A scheduling method for anesthesia drugs

Abstract

The present invention relates to the technical field of scheduling of anesthesia drugs, and specifically discloses a scheduling method for anesthesia drugs, which realizes intelligent and standardized scheduling management of anesthetic drugs through the following stages: acquiring data of each operation, analyzing historical usage status parameters of anesthetic drugs to predict demand and derive pre-allocated values, acquiring a prescription for anesthetic drugs issued by a doctor and monitoring the patient's physical condition information at the same time to obtain a prescription review value, and determining a drug dispensing signal based on the pre-allocated value and the review value, then monitoring the doctor's voice status parameters to determine the anesthetic drug demand state to generate a corresponding signal, identifying and analyzing the anesthetic drug appearance state parameters to determine the recycling processing state to generate a corresponding recycling processing signal, and finally, recording and storing information data of anesthetic drugs used in the operation; thereby achieving the improvement of the safety and efficiency of the operation, optimizing resource allocation, and providing strong support for the improvement of anesthesia drug distribution scheduling.

Description

Technical Field

[0001] The present invention relates to the technical field of scheduling of anesthesia drugs, and in particular to a scheduling method for anesthesia drugs. Background Art

[0002] With the continuous advancement of medical technology, the status of anesthesiology in surgery has become increasingly prominent. Anesthetic drugs, as a key element in surgery, are of vital importance in ensuring patient safety, improving surgical outcomes, and promoting postoperative recovery. However, in actual operations, the scheduling and management of anesthetic drugs still faces many challenges and problems.

[0003] First, the lack of standardized processes is one of the main reasons for the irrational allocation of anesthetic drugs. Due to the lack of unified management regulations and operating standards, different hospitals and doctors have differences in the dispatch of anesthetic drugs, which not only affects the rational use of drugs, but also may threaten the safety of patients.

[0004] Secondly, poor communication is an important factor affecting errors in drug information transmission and anesthesia effects. Information transmission between anesthesiologists, doctors, nurses and other members of the surgical team is crucial to ensuring the smooth progress of the operation. However, in actual work, due to poor communication or untimely information transmission, drugs may not be prepared in time or errors may occur, thus affecting patient safety and surgical effects. Summary of the invention

[0005] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides a scheduling method for anesthesia drugs, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method for scheduling anesthesia drugs, comprising the following steps:

[0008] Step 1: Plan pre-allocation: Obtain the data of each operation in the current monitoring period of the target hospital, and obtain and analyze the historical usage status parameters of the anesthetic drugs corresponding to each operation. Based on this, perform forecast demand analysis and processing to obtain the pre-allocation value of the anesthetic drugs corresponding to each operation;

[0009] Step 2: Prescription review: Obtain and analyze the anesthetic prescriptions issued by the doctors for each surgery, and monitor and analyze the patient's physical condition information for each surgery to obtain the influencing factor coefficient, thereby reviewing and analyzing the anesthetic prescription status issued by the doctors for each surgery to obtain the review value of the anesthetic prescription issued by the doctors for each surgery;

[0010] Step 3: Drug distribution: Based on the pre-allocated value of the anesthetic drug corresponding to each operation and the audit value of the anesthetic drug prescription issued by the doctor corresponding to each operation, the drug distribution is judged and analyzed to obtain the anesthetic drug distribution signal and the early warning reminder signal;

[0011] Step 4: Usage monitoring: monitor and analyze the voice status parameters of the doctors in the operating room corresponding to each surgery to obtain the target demand preparation level, thereby determining and analyzing the anesthetic drug demand status in the operating room corresponding to each surgery, and obtaining the anesthetic drug preparation signal and the anesthetic drug re-issuance signal;

[0012] Step 5: Recovery and processing: Identify and analyze the appearance state parameters of the anesthetic drugs in the operating room corresponding to each surgery, thereby determining and analyzing the recovery and processing state of the anesthetic drugs in the operating room corresponding to each surgery, and obtain corresponding recovery and processing signals accordingly;

[0013] Step 6: Record and store: record and store the information data of the anesthetic drugs used in each operation.

[0014] Furthermore, the process of solving the pre-allocated values ​​of anesthetic drugs corresponding to each operation is as follows:

[0015] By extracting the surgical type features, surgical time features, and patient information features from the surgical data of each operation in the current monitoring time period of the target hospital, each feature corresponds to a preset evaluation value, and all the identified features are matched to the corresponding preset evaluation values ​​and summed to obtain the basic evaluation value of each operation, and the basic evaluation value of each operation is compared and matched with the basic state determination table stored in the cloud database, thereby obtaining the basic state level of each operation, and each basic evaluation value obtained for each operation corresponds to a basic state level, and at the same time, it is matched with the historical use state parameters of the anesthetic drugs corresponding to the basic state level, thereby obtaining the historical use state parameters of the anesthetic drugs corresponding to each operation;

[0016] Extract the average dosage value, average time value, and average frequency value of the historical usage status parameters of the anesthetic drugs corresponding to each operation, and mark them as ksz jk ,shz jk and spz jk , j represents the number of each operation, j = 1, 2, 3 ... n, n represents the total number of operation numbers, k represents the number of each type of anesthetic drug, k = 1, 2, 3 ... m, m represents the total number of each type of anesthetic drug number, extract the values ​​of the three for normalization, according to the formula:

[0017] The pre-assigned value YFP of the anesthetic drug corresponding to each operation is obtained, where λ represents a natural constant, and They respectively represent the weight coefficients of average usage value, average time value, and average frequency value.

[0018] Furthermore, the process of solving the audit value of the anesthetic prescription issued by the doctor for each operation is as follows:

[0019] The anesthetic prescriptions issued by the doctors for each surgery in the current monitoring period of the target hospital are obtained, and the patient's physical status information corresponding to each surgery in the current monitoring period of the target hospital is obtained. The patient's physical information includes blood pressure, body temperature and heart rate. The values ​​of blood pressure, body temperature and heart rate are extracted and multiplied by the corresponding weight coefficients respectively, and then added to obtain the influencing factor coefficient, which is recorded as δ; the prescription time is extracted from the anesthetic prescriptions issued by the doctors for each surgery in the current monitoring period of the target hospital, and the actual operation time is obtained. The difference between the prescription time and the actual operation time is calculated to obtain the drug evaluation value, which is recorded as yhz jk ; Extract the dosage and type of anesthetic drugs from the anesthetic drug prescriptions issued by the corresponding doctors for each surgery in the current monitoring period of the target hospital, and record them as dosage value and type value, and record them as dosage value dgz jk and the value of zzs jk ; Extract impact factor coefficient δ, drug evaluation and value yhz jk , dosage value dgz jk and the value of zzs jk The value of is normalized according to the formula: The audited value SHZ of the anesthetic drug prescription issued by the corresponding doctor for each operation is obtained, e1, e2, e3 are all expressed as natural constants, μ1, μ2 and μ3 represent the weight coefficients of drug evaluation value, dosage value and species value respectively, and μ2>μ1>μ3.

[0020] Furthermore, the specific process of determining and analyzing drug distribution is as follows:

[0021] The pre-allocated value YFP of the anesthetic drug corresponding to each operation and the audit value SHZ of the anesthetic drug prescription issued by the doctor for each operation are extracted and normalized according to the formula: A matching value PA is obtained, wherein φ1 and φ2 represent preset weight factor coefficients;

[0022] Setting a comparison reference interval for the matching value, comparing and analyzing the matching value with the comparison reference interval, generating an anesthetic drug release signal when the matching value is within the comparison reference interval, and generating an early warning reminder signal when the matching value is outside the comparison reference interval;

[0023] According to the captured anesthetic drug delivery signal, the anesthetic drug delivery instruction is triggered, and according to the triggered anesthetic drug delivery instruction, the required anesthetic drugs are delivered to the corresponding operating room within the set F time period, and step four is executed;

[0024] Based on the captured early warning reminder signal, a text message notification instruction is triggered, and based on the triggered text message notification instruction, relevant personnel are notified via text message. The relevant personnel may be pharmacists, doctors or other relevant managers to remind them to pay attention to abnormal situations or potential problems in the distribution of anesthetic drugs.

[0025] Furthermore, the specific process of determining and analyzing the anesthetic drug demand status in the operating room corresponding to each operation is as follows: by real-time monitoring and acquiring the content of the doctor's speech in the operating room corresponding to each operation, the content of the doctor's speech in the operating room corresponding to each operation is obtained, and at the same time, the content related to the use of anesthetic drugs is extracted from the content of the doctor's speech, and the content related to the use of anesthetic drugs is split into text to obtain a text set of the content related to the use of anesthetic drugs, and each word of the content related to the use of anesthetic drugs is extracted from the text set of the content related to the use of anesthetic drugs, and each word of the content related to the use of anesthetic drugs is matched with the word set corresponding to the interference words stored in the cloud database to obtain each interference word of the content related to the use of anesthetic drugs, and each interference word is eliminated to obtain each marked word of the content related to the use of anesthetic drugs, and then each marked word of the content related to the use of anesthetic drugs is matched with the word set corresponding to the anesthetic drug demand preparation level table stored in the cloud database, the number of successfully matched words is counted, and the anesthetic drug demand preparation level corresponding to the anesthetic drug demand preparation level table with the largest number of successfully matched words is marked as the target demand preparation level;

[0026] Among them, the anesthetic drug demand preparation level includes level one demand preparation, level two demand preparation and level three demand preparation. When the target demand preparation level is level one demand preparation or level two demand preparation, an anesthetic drug preparation signal is generated. When the target demand preparation level is level three demand preparation, an anesthetic drug re-issuance signal is generated.

[0027] Furthermore, the specific process of determining and analyzing the recovery and processing status of the anesthetic drugs in the operating room corresponding to each operation is as follows:

[0028] By collecting all the anesthetic drug images in the operating room corresponding to each surgery, we can obtain a set of anesthetic drug images in the operating room corresponding to each surgery, and identify the number of dirty places of anesthetic drugs, which is recorded as N. jk , and at the same time obtain the total contaminated area of ​​anesthetic drugs, recorded as S jk .

[0029] The bacterial content of the anesthetic drugs in the operating room corresponding to each surgery was tested by a bacteria detector to obtain the bacterial content of the anesthetic drugs in the operating room corresponding to each surgery, which was recorded as C jk , according to the formula:

[0030] The recovery and processing status evaluation index HCL of the anesthetic drugs in the operating room corresponding to each operation is obtained, where e is expressed as a natural constant, and N * , S * and C * They represent the number of allowed dirty places, the total area of ​​allowed dirty places, and the allowed bacterial content stored in the database, respectively. a1, a2, and a3 represent the set weight factors, respectively.

[0031] Compare and analyze the recovery and processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation with the set recovery and processing state evaluation index threshold value, and generate a Class A recovery and processing signal when the recovery and processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation is greater than the set recovery and processing state evaluation index threshold value;

[0032] When the recovery processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation is equal to the set recovery processing state evaluation index threshold, a Class B recovery processing signal is generated;

[0033] When the recovery processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation is less than the set recovery processing state evaluation index threshold, a Class C recovery processing signal is generated.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention extracts relevant features from the data of each operation in the current monitoring time period of the target hospital and analyzes them to obtain the basic evaluation value of each operation. According to the basic evaluation value of each operation, it is compared and matched with the basic state determination table stored in the cloud database. The basic state determination table contains various basic state levels, and each basic state level stores the historical use state parameters of the corresponding anesthetic drugs. Thus, the historical use state parameters of the anesthetic drugs corresponding to each operation are obtained, and the historical use state parameters of the anesthetic drugs corresponding to each operation are analyzed and processed to obtain the pre-allocated value of the anesthetic drugs corresponding to each operation, thereby providing strong data support for the subsequent formulation of effective drug scheduling and allocation decision analysis;

[0036] By extracting and analyzing the data information in the anesthetic prescriptions issued by the doctors for each surgery in the current monitoring period of the target hospital, and monitoring and analyzing the physical status information of the patients corresponding to each surgery, the anesthetic prescription status issued by the doctors for each surgery is reviewed and analyzed, and the review value of the anesthetic prescription issued by the doctors for each surgery is obtained. Based on the pre-allocated value of the anesthetic corresponding to each surgery, the matching degree of the two data is analyzed to obtain the matching value. If the matching value is within the preset comparison reference interval, the anesthetic is issued, otherwise an early warning notification is issued. This analysis method can automatically match the pre-allocated value and the review value, reduce human intervention and errors, improve the intelligent level of decision-making, and provide a more scientific and accurate decision-making basis for drug scheduling;

[0037] By monitoring the voice status parameters of doctors in the operating room, the system can analyze the demand status of anesthetic drugs in real time, thereby ensuring the timely supply of drug scheduling and helping to reduce the risks caused by drug shortages or delays;

[0038] By identifying and analyzing the appearance status parameters of anesthetic drugs, the recovery and processing status of anesthetic drugs can be automatically determined. Different recovery and processing signals can be generated based on the comparison between the evaluation index and the set threshold value to guide the hospital to classify and process anesthetic drugs, thereby helping to improve the hospital's management efficiency of anesthetic drugs, reduce drug waste and pollution, and record and store information data on anesthetic drugs used in each operation, thereby achieving comprehensive traceability of anesthetic drug use, which not only helps hospitals optimize the management of anesthetic drugs, but also can continuously optimize planned pre-allocation operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0040] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0041] The technical solution of the present invention will be described clearly and completely in conjunction with the embodiments below. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. 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. Figure 1 As shown, a scheduling method for anesthesiology drugs includes:

[0042] Step 1: Plan pre-allocation: Obtain the data of each operation in the current monitoring period of the target hospital, and obtain and analyze the historical usage status parameters of the anesthetic drugs corresponding to each operation, and perform forecast demand analysis and processing based on this. The specific operation process is as follows:

[0043] By extracting the surgical type features, surgical time features, and patient information features from the surgical data of each operation in the current monitoring time period of the target hospital, each feature corresponds to a preset evaluation value, and all the identified features are matched to the corresponding preset evaluation values ​​and summed to obtain the basic evaluation value of each operation, and the basic evaluation value of each operation is compared and matched with the basic state determination table stored in the cloud database, thereby obtaining the basic state level of each operation, and each basic evaluation value obtained for each operation corresponds to a basic state level, and at the same time, it is matched with the historical use state parameters of the anesthetic drugs corresponding to the basic state level, thereby obtaining the historical use state parameters of the anesthetic drugs corresponding to each operation;

[0044] Extract the average dosage value, average time value, and average frequency value of the historical usage status parameters of the anesthetic drugs corresponding to each operation, and mark them as ksz jk ,shz jk and spz jk , j represents the number of each operation, j = 1, 2, 3 ... n, n represents the total number of operation numbers, k represents the number of each type of anesthetic drug, k = 1, 2, 3 ... m, m represents the total number of each type of anesthetic drug number, extract the values ​​of the three for normalization, according to the formula:

[0045] The pre-assigned value YFP of the anesthetic drug corresponding to each operation is obtained, where λ represents a natural constant, and They represent the weight coefficients of the average usage value, the average time value, and the average frequency value, respectively, and The weight coefficient is used to balance the weight of each data in the formula calculation, thereby promoting the accuracy of the calculation results;

[0046] It should be noted that the average dosage value refers to the average amount of anesthetic drugs used in surgery over a period of time, the average duration value refers to the average duration of anesthetic drug use, and the average frequency value refers to the frequency of anesthetic drug use;

[0047] Step 2: Prescription review: Obtain and analyze the anesthetic prescriptions issued by the doctors for each surgery, and then review and analyze the status of the anesthetic prescriptions issued by the doctors for each surgery. The specific operation process is as follows:

[0048] The anesthetic prescriptions issued by the doctors for each surgery in the current monitoring period of the target hospital are obtained, and the patient's physical status information corresponding to each surgery in the current monitoring period of the target hospital is obtained. The patient's physical information includes blood pressure, body temperature and heart rate. The values ​​of blood pressure, body temperature and heart rate are extracted and multiplied by the corresponding weight coefficients respectively, and then added to obtain the influencing factor coefficient, which is recorded as δ; the prescription time is extracted from the anesthetic prescriptions issued by the doctors for each surgery in the current monitoring period of the target hospital, and the actual operation time is obtained. The difference between the prescription time and the actual operation time is calculated to obtain the drug evaluation value, which is recorded as yhz jk ; Extract the dosage and type of anesthetic drugs from the anesthetic drug prescriptions issued by the corresponding doctors for each surgery in the current monitoring period of the target hospital, and record them as the dosage value dgz jk and the value of zzs jk ;

[0049] Extract impact factor coefficient δ, drug review and value yhz jk , dosage value dgz jk and the value of zzs jk The value of is normalized according to the formula: The audit value SHZ of the anesthetic drug prescription issued by the doctor for each operation is obtained, e1, e2, and e3 are all expressed as natural constants, μ1, μ2, and μ3 represent the weight coefficients of drug evaluation value, dosage value, and species value, respectively, and μ2>μ1>μ3. The weight coefficient is used to balance the weight of each data in the formula calculation, thereby promoting the accuracy of the calculation result;

[0050] It should be noted that the impact factor coefficient comprehensively considers the patient's physical condition information and is used to evaluate the patient's sensitivity to and possible reactions to anesthetic drugs. The drug evaluation value reflects the timeliness of the prescription and its matching degree with the surgery. The dosage value indicates the amount of anesthetic drugs required for each surgery and is a key parameter for evaluating whether the drug use is appropriate. The species value indicates the number of anesthetic drugs in the prescription.

[0051] Step 3: Drug distribution: Based on the pre-allocated value YFP of the anesthetic drug corresponding to each surgery and the audit value SHZ of the anesthetic drug prescription issued by the doctor for each surgery, the drug distribution is judged and analyzed. The specific operation process is as follows:

[0052] The pre-allocated value YFP of the anesthetic drug corresponding to each operation and the audit value SHZ of the anesthetic drug prescription issued by the doctor for each operation are extracted and normalized according to the formula: A matching value PA is obtained, wherein φ1 and φ2 represent preset weight factor coefficients;

[0053] The comparison reference interval of the matching value is set to QJ, and the matching value PA is compared and analyzed with the comparison reference interval QJ. When the matching value PA is within the comparison reference interval QJ, an anesthetic drug release signal is generated, and when the matching value PA is outside the comparison reference interval QJ, an early warning reminder signal is generated;

[0054] According to the captured anesthetic drug delivery signal, the anesthetic drug delivery instruction is triggered, and according to the triggered anesthetic drug delivery instruction, the required anesthetic drugs are delivered to the corresponding operating room within the set F time period, and step 4 is executed; wherein, the F time period is pre-set and ensures that the anesthetic drugs can be delivered to the operating room at the appropriate time;

[0055] According to the captured early warning reminder signal, a text message notification instruction is triggered, and according to the triggered text message notification instruction, a relevant person is notified via text message. The relevant person may be a pharmacist, a doctor or other relevant management personnel, so as to remind them to pay attention to abnormal conditions or potential problems in the dispensing of anesthetic drugs. The setting of specific relevant persons can be set by technical personnel in this field according to actual conditions;

[0056] Step 4: Usage monitoring: Monitor and analyze the voice status parameters of the doctors in the operating room corresponding to each surgery, and thereby determine and analyze the anesthetic drug demand status in the operating room corresponding to each surgery. The specific operation process is as follows:

[0057] The contents of the doctors' speeches in the operating rooms corresponding to the respective surgeries are acquired by real-time monitoring, thereby obtaining the contents of the doctors' speeches in the operating rooms corresponding to the respective surgeries, and extracting the contents related to the use of anesthetic drugs from the contents of the doctors' speeches, and performing text segmentation on the contents related to the use of anesthetic drugs to obtain a text set of the contents related to the use of anesthetic drugs, extracting the words related to the contents related to the use of anesthetic drugs from the text set of the contents related to the use of anesthetic drugs, matching the words related to the contents related to the use of anesthetic drugs with the word set corresponding to the interference words stored in the cloud database to obtain the interference words related to the contents related to the use of anesthetic drugs, and eliminating the interference words to obtain the marked words related to the contents related to the use of anesthetic drugs, and then matching the marked words related to the contents related to the use of anesthetic drugs with the word set corresponding to the anesthetic drug demand preparation level table stored in the cloud database, counting the number of words that are successfully matched, and calibrating the anesthetic drug demand preparation level corresponding to the anesthetic drug demand preparation level table having the largest number of successfully matched words as the target demand preparation level;

[0058] Among them, the anesthetic drug demand preparation level includes first-level demand preparation, second-level demand preparation and third-level demand preparation. When the target demand preparation level is first-level demand preparation or second-level demand preparation, an anesthetic drug preparation signal is generated, and the required anesthetic drugs are prepared according to the generated drug preparation signal. When the target demand preparation level is third-level demand preparation, an anesthetic drug re-issuance signal is generated, and the required anesthetic drugs are issued to the corresponding operating room according to the generated anesthetic drug re-issuance signal.

[0059] Step 5: Recycling: Identify and analyze the appearance parameters of the anesthetic drugs in the operating room corresponding to each surgery, and then determine and analyze the recycling status of the anesthetic drugs in the operating room corresponding to each surgery. The specific operation process is as follows: The anesthetic drug images in the operating room corresponding to each surgery are collected in all directions by the intelligent camera to obtain the image set of the anesthetic drugs in the operating room corresponding to each surgery, and identify the number of dirty places of the anesthetic drugs, which is recorded as N. jk , and at the same time obtain the total contaminated area of ​​anesthetic drugs, recorded as S jk .

[0060] The bacterial content of the anesthetic drugs in the operating room corresponding to each surgery was tested by a bacteria detector to obtain the bacterial content of the anesthetic drugs in the operating room corresponding to each surgery, which was recorded as C jk , according to the formula:

[0061] The recovery and processing status evaluation index HCL of the anesthetic drugs in the operating room corresponding to each operation is obtained, where e is expressed as a natural constant, and N * , S * and C * They represent the number of allowed dirty places, the total area of ​​allowed dirty places, and the allowed bacterial content stored in the database, respectively. a1, a2, and a3 represent the set weight factors, respectively.

[0062] Compare and analyze the recovery and processing status evaluation index of the anesthetic drugs in the operating room corresponding to each operation with the set recovery and processing status evaluation index threshold; when the recovery and processing status evaluation index of the anesthetic drugs in the operating room corresponding to each operation is greater than the set recovery and processing status evaluation index threshold, a Class A recovery and processing signal is generated; when the recovery and processing status evaluation index of the anesthetic drugs in the operating room corresponding to each operation is equal to the set recovery and processing status evaluation index threshold, a Class B recovery and processing signal is generated; when the recovery and processing status evaluation index of the anesthetic drugs in the operating room corresponding to each operation is less than the set recovery and processing status evaluation index threshold, a Class C recovery and processing signal is generated;

[0063] Step 6: Record and store: record and store the information data of the anesthetic drugs used in each operation.

[0064] 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. A method for scheduling anesthesia drugs, characterized in that: The following steps are involved: Step 1: Plan pre-allocation: Obtain the data of each operation in the current monitoring period of the target hospital, and obtain and analyze the historical usage status parameters of the anesthetic drugs corresponding to each operation. Based on this, perform forecast demand analysis and processing to obtain the pre-allocation value of the anesthetic drugs corresponding to each operation; Step 2: Prescription review: Obtain and analyze the anesthetic prescriptions issued by the doctors for each surgery, and monitor and analyze the patient's physical condition information for each surgery to obtain the influencing factor coefficient, thereby reviewing and analyzing the anesthetic prescription status issued by the doctors for each surgery to obtain the review value of the anesthetic prescription issued by the doctors for each surgery; Step 3: Drug distribution: Based on the pre-allocated value of the anesthetic drug corresponding to each operation and the audit value of the anesthetic drug prescription issued by the doctor corresponding to each operation, the drug distribution is judged and analyzed to obtain the anesthetic drug distribution signal and the early warning reminder signal; Step 4: Usage monitoring: monitor and analyze the voice status parameters of the doctors in the operating room corresponding to each surgery to obtain the target demand preparation level, thereby determining and analyzing the anesthetic drug demand status in the operating room corresponding to each surgery, and obtaining the anesthetic drug preparation signal and the anesthetic drug re-issuance signal; Step 5: Recovery and processing: Identify and analyze the appearance state parameters of the anesthetic drugs in the operating room corresponding to each surgery, thereby determining and analyzing the recovery and processing state of the anesthetic drugs in the operating room corresponding to each surgery, and obtain corresponding recovery and processing signals accordingly; Step 6: Record and store: record and store the information data of anesthetic drugs used in each operation; The process of obtaining and analyzing the historical usage status parameters of anesthetic drugs corresponding to each operation and conducting forecast demand analysis based on them is as follows: By extracting the surgical type features, surgical time features, and patient information features from the surgical data of each operation in the current monitoring time period of the target hospital, each feature corresponds to a preset evaluation value, and all the identified features are matched to the corresponding preset evaluation values ​​and summed to obtain the basic evaluation value of each operation, and the basic evaluation value of each operation is compared and matched with the basic state determination table stored in the cloud database, thereby obtaining the basic state level of each operation, and each basic evaluation value obtained for each operation corresponds to a basic state level, and at the same time, it is matched with the historical use state parameters of the anesthetic drugs corresponding to the basic state level, thereby obtaining the historical use state parameters of the anesthetic drugs corresponding to each operation; Extract the average dosage value, average time value, and average frequency value of the historical usage status parameters of the anesthetic drugs corresponding to each operation, and mark them as ksz jk ,shz jk and spz jk , j represents the number of each operation, j=1, 2, 3...n, n represents the total number of operation numbers, k represents the number of each type of anesthetic drug, k=1, 2, 3...m, m represents the total number of each type of anesthetic drug number, extract the values ​​of the three for normalization, according to the formula: , and obtain the pre-assigned value YFP of the anesthetic drug corresponding to each operation, where λ represents a natural constant, Respectively represent the weight coefficients of average usage value, average time value and average frequency value; The process of solving the audit value of the anesthetic prescription issued by the doctor for each operation is as follows: The anesthetic prescriptions issued by the doctors for each surgery in the current monitoring time period of the target hospital are obtained, and the patient's physical condition information corresponding to each surgery in the current monitoring time period of the target hospital is obtained. The patient's physical information includes blood pressure, body temperature and heart rate. The values ​​of blood pressure, body temperature and heart rate are extracted and multiplied by the corresponding weight coefficients and then added to obtain the influencing factor coefficient; the prescription time is extracted from the anesthetic prescriptions issued by the doctors for each surgery in the current monitoring time period of the target hospital, and the actual operation time is obtained at the same time, and the difference between the prescription time and the actual operation time is calculated to obtain the drug evaluation value; the dosage and number of types of anesthetic drugs are extracted from the anesthetic prescriptions issued by the doctors for each surgery in the current monitoring time period of the target hospital, and they are recorded as dosage value and type value respectively; The influencing factor coefficient, drug evaluation value, dosage value and species value are extracted and normalized and calculated to obtain the audit value of the anesthetic drug prescription issued by the doctor for each operation.

2. A method for scheduling anesthesia drugs according to claim 1, characterized in that: The specific process of determining and analyzing drug delivery is as follows: Extract the pre-allocated value of the anesthetic drug corresponding to each surgery and the audit value of the anesthetic drug prescription issued by the doctor corresponding to each surgery, perform normalization calculation and processing, and obtain the matching value; A comparison reference interval is set for the matching value, and the matching value is compared and analyzed with the comparison reference interval. When the matching value is within the comparison reference interval, an anesthetic drug release signal is generated; when the matching value is outside the comparison reference interval, an early warning reminder signal is generated.

3. A method for scheduling anesthesia drugs according to claim 1, characterized in that: The specific process of determining and analyzing the anesthetic drug demand status in the operating room for each operation is as follows: The contents of the doctors' speeches in the operating rooms corresponding to the respective surgeries are acquired by real-time monitoring, thereby obtaining the contents of the doctors' speeches in the operating rooms corresponding to the respective surgeries, and extracting the contents related to the use of anesthetic drugs from the contents of the doctors' speeches, and performing text segmentation on the contents related to the use of anesthetic drugs to obtain a text set of the contents related to the use of anesthetic drugs, extracting the words related to the contents related to the use of anesthetic drugs from the text set of the contents related to the use of anesthetic drugs, matching the words related to the contents related to the use of anesthetic drugs with the word set corresponding to the interference words stored in the cloud database to obtain the interference words related to the contents related to the use of anesthetic drugs, and eliminating the interference words to obtain the marked words related to the contents related to the use of anesthetic drugs, and then matching the marked words related to the contents related to the use of anesthetic drugs with the word set corresponding to the anesthetic drug demand preparation level table stored in the cloud database, counting the number of words that are successfully matched, and calibrating the anesthetic drug demand preparation level corresponding to the anesthetic drug demand preparation level table having the largest number of successfully matched words as the target demand preparation level; Among them, the anesthetic drug demand preparation level includes level one demand preparation, level two demand preparation and level three demand preparation. When the target demand preparation level is level one demand preparation or level two demand preparation, an anesthetic drug preparation signal is generated. When the target demand preparation level is level three demand preparation, an anesthetic drug re-issuance signal is generated.

4. A method for scheduling anesthesia drugs according to claim 1, characterized in that: The specific process of determining and analyzing the recovery and processing status of anesthetic drugs in the operating room corresponding to each operation is as follows: By collecting all the anesthetic drug images in the operating room corresponding to each surgery, we can obtain a set of anesthetic drug images in the operating room corresponding to each surgery, and identify the number of dirty places of anesthetic drugs, which is recorded as N. jk , and at the same time obtain the total contamination area of ​​anesthetic drugs, recorded as S jk ; The bacterial content of the anesthetic drugs in the operating room corresponding to each surgery was tested by a bacteria detector to obtain the bacterial content of the anesthetic drugs in the operating room corresponding to each surgery, which was recorded as C jk , according to the formula: , the recovery and processing status evaluation index HCL of the anesthetic drugs in the operating room corresponding to each operation is obtained, e is expressed as a natural constant, N * , S * and C * They represent the number of allowed dirty places, the total area of ​​allowed dirty places, and the allowed bacterial content stored in the database, respectively. a1, a2, and a3 represent the set weight factors, respectively. Compare and analyze the recovery and processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation with the set recovery and processing state evaluation index threshold value, and generate a Class A recovery and processing signal when the recovery and processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation is greater than the set recovery and processing state evaluation index threshold value; When the recovery processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation is equal to the set recovery processing state evaluation index threshold, a Class B recovery processing signal is generated; When the recovery processing state evaluation index of the anesthetic drugs in the operating room corresponding to each operation is less than the set recovery processing state evaluation index threshold, a Class C recovery processing signal is generated.

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