CN109544363A - Medical supervision method, apparatus, terminal and medium based on data visualization - Google Patents
Medical supervision method, apparatus, terminal and medium based on data visualization Download PDFInfo
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- CN109544363A CN109544363A CN201811265085.0A CN201811265085A CN109544363A CN 109544363 A CN109544363 A CN 109544363A CN 201811265085 A CN201811265085 A CN 201811265085A CN 109544363 A CN109544363 A CN 109544363A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The embodiment of the invention discloses a kind of medical supervision method, apparatus and server based on data visualization, wherein, this method comprises: obtaining the risk-pooling fund data that target handles area, the risk-pooling fund data in area are handled according to target, determine that target handles the risk-pooling fund monitoring index data in area, the risk-pooling fund monitoring index includes risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, risk-pooling fund expenditure and at least one in the ratio of medical expense；According to the corresponding relationship of risk-pooling fund monitoring index data and intensity of anomaly, determine that target handles the intensity of anomaly of the risk-pooling fund data in area；According to the corresponding relationship of intensity of anomaly and exhibition method, determine that target handles the intended display mode of the risk-pooling fund data in area；It is shown according to the risk-pooling fund data that intended display mode handles area to target.By implementing the above method, the abnormal conditions of risk-pooling fund expenditure can be automatically detected, medical supervision efficiency is promoted.
Description
Technical field
This application involves medical insurance technical field more particularly to a kind of medical supervision method based on data visualization,
Device, terminal and medium.
Background technique
Medical insurance risk-pooling fund refers to that certain is handled in the hospitalization premiums that all employing units, area pay for worker, deducts
Rest part after being divided into personal account.Medical insurance risk-pooling fund belongs to all insurants, by social insurance handling institution
Centralized management, unified adjust use, and are mainly used for paying medical fee, the Operation Fee, nurse fees, Basic examination that insured employees occur
Take.In medical security social system, medical procedure will use a large amount of drug, while the quantity that adjoint inspection checks
It is very huge and many kinds of.Therefore there may be fabricating false medical information, using the loophole of medical insurance processing system with
The case where seeking illegitimate benefits, these behaviors have seriously affected the balance between revenue and expenditure of medical insurance risk-pooling fund, have encroached on insured
The interests of people.
In existing processing mode, usually by manually being supervised to each medical insurance risk-pooling fund for handling area
It surveys.But labor intensity is very big, data-handling efficiency is low, and is easy to appear calculating mistake, influences the accurate of monitoring
Property.
Summary of the invention
The embodiment of the present application provides a kind of medical supervision method, apparatus, terminal and medium based on data visualization, can be with
The abnormal conditions of risk-pooling fund expenditure are automatically detected, medical supervision efficiency is promoted.
In a first aspect, the embodiment of the invention provides a kind of medical supervision method based on data visualization, the method
Include:
The risk-pooling fund data that target handles area are obtained, it includes at least one medical institutions under area that the target, which is handled,；
The risk-pooling fund data that area is handled according to the target determine that the target handles the risk-pooling fund monitoring index in area
Data, the risk-pooling fund monitoring index include risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, risk-pooling fund expenditure and doctor
At least one of in the ratio for the treatment of expense；
According to the corresponding relationship of the risk-pooling fund monitoring index data and intensity of anomaly, determine that the target handles area
The intensity of anomaly of risk-pooling fund data, the intensity of anomaly be divided into that level-one is abnormal, second level is abnormal and normal, and the level-one is abnormal
Intensity of anomaly is higher than that the second level is abnormal, the intensity of anomaly of second level exception be higher than it is described normal, the second level exception it is different
Chang Chengdu is higher than described normal；
According to the corresponding relationship of the intensity of anomaly and exhibition method, determine that the target handles the risk-pooling fund data in area
Intended display mode；
It is shown according to the risk-pooling fund data that the intended display mode handles area to the target.
Second aspect, the embodiment of the invention provides a kind of the medical supervision device based on data visualization, described device
Include:
Module is obtained, the risk-pooling fund data in area are handled for obtaining target, it includes at least one under area that the target, which is handled,
A medical institutions；
Determining module determines that the target handles the system in area for handling the risk-pooling fund data in area according to the target
Fund monitoring index data are raised, the risk-pooling fund monitoring index includes risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, system
Raise at least one in the ratio of fund expenditure and medical expense；
The determining module is also used to the corresponding relationship according to the risk-pooling fund monitoring index data and intensity of anomaly,
Determine that the target handles the intensity of anomaly of the risk-pooling fund data in area, it is abnormal that the intensity of anomaly is divided into level-one exception, second level
With it is normal, the intensity of anomaly of the level-one exception is higher than that the second level is abnormal, described in the intensity of anomaly of second level exception is higher than
Normally, the intensity of anomaly of the second level exception is higher than described normal；The determining module, be also used to according to the intensity of anomaly with
The corresponding relationship of exhibition method determines that the target handles the intended display mode of the risk-pooling fund data in area；
Display module, the risk-pooling fund data for handling area to the target according to the intended display mode are opened up
Show.
The third aspect the embodiment of the invention provides a kind of terminal, including processor, input equipment, output equipment and is deposited
Reservoir, the processor, input equipment, output equipment and memory are connected with each other, wherein the memory is calculated for storing
Machine program, the computer program include program instruction, and the processor is configured for calling described program instruction, execute the
Method described in one side.
Fourth aspect, the embodiment of the invention provides a kind of computer readable storage mediums, which is characterized in that the calculating
Machine storage medium is stored with computer program, and the computer program includes program instruction, and described program instruction is when by processor
The processor is set to execute method described in first aspect when execution.
In the embodiment of the present invention, terminal obtains the risk-pooling fund data that target handles area, handles area according to the target
Risk-pooling fund data determine that the target handles the risk-pooling fund monitoring index data in area, the risk-pooling fund monitoring index packet
Include risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, risk-pooling fund expenditure and at least one in the ratio of medical expense；Root
According to the corresponding relationship of the risk-pooling fund monitoring index data and intensity of anomaly, determine that the target handles the risk-pooling fund number in area
According to intensity of anomaly；According to the corresponding relationship of the intensity of anomaly and exhibition method, determine that the target handles the pool base in area
The intended display mode of golden number evidence；It is opened up according to the risk-pooling fund data that the intended display mode handles area to the target
Show.By implementing the above method, the abnormal conditions of risk-pooling fund expenditure can be automatically detected, medical supervision efficiency is promoted.
Detailed description of the invention
Technical solution in order to illustrate the embodiments of the present invention more clearly, below will be to needed in embodiment description
Attached drawing is briefly described, it should be apparent that, drawings in the following description are some embodiments of the invention, general for this field
For logical technical staff, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow diagram of medical supervision method based on data visualization provided in an embodiment of the present invention；
Fig. 2 is the process signal of another medical supervision method based on data visualization provided in an embodiment of the present invention
Figure；
Fig. 3 is that a kind of data provided in an embodiment of the present invention show interface schematic diagram；
Fig. 4 is a kind of structural schematic diagram of medical supervision device based on data visualization provided in an embodiment of the present invention；
Fig. 5 is a kind of structural schematic diagram of terminal provided in an embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Image search method provided in an embodiment of the present invention is implemented in terminal, and the terminal includes smart phone, plate electricity
The electronic equipments such as brain, digital audio & video players, electronic reader, handheld game machine or vehicle electronic device.
Fig. 1 is a kind of flow diagram of the medical supervision method based on data visualization in the embodiment of the present invention.Such as figure
The process of the medical supervision method based on data visualization in shown the present embodiment may include:
S101, terminal obtain the risk-pooling fund data that target handles area, and it includes at least one doctor that the target, which is handled under area,
Treat mechanism.
In the embodiment of the present invention, risk-pooling fund is medical insurance risk-pooling fund, handles the region coordination that area is risk-pooling fund,
It includes at least one medical institutions under area that target, which is handled,.It is times handled in area that at least one needs detects that the target, which handles area,
Meaning one, in the specific implementation, terminal can receive user's input handle area's selection instruction, and by user's selection to handle area true
It is set to target and handles area.Risk-pooling fund data specifically include: the risk-pooling fund in each period is taken in, risk-pooling fund is paid,
Risk-pooling fund total value etc..
S102, terminal handle the risk-pooling fund data in area according to target, determine target handle area risk-pooling fund monitoring refer to
Mark data.
In the embodiment of the present invention, the risk-pooling fund monitoring index includes risk-pooling fund expenditure, risk-pooling fund expenditure growth
Rate, risk-pooling fund expenditure and at least one in the ratio of medical expense.Terminal gets target and handles risk-pooling fund under area
After data, it may further determine that risk-pooling fund monitoring index data.In the specific implementation, can determine in preset time period
Risk-pooling fund expenditure and doctor under risk-pooling fund expenditure growth rate, each timing node in risk-pooling fund expenditure, preset time period
The ratio etc. for the treatment of expense, preset time period can be 1 year, one month, one week etc., and e.g., preset time period is one month, then unite
Raising fund expenditure Growth Rate Calculation mode is to calculate the difference of current moon risk-pooling fund expenditure and risk-pooling fund last month expenditure, will
The ratio of the difference and risk-pooling fund last month expenditure is as risk-pooling fund growth rate.Medical expense can be passed through according to the target
The income summation for doing each medical institutions under area is determined.
S103, terminal determine that target handles area according to the corresponding relationship of risk-pooling fund monitoring index data and intensity of anomaly
Risk-pooling fund data intensity of anomaly.
In the embodiment of the present invention, after terminal gets the risk-pooling fund data that target handles area, it will test target and handle
The risk-pooling fund data in area further detect its intensity of anomaly with the presence or absence of exception, in the specific implementation, terminal can be according to system
The corresponding relationship for raising fund monitoring index data and intensity of anomaly determines that target handles the abnormal journey of the risk-pooling fund data in area
Degree.
In one implementation, terminal determines that target passes through according to the corresponding relationship of risk-pooling fund expenditure and intensity of anomaly
Do the intensity of anomaly of the risk-pooling fund data in area.
Specifically, terminal, which obtains target, handles medical institutions' quantity under area, and first is determined according to medical institutions' quantity
Metrics-thresholds.Wherein, the corresponding standard risk-pooling fund expenditure of each medical institutions, terminal get target and handle under area
Medical institutions quantity after, standard risk-pooling fund can be paid and be determined as the first index with the product of medical institutions' quantity
Threshold value, wherein standard risk-pooling fund expenditure can be average for the risk-pooling fund expenditure of each sample medical institutions counted in advance
Value, median, mode etc., alternatively, being preset by research staff, the risk-pooling fund expenditure of medical institutions is insured people in medical treatment
Mechanism uses the summation of the amount of money of risk-pooling fund reimbursement.For example, standard risk-pooling fund expenditure is 1000, which handles the doctor in area
Treating mechanism quantity is 200, then can determine that the first metrics-thresholds are 200000.
Further, because different grades of medical institutions' risk-pooling fund spending variance is larger, different grades of medical institutions
Corresponding standard risk-pooling fund expenditure can be different, wherein medical institutions' grade can be according to " Hospital stratified management standard "
The grade determined after evaluation, such as three-level top grade, three-level is first-class, three-level the second grade, the three-level third gradegrade C, second-rank first class ... the level-one third gradegrade C.
Therefore, the method for determination of the first metrics-thresholds can also be that terminal obtains target and handles at least one medical institutions that area includes
Grade, and determine that the corresponding target of each medical institutions' grade at least one medical institutions' grade handles the therapeutic machine under area
Structure quantity.Handling area such as target includes 20 medical institutions, respectively three-level top grade medical institutions 1, the first-class therapeutic machine of three-level
Structure 2, second-rank first class medical institutions 4, level-one the second grade medical institutions 13.Then, terminal is according to preset medical institutions etc.
The corresponding relationship of grade and standard risk-pooling fund expenditure determines the corresponding standard risk-pooling fund expenditure of each medical institutions' grade, and
According to the corresponding medical institutions' quantity of each medical institutions' grade standard risk-pooling fund branch corresponding with each medical institutions' grade
Out, the first metrics-thresholds are determined.Wherein, the first metrics-thresholds can for calculate medical institutions' quantity of each grade with it is corresponding
The product of standard risk-pooling fund expenditure, then is summed each product being calculated to obtain the first metrics-thresholds.
For example, target handles pair of preset medical institutions' grade and standard risk-pooling fund expenditure and quantity under area
Should be related to can be as shown in table 1:
Table 1:
| Mechanism grade | Standard risk-pooling fund | Quantity |
| Three-level top grade | 8000 | 1 |
| Three-level is first-class | 6000 | 2 |
| Second-rank first class | 3000 | 4 |
| Level-one the second grade | 1000 | 13 |
The first metrics-thresholds S is then calculated are as follows: S=8000*1+6000*2+3000*4+1000*13=45000.
In the specific implementation, the first metrics-thresholds can also be preset by research staff, the embodiment of the present invention is without limitation.
Terminal is after determining the first metrics-thresholds, will calculate the first difference of risk-pooling fund expenditure and the first metrics-thresholds, according to
The corresponding relationship of first difference and intensity of anomaly determines that the target handles the intensity of anomaly of the risk-pooling fund data in area.Wherein,
Intensity of anomaly can be divided into that level-one is abnormal, second level is abnormal and normal, and the intensity of anomaly of level-one exception is different higher than the second level
Often, the intensity of anomaly of the second level exception is higher than described normal.If the first difference is greater than the first preset threshold, it is determined that abnormal journey
Degree is that level-one is abnormal, if the first difference is between the first preset threshold and the second preset threshold, it is determined that intensity of anomaly two
Grade is abnormal, if the first difference is less than the second preset threshold, it is determined that risk-pooling fund data are normal.Wherein, the first preset threshold is big
In the second preset threshold, the size of the first preset threshold and the second preset threshold can be preset by research staff, and the present invention is real
Apply example without limitation.
In one implementation, terminal pays the corresponding relationship of growth rate and intensity of anomaly according to risk-pooling fund, determines
Target handles the intensity of anomaly of the risk-pooling fund data in area.Wherein, risk-pooling fund expenditure growth rate is to plan as a whole in preset time period
The growth rate of fund expenditure.
Specifically, terminal, which obtains target, handles the insurant growth rate under area, wherein insurant growth rate is described
Insurant growth rate in preset time period, if preset time period is one month, then the calculation of insurant growth rate
The difference of current moon insurant quantity Yu insurant last month quantity to be calculated, by the difference and insurant last month number
The ratio of amount is as insurant growth rate.After terminal gets insurant growth rate, it will be increased according to the insurant
Long rate determines the second metrics-thresholds, wherein the second metrics-thresholds can be identical as the insurant growth rate.Insurant can
Think the personnel of purchase medical insurance, or the people for the purchase medical insurance that the medical institutions under handling area to target go to a doctor
Member.
Terminal will calculate the of risk-pooling fund expenditure growth rate and the second metrics-thresholds after determining the second metrics-thresholds
Two differences, and determine that target handles the intensity of anomaly of the risk-pooling fund in area according to the corresponding relationship of the second difference and intensity of anomaly.
Wherein, intensity of anomaly can be divided into that level-one is abnormal, second level is abnormal and normal, and the intensity of anomaly of level-one exception is higher than second level exception,
The intensity of anomaly of second level exception is higher than normal.If the second difference is greater than the first default growth rate, it is determined that intensity of anomaly is level-one
It is abnormal, if the second difference is between the first default growth rate and the second default growth rate, it is determined that intensity of anomaly is that second level is different
Often, if the second difference is less than the second default growth rate, risk-pooling fund data are normal.Wherein, the first default growth rate is greater than the
The size of two default growth rates, the first default growth rate and the second default growth rate can be preset by research staff, the present invention
Embodiment is without limitation.
In one implementation, because in existing medical system, the allowable project of higher grade medical institutions
More than the allowable project of junior medical institutions, leading to the reimbursement ratios of different grades of medical institutions, there may be differences
It is different.If the allowable project of Grade III Class A hospital is higher than the allowable project of level-one third gradegrade C hospital, lead to Grade III Class A hospital
Reimbursement ratio is higher than the reimbursement ratio of level-one third gradegrade C hospital, the reimbursement ratio be insured people using risk-pooling fund reimbursement expense with
The ratio of medical expense.Therefore, terminal can be paid corresponding with the ratio of medical expense and intensity of anomaly according to risk-pooling fund
Relationship determines that the target handles the intensity of anomaly of the risk-pooling fund data in area.
Specifically, terminal obtains the medical institutions' quantity and medical treatment for default medical institutions' grade that the target is handled under area
First ratio of mechanism total quantity, and third metrics-thresholds are determined according to first ratio.Wherein, medical institutions' grade is preset
Can be first-class for three-level, second level the second grade etc. further, can also be by the same one dividing into three of medical institutions for the convenience of statistics
A grade is such as divided into three-level, second level and level-one.For example, predetermined level is three-level, terminal gets the quantity of three-level medical institutions
It is 5, which is 20, it is determined that the first ratio is 25%, and from preset mapping table
Finding the corresponding third metrics-thresholds of ratio 25% is 80%.After terminal gets third predetermined threshold value, plan as a whole calculating
The third difference of the ratio of fund expenditure and medical expense and third metrics-thresholds, and according to pair of third difference and intensity of anomaly
It should be related to that determining target handles the intensity of anomaly of the risk-pooling fund in area.Wherein, it is different can be divided into level-one exception, second level for intensity of anomaly
Often and normal, it is abnormal that the intensity of anomaly of level-one exception is higher than second level.If third difference is greater than the first default ratio, it is determined that abnormal
Degree is that level-one is abnormal, if third difference is between the first default ratio and the second default ratio, it is determined that intensity of anomaly is
Second level is abnormal, if third difference is less than the second default ratio, it is determined that risk-pooling fund data are normal.Wherein, the first default ratio
Greater than the second default ratio, the size of the first default ratio and the second default ratio can be preset by research staff, the present invention
Embodiment is without limitation.
In one implementation, because different classes of hospital may also lead to reimbursement ratio difference, such as tumour hospital
Reimbursement ratio is higher than stomatological hospital, after terminal determines the grade of medical institutions, can be combined with medical institutions' classification and determines system
Raise the intensity of anomaly of fund.Medical institutions' classification can be divided into general hospital, the hospital of traditional Chinese hospital, the hospitals of traditional Chinese and western medicine, the people
Hospital, race, tumour hospital, stomatological hospital etc..In the specific implementation, terminal, which obtains target, handles default medical institutions' classification under area
Medical institutions' quantity and medical institutions' total quantity the second ratio, four-index threshold value is determined according to second ratio, count
Risk-pooling fund expenditure and the ratio of medical expense and the 4th difference of the four-index threshold value are calculated, according to the 4th difference and exception
The corresponding relationship of degree determines that target handles the intensity of anomaly of the risk-pooling fund in area.
S104, terminal determine that target handles the risk-pooling fund number in area according to the corresponding relationship of intensity of anomaly and exhibition method
According to intended display mode.
In the embodiment of the present invention, after terminal determines the intensity of anomaly of risk-pooling fund data that target handles area, by basis
The corresponding relationship of intensity of anomaly and exhibition method determines that the target handles the intended display mode of the risk-pooling fund data in area.
In one implementation, intensity of anomaly can correspond to different present graphicals, wherein the extremely corresponding exhibition of level-one
Diagram shape is histogram, and the extremely corresponding present graphical of second level is line chart, and normal corresponding present graphical is cake chart.
In one implementation, intensity of anomaly corresponds to different displaying colors, for example, the extremely corresponding displaying face of level-one
Color is black, and the extremely corresponding displaying color of second level is blue, and normal corresponding displaying color is white.
S105, terminal are shown according to the risk-pooling fund data that intended display mode handles area to target.
It, will be according to the intended display mode to described after terminal determines intended display mode in the embodiment of the present invention
The risk-pooling fund data that target handles area are shown.
In one implementation, when being shown to each risk-pooling fund data for handling area, if target handles area
Intensity of anomaly be that level-one is abnormal, then each risk-pooling fund data for handling area are shown using histogram, if target passes through
The intensity of anomaly for doing area is that second level is abnormal, then is shown using line chart to each risk-pooling fund data for handling area, if mesh
Mark handle area risk-pooling fund data be it is normal, then use cake chart each risk-pooling fund data for handling area are shown.
In one implementation, when being shown to each risk-pooling fund data for handling area, if target handles area
Intensity of anomaly be that level-one is abnormal, then area's risk-pooling fund data are handled to the target using black and are shown, if target is handled
The intensity of anomaly in area is that second level is abnormal, then is shown using the risk-pooling fund data that blue handles area to the target, if target
Handle area risk-pooling fund data be it is normal, then using white area is handled to the target risk-pooling fund data be shown.
As shown in figure 3, the interface schematic diagram shown for a kind of risk-pooling fund that inventive embodiments provide.The schematic diagram is specific
The risk-pooling fund index of displaying is that risk-pooling fund pays growth rate, and it is that target handles area, and the target handles area that third, which handles area,
Intensity of anomaly be that level-one is abnormal, then each risk-pooling fund expenditure growth rate for handling area is shown using histogram, and
The displaying color that third handles area is determined as black.
In the embodiment of the present invention, terminal is according to the abnormal journey by setting many index threshold value to the risk-pooling fund for handling area
Degree is monitored, and the exhibition method of the risk-pooling fund data in area is handled described in determination, according to the exhibition method to the warp
The risk-pooling fund data for doing area are shown.By implementing the above method, the exception of risk-pooling fund expenditure can be automatically detected
Situation promotes medical supervision efficiency.
Fig. 2 is the flow diagram of medical supervision method of the another kind based on data visualization in the embodiment of the present invention.Such as
The process of the medical supervision method based on data visualization shown in scheming in the present embodiment may include:
S201, terminal obtain the risk-pooling fund data that target handles area, and it includes at least one doctor that the target, which is handled under area,
Treat mechanism.
S202, terminal handle the risk-pooling fund data in area according to target, determine target handle area risk-pooling fund monitoring refer to
Mark data.
In the embodiment of the present invention, the risk-pooling fund monitoring index includes risk-pooling fund expenditure, risk-pooling fund expenditure growth
Rate, risk-pooling fund expenditure and at least one in the ratio of medical expense.
S203, terminal determine that target handles area according to the corresponding relationship of risk-pooling fund monitoring index data and intensity of anomaly
Risk-pooling fund data intensity of anomaly.
In the embodiment of the present invention, terminal can pay the corresponding relationship with intensity of anomaly according to the risk-pooling fund, determine
The target handle the risk-pooling fund data in area intensity of anomaly or terminal can according to risk-pooling fund pay growth rate with it is different
The corresponding relationship of Chang Chengdu determines that the target handles the intensity of anomaly of the risk-pooling fund data in area, alternatively, terminal can be with root
According to risk-pooling fund expenditure and the ratio of medical expense and the corresponding relationship of intensity of anomaly, determine that the target handles the pool base in area
The intensity of anomaly of gold.
Further, the intensity of anomaly that each risk-pooling fund monitoring index detects can be combined by terminal, be determined
Target handles the intensity of anomaly of the risk-pooling fund data in area.For example, terminal is true by intensity of anomaly highest in each monitoring index
It is set to the intensity of anomaly that target handles the risk-pooling fund data in area.Paying corresponding intensity of anomaly such as risk-pooling fund is normal, system
Raising the corresponding intensity of anomaly of fund expenditure growth rate is that level-one is abnormal, and risk-pooling fund expenditure is corresponding with the ratio of medical expense different
Chang Chengdu is that second level is abnormal, then the intensity of anomaly that terminal determines that target handles the risk-pooling fund data in area is that level-one is abnormal.It is optional
, in three monitoring indexes, the corresponding intensity of anomaly of at least two monitoring indexes is that second level is abnormal if it exists, then terminal determines
The intensity of anomaly that target handles the risk-pooling fund data in area is that level-one is abnormal.
If the risk-pooling fund that the target handles area has exception, the exception includes that level-one is abnormal and second level is abnormal, then
Terminal is classified according to that can preset the risk-pooling fund that dimension handles area to target, and default dimension includes visit type, personnel
At least one of type, disease category, medical institutions' grade, and detect target and handle risk-pooling fund under the default dimension in area
The intensity of anomaly of data, so that it is determined that the risk-pooling fund for causing target to handle area pays abnormal reason.Wherein, risk-pooling fund number
It is paid according to can be risk-pooling fund.
For visit type dimension, terminal can be analyzed risk-pooling fund data according to the difference of visit type,
In, visit type can be divided into hospital, outpatient service serious disease, outpatient service plan as a whole, the risk-pooling fund of terminal observation difference visit type expenditure
Trend, if certain type of risk-pooling fund expenditure biggish variation has occurred in a short time, illustrate the fund expenditure may
There is a situation where exception；It is also possible to the comparison that all types of risk-pooling funds is paid be carried out in conjunction with Settlement Date, if at one
In Settlement Date, the variation tendency of a plurality of types of fund expenditures is consistent, and different changes is presented in the fund expenditure of a few types
Change trend, then illustrating the fund expenditures of a few types, there may be abnormal situations.
For personnel's classification dimension, terminal analyzes risk-pooling fund according to the difference of personnel's classification, specifically, personnel
Classification can be divided into resident and worker.Terminal calculates the difference of the risk-pooling fund expenditure of resident and worker, presets if difference is greater than
Threshold value then illustrates that there may be abnormal situations for risk-pooling fund expenditure.
For disease category dimension, terminal analyzes risk-pooling fund expenditure according to disease category, obtains various diseases
Patient person-time and medical total cost, and time equal disbursement is calculated with this.Time equal disbursement of each disease is all
Equipped with a standard value, calculates time difference of disbursement and standard value and then illustrate the disease category if more than preset difference value
There may be abnormal situations for lower risk-pooling fund expenditure.
For medical institutions' rank dimension, terminal gets the pool base that target handles the medical institutions of different stage under area
Gold expenditure, terminal detects whether that the risk-pooling fund data of the medical institutions there are some rank are greater than preset value, if so, determining
The risk-pooling fund data of the medical institutions of the rank exist abnormal.
S204, terminal obtain the corresponding early warning information of intensity of anomaly of risk-pooling fund.
In the embodiment of the present invention, after terminal determines the intensity of anomaly of risk-pooling fund data, the risk-pooling fund will be determined
The corresponding early warning information of intensity of anomaly.The intensity of anomaly and the specific corresponding relationship of early warning information can be level-one
Abnormal corresponding red early warning and reminding information, the extremely corresponding blue early warning information of second level.Wherein, early warning prompt information is same
Risk-pooling fund monitoring index including causing the intensity of anomaly, risk-pooling fund monitoring index include risk-pooling fund expenditure, plan as a whole base
Gold expenditure growth rate, risk-pooling fund expenditure and at least one in the ratio of medical expense.
S205, terminal export early warning information.
S206, terminal determine that the target handles the system in area according to the corresponding relationship of the intensity of anomaly and exhibition method
Raise the intended display mode of fund data.
S207, terminal are shown according to the risk-pooling fund data that the intended display mode handles area to the target.
In the embodiment of the present invention, terminal is according to the abnormal journey by setting many index threshold value to the risk-pooling fund for handling area
Degree is monitored, and the exhibition method of the risk-pooling fund data in area is handled described in determination, according to the exhibition method to the warp
The risk-pooling fund data for doing area are shown.By implementing the above method, the exception of risk-pooling fund expenditure can be automatically detected
Situation promotes medical supervision efficiency.
The medical supervision device provided in an embodiment of the present invention based on data visualization is carried out below in conjunction with attached drawing 4 detailed
It is thin to introduce.It should be noted that the attached medical supervision device shown in Fig. 4 based on data visualization, for executing figure of the present invention
The method of 1- embodiment illustrated in fig. 2, for ease of description, only parts related to embodiments of the present invention are shown, particular technique
What details did not disclosed, through referring to Fig. 1-of the present invention embodiment shown in Fig. 2.
Fig. 4 is referred to, is a kind of structural schematic diagram of the medical supervision device based on data visualization provided by the invention,
The medical supervision device 40 based on data visualization can include: obtain module 401, determining module 402 and display module 403.
Module 401 is obtained, the risk-pooling fund data in area are handled for obtaining target, it includes at least that the target, which is handled under area,
One medical institutions；
Determining module 402 determines that the target handles area for handling the risk-pooling fund data in area according to the target
Risk-pooling fund monitoring index data, the risk-pooling fund monitoring index include risk-pooling fund expenditure, risk-pooling fund expenditure growth rate,
Risk-pooling fund expenditure and at least one in the ratio of medical expense；
The determining module 402 is also used to close according to the risk-pooling fund monitoring index data are corresponding with intensity of anomaly
System determines that the target handles the intensity of anomaly of the risk-pooling fund data in area, and it is different that the intensity of anomaly is divided into level-one exception, second level
Often and normal, the intensity of anomaly of the level-one exception is higher than the second level exception, and the intensity of anomaly of the second level exception is higher than institute
It states normally, the intensity of anomaly of the second level exception is higher than described normal；
The determining module 402 is also used to the corresponding relationship according to the intensity of anomaly and exhibition method, determines the mesh
Mark handles the intended display mode of the risk-pooling fund data in area；
Display module 403, for according to the intended display mode to the target handle the risk-pooling fund data in area into
Row is shown.
In one implementation, the risk-pooling fund monitoring index includes risk-pooling fund expenditure, the determining module 402
It is specifically used for:
It obtains the target and handles medical institutions' quantity under area；
The first metrics-thresholds are determined according to medical institutions' quantity；
Calculate the first difference of the risk-pooling fund expenditure and first metrics-thresholds；
Determine that the target handles the different of the risk-pooling fund data in area according to the corresponding relationship of the first difference and intensity of anomaly
Chang Chengdu.
In one implementation, the determining module 402 is specifically used for:
Determine that the target handles at least one the medical institutions' grade for including under area；
Determine that the corresponding target of each medical institutions' grade at least one described medical institutions' grade handles area
Under medical institutions' quantity；
According to the corresponding relationship of preset medical institutions' grade and standard risk-pooling fund expenditure, each therapeutic machine is determined
The corresponding standard risk-pooling fund expenditure of structure grade；
According to the corresponding medical institutions' quantity of each medical institutions' grade mark corresponding with each medical institutions' grade
Quasi- risk-pooling fund expenditure, determines the first metrics-thresholds.
In one implementation, the risk-pooling fund monitoring index includes risk-pooling fund expenditure growth rate, the determination
Module 402 is specifically used for:
It obtains the target and handles insurant quantity growth rate under area；
The second metrics-thresholds are determined according to the insurant quantity growth rate；
Calculate the second difference of risk-pooling fund the expenditure growth rate and second metrics-thresholds；
Determine that the target handles the different of the risk-pooling fund in area according to the corresponding relationship of second difference and intensity of anomaly
Chang Chengdu.
In one implementation, the risk-pooling fund monitoring index includes the ratio of risk-pooling fund expenditure and medical expense
Value, the determining module 402 are specifically used for:
Obtain the medical institutions' quantity and medical institutions' total quantity of default medical institutions' grade that the target is handled under area
The first ratio；
Third metrics-thresholds are determined according to first ratio；
Calculate the risk-pooling fund expenditure and the ratio of medical expense and the third difference of the third metrics-thresholds；
Determine that the target handles the abnormal journey of the risk-pooling fund in area according to the corresponding relationship of third difference and intensity of anomaly
Degree.
In one implementation, described device further includes categorization module 404, detection module 405.
If there is exception in risk-pooling fund of the categorization module 404 for the target to handle area, according to default dimension to institute
It states target and handles the risk-pooling fund in area and classify, the default dimension includes visit type, personnel's type, disease category, doctor
Treat at least one of mechanism grade；
Detection module 405 handles the abnormal journey of the risk-pooling fund data under the default dimension in area for detecting the target
Degree.
In one implementation, described device further includes output module 406:
Obtain the corresponding early warning information of intensity of anomaly that module 401 is used to obtain the risk-pooling fund；
Output module 406 is for exporting the early warning information.
In the embodiment of the present invention, the risk-pooling fund data that target handles area, determining module are obtained by obtaining module 401
402 handle the risk-pooling fund data in area according to the target, determine that the target handles the risk-pooling fund monitoring index data in area,
Determining module 402 determines that the target is handled according to the corresponding relationship of the risk-pooling fund monitoring index data and intensity of anomaly
The intensity of anomaly of the risk-pooling fund data in area, determining module 402 is according to the corresponding relationship of the intensity of anomaly and exhibition method, really
The fixed target handles the intended display mode of the risk-pooling fund data in area, and display module 403 is according to the intended display mode
The risk-pooling fund data for handling area to the target are shown, and can automatically detect the abnormal conditions of risk-pooling fund expenditure,
Promote medical supervision efficiency.
Fig. 5 is referred to, for the embodiment of the invention provides a kind of structural schematic diagrams of terminal.As shown in figure 5, the terminal packet
It includes: at least one processor 501, input equipment 503, output equipment 504, memory 505, at least one communication bus 502.Its
In, communication bus 502 is for realizing the connection communication between these components.Wherein, input equipment 503 can be control panel or
Person's microphone etc., output equipment 504 can be display screen etc..Wherein, memory 505 can be high speed RAM memory, can also be with
It is non-labile memory (non-volatile memory), for example, at least a magnetic disk storage.Memory 505 is optional
Can also be that at least one is located remotely from the storage device of aforementioned processor 501.Wherein processor 501 can combine Fig. 4 institute
The device of description, batch processing code, and processor 501, input equipment 503 are stored in memory 505, and output equipment 504 is adjusted
With the program code stored in memory 505, for performing the following operations:
Input equipment 503 handles the risk-pooling fund data in area for obtaining target, and it includes at least that the target, which is handled under area,
One medical institutions；
Processor 501 is used to handle the risk-pooling fund data in area according to the target, determines that the target handles the system in area
Fund monitoring index data are raised, the risk-pooling fund monitoring index includes risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, system
Raise at least one in the ratio of fund expenditure and medical expense；
Processor 501 is used for the corresponding relationship according to the risk-pooling fund monitoring index data and intensity of anomaly, determines institute
State the intensity of anomaly that target handles the risk-pooling fund data in area, the intensity of anomaly is divided into that level-one is abnormal, second level is abnormal and normal,
The intensity of anomaly of the level-one exception is higher than the second level exception, and the intensity of anomaly of the second level exception is higher than described normal, institute
The intensity of anomaly for stating second level exception is normal higher than described；
Processor 501 is used for the corresponding relationship according to the intensity of anomaly and exhibition method, determines that the target handles area
Risk-pooling fund data intended display mode；
Processor 501 according to the risk-pooling fund data that the intended display mode handles area to the target for opening up
Show.
In one implementation, the risk-pooling fund monitoring index includes that risk-pooling fund is paid, processor 501, specifically
For:
It obtains the target and handles medical institutions' quantity under area；
The first metrics-thresholds are determined according to medical institutions' quantity；
Calculate the first difference of the risk-pooling fund expenditure and first metrics-thresholds；
Determine that the target handles the different of the risk-pooling fund data in area according to the corresponding relationship of the first difference and intensity of anomaly
Chang Chengdu.
In one implementation, processor 501 is specifically used for:
Determine that the target handles at least one the medical institutions' grade for including under area；
Determine that the corresponding target of each medical institutions' grade at least one described medical institutions' grade handles area
Under medical institutions' quantity；
According to the corresponding relationship of preset medical institutions' grade and standard risk-pooling fund expenditure, each therapeutic machine is determined
The corresponding standard risk-pooling fund expenditure of structure grade；
According to the corresponding medical institutions' quantity of each medical institutions' grade mark corresponding with each medical institutions' grade
Quasi- risk-pooling fund expenditure, determines the first metrics-thresholds.
In one implementation, the risk-pooling fund monitoring index includes risk-pooling fund expenditure growth rate, processor 501
It is specifically used for:
It obtains the target and handles insurant quantity growth rate under area；
The second metrics-thresholds are determined according to the insurant quantity growth rate；
Calculate the second difference of risk-pooling fund the expenditure growth rate and second metrics-thresholds；
Determine that the target handles the different of the risk-pooling fund in area according to the corresponding relationship of second difference and intensity of anomaly
Chang Chengdu.
In one implementation, the risk-pooling fund monitoring index includes the ratio of risk-pooling fund expenditure and medical expense
Value, processor 501 are specifically used for:
Obtain the medical institutions' quantity and medical institutions' total quantity of default medical institutions' grade that the target is handled under area
The first ratio；
Third metrics-thresholds are determined according to first ratio；
Calculate the risk-pooling fund expenditure and the ratio of medical expense and the third difference of the third metrics-thresholds；
Determine that the target handles the abnormal journey of the risk-pooling fund in area according to the corresponding relationship of third difference and intensity of anomaly
Degree.
In one implementation, processor 501 is also used to:
If the risk-pooling fund that the target handles area has exception, the system in area is handled to the target according to default dimension
Fund is raised to classify, the default dimension include visit type, personnel's type, disease category, medical institutions grade at least
It is a kind of；
Detect the intensity of anomaly for the risk-pooling fund data that the target is handled under the default dimension in area.
In one implementation, input equipment 503 is used to obtain the corresponding early warning of intensity of anomaly of the risk-pooling fund
Prompt information；
Output equipment 504 is for exporting the early warning information.
In the embodiment of the present invention, the risk-pooling fund data that target handles area, processor 501 are obtained by input equipment 503
The risk-pooling fund data that area is handled according to the target determine that the target handles the risk-pooling fund monitoring index data in area, place
Device 501 is managed according to the corresponding relationship of the risk-pooling fund monitoring index data and intensity of anomaly, determines that the target handles area
The intensity of anomaly of risk-pooling fund data, processor 501 according to the corresponding relationship of the intensity of anomaly and exhibition method, determine described in
Target handles the intended display mode of the risk-pooling fund data in area, and processor 501 is according to the intended display mode to the mesh
The risk-pooling fund data that mark handles area are shown, and can automatically detect the abnormal conditions of risk-pooling fund expenditure, promote medical treatment
Supervisory efficiency.
Module described in the embodiment of the present invention can pass through universal integrated circuit, such as CPU (Central
Processing Unit, central processing unit), or pass through ASIC (Application Specific Integrated
Circuit, specific integrated circuit) Lai Shixian.
It should be appreciated that in embodiments of the present invention, alleged processor 501 can be central processing module (Central
Processing Unit, CPU), which can also be other general processors, digital signal processor (Digital
Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit,
ASIC), ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic
Device, discrete gate or transistor logic, discrete hardware components etc..General processor can be microprocessor or this at
Reason device is also possible to any conventional processor etc..
It is total that bus 502 can be industry standard architecture (Industry Standard Architecture, ISA)
Line, Peripheral Component Interconnect (Peripheral Component, PCI) bus or extended industry-standard architecture (Extended
Industry Standard Architecture, EISA) bus etc., it is total which can be divided into address bus, data
Line, control bus etc., for convenient for indicating, Fig. 5 is only indicated with a thick line, it is not intended that an only bus or a seed type
Bus.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the program can be stored in computer storage medium, the journey
Sequence is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the computer storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
The above disclosure is only the preferred embodiments of the present invention, cannot limit the right model of the present invention with this certainly
It encloses, therefore equivalent changes made in accordance with the claims of the present invention, is still within the scope of the present invention.
Claims (10)
1. a kind of medical supervision method based on data visualization characterized by comprising
The risk-pooling fund data that target handles area are obtained, it includes at least one medical institutions under area that the target, which is handled,；
The risk-pooling fund data that area is handled according to the target determine that the target handles the risk-pooling fund monitoring index number in area
According to the risk-pooling fund monitoring index includes risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, risk-pooling fund expenditure and medical treatment
At least one of in the ratio of expense；
According to the corresponding relationship of the risk-pooling fund monitoring index data and intensity of anomaly, determine that the target handles the pool in area
The intensity of anomaly of fund data, the intensity of anomaly are divided into abnormal level-one, second level exception and normal, the exception of the level-one exception
Degree is higher than the second level exception, and the intensity of anomaly of the second level exception is higher than described normal, the abnormal journey of the second level exception
Degree is higher than described normal；
According to the corresponding relationship of the intensity of anomaly and exhibition method, determine that the target handles the mesh of the risk-pooling fund data in area
Mark exhibition method；
It is shown according to the risk-pooling fund data that the intended display mode handles area to the target.
2. the method according to claim 1, wherein the risk-pooling fund monitoring index includes risk-pooling fund branch
Out；
The corresponding relationship according to the risk-pooling fund monitoring index data and intensity of anomaly, determines that the target handles area
The intensity of anomaly of risk-pooling fund data, comprising:
It obtains the target and handles medical institutions' quantity under area；
The first metrics-thresholds are determined according to medical institutions' quantity；
Calculate the first difference of the risk-pooling fund expenditure and first metrics-thresholds；
Determine that the target handles the abnormal journey of the risk-pooling fund data in area according to the corresponding relationship of the first difference and intensity of anomaly
Degree.
3. according to the method described in claim 2, it is characterized in that, described determine the first index threshold according to medical institutions' quantity
Value, comprising:
Determine that the target handles at least one the medical institutions' grade for including under area；
Determine that the corresponding target of each medical institutions' grade at least one described medical institutions' grade is handled under area
Medical institutions' quantity；
According to the corresponding relationship of preset medical institutions' grade and standard risk-pooling fund expenditure, described each medical institutions etc. are determined
The corresponding standard risk-pooling fund expenditure of grade；
It is united according to the corresponding medical institutions' quantity of each medical institutions' grade standard corresponding with each medical institutions' grade
Fund expenditure is raised, determines the first metrics-thresholds.
4. the method according to claim 1, wherein the risk-pooling fund monitoring index includes risk-pooling fund expenditure
Growth rate；
The corresponding relationship according to the risk-pooling fund monitoring index data and intensity of anomaly, determines that the target handles area
The intensity of anomaly of risk-pooling fund data, comprising:
It obtains the target and handles insurant quantity growth rate under area；
The second metrics-thresholds are determined according to the insurant quantity growth rate；
Calculate the second difference of risk-pooling fund the expenditure growth rate and second metrics-thresholds；
Determine that the target handles the abnormal journey of the risk-pooling fund in area according to the corresponding relationship of second difference and intensity of anomaly
Degree.
5. the method according to claim 1, wherein the risk-pooling fund monitoring index includes risk-pooling fund expenditure
With the ratio of medical expense；
The corresponding relationship according to the risk-pooling fund monitoring index data and intensity of anomaly, determines that the target handles area
The intensity of anomaly of risk-pooling fund data, comprising:
Obtain the target handle default medical institutions' grade under area medical institutions' quantity and medical institutions' total quantity the
One ratio；
Third metrics-thresholds are determined according to first ratio；
Calculate the risk-pooling fund expenditure and the ratio of medical expense and the third difference of the third metrics-thresholds；
Determine that the target handles the intensity of anomaly of the risk-pooling fund in area according to the corresponding relationship of third difference and intensity of anomaly.
6. the method according to claim 1, wherein the determination target handles the different of the risk-pooling fund in area
After Chang Chengdu, further includes:
If the risk-pooling fund that the target handles area has exception, the pool base in area is handled to the target according to default dimension
Gold is classified, and the default dimension includes at least one of visit type, personnel's type, disease category, medical institutions' grade；
Detect the intensity of anomaly for the risk-pooling fund data that the target is handled under the default dimension in area.
7. the method according to claim 1, wherein the method determines that the target handles the risk-pooling fund in area
Intensity of anomaly after, further includes:
Obtain the corresponding early warning information of intensity of anomaly of the risk-pooling fund；
Export the early warning information.
8. a kind of medical supervision device based on data visualization, which is characterized in that described device includes:
Module is obtained, the risk-pooling fund data in area are handled for obtaining target, it includes at least one doctor that the target, which is handled under area,
Treat mechanism；
Determining module determines that the target handles the pool base in area for handling the risk-pooling fund data in area according to the target
Golden monitoring index data, the risk-pooling fund monitoring index include risk-pooling fund expenditure, risk-pooling fund expenditure growth rate, plan as a whole base
Gold expenditure and at least one in the ratio of medical expense；
The determining module is also used to the corresponding relationship according to the risk-pooling fund monitoring index data and intensity of anomaly, determines
The target handles the intensity of anomaly of the risk-pooling fund data in area, and the intensity of anomaly is divided into that level-one is abnormal, second level is abnormal and just
Often, the intensity of anomaly of the level-one exception is higher than the second level exception, and the intensity of anomaly of the second level exception is normal higher than described,
The intensity of anomaly of the second level exception is higher than described normal；
The determining module is also used to the corresponding relationship according to the intensity of anomaly and exhibition method, determines that the target is handled
The intended display mode of the risk-pooling fund data in area；
Display module, the risk-pooling fund data for handling area to the target according to the intended display mode are shown.
9. a kind of terminal, which is characterized in that the processor, defeated including processor, input equipment, output equipment and memory
Enter equipment, output equipment and memory to be connected with each other, wherein the memory is for storing computer program, the computer
Program includes program instruction, and the processor is configured for calling described program instruction, is executed such as any one of claim 1-7
The method.
10. a kind of computer readable storage medium, which is characterized in that the computer storage medium is stored with computer program,
The computer program includes program instruction, and described program instruction makes the processor execute such as right when being executed by a processor
It is required that the described in any item methods of 1-7.
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