A method, device and equipment for determining medication data and dispensing

Abstract

The application discloses a kind of determining medication data and distribution method, device and equipment. Receive and associated data including historical diagnosis and treatment data, current symptom description information and location information associated with the user of medical treatment;Determine the keyword corresponding to associated data and the corresponding to-be-selected medication data based on at least two medication data recommendation methods;According to historical medication data and disease progression information, determine the target medication data corresponding to the keyword from the to-be-selected medication data;Determine the target distribution strategy corresponding to the target medication data based on the target medication data, location information and distribution demand;Based on the target distribution strategy, the target medicine corresponding to the target medication data is distributed to the target location corresponding to the location information, solves the reception user to issue prescription efficiency in the process of medical treatment Low, the rationality of issuing prescription is not guaranteed, the problem of complex interface in the process of issuing prescription and medicine distribution, improves the convenience of medical treatment and medicine distribution.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, and equipment for determining medication data and delivery. Background Technology

[0002] With the rapid development of telemedicine and internet-based medical services in China, more and more medical institutions are implementing online medical services to facilitate patients. In the current process of separating prescribing and dispensing, medical institutions or regional healthcare systems are prescribing a wider range of medications for patients, and patients have more and more channels to obtain and access their medications.

[0003] Currently, in existing medical services, the receiving physician diagnoses the patient's condition based on their description of their symptoms and combined with examinations and tests, and prescribes medication accordingly. After the prescription is issued, the medication is either delivered by express from the clinic's pharmacy, or the patient purchases the medication at a nearby pharmacy based on the prescription.

[0004] However, when prescribing medications, clinics often spend a significant amount of time searching for and selecting drugs. Sometimes, due to time constraints during diagnosis, the prescribed medications may not achieve the best therapeutic effect. Furthermore, during the medication delivery phase, clinic pharmacies frequently experience shortages, necessitating prescription splitting. In such cases, medications prescribed by clinics are delivered from different pharmacies to the patient's location at varying times, resulting in multiple pickups. When the clinic's prescription system interfaces with external pharmacies, multiple integrations, complex processing logic, and low efficiency arise. Summary of the Invention

[0005] This invention provides a method, apparatus, and equipment for determining medication data and delivery, enabling dynamic generation of drug recommendations and delivery strategies, thereby improving the convenience of medical treatment and medication acquisition, and ensuring the recovery process of patients.

[0006] In a first aspect, the present invention provides a method for determining medication data and delivery, the method comprising:

[0007] Receive associated data related to patients; wherein, the associated data includes historical medical data, current symptom description information and location information, and the historical medical data includes historical symptom description data and historical medication data;

[0008] Based on at least two medication data recommendation methods, determine at least one keyword corresponding to the associated data and corresponding medication data to be selected;

[0009] Based on the historical medication data and disease progression information, target medication data corresponding to the at least one keyword is determined from the drug selection data;

[0010] Based on the target medication data, the location information, and at least one delivery requirement, a target delivery strategy corresponding to the target medication data is determined;

[0011] Based on the target delivery strategy, the target medicine corresponding to the target medication data will be delivered to the target location corresponding to the location information.

[0012] In a second aspect, the present invention provides a device for determining medication data and delivery, the device comprising:

[0013] The associated data receiving module is used to receive associated data related to the patient; wherein, the associated data includes historical medical data, current symptom description information and location information, and the historical medical data includes historical symptom description data and historical medication data;

[0014] The medication data determination module is used to determine at least one keyword corresponding to the associated data and the corresponding medication data to be selected based on at least two medication data recommendation methods.

[0015] The target medication determination module is used to determine the target medication data corresponding to the at least one keyword from the drug selection data based on the historical medication data and disease progression information.

[0016] The delivery strategy determination module is used to determine a target delivery strategy corresponding to the target medication data based on the target medication data, the location information, and at least one delivery requirement;

[0017] The target drug delivery module is used to deliver the target drug corresponding to the target medication data to the target location corresponding to the location information based on the target delivery strategy.

[0018] Thirdly, the present invention provides a data processing electronic device, comprising:

[0019] At least one processor; and

[0020] A memory that is communicatively connected to at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the determination of medication data and delivery method according to any embodiment of the present invention.

[0022] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the medication determination data and delivery method of any embodiment of the present invention.

[0023] Fifthly, the present invention provides a computer program product, which includes a computer program that, when executed by a processor, implements the medication data determination and delivery method of any embodiment of the present invention.

[0024] The technical solution provided by this invention receives associated data related to a patient, including historical medical data, current symptom description information, and location information. The historical medical data includes historical symptom description data and historical medication data. Based on at least two medication data recommendation methods, at least one keyword corresponding to the associated data and corresponding candidate medication data are determined. Further, based on historical medication data and disease progression information, target medication data corresponding to at least one keyword is determined from the candidate medication data. Subsequently, based on the target medication data, location information, and at least one delivery requirement, a target delivery strategy corresponding to the target medication data is determined. Finally, based on the target delivery strategy, the target medication corresponding to the target medication data is delivered to the target location corresponding to the location information. This invention addresses the problems of low efficiency in prescribing medications, lack of assurance regarding the rationality of prescriptions, and complex coordination in the medication delivery process. It establishes a unified, distributed information system within a certain area, dynamically generating medication recommendations and delivery strategies based on multi-dimensional data such as patient association information, disease progression information, and delivery needs. This improves the convenience of medical visits and medication delivery, ensuring the patient's recovery process.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a method for determining medication data and delivery, provided in Embodiment 1 of the present invention;

[0028] Figure 2 This is a flowchart of a method for determining medication data and delivery, provided in Embodiment 2 of the present invention;

[0029] Figure 3 This is a schematic diagram of a method for determining medication data and delivery provided in Embodiment 3 of the present invention;

[0030] Figure 4 This is a flowchart of a method for determining medication data and delivery, provided in Embodiment 3 of the present invention;

[0031] Figure 5 This is a schematic diagram of a medication data determination and delivery device provided in Embodiment 4 of the present invention;

[0032] Figure 6 This is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first preset condition," "second preset condition," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] Before introducing this technical solution, an exemplary application scenario can be provided. This invention is applicable to the process of seeking medical treatment at offline physical medical institutions, or during online medical services, by recommending suitable medications to patients based on their associated data, and by employing a highly convenient delivery strategy to deliver the prescribed medications to the patients.

[0036] Example 1

[0037] Figure 1 This is a flowchart illustrating a method for determining medication data and delivery according to Embodiment 1 of the present invention. This embodiment is applicable to situations where medications for treating illnesses are determined based on the associated data of patients, and the medications are delivered to the patients. This method can be executed by a device for determining medication data and delivery. This device can be implemented in hardware and / or software and can be configured on a computer device, such as a laptop, desktop computer, or tablet. Figure 1 As shown, the method includes:

[0038] S110, Receive associated data related to the patient.

[0039] In this application, any user can be a patient. Patients can provide relevant data, which is then used to recommend medications for their conditions. This relevant data includes historical medical records, current symptom descriptions, and location information. Historical medical records include historical symptom descriptions and historical medication data. Historical symptom descriptions are the patient's subjective description of their symptoms before the current visit. Historical medication data consists of medications used by the patient before the current visit. Current symptom descriptions are the patient's subjective description of their symptoms during the current visit. Location information can be the patient's residential address. Obtaining location information is for the purpose of delivering appropriate medications to the patient.

[0040] In this embodiment, patients can seek medical treatment at offline physical medical institutions or online medical institutions. If a patient seeks treatment at an offline physical medical institution, the historical treatment data, current symptom description information, and location information contained in the associated data can be conveyed to the receiving user. The receiving user can then enter the patient's associated data into the pre-developed system in text form. If a patient seeks medical treatment online, the patient can input the associated information into the pre-developed system in text form through a pre-configured associated information input page.

[0041] In practical applications, a subpage for entering historical medical data and current symptom descriptions can be provided within a pre-configured associated information entry page. Patients at medical institutions or those seeking online medical care can access these subpages by triggering corresponding controls, and then complete the relevant information entry using the edit boxes within the subpage. Regarding location information, if the patient is seeking treatment at an offline medical institution, their location information can be provided and entered by the receiving patient. In the case of online medical care, the location information can be detected using a positioning device on the patient's mobile device, and the confirmed location information can be entered into the pre-developed system. Based on this, after the associated data entry is completed, the system can receive the patient's associated data.

[0042] S120. Based on at least two medication data recommendation methods, determine at least one keyword corresponding to the associated data and the corresponding medication data to be selected.

[0043] The "selectable medication data" consists of multiple medication options for the patient to choose from. The patient can then select the final medication from these options. Medication delivery is then completed based on the final selected medication data. Keywords are text terms related to the patient's symptoms, determined by a medication data recommendation method based on associated data. There can be multiple keywords.

[0044] In this embodiment, the medication data recommendation method can include various approaches. It could be that the receiving user determines the relevant keywords and corresponding medication data based on the patient's associated data and their medical experience; it could also be based on a rule-matching algorithm, which splits the associated data according to pre-defined rules to determine the relevant keywords and corresponding medication data; or it could be based on an association recommendation algorithm, which analyzes and processes the associated data according to a pre-defined recommendation algorithm to determine the relevant keywords and corresponding medication data.

[0045] Based on the above embodiments, determining at least one keyword corresponding to the associated data and the corresponding drug data to be selected based on at least two medication data recommendation methods may include the following steps:

[0046] S121. Based on the analysis and processing of related data of target patients, determine at least one first-type keyword.

[0047] In this context, "target patients" can be understood as patients who will prescribe medication for those seeking medical attention. The first type of keywords consists of related terms determined by the target patients based on relevant data and their own medical experience.

[0048] In this embodiment, the target patient can analyze and process the associated data of the patient based on their professional knowledge and years of medical experience to determine one or more keywords.

[0049] S122. Based on the rule matching algorithm, the historical symptom description data and the current symptom description data in the associated data are split to obtain at least one second type of keyword.

[0050] The first type of keyword is the rule-matching algorithm, which is a pre-defined algorithm. This algorithm can be encapsulated into a model that directly extracts keywords; this model is called the rule-matching algorithm model. The second type of keyword is determined by the rule-matching algorithm through splitting historical and current symptom description data within the associated data.

[0051] In this embodiment, the historical symptom description data and current symptom description data of the patient can be input into the rule matching algorithm model. The rule matching algorithm model can split the input data to determine the second type of keywords.

[0052] S123. Analyze historical symptom description data and current symptom description data based on the association recommendation algorithm to obtain at least one third-type keyword.

[0053] In this embodiment, the association recommendation algorithm can also be encapsulated into an association recommendation algorithm model capable of keyword extraction. The third type of keyword is the keyword determined by the association recommendation algorithm through analysis of historical symptom description data and current symptom description data in the associated data.

[0054] In practical applications, the historical symptom description data and current symptom description data of patients can be input into the association recommendation algorithm model. The association recommendation algorithm model can analyze the input data to determine the third type of keywords.

[0055] S124. Based on at least one first-type keyword, at least one second-type keyword, and at least one third-type keyword, determine at least one keyword.

[0056] In this embodiment, if the first type of keyword, at least one second type of keyword, and at least one third type of keyword all contain the same keyword, then that keyword is retained. If none of the first type of keyword, at least one second type of keyword, and at least one third type of keyword contain the same keyword, then based on the second type of keyword, some keywords from the at least one first type of keyword and at least one third type of keyword are removed. At this point, at least one keyword can be identified. Based on this, multiple keywords can be identified, and these multiple keywords can be fed back to the target patient, who can then determine which keyword to retain and which to remove. The at least one keyword ultimately identified is related to the patient's symptoms.

[0057] S125. Based on prescription data stored in the database corresponding to at least one keyword, determine the drug data to be selected for at least one keyword.

[0058] In this embodiment, prescription data corresponding to keywords can be pre-stored in the database, and the correspondence between keywords and prescription data can be stored in key-value pairs. For example, the keyword is "insomnia," and the corresponding prescription data is "drug A." After determining at least one keyword, the data stored in the database can be retrieved and indexed to determine the medication data to be selected corresponding to at least one keyword.

[0059] For example, if at least one keyword includes "insomnia", "fatigue" and "headache", and the prescription data corresponding to the keyword "insomnia" stored in the database in advance are "drug A" and "drug B"; and the prescription data corresponding to "fatigue" and "headache" is "drug C", then "drug A", "drug B" and "drug C" will be used as the drug data to be selected.

[0060] Based on the above embodiments, the target medication data includes partial medication data from historical medication data and alternative medication data corresponding to the partial medication data.

[0061] In this embodiment, if the drugs corresponding to some medication data in the historical medication data have an effect on improving the symptoms of the patient, then this part of the medication data is retained; if the drugs corresponding to some medication data in the historical medication data do not have an effect on improving the symptoms of the patient, then this part of the medication data is replaced, and the historical medication data that has no effect on the patient is replaced with new medication data.

[0062] It should be noted that the prescription data in S125 of this embodiment can be used as training reference data for the drug association recommendation system in S123. It can be repeatedly added to the database as the data basis for drug recommendation analysis when other patients with similar symptoms visit the same hospital. Similarly, the doctor's suggestions for modifying the recommendation scheme during this visit can be used as high-weight correction rules in the system's recommendation algorithm in S122 to enrich the rule engine and improve the accuracy of the system's recommendations.

[0063] S130. Based on historical medication data and disease progression information, determine the target medication data corresponding to at least one keyword from the medication data to be selected.

[0064] Among them, disease progression information can characterize the direction of disease development for patients. For example, disease progression information can include disease relief or no change in disease status.

[0065] In this embodiment, some patients are first-time visitors, while others are repeat visitors. If a patient is a first-time visitor, the attending physician directly selects the target medication from a pool of available options. If the patient has a chronic illness, or has a prior medical history, the physician first assesses the patient's disease progression to determine the effectiveness of any medications taken prior to this visit.

[0066] In practical applications, for patients who are not first-time visitors, if the symptom progression information indicates symptom relief after assessing the symptoms, it means that the medications corresponding to the historical medication data are effective for the patient's condition. In this case, while retaining the historical medication data, target medication data corresponding to at least one keyword can be determined from the pool of available medications. If the symptom progression information indicates no change in symptoms, it means that the historical medications have no therapeutic effect on the patient's condition. In this case, some medications corresponding to the historical medication data need to be removed, and medications that can replace the historical medications need to be determined from the pool of available medications, thus identifying the target medication data corresponding to at least one keyword.

[0067] For example, for user A who is not a first-time visitor, user A's historical medication data includes medication 1, and the medication data to be selected includes medication 2, medication 3, and medication 4. Medication 1, medication 2, medication 3, and medication 4 correspond to a specific keyword. After analyzing user A's symptoms, if the symptoms are determined to be improving, then medication 1 can be retained, and medication 3 can be selected from medications 2, 3, and 4 as the new medication for this visit. Medication 1 and medication 3 will then be used as the target medication data. If the symptoms remain unchanged, then medication 1 is removed, and medication 3 can be selected from medications 2, 3, and 4 as the new medication for this visit. Medication 4 can then be selected to replace medication 1, and medications 3 and 4 will then be used as the target medication data.

[0068] S140. Based on the target medication data, location information, and at least one delivery requirement, determine the target delivery strategy corresponding to the target medication data.

[0069] Delivery demand is relative to the patient seeking medical treatment. Delivery demand includes at least one of the following: timeliness requirements, distance requirements, value attribute requirements, delivery cost requirements, order quantity splitting, and delivery origin / origin. The target delivery strategy is the specific delivery method used when delivering medications corresponding to the target medication data. The target delivery strategy may include which pharmacy the delivery person picks up the medication from and what route is used to deliver the target medication.

[0070] Specifically, after determining the target medication data and location information, the specific medications to be delivered and their destinations can be determined. Multiple pharmacies may have identified target medications, but the exact pharmacy from which the delivery person picks up the medication and the delivery route can be determined based on delivery requirements. In practical applications, multiple delivery request options can be pre-set for patients to choose from. For example, controls corresponding to various delivery requests can be displayed on the patient's mobile device screen. Patients can trigger the corresponding controls based on their actual situation to select their delivery request. Based on this, the specific types of medications to be delivered, the delivery destination, the delivery origin, and the delivery route are all determined, allowing for the establishment of a target delivery strategy corresponding to the target medication data.

[0071] S150. Based on the target delivery strategy, the target medicine corresponding to the target medication data is delivered to the target location corresponding to the location information.

[0072] The target drug refers to the drug indicated by the target medication data. For example, the target medication data could be the Chinese name of the target drug or a pre-defined drug code, while the target drug is the actual drug. The target location is the specific location corresponding to the location information of the patient.

[0073] In this embodiment, after determining the target delivery strategy, the delivery person can pick up the target medicine from the pharmacy determined in the target delivery strategy, and then deliver the target medicine to the target location corresponding to the location information according to the route planned by the system.

[0074] The technical solution provided by this invention receives associated data related to a patient, including historical medical data, current symptom description information, and location information. The historical medical data includes historical symptom description data and historical medication data. Based on at least two medication data recommendation methods, at least one keyword corresponding to the associated data and corresponding candidate medication data are determined. Further, based on historical medication data and disease progression information, target medication data corresponding to at least one keyword is determined from the candidate medication data. Subsequently, based on the target medication data, location information, and at least one delivery requirement, a target delivery strategy corresponding to the target medication data is determined. Finally, based on the target delivery strategy, the target medication corresponding to the target medication data is delivered to the target location corresponding to the location information. This invention addresses the problems of low efficiency in prescribing medications, lack of assurance regarding the rationality of prescriptions, and complex coordination in the medication delivery process. It establishes a unified, distributed information system within a certain area, dynamically generating medication recommendations and delivery strategies based on multi-dimensional data such as patient association information, disease progression information, and delivery needs. This improves the convenience of medical visits and medication delivery, ensuring the patient's recovery process.

[0075] Example 2

[0076] Figure 2 This is a flowchart of a method for determining medication data and delivery, provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment further refines the content corresponding to S130 and S140 of the aforementioned embodiments. This embodiment can be combined with various optional solutions from one or more of the above embodiments. For example... Figure 2 As shown, the method includes:

[0077] S210, Receive associated data related to the patient.

[0078] S220. Based on at least two medication data recommendation methods, determine at least one keyword corresponding to the associated data and the corresponding medication data to be selected.

[0079] S230. Determine whether the disease progression information is consistent with the preset disease progression.

[0080] Among them, the preset disease progression refers to the pre-defined disease progression information, such as the preset disease progression being "disease relief".

[0081] In this embodiment, if the disease progression information is consistent with the preset disease progression, then S231 is executed; if the disease progression information is inconsistent with the preset disease progression, then S232 is executed.

[0082] S231. If not, then remove some medication data from the candidate medication data based on the historical medication duration corresponding to the historical medication data; determine the target medication data based on the removed medication data and the candidate medication data.

[0083] In this embodiment, if the preset symptom progression for a single symptom is "symptom relief," but the actual symptom progression for the patient is "symptom worsening," then the symptom progression information is inconsistent with the preset progression, indicating that some medications in the historical medication data have no therapeutic effect on the patient's symptom. For example, if the patient's historical medication data includes medication A corresponding to the current symptom, and the historical duration of medication A is one month, then it can be known that medication A is ineffective for the patient. If medication A is still included in the list of available medications, then medication A is removed from the list. From the list of available medications after removing medication A, the target medication data corresponding to the patient's keywords can then be determined.

[0084] S232. If so, retain historical medication data; based on historical medication data and medication data to be selected, determine the target medication data corresponding to the relevant keywords.

[0085] Based on the above example, if the preset symptom progression is "symptom relief," and the actual symptom progression information of the patient is also "symptom relief," then the symptom progression information is consistent with the preset symptom progression, indicating that some of the corresponding drugs in the historical medication data have a therapeutic effect on the patient's symptom. For example, if the patient's historical medication data includes drug B corresponding to the current symptom, then the target medication data will still include drug B. In addition, the target medication data also includes drug data other than drug B from the drug selection data; the specific drug data included can be determined by the target patient.

[0086] Based on the above embodiments, the target medication data includes partial medication data from historical medication data and alternative medication data corresponding to the partial medication data.

[0087] In this embodiment, if the drugs corresponding to some medication data in the historical medication data have an effect on improving the symptoms of the patient, then this part of the medication data is retained; if the drugs corresponding to some medication data in the historical medication data do not have an effect on improving the symptoms of the patient, then this part of the medication data is replaced, and the historical medication data that has no effect on the patient is replaced with new medication data.

[0088] S240: Obtain at least one pre-set delivery request.

[0089] In practical applications, multiple delivery request options can be pre-set for users to choose from. Controls corresponding to these delivery requests are displayed on the user's mobile terminal screen. The user or the receiving administrator can trigger these controls based on the user's preferences, thus selecting a delivery request and inputting at least one request into the system. When determining the target delivery strategy later, the selected delivery requests can be retrieved. It is important to note that if the user does not select any delivery requests, the default delivery requests will be used to determine the target delivery strategy.

[0090] S250. Based on the target medication data and location information, determine the delivery information to be selected for at least one delivery demand.

[0091] The delivery options are corresponding to delivery needs, with different delivery needs corresponding to different delivery options. There can be multiple options, from which the final target delivery strategy can be determined.

[0092] In this embodiment, after determining the target medication data and location information, it is possible to determine what specific medications will be delivered and the destinations to which these medications will be delivered. Based on at least one delivery requirement, alternative delivery information corresponding to the delivery requirement can be determined.

[0093] For example, if the delivery requirement is a "distance requirement", the delivery information to be selected may include: target medication data, location information, and the pharmacy closest to the patient's location that has the target medication.

[0094] Based on the above embodiments, according to the target medication data and location information, the candidate delivery information corresponding to at least one delivery demand is determined, including: based on the target medication data, the remaining medication information in the historical medication data and the location information, the candidate delivery information corresponding to each delivery demand is determined.

[0095] In this embodiment, based on the remaining medication information, it can be determined whether the medication that is effective for the patient's condition in the historical medication data needs to be delivered again in this delivery.

[0096] In this embodiment, if the remaining medication information indicates that the patient still has a large number of medications corresponding to historical medication data, then the corresponding medications will not be delivered in this delivery. Historical medication data can be removed from the target medication data, and then the delivery information to be selected can be determined based on the location information and the corresponding delivery requirements. If the remaining medication information indicates that the number of medications corresponding to the patient's historical medication data is not large, then the corresponding medications will be delivered in this delivery.

[0097] S260: Feedback the delivery information to be selected to the target client.

[0098] The target client is the client corresponding to the patient or the user receiving the treatment. The target client can be a mobile phone, smartwatch, tablet, or computer. If the patient is receiving treatment at an offline medical institution, the target client can be the client corresponding to the user receiving the treatment; if the patient is receiving treatment online, the target client can be the client corresponding to the patient receiving the treatment.

[0099] In this embodiment, after determining the delivery information to be selected, the delivery information can be fed back to the target client corresponding to the patient or the receiving user. The patient or the receiving user can select one of the delivery information to be selected based on the feedback.

[0100] S270. Based on the triggering operation on the target client, determine the target delivery strategy from the delivery information to be selected.

[0101] In this implementation, multiple delivery options can be displayed on the target client's display page for the user to choose from. A corresponding trigger control can be configured for each delivery option. When the user triggers the control corresponding to a delivery option, a target delivery strategy can be generated based on that delivery option.

[0102] S280. Based on the target delivery strategy, the target medicine corresponding to the target medication data is delivered to the target location corresponding to the location information.

[0103] Based on the above embodiments, the method further includes: updating the target medication data to the database corresponding to the patient, and updating the weight value of at least one delivery request corresponding to the patient based on the target medication data; determining the sorting order corresponding to the delivery information to be selected based on the corresponding weight value, and displaying it based on the sorting order.

[0104] In this embodiment, a database unique to each patient can be established. After determining the target medication data, this data can be updated in the database corresponding to the patient. If the patient's symptoms improve after taking the medication from the target medication data, it indicates that the medication is effective, and the weight of the medication data corresponding to this type of medication can be increased, thereby increasing the weight of delivery requests for this type of medication. Conversely, if the patient's symptoms worsen after taking a certain medication, the weight of the medication data corresponding to this type of medication can be significantly decreased, thereby decreasing the weight of delivery requests for this type of medication. Based on this, after adjusting the weight values ​​of delivery requests, the order of the corresponding delivery options can be determined. When displaying the delivery options, they can be presented according to the sorting order. In this way, different medication data is recommended for different patients, achieving the effect of personalized medication recommendations.

[0105] The technical solution provided by this invention receives associated data related to a patient, including historical medical data, current symptom description information, and location information. The historical medical data includes historical symptom description data and historical medication data. Based on at least two medication data recommendation methods, at least one keyword corresponding to the associated data and corresponding candidate medication data are determined. Further, the method determines whether the symptom progression information is consistent with a preset symptom progression. If the symptom progression information is inconsistent with the preset symptom progression, a portion of the medication data is removed from the candidate medication data based on the historical medication duration corresponding to the historical medication data. The target medication data is then determined based on the removed medication data and the candidate medication data. If the symptom progression information is consistent with the preset symptom progression, the historical medication data is retained. The target medication data corresponding to the corresponding keyword is then determined based on the historical medication data and the candidate medication data. Subsequently, at least one pre-set delivery request can be obtained, and based on the target medication data and location information, the candidate delivery information corresponding to the at least one delivery request can be determined. Then, the candidate delivery information is fed back to the target client, so that a target delivery strategy can be determined from the candidate delivery information based on the triggered operation on the target client. Finally, based on the target delivery strategy, the target medication corresponding to the target medication data is delivered to the target location corresponding to the location information. This invention can determine the target medication data based on the patient's association information and disease progression information, and can generate a target delivery strategy corresponding to the target medication data based on the user's delivery request. This achieves the effect of personalized medication recommendation data, further improving the convenience of medical visits and medication delivery, and ensuring the recovery process of the patient.

[0106] Example 3

[0107] In this embodiment of the invention, a specific implementation method for determining medication data and a delivery method is described. Figure 3 This is a schematic diagram of a method for determining medication data and delivery, provided in Embodiment 3 of the present invention. Figure 3 As shown, this embodiment uses a regional specialist alliance as the main body to establish a cloud platform for determining medication data and delivery. The cloud platform mainly provides unified indexing services, related recommendation algorithm training and inference services, centralized control services, and cloud storage services. This method establishes multiple sub-centers (sub-center A, sub-center B, ... sub-center Z) based on offline medical institutions and internet-based medical service systems. Each sub-center operates independently, collecting real-time information on local patients, pharmacy drug information, and pharmacy drug catalogs according to its region. The cloud platform can connect patients, internet-based medical service systems, medical institution HIS systems, and pharmacies within the region, forming a unified distributed information system within a certain area. It can dynamically generate drug recommendations and delivery strategies based on multi-dimensional data such as patient information, diagnostic information, drug availability, pharmacy and pharmaceutical company inventory, and location conditions.

[0108] The cloud platform's unified indexing service generates a globally unique hash index using factors such as drug number, patient's illness type, drug's location, symptom changes observed after the patient took the drug, number of times the drug was prescribed for a specific symptom, and prescription time. During data collection, each branch center uses the cloud platform's unified indexing service to create a hash index, distributes it to each branch center, and associates it with local patient information, illness type, and examination symptoms in the database. Simultaneously, the cloud platform also records a copy of the unified index and its association with illness type and examination symptoms for easy global querying.

[0109] The cloud platform's centralized control service is used to manage and maintain information for each branch center and monitor the operation of each branch center in real time. When global data is accessed, the control service distributes the data to the branch centers according to the query conditions.

[0110] The cloud platform's association recommendation algorithm is used to train the algorithm based on all the drugs on the cloud platform and the corresponding patient's disease type, condition description, continuous treatment orders, examination and test reports, health data changes, patient's own information, adverse symptoms, location, inventory, express delivery history, drug data of each pharmacy, and geographical location information. It is also used to provide each branch center with the drugs that can be prescribed when querying, as well as the recommended list of supply information.

[0111] The cloud storage service of the cloud platform is used to store data such as a unified index, information of each branch center, all drug information, all patient information, and all medical institution information.

[0112] Figure 4 This is a flowchart of a method for determining medication data and delivery provided in Embodiment 3 of the present invention. The following example, using an online follow-up consultation service of an internet-based medical institution on a regional cloud platform, illustrates the application process of the technical solution of the present invention:

[0113] 1. Medical Treatment for Patients: Through the client software of the Internet medical institution, patients register, seek medical treatment, introduce their symptoms and medical history to the receiving user, upload examination and test reports, imaging files, historical prescriptions and other information, answer the receiving user's questions, and submit prescription requests (including examination and test results) to the receiving user. All information is sent and uploaded to the Internet medical institution's system (as opposed to the branch center system of the cloud platform).

[0114] 2. Internet-based medical institutions upload patient information: The system of internet-based medical institutions uploads all patient information to the cloud platform, and at the same time requests all cloud-based drug information suitable for the patient from the unified index service of the cloud platform.

[0115] 3. Cloud Platform Feedback: The cloud platform will feed back all information on suitable medications and pharmacies for the patient's condition to the internet-based medical institution system.

[0116] 4. The internet-based medical institution system will provide the patient's information and the drug information fed back to the platform to the receiving patient.

[0117] 5. Prescriptions are issued to patients and the results are fed back to the online medical service system.

[0118] 6. The online medical institution system queries and analyzes the prescription drugs on the cloud platform: The online medical institution system queries the cloud platform for recommendations of all drugs in the prescription and sends them to the pharmacy and more suitable drugs.

[0119] 7. The cloud platform provides recommendations to the online medical institution system: Based on the patient's information and the medications prescribed, the cloud platform provides feedback to the online medical institution system on the medication and dosage assessment, suitable pharmacies in the region, and possible alternative medications.

[0120] 8. Feedback from the Internet-based medical service system to patients: The Internet-based medical service system will send the cloud platform's assessment results and recommended pharmacies and medications to patients for reference.

[0121] 9. Patients will send their feedback to the online medical service system.

[0122] 10. The online medical service system will push the final prescription results and recommended purchase methods to the patients.

[0123] 11. Patients confirm and pay for the final prescription and recommended purchase method through the online medical service system.

[0124] 12. The internet-based medical service system sends a prescription order to pharmacy A within the region.

[0125] 13. Pharmacy A within the region confirms the order and information such as medication pickup and delivery, and then feeds it back to the Internet medical institution system.

[0126] 14. The online medical service system provides patients with feedback on order and medication delivery information.

[0127] 15. The internet-based medical service system stores the drug prescription and analysis records to the cloud platform as an optimized dataset for training the recommendation algorithm.

[0128] 16. The cloud platform's association recommendation algorithm periodically retrieves data from cloud storage.

[0129] 17. Cloud storage feeds data back to the cloud platform's related recommendation algorithm.

[0130] 18. The cloud platform's association recommendation algorithm is retrained and optimized based on the acquired data.

[0131] The technical solution provided by this invention can determine target medication data based on the associated information and disease progression information of the patient, and generate a target delivery strategy corresponding to the target medication data based on the user's delivery needs. This can achieve the effect of personalized medication recommendation data, improve the convenience of medical treatment and medication, and ensure the recovery process of the patient.

[0132] Example 4

[0133] Figure 5 This is a schematic diagram of a medication data determination and delivery device provided in Embodiment 4 of the present invention. The device can execute the medication data determination and delivery method provided in this embodiment of the invention. The device includes: a related data receiving module 410, a medication data determination module 420, a target medication determination module 430, a delivery strategy determination module 440, and a target drug delivery module 450.

[0134] The associated data receiving module 410 is used to receive associated data related to the patient; wherein, the associated data includes historical medical data, current symptom description information and location information, and the historical medical data includes historical symptom description data and historical medication data;

[0135] The medication data determination module 420 is used to determine at least one keyword corresponding to the associated data and corresponding medication data to be selected based on at least two medication data recommendation methods.

[0136] The target medication determination module 430 is used to determine target medication data corresponding to the at least one keyword from the drug selection data based on the historical medication data and disease progression information.

[0137] The delivery strategy determination module 440 is used to determine a target delivery strategy corresponding to the target medication data based on the target medication data, the location information, and at least one delivery requirement;

[0138] The target drug delivery module 450 is used to deliver the target drug corresponding to the target medication data to the target location corresponding to the location information based on the target delivery strategy.

[0139] Based on the above technical solutions, the medication data determination module 420 further includes: a first keyword determination unit, a second keyword determination unit, a third keyword determination unit, a keyword determination unit, and a medication data determination unit.

[0140] The first keyword determination unit is used to analyze and process related data based on the target patients to determine at least one first-type keyword.

[0141] The second keyword determination unit is used to split the historical symptom description data and the current symptom description data in the associated data based on the rule matching algorithm to obtain at least one second type keyword;

[0142] The third keyword determination unit is used to analyze historical symptom description data and current symptom description data based on the association recommendation algorithm to obtain at least one third type of keyword;

[0143] The keyword determination unit is used to determine at least one keyword based on at least one first-type keyword, at least one second-type keyword, and at least one third-type keyword;

[0144] The medication data determination unit is used to determine the medication data to be selected for at least one keyword based on prescription data corresponding to at least one keyword stored in the database.

[0145] Based on the above technical solutions, the target medication determination module 430 also includes a medication data elimination unit and a target data determination unit.

[0146] The medication data removal unit is used to remove part of the medication data from the drug data to be selected if the disease progression information is inconsistent with the preset disease progression.

[0147] The target data determination unit is used to determine the target drug data based on the excluded drug data and the drug data to be selected.

[0148] Based on the above technical solutions, the target medication determination module 430 also includes a medication data retention unit and a target data determination unit.

[0149] The medication data retention unit is used to retain historical medication data if the disease progression information is consistent with the preset disease progression.

[0150] The target data determination unit is used to determine the target drug data corresponding to the relevant keywords based on historical drug use data and drug use data to be selected.

[0151] Based on the above technical solutions, the target medication data includes partial medication data from historical medication data and alternative medication data corresponding to the partial medication data.

[0152] Based on the above technical solutions, the delivery strategy determination module 440 also includes: a delivery demand acquisition unit, a candidate delivery information determination unit, a delivery information feedback unit, and a target delivery strategy determination unit.

[0153] The delivery demand acquisition unit is used to acquire at least one pre-set delivery demand; wherein the delivery demand includes at least one of the following: timeliness demand, distance demand, value attribute demand, delivery cost demand, order split quantity, and delivery origin and destination;

[0154] The unit for determining delivery information to be selected is used to determine the delivery information to be selected corresponding to at least one delivery demand based on the target medication data and location information.

[0155] The delivery information feedback unit is used to send the delivery information to be selected to the target client.

[0156] The target delivery strategy determination unit is used to determine the target delivery strategy from the delivery information to be selected based on the triggering operation on the target client.

[0157] Based on the above technical solutions, the delivery strategy determination module 440 is also used to determine the delivery information to be selected for each delivery need based on the target medication data, the remaining medication information in the historical medication data, and the location information.

[0158] Based on the above technical solutions, the determination of medication data and delivery devices also includes: a weight value update unit and a delivery information display unit.

[0159] The weight value update unit is used to update the target medication data to the database corresponding to the patient, and update the weight value of at least one delivery request corresponding to the patient based on the target medication data.

[0160] The delivery information display unit is used to determine the sorting order of the delivery information to be selected based on the corresponding weight values, and to display the information based on the sorting order.

[0161] The technical solution provided by this invention receives associated data related to a patient, including historical medical data, current symptom description information, and location information. The historical medical data includes historical symptom description data and historical medication data. Based on at least two medication data recommendation methods, at least one keyword corresponding to the associated data and corresponding candidate medication data are determined. Further, based on historical medication data and disease progression information, target medication data corresponding to at least one keyword is determined from the candidate medication data. Subsequently, based on the target medication data, location information, and at least one delivery requirement, a target delivery strategy corresponding to the target medication data is determined. Finally, based on the target delivery strategy, the target medication corresponding to the target medication data is delivered to the target location corresponding to the location information. This invention addresses the problems of low efficiency in prescribing medications, lack of assurance regarding the rationality of prescriptions, and complex coordination in the medication delivery process. It establishes a unified, distributed information system within a certain area, dynamically generating medication recommendations and delivery strategies based on multi-dimensional data such as patient association information, disease progression information, and delivery needs. This improves the convenience of medical visits and medication delivery, ensuring the patient's recovery process.

[0162] The medication data determination and delivery device provided in this disclosure can execute the medication data determination and delivery method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0163] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of this disclosure.

[0164] Example 5

[0165] Figure 6This is a schematic diagram of an electronic device provided in Embodiment 5 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0166] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0167] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0168] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as determining medication data and delivery methods.

[0169] In some embodiments, the determination of medication data and delivery method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the determination of medication data and delivery method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the determination of medication data and delivery method by any other suitable means (e.g., by means of firmware).

[0170] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0171] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a general-purpose computer, a special-purpose computer, or other programmable processor for determining medication data and delivery devices, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0172] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0173] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0174] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0175] A computing system may include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is established by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within the cloud computing service system, addressing the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability. It should be understood that various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of this invention are achieved, and this is not limited herein. The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining medication data and delivery, characterized in that, include: Receive associated data related to patients; wherein, the associated data includes historical medical data, current symptom description information and location information, and the historical medical data includes historical symptom description data and historical medication data; Based on at least two medication data recommendation methods, determine at least one keyword corresponding to the associated data and corresponding medication data to be selected; Based on the historical medication data and disease progression information, target medication data corresponding to the at least one keyword is determined from the drug selection data; Based on the target medication data, the location information, and at least one delivery requirement, a target delivery strategy corresponding to the target medication data is determined; wherein, the delivery requirement includes at least one of timeliness requirement, distance requirement, value attribute requirement, delivery cost requirement, order split quantity, and delivery origin. Based on the target delivery strategy, the target medicine corresponding to the target medication data will be delivered to the target location corresponding to the location information. The step of determining at least one keyword corresponding to the associated data and corresponding drug selection data based on at least two medication data recommendation methods includes: Based on the analysis and processing of the associated data of the target patients, at least one first type of keyword is identified; Based on the rule matching algorithm, the historical symptom description data and the current symptom description information in the associated data are split to obtain at least one second type of keyword; The historical symptom description data and the current symptom description information are analyzed based on the association recommendation algorithm to obtain at least one third type of keyword; Based on the at least one first-type keyword, the at least one second-type keyword, and the at least one third-type keyword, determine at least one keyword; Based on the prescription data corresponding to the at least one keyword stored in the database, the candidate medication data for the at least one keyword is determined.

2. The method according to claim 1, characterized in that, The step of determining target medication data corresponding to at least one keyword from the candidate medication data based on the historical medication data and disease progression information includes: If the disease progression information is inconsistent with the preset disease progression, then some medication data will be removed from the drug data to be selected based on the historical medication duration corresponding to the historical medication data. Based on the excluded medication data and the medication data to be selected, the target medication data is determined.

3. The method according to claim 2, characterized in that, Also includes: If the disease progression information is consistent with the preset disease progression, then the historical medication data is retained; Based on the historical medication data and the medication data to be selected, the target medication data corresponding to the corresponding keywords is determined.

4. The method according to claim 1, characterized in that, The step of determining a target delivery strategy corresponding to the target medication data based on the target medication data, the location information, and at least one delivery requirement includes: Obtain at least one pre-set delivery request; wherein the delivery request includes at least one of timeliness requirement, distance requirement, value attribute requirement, delivery cost requirement, order split quantity, and delivery origin and destination; Based on the target medication data and the location information, determine the delivery information to be selected corresponding to the at least one delivery request; The delivery information to be selected is then fed back to the target client. Based on the triggered operation on the target client, a target delivery strategy is determined from the delivery information to be selected.

5. The method according to claim 4, characterized in that, The step of determining the candidate delivery information corresponding to the at least one delivery request based on the target medication data and the location information includes: Based on the target medication data, the remaining medication information in the historical medication data, and the location information, the delivery information to be selected for each delivery demand is determined.

6. The method according to claim 5, characterized in that, Also includes: Update the target medication data to the database corresponding to the patient, and update the weight value of at least one delivery request corresponding to the patient based on the target medication data; Based on the corresponding weight values, the sorting order of the delivery information to be selected is determined, and the information is displayed based on the sorting order.

7. A device for determining medication data and delivery, characterized in that, include: The associated data receiving module is used to receive associated data related to the patient; wherein, the associated data includes historical medical data, current symptom description information and location information, and the historical medical data includes historical symptom description data and historical medication data; The medication data determination module is used to determine at least one keyword corresponding to the associated data and the corresponding medication data to be selected based on at least two medication data recommendation methods. The target medication determination module is used to determine the target medication data corresponding to the at least one keyword from the drug selection data based on the historical medication data and disease progression information. The delivery strategy determination module is used to determine a target delivery strategy corresponding to the target medication data based on the target medication data, the location information, and at least one delivery requirement; wherein the delivery requirement includes at least one of timeliness requirement, distance requirement, value attribute requirement, delivery cost requirement, order split quantity, and delivery origin. The target drug delivery module is used to deliver the target drug corresponding to the target medication data to the target location corresponding to the location information based on the target delivery strategy. Specifically, the medication data determination module is used to analyze and process the associated data based on the target patient, and determine at least one first-type keyword; to split the historical symptom description data and the current symptom description information in the associated data based on a rule matching algorithm, and obtain at least one second-type keyword; to analyze the historical symptom description data and the current symptom description information based on an association recommendation algorithm, and obtain at least one third-type keyword; to determine at least one keyword based on the at least one first-type keyword, the at least one second-type keyword, and the at least one third-type keyword; and to determine the medication data to be selected for the at least one keyword based on the prescription data corresponding to the at least one keyword stored in the database.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining medication data and delivery as described in any one of claims 1-6.

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