CN109658267A - Social security violation detection method, device, equipment and computer storage medium - Google Patents
Social security violation detection method, device, equipment and computer storage medium Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 108
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- 239000003814 drug Substances 0.000 claims abstract description 99
- 229940079593 drug Drugs 0.000 claims abstract description 85
- 230000002159 abnormal effect Effects 0.000 claims abstract description 59
- 230000035622 drinking Effects 0.000 claims abstract description 22
- 235000008216 herbs Nutrition 0.000 claims abstract description 22
- 230000010354 integration Effects 0.000 claims abstract description 22
- 230000033228 biological regulation Effects 0.000 claims description 18
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Abstract
The present invention provides a kind of social security violation detection method, comprising: obtains the first medical data that user settles accounts medical expenditure by social security card；By the described first medical data input deviation detection model, classified by separate-blas estimation model to the drug in the described first medical data, and calculate the accounting value of integration of drinking and medicinal herbs in drug according to classification results, determines whether the accounting value is greater than preset threshold；If the accounting value is greater than preset threshold, it is determined that the first medical data exception, and the abnormal data in the described first medical data is extracted, to provide the punishment certificate punished to the user.The present invention also provides a kind of social security violation detection device, equipment and computer storage mediums.The present invention, which is realized, is supervised user by the first medical data that social security card is settled accounts by separate-blas estimation model based on machine learning, so as to avoid manpower waste and the waste of outpatient service risk-pooling fund caused by artificial supervision, the supervisory efficiency to outpatient service risk-pooling fund is improved.
Description
Technical field
Data monitoring technical field of the present invention more particularly to a kind of social security violation detection method, device, equipment and computer
Storage medium.
Background technique
Medical insurance refers generally to basic medical insurance, due to being to compensate for labourer's economic loss caused by disease risks
The social security system established.By employing unit and personal payment, Medical Benefits Fund is established, insurant illness is just
It examines after medical expense occurs, gives certain economic compensation to it by Medical Insurance Organizations.Insured people is in designated medical organization, spy
When not being pharmacy's purchase medicine, purchase is mainly Chinese herbal medicine that is edible or nourishing, and the necessary drug of non-treatment disease violates doctor
The original intention for protecting reimbursement, is the unlawful practice that medical insurance is forbidden, great harm can be brought to medical insurance fund.
Currently, being monitored by the supervisor being equipped with to the social security behavior of insurant, the medical insurance document of settlement is carried out
It calculates, manages the expenditure of outpatient service risk-pooling fund, still, artificial supervision causes manpower to waste, and there are many China's insurant, make
It is inadequate at supervisor, so that criminal be allowed to have an opportunity to take advantage of, cause the waste of outpatient service risk-pooling fund.
Above content is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that above content is existing skill
Art.
Summary of the invention
The main purpose of the present invention is to provide the storages of a kind of social security violation detection method, device, equipment and computer to be situated between
Matter, it is intended to solve the technical issues of artificial supervision causes manpower waste and outpatient service risk-pooling fund to waste in the prior art.
To achieve the above object, the present invention provides a kind of social security violation detection method, the social security violation detection method packet
Include following steps:
Obtain the first medical data that user settles accounts medical expenditure by social security card；
By the described first medical data input deviation detection model, by separate-blas estimation model to the described first medical data
In drug classify, and according to classification results calculate drug in integration of drinking and medicinal herbs accounting value, whether determine the accounting value
Greater than preset threshold；
If the accounting value is greater than preset threshold, it is determined that the first medical data exception, and extract described first just
The abnormal data in data is examined, to provide the punishment certificate punished to the user.
Optionally, described by the described first medical data input deviation detection model, by separate-blas estimation model to described
Drug in first medical data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, determines institute
State that the step of whether accounting value is greater than preset threshold includes:
By the described first medical data input deviation detection model, by separate-blas estimation model by the described first medical data
In text data be converted into standardized field, to obtain normal data；
The normal data is detected by the Outlier Detection Algorithm based on statistics, according to testing result described in statistics
The classification of drug in normal data；
The accounting value of integration of drinking and medicinal herbs is calculated according to the classification of drug, and determines whether the accounting value is greater than preset threshold,
It is whether abnormal with the medical data of determination described first.
Optionally, described by the described first medical data input deviation detection model, it will be described by separate-blas estimation model
Text data in first medical data is converted into standardized field, and to obtain normal data the step of includes:
By the medical data input deviation detection model, medical data are cleaned by separate-blas estimation model, with
The medical data of specification after being cleaned；
Medical data configuration text feature is standardized to described, to obtain term vector, and by double in separate-blas estimation model
Sentence vector matrix is converted by term vector to RNN submodel；
The operation of attention mechanism is carried out based on the sentence vector matrix, to obtain the normal data.
Optionally, the social security violation detection method further include:
The second medical data in user preset number are obtained, and count the drug variety in the described second medical data,
To obtain statistical result；
It is calculated based on the statistical result similar between the drug variety that user buys every time in the described second medical data
Degree, and determine whether the similarity is less than default similarity；
If the similarity is less than default similarity, it is determined that the second medical data exception, and extract described second
The second abnormal data in medical data, to provide the punishment certificate punished to the user.
Optionally, if the similarity is less than default similarity, it is determined that the second medical data exception, and mention
The second abnormal data in the described second medical data is taken, includes: the step of the punishment certificate punished to the user to provide
If the similarity is less than default similarity, the second medical data Chinese medicine is calculated based on the statistical result
The variation range of kind class；
Determine the variation range whether within preset range；
If the variation range is within preset range, it is determined that the second medical data exception, and extraction is described just
The second abnormal data in data is examined, to provide the punishment certificate punished to the user.
Optionally, the social security violation detection method further include:
Default punishment rule is obtained, notice of punishment is generated based on the default punishment rule and abnormal data；
The notice of punishment and the punishment certificate are sent to customer mobile terminal.
Optionally, the social security violation detection method further include:
The history violation number of the user is obtained, and determines the numbers range where the history violation number；
The corresponding discipline rating of the numbers range is determined based on the punishment rule, and it is corresponding to obtain the discipline rating
Punishment measure；
User is punished automatically based on the punishment measure.
In addition, to achieve the above object, the present invention also provides a kind of social security violation detection device, the social security detects in violation of rules and regulations
Device includes:
Module is obtained, passes through the first medical data of social security card clearing medical expenditure for obtaining user；
Detection module is used for by the described first medical data input deviation detection model, by separate-blas estimation model to institute
The drug stated in the first medical data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, is determined
Whether the accounting value is greater than preset threshold；
Extraction module, if being greater than preset threshold for the accounting value, it is determined that the first medical data exception, and mention
The abnormal data in the described first medical data is taken, to provide the punishment certificate punished to the user.
In addition, to achieve the above object, the present invention also provides a kind of social security violation detection device, the social security detects in violation of rules and regulations
Equipment includes processor, memory and is stored on the memory and can be examined in violation of rules and regulations by the social security that the processor executes
Ranging sequence, wherein realizing when social security violation detection program is executed by the processor such as above-mentioned social security violation detection side
The step of method.
In addition, to achieve the above object, the present invention also provides a kind of computer storage medium, the computer storage medium
On be stored with social security detection program in violation of rules and regulations, wherein the social security in violation of rules and regulations realize as above-mentioned when being executed by processor by detection program
The step of social security violation detection method.
The present invention provides a kind of social security violation detection method, device, equipment and computer storage medium, and the present invention is by obtaining
The first medical data that medical expenditure is settled accounts at family by social security card are taken, then detect the described first medical data input deviation
Model classifies to the drug in the described first medical data by separate-blas estimation model, and calculates medicine according to classification results
The accounting value of integration of drinking and medicinal herbs in product, determines whether the accounting value is greater than preset threshold, presets if the last accounting value is greater than
Threshold value, it is determined that the first medical data exception, and the abnormal data in the described first medical data is extracted, to provide to institute
State the punishment certificate of user's punishment；Realize the first medical data settled accounts to user by social security card by separate-blas estimation model
It is supervised, so as to avoid manpower waste and the waste of outpatient service risk-pooling fund caused by artificial supervision, improves and unite to outpatient service
Raise the supervisory efficiency of fund.
Detailed description of the invention
Fig. 1 is the hardware structural diagram for the social security violation detection device that various embodiments of the present invention are related to；
Fig. 2 is the flow diagram of social security violation detection method first embodiment of the present invention；
Fig. 3 is the flow diagram of social security violation detection method second embodiment of the present invention；
Fig. 4 is the flow diagram of social security violation detection method 3rd embodiment of the present invention；
Fig. 5 is the flow diagram of social security violation detection method fourth embodiment of the present invention；
Fig. 6 is the flow diagram of the 5th embodiment of social security violation detection method of the present invention；
Fig. 7 is the flow diagram of social security violation detection method sixth embodiment of the present invention；
Fig. 8 is the flow diagram of the 7th embodiment of social security violation detection method of the present invention；
Fig. 9 is the functional block diagram of social security violation detection device first embodiment of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present embodiments relate to social security violation detection method be mainly used in social security violation detection device, which disobeys
Rule detection device, which can be PC (personal computer personal computer), portable computer, mobile terminal etc., has display
With the equipment of processing function.
Referring to Fig.1, Fig. 1 is the hardware configuration signal of social security violation detection device involved in the embodiment of the present invention
Figure.In the embodiment of the present invention, social security violation detection device may include (such as the central processing unit Central of processor 1001
Processing Unit, CPU), communication bus 1002, user interface 1003, network interface 1004, memory 1005.Wherein,
Communication bus 1002 is for realizing the connection communication between these components；User interface 1003 may include display screen
(Display), input unit such as keyboard (Keyboard)；Network interface 1004 optionally may include that the wired of standard connects
Mouth, wireless interface (such as WI-FI interface)；Memory 1005 can be high speed RAM memory, be also possible to stable memory
(non-volatile memory), such as magnetic disk storage, memory 1005 optionally can also be independently of aforementioned processor
1001 storage device.It will be understood by those skilled in the art that hardware configuration shown in Fig. 1 is not constituted to limit of the invention
It is fixed, it may include perhaps combining certain components or different component layouts than illustrating more or fewer components.
With continued reference to Fig. 1, the memory 1005 in Fig. 1 as a kind of computer storage medium may include operating system,
Network communication module and social security detect program in violation of rules and regulations.In Fig. 1, network communication module is mainly used for connecting server, with clothes
Business device carries out data communication；And processor 1001 can call the social security stored in memory 1005 detection program in violation of rules and regulations, and hold
Row social security violation detection method provided in an embodiment of the present invention.
The present invention further provides a kind of social security violation detection methods.Referring to Fig. 2, Fig. 2 is that social security of the present invention detects in violation of rules and regulations
The method schematic diagram of method first embodiment.
In the present embodiment, the executing subject of social security violation detection method of the present invention is people society core system, the people society core
Feel concerned about system include equipment violation detection device, people society core system be able to detect integration of drinking and medicinal herbs in medical data accounting value whether
Greater than preset threshold, if more than then medical data exception, and the abnormal data in the medical data of extraction, to filter out not
Meet abnormal data as defined in medical insurance, and using the abnormal data as the punishment certificate punished to user.
The social security violation detection method includes:
Step S10 obtains the first medical data that user settles accounts medical expenditure by social security card；
In the present embodiment, insurant is settled accounts in designated medical organization (for example, hospital, pharmacy) using social security card
When, the terminal device of designated medical organization generates prescription list according to prescription information, insured people's information and cost details etc., will
The prescription list is uploaded to people society core system, and people society core system receives the prescription that the terminal device of designated medical organization is sent
It is single, the first medical data in prescription list are obtained, are detected in violation of rules and regulations with carrying out social security to the first medical data, wherein first is medical
Data include consultation time, medical medical institutions' title or code, insured people's information, prescription information and cost details etc.,
Wherein, insured people's information includes the identity information of insured people, insured people's social security card information etc., and the identity information of insured people includes year
Age, identification card number, weight, height etc., prescription information include medicine information, drug usage (for example, oral, once a day), medicine
Product prescription time etc., the medicine information include nomenclature of drug, specification, unit, quantity etc..
Step S20, by the described first medical data input deviation detection model, by separate-blas estimation model to described first
Drug in medical data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, is accounted for described in determination
Whether ratio is greater than preset threshold；
In the present embodiment, which can use cluster, sequence variation, nearest-neighbors method, multidimensional data
The first medical data are analyzed in analysis etc., whether to be extremely able to detect the first medical data by separate-blas estimation model, tool
Body, the first medical data got are cleaned by separate-blas estimation model first, cleaning refers to the first medical number
Text data in carries out word segmentation processing, and there are some unnecessary data or nonstandard numbers in the first medical data
According to, not only indicating word itself but also can be considered semantic distance requirement under, utilize the RNN submodeling analysis in separate-blas estimation model
Longer more complicated content of text carries out word segmentation processing to the first medical data, for example, a Chinese sentence, between word all
It is continuous, and the minimum unit granularity of data analysis is word, so need to carry out word segmentation processing, and for English text
Sentence, the minimum unit of English sentence are words, are separated between word by space, meanwhile, it needs to be labeled part of speech,
For example, noun, from word, adjective, numeral-classifier compound etc., the purpose of part-of-speech tagging be in order to allow sentence below processing in incorporate more
More useful language messages for some text-processing tasks, can not have to part-of-speech tagging certainly.
Further, stop words can also be removed, stop words is exactly the word for not having any contribution function to text feature,
For example, eh, punctuation mark etc., need to get rid of these stop words when carrying out text analyzing, certainly, for different
Using the word that parameter removal regulation part of speech can be arranged in separate-blas estimation model.
Further, after carrying out cleaning operation to the first medical data, to the first medical data configuration text after cleaning
Feature indicates text with the sequence of a vector, and word word vector is indicated, splicing is calculated and inversely calculated by forward direction
Complete term vector is obtained, the sequence of term vector is obtained, the use of two-way RNN model is then one by term vector coding (conversion)
Sentence vector matrix, distich subvector matrix carry out attention mechanism, obtain final normal data.
Further, some drugs are edible or nourish, and the necessary drug of non-treatment disease violates medical insurance reimbursement
Original intention is the unlawful practice that medical insurance is forbidden, classified using the classifier in separate-blas estimation model to normal data, the classification
Refer to that the drug in medical data, which is divided into treatment disease, drug and to nourish drug, according in classifier based on statistics
Outlier Detection Algorithm detects normal data, counts the classification of drug in medical data, and calculates the accounting of integration of drinking and medicinal herbs
Value, which refers to the ratio of the total drug of drug Zhan that is edible or nourishing, for example, if a total of 10 kinds of Chinese herbal medicine,
The Chinese herbal medicine that can be nourished has 8 kinds, then the accounting value is 80 percent, and determines whether the accounting value is greater than preset threshold, when
So, which is also possible to the ratio of the dosage of edible or drug of nourishing dosage and total drug.
Step S30, if the accounting value is greater than preset threshold, it is determined that the first medical data exception, and extract institute
The abnormal data in the first medical data is stated, to provide the punishment certificate punished to the user.
In the present embodiment, if detecting, the accounting value of integration of drinking and medicinal herbs in drug is greater than preset threshold, it is believed that medical data
In it is edible or the drug nourished excessive, it is determined that the first medical data exist abnormal, then are mentioned according to separate-blas estimation model
The abnormal data in the first medical data is taken, and generates punishment certificate, which includes the title for punishing object, punishes and arrange
Apply, punish reason, punishment mechanism, penalty minutes etc..The abnormal data can be used as user and utilize social security card violation operation
Evidence.
The social security violation detection method that the present embodiment proposes, by obtaining user by the of social security card clearing medical expenditure
One medical data, then by the described first medical data input deviation detection model, by separate-blas estimation model to described first
Drug in medical data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, is accounted for described in determination
Whether ratio is greater than preset threshold, if the last accounting value is greater than preset threshold, it is determined that the first medical data exception,
And the abnormal data in the described first medical data is extracted, to provide the punishment certificate punished to the user；It realizes and passes through
Separate-blas estimation model supervises user by the first medical data that social security card is settled accounts, and causes so as to avoid artificial supervision
Manpower waste and outpatient service risk-pooling fund waste, improve the supervisory efficiency to outpatient service risk-pooling fund.
Based on first embodiment, the second embodiment of social security violation detection method of the present invention is proposed, referring to Fig. 3, this implementation
In example, step S20 includes:
Step S21, by the described first medical data input deviation detection model, by separate-blas estimation model by described first
Text data in medical data is converted into standardized field, to obtain normal data；
In the present embodiment, which can use cluster, sequence variation, nearest-neighbors method, multidimensional data
The first medical data are analyzed in analysis etc., are able to detect integration of drinking and medicinal herbs in the first medical data by separate-blas estimation model
Accounting value specifically first cleans the first medical data got by separate-blas estimation model, the first medical data
In there are some unnecessary data or nonstandard data, by being cleaned to obtain normal data to these data.
Step S22 detects the normal data by the Outlier Detection Algorithm based on statistics, according to testing result
Count the classification of drug in the normal data；
In the present embodiment, it is detected according to the Outlier Detection Algorithm in the classifier of separate-blas estimation model based on statistics medical
Abnormal data in data, specifically, the Outlier Detection Algorithm based on statistics first can be with data points in SS data
Distribution obtains " the completely collection " for being free of outlier, and then basis " should completely collect " to remaining other data points gradually
Outliers Detection is carried out, statistics is then according to the distribution of data point come the classification of drug in SS data according to testing result.
Step S23 calculates the accounting value of integration of drinking and medicinal herbs according to the classification of drug, and it is pre- to determine whether the accounting value is greater than
It is whether abnormal with the medical data of determination described first if threshold value.
In the present embodiment, which refers to the ratio of the total drug of drug Zhan that is edible or nourishing, for example, if
A total of 10 kinds of Chinese herbal medicine, the Chinese herbal medicine that can be nourished has 8 kinds, then the accounting value is 80 percent, and determines that the accounting value is
No to be greater than preset threshold, certainly, which is also possible to the ratio of the dosage of edible or drug of nourishing dosage and total drug
Value.It is whether abnormal that the first medical data are detected according to accounting value, if accounting value is greater than preset threshold, the first medical data are different
Often, if accounting value is less than preset threshold, the first medical data are without exception.
The social security violation detection method that the present embodiment proposes, by the way that the described first medical data input deviation is detected mould
Type converts standardized field for the text data in the described first medical data by separate-blas estimation model, to be marked
Then quasi- data detect the normal data by the Outlier Detection Algorithm based on statistics, count according to testing result
The classification of drug in the normal data finally calculates the accounting value of integration of drinking and medicinal herbs according to the classification of drug, and accounts for described in determination
Whether whether ratio is greater than preset threshold, abnormal with the medical data of determination described first；It realizes through separate-blas estimation model pair
Medical data are detected, and whether the accounting value for calculating integration of drinking and medicinal herbs in medical data is greater than preset threshold, determine medical data
It is whether abnormal, so as to detect abnormal data automatically, avoid manpower waste caused by manually avoiding artificial supervision and
The waste of outpatient service risk-pooling fund improves the supervisory efficiency to outpatient service risk-pooling fund.
Based on second embodiment, the 3rd embodiment of social security violation detection method of the present invention is proposed, referring to Fig. 4, this implementation
In example, step S21 includes:
Step S211, by the medical data input deviation detection model, by separate-blas estimation model to medical data into
Row cleaning, with the medical data of specification after clean；
In the present embodiment, which can use cluster, sequence variation, nearest-neighbors
Method, multidimensional data analysis etc. analyze medical data, whether to be extremely able to detect medical data by separate-blas estimation model,
Specifically, the medical data got are cleaned by separate-blas estimation model first, cleaning is exactly in medical data
Circumferential edge carries out word segmentation processing, and there are some unnecessary data or nonstandard data in data of going to a doctor, and is both indicating
Word itself is can be considered again under the requirement of semantic distance, using the longer more complicated content of text of RNN model analysis, to medical number
According to word segmentation processing is carried out, the medical data of specification are obtained by word segmentation processing, are all to connect between word for example, a Chinese sentence
Continuous, and the minimum unit granularity of data analysis is word, so need to carry out word segmentation processing, and for the sentence of English text
Son, the minimum unit of English sentence are words, are separated between word by space, meanwhile, it needs to be labeled part of speech, example
Such as, noun, from word, adjective, numeral-classifier compound etc., the purpose of part-of-speech tagging is to allow sentence to incorporate in processing below more
Useful language message for some text-processing tasks, part-of-speech tagging can not had to certainly.
Further, stop words can also be removed, stop words is exactly the word for not having any contribution function to text feature,
For example, eh, punctuation mark etc., need to get rid of these stop words when carrying out text analyzing, certainly, for different
Using the word that parameter removal regulation part of speech can be arranged in separate-blas estimation model.
Step S212 standardizes medical data configuration text feature to described, to obtain term vector, and passes through separate-blas estimation mould
Term vector is converted sentence vector matrix by two-way RNN submodel in type；
In the present embodiment, after carrying out cleaning operation to medical data, to the medical data configuration text feature after cleaning,
Text is indicated with the sequence of a vector, word word vector is indicated, is calculated by forward direction and reverse calculating splicing obtains
Complete term vector obtains the sequence of term vector, is then compiled term vector using the two-way RNN submodel in separate-blas estimation model
Code (conversion) is a sentence vector matrix, and distich subvector matrix carries out attention mechanism, obtains final normal data.
Step S213 carries out the operation of attention mechanism based on the sentence vector matrix, to obtain the normal data.
In the present embodiment, in the present embodiment, distich subvector matrix carries out attention mechanism, will be in step S212
One vector of sentence vector matrix boil down to indicates that the feedforward neural network being sent into separate-blas estimation model is predicted, inputs
One matrix exports a vector, a context vector is extracted from input content, the context vector of the mechanism is to be worked as
The parameter learning for making model obtains.This makes attention mechanism become a pure squeeze operation, can replace any pond
Step.Content of text is compressed into after a vector, obtains final normal data, for example, a kind of class label, a reality
Numerical value etc..
The social security violation detection method that the present embodiment proposes, by leading to the medical data input deviation detection model
It crosses separate-blas estimation model to clean medical data, be gone to a doctor data with the specification after being cleaned, then just to the specification
Data configuration text feature is examined, to obtain term vector, and is turned term vector by the two-way RNN submodel in separate-blas estimation model
Sentence vector matrix is turned to, the operation of attention mechanism is finally carried out based on the sentence vector matrix, to obtain the criterion numeral
According to；It realizes and normal data is converted for medical data by separate-blas estimation model, thus be conducive to the detection of abnormal data, into
And improve the correctness of anomaly data detection.
Based on first embodiment, the fourth embodiment of social security violation detection method of the present invention is proposed, referring to Fig. 5, this implementation
In example, the social security violation detection method further include:
Step S40 obtains the second medical data in user preset number, and counts the medicine in the described second medical data
Kind class, to obtain statistical result；
In the present embodiment, the patient of certain class illness is typically belonged to when buying drug, and there is no too big for drug variety
Difference, if there are violation operations by the patient when abnormal to user's purchase medicament categories variation by model inspection
Behavior, so, it can be with the second medical data in counting user preset times, according in the medical data of separate-blas estimation modeling statistics
Each drug variety, the preset times are set by technical staff, can be twice, it is three inferior, can be with for example, statistics
User twice in succession in medical data, statistics obtain user for the first time go to a doctor data in six kinds including A, B, C, D, E and F etc.
Chinese medicine includes tetra- kinds of Chinese medicines of B, C, D and E in the second medical data.
Step S50 calculates the drug variety that user buys every time in the described second medical data based on the statistical result
Between similarity, and determine whether the similarity is less than default similarity；
In the present embodiment, user is in preset times when drug purchase, if all there is no becoming for the type of drug every time
To change, then the similarity in the second medical data is a hundred percent, if buy different types of drug in user preset number,
Similarity is calculated according to the drug variety bought every time, and determines whether the similarity is greater than preset threshold, which can be with
It is decimal, score, percentage etc., which is configured by technical staff according to social security regulation, for example, statistics is used
Family is gone to a doctor in data six kinds of Chinese medicine such as including A, B, C, D, E and F for the first time, including B, C, D and E tetra- in the second medical data
Kind Chinese medicine, then total Chinese medicine number of species are 6, and identical drug variety is 4 kinds, then calculating similarity is 2/3, if be calculated
Similarity is greater than preset threshold, then the therapeutic regimen in the data that illustrate to go to a doctor twice is similar therapeutic regimen, if user is twice
Therapeutic regimen in similarity be less than preset threshold when, then it is assumed that user buy drug type variation it is excessive.
Step S60, if the similarity is less than default similarity, it is determined that the second medical data exception, and extract
The second abnormal data in the second medical data, to provide the punishment certificate punished to the user.
In the present embodiment, if the similarity being calculated is greater than preset threshold, the use in the data that illustrate to go to a doctor twice
Prescription case is similar therapeutic regimen, then the second medical data are without abnormal, if similarity is small in the therapeutic regimen of user twice
When preset threshold, then it is assumed that the type variation that user buys drug is excessive, then the second medical data exception, and by inclined
Poor detection model extracts the second abnormal data in the second medical data, using second abnormal data as the punishment of punishment user
It proves.
The social security violation detection method that the present embodiment proposes, by obtaining the second medical data in user preset number,
And the drug variety in the described second medical data is counted, to obtain statistical result, it is then based on the statistical result and calculates institute
The similarity between the drug variety that user buys every time in the second medical data is stated, and it is default to determine whether the similarity is less than
Similarity, if the last similarity is less than default similarity, it is determined that the second medical data exception, and extract described the
The second abnormal data in two medical data, to provide the punishment certificate punished to the user；It realizes medical according to calculating
Whether the similarity of data is abnormal to determine medical data, to extract abnormal data, and then can automatically detect out abnormal number
According to avoiding manpower waste and the waste of outpatient service risk-pooling fund caused by manually avoiding artificial supervision, improve and unite to outpatient service
Raise the supervisory efficiency of fund.
Based on fourth embodiment, the 5th embodiment of social security violation detection method of the present invention is proposed, referring to Fig. 6, this implementation
In example, step S60 includes:
It is medical to calculate described second based on the statistical result if the similarity is less than default similarity by step S61
The variation range of data herbal species class；
In the present embodiment, the patient of certain class illness is typically belonged to when buying drug, and there is no too big for drug variety
Difference, if there are violation operations by the patient when abnormal to user's purchase medicament categories variation by model inspection
Behavior, so, the variation range of drug variety can also be calculated according to statistical result, for example, the kind of this purchase drug of user
Class has six kinds, and there are five types of the drugs of last time purchase, then the drug variety of last purchase has 7 kinds, then the medicine that user buys three times
Product category is -1 to 1.It is of course also possible to calculate the changing value of the second medical data herbal species class, for example, user this
The type of purchase drug has six kinds, and there are five types of the drugs of last time purchase, then the variation of user's drug variety of drug purchase twice
Value is 1.
Whether step S62 determines the variation range within preset range；
In the present embodiment, which is configured by technical staff, by the variation range being calculated or change
Whether change value is compared with preset range, determine the variation range or changing value within default variation range.
Step S63, if the variation range is within preset range, it is determined that the second medical data exception, and mention
The second abnormal data in the medical data is taken, to provide the punishment certificate punished to the user.
In the present embodiment, if calculating getable variation range or changing value not within default variation range,
Illustrate that the type amplitude of variation of user's drug purchase is larger, then the second medical data exception, just according to separate-blas estimation model extraction
The second abnormal data in data is examined, using second abnormal data as the punishment certificate of punishment user.
The social security violation detection method that the present embodiment proposes is based on if being less than default similarity by the similarity
The statistical result calculates the variation range of the described second medical data herbal species class, whether then determines the variation range
Within preset range, if the last variation range is within preset range, it is determined that the second medical data exception, and
The second abnormal data in the medical data is extracted, to provide the punishment certificate punished to the user；It realizes according to
Whether the variation range of two medical data herbal species classes is abnormal to determine medical data, so that abnormal data is extracted, Jin Erneng
It is enough to detect abnormal data automatically, avoid the wave of manpower waste and outpatient service risk-pooling fund caused by manually avoiding artificial supervision
Take, improves the supervisory efficiency to outpatient service risk-pooling fund.
Based on first embodiment, the sixth embodiment of social security violation detection method of the present invention is proposed, referring to Fig. 7, this implementation
In example, the social security violation detection method further include:
Step S70 obtains default punishment rule, generates notice of punishment based on the default punishment rule and abnormal data；
In the present embodiment, if detecting, there are abnormal datas in medical data, search default punishment in the database
Rule, and rule of punishing is then according to this and abnormal data generates notice of punishment, which is set by technical staff, at this
Penalizing notice includes title, punishment measure, punishment reason, punishment mechanism, penalty minutes of punishment object etc..
The notice of punishment and the punishment certificate are sent to customer mobile terminal by step S80.
In the present embodiment, notice of punishment is sent to mobile terminal by people society core system, and automatically to user at
It penalizes, wherein the degree of punitive measures can also be determined with the number of counting user preset time period violation operation, for example, warning,
Fine, cancellation medical insurance card etc., alternatively, can carry out related prompt when detecting that user has the pre- behavior of violation, pre- behavior is
Refer to the behavior for buying drug user's next time according to the behavioural analysis prediction of the purchase drug of user, reminding method can be short message and mention
Show, Advise By Wire or wechat message notifying etc..
The social security violation detection method that the present embodiment proposes is based on the default punishment by obtaining default punishment rule
Rule and abnormal data generate notice of punishment, and it is mobile eventually that the notice of punishment and the punishment certificate are then sent to user
End；Realize detect user go to a doctor data deposit when abnormal, user is punished automatically, so as to avoid manually avoiding
The waste of manpower caused by artificial supervision and the waste of outpatient service risk-pooling fund, improve the supervisory efficiency to outpatient service risk-pooling fund.
Based on sixth embodiment, the 7th embodiment of social security violation detection method of the present invention is proposed, referring to Fig. 8, this implementation
In example, the social security violation detection method further include:
Step S90 obtains the history violation number of the user, and determines number model where the history violation number
It encloses；
In the present embodiment, people society core system can go to a doctor data according to the history for obtaining user, and according to user's
The history violation number of the medical data statistics user of history, different violation numbers corresponds to different punishment etc. in punishment rule
Grade, so, it is first determined user's history violation number numbers range corresponding in punishment rule, according to the number model
Enclose the discipline rating of determining user.
Step S100 determines the corresponding discipline rating of the numbers range based on the punishment rule, and obtains described disobey
Advise the corresponding punishment measure of grade；
In the present embodiment, when history violation number is in different numbers ranges, corresponding discipline rating is different, according to
Punishment rule determines the numbers range where history violation number, and the corresponding punishment measure of determined number range, for example, at this
The first estate, the second grade, tertiary gradient etc. can be divided by penalizing grade, and the first estate, which corresponds to punishment measure and can be warning, to be mentioned
Show, the corresponding punishment measure of the second grade, which can be, carries out certain amount of money fine, and the corresponding punishment measure of the tertiary gradient can be
Medical insurance card etc. is nullified, of course, it is possible to carry out different gold to user according to numbers range different where user's history violation number
The fine of volume.
Step S110 automatically punishes user based on the punishment measure.
In the present embodiment, people society core system automatically punishes user according to punishment rule, for example, people society core
The contact method of the available user of system, which can be wechat, phone, mail etc., by warning prompt with wechat
The modes such as message, mail, short message are sent to user, alternatively, people society core system can directly with user's wechat, Alipay or
Bank card binding directly deducts corresponding fine according to punishment rule, alternatively, people society from user's wechat, Alipay, bank card
Core system directly can be with logging off users medical insurance card.
The social security violation detection method that the present embodiment proposes by obtaining the history violation number of the user, and determines
Numbers range where the history violation number is then based on the punishment rule and determines the corresponding violation of the numbers range
Grade, and the corresponding punishment measure of the discipline rating is obtained, finally user is punished automatically based on the punishment measure；
It realizes and different punishment measures is carried out to user according to the history violation number of user is improved to be punished automatically
To the supervisory efficiency of outpatient service risk-pooling fund.
In addition, the embodiment of the present invention also provides a kind of social security violation detection device.
It is the functional block diagram of social security violation detection device first embodiment of the present invention referring to Fig. 9, Fig. 9.
Social security violation detection device of the present invention is virtual bench, is stored in the storage of the detection device of social security violation shown in Fig. 1
In device 1005, the institute for realizing social security detection program in violation of rules and regulations is functional: obtaining user and passes through social security card clearing medical expenditure
First medical data；By the described first medical data input deviation detection model, by separate-blas estimation model to described first just
The drug examined in data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, determines the accounting
Whether value is greater than preset threshold；If the accounting value is greater than preset threshold, it is determined that the first medical data exception, and extract
Abnormal data in the first medical data, to provide the punishment certificate punished to the user.
Specifically, in the present embodiment, the social security violation detection device includes:
Module 101 is obtained, the first medical data that user settles accounts medical expenditure by social security card are obtained；
Detection module 102, by the described first medical data input deviation detection model, by separate-blas estimation model to described
Drug in first medical data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, determines institute
State whether accounting value is greater than preset threshold；
Extraction module 103, if the accounting value is greater than preset threshold, it is determined that the first medical data exception, and mention
The abnormal data in the described first medical data is taken, to provide the punishment certificate punished to the user.
Further, the detection module 102 is also used to:
By the described first medical data input deviation detection model, by separate-blas estimation model by the described first medical data
In text data be converted into standardized field, to obtain normal data；
The normal data is detected by the Outlier Detection Algorithm based on statistics, according to testing result described in statistics
The classification of drug in normal data；
The accounting value of integration of drinking and medicinal herbs is calculated according to the classification of drug, and determines whether the accounting value is greater than preset threshold,
It is whether abnormal with the medical data of determination described first.
Further, the detection module 102 is also used to:
By the medical data input deviation detection model, medical data are cleaned by separate-blas estimation model, with
The medical data of specification after being cleaned；
Medical data configuration text feature is standardized to described, to obtain term vector, and by double in separate-blas estimation model
Sentence vector matrix is converted by term vector to RNN submodel；
The operation of attention mechanism is carried out based on the sentence vector matrix, to obtain the normal data.
Further, the social security violation detection device further include:
Module is obtained, for obtaining the second medical data in user preset number, and counts the described second medical data
In drug variety, to obtain statistical result；
Computing module, for calculating the drug that user buys every time in the described second medical data based on the statistical result
Similarity between type, and determine whether the similarity is less than default similarity；
Extraction module, if being less than default similarity for the similarity, it is determined that the second medical data exception, and
The second abnormal data in the described second medical data is extracted, to provide the punishment certificate punished to the user.
Further, the social security violation detection device further include:
Computing module calculates described the based on the statistical result if being less than default similarity for the similarity
The variation range of two medical data herbal species classes；
Judgment module, for determining the variation range whether within preset range；
Extraction module, if for the variation range within preset range, it is determined that the second medical data exception,
And the second abnormal data in the medical data is extracted, to provide the punishment certificate punished to the user.
Further, the social security violation detection device further include:
Generation module generates punishment based on the default punishment rule and abnormal data for obtaining default punishment rule
Notice；
Sending module, for the notice of punishment and the punishment certificate to be sent to customer mobile terminal.
Further, the social security violation detection device further include:
Module is obtained, for obtaining the history violation number of the user, and where the determining history violation number
Numbers range；
The corresponding discipline rating of the numbers range is determined based on the punishment rule, and it is corresponding to obtain the discipline rating
Punishment measure；
Module is punished, for punishing automatically to user based on the punishment measure.
In addition, the embodiment of the present invention also provides a kind of computer storage medium.
Social security detection program in violation of rules and regulations is stored in computer storage medium of the present invention, wherein the social security detects program in violation of rules and regulations
When being executed by processor, realize such as the step of above-mentioned social security violation detection method.
Wherein, social security violation detection program, which is performed realized method, can refer to social security violation detection method of the present invention
Each embodiment, details are not described herein again.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone,
Computer, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of social security violation detection method, which is characterized in that detection method includes the following steps in violation of rules and regulations for the social security:
Obtain the first medical data that user settles accounts medical expenditure by social security card；
By the described first medical data input deviation detection model, by separate-blas estimation model in the described first medical data
Drug is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, determines whether the accounting value is greater than
Preset threshold；
If the accounting value is greater than preset threshold, it is determined that the first medical data exception, and extract the described first medical number
Abnormal data in, to provide the punishment certificate punished to the user.
2. social security violation detection method as described in claim 1, which is characterized in that described to input the described first medical data
Separate-blas estimation model classifies to the drug in the described first medical data by separate-blas estimation model, and is tied according to classification
Fruit calculates the accounting value of integration of drinking and medicinal herbs in drug, determines that the step of whether the accounting value is greater than preset threshold includes:
It, will be in the described first medical data by separate-blas estimation model by the described first medical data input deviation detection model
Text data is converted into standardized field, to obtain normal data；
The normal data is detected by the Outlier Detection Algorithm based on statistics, counts the standard according to testing result
The classification of drug in data；
The accounting value of integration of drinking and medicinal herbs is calculated according to the classification of drug, and determines whether the accounting value is greater than preset threshold, with true
Whether the fixed first medical data are abnormal.
3. social security violation detection method as claimed in claim 2, which is characterized in that described to input the described first medical data
Separate-blas estimation model converts standardized word for the text data in the described first medical data by separate-blas estimation model
Section, to obtain normal data the step of include:
By separate-blas estimation model medical data are cleaned, the medical data input deviation detection model with to obtain
The medical data of specification after cleaning；
Medical data configuration text feature is standardized to described, to obtain term vector, and passes through the two-way RNN in separate-blas estimation model
Term vector is converted sentence vector matrix by submodel；
The operation of attention mechanism is carried out based on the sentence vector matrix, to obtain the normal data.
4. social security violation detection method as described in claim 1, which is characterized in that the social security violation detection method is also wrapped
It includes:
The second medical data in user preset number are obtained, and count the drug variety in the described second medical data, with
To statistical result；
The similarity between the drug variety that user buys every time in the described second medical data is calculated based on the statistical result, and
Determine whether the similarity is less than default similarity；
If the similarity is less than default similarity, it is determined that the second medical data exception, and it is medical to extract described second
The second abnormal data in data, to provide the punishment certificate punished to the user.
5. social security violation detection method as claimed in claim 4, which is characterized in that if the similarity is less than default phase
Like degree, it is determined that the second medical data exception, and the second abnormal data in the described second medical data is extracted, to provide
To the user punishment punishment certificate the step of include:
If the similarity is less than default similarity, the second medical data herbal species are calculated based on the statistical result
The variation range of class；
Determine the variation range whether within preset range；
If the variation range is within preset range, it is determined that the second medical data exception, and extract the medical number
The second abnormal data in, to provide the punishment certificate punished to the user.
6. social security violation detection method as described in claim 1, which is characterized in that the social security violation detection method is also wrapped
It includes:
Default punishment rule is obtained, notice of punishment is generated based on the default punishment rule and abnormal data；
The notice of punishment and the punishment certificate are sent to customer mobile terminal.
7. social security violation detection method as claimed in claim 6, which is characterized in that the social security violation detection method is also wrapped
It includes:
The history violation number of the user is obtained, and determines the numbers range where the history violation number；
The corresponding discipline rating of the numbers range is determined based on the punishment rule, and obtains the corresponding place of the discipline rating
Penalize measure；
User is punished automatically based on the punishment measure.
8. a kind of social security violation detection device, which is characterized in that the social security violation detection device includes:
Module is obtained, passes through the first medical data of social security card clearing medical expenditure for obtaining user；
Detection module, for by the described first medical data input deviation detection model, by separate-blas estimation model to described the
Drug in one medical data is classified, and the accounting value of integration of drinking and medicinal herbs in drug is calculated according to classification results, described in determination
Whether accounting value is greater than preset threshold；
Extraction module, if being greater than preset threshold for the accounting value, it is determined that the first medical data exception, and extract institute
The abnormal data in the first medical data is stated, to provide the punishment certificate punished to the user.
9. a kind of social security violation detection device, which is characterized in that the social security violation detection device include processor, memory,
And be stored on the memory and program can be detected by the social security that the processor executes in violation of rules and regulations, wherein the social security is in violation of rules and regulations
When detection program is executed by the processor, realizing the social security violation detection method as described in any one of claims 1 to 7
Step.
10. a kind of computer storage medium, which is characterized in that credit evaluation program is stored in the computer storage medium,
When wherein the social security violation detection program is executed by processor, realize that the social security as described in any one of claims 1 to 7 is disobeyed
The step of advising detection method.
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