A drug information tracking method and system based on statistical amplification model

Abstract

The present invention relates to the technical field of drug information tracking, and in particular to a drug information tracking method and system based on a statistical amplification model. The present invention counts each drug transport bill at the drug cold chain storage end, determines whether there are unstable drugs through corresponding drug information, determines whether there is a temperature control risk in the transportation of unstable drugs by obtaining the distance between the transport destinations corresponding to the drug transport bill, determines the transportation risk feature category of unstable drugs by calculating the risk superposition characterization coefficient, determines key risk drugs by the number of drug cargoes corresponding to the unstable drugs, determines the transportation mode of key risk drugs based on different transportation risk feature categories, and thus realizes the screening of drugs with poor resistance to temperature fluctuations, and adjusts the drug transportation mode in a targeted manner according to the drug transportation data, thereby realizing refined management and scientific planning of drug transportation.

Description

Technical Field

[0001] The present invention relates to the technical field of drug information tracking, and in particular to a drug information tracking method and system based on a statistical amplification model. Background Art

[0002] In the medical industry, the tracking and management of drug information is crucial. Traditional drug tracking methods mainly rely on RFID technology. By attaching RFID tags to drugs, the storage, distribution and use of drugs can be tracked in real time. For the cold chain delivery of special drugs, it is necessary to meet the high requirements of the cold chain temperature and the timeliness of delivery. In order to more effectively monitor and analyze various interferences in the circulation of cold chain stored drugs, it is necessary to count and analyze various information data that affect drug delivery, so as to achieve comprehensive monitoring of the drug circulation process and scientific planning of the delivery method.

[0003] For example, China Patent Publication No.: CN103208056A, the invention discloses a drug traceability system based on trajectory tracking and its drug traceability method, the system includes a trajectory tracking platform and a trajectory data collection terminal and a traceability terminal deployed on the supply chain node; the trajectory data collector reads the trajectory data and electronic evidence data of the drug when it flows through the supply chain node, and transmits it to the drug trajectory tracking platform; the drug trajectory tracking platform integrates the trajectory data and evidence data of the drug, and stores them in the traceability database; combined with the drug traceability method of the invention, the user can obtain the trajectory data and evidence data of the corresponding batch of drugs through the human-computer interaction interface of the traceability terminal.

[0004] The prior art still has the following problems:

[0005] The existing technology does not take into account the unloading process of cold chain drug transportation, resulting in poor temperature control during the transportation of drugs that have poor resistance to temperature fluctuations, and cannot adjust the drug delivery method in a targeted manner based on the drug delivery data, which is not conducive to the refined management of drug delivery. Summary of the invention

[0006] To this end, the present invention provides a drug information tracking method and system based on a statistical amplification model to overcome the problems in the prior art that drugs with poor resistance to temperature fluctuations cannot be screened and the drug delivery method cannot be adjusted in a targeted manner according to the drug delivery data.

[0007] To achieve the above object, the present invention provides a drug information tracking method based on a statistical amplification model, comprising:

[0008] Counting each drug delivery bill at the drug cold chain storage end, obtaining drug information corresponding to each drug delivery bill, and determining whether there is an unstable drug based on the drug information;

[0009] The drug information includes the storage time of the drug, the destination of the drug, and the quantity of the drug;

[0010] Obtain the delivery destinations corresponding to each drug delivery bill of the unstable drug, and determine whether there is a temperature control risk in the delivery of the unstable drug based on the distance between each delivery destination;

[0011] In response to the temperature control risk in the transportation of the unstable drug, a risk superposition characterization coefficient is calculated based on the quantity of drug cargo corresponding to each drug transportation bill of the unstable drug and the distance between drug transportation destinations to determine the transportation risk characteristic category of the unstable drug;

[0012] Determine the key risk drugs based on the quantity of drug cargo corresponding to each drug delivery bill of unstable drugs, and determine the delivery method of the key risk drugs based on different delivery risk feature categories, including:

[0013] Determining a delivery route for the critical risk drug based on a drug delivery destination corresponding to the critical risk drug;

[0014] Alternatively, the critical risk drugs may be delivered separately.

[0015] Furthermore, the steps of counting the delivery orders of each drug at the drug cold chain storage end include:

[0016] Receive medicines and record the time when the medicines enter cold chain storage;

[0017] Receive drug orders from various drug sales outlets to obtain drug delivery destinations and drug cargo quantities;

[0018] Determine the storage time of the drugs corresponding to each drug order in the cold chain storage based on the time when the drugs enter the cold chain storage;

[0019] The drug delivery destination, drug cargo quantity and drug storage time are determined as the drug information corresponding to the drug delivery bill.

[0020] Furthermore, the process of determining whether there is an unstable drug includes:

[0021] Comparing the drug storage time with a preset drug storage time threshold;

[0022] If the drug storage time is less than the drug storage time threshold, it is determined that there is an unstable drug.

[0023] Furthermore, the process of determining whether there is a temperature control risk in the transportation of unstable drugs includes:

[0024] Obtaining the distances between the delivery destinations, calculating the average distance value, and comparing the average distance value with a preset average distance value threshold;

[0025] If the distance average value is less than the distance average value threshold, it is determined that there is a temperature control risk in the transportation of unstable drugs.

[0026] Furthermore, the risk superposition characterization coefficient is calculated according to the following formula:

[0027]

[0028] Among them, S is the risk superposition characterization coefficient, m is the quantity of the drug goods, and m 0 is the preset reference value of the quantity of pharmaceutical goods, d min is the minimum distance between the delivery destinations, d 0 is the preset reference value of the distance between the delivery destinations, α is the weight coefficient of the quantity of pharmaceutical goods, β is the weight coefficient of the distance between the delivery destinations, and e is a constant.

[0029] Furthermore, the process of determining the transport risk characteristic category of the unstable drug includes:

[0030] Compare the maximum value of the risk superposition characterization coefficient with a preset risk superposition characterization coefficient threshold;

[0031] If the maximum value of the risk superposition characterization coefficient is less than or equal to the risk superposition characterization coefficient threshold value, it is determined that the transportation risk characteristic category of the unstable drug is a transportation weak risk characteristic category;

[0032] If the maximum value of the risk superposition characterization coefficient is greater than the risk superposition characterization coefficient threshold, the transportation risk characteristic category of the unstable drug is determined to be a transportation strong risk characteristic category.

[0033] Further, the process of determining the delivery method for critical risk drugs includes:

[0034] If the unstable drug is of a weak risk characteristic category, determining a delivery route for the critical risk drug based on a drug delivery destination corresponding to the critical risk drug;

[0035] If the unstable drug is of a category with strong risk characteristics for transportation, the key risk drug shall be transported separately.

[0036] Furthermore, the process of determining the delivery route of the critical risk drugs includes:

[0037] The drug delivery destination corresponding to the critical risk drug is determined as the end point of the delivery route.

[0038] Furthermore, the process of identifying key risk drugs includes:

[0039] The quantity of drug cargo corresponding to each drug delivery bill of unstable drugs is obtained, and the drug corresponding to the maximum drug cargo quantity is determined as the key risk drug.

[0040] Furthermore, the present invention also provides a drug information tracking system based on a statistical amplification model, which is characterized by comprising:

[0041] Data statistics module, used to obtain drug information;

[0042] Several data analysis modules, connected to the data statistics module, for determining the risk characteristic category of drug transportation based on the drug information;

[0043] Several processing modules are connected to the data analysis module to determine the delivery mode of the drug.

[0044] Compared with the prior art, the beneficial effects of the present invention lie in that the present invention counts the drug delivery lists at the drug cold chain storage end, determines whether there are unstable drugs through corresponding drug information, obtains the delivery destinations corresponding to the drug delivery lists, determines whether there is a temperature control risk in the delivery of unstable drugs based on the distances between the delivery destinations, calculates the risk superposition characterization coefficient to determine the delivery risk characteristic category of unstable drugs, determines key risk drugs through the number of drug cargoes corresponding to unstable drugs, determines the delivery methods of key risk drugs based on different delivery risk characteristic categories, thereby achieving screening of drugs with poor resistance to temperature fluctuations, and targeted adjustment of drug delivery methods according to drug delivery data, thereby achieving refined management and scientific planning of drug delivery.

[0045] In particular, the present invention determines whether there are unstable drugs by the storage time of the drugs. Those skilled in the art will understand that the longer the drugs that need to be refrigerated are stored in the cold chain, the higher the temperature consistency between the outside and inside of the drug package. Conversely, the shorter the cold chain storage time of the drugs that need to be refrigerated, the higher the possibility of a difference between the external and internal temperatures of the drug package. The present invention determines whether the storage status of the drugs is stable by the storage time of the drugs, thereby achieving the screening of drugs with poor resistance to temperature fluctuations.

[0046] In particular, the present invention determines whether there is a temperature control risk in the transportation of drugs by the distance between the delivery destinations of unstable drugs. In the actual cold chain transportation of drugs, if there is a temperature difference between the inside and outside of the drug package, and the distance intervals between the delivery destinations of these drugs are relatively close, then frequent drug unloading needs will affect the temperature control state of cold chain stored drugs. The present invention compares the distance between the delivery destinations of unstable drugs with a preset threshold value, and uses the distance between the drug destinations to characterize the density of drug unloading needs, thereby realizing risk assessment for the transportation of drugs with poor resistance to temperature fluctuations.

[0047] In particular, the present invention determines the transportation risk characteristic category of unstable drugs by calculating the risk superposition characterization coefficient. Those skilled in the art can understand that in the actual cold chain transportation process of drugs, the more drugs in each drug transportation bill of unstable drugs, the longer the unloading time of the unstable drugs, and the longer the time of affecting the temperature of the drugs. Similarly, the closer the distance between the drug transportation destinations, the more frequent the impact on the cold chain temperature control in a short period of time. The present invention combines multiple data with amplified calculations to achieve the characterization of the degree of temperature control impact of cold chain storage drugs that are difficult to characterize.

[0048] In particular, in the case where the risk of drug transportation is relatively small, the larger the quantity of drug cargo, the longer the unloading time required, resulting in worse temperature control of unstable drugs. The present invention transports drugs with large quantities last to avoid affecting the temperature control of other transported drugs, while extending their time in the cold chain transportation, reducing possible temperature differences between the outside and inside of the packaging, ensuring the delivery quality of drugs, and realizing targeted adjustment of drug delivery methods based on drug delivery data, thereby realizing refined management and scientific planning of drug transportation.

[0049] In particular, in the case where the transportation risk of medicines is relatively high, the larger the quantity of medicine cargo is, the greater the possibility that the quality will be affected by temperature during the unloading process. The present invention ensures the transportation quality of medicines with a temperature difference between the outside and inside of the package by independently transporting unstable medicines with relatively high transportation risks, and achieves targeted adjustment of the medicine transportation method according to the medicine transportation data, thereby realizing refined management and scientific planning of medicine transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a step diagram of a drug information tracking method based on a statistical amplification model according to an embodiment of the present invention;

[0051] Figure 2 A diagram showing the steps of counting the shipping bills of each drug at the drug cold chain storage end according to an embodiment of the present invention;

[0052] Figure 3 A logic flow chart for determining whether there is a temperature control risk in the transportation of unstable drugs according to an embodiment of the present invention;

[0053] Figure 4 The present invention is a logical flow chart for determining the shipping risk feature category of unstable drugs according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0056] It should be noted that in the description of the present invention, the terms "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0057] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0058] See also Figure 1 As shown, it is a step diagram of a drug information tracking method based on a statistical amplification model according to an embodiment of the present invention. A drug information tracking method based on a statistical amplification model according to an embodiment of the present invention includes:

[0059] Step S100, counting each drug delivery bill at the drug cold chain storage end, obtaining drug information corresponding to each drug delivery bill, and determining whether there is an unstable drug based on the drug information;

[0060] The drug information includes the storage time of the drug, the destination of the drug, and the quantity of the drug;

[0061] Step S200, obtaining the delivery destinations corresponding to the delivery bills of the unstable drugs, and determining whether there is a temperature control risk in the delivery of the unstable drugs based on the distances between the delivery destinations;

[0062] Step S300, in response to the temperature control risk in the transportation of the unstable drug, a risk superposition characterization coefficient is calculated based on the quantity of drug cargo corresponding to each drug transportation bill of the unstable drug and the distance between drug transportation destinations, so as to determine the transportation risk characteristic category of the unstable drug;

[0063] Step S400, determining the critical risk drugs based on the quantity of drug cargo corresponding to each drug delivery bill of unstable drugs, and determining the delivery method of the critical risk drugs based on different delivery risk feature categories, including:

[0064] Determining a delivery route for the critical risk drug based on a drug delivery destination corresponding to the critical risk drug;

[0065] Alternatively, the critical risk drugs may be delivered separately.

[0066] Specifically, in the embodiment of the present invention, the quantity of pharmaceutical cargo can be determined according to the number of pharmaceutical cargo boxes.

[0067] Specifically, see Figure 2 As shown, it is a step diagram of counting the delivery orders of each drug at the drug cold chain storage end according to an embodiment of the present invention. In step S100, the step of counting the delivery orders of each drug at the drug cold chain storage end includes:

[0068] Step S101, receiving the medicine and recording the time when the medicine enters the cold chain storage;

[0069] Step S102, receiving drug orders from various drug sales terminals to obtain drug delivery destinations and drug cargo quantities;

[0070] Step S103, determining the storage time of the drugs corresponding to each drug order in the cold chain storage based on the time when the drugs enter the cold chain storage;

[0071] Step S104, determining the drug delivery destination, drug cargo quantity and drug storage time as drug information corresponding to the drug delivery bill.

[0072] Specifically, in the embodiment of the present invention, data information of the RFID tag of the medicine can be read, and the data information stored in the RFID tag of the medicine includes the time when the medicine enters the cold chain storage.

[0073] Specifically, in step S100, the process of determining whether there is an unstable drug includes:

[0074] Comparing the drug storage time with a preset drug storage time threshold;

[0075] If the storage time of the drug is greater than or equal to the drug storage time threshold, it is determined that there is no unstable drug;

[0076] If the drug storage time is less than the drug storage time threshold, it is determined that there is an unstable drug.

[0077] Specifically, the present invention determines whether there are unstable drugs by the storage time of the drugs. Those skilled in the art will understand that the longer the drugs that need to be refrigerated are stored in the cold chain, the higher the temperature consistency between the outside and inside of the drug package. Conversely, the shorter the cold chain storage time of the drugs that need to be refrigerated, the higher the possibility of a difference between the external and internal temperatures of the drug package. The present invention determines whether the storage status of the drugs is stable by the storage time of the drugs, thereby achieving the screening of drugs with poor resistance to temperature fluctuations.

[0078] In an embodiment of the present invention, the drug storage time threshold is based on the results of preliminary tests by technicians in this field. The temperature difference curve between the inside and outside of the package of the same type of drugs entering the cold chain storage is pre-tested over time to obtain the time required for the temperature difference between the inside and outside of several packages to reach the preset requirements. The average time obtained from several experiments is determined as the drug storage time threshold.

[0079] Specifically, see Figure 3 As shown, it is a logic flow chart for determining whether there is a temperature control risk in the transportation of unstable drugs according to an embodiment of the present invention. In step S200, the process of determining whether there is a temperature control risk in the transportation of unstable drugs includes:

[0080] Obtain the distance between each of the transport destinations, calculate the average distance, and compare the average distance with the preset average distance threshold d a Make a comparison;

[0081] If the distance average is greater than or equal to the distance average threshold d a , it is determined that there is no temperature control risk in the transportation of unstable drugs;

[0082] If the average distance is less than the average distance threshold d a , it is determined that there is a temperature control risk in the transportation of unstable drugs.

[0083] In the embodiment of the present invention, the distance average value threshold d a Total route mileage based on the delivery route d s OK, a =ε×d s, where ε is the distance average threshold determination factor, and the value range of ε is [0.05, 0.2].

[0084] Specifically, the present invention determines whether there is a temperature control risk in the transportation of drugs by the distance between the delivery destinations of unstable drugs. In the actual cold chain transportation of drugs, if there is a temperature difference between the inside and outside of the drug package, and the distance intervals between the delivery destinations of these drugs are relatively close, then frequent drug unloading needs will affect the temperature control state of cold chain stored drugs. The present invention compares the distance between the delivery destinations of unstable drugs with a preset threshold value, and uses the distance between the drug destinations to characterize the density of drug unloading needs, thereby realizing risk assessment of the transportation of drugs with poor resistance to temperature fluctuations.

[0085] Specifically, in step S300, the risk superposition characterization coefficient is calculated according to the following formula:

[0086]

[0087] Among them, S is the risk superposition characterization coefficient, m is the quantity of the drug goods, and m 0 is the preset reference value of the quantity of pharmaceutical goods, d min is the minimum distance between the delivery destinations, d 0 is the preset reference value of the distance between the delivery destinations, α is the weight coefficient of the quantity of pharmaceutical goods, β is the weight coefficient of the distance between the delivery destinations, α+β=1, and e is a constant.

[0088] In the embodiment of the present invention, the reference value m of the quantity of the medicines 0 The average value of the quantity of medicines corresponding to several medicine delivery orders is calculated in advance, and the average value is determined as the reference value m of the quantity of medicines 0 , the reference distance d between the delivery destinations 0 Total route mileage based on the delivery route d s OK, 0 =δ×d 0 , where δ is the distance reference value determination factor, and the value range of δ is [0.05, 0.1].

[0089] The weight coefficient α for the quantity of pharmaceutical cargo and the weight coefficient β for the distance between the delivery destinations are selected by technical personnel in this field based on the degree of influence of the quantity of pharmaceutical cargo and the distance between the delivery destinations in historical data on the calculation results. Preferably, the weight coefficient α for the quantity of pharmaceutical cargo and the weight coefficient β for the distance between the delivery destinations can be set to 0.4, and the weight coefficient β for the distance between the delivery destinations can be set to 0.6.

[0090] Specifically, the present invention determines the transportation risk characteristic category of unstable drugs by calculating the risk superposition characterization coefficient. Those skilled in the art can understand that in the actual cold chain transportation process of drugs, the more drugs in each drug transportation bill of unstable drugs, the longer the unloading time of the unstable drugs, and the longer the time of affecting the temperature of the drugs. Similarly, the closer the distance between the drug transportation destinations, the more frequent the impact on the cold chain temperature control in a short period of time. The present invention combines multiple data with amplified calculations to achieve the characterization of the degree of temperature control impact of cold chain storage drugs that are difficult to characterize.

[0091] Specifically, see Figure 4 As shown, it is a logic flow chart of determining the transportation risk characteristic category of unstable drugs according to an embodiment of the present invention. In step S300, the process of determining the transportation risk characteristic category of the unstable drugs includes:

[0092] The maximum value S of the risk superposition characterization coefficient max The preset risk superposition coefficient threshold S 0 Make a comparison;

[0093] If the maximum value of the risk superposition characterization coefficient S max Less than or equal to the risk superposition characterization coefficient threshold S 0 , then the transportation risk characteristic category of the unstable drug is determined to be a weak transportation risk characteristic category;

[0094] If the maximum value of the risk superposition characterization coefficient S max Greater than the risk superposition characterization coefficient threshold S 0 , then the transportation risk characteristic category of the unstable drug is determined to be a transportation strong risk characteristic category.

[0095] In this embodiment of the present invention, the risk superposition characterization coefficient threshold S 0 The value range is [1.1, 1.15].

[0096] Specifically, in step S400, the process of determining the delivery method of the critical risk drugs includes:

[0097] If the unstable drug is of a weak risk characteristic category, determining a delivery route for the critical risk drug based on a drug delivery destination corresponding to the critical risk drug;

[0098] If the unstable drug is of a category with strong risk characteristics for transportation, the key risk drug shall be transported separately.

[0099] Specifically, in the case where the transportation risk of medicines is relatively high, the larger the quantity of medicine cargo is, the greater the possibility that the quality will be affected by temperature during the unloading process. The present invention ensures the transportation quality of medicines with a temperature difference between the outside and inside of the package by independently transporting unstable medicines with relatively high transportation risks, and achieves targeted adjustment of the medicine transportation method according to the medicine transportation data, thereby realizing refined management and scientific planning of medicine transportation.

[0100] Specifically, in step S400, the process of determining the delivery route of the critical risk drug includes:

[0101] The drug delivery destination corresponding to the critical risk drug is determined as the end point of the delivery route.

[0102] Specifically, in the case where the risk of drug transportation is relatively small, the larger the quantity of drug cargo, the longer the unloading time required, resulting in worse temperature control of unstable drugs. The present invention transports drugs with a large quantity last to avoid affecting the temperature control of other transported drugs, while extending their time in the cold chain transportation, reducing possible temperature differences between the outside and inside of the package, ensuring the delivery quality of the drugs, and realizing targeted adjustment of the drug delivery method according to the drug delivery data, thereby realizing refined management and scientific planning of drug transportation.

[0103] Specifically, in step S400, the process of determining key risk drugs includes:

[0104] The quantity of drug cargo corresponding to each drug delivery bill of unstable drugs is obtained, and the drug corresponding to the maximum drug cargo quantity is determined as the key risk drug.

[0105] Specifically, the present invention further provides a drug information tracking system based on a statistical amplification model, which is used to execute a drug information tracking method based on a statistical amplification model in the above embodiment, including:

[0106] Data statistics module, used to obtain drug information;

[0107] Several data analysis modules, connected to the data statistics module, for determining the risk characteristic category of drug transportation based on the drug information;

[0108] Several processing modules are connected to the data analysis module to determine the delivery mode of the drug.

[0109] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A drug information tracking method based on a statistical amplification model, characterized in that: include: Counting each drug delivery bill at the drug cold chain storage end, obtaining drug information corresponding to each drug delivery bill, and determining whether there is an unstable drug based on the drug information; The drug information includes the storage time of the drug, the destination of the drug, and the quantity of the drug; The process of determining whether an unstable drug exists includes: Comparing the drug storage time with a preset drug storage time threshold; If the storage time of the drug is less than the drug storage time threshold, it is determined that there is an unstable drug; Obtain the delivery destinations corresponding to each drug delivery bill of the unstable drug, and determine whether there is a temperature control risk in the delivery of the unstable drug based on the distance between each delivery destination; The process of determining whether the transportation of unstable drugs poses a temperature control risk includes: Obtaining the distances between the delivery destinations, calculating the average distance value, and comparing the average distance value with a preset average distance value threshold; If the average distance value is less than the average distance value threshold, it is determined that there is a temperature control risk in the transportation of the unstable drug; In response to the temperature control risk in the transportation of the unstable drug, a risk superposition characterization coefficient is calculated based on the quantity of drug cargo corresponding to each drug transportation bill of the unstable drug and the distance between drug transportation destinations to determine the transportation risk characteristic category of the unstable drug; The risk superposition characterization coefficient is calculated according to the following formula; Wherein, S is the risk superposition characterization coefficient, m is the quantity of the pharmaceutical goods, m0 is the preset reference value of the quantity of the pharmaceutical goods, d min is the minimum distance between the delivery destinations, d0 is the preset reference distance between the delivery destinations, α is the weight coefficient of the quantity of pharmaceutical goods, β is the weight coefficient of the distance between the delivery destinations, and e is a constant; Determine the key risk drugs based on the quantity of drug cargo corresponding to each drug delivery bill of unstable drugs, and determine the delivery method of the key risk drugs based on different delivery risk feature categories, including: Determining a delivery route for the critical risk drug based on a drug delivery destination corresponding to the critical risk drug; Alternatively, the critical risk drugs may be delivered separately.

2. The drug information tracking method based on the statistical amplification model according to claim 1 is characterized in that: The steps for counting the delivery orders of each drug at the drug cold chain storage end include: Receive medicines and record the time when the medicines enter cold chain storage; Receive drug orders from various drug sales outlets to obtain drug delivery destinations and drug cargo quantities; Determine the storage time of the drugs corresponding to each drug order in the cold chain storage based on the time when the drugs enter the cold chain storage; The drug delivery destination, drug cargo quantity and drug storage time are determined as the drug information corresponding to the drug delivery bill.

3. The drug information tracking method based on the statistical amplification model according to claim 1 is characterized in that: The process of determining the shipping risk characteristic category of the unstable drug includes: Compare the maximum value of the risk superposition characterization coefficient with a preset risk superposition characterization coefficient threshold; If the maximum value of the risk superposition characterization coefficient is less than or equal to the risk superposition characterization coefficient threshold value, it is determined that the transportation risk characteristic category of the unstable drug is a transportation weak risk characteristic category; If the maximum value of the risk superposition characterization coefficient is greater than the risk superposition characterization coefficient threshold, the transportation risk characteristic category of the unstable drug is determined to be a transportation strong risk characteristic category.

4. The drug information tracking method based on the statistical amplification model according to claim 3 is characterized in that: The process for determining how critical risk drugs should be delivered includes: If the unstable drug is of a weak risk characteristic category, determining a delivery route for the critical risk drug based on a drug delivery destination corresponding to the critical risk drug; If the unstable drug is of a category with strong risk characteristics for transportation, the key risk drug shall be transported separately.

5. The drug information tracking method based on the statistical amplification model according to claim 4 is characterized in that: The process of determining the delivery route of the critical risk drugs includes: The drug delivery destination corresponding to the critical risk drug is determined as the end point of the delivery route.

6. The drug information tracking method based on the statistical amplification model according to claim 5 is characterized in that: The process for identifying critical risk drugs includes: The quantity of drug cargo corresponding to each drug delivery bill of unstable drugs is obtained, and the drug corresponding to the maximum drug cargo quantity is determined as the key risk drug.

7. A drug information tracking system applied to the drug information tracking method based on statistical amplification model as claimed in any one of claims 1 to 6, characterized in that: include: Data statistics module, used to obtain drug information; Several data analysis modules, connected to the data statistics module, for determining the transportation risk characteristic category of the drug based on the drug information; Several processing modules are connected to the data analysis module to determine the delivery mode of the drug.

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