CN111028089A - Abnormal operation identification method and device, computer storage medium and electronic equipment - Google Patents
Abnormal operation identification method and device, computer storage medium and electronic equipment Download PDFInfo
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Abstract
The present disclosure relates to the field of computer technology, and provides an abnormal operation identification method, an abnormal operation identification device, a computer storage medium, and an electronic device, wherein the abnormal operation identification method includes: responding to the medicine taking operation of the target user, and acquiring characteristic information of the target user and state information of a medical insurance card used by the target user; acquiring the historical record times of the characteristic information of the target user in a preset time period; if the state information of the medical insurance card is in a frozen state or the historical record times are greater than a first preset threshold value, determining that the medicine taking operation is abnormal operation; and stopping the medicine taking process corresponding to the medicine taking operation. The abnormal operation identification method in the disclosure can not only identify the abnormal operation in real time, but also improve the identification accuracy.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to an abnormal operation identification method, an abnormal operation identification apparatus, a computer storage medium, and an electronic device.
Background
With the continuous improvement of the living standard of people, people gradually receive various insurance projects, and particularly medical insurance for guaranteeing basic medical requirements is particularly emphasized by people. However, with the popularization of medical insurance and the uncoordinated development of claim settlement auditing mechanisms, abnormal use of medical insurance frequently occurs, and unnecessary loss is brought to medical insurance organizations such as state organs and enterprises.
At present, the related medical insurance institutions generally identify abnormal operating personnel of medical insurance through traditional means such as customer blacklists recorded in a credit investigation system, and cannot distinguish abnormal operating behaviors or abnormal operating personnel in real time when a medicine taking window of a hospital or a pharmacy purchases medicines. Thus, the prior art is not real-time enough and has poor recognition accuracy.
In view of the above, there is a need in the art to develop a new abnormal operation identification method and apparatus.
It is to be noted that the information disclosed in the background section above is only used to enhance understanding of the background of the present disclosure.
Disclosure of Invention
The present disclosure is directed to provide an abnormal operation identification method, an abnormal operation identification apparatus, a computer storage medium, and an electronic device, so as to avoid, at least to a certain extent, the technical problem of poor real-time performance of the method in the prior art.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to a first aspect of the present disclosure, there is provided an abnormal operation identification method, including: responding to the medicine taking operation of a target user, and acquiring the characteristic information of the target user and the state information of a medical insurance card used by the target user; acquiring the historical record times of the characteristic information of the target user in a preset time period; if the state information of the medical insurance card is in a frozen state or the historical record times are greater than a first preset threshold value, determining that the medicine taking operation is abnormal operation; and stopping the medicine taking process corresponding to the medicine taking operation.
In an exemplary embodiment of the present disclosure, the characteristic information of the target user includes at least one of: face information, fingerprint information, voiceprint information.
In an exemplary embodiment of the present disclosure, the method further comprises: acquiring a historical medicine taking record of the target user based on the characteristic information of the target user; acquiring the disease type corresponding to the medicine contained in the historical medicine taking record; and if the number of the disease types is larger than a second preset threshold value, determining that the medicine taking operation of the target user is abnormal operation.
In an exemplary embodiment of the present disclosure, the method further comprises: acquiring prescription information of the target user; taking the current time as the current taking date of the target medicine contained in the prescription information; determining a first taking date of the target medicine from the historical medicine taking record, wherein the first taking date is a date of taking the target medicine the last time the current taking date is; determining the taking frequency of the target medicine according to the time interval between the first taking date and the current taking date; and when the taking frequency of the target medicine is detected to be greater than the standard taking frequency corresponding to the target medicine, determining that the medicine taking operation of the target user is abnormal operation.
In an exemplary embodiment of the present disclosure, the method further comprises: acquiring the number of medical insurance cards used by the target user based on the characteristic information of the target user; and if the number of the medical insurance cards is larger than a third preset threshold value, judging that the medicine taking operation is abnormal operation.
In an exemplary embodiment of the present disclosure, the method further comprises: acquiring the number of the users of the medical insurance card in the preset time period; and if the number of the users is larger than a fourth preset threshold, judging that the medicine taking operation is abnormal operation.
In an exemplary embodiment of the present disclosure, the method further comprises: if the medicine taking operation is not abnormal operation, acquiring the treatment information of the target user, wherein the treatment information comprises medical expense information and medical insurance card information; calling an interface of a medical insurance system to enable the medical insurance system to determine medical insurance payment cost according to the medical expense information and the medical insurance card information; acquiring medical insurance payment cost returned by the medical insurance system, and determining self-payment cost according to the medical expense information and the medical insurance payment cost; and settling medical expenses according to the self-payment expense and the medical insurance payment expense.
According to a second aspect of the present disclosure, there is provided an abnormal operation identifying apparatus including: the first acquisition module is used for responding to the medicine taking operation of a target user and acquiring the characteristic information of the target user and the state information of a medical insurance card used by the target user; the second acquisition module is used for acquiring the historical record times of the characteristic information of the target user in a preset time period; the identification module is used for determining that the medicine taking operation is abnormal operation if the state information of the medical insurance card is in a frozen state or the historical record times are greater than a first preset threshold value; and the flow stopping module is used for stopping the medicine taking flow corresponding to the medicine taking operation.
According to a third aspect of the present disclosure, there is provided a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the abnormal operation identifying method of the first aspect described above.
According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the abnormal operation identification method of the first aspect via execution of the executable instructions.
As can be seen from the foregoing technical solutions, the abnormal operation identification method, the abnormal operation identification apparatus, the computer storage medium and the electronic device in the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:
in the technical solutions provided in some embodiments of the present disclosure, on one hand, in response to a medicine taking operation of a target user, feature information of the target user and state information of a medical insurance card used by the target user are obtained, and the number of times of a history record of the feature information of the target user in a preset time period is obtained, so that the identity of the target user can be accurately verified, and occurrence of abnormal behaviors such as medical insurance fraud and the like is reduced. Furthermore, if the state information of the medical insurance card is in a frozen state or the number of times of historical records is greater than a first preset threshold value, the medicine taking operation is determined to be abnormal operation, real-time monitoring on a target user can be realized, the technical problem that only a credit investigation system, a historical blacklist system and the like are used for identification in the prior art, so that the real-time performance and accuracy are poor is solved, the identification accuracy is improved, and abnormal behaviors such as medical insurance fraud and the like are avoided. On the other hand, after the abnormal operation is identified, the medicine taking process corresponding to the medicine taking operation is stopped in time, the legal rights and interests of the medical insurance personnel can be reasonably maintained, the medical insurance resources can be used on the cutting edge, the personnel with the requirements of the medical insurance can be guaranteed to obtain more sufficient medical guarantee, and the practicability of the medical insurance is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
FIG. 1 illustrates a flow diagram of an abnormal operation identification method in an exemplary embodiment of the present disclosure;
FIG. 2 illustrates a flow diagram of an abnormal operation identification method in another exemplary embodiment of the present disclosure;
FIG. 3 illustrates a flow diagram of an abnormal operation identification method in yet another exemplary embodiment of the present disclosure;
FIG. 4 shows a flow diagram of an abnormal operation identification method in yet another exemplary embodiment of the present disclosure;
FIG. 5 illustrates an overall flow diagram of a method of abnormal operation identification in an exemplary embodiment of the present disclosure;
fig. 6 shows a schematic configuration diagram of an abnormal operation recognition apparatus in an exemplary embodiment of the present disclosure;
FIG. 7 shows a schematic diagram of a structure of a computer storage medium in an exemplary embodiment of the disclosure;
fig. 8 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
The terms "a," "an," "the," and "said" are used in this specification to denote the presence of one or more elements/components/parts/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.; the terms "first" and "second", etc. are used merely as labels, and are not limiting on the number of their objects.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.
At present, the related medical insurance institutions generally identify abnormal operating personnel of medical insurance through traditional means such as customer blacklists recorded in a credit investigation system, and cannot distinguish abnormal operating behaviors or abnormal operating personnel in real time when a medicine taking window of a hospital or a pharmacy purchases medicines. Thus, the prior art is not real-time enough and has poor recognition accuracy.
In the embodiment of the present disclosure, firstly, an abnormal operation identification method is provided, which overcomes, at least to some extent, the defect of poor method identification accuracy of the abnormal operation identification method provided in the prior art.
Fig. 1 is a flowchart illustrating an abnormal operation recognition method according to an exemplary embodiment of the present disclosure, where an execution subject of the abnormal operation recognition method may be a server that recognizes an abnormal operation.
Referring to fig. 1, an abnormal operation identification method according to one embodiment of the present disclosure includes the steps of:
step S110, responding to the medicine taking operation of the target user, and acquiring characteristic information of the target user and state information of a medical insurance card used by the target user;
step S120, acquiring the historical record times of the characteristic information of the target user in a preset time period;
step S130, if the state information of the medical insurance card is in a frozen state or the historical record times are larger than a first preset threshold value, determining that the medicine taking operation is abnormal operation;
in step S140, the medicine taking process corresponding to the medicine taking operation is terminated.
In the technical scheme provided in the embodiment shown in fig. 1, on one hand, in response to a medicine taking operation of a target user, feature information of the target user and state information of a medical insurance card used by the target user are obtained, and the number of times of history records of the feature information of the target user in a preset time period is obtained, so that the identity of the target user can be accurately verified, and abnormal behaviors such as medical insurance fraud and the like are reduced. Furthermore, if the state information of the medical insurance card is in a frozen state or the number of times of historical records is greater than a first preset threshold value, the medicine taking operation is determined to be abnormal operation, real-time monitoring on a target user can be realized, the technical problem that only a credit investigation system, a historical blacklist system and the like are used for identification in the prior art, so that the real-time performance and accuracy are poor is solved, the identification accuracy is improved, and abnormal behaviors such as medical insurance fraud and the like are avoided. On the other hand, after the abnormal operation is identified, the medicine taking process corresponding to the medicine taking operation is stopped in time, the legal rights and interests of the medical insurance personnel can be reasonably maintained, the medical insurance resources can be used on the cutting edge, the personnel with the requirements of the medical insurance can be guaranteed to obtain more sufficient medical guarantee, and the practicability of the medical insurance is improved.
The following describes the specific implementation of each step in fig. 1 in detail:
in step S110, in response to the medicine taking operation of the target user, feature information of the target user and status information of a medical insurance card used by the target user are acquired.
In an exemplary embodiment of the present disclosure, when a medicine taking operation of a target user is received, feature information of the target user may be acquired, and status information of a medical insurance card used by the target user may be acquired.
In an exemplary embodiment of the present disclosure, the target user may be a patient who visits a hospital, or a family or accompanying person of the patient, or the like. The medicine taking operation can be an operation that the target user scans the two-dimensional code on a charging bill (the charging bill provided by a charging staff after the target user pays the medicine fee before the medicine taking operation) on an operation device (such as a queuing and calling device provided with a scanning area) to carry out queuing and calling.
In an exemplary embodiment of the present disclosure, the feature information of the target user may be one or more of face information, fingerprint information, and voiceprint information of the target user. Illustratively, a face collecting device may be arranged, and then, after detecting that the target user performs the medicine taking operation, the user is prompted to perform a face brushing operation to acquire the face information of the target user. Illustratively, a fingerprint acquisition device can be further arranged to acquire fingerprint information of the target user. Illustratively, a voiceprint acquisition device can be further arranged to acquire voiceprint information of the target user. It should be noted that the manner of acquiring the feature information may be set according to actual conditions, and belongs to the protection scope of the present disclosure. By collecting the characteristic information of the target user, the identity of the target user can be effectively verified, and abnormal behaviors such as medical insurance fraud and the like are reduced.
In an exemplary embodiment of the present disclosure, the medical insurance card, i.e. the social medical insurance card, is a card dedicated to a medical insurance personal account, and stores and records the personal identification card number, name, sex, and detailed information such as the payment and consumption of the account money, etc. by using the personal identification card as an identification code. The status information of the medical insurance card may include: a normal use state and a frozen state. Illustratively, when the medical insurance card of the insured person is in normal use, the status information may be in normal use status. When the medical insurance card of the insurance personnel is lost, the insurance personnel can freeze the medical insurance card so as to convert the state information of the medical insurance card into a frozen state.
In step S120, the number of times of history of the feature information of the target user within a preset time period is acquired.
In an exemplary embodiment of the present disclosure, the number of times of history of the feature information of the target user within a preset time period (e.g., half a year) may be acquired. For example, by taking the feature information of the target user as the face information, the number of times of face brushing of the target user on the face acquisition device within half a year may be obtained as the number of times of the history. It should be noted that, the specific duration of the preset time period may be set according to actual situations, and belongs to the protection scope of the present disclosure.
In step S130, if the status information of the medical insurance card is in a frozen state or the number of times of history is greater than a first preset threshold, it is determined that the medication taking operation is an abnormal operation.
In an exemplary embodiment of the present disclosure, after the history number and the state information of the medical insurance card are acquired, if the acquired state information is in a frozen state, it may be determined that the medicine taking operation is an abnormal operation. Or, the obtained number of times of history is greater than a first preset threshold (a preset numerical value that can be numerically changed according to actual conditions, for example, 12), for example, when the number of times of history is 12 and the first preset threshold is 10, it may be determined that the number of times of history is greater than the first preset threshold, and further, it is determined that the above-mentioned medicine taking operation is an abnormal operation.
In the exemplary embodiment of the disclosure, the identity of the target user can be accurately and effectively verified based on the state information of the medical insurance card, and abnormal behaviors such as medical insurance fraud and the like are reduced.
In an exemplary embodiment of the present disclosure, reference may be made to fig. 2, fig. 2 shows a flowchart of an abnormal operation identification method in another exemplary embodiment of the present disclosure, specifically shows a flowchart of acquiring a historical medicine taking record of a target user and identifying an abnormal operation according to a disease type of a medication, and a specific implementation is explained below with reference to fig. 2.
In step S201, a history of medication taking of the target user is acquired based on the feature information of the target user.
In an exemplary embodiment of the present disclosure, a historical fetching record of the target user may be obtained based on the characteristic information of the target user, and specifically, the historical fetching record may include: the number of times of taking the medicine, the amount of the medicine taken, the type of the medicine contained in each taking of the medicine, the name of the medicine contained in each taking of the medicine, and the like.
In step S202, a disease type corresponding to a drug included in the history of drug taking is acquired.
In an exemplary embodiment of the present disclosure, after the historical medication taking record is obtained, the medications contained in the historical medication taking record may be obtained, and then, the disease types of the respective medication treatments are counted, and all the disease types are summarized.
In step S203, if the number of disease types is greater than a second preset threshold, it is determined that the medicine taking operation of the target user is an abnormal operation.
In the exemplary embodiment of the present disclosure, after the disease type of the medication is obtained, if the disease type is greater than the second preset threshold (a preset numerical value that can be numerically changed according to actual conditions, for example, 10), for example, when the disease type of the medication is obtained to be 15, it may be determined that the disease type is greater than the second preset threshold, and further, it may be determined that the medication taking operation of the target user is an abnormal operation.
In an exemplary embodiment of the present disclosure, by way of example, referring to fig. 3, fig. 3 is a schematic flowchart illustrating an abnormal operation identification method in yet another exemplary embodiment of the present disclosure, specifically illustrating a schematic flowchart of acquiring prescription information of a target user and identifying an abnormal operation according to the prescription information, and the following explains a specific implementation manner with reference to fig. 3.
In step S301, prescription information of a target user is acquired.
In an exemplary embodiment of the present disclosure, prescription information of the target user may also be acquired. Illustratively, referring to the related explanation of step S110, after receiving the medicine taking operation of the target user, the prescription information of the target user may also be received, and for example, the target user may perform a scanning operation on the prescription information prescribed by the physician in the scanning area of the operation device, so that the operation device acquires the prescription information. The prescription is a medical document which is issued by registered medical practitioners and medical assistant physicians (hereinafter referred to as doctors) for patients during diagnosis and treatment activities, is checked, allocated and checked by medical professionals (hereinafter referred to as pharmacists) who acquire the qualification of medical professional technical duties, is used as a certificate for taking medicines by patients, is the basis for allocating medicines by pharmacy staff, and has legal, technical and economic responsibilities.
In step S302, the current time is set as the current date of taking of the target medicine included in the prescription information.
In an exemplary embodiment of the present disclosure, after acquiring the prescription information, the current time may be taken as the current date of taking of the target medicine contained in the prescription information. Illustratively, the target drug may be drug a and the current date of administration may be 10 months and 20 days 2018.
In step S303, a first date of taking of the target medicine is determined from the historical record of taking medicine, and the first date of taking is a date on which the target medicine was taken the latest time from the current date of taking.
In an exemplary embodiment of the present disclosure, referring to the explanation of step S201 described above, the first taking date of the target medicine (the date on which the target medicine was taken the last time as compared with the current taking date) may be determined from the historical medicine taking record, and the first taking date on which the medicine a was acquired is, for example, 2018, 10 months and 10 days.
In step S304, the frequency of taking the target drug is determined based on the time interval between the first taking date and the current taking date.
In an exemplary embodiment of the present disclosure, after the current taking date and the first taking date are obtained, the time interval between the two may be determined to be 10 days, and further, the taking frequency of the target medicine may be determined to be once in 10 days.
In step S305, when it is detected that the frequency of taking the target medicine is greater than the standard frequency of taking the target medicine, it is determined that the medicine taking operation of the target user is an abnormal operation.
In an exemplary embodiment of the present disclosure, when it is detected that the taking frequency of the target medicine is greater than the corresponding standard taking frequency (for example, the standard taking frequency is once every 15 days), it may be determined that the taking frequency is greater than the standard taking frequency, and further, it may be determined that the medicine taking operation of the target user is an abnormal operation.
In an exemplary embodiment of the disclosure, the number of the medical insurance cards used by the target user may also be obtained based on the characteristic information of the target user, and for example, when the number of the medical insurance cards used by the target user is obtained to be 8 and is greater than a third preset threshold (a preset numerical value that can be numerically changed according to actual conditions, for example, 3), it may be determined that the medicine taking operation of the target user is an abnormal operation.
In an exemplary embodiment of the disclosure, the number of the users of the medical insurance card used by the target user in a preset time period may also be obtained, and for example, when the number of the users who have used the medical insurance card is 20 within half a year and is greater than a fourth preset threshold (a preset numerical value which can be changed according to actual conditions, for example, 5), it may be determined that the medicine taking operation of the target user is an abnormal operation.
In the exemplary embodiment of the disclosure, by identifying abnormal operations based on the characteristic information of the target user and the related information of the medical insurance card used by the target user, the target user can be monitored in real time, the technical problem of poor real-time performance and accuracy caused by identification only through a credit investigation system, a history blacklist system and the like in the prior art is solved, the identification accuracy is improved, and therefore abnormal behaviors such as medical insurance fraud and the like can be avoided.
With continued reference to fig. 1, in step S140, the medicine fetching process corresponding to the medicine fetching operation is terminated.
In an exemplary embodiment of the present disclosure, referring to the related explanation in step S130, when it is determined that the medicine taking operation of the target user is an abnormal operation, the medicine taking process corresponding to the medicine taking operation may be terminated, and for example, an alarm prompt may be sent to a medicine taking center of a hospital to prompt related medicine taking personnel to refuse to take medicine for the target user. Therefore, the legal rights of medical insurance personnel can be reasonably maintained, medical insurance resources can be used on the cutting edge, the personnel who need the medical insurance can be guaranteed to obtain more sufficient medical guarantee, and the practicability of the medical insurance is improved.
In an exemplary embodiment of the present disclosure, by way of example, referring to fig. 4, fig. 4 shows a flowchart of an abnormal operation identification method in another exemplary embodiment of the present disclosure, and specifically shows a flowchart of settling medical fees when it is identified that a medicine taking operation of a target user is not an abnormal operation. A specific embodiment is explained below with reference to fig. 4.
In step S401, if the medication taking operation is not an abnormal operation, the visit information of the target user is acquired, and the visit information includes medical expense information and medical insurance card information.
In an exemplary embodiment of the present disclosure, if it is determined that the above-mentioned medicine taking operation is not an abnormal operation, the visit information of the target user may be obtained, and further, when the target user is a visit patient, medical expense information (including hospitalization expense, medical instrument use expense, and the like) and medical insurance card information (name of a sponsor, medical insurance payment information, and the like) of the target user may be obtained.
In step S402, an interface of the medical insurance system is called, so that the medical insurance system determines the payment fee of the medical insurance according to the medical expense information and the medical insurance card information.
In an exemplary embodiment of the present disclosure, after obtaining the visit information of the target user, the medical insurance system may be caused to determine the medical insurance payment rate according to the medical expense information and the medical insurance card information. The medical insurance payment cost can be directly paid by using the medical insurance card.
In step S403, the medical insurance payment fee returned by the medical insurance system is obtained, and the self-fee is determined according to the medical fee information and the medical insurance payment fee.
In an exemplary embodiment of the present disclosure, after acquiring the medical insurance payment returned by the medical insurance system, the medical insurance payment information may be subtracted by the medical insurance payment to determine the self-payment fee of the target user.
In step S404, medical fees are settled according to the self-payment fee and the medical insurance payment fee.
In an exemplary embodiment of the present disclosure, after the self-fee and the medical insurance payment are determined, the medical fee settlement may be performed according to the self-fee and the medical insurance payment. Specifically, the medical insurance payment fee can be settled based on the interface of the medical insurance system and the medical insurance card information. The self-payment fee can be settled based on other payment platforms (such as WeChat, Payment, Unionpay) and the like.
In an exemplary embodiment of the present disclosure, for example, fig. 5 may be referred to, and fig. 5 shows an overall flow diagram of an abnormal operation identification method in an exemplary embodiment of the present disclosure, and specifically shows an interaction flow diagram of a charging terminal, a medicine taking terminal, and a medical insurance system. A specific embodiment is explained below with reference to fig. 5.
In step S501, the charging terminal performs charging;
in step S502, the medicine taking end receives a medicine taking operation of a target user;
in step S503, the prescription terminal acquires prescription information of the target user;
in step S504, the medicine taking end prompts the target user to perform a face brushing operation, and sends the acquired information to the medical insurance system;
in step S505, the medical insurance system records face brushing information, medical insurance card information, and prescription information;
in step S506, the medical insurance system queries historical data to identify the medication taking operation of the target user;
in step S507, the medical insurance system obtains the identification result and sends the identification result to the medicine taking end;
in step S508, the medicine taking end receives the identification result sent by the medical insurance system;
in step S509, the medicine fetching end determines whether the medicine fetching operation of the target user is an abnormal operation according to the recognition result;
in step S510, if the operation is abnormal, an abnormal prompt message is sent to the charging terminal, and the charging terminal performs a fee refunding operation;
in step S511, if the operation is not abnormal, the medical insurance system performs medical insurance settlement;
in step S512, the hospital settles the fee;
in step S513, the drug dispensing terminal dispenses the drug;
in step S514, the medication is taken.
The present disclosure also provides an abnormal operation recognition apparatus, and fig. 6 shows a schematic structural diagram of the abnormal operation recognition apparatus in an exemplary embodiment of the present disclosure; as shown in fig. 6, the abnormal operation identifying apparatus 600 may include a first obtaining module 601, a second obtaining module 602, an identifying module 603, and a flow suspending module 604. Wherein:
the first obtaining module 601 is configured to obtain feature information of a target user and state information of a medical insurance card used by the target user in response to a medicine taking operation of the target user.
In an exemplary embodiment of the present disclosure, the characteristic information of the target user includes at least one of: the first acquisition module is used for responding to the medicine taking operation of the target user and acquiring the characteristic information of the target user and the state information of the medical insurance card used by the target user.
A second obtaining module 602, configured to obtain the number of times of history records of the feature information of the target user in a preset time period.
In an exemplary embodiment of the disclosure, the second obtaining module is configured to obtain the number of times of history records of the feature information of the target user in a preset time period.
The identification module 603 is configured to determine that the medicine taking operation is an abnormal operation if the state information of the medical insurance card is in a frozen state or the number of times of the history is greater than a first preset threshold.
In an exemplary embodiment of the disclosure, the identification module is configured to determine that the medicine taking operation is an abnormal operation if the status information of the medical insurance card is in a frozen state or the number of times of history is greater than a first preset threshold.
In an exemplary embodiment of the present disclosure, the identification module is configured to obtain a historical medication taking record of the target user based on the characteristic information of the target user; acquiring the disease type corresponding to the medicine contained in the historical medicine taking record; and if the number of the disease types is larger than a second preset threshold value, determining that the medicine taking operation of the target user is abnormal operation.
In an exemplary embodiment of the present disclosure, the identification module is configured to obtain prescription information of a target user; taking the current time as the current taking date of the target medicine contained in the prescription information; determining a first taking date of the target medicine from the historical medicine taking record, wherein the first taking date is the date of taking the target medicine the last time from the current taking date; determining the taking frequency of the target medicine according to the time interval between the first taking date and the current taking date; and when the taking frequency of the target medicine is detected to be greater than the standard taking frequency corresponding to the target medicine, determining that the medicine taking operation of the target user is abnormal operation.
In an exemplary embodiment of the disclosure, the identification module is used for acquiring the number of medical insurance cards used by the target user based on the characteristic information of the target user; and if the number of the medical insurance cards is larger than a third preset threshold value, judging that the medicine taking operation is abnormal operation.
In an exemplary embodiment of the disclosure, the identification module is configured to obtain the number of users of the medical insurance card within the preset time period; and if the number of the users is larger than a fourth preset threshold, judging that the medicine taking operation is abnormal operation.
A flow stopping module 604, configured to stop a medicine fetching flow corresponding to the medicine fetching operation.
In an exemplary embodiment of the disclosure, the flow suspending module is configured to suspend a medicine taking flow corresponding to the medicine taking operation.
In an exemplary embodiment of the present disclosure, the flow suspending module is further configured to, if the medicine fetching operation is not an abnormal operation, obtain the medical treatment information of the target user, where the medical treatment information includes medical expense information and medical insurance card information; calling an interface of the medical insurance system to ensure that the medical insurance system determines the payment cost of medical insurance according to the medical expense information and the medical insurance card information; acquiring medical insurance payment cost returned by the medical insurance system, and determining self-payment cost according to the medical expense information and the medical insurance payment cost; and settling medical expenses according to the self-payment expense and the medical insurance payment expense.
The specific details of each module in the abnormal operation recognition apparatus have been described in detail in the corresponding abnormal operation recognition method, and therefore are not described herein again.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the "exemplary methods" section above of this specification, when the program product is run on the terminal device.
Referring to fig. 7, a program product 700 for implementing the above method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 800 according to this embodiment of the disclosure is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 8, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, and a bus 830 that couples the various system components including the memory unit 820 and the processing unit 810.
Wherein the storage unit stores program code that is executable by the processing unit 810 to cause the processing unit 810 to perform steps according to various exemplary embodiments of the present disclosure as described in the "exemplary methods" section above in this specification. For example, the processing unit 810 may perform the following as shown in fig. 1: step S110, responding to the medicine taking operation of a target user, and acquiring the characteristic information of the target user and the state information of a medical insurance card used by the target user; step S120, acquiring the historical record times of the characteristic information of the target user in a preset time period; step S130, if the state information of the medical insurance card is in a frozen state or the historical record times are larger than a first preset threshold value, determining that the medicine taking operation is abnormal operation; step S140, the medicine fetching process corresponding to the medicine fetching operation is terminated.
The storage unit 820 may include readable media in the form of volatile memory units such as a random access memory unit (RAM)8201 and/or a cache memory unit 8202, and may further include a read only memory unit (ROM) 8203.
The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 800 may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 850. Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. An abnormal operation recognition method, comprising:
responding to the medicine taking operation of a target user, and acquiring the characteristic information of the target user and the state information of a medical insurance card used by the target user;
acquiring the historical record times of the characteristic information of the target user in a preset time period;
if the state information of the medical insurance card is in a frozen state or the historical record times are greater than a first preset threshold value, determining that the medicine taking operation is abnormal operation;
and stopping the medicine taking process corresponding to the medicine taking operation.
2. The method of claim 1, wherein the feature information of the target user comprises at least one of: face information, fingerprint information, voiceprint information.
3. The method according to claim 1 or 2, characterized in that the method further comprises:
acquiring a historical medicine taking record of the target user based on the characteristic information of the target user;
acquiring the disease type corresponding to the medicine contained in the historical medicine taking record;
and if the number of the disease types is larger than a second preset threshold value, determining that the medicine taking operation of the target user is abnormal operation.
4. The method of claim 3, further comprising:
acquiring prescription information of the target user;
taking the current time as the current taking date of the target medicine contained in the prescription information;
determining a first taking date of the target medicine from the historical medicine taking record, wherein the first taking date is a date of taking the target medicine the last time the current taking date is;
determining the taking frequency of the target medicine according to the time interval between the first taking date and the current taking date;
and when the taking frequency of the target medicine is detected to be greater than the standard taking frequency corresponding to the target medicine, determining that the medicine taking operation of the target user is abnormal operation.
5. The method of claim 4, further comprising:
acquiring the number of medical insurance cards used by the target user based on the characteristic information of the target user;
and if the number of the medical insurance cards is larger than a third preset threshold value, judging that the medicine taking operation is abnormal operation.
6. The method of claim 5, further comprising:
acquiring the number of the users of the medical insurance card in the preset time period;
and if the number of the users is larger than a fourth preset threshold, judging that the medicine taking operation is abnormal operation.
7. The method of claim 1, further comprising:
if the medicine taking operation is not abnormal operation, acquiring the treatment information of the target user, wherein the treatment information comprises medical expense information and medical insurance card information;
calling an interface of a medical insurance system to enable the medical insurance system to determine medical insurance payment cost according to the medical expense information and the medical insurance card information;
acquiring medical insurance payment cost returned by the medical insurance system, and determining self-payment cost according to the medical expense information and the medical insurance payment cost;
and settling medical expenses according to the self-payment expense and the medical insurance payment expense.
8. An abnormal operation recognition apparatus, comprising:
the first acquisition module is used for responding to the medicine taking operation of a target user and acquiring the characteristic information of the target user and the state information of a medical insurance card used by the target user;
the second acquisition module is used for acquiring the historical record times of the characteristic information of the target user in a preset time period;
the identification module is used for determining that the medicine taking operation is abnormal operation if the state information of the medical insurance card is in a frozen state or the historical record times are greater than a first preset threshold value;
and the flow stopping module is used for stopping the medicine taking flow corresponding to the medicine taking operation.
9. A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the abnormal operation recognition method of any one of claims 1 to 7.
10. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the abnormal operation identification method of any one of claims 1 to 7 via execution of the executable instructions.
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