Pharmaceutical supply chain flow data security analysis method and system based on data processing
By introducing a flow data security analysis system in the pharmaceutical supply chain, the problem of insufficient abnormal analysis of flow data in the existing technology is solved, and accurate screening and security analysis of flow data of pharmaceutical products is realized, the accuracy and dynamicity of monitoring results are improved, and inventory management is optimized.
Patent Information
- Application Number
- CN202510179590.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-19
- Publication Date
- 2025-04-18
- Estimated Expiration
- 2045-02-19
AI Technical Summary
The prior art fails to effectively analyze abnormal sales data in monitoring the flow direction of pharmaceutical products, resulting in differences in monitoring results and the sales situation cannot be analyzed dynamically based on purchase prices.
Provides a medical supply chain flow data security analysis system based on data processing, including a flow data processing module, a flow data security analysis module, a security early warning module and a supply chain management module. By building a distribution model for medical institutions, screening and processing flow data, analyzing data security, and issuing early warnings and managing supply chains based on the analysis results.
It realizes accurate screening and safety analysis of the flow data of pharmaceutical products, improves the accuracy and dynamicity of monitoring results, can adapt to changes in the sales environment, optimizes inventory management, and reduces the operating costs of the enterprise.
Smart Images
Figure CN119646886B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of pharmaceutical supply chain flow data security analysis, and in particular to a pharmaceutical supply chain flow data security analysis method and system based on data processing. Background Art
[0002] Pharmaceutical flow data refers to the flow and destination data of drugs in the distribution channel, including the whole process information of drugs from manufacturers to distributors at all levels and finally to sales terminals (such as hospitals, pharmacies, etc.). In a narrow sense, flow data only refers to the sales data (delivery orders) of drugs distributed by distributors to terminals, while in a broad sense, flow data covers the whole process of drugs flowing from manufacturers to pharmaceutical companies, then to sales terminals, and finally being purchased by consumers.
[0003] Nowadays, during the sales process of pharmaceutical products, the flow of pharmaceutical products is monitored by collecting their sales data. However, during the monitoring process, the anomalies in the collected sales data are not analyzed, resulting in differences in the monitoring results. Or, anomaly analysis is only achieved by comparing sales data with distribution data. At the same time, it is impossible to dynamically analyze the sales of pharmaceutical products based on their purchase prices. Summary of the invention
[0004] The purpose of the present invention is to provide a pharmaceutical supply chain flow data security analysis method and system based on data processing to solve the problems raised in the prior art.
[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a pharmaceutical supply chain flow data security analysis system based on data processing, the system comprising a flow data processing module, a flow data security analysis module, a security warning module and a supply chain management module;
[0006] The flow data processing module is used to filter and process the flow data of each pharmaceutical product according to the distribution terminal coverage, flow change, and inventory and distribution of each pharmaceutical product of the enterprise to obtain target flow data;
[0007] The flow data security analysis module searches for target medical institutions according to the loss of enterprise medical institutions, determines the supplementary target flow data, and analyzes the security of each target flow data stored in the target flow data set based on the determination result;
[0008] The security warning module is used to select whether to issue a warning signal according to the analysis results of the flow data security analysis module, and determine the time of issuing the warning signal;
[0009] The supply chain management module manages the supply status of each pharmaceutical product of the enterprise in real time according to the issuance of the early warning signal.
[0010] Further, the flow data processing module includes a flow data acquisition unit and a flow data processing unit;
[0011] The flow data collection unit collects the distribution terminal coverage rate, flow change rate, inventory data and distribution data of each pharmaceutical product of the enterprise within the selected time period, the distribution terminal coverage rate = the number of medical institutions with distribution relationships within the selected time period / the total number of medical institutions, the flow change rate = exp{-[(pharmaceutical product purchase price - pharmaceutical product purchase limit price) / pharmaceutical product purchase limit price]};
[0012] The flow data processing unit screens the flow data collected by the flow data collection unit according to the distribution acceptance of each medical institution for each pharmaceutical product within a selected time period to obtain target flow data.
[0013] Furthermore, the specific method for the flow data processing unit to obtain the target flow data is:
[0014] Using the historical flow rate change rate of each pharmaceutical product and the historical distribution data of each pharmaceutical product in each medical institution as the training data set, the linear model Y = k * E + b is trained to obtain the distribution model Y of the j-th pharmaceutical product in the medical institution numbered i under each sales environment. jt =k ij *E ij +b ij , where i=1,2,…,m, represents the number of each medical institution, m represents the total number of medical institutions, j=1,2,…,n, represents the number of each pharmaceutical product, n represents the total number of pharmaceutical products, k, k ij Represent the weights of the linear model and the distribution model, b and b ij Respectively represent the bias of the linear model and the distribution model, Y jt represents the flow rate change rate of the jth pharmaceutical product at time t, which is the independent variable, E ij(t→t+d) It represents the quantity of the jth pharmaceutical product distributed in the medical institution numbered i in the time period [t, t+d], which is the dependent variable;
[0015] According to the flow rate change rate of each pharmaceutical product at time t and the distribution quantity of each pharmaceutical product in each medical institution in the time period [t, t+d], the distribution acceptance of each pharmaceutical product in each medical institution in the time period [t, t+d] is calculated. The specific calculation formula is:
[0016] When X ij(t→t+d) -[(Y jt -bij ) / k ij ]<0:
[0017] W ij(t→t+d) =1-{{[(Y jt -b ij ) / k ij ]-X ij(t→t+d)} / [(Y jt -b ij ) / k ij ]};
[0018] When X ij(t→t+d) ≥[(Y jt -b ij ) / k ij ]hour:
[0019] W ij(t→t+d) =1;
[0020] Among them, X ij(t→t+d) represents the actual delivery quantity of the jth pharmaceutical product in the medical institution numbered i in the time period [t, t+d], d represents the collection interval of the flow rate change rate, W ij(t→t+d) It represents the acceptance of the distribution of the jth medical product by the medical institution numbered i in the time period [t, t+d];
[0021] When 0≤W ij(t→t+d) When t is less than 0.8, the contract order between the medical institution numbered i and the enterprise for the j-th pharmaceutical product is obtained. Based on the obtained contract order, the flow data of the enterprise's j-th pharmaceutical product in the time period [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] as the target flow data, where G jt represents the inventory quantity of the jth pharmaceutical product of the enterprise, and the target flow data [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] is associated with the medical institution numbered i.
[0022] Furthermore, the flow data security analysis module includes a target medical institution search unit, a target flow data supplement unit and a security analysis unit;
[0023] The target medical institution search unit calculates the distribution terminal coverage rate F of the enterprise's j-th pharmaceutical product in the time period [t, t+d]. j(t→t+d) , and the distribution terminal coverage rate F of the company's j-th pharmaceutical product in the [td, t] periodj(t-d→t) Compare and analyze the loss of enterprise medical institutions in combination with the new additions of enterprise medical institutions in the time period [td, t+d], and search for target medical institutions based on the analysis results;
[0024] The target flow data supplement unit adds the flow data [G jt ,0] as the target flow direction data supplementing the target flow direction data obtained by the flow direction data processing unit, the supplemented target flow direction data and the target flow direction data obtained by the flow direction data processing unit are stored in a set M, and a target flow direction data set is obtained;
[0025] The security analysis unit analyzes the security of each target flow data in the target flow data set through funnel analysis.
[0026] Furthermore, the specific method for the target medical institution searching unit to search for the target medical institution is:
[0027] According to F j(t→t+d) =F j(t-d→t) -(h t / m)+(T j(t→t+d) / m) calculates the theoretical distribution terminal coverage rate of the company's j-th pharmaceutical product in the time period [t, t+d], where h t represents the mean value of the total number of medical institutions associated with the target flow data calculated at time t, T j(t→t+d) represents the number of new medical institutions for the company's j-th pharmaceutical product in the time period [t, t+d];
[0028] If F j(t→t+d) >Q j(t→t+d) , then the set of medical institutions lost by the enterprise and medical institutions associated with the target flow data is taken as the target medical institution, where Q j(t→t+d) represents the actual distribution terminal coverage rate of the company's j-th pharmaceutical product in the time period [t, t+d];
[0029] If F j(t→t+d) =Q j(t→t+d) , it means that the medical institution associated with the target flow data is the target medical institution.
[0030] Furthermore, the specific method for the security analysis unit to analyze the security of each target flow data in the target flow data set is:
[0031] The historical usage of the j-th pharmaceutical product in the medical institution numbered i is obtained, as well as the historical distribution volume of the j-th pharmaceutical product distributed by the enterprise to the medical institution numbered i. The obtained historical distribution volume and historical usage volume are summed to obtain the historical distribution cumulative volume A. ij and historical usage accumulation B ij ;
[0032] According to R ijp(t→t+d) ={[[(Y j(t-2*d) -b ij ) / k ij ]-X ij(t-2*d→t-d) ]-[[(Y j(t-d) -b ij ) / k ij ]-X ij(t-d→t)}} / [[(Y j(t-2*d) -b ij ) / k ij ]-X ij(t-2*d→t-d) ] is used to calculate the loss rate of the contracted orders between the enterprise and the medical institution numbered i for the j-th medical product due to the distribution quantity of the medical products in the time period [t, t+d], where p=1,2,…,q, represents the number corresponding to each order contract information, q represents the total number, and R ijp(t→t+d) It represents the loss rate of the contracted order between the enterprise and the medical institution numbered i for the j-th medical product due to the delivery quantity of the medical products in the time period [t, t+d];
[0033] Based on the target flow data stored in the target flow dataset [G jt ,0]:
[0034] If A ij -B ij ≥(Y jt -b ij ) / k ij , then it means the target flow data stored in the target flow data set [G jt ,0] = R ijp(t→t+d) ;
[0035] If A ij -B ij <(Y jt -b ij ) / k ij , then it means the target flow data stored in the target flow data set [G jt ,0] = {{[(Y jt -b ij ) / k ij ]-(A ij -B ij)} / [(Y jt -b ij ) / k ij ]}*R ijp(t→t+d) ;
[0036] Based on the target flow data stored in the target flow dataset [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]:
[0037] If A ij -B ij ≥(Y jt -b ij ) / k ij ]-X ij(t→t+d) , then it means the target flow data stored in the target flow data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] safety factor = R ijp(t→t+d) ;
[0038] If A ij -B ij <(Y jt -b ij ) / k ij ]-X ij(t→t+d) , then it means the target flow data stored in the target flow data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] safety factor = {{[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]-(A ij -B ij )} / [(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]}*R ijp(t→t+d) .
[0039] Further, the safety warning module includes a safety warning analysis unit, a warning time determination unit and a warning unit;
[0040] The safety warning analysis unit compares the safety factor of each target flow direction data stored in the target flow direction data set with a set threshold value. If the safety factor is greater than or equal to the set threshold value, it indicates that the corresponding target flow direction data is non-abnormal flow direction data. If the safety factor is less than the set threshold value, it indicates that the corresponding target flow direction data is abnormal flow direction data.
[0041] The warning time determination unit uses the end time of the time period corresponding to the abnormal flow direction data as the issuance time of the warning signal;
[0042] The early warning unit sends the abnormal flow direction data to the display terminal at the time when the early warning signal is issued.
[0043] Furthermore, the supply chain management module receives the warning signal sent by the display terminal, and based on the received information, calculates the remaining supply D of the jth pharmaceutical product in the enterprise at time t+d. j(t+d) To determine, according to G t -D j(t+d) The supply quantity of the j-th pharmaceutical product by the enterprise at time t+d is determined, and based on the determination result, the supply status of each pharmaceutical product by the enterprise is managed.
[0044] Furthermore, the supply chain management module calculates the remaining supply D of the jth pharmaceutical product in the enterprise at time t+d. j(t+d) The specific method for determination is:
[0045] according to The remaining supply of the j-th pharmaceutical product in the enterprise at time t+d is determined, where c=1,2,…,C, represents the number corresponding to each medical institution associated with each supplementary target flow data, C represents the total number of medical institutions associated with the supplementary target flow data, v=1,2,…,f, represents the number corresponding to each medical institution associated with the target flow data, and f represents the total number of medical institutions associated with the target flow data.
[0046] A data processing-based method for analyzing the flow data security of a pharmaceutical supply chain, the method comprising:
[0047] S10: According to the distribution terminal coverage, flow change, and inventory and distribution status of each pharmaceutical product of the enterprise, the flow direction data of each pharmaceutical product is screened and processed to obtain the target flow direction data;
[0048] S20: according to the loss of the enterprise's medical institutions, the target medical institutions are searched, the supplementary target flow data are determined, and based on the determination result, the security of each target flow data stored in the target flow data set is analyzed;
[0049] S30: selectively sending a warning signal to the display terminal, and determining the time of sending the warning signal;
[0050] S40: Based on the issuance of early warning signals, the supply situation of various pharmaceutical products of enterprises is managed in real time.
[0051] Compared with the prior art, the present invention has the following beneficial effects:
[0052] 1. The present invention constructs a distribution model for pharmaceutical products in each medical institution through the historical flow changes and historical distribution conditions of pharmaceutical products, and analyzes the target flow data in combination with the actual distribution conditions of each pharmaceutical product in each medical institution. Based on the analyzed target flow data and the distribution terminal coverage of each pharmaceutical product of the enterprise within the selected time period, the supplementary target flow data is determined, which is conducive to the accurate search for the target medical institution. This process can also adapt to the dynamic changes of the sales environment and improve the use effect of the system.
[0053] 2. The present invention uses the funnel analysis method to analyze the historical usage and historical distribution of corresponding pharmaceutical products in medical institutions associated with each target flow data in the target flow data set, calculates the loss rate of contracted orders between the enterprise and the associated medical institutions due to the distribution quantity of pharmaceutical products in the selected time period, and analyzes the security of each target flow data in the target flow data set based on the calculation results. The funnel analysis method can analyze whether the target flow data is the bottleneck that causes the loss of contracted orders, which is conducive to accurately analyzing the security of the target flow data and further improving the security analysis effect of the system.
[0054] 3. The present invention chooses whether to issue an early warning according to the security situation of the target flow data, and manages the supply situation of each pharmaceutical product of the enterprise according to the early warning information. While optimizing the inventory management of the enterprise, it can also reduce costs and increase efficiency for the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS
[0055] Figure 1 This is a schematic diagram of the working principle structure of the pharmaceutical supply chain flow data security analysis system based on data processing of the present invention;
[0056] Figure 2 The figure is a schematic diagram of the workflow of the data security analysis method of the pharmaceutical supply chain flow based on data processing of the present invention. DETAILED DESCRIPTION
[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.
[0058] like Figure 1-Figure 2 As shown, the present invention provides a pharmaceutical supply chain flow data security analysis method and system technical solution based on data processing, and a pharmaceutical supply chain flow data security analysis system based on data processing, the system includes a flow data processing module, a flow data security analysis module, a security warning module and a supply chain management module;
[0059] The flow data processing module is used to filter and process the flow data of each pharmaceutical product according to the distribution terminal coverage, flow change, and inventory and distribution status of each pharmaceutical product of the enterprise to obtain the target flow data;
[0060] The flow data processing module includes a flow data acquisition unit and a flow data processing unit;
[0061] The flow data collection unit collects the distribution terminal coverage rate, flow change rate, inventory data and distribution data of each pharmaceutical product of the enterprise within the selected time period. The distribution terminal coverage rate = the number of medical institutions with distribution relationships within the selected time period / the total number of medical institutions. The distribution relationship refers to the medical institutions that can receive pharmaceutical products within the selected time period. The distribution terminal refers to the medical institution. The flow change rate = exp{-[(pharmaceutical product purchase price-pharmaceutical product purchase limit price) / pharmaceutical product purchase limit price]}. The pharmaceutical product purchase limit price refers to the winning bid price of the pharmaceutical product. The winning bid price refers to the price of the bidder who is rated as the best after passing the comprehensive evaluation standards of the tenderer in the centralized procurement bidding activity. exp() represents an exponential function with e as the base, e=2.73;
[0062] The flow data processing unit screens and processes the flow data collected by the flow data collection unit according to the distribution acceptance of each medical institution for each pharmaceutical product within the selected time period to obtain the target flow data. The specific method is as follows:
[0063] Using the historical flow rate change rate of each pharmaceutical product and the historical distribution data of each pharmaceutical product in each medical institution as the training data set, the linear model Y = k * E + b is trained to obtain the distribution model Y of the j-th pharmaceutical product in the medical institution numbered i under each sales environment. jt =k ij *E ij +b ij, where i=1,2,…,m, represents the number of each medical institution, m represents the total number of medical institutions, j=1,2,…,n, represents the number of each pharmaceutical product, n represents the total number of pharmaceutical products, k, k ij Represent the weights of the linear model and the distribution model, b and b ij Respectively represent the bias of the linear model and the distribution model, Y jt represents the flow rate change rate of the jth pharmaceutical product at time t, which is the independent variable, E ij(t→t+d) It represents the quantity of the jth pharmaceutical product distributed in the medical institution numbered i in the time period [t, t+d], which is the dependent variable;
[0064] According to the flow rate change rate of each pharmaceutical product at time t and the distribution quantity of each pharmaceutical product in each medical institution in the time period [t, t+d], the distribution acceptance of each pharmaceutical product in each medical institution in the time period [t, t+d] is calculated. The specific calculation formula is:
[0065] When X ij(t→t+d) -[(Y jt -b ij ) / k ij ]<0:
[0066] W ij(t→t+d) =1-{{[(Y jt -b ij ) / k ij ]-X ij(t→t+d)} / [(Y jt -b ij ) / k ij ]};
[0067] When X ij(t→t+d) ≥[(Y jt -b ij ) / k ij ]hour:
[0068] W ij(t→t+d) =1;
[0069] Among them, X ij(t→t+d) represents the actual delivery quantity of the jth pharmaceutical product in the medical institution numbered i in the time period [t, t+d], d represents the collection interval of the flow rate change rate, W ij(t→t+d) It represents the acceptance of the distribution of the jth medical product by the medical institution numbered i in the time period [t, t+d];
[0070] When 0≤W ij(t→t+d)When t is less than 0.8, the contract order between the medical institution numbered i and the enterprise for the j-th pharmaceutical product is obtained. Based on the obtained contract order, the flow data of the enterprise's j-th pharmaceutical product in the time period [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] as the target flow data, where G jt represents the inventory quantity of the jth pharmaceutical product of the enterprise, and the target flow data [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] is associated with the medical institution numbered i;
[0071] The flow data security analysis module searches for target medical institutions according to the loss of enterprise medical institutions, determines the supplementary target flow data, and analyzes the security of each target flow data stored in the target flow data set based on the determination results;
[0072] The flow data security analysis module includes a target medical institution search unit, a target flow data supplement unit and a security analysis unit;
[0073] The target medical institution search unit calculates the distribution terminal coverage rate F of the enterprise's j-th pharmaceutical product in the time period [t, t+d] j(t→t+d) , and the distribution terminal coverage rate F of the company's j-th pharmaceutical product in the [td, t] period j(t-d→t) Compare and analyze the loss of enterprise medical institutions in combination with the new additions of enterprise medical institutions in the time period [td, t+d]. Based on the analysis results, find the target medical institutions. The specific method is as follows:
[0074] According to F j(t→t+d) =F j(t-d→t) -(h t / m)+(T j(t→t+d) / m) calculates the theoretical distribution terminal coverage rate of the company's j-th pharmaceutical product in the time period [t, t+d], where h t represents the mean value of the total number of medical institutions associated with the target flow data calculated at time t, T j(t→t+d)Indicates the number of new medical institutions for the company's j-th pharmaceutical product in the time period [t, t+d]. For example, in the time period [t-2*d, td], the total number of medical institutions associated with the target flow data is 6, and in the time period [td, t], the total number of medical institutions associated with the target flow data is 4. Then the mean of the total number of medical institutions associated with the target flow data calculated at time t = (6+4) / 2=5;
[0075] If F j(t→t+d) >Q j(t→t+d) , then the set of medical institutions lost by the enterprise and medical institutions associated with the target flow data is taken as the target medical institution, where Q j(t→t+d) represents the actual distribution terminal coverage rate of the enterprise's j-th pharmaceutical product in the time period [t, t+d]. The lost medical institutions refer to the medical institutions that have distribution relationships in the time period [td, t] and have no distribution relationships in the time period [t, t+d].
[0076] If F j(t→t+d) =Q j(t→t+d) , it means that the medical institution associated with the target flow data is the target medical institution;
[0077] The target flow data supplement unit adds the flow data of the medical institutions lost by the enterprise in the time period [t, t+d] [G jt ,0] as the target flow direction data supplementing the target flow direction data obtained by the flow direction data processing unit, the supplemented target flow direction data and the target flow direction data obtained by the flow direction data processing unit are stored in a set M, and a target flow direction data set is obtained;
[0078] The security analysis unit analyzes the security of each target flow data in the target flow data set through funnel analysis. The specific method is as follows:
[0079] The historical usage of the j-th pharmaceutical product in the medical institution numbered i is obtained, as well as the historical distribution volume of the j-th pharmaceutical product distributed by the enterprise to the medical institution numbered i. The obtained historical distribution volume and historical usage volume are summed to obtain the historical distribution cumulative volume A. ij and historical usage accumulation B ij ;
[0080] According to R ijp(t→t+d) ={[[(Y j(t-2*d) -b ij ) / k ij ]-X ij(t-2*d→t-d) ]-[[(Y j(t-d) -b ij ) / k ij ]-X ij(t-d→t)}} / [[(Y j(t-2*d) -bij ) / k ij ]-X ij(t-2*d→t-d) ] is used to calculate the loss rate of the contracted orders between the enterprise and the medical institution numbered i for the j-th medical product due to the distribution quantity of the medical products in the time period [t, t+d], where p=1,2,…,q, represents the number corresponding to each order contract information, q represents the total number, and R ijp(t→t+d) It represents the loss rate of the contracted order between the enterprise and the medical institution numbered i for the j-th medical product due to the delivery quantity of the medical products in the time period [t, t+d];
[0081] Based on the target flow data stored in the target flow dataset [G jt ,0]:
[0082] If A ij -B ij ≥(Y jt -b ij ) / k ij , then it means the target flow data stored in the target flow data set [G jt ,0] = R ijp(t→t+d) ;
[0083] If A ij -B ij <(Y jt -b ij ) / k ij , then it means the target flow data stored in the target flow data set [G jt ,0] = {{[(Y jt -b ij ) / k ij ]-(A ij -B ij )} / [(Y jt -b ij ) / k ij ]}*R ijp(t→t+d) ;
[0084] Based on the target flow data stored in the target flow dataset [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]:
[0085] If A ij -B ij ≥(Y jt -b ij ) / k ij ]-X ij(t→t+d), then it means the target flow data stored in the target flow data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] safety factor = R ijp(t→t+d) ;
[0086] If A ij -B ij <(Y jt -b ij ) / k ij ]-X ij(t→t+d) , then it means the target flow data stored in the target flow data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] safety factor = {{[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]-(A ij -B ij )} / [(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]}*R ijp(t→t+d) ;
[0087] The security warning module is used to select whether to issue a warning signal and determine the time of issuing the warning signal according to the analysis results of the flow data security analysis module;
[0088] The safety warning module includes a safety warning analysis unit, a warning time determination unit and a warning unit;
[0089] The safety warning analysis unit compares the safety factor of each target flow direction data stored in the target flow direction data set with the set threshold value. If the safety factor is ≥ the set threshold value, it indicates that the corresponding target flow direction data is non-abnormal flow direction data. If the safety factor is < the set threshold value, it indicates that the corresponding target flow direction is abnormal flow direction data.
[0090] The warning time determination unit uses the end time of the time period corresponding to the abnormal flow direction data as the issuance time of the warning signal;
[0091] The early warning unit sends the abnormal flow data to the display terminal at the time when the early warning signal is issued.
[0092] The supply chain management module manages the supply of various pharmaceutical products of enterprises in real time according to the issuance of early warning signals;
[0093] The supply chain management module receives the warning signal sent by the display terminal and calculates the remaining supply D of the jth pharmaceutical product in the enterprise at time t+d based on the received information. j(t+d) To confirm, , according to G t -D j(t+d) Determine the supply quantity of the j-th pharmaceutical product by the enterprise at time t+d, and manage the supply situation of each pharmaceutical product by the enterprise based on the determination result, wherein c=1,2,…,C, represents the number corresponding to each medical institution associated with each supplementary target flow data, C represents the total number of medical institutions associated with the supplementary target flow data, v=1,2,…,f, represents the number corresponding to each medical institution associated with the target flow data, and f represents the total number of medical institutions associated with the target flow data.
[0094] A pharmaceutical supply chain flow data security analysis system based on data processing, the method includes:
[0095] S10: According to the distribution terminal coverage, flow change, and inventory and distribution status of each pharmaceutical product of the enterprise, the flow direction data of each pharmaceutical product is screened and processed to obtain the target flow direction data;
[0096] S20: according to the loss of the enterprise's medical institutions, the target medical institutions are searched, the supplementary target flow data are determined, and based on the determination result, the security of each target flow data stored in the target flow data set is analyzed;
[0097] S30: selectively sending a warning signal to the display terminal, and determining the time of sending the warning signal;
[0098] S40: Based on the issuance of early warning signals, the supply situation of various pharmaceutical products of enterprises is managed in real time.
[0099] Example 1: Assume that the target flow direction data stored in the target flow direction data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] has a safety factor of 0.7 and a threshold of 0.8;
[0100] Since the safety factor = 0.7 < the set threshold = 0.8, it is considered that the target flow data [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] is abnormal flow data;
[0101] Abnormal flow data[Gjt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] corresponds to the time period [t, t+d], and the end time t+d of the time period [t, t+d] is the time when the warning signal is issued;
[0102] At time t+d, the abnormal flow data [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] is sent to the display terminal as a warning signal.
[0103] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.
Claims
1. A pharmaceutical supply chain flow data security analysis system based on data processing, characterized by: The system includes a flow data processing module, a flow data security analysis module, a security warning module and a supply chain management module; The flow data processing module is used to filter and process the flow data of each pharmaceutical product according to the distribution terminal coverage, flow change, and inventory and distribution of each pharmaceutical product of the enterprise to obtain the target flow data. The specific method is as follows: Using the historical flow rate change rate of each pharmaceutical product and the historical distribution data of each pharmaceutical product in each medical institution as the training data set, the linear model Y = k*E + b is trained to obtain the distribution model Y of the jth pharmaceutical product in the medical institution numbered i under each sales environment. jt =k ij *E ij +b ij , where i = 1, 2, ..., m, represents the number of each medical institution, m represents the total number of medical institutions, j = 1, 2, ..., n, represents the number of each pharmaceutical product, n represents the total number of pharmaceutical products, k, k ij Represent the weights of the linear model and the distribution model, b and b ij Respectively represent the bias of the linear model and the distribution model, Y jt represents the flow rate change rate of the jth pharmaceutical product at time t, which is the independent variable, E ij(t→t+d) represents the quantity of the jth pharmaceutical product delivered in the time period [t, t+d] in the medical institution numbered i, which is the dependent variable, and the flow rate change rate = exp{-[(pharmaceutical product purchase price-pharmaceutical product purchase limit price) / pharmaceutical product purchase limit price]}; According to the flow rate change rate of each pharmaceutical product at time t and the distribution quantity of each pharmaceutical product in each medical institution in the time period [t, t+d], the distribution acceptance of each pharmaceutical product in each medical institution in the time period [t, t+d] is calculated. The specific calculation formula is: When X ij(t→t+d) -[(Y jt -b ij ) / k ij ]<0: W ij(t→t+d) =1-{{[(Y jt -b ij ) / k ij ]-X ij(t→t+d) } / [(Y jt -b ij ) / k ij ]}; When X ij(t→t+d) ≥[(Y jt -b ij ) / k ij ]hour: W ij(t→t+d) ＝1； Among them, X ij(t→t+d) represents the actual delivery quantity of the jth pharmaceutical product in the medical institution numbered i in the time period [t, t+d], d represents the collection interval of the flow rate change rate, W ij(t→t+d) It represents the acceptance of the distribution of the jth medical product by the medical institution numbered i in the time period [t, t+d]; When 0≤W ij(t→t+d) When t is less than 0.8, the contract order between the medical institution numbered i and the enterprise for the j-th pharmaceutical product is obtained. Based on the obtained contract order, the flow data [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] as the target flow data, where G jt represents the inventory quantity of the jth pharmaceutical product of the enterprise, and the target flow data [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] is associated with the medical institution numbered i; The flow data security analysis module searches for target medical institutions according to the loss of enterprise medical institutions, determines the supplementary target flow data, and analyzes the security of each target flow data stored in the target flow data set based on the determination result; The flow data security analysis module includes a target medical institution search unit, a target flow data supplement unit and a security analysis unit; The target medical institution search unit calculates the distribution terminal coverage rate F of the enterprise's j-th pharmaceutical product in the time period [t, t+d]. j(t→t+d) , and the distribution terminal coverage rate F of the company's j-th pharmaceutical product in the [td, t] period j(t-d→t) Compare and analyze the loss of enterprise medical institutions in combination with the new additions of enterprise medical institutions in the time period [td, t+d]. Based on the analysis results, find the target medical institutions. The specific method is as follows: According to F j(t→t+d) =F j(t-d→t) -(h t / m)+(T j(t→t+d) / m) calculates the theoretical distribution terminal coverage rate of the company's j-th pharmaceutical product in the time period [t, t+d], where h t represents the mean value of the total number of medical institutions associated with the target flow data calculated at time t, T j(t→t+d) It represents the number of new medical institutions for the company's j-th pharmaceutical product in the time period [t, t+d]. The distribution terminal coverage rate = the number of medical institutions with distribution relationships in the selected time period / the total number of medical institutions; If F j(t→t+d) >Q j(t→t+d) , then the set of medical institutions lost by the enterprise and medical institutions associated with the target flow data is taken as the target medical institution, where Q j(t→t+d) represents the actual distribution terminal coverage rate of the company's j-th pharmaceutical product in the time period [t, t+d]; If F j(t→t+d) =Q j(t→t+d) , it means that the medical institution associated with the target flow data is the target medical institution; The target flow data supplement unit adds the flow data [G jt ,0] as the target flow direction data supplementing the target flow direction data obtained by the flow direction data processing unit, the supplemented target flow direction data and the target flow direction data obtained by the flow direction data processing unit are stored in a set M, and a target flow direction data set is obtained; The security analysis unit analyzes the security of each target flow data in the target flow data set through funnel analysis; The security warning module is used to select whether to issue a warning signal according to the analysis results of the flow data security analysis module, and determine the time of issuing the warning signal; The supply chain management module manages the supply status of each pharmaceutical product of the enterprise in real time according to the issuance of the early warning signal.
2. The pharmaceutical supply chain flow data security analysis system based on data processing according to claim 1 is characterized by: The flow data processing module includes a flow data acquisition unit and a flow data processing unit; The flow data collection unit collects the distribution terminal coverage rate, flow rate change rate, inventory data and distribution data of each pharmaceutical product of the enterprise within a selected time period; The flow data processing unit screens the flow data collected by the flow data collection unit according to the distribution acceptance of each medical institution for each pharmaceutical product within a selected time period to obtain target flow data.
3. The pharmaceutical supply chain flow data security analysis system based on data processing according to claim 2 is characterized by: The specific method for the security analysis unit to analyze the security of each target flow data in the target flow data set is: The historical usage of the j-th pharmaceutical product in the medical institution numbered i is obtained, as well as the historical distribution volume of the j-th pharmaceutical product distributed by the enterprise to the medical institution numbered i. The obtained historical distribution volume and historical usage volume are summed to obtain the historical distribution cumulative volume A. ij and historical usage accumulation B ij ; According to R ijp(t→t+d) ={[[(Y j(t-2*d) -b ij ) / k ij ]-X ij(t-2*d→t-d) ]-[[(Y j(t-d) -b ij ) / k ij ]-X ij(t-d→t) }} / [[(Y j(t-2*d) -b ij ) / k ij ]-X ij(t-2*d→t-d) ] is used to calculate the loss rate of the contracted orders between the enterprise and the medical institution numbered i for the j-th medical product due to the distribution quantity of the medical products in the time period [t, t+d], where p = 1, 2, …, q, represents the number corresponding to the contracted information of each order, q represents the total number, and R ijp(t→t+d) It represents the loss rate of the contracted order between the enterprise and the medical institution numbered i for the j-th medical product due to the delivery quantity of the medical products in the time period [t, t+d]; Based on the target flow data stored in the target flow dataset [G jt ,0]: If A ij -B ij ≥(Y jt -b ij ) / k ij , then it means the target flow data stored in the target flow data set [G jt ,0] = R ijp(t→t+d) ; If A ij -B ij <(Y jt -b ij ) / k ij , then it means the target flow data stored in the target flow data set [G jt ,0]={{[(Y jt -b ij ) / k ij ]-(A ij -B ij )} / [(Y jt -b ij ) / k ij ]}*R ijp(t→t+d) ; Based on the target flow data stored in the target flow dataset [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]: If A ij -B ij ≥(Y jt -b ij ) / k ij ]-X ij(t→t+d) , then it means the target flow data stored in the target flow data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] safety factor = R ijp(t→t+d) ; If A ij -B ij <(Y jt -b ij ) / k ij ]-X ij(t→t+d) , then it means the target flow data stored in the target flow data set [G jt ,[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ] = {{[(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]-(A ij -B ij )} / [(Y jt -b ij ) / k ij ]-X ij(t→t+d) ]}*R ijp(t→t+d) .
4. The pharmaceutical supply chain flow data security analysis system based on data processing according to claim 3 is characterized by: The safety warning module includes a safety warning analysis unit, a warning time determination unit and a warning unit; The safety warning analysis unit compares the safety factor of each target flow direction data stored in the target flow direction data set with a set threshold value. If the safety factor is greater than or equal to the set threshold value, it indicates that the corresponding target flow direction data is non-abnormal flow direction data. If the safety factor is less than the set threshold value, it indicates that the corresponding target flow direction data is abnormal flow direction data. The warning time determination unit uses the end time of the time period corresponding to the abnormal flow direction data as the issuance time of the warning signal; The early warning unit sends the abnormal flow direction data to the display terminal at the time when the early warning signal is issued.
5. The pharmaceutical supply chain flow data security analysis system based on data processing according to claim 4 is characterized by: The supply chain management module receives the warning signal sent by the display terminal, and based on the received information, calculates the remaining supply D of the jth pharmaceutical product in the enterprise at time t+d. j(t+d) To determine, according to G t -D j(t+d) The supply quantity of the j-th pharmaceutical product by the enterprise at time t+d is determined, and based on the determination result, the supply status of each pharmaceutical product by the enterprise is managed.
6. The pharmaceutical supply chain flow data security analysis system based on data processing according to claim 5 is characterized by: The supply chain management module calculates the remaining supply D of the jth pharmaceutical product in the enterprise at time t+d. j(t+d) The specific method for determination is: according to The remaining supply of the j-th pharmaceutical product in the enterprise at time t+d is determined, where c=1,2,…,C, represents the number corresponding to each medical institution associated with each supplementary target flow data, C represents the total number of medical institutions associated with the supplementary target flow data, v=1,2,…,f, represents the number corresponding to each medical institution associated with the target flow data, and f represents the total number of medical institutions associated with the target flow data.
7. A method for data security analysis of pharmaceutical supply chain flow direction based on data processing, realizing a system for data security analysis of pharmaceutical supply chain flow direction based on data processing as claimed in any one of claims 1 to 6, characterized in that: The method comprises: S10: According to the distribution terminal coverage, flow change, and inventory and distribution status of each pharmaceutical product of the enterprise, the flow direction data of each pharmaceutical product is screened and processed to obtain the target flow direction data; S20: according to the loss of the enterprise's medical institutions, the target medical institutions are searched, the supplementary target flow data are determined, and based on the determination result, the security of each target flow data stored in the target flow data set is analyzed; S30: selectively sending a warning signal to the display terminal, and determining the time of sending the warning signal; S40: Based on the issuance of early warning signals, the supply situation of various pharmaceutical products of enterprises is managed in real time.
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