CN116580856A

CN116580856A - Online inquiry method, system, equipment and medium based on artificial intelligence

Info

Publication number: CN116580856A
Application number: CN202310530942.XA
Authority: CN
Inventors: 单琛宇
Original assignee: Kangjian Information Technology Shenzhen Co Ltd
Current assignee: Kangjian Information Technology Shenzhen Co Ltd
Priority date: 2023-05-11
Filing date: 2023-05-11
Publication date: 2023-08-11

Abstract

The application provides an on-line consultation method, system, equipment and medium based on artificial intelligence, relating to the field of artificial intelligence and the field of digital medical treatment; comprising the following steps: receiving a consultation request of a first object, acquiring physical state information of the first object according to the consultation request, receiving an electronic prescription generated by a second object according to the physical state information, and carrying out keyword recognition on the electronic prescription to obtain a first medicine contained in the electronic prescription; matching the first medicine with the second medicine, and feeding back the electronic prescription to the first object when the medicines are partially matched or completely matched; or prompting the second object to adjust the electronic prescription when the medicines are not matched at all; wherein the second drug comprises: a drug that requires a partial fee, a drug that does not require a fee. The application can realize online inquiry and solves the problem that the electronic prescription medicine cannot be accurately matched with the actual condition of the first object through medicine matching, thereby reducing the economic expenditure of the first object.

Description

Online inquiry method, system, equipment and medium based on artificial intelligence

Technical Field

The application relates to the technical field of artificial intelligence and the field of digital medical treatment, in particular to an on-line inquiry method, system, equipment and medium based on artificial intelligence.

Background

As the standard of living increases, people are also paying more attention to personal health, whether they see a doctor for a doctor or for nutrition and health care, they want to get the most effective medical information in the shortest time in order to perform better treatment. Then, since some hospitals may be far apart, or the queuing of hospitals is time-consuming and cumbersome, people may spend a lot of time on the way, thus delaying the inquiry time.

With the rise of artificial intelligence (Artificial Intelligence, abbreviated as AI) technology, most medical institutions currently develop digital medical platforms, and support functions of disease auxiliary diagnosis, health management, online consultation and the like through the digital medical platforms. Thus, more and more people have chosen the way of on-line interrogation.

However, when a part of patients are on-line asked, doctors may not know the economic condition of the part of patients, so that the prescription medicines prescribed by the doctors may exceed the economic income of the patients, thereby greatly increasing the economic expenditure of the patients, and causing the problem that the patients are easy to see the diseases. Meanwhile, if the patient purchases the commercial insurance, but the prescription medicine issued by the doctor is not in the medicine range of the commercial insurance claim, the economic expenditure of the patient can be increased, the patient can easily generate error cognition on the commercial insurance, and the commercial insurance is considered to have no normal guarantee function. Meanwhile, if the patient gives up diagnosis or treatment due to economic problems, not only the physical health of the patient is impaired, but also the pay cost of the commercial insurance company is increased at a later stage.

Disclosure of Invention

In view of the above-mentioned shortcomings of the prior art, the present application aims to provide an on-line inquiry method, system, device and medium based on artificial intelligence, which are used for solving the problem that doctor electronic prescription medicines cannot be accurately matched with actual conditions of patients during on-line inquiry in the prior art.

To achieve the above and other related objects, the present application provides an on-line interrogation method based on artificial intelligence, the method comprising the steps of:

receiving a consultation request input by a first object, and acquiring physical state information of the first object according to the consultation request;

receiving an electronic prescription generated by a second object according to the physical state information of the first object;

keyword recognition is carried out on the electronic prescription, and a first medicine contained in the electronic prescription is obtained;

matching the first drug with a second drug and feeding back the electronic prescription to the first subject when the first drug is partially matched or completely matched with the second drug; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that requires a partial fee, a drug that does not require a fee.

Optionally, the process of receiving a request for a consultation input by a first subject and acquiring physical state information of the first subject according to the request for the consultation includes:

receiving and responding to the inquiry request input by the first object, and prompting to input the identity information of the first object according to a request response result;

the identity information input at the current moment is used as first identity information, the first identity information is matched with a preset identity database, and whether the first identity information exists in the preset identity database is determined;

if the first identity information exists in the preset identity database, analyzing the inquiry request to acquire the physical state information of the first object;

and if the first identity information does not exist in the preset identity database, carrying out identity marking on the first object.

Optionally, before parsing the inquiry request, the method further includes:

shooting the first object at the current moment to obtain an image to be identified;

identifying an image to be identified, and matching identity information associated with the image to be identified from the preset identity database according to an image identification result, and marking the identity information as second identity information;

Verifying and comparing the first identity information with the second identity information to determine whether the first identity information and the second identity information are identical;

if the first identity information is the same as the second identity information, analyzing the inquiry request;

and if the first identity information and the second identity information are different, or the identity information associated with the image to be identified cannot be matched from the preset identity database according to the image identification result, carrying out identity marking on the first object.

Optionally, the determining of the second medicine includes:

acquiring insurance purchase information of the first object, and determining insurance ordered by the first object according to the insurance purchase information as target insurance;

and screening medicines belonging to the target insurance claim range from a preset medicine database to serve as the second medicines.

Optionally, after obtaining the first drug contained in the electronic prescription, the method further comprises:

acquiring drug attribute information of the first drug, the age of the first object and the sex of the first object;

determining an age application range and a gender application range of the first medicine according to the medicine attribute information;

Judging whether the age of the first object is in the age application range of the first medicine, and judging whether the sex of the first object is in the sex application range of the first medicine;

if the age of the first object is within the age application range of the first medicine and the sex of the first object is within the sex application range of the first medicine, matching the first medicine with the second medicine;

and if the age of the first object is not in the age application range of the first medicine and/or the sex of the first object is not in the sex application range of the first medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription.

acquiring the total dose of the first medicine, comparing the total dose with a preset standard dose, and judging whether the total dose is larger than the preset standard dose or not;

if the total dose is larger than the preset standard dose, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription;

If the total dose is smaller than or equal to the preset standard dose, matching the first medicine with the second medicine;

and/or, acquiring the total duration of the first object taking the first medicine, and recording the total duration as a medicine taking period;

comparing the medication period with a preset treatment period, and judging whether the medication period exceeds the preset treatment period;

if the medication period exceeds the preset treatment period, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription;

and if the medication period does not exceed the preset treatment period, matching the first medicine with the second medicine.

Optionally, after feeding back the electronic prescription to the first object, the method further comprises:

acquiring medicine purchase record information, insurance purchase record information and insurance claim record information of the first object;

evaluating the risk level of the first object according to the medicine purchase record information, the insurance purchase record information and the insurance claim record information of the first object; the method comprises the steps of,

And adjusting the insurance purchase amount and the insurance claim proportion of the first object in the next purchase period according to the evaluated risk level.

The application also provides an on-line inquiry system based on artificial intelligence, which comprises:

the identity state identification module is used for receiving a consultation request input by a first object and acquiring physical state information of the first object according to the consultation request;

the electronic prescription module is used for receiving an electronic prescription generated by a second object according to the physical state information of the first object;

the medicine identification module is used for carrying out keyword identification on the electronic prescription to obtain a first medicine contained in the electronic prescription;

a drug matching module for matching the first drug with the second drug and feeding back the electronic prescription to the first subject when the first drug is partially or completely matched with the second drug; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that requires a partial fee, a drug that does not require a fee.

The present application also provides a computer device comprising:

a processor; and, a step of, in the first embodiment,

a computer readable medium storing instructions that, when executed by the processor, cause the apparatus to perform a method as described in any one of the above.

The application also provides a computer readable medium having instructions stored thereon, the instructions being loaded by a processor and performing a method as described in any of the above.

As described above, the application provides an on-line inquiry method, system, equipment and medium based on artificial intelligence, which has the following beneficial effects:

firstly, receiving a consultation request input by a first object, and then acquiring physical state information of the first object according to the consultation request; receiving an electronic prescription generated by a second object according to the physical state information of the first object; performing keyword recognition on the electronic prescription to obtain a first medicine contained in the electronic prescription; finally, matching the first medicine with a second medicine, and feeding back the electronic prescription to the first object when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that pays a partial fee and/or a drug that does not pay a fee. Therefore, the application can realize the on-line inquiry of the first object by receiving the inquiry request input by the first object on line and then generating the electronic prescription on line by the second object. Meanwhile, the first medicine on the electronic prescription is identified, then the first medicine is matched with the second medicine, and if the first medicine is completely matched with or partially matched with the second medicine, the electronic prescription provided by the second object is indicated that the first object only needs to pay partial expense or does not need to pay the medicine of expense, so that the expense of the first object in the current inquiry can be reduced; and when the first medicine and the second medicine are not matched, the application can send a reminding message to the second object to remind the second object to adjust the electronic prescription, so that the first medicine and the second medicine are possibly partially matched as much as possible, thereby reducing the cost required to be paid by the first object in the current inquiry and reducing the economic expenditure of the first object in the disease inquiry. Therefore, the application solves the problem that the doctor electronic prescription medicine cannot be accurately matched with the actual condition of the first object (such as a patient) in the prior art by identifying the first medicine on the electronic prescription and then matching the first medicine with the second medicine, and simultaneously reduces the economic expenditure of the first object in the process of disease inquiry and relieves the problem of difficult seeing of the first object through medicine matching.

Drawings

FIG. 1 is a schematic diagram of an exemplary system architecture to which the teachings of one or more embodiments of the present application may be applied;

FIG. 2 is a flow chart of an on-line interrogation method based on artificial intelligence according to an embodiment of the application;

FIG. 3 is a flow chart of an on-line interrogation method based on artificial intelligence according to another embodiment of the present application;

FIG. 4 is a schematic diagram of a hardware architecture of an on-line interrogation system based on artificial intelligence according to an embodiment of the present application;

FIG. 5 is a schematic diagram of an on-line interrogation system based on artificial intelligence according to another embodiment of the present application;

FIG. 6 is a schematic diagram of a hardware architecture of a computer device suitable for implementing one or more embodiments of the application.

Detailed Description

Other advantages and effects of the present application will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present application with reference to specific examples. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.

It should be noted that, the illustrations provided in the present embodiment merely illustrate the basic concept of the present application by way of illustration, and only the components related to the present application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.

The on-line inquiry generally receives an inquiry request through an on-line inquiry platform (or a digital medical platform), and establishes communication connection between a user and terminal equipment corresponding to a doctor based on the inquiry request, so that the user and the doctor can perform on-line disease condition communication through text, voice and other modes based on the established communication connection, and on-line inquiry is completed.

FIG. 1 illustrates a schematic diagram of an exemplary system architecture to which the teachings of one or more embodiments of the present application may be applied. As shown in fig. 1, system architecture 100 may include a terminal device 110, a network 120, and a server 130. Terminal device 110 may include various electronic devices such as smart phones, tablet computers, notebook computers, desktop computers, and the like. The server 130 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud computing services. Network 120 may be a communication medium of various connection types capable of providing a communication link between terminal device 110 and server 130, and may be, for example, a wired communication link or a wireless communication link.

The system architecture in embodiments of the present application may have any number of terminal devices, networks, and servers, as desired for implementation. For example, the server 130 may be a server group composed of a plurality of server devices. In addition, the technical solution provided in the embodiment of the present application may be applied to the terminal device 110, or may be applied to the server 130, or may be implemented by the terminal device 110 and the server 130 together, which is not limited in particular.

In one embodiment of the present application, the terminal device 110 or the server 130 of the present application may receive a request for inquiry input by a first subject, and then acquire physical state information of the first subject according to the request for inquiry; receiving an electronic prescription generated by a second object according to the physical state information of the first object; performing keyword recognition on the electronic prescription to obtain a first medicine contained in the electronic prescription; finally, matching the first medicine with a second medicine, and feeding back the electronic prescription to the first object when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that pays a partial fee and/or a drug that does not pay a fee. The on-line inquiry method based on artificial intelligence is performed by using the terminal device 110 or the server 130, so that the on-line inquiry of the first object can be realized; meanwhile, by identifying the first medicine on the electronic prescription and then matching the first medicine with the second medicine, if the first medicine and the second medicine are completely matched or partially matched, the electronic prescription issued by the second object is indicated that the first object only needs to pay partial expense or does not need to pay the medicine of expense, so that the expense of the first object in the current inquiry can be reduced; and when the first medicine and the second medicine are not matched, a reminding message is sent to the second object to remind the second object to adjust the electronic prescription, so that the first medicine and the second medicine are partially matched as much as possible, the cost of the first object to be paid in the current inquiry is reduced, the economic expenditure of the first object in the disease inquiry is reduced, and the problem of difficulty in seeing a doctor of the first object is relieved.

The above section describes the content of an exemplary system architecture to which the technical solution of the present application is applied, and the on-line interrogation method based on artificial intelligence of the present application is further described.

Fig. 2 is a schematic flow chart of an on-line interrogation method based on artificial intelligence according to an embodiment of the application. Specifically, in an exemplary embodiment, as shown in fig. 2, the present embodiment provides an on-line interrogation method based on artificial intelligence, which includes the steps of:

s210, receiving a consultation request input by a first object, and acquiring physical state information of the first object according to the consultation request;

s220, receiving an electronic prescription generated by a second object according to the physical state information of the first object;

s230, keyword recognition is carried out on the electronic prescription, and a first medicine contained in the electronic prescription is obtained;

s240, matching the first medicine with a second medicine, and feeding back the electronic prescription to the first object when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that requires a partial fee, a drug that does not require a fee.

In this embodiment, the first subject may be a person suffering from one or more diseases, or may be a person suffering from one or more symptoms of a disease; for example, the first subject may be a person suffering from a rheumatic disease, a person having influenza symptoms, or the like. The second object in this embodiment may be a doctor of a medical institution, for example, the second object may be a doctor of a public medical institution, a doctor of a civil medical institution, or the like.

According to the above description, as an example, specifically, when a person a inputs a consultation corpus in an online consultation box on the digital medical platform, the digital medical platform generates a consultation request of the person a at this time. For example, when person a inputs "i have cough and nasal congestion symptoms in the online consultation box on the digital medical platform," if the consultation corpus is cold, "the digital medical platform will generate a consultation request of person a. Meanwhile, the neural network model on the digital medical platform can analyze the inquiry request to obtain the physical state information of the personnel A. The digital medical platform in this embodiment is embedded with a neural network model for analyzing the corpus, such as an OCR model (Optical Character Recognition, character recognition model, abbreviated as OCR), an LSTM model (Long Short-Term Memory network, abbreviated as LSTM), and the like. The method for acquiring the neural network model such as the OCR model and the LSTM model in this embodiment is not described herein, and may be acquired from an existing document. Therefore, when a person A inputs 'i's cough with a spot and nasal obstruction symptoms 'in an online consultation box on a digital medical platform, whether the person A is cold or not' is the consultation corpus ', an OCR model on the digital medical platform can identify and analyze whether the consultation corpus is cold or not' after keyword identification, medical keywords 'cough', 'nasal obstruction' and 'cold' are extracted from the consultation corpus, and then the extracted medical keywords 'cough', 'nasal obstruction' and 'cold' are used as physical state information of the person A.

After obtaining the physical state information of the person a, the present embodiment may match a doctor related to the physical state information of the person a from among doctors previously entered in the digital medical platform, for example, match doctor B, and then analyze the identity state information of the person a by doctor B, while generating the electronic prescription C by doctor B according to the physical state information of the person a. In this embodiment, in the process of generating the electronic prescription C of the person a according to the physical state information of the person a, the doctor B may also inquire about the person a, and at the same time, the person a may also answer the inquiry of the doctor B later, for example, the doctor B may inquire about what the body temperature of the person a is, and the person a may answer 38.5 degrees later. For the following procedure of doctor B and the subsequent reply procedure of person a, the description of this embodiment is omitted.

After the doctor B generates the electronic prescription C according to the physical state information of the person a, the embodiment may identify the keyword of the electronic prescription C through the OCR model on the digital medical platform, so as to obtain the medicine contained in the electronic prescription C, and record the medicine as the first medicine. Matching the first medicine with a second medicine obtained in advance or in real time, and if the first medicine and the second medicine are partially identical, considering that the first medicine and the second medicine are partially matched; similarly, if the first drug is identical to the second drug, then the first drug is considered to be exactly matched to the second drug; conversely, if the first and second drugs are not identical, then the first and second drugs are considered to be completely mismatched. The second medicines in this embodiment include, but are not limited to, medicines requiring a part of the fee payment, medicines requiring no fee payment.

For example, the first medicine contained in the electronic prescription C is: drug m, drug n, and drug k; the second medicine is: if the medicine n requiring a part of the fee and the medicine k not requiring a part of the fee are the same, the first medicine is considered to be the same as the second medicine, and the electronic prescription C is directly fed back to the person a. For another example, if the second medicine contains a medicine m for which a partial fee is required, a medicine n for which a partial fee is required, and a medicine k for which a fee is not required, the first medicine is considered to be identical to the second medicine, and the electronic prescription C is directly fed back to the person a. For example, if the second medicine contains a medicine p needing to pay part of the fees and a medicine q needing not to pay the fees, the first medicine is considered to be completely different from the second medicine, and the doctor B is reminded to adjust the electronic prescription C; if doctor B does not adjust electronic prescription C, electronic prescription C is directly fed back to person A. If doctor B adjusts the electronic prescription C, then the adjusted electronic prescription C1 is identified by keywords, and the above procedure is repeated.

Therefore, in this embodiment, the on-line inquiry of the person a can be achieved by receiving the inquiry request input by the person a on line and then generating the electronic prescription C on line by the doctor B. Meanwhile, according to the method, the first medicine on the electronic prescription is identified, and then the first medicine is matched with the second medicine, so that the medicine which only needs to pay part of the cost or does not need to pay the cost of the personnel A can be obtained, the cost which needs to be paid by the personnel A in the current inquiry is reduced, the economic expenditure of the personnel A in the disease inquiry is reduced, and the problem of difficulty in seeing the disease of the personnel A is relieved.

In some exemplary implementations, the determining of the second drug may include: acquiring insurance purchase information of the first object, and determining insurance ordered by the first object according to the insurance purchase information as target insurance; and screening medicines belonging to the target insurance claim range from a preset medicine database to serve as the second medicines. That is, the second medicine in this embodiment is a medicine which belongs to the first object and to which the purchased insurance can be reimbursed or paid. For example, the second medication may be a medication that the resident medical insurance purchased by the first subject may reimburse or pay for. For another example, the second medication may be a medication that may be reimbursed or paid for by the employee medical insurance purchased by the first subject. For another example, the second medication may be a medication that the business insurance purchased by the first subject may reimburse or pay for. The preset drug database in this embodiment may be matched with a disease library, and the disease library may be obtained according to the international disease classification icd10 code management. For example, the embodiment can be used for maintaining basic data of Chinese and western medicines, then establishing a set of flexible extended label attribute values, and marking various labels for related medicines according to different wind control requirements; and establishing an international unified icd10 coding library and performing unified association on related diseases and medicines.

Therefore, in this embodiment, the first medicine prescribed by the doctor is compared with the second medicine which can be paid less or not paid by the first object, so that the patient can complete the inquiry and treatment of the disease with less money. Meanwhile, when a doctor makes a consultation, for some medicines with higher price or medicines which are not in the claimation responsibility of a commercial insurance company, the doctor can be guided to adjust the prescription without opening or as a risk prompt, so that the expense of the consultation of the patient is reduced, and the problem of difficulty in seeing the patient is relieved. In addition, for the commercial insurance company, because the current clinic medical cost is higher, the supplementary claim settlement cost of the corresponding commercial insurance company is also high, and the online inquiry service described in the embodiment can help the commercial insurance company to complete the cost control target, so that the clinic claim settlement cost is reduced.

According to the above description, in an exemplary implementation, the process of receiving a request for a consultation input by a first subject and acquiring physical state information of the first subject according to the request for the consultation includes: receiving and responding to the inquiry request input by the first object, and prompting to input the identity information of the first object according to a request response result; the identity information input in this embodiment includes, but is not limited to: name, gender, date of birth, type of certificate, and number of certificate, etc. The identity information input at the current moment is used as first identity information, the first identity information is matched with a preset identity database, and whether the first identity information exists in the preset identity database is determined; the preset identity database in this embodiment may be an identity database registered on the digital medical platform in advance. For example, if a user completes registration on the digital medical platform in advance, the identity information of the user is stored in the identity database of the digital medical platform. If the first identity information exists in the preset identity database, analyzing the inquiry request to acquire the physical state information of the first object; and if the first identity information does not exist in the preset identity database, carrying out identity marking on the first object.

Therefore, the first object or the inquirer is authenticated by real name, so that the online inquiry and the doctor's prescription link can not be changed by other inquirers, and the fraudulent medicine behavior, the fraudulent insurance behavior and the like are avoided.

According to the foregoing description, in an exemplary implementation, before the analyzing the inquiry request, the method may further include: shooting the first object at the current moment to obtain an image to be identified; identifying an image to be identified, and matching identity information associated with the image to be identified from the preset identity database according to an image identification result, and marking the identity information as second identity information; verifying and comparing the first identity information with the second identity information to determine whether the first identity information and the second identity information are identical; if the first identity information is the same as the second identity information, analyzing the inquiry request; and if the first identity information and the second identity information are different, carrying out identity marking on the first object. Or if the identity information associated with the image to be identified is not matched from the preset identity database according to the image identification result, the identity of the first object is marked.

Therefore, the embodiment can ensure the authenticity of the on-line inquiry by shooting the image in real time to perform the secondary authentication on the first object or the inquiry person. Meanwhile, in the embodiment, the first object or the inquirer is subjected to double authentication in the form of images and characters, so that other people can be prevented from performing medicine cheating behaviors, warranty behaviors and the like by using the identity information of the first object or the inquirer.

According to the above description, in an exemplary implementation, after obtaining the first medicine included in the electronic prescription, the method may further include: acquiring drug attribute information of the first drug, the age of the first object and the sex of the first object; determining an age application range and a gender application range of the first medicine according to the medicine attribute information; judging whether the age of the first object is in the age application range of the first medicine, and judging whether the sex of the first object is in the sex application range of the first medicine; if the age of the first object is within the age application range of the first medicine and the sex of the first object is within the sex application range of the first medicine, matching the first medicine with the second medicine; and if the age of the first object is not in the age application range of the first medicine and/or the sex of the first object is not in the sex application range of the first medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription.

Therefore, the embodiment can set the applicable object of the medicine, and prevent the medicine from being used on unreasonable personnel and presenting unpredictable risks. Namely, in the embodiment, by setting the expansion label of the medicine, which kind of medicine is used by men or women, if the inquirer is men, the doctor can not prescribe the medicine of women; the age limit of the medicine, for example, the limited age of the medicine is within 18 years, and then the consultants beyond 18 years cannot meet the requirements of claim management and management, so that the medicine does not meet the age requirements, the medication risk is reduced, and the problem of increased claim cost caused by medication is also solved.

According to the above description, in an exemplary implementation, after obtaining the first medicine included in the electronic prescription, the method may further include: acquiring the total dose of the first medicine, comparing the total dose with a preset standard dose, and judging whether the total dose is larger than the preset standard dose or not; if the total dose is larger than the preset standard dose, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; and if the total dose is smaller than or equal to the preset standard dose, matching the first medicine with the second medicine. And/or, acquiring the total duration of the first object taking the first medicine, and recording the total duration as a medicine taking period; comparing the medication period with a preset treatment period, and judging whether the medication period exceeds the preset treatment period; if the medication period exceeds the preset treatment period, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; and if the medication period does not exceed the preset treatment period, matching the first medicine with the second medicine.

From this, the present embodiment can control overdosing. The preset standard dose may be a dose corresponding to a preset treatment period, for example, the preset treatment period in this embodiment may be 7 days, and the maximum standard dose within 7 days is 30 boxes. The method is equivalent to the embodiment, the period of treatment of different medicines can be maintained, for example, the limited purchase amount is 30 boxes within 7 days, and the doctor can be prompted whether overdose exists by checking whether the purchase total amount of the medicines exceeds the limited purchase amount within 7 days. If so, the doctor is reminded to adjust the prescription, so that the patient is not overdosed. In addition, the application can calculate the treatment course days through the current treatment time-the last treatment time, and if the calculated treatment course days are less than or equal to the treatment course period, the overdose is prompted or the patient and the doctor are informed that the risk of failing to settle the claim exists in the current medication. In addition, the period of the treatment course of the medicine of the present application may be set to 10 days.

In an exemplary implementation, after feeding back the electronic prescription to the first object, the method may further include: acquiring medicine purchase record information, insurance purchase record information and insurance claim record information of the first object; performing risk control on the first object according to the medicine purchase record information, the insurance purchase record information and the insurance claim record information of the first object, and evaluating the risk level of the first object; and adjusting the insurance purchase amount and the insurance claim proportion of the first object in the next purchase period according to the evaluated risk level.

Therefore, the risk level management can be performed on the user, and different risk level factors are set, for example, the risk of serious illness is defined according to the medication records of the user, and the disease risk level of which type is marked is higher, so that different risk levels are calculated, and intervention of some diseases and adjustment of whether to renew and rate can be pre-performed according to the level of the risk level. Meanwhile, in this embodiment, for an insurance company selling commercial insurance to users, it is reasonable to set different pay proportions for different types of users, that is, this embodiment may set pay proportions and limits according to policy responsibilities, or set different pay proportions according to different label users, for example, different pay proportions for patients with slow diseases, and identify the risk level of users according to the past user medication records, set different pay proportions, and for users with higher risk levels, determine whether to allow users to renew. The method and the system are equivalent to the method and the system, the risk level of the user can be estimated according to the past medication records and the wind control early warning of the user, and the pay proportion, pay amount or pay amount of each user can be determined according to the insurance policy of different dangerous responsibilities.

In another exemplary embodiment, as shown in fig. 3, the present embodiment further provides an on-line interrogation method based on artificial intelligence, including the following steps:

1) Limiting inquiry of the insured life; comprising the following steps: according to the 5 items (name, sex, date of birth, certificate type and certificate number) of the insured person, the real name authentication creates the doctor to ensure that the on-line inquiry and doctor's prescription link can not change other doctor, thereby avoiding the risk of cheating insurance.

2) A drug-applicable subject is determined, including a drug-applicable age limit and a drug-applicable gender limit. Specifically, the drug sex restriction process includes: setting an expansion label of the medicine to distinguish which type of medicine is used by men or women, and if the doctor is a male, then the doctor can not prescribe the medicine of the women. The drug age limiting process includes: for example, if a certain medicine is limited to be within 18 years old, the doctor beyond 18 years old does not meet the requirements of claim settlement and wind control, and prompts that the medicine does not meet the requirements of the age, so that the problem of increasing the claim settlement cost caused by medication risk is solved. If the age and sex of the doctor meet the requirements of the medicine, the doctor can be considered to be able to conduct insurance claim settlement on the current doctor; otherwise, when the age or sex of the doctor does not meet the requirement of the medicine, the doctor considers that the doctor cannot conduct insurance claim settlement on the current doctor, and informs the doctor and doctor that the current medicine has risk of failing claim settlement.

3) Managing the disease of claim; comprising the following steps: according to the international disease classification icd10 code management, a disease library is obtained, and then the diseases (the claim disease blacklist) which are not in the insurance responsibility and the diseases (the claim disease whitelist) which are in the insurance responsibility are maintained and distinguished according to the policy responsibility, so that a doctor or a doctor can be reminded before the doctor prescribes, the prescription purchasing medicine is not in the claim responsibility range, and the payment cost exceeding the claim responsibility is reduced. Specifically, the method comprises the steps of judging the claim range of a prescription issued by a doctor, and if the prescription issued by the doctor is within the claim range, considering that insurance claim settlement can be carried out on current doctor; otherwise, inform the doctor of the risk of the current prescription being unable to be paid.

4) Managing the claim medicine; comprising the following steps: drugs (black list of drugs) which are not in the claims are maintained, such as that the toxic side effect is large or that part of the health care products are not in the claims of the commercial insurance company, and the doctor of the drugs can not prescribe or the risk prompt is not in the claims. Specifically, judging the claim range of the medicine prescribed by the doctor, and if the prescription medicine is within the claim range, considering that the insurance claim can be paid to the current doctor; otherwise, inform the doctor and doctor that there is risk of failing to claim the current medicine.

5) Overdose management; comprising the following steps: and maintaining the treatment course period of different medicines, for example, limiting the purchase amount by 30 boxes within 7 days, checking whether the purchase total amount of the medicines exceeds the limit purchase amount within 7 days, and if so, prompting overdose and failing to purchase the medicines again by a user. If the treatment period of the medicine is set to be 10 days, the treatment period number can be calculated by the current treatment time-the last treatment date, and if the calculated treatment period number is less than or equal to the treatment period, overdose is prompted or the doctor is informed that the risk of failing to settle the claim exists in the current medicine.

6) User pay proportion management; comprising the following steps: the method comprises the steps of setting the pay proportion and the limit according to the policy responsibility, or setting different pay proportions according to different label users, such as setting different pay proportions for patients with chronic diseases, identifying the risk level of the users according to the traditional user medication records, setting different pay proportions, and determining whether the users can renew the pay proportion again by the users with higher risk levels. Specifically, in making policy claims, the payoff amount=the sum of the insurance orders is the payoff proportion. If the payable amount is less than or equal to the limit, the payable amount available to the attendant = limit-total amount of the insurance order. If the payable amount is greater than the limit, the attendant may receive a full claim.

7) Managing risk levels; comprising the following steps: different risk level factors are set, for example, the risk of serious diseases is defined according to the medication records of users, and the disease risk level of which type is higher is marked, so that different risk levels are calculated, and according to the level of the risk level, the prepositive intervention of some diseases can be performed, whether to keep the doctor for a long time and whether to adjust the insurance rate of the doctor can be determined.

In summary, the application provides an on-line inquiry method based on artificial intelligence, which comprises the steps of firstly receiving an inquiry request input by a first object, and then acquiring physical state information of the first object according to the inquiry request; receiving an electronic prescription generated by a second object according to the physical state information of the first object; performing keyword recognition on the electronic prescription to obtain a first medicine contained in the electronic prescription; finally, matching the first medicine with a second medicine, and feeding back the electronic prescription to the first object when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that pays a partial fee and/or a drug that does not pay a fee. Therefore, the method can realize the on-line inquiry of the first object by receiving the inquiry request input by the first object on line and then generating the electronic prescription on line by the second object. Meanwhile, the method identifies the first medicine on the electronic prescription, then matches the first medicine with the second medicine, and if the first medicine and the second medicine are completely matched or partially matched, the method shows that the electronic prescription prescribed by the second object only needs to pay partial expense or does not need to pay the medicine of expense, so that the expense of the first object in the current inquiry can be reduced; and when the first medicine and the second medicine are not matched, the method can send a reminding message to the second object to remind the second object to adjust the electronic prescription, so that the first medicine and the second medicine are possibly partially matched as much as possible, the cost of the first object to be paid in the current inquiry is reduced, and the economic expenditure of the first object in the disease inquiry is reduced. Therefore, the method solves the problem that the doctor electronic prescription medicine cannot be accurately matched with the actual condition of the patient in the on-line consultation of the prior art by identifying the first medicine on the electronic prescription and then matching the first medicine with the second medicine, and simultaneously can reduce the economic expenditure of the patient in the disease consultation and relieve the problem of difficult patient seeing through medicine matching. In addition, the method can realize the purposes of reducing premium payment cost and improving profitability for commercial insurance companies by designing a set of charge control scheme for the prescription, and is better combined with medical services. Moreover, the application provides a symbiotic mode of insurance and health service, which is a great direction of actively responding to national policies, and also encourages business insurance to be more and more innovated in the service mode. In addition, the method can help the business insurance company to complete the fee control target through the online inquiry service, and reduces the cost of clinic reimbursement. Meanwhile, in the process of inquiring and prescribing medicines by doctors, the method can guide the doctors to adjust prescriptions without opening doctors or as risk prompts for medicines which are not in the claimation responsibility of the commercial insurance companies, and evaluate risk customers according to the traditional medicine records, so that the commercial insurance companies can determine whether follow-up maintenance or rate adjustment can be carried out, thereby reducing the pay rate of the insurance companies. In addition, the method can remind customers to intervene in diseases or manage health in advance according to customers with different risk grades, especially high risk customers, and finally reduce the claim settlement cost for business insurance companies.

As shown in fig. 4, the present application further provides an on-line interrogation system based on artificial intelligence, the system comprising:

the identity state recognition module 410 is configured to receive a query request input by a first object, and obtain physical state information of the first object according to the query request;

an electronic prescription module 420, configured to receive an electronic prescription generated by a second subject according to physical state information of the first subject;

the medicine identification module 430 is configured to identify a keyword of the electronic prescription, so as to obtain a first medicine included in the electronic prescription;

a medicine matching module 440 for matching the first medicine with a second medicine and feeding back the electronic prescription to the first subject when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that requires a partial fee, a drug that does not require a fee.

In another exemplary embodiment, as shown in fig. 5, the present embodiment further provides an on-line interrogation system based on artificial intelligence, including: the system comprises an insurance user management module, a medicine basic data module, a medicine starting monitoring module, a health file management module and an order transaction module.

The insurance user management module is mainly used for managing client information and insurance policy information of insurance policy users of a commercial insurance company through an internal insurance policy user management unit, an insurance policy claim liability unit, a user claim proportion and limit unit, a user limit management unit and a user wind control grade unit, and evaluating the risk grade of the user according to the claim proportion, the amount or claim limit of the insurance policy corresponding to each user and the past medication records and wind control early warning of the user.

The medicine basic data module is mainly used for maintaining basic data of Chinese and western medicines through an internal medicine management unit, a label management unit, a medicine label decoupling unit, an icd10 coding disease library unit and a medicine disease association maintenance unit, and establishing a set of flexible extended label attribute values, so that various labels can be marked for related medicines according to different wind control requirements; an international unified icd10 code library is established, and related diseases and medicines are uniformly associated.

The medicine-opening monitoring module mainly sets a black-and-white list within a claim-settling range or not through an internal except disease management unit, a claim-settling disease management unit, a except medicine management unit, a medicine overdose setting unit, a medicine treatment course period unit, a wind control factor definition and weight setting unit, and controls the medicine range prescribed by doctors; or setting overdose or treatment period of the medicine, and if the overdose or treatment period is exceeded, the medicine is not allowed to be started again.

The health file management module mainly creates a doctor according to 5 items of information of a insured person or an applicant of a policy through an internal doctor management unit, a doctor inquiry recording unit and a prescription recording unit, and manages the generated corresponding doctor inquiry records and prescription information.

The order transaction module is mainly used for calculating the pay amount of the insurance policy according to the individual pay proportion and limit of the user through an internal claim settlement component unit, an insurance policy settlement unit and an order recording unit, interfacing with a claim settlement system of a commercial insurance company, opening a direct purchasing claim, and managing the order record of the purchasing order of the prescription of the user.

In another exemplary embodiment, the present embodiment also provides an artificial intelligence based on-line interrogation system for performing the following process:

It should be noted that, the on-line interrogation system based on artificial intelligence provided in the above embodiment and the on-line interrogation method based on artificial intelligence provided in the above embodiment belong to the same concept, and the specific manner in which each module performs the operation has been described in detail in the method embodiment, which is not repeated here. In practical application, the on-line inquiry system based on artificial intelligence provided in the above embodiment may distribute the functions to be completed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above, which is not limited herein.

In summary, the application provides an on-line inquiry system based on artificial intelligence, which firstly receives an inquiry request input by a first object, and then obtains physical state information of the first object according to the inquiry request; receiving an electronic prescription generated by a second object according to the physical state information of the first object; performing keyword recognition on the electronic prescription to obtain a first medicine contained in the electronic prescription; finally, matching the first medicine with a second medicine, and feeding back the electronic prescription to the first object when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that pays a partial fee and/or a drug that does not pay a fee. Therefore, the system can realize the on-line inquiry of the first object by receiving the inquiry request input by the first object on line and then generating the electronic prescription on line by the second object. Meanwhile, the system identifies the first medicine on the electronic prescription, then matches the first medicine with the second medicine, and if the first medicine and the second medicine are completely matched or partially matched, the electronic prescription provided by the second object is indicated that the first object only needs to pay partial expense or does not need to pay the medicine of expense, so that the expense of the first object in the current inquiry can be reduced; and when the first medicine and the second medicine are not matched completely, the system can send a reminding message to the second object to remind the second object to adjust the electronic prescription, so that the first medicine and the second medicine are possibly partially matched as much as possible, the cost of the first object to be paid in the current inquiry is reduced, and the economic expenditure of the first object in the disease inquiry is reduced. Therefore, the system solves the problem that the doctor electronic prescription medicine cannot be accurately matched with the actual condition of the patient in the on-line consultation of the prior art by identifying the first medicine on the electronic prescription and then matching the first medicine with the second medicine, and simultaneously can reduce the economic expenditure of the patient in the disease consultation and relieve the problem of difficult patient seeing through medicine matching. In addition, the system can realize the purposes of reducing premium payment cost and improving profitability for commercial insurance companies by designing a set of charge control scheme for starting medicines, and is better combined with medical services. Moreover, the application provides a symbiotic mode of insurance and health service, which is a great direction of actively responding to national policies, and also encourages business insurance to be more and more innovated in the service mode. In addition, the system can help the business insurance company to complete the fee control target through the online inquiry service, and reduces the cost of clinic claims. Meanwhile, in the process of inquiring and prescribing medicines by doctors, the system can guide the doctors to adjust prescriptions without opening doctors or as risk prompts for medicines which are not in the claimation responsibility of commercial insurance companies, and evaluate risk clients according to the traditional medicine records, so that the commercial insurance companies can determine whether follow-up maintenance or rate adjustment can be carried out, and the pay rate of the insurance companies is reduced. In addition, the system can remind customers to intervene in diseases or manage health in advance according to customers with different risk grades, especially high risk customers, and finally reduces the claim settlement cost for business insurance companies. Therefore, the application effectively overcomes various defects in the prior art and has high industrial utilization value.

The embodiment of the application also provides a computer device, which can comprise: one or more processors; and one or more machine readable media having instructions stored thereon, which when executed by the one or more processors, cause the apparatus to perform the method described in fig. 2. Fig. 6 shows a schematic structural diagram of a computer device 600. Referring to fig. 6, a computer apparatus 600 includes: processor 610, memory 620, power source 630, display unit 640, input unit 660.

The processor 610 is a control center of the computer device 600, connects the various components using various interfaces and lines, and performs various functions of the computer device 600 by running or executing software programs and/or data stored in the memory 620, thereby performing overall monitoring of the computer device 600. In an embodiment of the present application, the processor 610 performs the method described in FIG. 2 when it invokes a computer program stored in the memory 620. Optionally, the processor 610 may include one or more processing units; preferably, the processor 610 may integrate an application processor that primarily handles operating systems, user interfaces, applications, etc., with a modem processor that primarily handles wireless communications. In some embodiments, the processor, memory, may be implemented on a single chip, and in some embodiments, they may be implemented separately on separate chips.

The memory 620 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, various applications, and the like; the storage data area may store data created according to the use of the computer device 600, etc. In addition, memory 620 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device, and the like.

The computer device 600 also includes a power supply 630 (e.g., a battery) for powering the various components that can be logically connected to the processor 610 through a power management system that can perform functions for managing charge, discharge, and power consumption.

The display unit 640 may be used to display information input by a user or information provided to the user, various menus of the computer device 600, and the like, and in the embodiment of the present application, is mainly used to display a display interface of each application in the computer device 600, and objects such as text and pictures displayed in the display interface. The display unit 640 may include a display panel 650. The display panel 650 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an Organic Light-Emitting Diode (OLED), or the like.

The input unit 660 may be used to receive information such as numbers or characters input by a user. The input unit 660 may include a touch panel 670 and other input devices 680. Wherein the touch panel 670, also referred to as a touch screen, may collect touch operations thereon or thereabout by a user (such as operations of the user on the touch panel 670 or thereabout using any suitable object or accessory such as a finger, stylus, etc.).

Specifically, the touch panel 670 may detect a touch operation by a user, detect signals resulting from the touch operation, convert the signals into coordinates of contacts, send the coordinates to the processor 610, and receive and execute commands sent from the processor 610. In addition, the touch panel 670 may be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. Other input devices 680 may include, but are not limited to, one or more of a physical keyboard, function keys (e.g., volume control keys, on-off keys, etc.), a trackball, mouse, joystick, etc.

Of course, the touch panel 670 may cover the display panel 650, and when the touch panel 670 detects a touch operation thereon or thereabout, the touch operation is transmitted to the processor 610 to determine the type of touch event, and then the processor 610 provides a corresponding visual output on the display panel 650 according to the type of touch event. Although in fig. 6, the touch panel 670 and the display panel 650 are implemented as two separate components for the input and output functions of the computer device 600, in some embodiments, the touch panel 670 and the display panel 650 may be integrated to implement the input and output functions of the computer device 600.

The computer device 600 may also include one or more sensors, such as a pressure sensor, a gravitational acceleration sensor, a proximity light sensor, and the like. Of course, the computer device 600 may also include other components such as cameras, as desired in a particular application.

Embodiments of the present application also provide a computer-readable storage medium having instructions stored therein that, when executed by one or more processors, enable the apparatus to perform the method of the present application as described in fig. 2.

It will be appreciated by those skilled in the art that fig. 6 is merely an example of a computer device and is not limiting of the device, and that the device may include more or fewer components than shown, or may combine certain components, or different components. For convenience of description, the above parts are described as being functionally divided into modules (or units) respectively. Of course, in implementing the present application, the functions of each module (or unit) may be implemented in the same piece or pieces of software or hardware.

It will be appreciated by those skilled in the art that the application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application, which are desirably implemented by computer program instructions, each flowchart and/or block diagram illustration, and combinations of flowchart illustrations and/or block diagrams. These computer program instructions may be applied to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. Accordingly, it is intended that all equivalent modifications and variations of the application be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.

Claims

1. An on-line interrogation method based on artificial intelligence, comprising the steps of:

2. The artificial intelligence based on-line inquiry method according to claim 1, wherein the process of receiving an inquiry request input by a first subject and acquiring physical state information of the first subject according to the inquiry request includes:

3. The artificial intelligence based on-line interrogation method of claim 2, wherein prior to parsing the interrogation request, the method further comprises:

4. An artificial intelligence based on-line interrogation method according to any of claims 1 to 3, wherein the process of determining the second drug product comprises:

5. The artificial intelligence based on-line interrogation method of claim 1, wherein after obtaining the first drug contained in the electronic prescription, the method further comprises:

6. The artificial intelligence based on-line interrogation method of claim 1 or 5, wherein after obtaining the first drug contained in the electronic prescription, the method further comprises:

7. The artificial intelligence based on-line interrogation method of claim 1, wherein after feeding back the electronic prescription to the first subject, the method further comprises:

8. An on-line interrogation system based on artificial intelligence, the system comprising:

the medicine matching module is used for matching the first medicine with the second medicine and feeding back the electronic prescription to the first object when the first medicine is partially matched or completely matched with the second medicine; or when the first medicine is not matched with the second medicine, returning the electronic prescription to the second object, and sending an adjustment message to the second object, wherein the adjustment message is used for prompting the second object to adjust the electronic prescription; wherein the second drug comprises: a drug that requires a partial fee, a drug that does not require a fee.

9. A computer device, comprising:

a processor; and, a step of, in the first embodiment,

a computer readable medium storing instructions which, when executed by the processor, cause the apparatus to perform the method of any one of claims 1 to 7.

10. A computer readable medium having instructions stored thereon, the instructions being loaded by a processor and performing the method of any of claims 1 to 7.