Drug management method and system considering purchase-sale-stock data analysis

Abstract

The invention provides a purchase-sales-stock data analysis-considered medicine management method and system, and belongs to the technical field of medicine management, and the method specifically comprises the steps: determining purchase comment data of purchase users of matched medicines of different screening manufacturers, determining reliable manufacturers in the screened manufacturers according to an association condition between keywords in the purchase comment data and concurrent disease types of the user and a similar condition between the purchase user and a diagnosis result of the user, and determining the matched medicines of the reliable manufacturers in different drugstores according to purchase-sales-stock data of the matched medicines in the target area. According to the method, the out-of-stock data of different drugstores in different dates is determined, and the purchase recommendation strategy of the matched medicine of the user is determined in combination with the spacing distance between the different drugstores and the residence address of the user, so that the accuracy of medicine recommendation processing is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of drug management, and in particular relates to a drug management method and system considering purchase, sales and inventory data analysis. Background Art

[0002] When patients purchase medicines at medical institutions, they are often unable to find a medical institution that matches their drug purchase needs, and the prices are also uneven. This causes patients to spend too long buying medicines and often cannot find a medical institution that best matches their needs.

[0003] To solve the above technical problems, the invention patent application CN201811266650.5 "A drug transaction processing method, server and storage medium" determines the target drug and the set of alternative pharmacies that supply the target drug based on prescription information, selects the best pharmacy, sends the best pharmacy and the corresponding target drug to the patient terminal, and generates a purchase order after receiving the purchase confirmation instruction issued by the patient terminal. However, there are the following technical problems: When making recommendations to pharmacies, there are often multiple manufacturers of the same type of drugs. The prices, efficacy and applicable populations of drugs from different manufacturers vary. Since users often lack relevant medical knowledge, it is difficult to select drugs and manufacturers that are suitable for them.

[0004] In order to solve the above technical problems, the present application provides a drug management method and system that takes into account the analysis of purchase, sales and inventory data. Summary of the Invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: Specifically, in a first aspect, the present application provides a drug management method that considers purchase, sales, and inventory data analysis, specifically including: S1 determines the matching medicine for the user and the reference purchasing user based on the user's diagnosis result; S2 determines the target area of ​​the user based on the user's residential address, obtains inventory data of matching drugs of different manufacturers in different pharmacies in the target area, and determines screening manufacturers among the manufacturers based on historical purchase data of reference users who purchased different matching drugs; S3: Determine purchase review data of users who purchased the matching drugs of different screened manufacturers, and determine reliable manufacturers among the screened manufacturers based on the correlation between keywords in the purchase review data and the types of concurrent diseases of the users, and the similarity between the diagnosis results of the purchasing users and the user; S4 uses the purchase, sales and inventory data of matching drugs of reliable manufacturers in different pharmacies in the target area to determine the out-of-stock data of different pharmacies on different dates, and determines the purchase recommendation strategy of the matching drugs for the user in combination with the distance between different pharmacies and the residential address of the user.

[0006] The beneficial effects of the present invention are: Based on the inventory data of matching drugs from different manufacturers in different pharmacies in the target area and the historical purchase data of reference purchasing users of different matching drugs, the screening manufacturers among the manufacturers are determined, and the inventory data of matching drugs in the target area where users can conveniently purchase drugs is used to screen manufacturers that are convenient for purchasing drugs. Furthermore, combined with the historical purchase data of reference purchasing users, the screening of manufacturers with a large number of historical purchases by reference purchasing users is achieved, avoiding the occurrence of technical problems such as the inability to accurately control the impact of the manufacturer's matching drugs on the user's concurrent disease types due to insufficient reference data.

[0007] The purchase recommendation strategy for the user's matching drugs is determined based on the out-of-stock data of different pharmacies on different dates and the distances between different pharmacies and the user's residential address. The purchase convenience of different reliable manufacturers is evaluated based on the out-of-stock data and the distances, and reliable manufacturers with higher purchase convenience are screened. At the same time, when there is no pharmacy that meets the purchase convenience requirements, the distances between the out-of-stock data of reliable manufacturers are used to determine a combination of reliable manufacturers that meet the purchase convenience requirements, thereby ensuring the user's convenience in purchasing drugs.

[0008] A further technical solution is that the diagnosis result includes the disease type, the type of concurrent disease and the detection abnormality index.

[0009] A further technical solution is that the matching medicine for the user is determined based on the therapeutic medicine corresponding to the disease type.

[0010] A further technical solution is that the reference purchasing user is a purchasing user of matching drugs who has the same disease type and concurrent disease type as the user and whose data deviations from different abnormal detection indicators are within a preset deviation range.

[0011] A further technical solution is that the target area of ​​the user is an area whose distance from the user's residential address is within a preset distance interval.

[0012] A further technical solution is that the method for determining the screening manufacturers among the manufacturers is: Using inventory data of the manufacturer's matching drugs in different pharmacies in the target area, determining a pharmacy in the target area that has the manufacturer's matching drugs, and using the pharmacy as the matching pharmacy; Based on the historical purchase data of the reference purchasing users of the matching drugs, determining the reference purchasing users of the matching drugs of the manufacturer and using them as the matching purchasing users; Whether the manufacturer is a screened manufacturer is determined by the number of matched pharmacies and the number of matched purchasing users.

[0013] A further technical solution is to determine whether the manufacturer is a screening manufacturer based on the number of matched pharmacies and the number of matched purchasing users, specifically including: When the number of matching pharmacies of the manufacturer's matching drugs is greater than a preset pharmacy number threshold and the number of matching purchasing users is greater than a preset matching purchasing user number, the manufacturer is determined to be a screening manufacturer.

[0014] A further technical solution is that the method for determining the purchase recommendation strategy of the user's matching medicine is: Based on the out-of-stock data of the reliable manufacturer in different pharmacies on different dates, determine the date on which no matching drug from the reliable manufacturer exists in different pharmacies on different dates, and use the date as the matching deviation date; Pharmacies that have matching drugs from the reliable manufacturers on different dates are used as matching purchase pharmacies on the dates, and the drug purchase distances on the different dates are determined based on the minimum distance between the matching purchase pharmacies on the different dates and the user's residential address; The purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers, the number ratio of matching deviation dates of different reliable manufacturers, and the drug purchase distance.

[0015] A further technical solution is to determine a purchase recommendation strategy for the user's matching drugs based on the overlap of matching deviation dates of different reliable manufacturers, the proportion of matching deviation dates of different reliable manufacturers, and the purchase distance, specifically including: When there is a reliable manufacturer whose number of matching deviation dates accounts for less than a preset date number ratio threshold and whose average purchase distance on different dates is less than the preset purchase distance threshold, the matching drug of the reliable manufacturer with the least number of matching deviation dates is used as the recommended matching drug processing result for the user; When there is no reliable manufacturer whose proportion of matching deviation dates is less than the preset date proportion threshold and the average value of drug purchase distances on different dates is less than the preset drug purchase distance threshold, the purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers.

[0016] A further technical solution is to determine a purchase recommendation strategy for the user's matching drugs based on the overlap of matching deviation dates of different reliable manufacturers, specifically including: The reliable manufacturers are freely combined to generate multiple reliable manufacturer combinations, and based on the overlap of matching deviation dates of different reliable manufacturers, a date is determined on which the matching drugs of the reliable manufacturers in the reliable manufacturer combination all fall within the matching deviation date, and the date is used as the combination matching deviation date; Determine a reliable manufacturer combination whose proportion of combination matching deviation dates is less than the preset date proportion threshold, and use it as the target recommendation combination; The target recommendation combination with the least number of reliable manufacturers is used as the recommendation processing result of the matching medicine for the user.

[0017] In a second aspect, the present invention provides a computer system comprising: a memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned drug management method that takes into account the analysis of purchase, sales and inventory data when running the computer program.

[0018] Other features and advantages will be described in the following description. The objectives and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other features and advantages of the present invention will become more apparent by describing in detail example embodiments thereof with reference to the accompanying drawings; Figure 1 It is a flowchart of a drug management method that takes into account the analysis of purchase, sales and inventory data; Figure 2 It is a flow chart of the method for determining the screening manufacturers among the manufacturers; Figure 3 It is a flowchart of a method for determining reliable manufacturers among screening manufacturers; Figure 4 is a flowchart of a method for determining a purchase recommendation strategy for a user's matching medicine; Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0021] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification without creative work should fall within the scope of protection of this specification.

[0022] In this application, based on the user's diagnosis results, the impact of drugs from different manufacturers on the user's concurrent diseases is determined, and the purchase, sales and inventory data is used to determine the convenience of purchasing drugs. The user's drug recommendations are made from the two perspectives of the impact and purchase convenience, thereby improving the accuracy of drug recommendation processing.

[0023] The screening manufacturers are those that have more than 2 pharmacies with matching drugs in the target area and have a historical purchase volume of more than 200 times by the reference purchasing users.

[0024] The purchasing users whose keywords in the purchase review data of the screened manufacturers include high blood sugar, dizziness, high blood pressure, and organ damage are taken as target users. When the number of target users whose diagnosis results are consistent with the user is more than 10, it is determined that the screened manufacturer is not a reliable manufacturer.

[0025] The out-of-stock data of different pharmacies on different dates, combined with the distance between different pharmacies and the user's residential address, determines the purchase recommendation strategy for the user's matching medicine. Reliable manufacturers are freely combined to construct a reliable manufacturer combination, and the reliable manufacturer combination with the least number of reliable manufacturers and the proportion of out-of-stock dates in pharmacies in the target area within 0.2 is used as the recommendation result.

[0026] Example 1 like Figure 1 As shown, the present application provides a drug management method considering purchase, sales and inventory data analysis, specifically including: S1 determines the matching medicine for the user and the reference purchasing user based on the user's diagnosis result; A further technical solution is that the diagnosis result includes the disease type, the type of concurrent disease and the detection abnormality index.

[0027] Furthermore, the matching medicine for the user is determined based on the therapeutic medicine corresponding to the disease type.

[0028] Specifically, the reference purchasing user is a purchasing user who has the same disease type and concurrent disease type as the user and whose data deviations from different abnormal detection indicators are within a preset deviation range for matching drugs.

[0029] S2 determines the target area of ​​the user based on the user's residential address, obtains inventory data of matching drugs of different manufacturers in different pharmacies in the target area, and determines screening manufacturers among the manufacturers based on historical purchase data of reference users who purchased different matching drugs;

[0030] Furthermore, the target area of ​​the user is an area whose distance from the user's residential address is within a preset distance interval.

[0031] Specifically, such as Figure 2 As shown, the method for determining the screening manufacturers among the manufacturers is: Using inventory data of the manufacturer's matching drugs in different pharmacies in the target area, determining a pharmacy in the target area that has the manufacturer's matching drugs, and using the pharmacy as the matching pharmacy; Based on the historical purchase data of the reference purchasing users of the matching drugs, determining the reference purchasing users of the matching drugs of the manufacturer and using them as the matching purchasing users; Whether the manufacturer is a screened manufacturer is determined by the number of matched pharmacies and the number of matched purchasing users.

[0032] Furthermore, determining whether the manufacturer is a screening manufacturer based on the number of matched pharmacies and the number of matched purchasing users includes: When the number of matching pharmacies of the manufacturer's matching drugs is greater than a preset pharmacy number threshold and the number of matching purchasing users is greater than a preset matching purchasing user number, the manufacturer is determined to be a screening manufacturer.

[0033] In another possible embodiment, the method for determining the screening manufacturer among the manufacturers is: Using inventory data of the manufacturer's matching drugs at different pharmacies in the target area, determining pharmacies in the target area that have the manufacturer's matching drugs, and using these pharmacies as matching pharmacies; and determining the inventory quantity of the matching drugs in the target area based on the inventory data of the matching pharmacies; Based on the historical purchase data of the reference purchasing users of the matching drugs, determining the reference purchasing users of the matching drugs of the manufacturer and using them as the matching purchasing users; The manufacturer's adaptation coefficient is determined by multiplying the inventory of matching drugs in the target area by the number of matching purchasing users, and whether the manufacturer is a screening manufacturer is determined based on the adaptation coefficient.

[0034] Furthermore, when the adaptation coefficient is greater than a preset adaptation coefficient threshold, the manufacturer is determined to be a screening manufacturer.

[0035] Optionally, the method for determining the screening manufacturer among the manufacturers is: Based on the historical purchase data of the reference purchasing users of the matching drugs, determining that there are reference purchasing users of the matching drugs of the manufacturer, and using them as matching purchasing users; if the number of the matching purchasing users does not meet the requirement, determining that the manufacturer does not belong to the screening manufacturer; When the number of matching purchase users meets the requirement: Based on the purchase data of the matched purchasing user, determining the historical purchase quantity of the matched drug of the manufacturer by the matched purchasing user, and determining that the manufacturer does not belong to the screening manufacturer when the sum of the historical purchase quantity of the matched drug of the manufacturer by the matched purchasing user does not meet the requirements; When the sum of the historical purchase quantity of the matched drug of the manufacturer by the matched purchase user meets the requirement: When it is determined that no pharmacy in the target area has the matching drugs of the manufacturer based on the inventory data of the matching drugs of the manufacturer in different pharmacies, the manufacturer is determined not to be a screening manufacturer; When determining that there are pharmacies in the target area that have matching drugs from the manufacturer: Pharmacies that have matching drugs from the manufacturer are considered matching pharmacies, and based on the inventory data of the matching pharmacies, the inventory quantity of the matching drugs in the target area is determined; if either the number of matching pharmacies or the inventory quantity of the matching drugs in the target area does not meet the requirements, the manufacturer is determined not to be a screening manufacturer; When the number of matching pharmacies and the inventory of matching drugs in the target area meet the requirements: The historical purchase matching coefficient of the manufacturer is determined based on the historical purchase quantity of the matching drugs of different matching purchasing users from the manufacturer, and the adaptation coefficient of the manufacturer is determined in combination with the inventory of the matching drugs in the target area and the inventory of different matching pharmacies. Based on the adaptation coefficient, it is determined whether the manufacturer is a screening manufacturer.

[0036] S3: Determine purchase review data of users who purchased the matching drugs of different screened manufacturers, and determine reliable manufacturers among the screened manufacturers based on the correlation between keywords in the purchase review data and the types of concurrent diseases of the users, and the similarity between the diagnosis results of the purchasing users and the user; Furthermore, the association between the keyword and the concurrent disease type of the user is determined based on a matching result between the keyword and a preset taboo keyword of the concurrent disease type.

[0037] Specifically, the preset taboo keywords include increased blood sugar, dizziness, increased blood pressure, and organ damage.

[0038] Specifically, such as Figure 3 As shown, the method for determining reliable manufacturers among the screening manufacturers is: Based on the correlation between the keywords in the purchase review data and the concurrent disease type of the user, determining whether there are purchasing users who have the same preset taboo keywords as the concurrent disease type of the user, and setting them as warning purchasing users; Determining the number of reference purchasing users among the warning purchasing users based on the similarity between the diagnosis results of the warning purchasing users and the user; Based on the number of reference purchasing users among the early warning purchasing users, it is determined whether the screened manufacturer is a reliable manufacturer.

[0039] Furthermore, when the number of reference purchasing users among the warning purchasing users is greater than a preset warning user number threshold, it is determined that the screened manufacturer is not a reliable manufacturer.

[0040] In another possible embodiment, the method for determining reliable manufacturers among the screened manufacturers is: Based on the correlation between the keywords in the purchase review data and the concurrent disease type of the user, determining whether there are purchasing users who have the same preset taboo keywords as the concurrent disease type of the user, and setting them as warning purchasing users; Based on the similarity between the diagnosis results of the user who purchased the early warning and the user, determine the proportion of the same disease types, concurrent disease types, and abnormal test indicators as the user, and use it as the similarity coefficient; Based on the average value of the similarity coefficients of different early warning purchasing users, it is determined whether the screened manufacturer is a reliable manufacturer.

[0041] Furthermore, when the average value of the similarity coefficients of different early warning purchasing users is greater than a preset similarity coefficient threshold, it is determined that the screened manufacturer is not a reliable manufacturer.

[0042] In another possible embodiment, the method for determining reliable manufacturers among the screened manufacturers is: Based on the correlation between the keywords in the purchase review data and the concurrent disease type of the user, if it is determined that there is no purchasing user with the same preset taboo keywords as the concurrent disease type of the user, then the screened manufacturer is determined to be a reliable manufacturer; When there is a purchasing user with the same preset taboo keyword as the concurrent disease type of the user: The purchasing users who have the same preset taboo keywords as the concurrent disease type of the user are used as warning purchasing users. When the number of the warning purchasing users does not meet the requirement, it is determined that the screening manufacturer is not a reliable manufacturer; When the number of users who purchased the warning meets the requirement: Obtaining a ratio of the number of warning purchasing users among the reference purchasing users of the matching drug of the screened manufacturer, and determining that the screened manufacturer is not a reliable manufacturer when the ratio of the number of warning purchasing users among the reference purchasing users does not meet the requirement; When the proportion of warning purchasing users among the reference purchasing users meets the requirement: Determine a reference purchase warning coefficient based on the proportion of the number of warning purchase users among the reference purchase users of the matching drugs of the screened manufacturer, and the number of reference purchase users. If the reference purchase warning coefficient does not meet the requirements, determine that the screened manufacturer is not a reliable manufacturer. When the reference purchase warning coefficient meets the requirements: Based on the similarity between the diagnosis results of the user who purchased the early warning and the user, the proportion of the same disease type, concurrent disease type and abnormal test indicators as the user is determined, and the proportion is used as the similarity coefficient. If the average value of the similarity coefficients of different early warning purchasing users does not meet the requirements, it is determined that the screening manufacturer is not a reliable manufacturer; When the average value of similarity coefficients of different early warning purchasing users meets the requirements: The taboo matching deviation coefficient of the screening manufacturer is determined based on the similarity coefficients of different warning purchasing users and the same number of preset taboo keywords of the concurrent disease types of the users, and whether the screening manufacturer is a reliable manufacturer is determined based on the taboo matching deviation coefficient.

[0043] Optionally, when the taboo matching deviation coefficient is greater than a preset taboo matching deviation coefficient threshold, it is determined that the screened manufacturer is not a reliable manufacturer.

[0044] S4 uses the purchase, sales and inventory data of matching drugs of reliable manufacturers in different pharmacies in the target area to determine the out-of-stock data of different pharmacies on different dates, and determines the purchase recommendation strategy of the matching drugs for the user in combination with the distance between different pharmacies and the residential address of the user.

[0045] Furthermore, the out-of-stock data of the pharmacy is determined based on monitoring data of the medical insurance system.

[0046] Specifically, such as Figure 4 As shown, the method for determining the purchase recommendation strategy of the user's matching medicine is: Based on the out-of-stock data of the reliable manufacturer in different pharmacies on different dates, determine the date on which no matching drug from the reliable manufacturer exists in different pharmacies on different dates, and use the date as the matching deviation date; Pharmacies that have matching drugs from the reliable manufacturers on different dates are used as matching purchase pharmacies on the dates, and the drug purchase distances on the different dates are determined based on the minimum distance between the matching purchase pharmacies on the different dates and the user's residential address; The purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers, the number ratio of matching deviation dates of different reliable manufacturers, and the drug purchase distance.

[0047] Furthermore, based on the overlap of matching deviation dates of different reliable manufacturers, the proportion of matching deviation dates of different reliable manufacturers, and the purchase distance, a purchase recommendation strategy for the user's matching drugs is determined, specifically including: When there is a reliable manufacturer whose number of matching deviation dates accounts for less than a preset date number ratio threshold and whose average purchase distance on different dates is less than the preset purchase distance threshold, the matching drug of the reliable manufacturer with the least number of matching deviation dates is used as the recommended matching drug processing result for the user; When there is no reliable manufacturer whose proportion of matching deviation dates is less than the preset date proportion threshold and the average value of drug purchase distances on different dates is less than the preset drug purchase distance threshold, the purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers.

[0048] It should also be noted that the purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers, specifically including: The reliable manufacturers are freely combined to generate multiple reliable manufacturer combinations, and based on the overlap of matching deviation dates of different reliable manufacturers, a date is determined on which the matching drugs of the reliable manufacturers in the reliable manufacturer combination all fall within the matching deviation date, and the date is used as the combination matching deviation date; Determine a reliable manufacturer combination whose proportion of combination matching deviation dates is less than the preset date proportion threshold, and use it as the target recommendation combination; The target recommendation combination with the least number of reliable manufacturers is used as the recommendation processing result of the matching medicine for the user.

[0049] Optionally, the method for determining the purchase recommendation strategy of the user's matching medicine is: Based on the out-of-stock data of the reliable manufacturer in different pharmacies on different dates, determine the date on which no matching drug from the reliable manufacturer exists in different pharmacies on different dates, and use the date as the matching deviation date; Pharmacies that have matching drugs from the reliable manufacturers on different dates are used as matching purchase pharmacies on the dates, and the drug purchase distances on the different dates are determined based on the minimum distance between the matching purchase pharmacies on the different dates and the user's residential address; Determine the recommended matching coefficient of the reliable manufacturer's drugs based on the percentage of matching deviation dates of the reliable manufacturer and the purchase distance on different dates. If there is a reliable manufacturer with a recommended matching coefficient greater than a preset recommended matching coefficient threshold, the matching drug of the reliable manufacturer with the largest recommended matching coefficient is used as the recommended matching drug processing result for the user. When there is no reliable manufacturer with a recommended matching coefficient greater than the preset recommended matching coefficient threshold: The reliable manufacturers are freely combined to generate multiple reliable manufacturer combinations. Based on the overlap of matching deviation dates of different reliable manufacturers, it is determined that the matching drugs of the reliable manufacturers in the reliable manufacturer combination all fall within the matching deviation date, and the date is used as the matching deviation date of the combination. If the proportion of the matching deviation dates of the combination does not meet the requirement, it is determined that the reliable manufacturer combination cannot be used as a recommended matching drug for the user; When the proportion of the combination matching deviation dates meets the requirements: Determine the minimum value of the purchase distances of the reliable drugs of the reliable manufacturer combination on different dates based on the purchase distances of the reliable drugs on different dates, and use the minimum value as the combined purchase distance; if the average value of the combined purchase distances of the reliable manufacturer combination on different dates does not meet the requirement, determine that the reliable manufacturer combination cannot be used as a recommended matching drug for the user; When the average value of the combined drug purchase distances of the reliable manufacturer combination on different dates meets the requirements: The combination matching coefficients of different reliable manufacturer combinations are determined based on the combination purchase distances of different reliable manufacturer combinations on different dates and the proportion of the number of combination matching deviation dates, and the purchase recommendation strategy for the user's matching drugs is determined using the combination matching coefficients.

[0050] Furthermore, the combination matching coefficient is used to determine a purchase recommendation strategy for the user's matching medicine, specifically including: The reliable manufacturer combination with the least number of reliable manufacturers whose combination matching coefficients are within the preset matching coefficient interval is used as the recommended processing result of the matching medicine for the user.

[0051] Example 2 Second, as Figure 5 As shown, the present invention provides a computer system, comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned drug management method that takes into account the analysis of purchase, sales and inventory data when running the computer program.

[0052] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0053] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0054] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A drug management method considering purchase, sales and inventory data analysis, characterized in that: Specifically include: Based on the user's diagnosis results, determine the user's matching drugs and reference purchasing users; Determine the user's target area based on the user's residential address, obtain inventory data of matching drugs from different manufacturers in different pharmacies in the target area, and determine the screening manufacturers among the manufacturers based on the historical purchase data of reference users who purchased the different matching drugs; Determining purchase review data of users who purchased matching drugs from different screened manufacturers, and determining reliable manufacturers from the screened manufacturers based on the correlation between keywords in the purchase review data and the types of concurrent diseases of the users, and the similarity between the diagnostic results of the purchasing users and the user; The purchase, sales and inventory data of matching drugs of reliable manufacturers in different pharmacies in the target area are used to determine the out-of-stock data of different pharmacies on different dates, and the purchase recommendation strategy of the matching drugs for the user is determined in combination with the distance between different pharmacies and the residential address of the user.

2. The drug management method considering purchase, sales and inventory data analysis according to claim 1, characterized in that: The diagnosis results include disease type, concurrent disease type and abnormal detection indicators.

3. The drug management method considering purchase, sales and inventory data analysis according to claim 1, characterized in that: The matching medicine for the user is determined based on the treatment medicine corresponding to the disease type.

4. The drug management method considering purchase, sales and inventory data analysis according to claim 1, characterized in that: The reference purchasing user is a purchasing user of matching drugs who has the same disease type and concurrent disease type as the user and whose data deviations from different abnormal detection indicators are within a preset deviation range.

5. The drug management method considering purchase, sales and inventory data analysis according to claim 1, characterized in that: The method for determining the screening manufacturers among the manufacturers is: Using inventory data of the manufacturer's matching drugs in different pharmacies in the target area, determining a pharmacy in the target area that has the manufacturer's matching drugs, and using the pharmacy as the matching pharmacy; Based on the historical purchase data of the reference purchasing users of the matching drugs, determining the reference purchasing users of the matching drugs of the manufacturer and using them as the matching purchasing users; Whether the manufacturer is a screened manufacturer is determined by the number of matched pharmacies and the number of matched purchasing users.

6. The drug management method considering purchase, sales and inventory data analysis according to claim 5, characterized in that: Determining whether the manufacturer is a screening manufacturer based on the number of matched pharmacies and the number of matched purchasing users includes: When the number of matching pharmacies of the manufacturer's matching drugs is greater than a preset pharmacy number threshold and the number of matching purchasing users is greater than a preset matching purchasing user number, the manufacturer is determined to be a screening manufacturer.

7. The drug management method considering purchase, sales and inventory data analysis according to claim 1, characterized in that: The out-of-stock data of the pharmacy is determined based on the monitoring data of the medical insurance system.

8. The drug management method considering purchase, sales and inventory data analysis according to claim 1, characterized in that: The method for determining the purchase recommendation strategy of the user's matching medicine is as follows: Based on the out-of-stock data of the reliable manufacturer in different pharmacies on different dates, determine the date on which no matching drug from the reliable manufacturer exists in different pharmacies on different dates, and use the date as the matching deviation date; Pharmacies that have matching drugs from the reliable manufacturers on different dates are used as matching purchase pharmacies on the dates, and the drug purchase distances on the different dates are determined based on the minimum distance between the matching purchase pharmacies on the different dates and the user's residential address; The purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers, the number ratio of matching deviation dates of different reliable manufacturers, and the drug purchase distance.

9. The drug management method considering purchase, sales and inventory data analysis according to claim 8, characterized in that: Based on the overlap of matching deviation dates of different reliable manufacturers, the proportion of matching deviation dates of different reliable manufacturers, and the purchase distance, a purchase recommendation strategy for the user's matching drugs is determined, specifically including: When there is a reliable manufacturer whose number of matching deviation dates accounts for less than a preset date number ratio threshold and whose average purchase distance on different dates is less than the preset purchase distance threshold, the matching drug of the reliable manufacturer with the least number of matching deviation dates is used as the recommended matching drug processing result for the user; When there is no reliable manufacturer whose proportion of matching deviation dates is less than the preset date proportion threshold and the average value of drug purchase distances on different dates is less than the preset drug purchase distance threshold, the purchase recommendation strategy for the user's matching drugs is determined based on the overlap of matching deviation dates of different reliable manufacturers.

10. A computer system comprising: A memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, characterized in that when the processor runs the computer program, a drug management method considering purchase, sales and inventory data analysis as described in any one of claims 1 to 9 is executed.

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