CN116665868A - Online evolution method, online evolution device, computer equipment and readable storage medium - Google Patents
Online evolution method, online evolution device, computer equipment and readable storage medium Download PDFInfo
- Publication number
- CN116665868A CN116665868A CN202310815711.3A CN202310815711A CN116665868A CN 116665868 A CN116665868 A CN 116665868A CN 202310815711 A CN202310815711 A CN 202310815711A CN 116665868 A CN116665868 A CN 116665868A
- Authority
- CN
- China
- Prior art keywords
- prescription
- target
- medicine
- user
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 239000003814 drug Substances 0.000 claims abstract description 286
- 238000011156 evaluation Methods 0.000 claims abstract description 122
- 229940126532 prescription medicine Drugs 0.000 claims abstract description 20
- 238000012545 processing Methods 0.000 claims abstract description 17
- 229940079593 drug Drugs 0.000 claims description 121
- 201000010099 disease Diseases 0.000 claims description 34
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 34
- 238000012550 audit Methods 0.000 claims description 31
- 238000003745 diagnosis Methods 0.000 claims description 21
- 239000000955 prescription drug Substances 0.000 claims description 21
- 238000004590 computer program Methods 0.000 claims description 9
- 230000035935 pregnancy Effects 0.000 claims description 8
- 206010020751 Hypersensitivity Diseases 0.000 claims description 7
- 208000026935 allergic disease Diseases 0.000 claims description 7
- 230000007815 allergy Effects 0.000 claims description 7
- 229930186147 Cephalosporin Natural products 0.000 description 5
- 229940124587 cephalosporin Drugs 0.000 description 5
- 150000001780 cephalosporins Chemical class 0.000 description 5
- 230000008901 benefit Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 239000000284 extract Substances 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000002354 daily effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000003203 everyday effect Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012797 qualification Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Health & Medical Sciences (AREA)
- General Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Epidemiology (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Educational Administration (AREA)
- Chemical & Material Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Biomedical Technology (AREA)
- Medicinal Chemistry (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The application discloses an online prescribing method, an online prescribing device, computer equipment and a readable storage medium, relates to the technical field of digital medical treatment, and solves the problems that patients need to spend a long time for queuing and prescribing an prescription and prescribing efficiency is low due to the limitation of the number of doctors receiving the hospital on the Internet at present. The method comprises the following steps: responding to a prescription request of a user, generating a virtual prescription according to user illness information and to-be-prescribed medicine information carried by the prescription request, performing risk evaluation on the virtual prescription according to medicine rules of target prescription medicines included in the virtual prescription to obtain a target risk evaluation result, determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to a terminal held by the user.
Description
Technical Field
The application belongs to the technical field of digital medical treatment, and particularly relates to an online evolution method, an online evolution device, computer equipment and a readable storage medium.
Background
With the generation and development of internet technology, internet hospitals gradually enter the public view. When a user purchases prescription drugs at a pharmacy, the user usually needs to buy the relevant prescription drugs by virtue of prescriptions issued by the hospital, and for patients who need to purchase prescription drugs urgently, the user can choose to acquire prescriptions through an internet hospital, and purchase prescription drugs urgently needed at the pharmacy based on the prescriptions.
Currently, about 60 thousands of drugstores exist nationally, for example, 10 prescriptions are estimated according to daily needs of each drugstore, a doctor of an internet hospital is required to receive 600 tens of thousands of prescriptions every day, the doctor and the patient mainly adopt a one-to-one inquiry and prescription-making mode, and the doctor can make prescriptions based on the illness state information of the patient after the inquiry of the doctor is completed. However, the applicant realizes that the number of co-operating doctor in the internet hospital is limited, the number of patients far exceeds the number of doctor, and in the time of issuing, the patients often need to spend a long time queuing for consultation, for example, 1000 patients need to be issued to buy prescription medicine in the time of issuing, while in the current time, only 100 doctor can be accessed in the internet hospital, the internet hospital distributes doctors according to the patient condition information, for example, doctor a distributes 30 issuing tasks, doctor B distributes 20 issuing tasks, doctor C distributes 10 issuing tasks, and the like, and the issuing efficiency is low for the patients distributed to doctor a to be required to wait for a long time to acquire the prescription.
Disclosure of Invention
In view of the above, the present application provides an online prescribing method, device, computer equipment and readable storage medium, which mainly aims to solve the problem that patients need to spend a long time for queuing and prescribing an prescription and the prescribing efficiency is low due to the limitation of the number of the doctors in the internet hospital.
According to a first aspect of the present application, there is provided an online evolution method comprising:
responding to a prescription request of a user, and generating a virtual prescription according to user illness information and to-be-prescribed medicine information carried by the prescription request;
performing risk evaluation on the virtual prescription according to a medicine rule of a target prescription medicine included in the virtual prescription to obtain a target risk evaluation result;
and determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to a terminal held by the user.
Optionally, the generating the virtual prescription according to the user condition information and the to-be-prescribed medicine information carried by the prescription request includes:
acquiring the illness state information of the user and the medicine information to be prescribed carried by the prescription request;
Extracting disease description information from the user disease information, and generating diagnosis disease information according to the disease description information;
inquiring instruction information of the to-be-prescribed medicine indicated by the to-be-prescribed medicine information, and determining that the to-be-prescribed medicine is the target to-be-prescribed medicine when the instruction information of the to-be-prescribed medicine is detected to comprise the diagnosis disease information;
extracting age information of the user from the illness state information of the user, and determining medication dosage corresponding to the age information based on the instruction information;
and acquiring a prescription template, and arranging the user illness state information, the diagnosis disease information, the target prescription drug information corresponding to the target prescription drug and the drug dosage by adopting the prescription template to obtain the virtual prescription.
Optionally, the performing risk evaluation on the virtual prescription according to the drug rule of the target prescription drug included in the virtual prescription to obtain a target risk evaluation result includes:
determining a plurality of problem labels to be determined according to the virtual prescription, and state information corresponding to each problem label to be determined in the plurality of problem labels to be determined, wherein the problem label to be determined is one of an age label, a gender label, a pregnancy label, a tabu label, an allergy label, a medication dosage label and a medication usage label;
Generating a plurality of to-be-determined medication problem points based on the plurality of to-be-determined problem labels and state information corresponding to each to-be-determined problem label in the plurality of to-be-determined problem labels;
extracting a medicine code of a target prescription medicine from the virtual prescription, and acquiring a medicine library comprising a plurality of medicine information;
extracting target medicine information indicated by the medicine codes from the medicine library, and acquiring a medicine rule corresponding to the target medicine information, wherein the medicine rule comprises a plurality of medicine sub-rules, and each medicine sub-rule is associated with a risk evaluation;
selecting at least one target medication sub-rule matched with the plurality of medication problem points to be determined from the plurality of medication sub-rules, and inquiring risk evaluation corresponding to each target medication sub-rule in the at least one target medication sub-rule to obtain at least one risk evaluation;
querying a risk evaluation with the highest indicated risk level in the at least one risk evaluation, and determining the risk evaluation with the highest indicated risk level as the target risk evaluation result of the virtual prescription.
Optionally, the selecting at least one target medication sub-rule matching the plurality of medication problem points to be determined from the plurality of medication sub-rules includes:
Determining a problem label associated with each medication sub-rule in the plurality of medication sub-rules to obtain a plurality of problem labels;
querying a plurality of target problem labels which are the same as the problem labels to be determined from the problem labels;
selecting a plurality of target medication sub-rules associated with the plurality of target problem labels from the plurality of medication sub-rules;
extracting state information corresponding to each to-be-determined problem label in the to-be-determined problem labels from the to-be-determined medication problem points to obtain a plurality of state information;
and respectively matching the plurality of state information with each target medicine rule in the plurality of target medicine rules, and determining the at least one target medicine rule.
Optionally, determining a prescription output policy according to the target risk evaluation result, processing the virtual prescription based on the prescription output policy to obtain a prescription result, and pushing the prescription result to the terminal held by the user, where the method includes:
and when the risk evaluation result indicates low risk, determining the virtual prescription as the prescription result, and sending the prescription result to a terminal held by the user so that the user purchases the medicine according to the prescription result when receiving the prescription result based on the terminal.
Optionally, determining a prescription output policy according to the target risk evaluation result, processing the virtual prescription based on the prescription output policy to obtain a prescription result, and pushing the prescription result to the terminal held by the user, where the method includes:
when the risk evaluation result indicates a risk in the medium, acquiring an auditor, and sending the virtual prescription to the auditor;
if the target auditor is detected to be in consultation within the preset duration, determining that the auditor is a target auditor, receiving an audit result fed back by the target auditor, and pushing the virtual prescription to a terminal held by the user as the prescription result when the audit result indicates that the audit is passed, wherein the audit result is obtained by the target auditor auditing the virtual prescription when the target auditor receives the virtual prescription;
if the auditor is not detected to receive the diagnosis within the preset time, an alternative doctor is selected, the virtual prescription, the user illness state information and the information to be prescribed are sent to the alternative doctor, the prescription information prescribed by the alternative doctor is obtained as the prescription result, the prescription result is pushed to the terminal held by the user, and the prescription information is prescribed by the alternative doctor according to the received virtual prescription, the received user illness state information and the received information to be prescribed.
Optionally, determining a prescription output policy according to the target risk evaluation result, processing the virtual prescription based on the prescription output policy to obtain a prescription result, and pushing the prescription result to the terminal held by the user, where the method includes:
when the risk evaluation result indicates high risk, a user blacklist is obtained, the user is marked into the user internal list, and the user blacklist comprises at least one user of which the medicine is not available in the same day;
deleting the virtual prescription, generating reminding information for indicating that the online purchase of the medicine in the hospital is recommended as the prescription result, and sending the prescription result to a terminal held by the user.
According to a second aspect of the present application, there is provided an online squaring device comprising:
the generation module is used for responding to the prescription request of the user and generating a virtual prescription according to the user illness state information and the medicine information to be prescribed carried by the prescription request;
the evaluation module is used for performing risk evaluation on the virtual prescription according to the medicine rules of the target prescription medicine included in the virtual prescription to obtain a target risk evaluation result;
and the pushing module is used for determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to the terminal held by the user.
Optionally, the generating module is further configured to: acquiring the illness state information of the user and the medicine information to be prescribed carried by the prescription request; extracting disease description information from the user disease information, and generating diagnosis disease information according to the disease description information; inquiring instruction information of the to-be-prescribed medicine indicated by the to-be-prescribed medicine information, and determining that the to-be-prescribed medicine is the target to-be-prescribed medicine when the instruction information of the to-be-prescribed medicine is detected to comprise the diagnosis disease information; extracting age information of the user from the illness state information of the user, and determining medication dosage corresponding to the age information based on the instruction information; and acquiring a prescription template, and arranging the user illness state information, the diagnosis disease information, the target prescription drug information corresponding to the target prescription drug and the drug dosage by adopting the prescription template to obtain the virtual prescription.
Optionally, the evaluation module is further configured to: determining a plurality of problem labels to be determined according to the virtual prescription, and state information corresponding to each problem label to be determined in the plurality of problem labels to be determined, wherein the problem label to be determined is one of an age label, a gender label, a pregnancy label, a tabu label, an allergy label, a medication dosage label and a medication usage label; generating a plurality of to-be-determined medication problem points based on the plurality of to-be-determined problem labels and state information corresponding to each to-be-determined problem label in the plurality of to-be-determined problem labels; extracting a medicine code of a target prescription medicine from the virtual prescription, and acquiring a medicine library comprising a plurality of medicine information; extracting target medicine information indicated by the medicine codes from the medicine library, and acquiring a medicine rule corresponding to the target medicine information, wherein the medicine rule comprises a plurality of medicine sub-rules, and each medicine sub-rule is associated with a risk evaluation; selecting at least one target medication sub-rule matched with the plurality of medication problem points to be determined from the plurality of medication sub-rules, and inquiring risk evaluation corresponding to each target medication sub-rule in the at least one target medication sub-rule to obtain at least one risk evaluation; querying a risk evaluation with the highest indicated risk level in the at least one risk evaluation, and determining the risk evaluation with the highest indicated risk level as the target risk evaluation result of the virtual prescription.
Optionally, the evaluation module is further configured to: determining a problem label associated with each medication sub-rule in the plurality of medication sub-rules to obtain a plurality of problem labels; querying a plurality of target problem labels which are the same as the problem labels to be determined from the problem labels; selecting a plurality of target medication sub-rules associated with the plurality of target problem labels from the plurality of medication sub-rules; extracting state information corresponding to each to-be-determined problem label in the to-be-determined problem labels from the to-be-determined medication problem points to obtain a plurality of state information; and respectively matching the plurality of state information with each target medicine rule in the plurality of target medicine rules, and determining the at least one target medicine rule.
Optionally, the pushing module is further configured to: and when the risk evaluation result indicates low risk, determining the virtual prescription as the prescription result, and sending the prescription result to a terminal held by the user so that the user purchases the medicine according to the prescription result when receiving the prescription result based on the terminal.
Optionally, the pushing module is further configured to: when the risk evaluation result indicates a risk in the medium, acquiring an auditor, and sending the virtual prescription to the auditor; if the target auditor is detected to be in consultation within the preset duration, determining that the auditor is a target auditor, receiving an audit result fed back by the target auditor, and pushing the virtual prescription to a terminal held by the user as the prescription result when the audit result indicates that the audit is passed, wherein the audit result is obtained by the target auditor auditing the virtual prescription when the target auditor receives the virtual prescription; if the auditor is not detected to receive the diagnosis within the preset time, an alternative doctor is selected, the virtual prescription, the user illness state information and the information to be prescribed are sent to the alternative doctor, the prescription information prescribed by the alternative doctor is obtained as the prescription result, the prescription result is pushed to the terminal held by the user, and the prescription information is prescribed by the alternative doctor according to the received virtual prescription, the received user illness state information and the received information to be prescribed.
Optionally, the pushing module is further configured to: when the risk evaluation result indicates high risk, a user blacklist is obtained, the user is marked into the user internal list, and the user blacklist comprises at least one user of which the medicine is not available in the same day; deleting the virtual prescription, generating reminding information for indicating that the online purchase of the medicine in the hospital is recommended as the prescription result, and sending the prescription result to a terminal held by the user.
According to a third aspect of the present application there is provided a computer device comprising a memory storing a computer program and a processor implementing the steps of the method of any of the first aspects described above when the computer program is executed by the processor.
According to a fourth aspect of the present application there is provided a readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor implements the steps of the method of any of the first aspects described above.
By means of the technical scheme, the application provides an online prescription making method, an online prescription making device, computer equipment and a readable storage medium, wherein in response to a prescription making request of a user, a virtual prescription is generated according to user illness information and to-be-prescribed medicine information carried by the prescription making request, then, risk evaluation is carried out on the virtual prescription according to medicine rules of target prescription-making medicines included in the virtual prescription to obtain a target risk evaluation result, a prescription output strategy is determined according to the target risk evaluation result, the virtual prescription is processed based on the prescription output strategy to obtain a prescription making result, and the prescription making result is pushed to a terminal held by the user; after the prescription robot automatically prescribes the virtual prescription, the medication safety of the virtual prescription including the target prescription drug is further checked, an output strategy is determined according to the checking result, namely the target risk evaluation result, the follow-up prescription processing logic is executed based on the output strategy, the prescription result is determined, the user purchases the drug immediately or adopts other strategies to purchase the drug according to the prescription result, the medication safety and compliance of the drug are ensured, the queuing waiting time of the user is reduced, and the online prescription efficiency is improved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 shows a flow chart of an online evolution method provided by an embodiment of the application;
fig. 2 shows a schematic structural diagram of an online squaring device according to an embodiment of the present application;
fig. 3 shows a schematic device structure of a computer device according to an embodiment of the present application.
Detailed Description
Various aspects and features of the present application are described herein with reference to the accompanying drawings.
It should be understood that various modifications may be made to the embodiments of the application herein. Therefore, the above description should not be taken as limiting, but merely as exemplification of the embodiments. Other modifications within the scope and spirit of the application will occur to persons of ordinary skill in the art.
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the application and, together with a general description of the application given above, and the detailed description of the embodiments given below, serve to explain the principles of the application.
These and other characteristics of the application will become apparent from the following description of a preferred form of embodiment, given as a non-limiting example, with reference to the accompanying drawings.
It is also to be understood that, although the application has been described with reference to some specific examples, those skilled in the art can certainly realize many other equivalent forms of the application.
The above and other aspects, features and advantages of the present application will become more apparent in light of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the present application will be described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the application, which can be embodied in various forms. Well-known and/or repeated functions and constructions are not described in detail to avoid obscuring the application in unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not intended to be limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present application in virtually any appropriately detailed structure.
The specification may use the word "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may each refer to one or more of the same or different embodiments in accordance with the application.
The embodiment of the application provides an online evolution method, as shown in fig. 1, comprising the following steps:
101. responding to the prescription request of the user, and generating a virtual prescription according to the user illness state information and the medicine information to be prescribed carried by the prescription request.
In the embodiment of the present application, the execution body may be an evolution robot or an internet hospital platform configured with the evolution robot, and for convenience of description, the evolution robot is generally described in the embodiment of the present application, but it should be noted that the evolution robot may be replaced by an internet hospital platform configured with the evolution robot.
Further, when the prescription robot receives the prescription request of the user, the prescription robot extracts the illness state information of the user carried by the prescription request and the medicine to be purchased by the user, namely the medicine to be prescribed, and automatically generates a virtual prescription according to the illness state information of the user and the information of the medicine to be prescribed.
102. And performing risk evaluation on the virtual prescription according to the medicine rules of the target prescription medicine included in the virtual prescription to obtain a target risk evaluation result.
In the embodiment of the application, the generated virtual prescription comprises a target prescription drug, the target prescription drug corresponds to a drug rule, and the prescription robot carries out risk evaluation on the virtual prescription according to the drug rule, so that a target risk evaluation result aiming at the virtual prescription can be obtained.
It should be noted that, the evolution robot is carried on a server, and the server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and an artificial intelligence platform, so that the evolution robot can execute the technical scheme of online evolution in the embodiment of the present application.
103. And determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to a terminal held by the user.
The applicant finds that about 60 thousands of drugstores exist in the whole country at present, if 10 prescriptions are estimated according to the daily requirement of each drugstore, a doctor of an internet hospital is required to receive 600 tens of thousands of prescriptions every day, the doctor and a patient mainly adopt a one-to-one inquiry and prescription mode, and the doctor can only prescribe the prescriptions based on the illness state information of the patient after the inquiry of the doctor is finished; the number of the cooperative consultation doctors in the internet hospital is often limited, the number of patients far exceeds the number of the consultation doctors, the patients often need to spend longer time queuing for consultation to be prescribed in the high-speed prescribing period, for example, 1000 patients need to be prescribed for purchasing prescription medicines in the country in the high-speed prescribing period, but only 100 consultation doctors in the internet hospital can be used in the current period, the internet hospital distributes doctors according to the disease condition information of the patients, for example, a doctor A distributes 30 prescribing tasks, a doctor B distributes 20 prescribing tasks, a doctor C distributes 10 prescribing tasks and the like, and the prescribing efficiency is lower for the patients distributed to the doctor A to wait longer for acquiring the prescription; based on the above, the inventor proposes an online inquiry method, after a prescription robot issues a virtual prescription, the prescription robot performs risk evaluation on the virtual prescription to obtain a target risk evaluation result, then determines a prescription output strategy according to the target risk evaluation result, processes the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushes the prescription result to a terminal held by a user.
According to the method provided by the embodiment of the application, firstly, a virtual prescription is generated according to the illness state information of a user and the information of a medicine to be prescribed carried by the prescription request in response to the prescription request of the user, then, risk evaluation is carried out on the virtual prescription according to the medicine rule of a target prescription medicine included in the virtual prescription to obtain a target risk evaluation result, finally, a prescription output strategy is determined according to the target risk evaluation result, the virtual prescription is processed based on the prescription output strategy to obtain a prescription result, and the prescription result is pushed to a terminal held by the user; after the prescription robot automatically prescribes the virtual prescription, the medication safety of the virtual prescription including the target prescription drug is further checked, an output strategy is determined according to the checking result, namely the target risk evaluation result, the follow-up prescription processing logic is executed based on the output strategy, the prescription result is determined, the user purchases the drug immediately or adopts other strategies to purchase the drug according to the prescription result, the medication safety and compliance of the drug are ensured, the queuing waiting time of the user is reduced, and the online prescription efficiency is improved.
Further, as a refinement and extension of the specific implementation manner of the foregoing embodiment, in order to fully describe the specific implementation process of this embodiment, the embodiment of the present application provides another online evolution method, which includes:
201. Responding to a prescription request of a user, and generating a virtual prescription according to the user illness state information and the medicine information to be prescribed carried by the prescription request.
In the embodiment of the application, when the prescription robot receives the prescription request of a user, the prescription robot acquires the user disease information and the to-be-prescribed medicine information carried by the prescription request, then extracts disease description information from the user disease information, generates diagnosis disease information according to the disease description information, inquires the instruction manual information of the to-be-prescribed medicine indicated by the to-be-prescribed medicine information, determines the to-be-prescribed medicine as a target prescription medicine when detecting that the instruction manual information of the to-be-prescribed medicine comprises the diagnosis disease information, extracts age information of the user from the user disease information, determines the medicine dosage corresponding to the age information based on the instruction manual information, finally acquires a prescription template, and sorts the user disease information, the diagnosis disease information, the target prescription medicine information corresponding to the target prescription medicine and the medicine dosage by adopting the prescription template to obtain a virtual prescription.
In an optional implementation manner of the embodiment of the present application, after acquiring the illness state information of the user and the information of the drug to be prescribed carried by the prescription request, the prescription robot further determines the on-line purchasing authority of the drug store where the user purchases the drug, and determines the qualification of the drug store through the confirmation of the authority of the drug store, because in the actual application process, some drug stores with poor qualification exist, and in order to avoid whether the user purchases the drug in such drug store, the prescription robot confirms the drug store. The method comprises the following specific steps: the method comprises the steps of obtaining current position information of a user initiating an opening request, determining a pharmacy name indicated by the current position information, then obtaining a pharmacy white list, if the pharmacy white list does not comprise the pharmacy name, generating reminding information for indicating replacement of the pharmacy, sending the reminding information to a terminal held by the user, and enabling the pharmacy white list to comprise at least one pharmacy name of non-purchasable medicines.
202. And performing risk evaluation on the virtual prescription according to the medicine rules of the target prescription medicine included in the virtual prescription to obtain a target risk evaluation result.
In the embodiment of the application, after a virtual prescription is acquired, a prescription robot determines a plurality of problem labels to be determined according to the virtual prescription, state information corresponding to each problem label to be determined in the plurality of problem labels to be determined is one of an age label, a sex label, a gestation label, a contraindication label, an allergy label, a medication dosage label and a medicine usage label, then based on the state information corresponding to each problem label to be determined in the plurality of problem labels to be determined, a plurality of medication problem points to be determined are generated, medicine codes of target prescription medicines are extracted from the virtual prescription, a medicine library comprising a plurality of medicine information is acquired, then target medicine information indicated by the medicine codes is extracted from the medicine library, a medicine rule corresponding to the target medicine information is acquired, the medicine rule comprises a plurality of medicine sub-rules, at least one target medicine sub-rule matched with the plurality of problem points to be determined is selected from the plurality of medicine sub-rules, at least one risk evaluation corresponding to each target medicine sub-rule is queried, and at least one risk evaluation is obtained in the at least one risk evaluation rule corresponding to the plurality of target medicine sub-rules to the target medicine sub-rule, and the risk evaluation is determined as a risk evaluation result indicating that the risk evaluation is at least one risk evaluation is at the highest risk evaluation level.
In an optional implementation manner of the embodiment of the present application, a specific implementation method for selecting at least one target medication sub-rule matching with a plurality of medication problem points to be determined from a plurality of medication sub-rules includes: determining a problem label associated with each of a plurality of medication sub-rules to obtain a plurality of problem labels, inquiring a plurality of target problem labels which are the same as the problem labels to be determined in the plurality of problem labels, selecting a plurality of target medication sub-rules associated with the target problem labels in the plurality of medication sub-rules, extracting state information corresponding to each of the plurality of issue labels to be determined from a plurality of medication sub-points to be determined to obtain a plurality of state information, and finally matching the plurality of state information with each of the target medication sub-rules to determine at least one target medication sub-rule.
It should be noted that, each of the plurality of pieces of medicine information included in the medicine library is maintained by a pharmacist, including but not limited to age limitation, sex limitation, pregnancy condition limitation, medicine compatibility tabulation, allergy limitation, tabulation, usage amount, and the like, and each rule corresponds to a different risk level, such as low risk, medium risk, high risk, and when determining a risk evaluation result of the virtual prescription, for example, all medicines included in the virtual prescription, patient information, allergy history, tabulation, and the like, the medicine matching success is indicated by the unique attribute of the medicine, that is, the medicine code, the embodiment in the code is medicine code, if (medicine code a=medicine code B), and the medicine rule of the medicine is queried. And determining the risk level of the virtual prescription based on the hit rule, and if a plurality of virtual prescriptions are hit, controlling the highest risk level.
The user is in a pregnant state, the medicine to be prescribed is cephalosporin, keywords such as pregnancy, cephalosporin, illness description and the like are required to be input into the terminal when the cephalosporin is purchased in a pharmacy, a prescription request is generated based on the keyword information, the prescription robot reads illness information of the user and the medicine information to be prescribed carried by the prescription request when receiving the prescription request and generates a virtual prescription, the prescription robot determines the medicine rule of the cephalosporin medicine contained in the virtual prescription, a plurality of sub-rules exist, for example, one medicine rule is that the cephalosporin cannot be taken during pregnancy, the risk level corresponding to the rule is high risk, and then the prescription robot considers the risk evaluation result corresponding to the virtual prescription to be high risk.
203. And determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to a terminal held by the user.
In the embodiment of the application, the target risk evaluation result has three risk levels, namely low risk, medium risk and high risk, and a specific prescription output strategy can be determined according to each risk level.
Specifically, when the risk evaluation result indicates low risk, the virtual prescription is determined to be the prescription result, and the prescription result is sent to the terminal held by the user, so that the user purchases the medicine according to the prescription result when receiving the prescription result based on the terminal, and for the medicine with low risk indicated by the risk evaluation result, the prescription robot directly sends the prescription result to the user, the user can directly purchase the medicine by using the prescription result, interaction between the user and a doctor is not needed, interaction time is saved, the user does not need to wait in a queue, time for waiting in a queue for prescription is reduced, and online prescription efficiency is greatly improved.
In an optional implementation manner of the embodiment of the present application, when the prescribing robot determines that the risk evaluation result indicates low risk, in order to further ensure the safety of medication, the prescribing robot may perform a spam risk audit on the virtual prescription, that is, after the prescribing robot directly sends the prescribing result to the user, the virtual prescription is sent to a spam auditor, the audit result fed back by the spam auditor is obtained by the spam auditor when the spam auditor receives the virtual prescription, when the audit result indicates that the audit is failed, a reminder message for indicating that the prescribing is unreasonable is generated, and the reminder message is sent to a terminal held by the user, so that the user stops using the prescribing result to purchase the medicine or stops taking the medicine purchased according to the prescribing result when the terminal receives the reminder message.
In another optional implementation manner of the embodiment of the present application, when the risk evaluation result indicates a low risk, in order to ensure the medication safety, the method may further send the result to a target auditor for auditing, that is, determine the target auditor, send the virtual prescription to the target auditor, receive the audit result fed back by the target auditor, where the audit result is obtained by the target auditor when the virtual prescription is received, and when the audit result indicates that the audit is failed, generate reminding information for indicating that the prescription is unreasonable, and send the reminding information to a terminal held by the user, and generate a new virtual prescription again for the user and send the new virtual prescription to the target auditor for auditing until the audit result fed back by the target auditor, where the instruction fed back by the target auditor is received, and push the current virtual prescription to the terminal held by the user as the development result.
Further, when the risk evaluation result indicates the risk, acquiring an auditor, transmitting a virtual prescription to the auditor, if the target auditor is detected to receive the diagnosis, determining the auditor as the target auditor, receiving the audit result fed back by the target auditor, when the audit result indicates the audit to pass, pushing the virtual prescription as the prescription result to a terminal held by a user, wherein the audit result is obtained by the target auditor auditing the virtual prescription when the virtual prescription is received, if the auditor is not detected to receive the diagnosis within the preset time, selecting an alternative interview, transmitting the virtual prescription, the user illness information and the information to be prescribed to the alternative interview, acquiring prescription information prescribed by the alternative interview as the prescription result, and pushing the prescription result to the terminal held by the user, the prescription information is provided by an alternative doctor according to the received virtual prescription, user illness state information and to-be-provided information, the risk virtual prescription in the risk evaluation result indication is further checked by an auditor in order to ensure the medication safety, the audit result is fed back by the auditor within a preset time length for reducing the queuing time of the user, the preset time length can be set to be 1 minute, 2 minutes and the like, the specific time length can be flexibly set according to the number of auditors and the number of users, when the audit result is not fed back by the auditor within the preset time length, the alternative doctor can be selected to avoid the further queuing of the user, the alternative doctor can manually provide the prescription information according to the virtual prescription, the user illness state information and the to-be-provided information, and the user can timely acquire the prescription information provided by the alternative doctor, and purchases the medicine according to the prescription information.
Further, when the risk evaluation result indicates high risk, a user blacklist is obtained, the user is marked into a user internal list, the user blacklist comprises at least one user incapable of purchasing medicines in the same day, a virtual prescription is deleted, reminding information for indicating that online medicine purchasing of a hospital is recommended to be used as an prescription result, and the prescription result is sent to a terminal held by the user; for a virtual prescription with risk evaluation indicating high risk, in order to ensure the safety of medication, the inquiry flow is directly stopped, and the user is recommended to go offline to a regular hospital for purchasing the medication.
According to the method provided by the embodiment of the application, firstly, a virtual prescription is generated according to the illness state information of a user and the information of a medicine to be prescribed carried by the prescription request in response to the prescription request of the user, then, risk evaluation is carried out on the virtual prescription according to the medicine rule of a target prescription medicine included in the virtual prescription to obtain a target risk evaluation result, finally, a prescription output strategy is determined according to the target risk evaluation result, the virtual prescription is processed based on the prescription output strategy to obtain a prescription result, and the prescription result is pushed to a terminal held by the user; after the prescription robot automatically prescribes the virtual prescription, the medication safety of the virtual prescription including the target prescription drug is further checked, an output strategy is determined according to the checking result, namely the target risk evaluation result, the follow-up prescription processing logic is executed based on the output strategy, the prescription result is determined, the user purchases the drug immediately or adopts other strategies to purchase the drug according to the prescription result, the medication safety and compliance of the drug are ensured, the queuing waiting time of the user is reduced, and the online prescription efficiency is improved.
Further, as a specific implementation of the method shown in fig. 1, an embodiment of the present invention provides an online squaring device, as shown in fig. 2, including: a generating module 201, an evaluating module 202 and a pushing module 203.
The generating module 201 is configured to respond to a request of a user to issue, and generate a virtual prescription according to user illness information and to-be-issued medicine information carried by the request;
the evaluation module 202 is configured to perform risk evaluation on the virtual prescription according to a drug rule of a target prescription drug included in the virtual prescription, so as to obtain a target risk evaluation result;
the pushing module 203 is configured to determine a prescription output policy according to the target risk evaluation result, process the virtual prescription based on the prescription output policy to obtain a prescription result, and push the prescription result to a terminal held by the user.
In a specific application scenario, the generating module 201 is further configured to: acquiring the illness state information of the user and the medicine information to be prescribed carried by the prescription request; extracting disease description information from the user disease information, and generating diagnosis disease information according to the disease description information; inquiring instruction information of the to-be-prescribed medicine indicated by the to-be-prescribed medicine information, and determining that the to-be-prescribed medicine is the target to-be-prescribed medicine when the instruction information of the to-be-prescribed medicine is detected to comprise the diagnosis disease information; extracting age information of the user from the illness state information of the user, and determining medication dosage corresponding to the age information based on the instruction information; and acquiring a prescription template, and arranging the user illness state information, the diagnosis disease information, the target prescription drug information corresponding to the target prescription drug and the drug dosage by adopting the prescription template to obtain the virtual prescription.
In a specific application scenario, the evaluation module 202 is further configured to: determining a plurality of problem labels to be determined according to the virtual prescription, and state information corresponding to each problem label to be determined in the plurality of problem labels to be determined, wherein the problem label to be determined is one of an age label, a gender label, a pregnancy label, a tabu label, an allergy label, a medication dosage label and a medication usage label; generating a plurality of to-be-determined medication problem points based on the plurality of to-be-determined problem labels and state information corresponding to each to-be-determined problem label in the plurality of to-be-determined problem labels; extracting a medicine code of a target prescription medicine from the virtual prescription, and acquiring a medicine library comprising a plurality of medicine information; extracting target medicine information indicated by the medicine codes from the medicine library, and acquiring a medicine rule corresponding to the target medicine information, wherein the medicine rule comprises a plurality of medicine sub-rules, and each medicine sub-rule is associated with a risk evaluation; selecting at least one target medication sub-rule matched with the plurality of medication problem points to be determined from the plurality of medication sub-rules, and inquiring risk evaluation corresponding to each target medication sub-rule in the at least one target medication sub-rule to obtain at least one risk evaluation; querying a risk evaluation with the highest indicated risk level in the at least one risk evaluation, and determining the risk evaluation with the highest indicated risk level as the target risk evaluation result of the virtual prescription.
In a specific application scenario, the evaluation module 202 is further configured to: determining a problem label associated with each medication sub-rule in the plurality of medication sub-rules to obtain a plurality of problem labels; querying a plurality of target problem labels which are the same as the problem labels to be determined from the problem labels; selecting a plurality of target medication sub-rules associated with the plurality of target problem labels from the plurality of medication sub-rules; extracting state information corresponding to each to-be-determined problem label in the to-be-determined problem labels from the to-be-determined medication problem points to obtain a plurality of state information; and respectively matching the plurality of state information with each target medicine rule in the plurality of target medicine rules, and determining the at least one target medicine rule.
In a specific application scenario, the pushing module 203 is further configured to: and when the risk evaluation result indicates low risk, determining the virtual prescription as the prescription result, and sending the prescription result to a terminal held by the user so that the user purchases the medicine according to the prescription result when receiving the prescription result based on the terminal.
In a specific application scenario, the pushing module 203 is further configured to: when the risk evaluation result indicates a risk in the medium, acquiring an auditor, and sending the virtual prescription to the auditor; if the target auditor is detected to be in consultation within the preset duration, determining that the auditor is a target auditor, receiving an audit result fed back by the target auditor, and pushing the virtual prescription to a terminal held by the user as the prescription result when the audit result indicates that the audit is passed, wherein the audit result is obtained by the target auditor auditing the virtual prescription when the target auditor receives the virtual prescription; if the auditor is not detected to receive the diagnosis within the preset time, an alternative doctor is selected, the virtual prescription, the user illness state information and the information to be prescribed are sent to the alternative doctor, the prescription information prescribed by the alternative doctor is obtained as the prescription result, the prescription result is pushed to the terminal held by the user, and the prescription information is prescribed by the alternative doctor according to the received virtual prescription, the received user illness state information and the received information to be prescribed.
In a specific application scenario, the pushing module 203 is further configured to: when the risk evaluation result indicates high risk, a user blacklist is obtained, the user is marked into the user internal list, and the user blacklist comprises at least one user of which the medicine is not available in the same day; deleting the virtual prescription, generating reminding information for indicating that the online purchase of the medicine in the hospital is recommended as the prescription result, and sending the prescription result to a terminal held by the user.
According to the device provided by the embodiment of the application, firstly, a generation module responds to a prescription request of a user, a virtual prescription is generated according to user illness information and to-be-prescribed medicine information carried by the prescription request, then, risk evaluation is carried out on the virtual prescription according to medicine rules of target prescription medicines included in the virtual prescription by an evaluation module to obtain a target risk evaluation result, finally, a prescription output strategy is determined according to the target risk evaluation result by a pushing module, the virtual prescription is processed based on the prescription output strategy to obtain the prescription result, and the prescription result is pushed to a terminal held by the user; after the prescription robot automatically prescribes the virtual prescription, the medication safety of the virtual prescription including the target prescription drug is further checked, an output strategy is determined according to the checking result, namely the target risk evaluation result, the follow-up prescription processing logic is executed based on the output strategy, the prescription result is determined, the user purchases the drug immediately or adopts other strategies to purchase the drug according to the prescription result, the medication safety and compliance of the drug are ensured, the queuing waiting time of the user is reduced, and the online prescription efficiency is improved.
It should be noted that, for other corresponding descriptions of each functional unit related to the online evolution device provided by the embodiment of the present application, reference may be made to corresponding descriptions in fig. 1 and fig. 2, and details are not repeated here.
In an exemplary embodiment, referring to fig. 3, there is also provided a computer device, which includes a communication bus, a processor, a memory, and a communication interface, and may further include an input-output interface and a display device, where each functional unit may perform communication with each other through the bus. The memory stores a computer program and a processor for executing the program stored in the memory to perform the online provisioning method in the above embodiment.
A computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of the online evolution method.
From the above description of the embodiments, it will be clear to those skilled in the art that the present application may be implemented in hardware, or may be implemented by means of software plus necessary general hardware platforms. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective implementation scenario of the present application.
Those skilled in the art will appreciate that the drawing is merely a schematic illustration of a preferred implementation scenario and that the modules or flows in the drawing are not necessarily required to practice the application. Those skilled in the art will appreciate that modules in an apparatus in an implementation scenario may be distributed in an apparatus in an implementation scenario according to an implementation scenario description, or that corresponding changes may be located in one or more apparatuses different from the implementation scenario. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application, the scope of which is defined by the claims. Various modifications and equivalent arrangements of this application will occur to those skilled in the art, and are intended to be within the spirit and scope of the application.
Claims (10)
1. An on-line evolution method, comprising:
responding to a prescription request of a user, and generating a virtual prescription according to user illness information and to-be-prescribed medicine information carried by the prescription request;
performing risk evaluation on the virtual prescription according to a medicine rule of a target prescription medicine included in the virtual prescription to obtain a target risk evaluation result;
And determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to a terminal held by the user.
2. The online prescription method as in claim 1, wherein generating a virtual prescription based on the user condition information and the drug information to be prescribed carried by the prescription request comprises:
acquiring the illness state information of the user and the medicine information to be prescribed carried by the prescription request;
extracting disease description information from the user disease information, and generating diagnosis disease information according to the disease description information;
inquiring instruction information of the to-be-prescribed medicine indicated by the to-be-prescribed medicine information, and determining that the to-be-prescribed medicine is the target to-be-prescribed medicine when the instruction information of the to-be-prescribed medicine is detected to comprise the diagnosis disease information;
extracting age information of the user from the illness state information of the user, and determining medication dosage corresponding to the age information based on the instruction information;
and acquiring a prescription template, and arranging the user illness state information, the diagnosis disease information, the target prescription drug information corresponding to the target prescription drug and the drug dosage by adopting the prescription template to obtain the virtual prescription.
3. The online prescription method according to claim 1, wherein performing risk evaluation on the virtual prescription according to a drug rule of a target prescription drug included in the virtual prescription to obtain a target risk evaluation result includes:
determining a plurality of problem labels to be determined according to the virtual prescription, and state information corresponding to each problem label to be determined in the plurality of problem labels to be determined, wherein the problem label to be determined is one of an age label, a gender label, a pregnancy label, a tabu label, an allergy label, a medication dosage label and a medication usage label;
generating a plurality of to-be-determined medication problem points based on the plurality of to-be-determined problem labels and state information corresponding to each to-be-determined problem label in the plurality of to-be-determined problem labels;
extracting a medicine code of a target prescription medicine from the virtual prescription, and acquiring a medicine library comprising a plurality of medicine information;
extracting target medicine information indicated by the medicine codes from the medicine library, and acquiring a medicine rule corresponding to the target medicine information, wherein the medicine rule comprises a plurality of medicine sub-rules, and each medicine sub-rule is associated with a risk evaluation;
Selecting at least one target medication sub-rule matched with the plurality of medication problem points to be determined from the plurality of medication sub-rules, and inquiring risk evaluation corresponding to each target medication sub-rule in the at least one target medication sub-rule to obtain at least one risk evaluation;
querying a risk evaluation with the highest indicated risk level in the at least one risk evaluation, and determining the risk evaluation with the highest indicated risk level as the target risk evaluation result of the virtual prescription.
4. The online prescription method of claim 3, wherein said selecting at least one target medication sub-rule from said plurality of medication sub-rules that matches said plurality of medication problem points to be determined comprises:
determining a problem label associated with each medication sub-rule in the plurality of medication sub-rules to obtain a plurality of problem labels;
querying a plurality of target problem labels which are the same as the problem labels to be determined from the problem labels;
selecting a plurality of target medication sub-rules associated with the plurality of target problem labels from the plurality of medication sub-rules;
extracting state information corresponding to each to-be-determined problem label in the to-be-determined problem labels from the to-be-determined medication problem points to obtain a plurality of state information;
And respectively matching the plurality of state information with each target medicine rule in the plurality of target medicine rules, and determining the at least one target medicine rule.
5. The online provisioning method according to claim 1, wherein determining a prescription output policy according to the target risk evaluation result, processing the virtual prescription based on the prescription output policy to obtain a provisioning result, and pushing the provisioning result to the terminal held by the user comprises:
and when the risk evaluation result indicates low risk, determining the virtual prescription as the prescription result, and sending the prescription result to a terminal held by the user so that the user purchases the medicine according to the prescription result when receiving the prescription result based on the terminal.
6. The online provisioning method according to claim 1, wherein determining a prescription output policy according to the target risk evaluation result, processing the virtual prescription based on the prescription output policy to obtain a provisioning result, and pushing the provisioning result to the terminal held by the user comprises:
when the risk evaluation result indicates a risk in the medium, acquiring an auditor, and sending the virtual prescription to the auditor;
If the target auditor is detected to be in consultation within the preset duration, determining that the auditor is a target auditor, receiving an audit result fed back by the target auditor, and pushing the virtual prescription to a terminal held by the user as the prescription result when the audit result indicates that the audit is passed, wherein the audit result is obtained by the target auditor auditing the virtual prescription when the target auditor receives the virtual prescription;
if the auditor is not detected to receive the diagnosis within the preset time, an alternative doctor is selected, the virtual prescription, the user illness state information and the information to be prescribed are sent to the alternative doctor, the prescription information prescribed by the alternative doctor is obtained as the prescription result, the prescription result is pushed to the terminal held by the user, and the prescription information is prescribed by the alternative doctor according to the received virtual prescription, the received user illness state information and the received information to be prescribed.
7. The online provisioning method according to claim 1, wherein determining a prescription output policy according to the target risk evaluation result, processing the virtual prescription based on the prescription output policy to obtain a provisioning result, and pushing the provisioning result to the terminal held by the user comprises:
When the risk evaluation result indicates high risk, a user blacklist is obtained, the user is marked into the user internal list, and the user blacklist comprises at least one user of which the medicine is not available in the same day;
deleting the virtual prescription, generating reminding information for indicating that the online purchase of the medicine in the hospital is recommended as the prescription result, and sending the prescription result to a terminal held by the user.
8. An on-line squaring device, comprising:
the generation module is used for responding to the prescription request of the user and generating a virtual prescription according to the user illness state information and the medicine information to be prescribed carried by the prescription request;
the evaluation module is used for performing risk evaluation on the virtual prescription according to the medicine rules of the target prescription medicine included in the virtual prescription to obtain a target risk evaluation result;
and the pushing module is used for determining a prescription output strategy according to the target risk evaluation result, processing the virtual prescription based on the prescription output strategy to obtain a prescription result, and pushing the prescription result to the terminal held by the user.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A readable storage medium having stored thereon a computer program, which when executed by a processor realizes the steps of the method according to any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310815711.3A CN116665868A (en) | 2023-07-04 | 2023-07-04 | Online evolution method, online evolution device, computer equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310815711.3A CN116665868A (en) | 2023-07-04 | 2023-07-04 | Online evolution method, online evolution device, computer equipment and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116665868A true CN116665868A (en) | 2023-08-29 |
Family
ID=87711913
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310815711.3A Pending CN116665868A (en) | 2023-07-04 | 2023-07-04 | Online evolution method, online evolution device, computer equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116665868A (en) |
-
2023
- 2023-07-04 CN CN202310815711.3A patent/CN116665868A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8046242B1 (en) | Systems and methods for verifying prescription dosages | |
| Grossman et al. | Transmitting and processing electronic prescriptions: experiences of physician practices and pharmacies | |
| US10635783B2 (en) | Systems and methods for determining patient adherence to a prescribed medication protocol | |
| US8548824B1 (en) | Systems and methods for notifying of duplicate product prescriptions | |
| US8392219B1 (en) | Systems and methods for streamlined patient enrollment for one or more healthcare programs | |
| US11869642B2 (en) | System and method to facilitate interoperability of health care modules | |
| US20190333158A1 (en) | Methods and systems for maintaining pharmacy provider networks | |
| CN109255721A (en) | Insurance recommended method, equipment, server and readable medium based on Cost Forecast | |
| CN114420240A (en) | Prescription management system based on artificial intelligence, big data and block chain | |
| JP2019207522A (en) | Data structure for prescription audit processing terminal | |
| US20230268049A1 (en) | Pharmacy platform system for providing electroceutical service based on online and offline and method thereof | |
| KR101818100B1 (en) | Apparatus and method for integrated management of medical service | |
| US20220293254A1 (en) | Automated data aggregation with file analysis and predictive modeling | |
| US20140297308A1 (en) | Referral and record sharing systems and methods | |
| US20160188844A1 (en) | Cloud based emr manager | |
| CN116665868A (en) | Online evolution method, online evolution device, computer equipment and readable storage medium | |
| JP6981635B2 (en) | system | |
| McCauley et al. | Reframing telehealth: regulation, licensing, and reimbursement in connected care | |
| Dixon et al. | Health information exchange and Interoperability | |
| US11250938B2 (en) | Method, apparatus, and computer program product for submission of medical eligibility and claim data | |
| JP7481053B1 (en) | Medication support system, medication support method, and medication support program | |
| US20210019296A1 (en) | System and method for data de-duplication and augmentation | |
| US20240105324A1 (en) | Medical item resupply engine and engagement controller | |
| US20220254518A1 (en) | Patient Information Network | |
| US20240105297A1 (en) | Medical item resupply engine and engagement controller |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |