Hb and ash concentration value Dc of the storage area during the test period;

[0044]

[0045] The test coefficient Tc of the storage area in the test cycle is obtained, wherein m1, m2, and m3 are all proportional coefficients, and m1>m2>m3>1.

[0046] Furthermore, the process of obtaining the temperature difference value Tdeviation includes: setting a number of test points in the storage area, obtaining the air temperature value of the test points in real time, retrieving the standard temperature range of the anesthesia drug storage bin, marking the average value of the maximum value and the minimum value of the standard temperature range as the temperature standard value, marking the absolute value of the difference between the air temperature value of the test point and the temperature standard value as the temperature difference value of the test point, and marking the maximum value of the temperature difference value of all test points in the storage area within the test period as the temperature difference value Tdeviation;

[0047] The process of obtaining the humidity difference value H deviation includes: obtaining the air humidity value of the test point in real time, retrieving the standard humidity range of the drug storage bin in the anesthesiology department, marking the average value of the maximum and minimum values of the standard humidity range as the humidity standard value, marking the absolute value of the difference between the air humidity value of the test point and the humidity standard value as the humidity difference value of the test point, and marking the maximum value of the humidity difference values of all test points in the storage area during the test period as the humidity difference value H deviation;

[0048] The process of obtaining the ash concentration value D concentration includes: obtaining the air dust concentration value of the test point in real time, and marking the maximum value of the air dust concentration values of all test points in the storage area during the test period as the ash concentration value D concentration.

[0049] Further, the sum of the test coefficients Tc of all storage areas is averaged to obtain the standard adjustment value, and the variance of the test coefficients Tc of all storage areas is calculated to obtain the structure optimization value.

[0050] Further, the specific process of determining whether the storage environment of the drug storage bin in the anesthesiology department meets the requirements includes: comparing the standard adjustment value and the structure optimization value with the preset standard adjustment threshold and structure optimization threshold respectively: if the structure optimization value is greater than or equal to the structure optimization threshold, it is determined that the drug storage environment of the drug storage bin in the anesthesiology department does not meet the requirements, generating a space optimization signal and sending the space optimization signal to the mobile terminal of the management personnel; if the structure optimization value is less than the structure optimization threshold and the standard adjustment value is greater than or equal to the standard adjustment threshold, it is determined that the drug storage environment of the drug storage bin in the anesthesiology department does not meet the requirements, generating a standard adjustment signal and sending the standard adjustment signal to the mobile terminal of the management personnel; if the structure optimization value is less than the structure optimization threshold and the standard adjustment value is less than the standard adjustment threshold, it is determined that the drug storage environment of the drug storage bin in the anesthesiology department meets the requirements, marking the L1 storage areas with the smallest test coefficient Tc value as high-quality areas, and sending the high-quality areas to the storage management module.

[0051] Further, the specific process of the storage management module managing and analyzing the drug storage space of the drugs in the anesthesiology department includes: marking the special drugs in the drugs in the anesthesiology department; matching and storing the special drugs with the high-quality areas, and then classifying and storing the remaining drugs in the anesthesiology department into the remaining storage areas according to the drug types.

[0052] The present invention also provides an electronic device, including a memory and a processor, the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the method for managing the storage of drugs in the anesthesiology department based on artificial intelligence as described above.

[0053] The present invention also provides a computer storage medium on which a computer program is stored. When the computer program is executed, the artificial intelligence-based anesthesia drug storage management method as described above is implemented.

[0054] The present invention has the following beneficial effects:

[0055] 1. The method and system of the present invention can test and analyze the storage environment of the anesthesia drug storage warehouse, collect the environmental parameters of each storage area in a regional test manner, and obtain the test coefficient of the storage area after numerical processing and calculation, so as to provide feedback on the environmental suitability of the storage area during the test period through the test coefficient, and provide data support for the test evaluation process;

[0056] 2. The method and system of the present invention can evaluate and analyze the storage environment test data of the anesthesiology drug storage warehouse, and perform numerical processing on the test coefficients of all storage areas to obtain the standard adjustment value and structural optimization value of the test cycle. The standard adjustment value indicates the rationality of the parameters of the environmental control mechanism of the anesthesiology drug storage warehouse, and the structural optimization value indicates the rationality of the spatial design of the anesthesiology drug storage warehouse, thereby directly generating a targeted abnormal processing decision signal when the storage environment is abnormal;

[0057] 3. The method and system of the present invention can manage and analyze the storage space of anesthesiology drugs, match special drugs with high-quality areas, so that drugs with high storage environment requirements can be stored in storage areas with more stable environments, and combine the storage status monitoring and analysis process to achieve dynamic optimization of drug types and storage areas, continuously ensure the overall storage status of anesthesiology drugs, and reduce the probability of drug deterioration during storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] 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.

[0059] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0060] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0061] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] Embodiment 1

[0063] like Figure 1 As shown, an artificial intelligence-based anesthesiology drug storage management system includes a regional testing module, a test evaluation module, a storage management module and a storage monitoring module. The regional testing module, the test evaluation module, the storage management module and the storage monitoring module are communicatively connected in sequence.

[0064] The regional test module is used to test and analyze the storage environment of the anesthesia drug storage warehouse:

[0065] The anesthesia drug storage warehouse is divided into several storage areas, each of which is equipped with an environmental adjustment mechanism;

[0066] Adjust the parameters of the environmental control mechanism of the anesthesia drug storage warehouse to the corresponding standard values. The environmental control mechanism includes fans, temperature controllers, humidifiers, etc.;

[0067] Then, a test cycle is generated for each storage area; a plurality of test points are set in each storage area, and the air temperature value, air humidity value and air dust concentration value of each test point are obtained in real time during the test cycle as the environmental test data;

[0068] Calculate the temperature difference value Tdeviation according to the air temperature value of each storage area;

[0069] Calculate the humidity difference value H bias according to the air humidity value of each storage area;

[0070] Calculate the dust concentration value Dconcentration according to the air dust concentration value of each storage area;

[0071] The test coefficient Tc is calculated according to the temperature difference value Tb, humidity difference value Hb and ash concentration value Dc of each area during the test cycle. The specific calculation formula is:

[0072]

[0073] Among them, m1, m2, and m3 are all proportional coefficients, and m1>m2>m3>1.

[0074] The process of obtaining the temperature difference value T deviation includes: setting several test points in the storage area, obtaining the air temperature values of the test points in real time, retrieving the standard temperature range of the anesthesiology drug storage bin, marking the average value of the maximum and minimum values of the standard temperature range as the temperature standard value, marking the absolute value of the difference between the air temperature value of the test point and the temperature standard value as the temperature difference value of the test point, and marking the maximum value of the temperature difference values of all test points in the storage area during the test period as the temperature difference value T deviation;

[0075] The process of obtaining the humidity difference value H deviation includes: obtaining the air humidity values of the test points in real time, retrieving the standard humidity range of the anesthesiology drug storage bin, marking the average value of the maximum and minimum values of the standard humidity range as the humidity standard value, marking the absolute value of the difference between the air humidity value of the test point and the humidity standard value as the humidity difference value of the test point, and marking the maximum value of the humidity difference values of all test points in the storage area during the test period as the humidity difference value H deviation;

[0076] The process of obtaining the ash concentration value D concentration includes: obtaining the air dust concentration values of the test points in real time, and marking the maximum value of the air dust concentration values of all test points in the storage area during the test period as the ash concentration value D concentration;

[0077] Send the test coefficients Tc of all storage areas to the test evaluation module;

[0078] The test evaluation module is used to test and analyze the storage environment of the anesthesiology drug storage bin, collect the environmental parameters of each storage area in the way of sub-region testing, obtain the test coefficients of the storage area after numerical processing and calculation, so as to feedback the environmental suitability of the storage area during the test period through the test coefficients, and provide data support for the test evaluation process.

[0079] The test evaluation module is used to evaluate and analyze the test data of the storage environment of the anesthesiology drug storage bin: sum and average the test coefficients Tc of all storage areas to obtain the standard adjustment value;

[0080] Calculate the variance of the test coefficients Tc of all storage areas to obtain the structure optimization value;

[0081] The standard adjustment value and the structural optimization value are compared with the preset standard adjustment threshold and the structural optimization threshold respectively: if the structural optimization value is greater than or equal to the structural optimization threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse does not meet the requirements, and a space optimization signal is generated and sent to the mobile terminal of the administrator. The environmental status of each storage area is uneven, that is, the storage warehouse needs to be spatially optimized to reduce the difference in environmental status between different storage areas; if the structural optimization value is less than the structural optimization threshold and the standard adjustment value is greater than or equal to the standard adjustment threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse does not meet the requirements, and a standard adjustment signal is generated and sent to the mobile terminal of the administrator. When there are a large number of storage areas that do not meet the requirements in the storage warehouse, the environmental adjustment mechanism needs to be The standard parameters are adjusted and corrected to match the standard parameters of the environmental control mechanism with the storage bin; if the structural optimization value is less than the structural optimization threshold and the standard adjustment value is less than the standard adjustment threshold, it is determined that the drug storage environment of the anesthesiology drug storage bin meets the requirements, and the L1 storage areas with the smallest test coefficient Tc values ​​are marked as high-quality areas, and the high-quality areas are sent to the storage management module; the storage environment test data of the anesthesiology drug storage bin are evaluated and analyzed, and the test coefficients of all storage areas are numerically processed to obtain the standard adjustment value and structural optimization value of the test cycle. The standard adjustment value indicates the rationality of the parameters of the environmental control mechanism of the anesthesiology drug storage bin, and the structural optimization value indicates the rationality of the space design of the anesthesiology drug storage bin, so that targeted abnormal handling decision signals can be directly generated when the storage environment is abnormal.

[0082] The storage management module is used to manage and analyze the storage space of anesthesia drugs:

[0083] Special drugs in the anesthesiology department are marked. Special drugs include drugs that are about to expire, volatile drugs, opened drugs, and emergency drugs. The time judgment limit for drugs that are about to expire and the boiling point judgment limit for volatile drugs are set by the management personnel. Special drugs are matched and stored in high-quality areas, and then the remaining anesthesia drugs are classified according to the type of drugs and stored in the remaining storage areas.

[0084] The storage monitoring module is used to monitor and analyze the storage status of anesthesia drugs:

[0085] Generate a storage cycle, and at the end of the storage cycle, perform quality inspection on the anesthesia drugs in the anesthesia drug storage warehouse, mark the deteriorated and damaged anesthesia drugs as quality inspection objects, and mark the number of anesthesia drugs of the same type marked as quality inspection objects as the quality inspection value of the drug type, then obtain the test coefficient Tc of each storage area during the storage cycle, arrange the storage areas outside the high-quality area in order from small to large according to the test coefficient Tc value to obtain a drug sequence, arrange the drug types of anesthesia drugs in order from large to small according to the quality inspection value to obtain a type sequence, match the drug sequence with the storage areas and drug types with the same sequence number in the type sequence, and update the storage area of ​​the drug type after the matching is completed; manage and analyze the drug storage space of anesthesia drugs, match special drugs with high-quality areas, so that drugs with high storage environment requirements can be stored in storage areas with more stable environments, and realize dynamic optimization of drug types and storage areas in combination with the storage status monitoring and analysis process, continuously ensure the overall storage status of anesthesia drugs, and reduce the probability of drug deterioration during storage.

[0086] An anesthesiology drug storage management system based on artificial intelligence, when working, divides an anesthesia drug storage warehouse into several storage areas, generates a test cycle for each storage area, obtains the temperature difference value T bias, humidity difference value H bias and ash concentration value D concentration of the storage area during the test cycle, and performs numerical calculation to obtain the test coefficient Tc; evaluates and analyzes the storage environment test data of the anesthesia drug storage warehouse and obtains the standard adjustment value and the structure optimization value, and judges whether the drug storage environment of the anesthesia drug storage warehouse meets the requirements through the standard adjustment value and the structure optimization value; marks special drugs in the anesthesia drugs, matches and stores the special drugs with high-quality areas; generates a storage cycle, performs quality inspection on the anesthesia drugs in the anesthesia drug storage warehouse at the end of the storage cycle, and updates the storage area of ​​the drug type according to the quality inspection result.

[0087] Embodiment 2

[0088] like Figure 2 As shown, the specific steps of an anesthesia drug storage management method based on artificial intelligence in this embodiment include:

[0089] S110. Test and analyze the storage environment of the anesthesia department's drug storage warehouse, specifically:

[0090] The anesthesia drug storage bin is divided into several storage areas, each storage area is provided with an environmental adjustment mechanism; the parameters of each environmental adjustment mechanism are adjusted to the corresponding standard values; a test cycle is generated for each storage area; the storage environment of each storage area is tested respectively during the test cycle to obtain environmental test data of each storage area; and the test coefficient Tc of each storage area during the test cycle is obtained according to the environmental test data of each storage area;

[0091] The environmental adjustment mechanism may include fans, temperature controllers, humidifiers, and the like.

[0092] S120, evaluating and analyzing the test coefficient Tc of the anesthesiology drug storage bin to obtain a standard adjustment value and a structural optimization value, and determining whether the storage environment of the anesthesiology drug storage bin meets the requirements based on the standard adjustment value and the structural optimization value;

[0093] S130. Manage and analyze the storage space for anesthesiology drugs.

[0094] In an optional implementation, the storage environment of each storage area is tested separately within the test cycle to obtain environmental test data of each storage area, specifically including:

[0095] Several test points are set in each storage area, and the air temperature value, air humidity value and air dust concentration value of each test point are obtained in real time during the test cycle as the environmental test data.

[0096] In an optional implementation manner, obtaining a test coefficient Tc of each storage area in a test cycle according to environmental test data of each storage area specifically includes:

[0097] Calculate the temperature difference value Tdeviation according to the air temperature value of each storage area;

[0098] Calculate the humidity difference value H bias according to the air humidity value of each storage area;

[0099] Calculate the dust concentration value Dconcentration according to the air dust concentration value of each storage area;

[0100] The test coefficient Tc is calculated according to the temperature difference value Tb, humidity difference value Hb and ash concentration value Dc of each area during the test cycle. The specific calculation formula is:

[0101]

[0102] Among them, m1, m2, and m3 are all proportional coefficients, and m1>m2>m3>1.

[0103] In an optional implementation, the calculating of the temperature difference value Tdeviation according to the air temperature values ​​of each storage area specifically includes:

[0104] Retrieve the standard temperature range of the anesthesia drug storage bin, and mark the average of the maximum and minimum values ​​of the standard temperature range as the temperature standard value;

[0105] The absolute value of the difference between the air temperature value at the test point and the temperature standard value is marked as the temperature difference value of the test point;

[0106] The maximum value of the temperature difference of all test points in the storage area during the test cycle is marked as the temperature difference value T deviation;

[0107] And / or, calculating the humidity difference value H bias according to the air humidity values ​​of each storage area, specifically including:

[0108] Retrieve the standard humidity range of the anesthesiology drug storage bin, and mark the average of the maximum and minimum values ​​of the standard humidity range as the humidity standard value;

[0109] The absolute value of the difference between the air humidity value at the test point and the humidity standard value is marked as the humidity difference value of the test point;

[0110] The maximum value of the humidity difference of all test points in the storage area during the test cycle is marked as the humidity difference value H bias;

[0111] And / or, calculating the dust concentration value Dconcentrate according to the air dust concentration value of each storage area, specifically including:

[0112] The maximum value of the air dust concentration values ​​at all test points in the storage area during the test cycle is marked as the dust concentration value Dconcentrate.

[0113] In an optional implementation, the test coefficients Tc of all storage areas are summed and averaged to obtain a standard adjustment value, and the test coefficients Tc of all storage areas are calculated for variance to obtain a structural optimization value.

[0114] In an optional implementation, the standard adjustment value and the structure optimization value are used to determine whether the storage environment of the anesthesia drug storage bin meets the requirements. Specifically, the standard adjustment value and the structure optimization value are compared with the preset standard adjustment threshold and the structure optimization threshold, respectively. The comparison process is as follows:

[0115] If the structural optimization value is greater than or equal to the structural optimization threshold, it is determined that the drug storage environment of the anesthesia department's drug storage warehouse does not meet the requirements, and a space optimization signal is generated and sent to the mobile phone terminal of the manager. The environmental status of each storage area is uneven, that is, the storage warehouse needs to be spatially optimized to reduce the differences in environmental status between different storage areas;

[0116] If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is greater than or equal to the standard adjustment threshold, it is determined that the drug storage environment of the anesthesia department's drug storage warehouse does not meet the requirements, and a standard adjustment signal is generated and sent to the administrator's mobile phone terminal. When there are a large number of storage areas that do not meet the requirements in the storage warehouse, it is necessary to adjust and correct the standard parameters of the environment adjustment mechanism so that the standard parameters of the environment adjustment mechanism match the storage warehouse;

[0117] If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is less than the standard adjustment threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse meets the requirements, and the L1 storage areas with the smallest test coefficient Tc value are marked as high-quality areas, and the high-quality areas are stored and managed.

[0118] The storage environment test data of the anesthesiology drug storage warehouse is evaluated and analyzed, and the test coefficients of all storage areas are numerically processed to obtain the standard adjustment value and structural optimization value of the test cycle. The standard adjustment value indicates the rationality of the parameters of the environmental control mechanism of the anesthesiology drug storage warehouse, and the structural optimization value indicates the rationality of the space design of the anesthesiology drug storage warehouse. Therefore, targeted abnormal handling decision signals can be directly generated when the storage environment is abnormal.

[0119] In an optional implementation, the management and analysis of the storage space for anesthesia drugs and the marking of special drugs in anesthesia drugs specifically include:

[0120] Special drugs are matched and stored with high-quality areas, and then the remaining anesthesia drugs other than special drugs are classified according to drug types and stored in various remaining storage areas other than the high-quality areas.

[0121] Among them, the special drugs include drugs that are about to expire, volatile drugs, opened drugs and emergency drugs. The time judgment limit of drugs that are about to expire and the boiling point judgment limit of volatile drugs are set by the management personnel.

[0122] In an optional implementation manner, the method of this embodiment further includes:

[0123] Monitor and analyze the storage status of anesthesiology drugs: generate a storage cycle, perform quality inspection on anesthesia drugs in the anesthesia drug storage bin at the end of the storage cycle, and update the storage area for each drug type based on the quality inspection results.

[0124] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0125] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; for example: Formula

[0126] A technician in this field collects multiple groups of sample data and sets corresponding test coefficients for each group of sample data; substitutes the set test coefficients and the collected sample data into the formula, and any three formulas constitute a three-variable linear equation system. The calculated coefficients are screened and averaged, and the values ​​of m1, m2, and m3 are obtained to be 4.65, 2.87, and 2.14, respectively;

[0127] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding test coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the test coefficient is proportional to the value of the temperature difference.

[0128] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0129] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An artificial intelligence-based anesthesia drug storage management method, characterized in that: The method comprises: S110. Test and analyze the storage environment of the anesthesia department's drug storage warehouse, specifically: The anesthesia drug storage bin is divided into several storage areas, each storage area is provided with an environmental adjustment mechanism; the parameters of each environmental adjustment mechanism are adjusted to the corresponding standard values; a test cycle is generated for each storage area; the storage environment of each storage area is tested respectively during the test cycle to obtain environmental test data of each storage area; and the test coefficient Tc of each storage area during the test cycle is obtained according to the environmental test data of each storage area; S120, evaluating and analyzing the test coefficient Tc of the anesthesiology drug storage bin to obtain a standard adjustment value and a structural optimization value, and determining whether the storage environment of the anesthesiology drug storage bin meets the requirements based on the standard adjustment value and the structural optimization value; S130. Manage and analyze the storage space for anesthesia drugs; During the test cycle, the storage environment of each storage area is tested respectively to obtain the environmental test data of each storage area, specifically including: A plurality of test points are set in each storage area, and the air temperature value, air humidity value and air dust concentration value of each test point are obtained in real time during the test cycle as the environmental test data; The step of obtaining the test coefficient Tc of each storage area in the test cycle according to the environmental test data of each storage area specifically includes: Calculate the temperature difference value based on the air temperature values ​​of each storage area ; Calculate humidity difference value based on air humidity value of each storage area ; Calculate the dust concentration value based on the air dust concentration value of each storage area ; According to the temperature difference value of each area during the test cycle , humidity difference Ash concentration Calculate the test coefficient Tc, the specific calculation formula is: in are proportionality coefficients, and ; The test coefficients Tc of all storage areas are summed and averaged to obtain the standard adjustment value, and the variance of the test coefficients Tc of all storage areas is calculated to obtain the structural optimization value; The standard adjustment value and the structure optimization value are used to determine whether the storage environment of the anesthesia drug storage bin meets the requirements. Specifically, the standard adjustment value and the structure optimization value are compared with the preset standard adjustment threshold and the structure optimization threshold, respectively. The comparison process is as follows: If the structural optimization value is greater than or equal to the structural optimization threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse does not meet the requirements, and a space optimization signal is generated and sent to the mobile phone terminal of the manager; If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is greater than or equal to the standard adjustment threshold, it is determined that the drug storage environment of the anesthesia department's drug storage warehouse does not meet the requirements, and a standard adjustment signal is generated and sent to the mobile phone terminal of the administrator; If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is less than the standard adjustment threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse meets the requirements, and the L1 storage areas with the smallest test coefficient Tc value are marked as high-quality areas, and the high-quality areas are stored and managed.

2. The method for storing and managing anesthesia drugs based on artificial intelligence according to claim 1, characterized in that: The temperature difference value is calculated according to the air temperature value of each storage area , specifically including: Retrieve the standard temperature range of the anesthesia drug storage bin, and mark the average of the maximum and minimum values ​​of the standard temperature range as the temperature standard value; The absolute value of the difference between the air temperature value at the test point and the temperature standard value is marked as the temperature difference value of the test point; The maximum value of the temperature difference of all test points in the storage area during the test cycle is marked as the temperature difference value. ; And / or, calculate humidity difference values ​​based on the air humidity values ​​of each storage area , specifically including: Retrieve the standard humidity range of the anesthesiology drug storage bin, and mark the average of the maximum and minimum values ​​of the standard humidity range as the humidity standard value; The absolute value of the difference between the air humidity value at the test point and the humidity standard value is marked as the humidity difference value of the test point; The maximum value of the humidity difference of all test points in the storage area during the test cycle is marked as the humidity difference value. ; And / or, calculate the dust concentration value based on the air dust concentration value of each storage area , specifically including: The maximum value of the air dust concentration of all test points in the storage area during the test cycle is marked as the dust concentration value. .

3. The method for storing and managing anesthesia drugs based on artificial intelligence according to claim 1, characterized in that: The management and analysis of the storage space for anesthesia drugs and the marking of special drugs in anesthesia drugs specifically include: Special drugs are matched and stored with high-quality areas, and then the remaining anesthesia drugs other than special drugs are classified according to drug types and stored in various remaining storage areas other than the high-quality areas.

4. An artificial intelligence-based anesthesia drug storage management system, characterized in that: It includes a regional test module, a test evaluation module and a storage management module, wherein the regional test module, the test evaluation module and the storage management module are sequentially connected in communication; The regional test module is used to test and analyze the storage environment of the anesthesia drug storage warehouse: the anesthesia drug storage warehouse is divided into several storage areas, each storage area is provided with an environmental adjustment mechanism; the parameters of the environmental adjustment mechanism of the anesthesia drug storage warehouse are adjusted to the corresponding standard values; a test cycle is generated for each storage area, and the storage environment of each storage area is tested separately during the test cycle to obtain the environmental test data of each storage area; the test coefficient Tc of each storage area during the test cycle is obtained according to the environmental test data of each storage area; the test coefficient Tc of all storage areas is sent to the test evaluation module; The test evaluation module is used to evaluate and analyze the test coefficient Tc of the anesthesiology drug storage bin and obtain the standard adjustment value and the structural optimization value, and to determine whether the storage environment of the anesthesiology drug storage bin meets the requirements through the standard adjustment value and the structural optimization value; The storage management module is used to manage and analyze the storage space of anesthesia drugs; During the test cycle, the storage environment of each storage area is tested respectively to obtain the environmental test data of each storage area, specifically including: A plurality of test points are set in each storage area, and the air temperature value, air humidity value and air dust concentration value of each test point are obtained in real time during the test cycle as the environmental test data; The step of obtaining the test coefficient Tc of each storage area in the test cycle according to the environmental test data of each storage area specifically includes: Calculate the temperature difference value based on the air temperature values ​​of each storage area ; Calculate humidity difference value based on air humidity value of each storage area ; Calculate the dust concentration value based on the air dust concentration value of each storage area ; The regional test module is used to calculate the test coefficient Tc in the following manner: obtaining the temperature difference value of the storage area during the test cycle , humidity difference Ash concentration ; Through the formula Get the test coefficient Tc of the storage area in the test cycle, where are proportionality coefficients, and ; The test coefficient Tc of the anesthesia drug storage bin is evaluated and analyzed to obtain the standard adjustment value and the structural optimization value, specifically including: The test coefficients Tc of all storage areas are summed and averaged to obtain the standard adjustment value, and the variance of the test coefficients Tc of all storage areas is calculated to obtain the structural optimization value; The standard adjustment value and the structure optimization value are used to determine whether the storage environment of the anesthesia drug storage bin meets the requirements. Specifically, the standard adjustment value and the structure optimization value are compared with the preset standard adjustment threshold and the structure optimization threshold, respectively. The comparison process is as follows: If the structural optimization value is greater than or equal to the structural optimization threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse does not meet the requirements, and a space optimization signal is generated and sent to the mobile phone terminal of the manager; If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is greater than or equal to the standard adjustment threshold, it is determined that the drug storage environment of the anesthesia department's drug storage warehouse does not meet the requirements, and a standard adjustment signal is generated and sent to the mobile phone terminal of the administrator; If the structural optimization value is less than the structural optimization threshold and the standard adjustment value is less than the standard adjustment threshold, it is determined that the drug storage environment of the anesthesiology drug storage warehouse meets the requirements, and the L1 storage areas with the smallest test coefficient Tc value are marked as high-quality areas, and the high-quality areas are stored and managed.

5. The anesthesia drug storage management system based on artificial intelligence according to claim 4 is characterized in that: Temperature difference The acquisition process includes: setting several test points in the storage area, obtaining the air temperature value of the test points in real time, calling the standard temperature range of the anesthesia drug storage bin, marking the average of the maximum and minimum values ​​of the standard temperature range as the temperature standard value, marking the absolute value of the difference between the air temperature value of the test point and the temperature standard value as the temperature difference value of the test point, and marking the maximum value of the temperature difference value of all test points in the storage area during the test cycle as the temperature difference value. ; Humidity difference The acquisition process includes: obtaining the air humidity value of the test point in real time, calling the standard humidity range of the anesthesia drug storage bin, marking the average of the maximum and minimum values ​​of the standard humidity range as the humidity standard value, marking the absolute value of the difference between the air humidity value of the test point and the humidity standard value as the humidity difference value of the test point, and marking the maximum value of the humidity difference values ​​of all test points in the storage area during the test cycle as the humidity difference value. ; Ash concentration The acquisition process includes: obtaining the air dust concentration value of the test point in real time, marking the maximum value of the air dust concentration value of all test points in the storage area during the test cycle as the dust concentration value .

6. An electronic device comprising a memory and a processor, characterized in that: The memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the artificial intelligence-based anesthesia drug storage management method as described in any one of claims 1-3.

7. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, it implements the artificial intelligence-based anesthesia drug storage management method as described in any one of claims 1-3.

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