CN113590683A - Multi-dimensional electronic bill suspicious ticket comprehensive monitoring and analyzing method - Google Patents
Multi-dimensional electronic bill suspicious ticket comprehensive monitoring and analyzing method Download PDFInfo
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Abstract
The invention relates to a multi-dimensional electronic bill suspicious ticket comprehensive analysis and monitoring method, which comprises an electronic bill system, a rule engine, a data supervision and analysis platform and a database; the electronic bill system is used for inputting bill information and performing bill information interaction with the rule engine and the database; the rule engine is used for defining suspicious bill monitoring rules, monitoring bills and storing monitoring results to the database; and the data supervision and analysis platform reads and displays the monitoring result of the suspicious bill in the database. The invention separately processes the common bill information and the medical bill information, and improves the real-time response capability of the system to the monitoring of the electronic bill.
Description
Technical Field
The invention relates to a multi-dimensional electronic bill suspicious ticket comprehensive analysis and monitoring method, and belongs to the technical field of suspicious electronic bill monitoring.
Background
The supervision department supervises suspicious bills and mainly depends on manual checking, and because the number of the electronic bills is huge, the workload of manual checking is large, the efficiency and the accuracy rate are limited, and the timeliness is poor, all the bills cannot be supervised. The existing bill supervision system supervises the electronic bill by setting a certain supervision rule and has the defect that the detection rule cannot be flexibly modified. When the medical bill is detected, the medical bill contains a great amount of medical list information, so that the requirement on a supervision system is higher.
The document with the application number of CN201910880666.3 discloses an electronic bill processing method, device, readable storage medium and computer equipment, which are used for improving the accuracy of electronic bill processing. Through the settable early warning rule, the early warning effect of the electronic bill meeting the user requirement is achieved. The disadvantage is that the problem of huge amount of medical list information in the medical bill is not solved.
Disclosure of Invention
In order to overcome the problems, the invention provides a multi-dimensional electronic bill suspicious ticket comprehensive analysis monitoring method, which separately processes common bill information and medical list information and improves the real-time response capability of a system to electronic bill monitoring.
The technical scheme of the invention is as follows:
a multi-dimensional electronic bill suspicious ticket comprehensive analysis and monitoring method comprises an electronic bill system, a rule engine, a data supervision and analysis platform and a database;
the electronic bill system is used for inputting bill information and performing bill information interaction with the rule engine and the database;
the rule engine is used for defining a suspicious bill monitoring rule, monitoring the bill information according to the bill monitoring rule and storing a monitoring result to the database;
and the data supervision and analysis platform reads and displays the monitoring result of the suspicious bill in the database.
Further, the bill types input by the electronic bill system comprise non-tax bills, round-trip bills, donation bills, community bills and medical bills;
each piece of bill information comprises a piece of bill main information and a plurality of pieces of project information; each item of information of the bill information of the medical bill comprises a plurality of medical list information;
the electronic bill system sends the bill information to the database; the electronic bill system sends the bill information except the medical list information to the rule engine;
the monitoring method further comprises an ETL service, wherein the ETL service comprises an analysis cleaning module and a medical list analysis module; the ETL service reads the bill information of the medical bills in the database, and analyzes, cleans and monitors the bill information of the medical bills through an analyzing and cleaning module and a medical bill analyzing module to obtain an analysis result; the ETL service stores the analysis results to the database.
Further, the electronic bill system sends the bill information except the medical list information to the rule engine in real time.
Further, the rule engine comprises a built-in rule module, and the built-in rule module monitors bill information by using built-in judgment rules; the built-in judgment rule is specifically as follows:
the bill type is non-tax bill, the bill meeting any one of the following conditions is judged as suspicious bill,
the money carrier has the word of 'army' or 'armed police';
the sum of the orders is more than 100 ten thousand;
the bill type is the incoming and outgoing bill, the bill meeting any one of the following conditions is judged as the suspicious bill,
the sum of the orders is more than 1000 ten thousand;
the paying person carries the word of 'company' or 'enterprise', and the billing item includes the business fund paid by the administrative department, the special fund paid by the administrative department, the scientific research topic fund paid by the administrative department, the special fund paid by the administrative department or the scientific research topic fund paid by the administrative department;
the bill type is donation bill, the bill meeting any one of the following conditions is judged as suspicious bill,
the sum of the orders is more than 1000 ten thousand;
remarks or itemized bands "contribute" word;
the bill type is the community bill, the bill meeting the following conditions is judged as the suspicious bill,
the expense item is contained, and the sum of the expense item is more than 100 ten thousand.
Further, the rule engine also comprises a self-defined rule module; the user-defined rule module is used for setting a user-defined judgment rule of the suspicious bill and monitoring bill information by using the user-defined judgment rule; the setting process of the self-defined judgment rule is as follows:
defining the name of the decision rule;
selecting the bill type suitable for the judgment rule;
selecting a matching rule of the decision rule; the matching rules comprise any matching rule and all matching rules;
selecting monitoring indexes of the judgment rule, wherein the number of the monitoring indexes is at least 1; the monitoring indexes comprise an opening amount and a face typeface;
setting a monitoring rule of the judgment rule corresponding to each monitoring index; when the monitoring index is the opening amount, the monitoring rule comprises a threshold value T1And the sum of the opening amount and the threshold value T1The relationship of (1); and when the monitoring index is the face typeface, the monitoring rule comprises the vocabulary which is set to be contained in the face typeface.
Further, the monitoring of the ticket by the rule engine comprises the following steps:
step S1, inputting bill information;
step S2, judging whether monitoring is carried out through a built-in rule module, if so, executing step S3, and if not, executing step S8;
step S3, acquiring built-in judgment rules;
step S4, matching the bill information with unmatched built-in judgment rules;
step S5, whether the current rule is matched or not is judged, if yes, step S6 is executed, and if not, step S7 is executed;
step S6, marking the bill information;
step S7, judging whether the bill information matches all the built-in judgment rules, if yes, executing step S8, and if not, executing step S4;
step S8, judging whether monitoring is carried out through the self-defined rule module, if so, executing step S9, and if not, executing step S14;
step S9, obtaining a self-defined judgment rule;
step S10, matching the bill information with the unmatched self-defined judgment rule;
step S11, whether the current rule is matched or not is judged, if yes, step S12 is executed, and if not, step S13 is executed;
step S12, marking the bill information;
step S13, judging whether the bill information matches all self-defined judgment rules, if yes, executing step S14, and if not, executing step S10;
and step S14, ending the monitoring process and storing the suspicious bill judgment result in the database.
Further, the data supervision and analysis platform comprises a suspicious bill analysis supervision module; and the suspicious bill analysis and supervision module reads a suspicious bill judgment result from the database and displays the suspicious bill judgment result.
Further, the medical checklist analyzing module monitors medical checklist information, and includes the following steps:
step G1, judging whether to monitor the medical list information for the first time, if so, executing step G2, and if not, executing step G5;
step G2, inquiring the medical inventory information of the past month;
g3, analyzing and cleaning the medical list information;
step G4, saving the medical list information analysis cleaning result to a temporary table;
step G5, inquiring the medical inventory information of the current day;
step G6, analyzing and cleaning the medical list information on the current day;
step G7, saving the medical list information analysis cleaning result of the current day to a temporary table;
step G8, circularly traversing all the charging items;
step G9, inquiring the charge items which are not inquired in the temporary table;
step G10, calculating the minimum value, the maximum value, the average value and the standard deviation sigma of the charging price of each data;
g11, judging and marking the abnormal data of the charging price;
step G12, judging whether all items in the temporary table have been inquired, if yes, executing step G13, and if not, executing step G9;
step G13, deleting the data of the first day in the temporary table;
and G14, finishing the monitoring of the medical list information and storing the result of the abnormal charge judgment of the medical list into the database.
Further, data in which the charged price differs by 3 σ or more from the average value is determined as abnormal charge.
Further, the data supervision and analysis platform comprises a medical institution abnormal charging item supervision module; and the medical institution abnormal charging item supervision module reads and displays the medical institution abnormal charging judgment result from the database.
The invention has the following beneficial effects:
1. the monitoring method monitors the suspicious bills through the built-in rules and the user-defined rules, and can select or combine two monitoring methods, so that bill monitoring is more flexible.
2. The monitoring method monitors the medical list information independently, and real-time monitoring is not needed because the medical list information has huge data volume and has low requirement on the real-time performance of monitoring.
3. The monitoring method analyzes and cleans medical inventory information, reduces the data volume of analysis and improves the working efficiency.
Drawings
FIG. 1 is a block diagram of an embodiment of the present invention.
Fig. 2 is a schematic diagram of a ticket information structure according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of the structure of the medical ticket information according to the embodiment of the invention.
FIG. 4 is a flow chart of a custom rule according to an embodiment of the present invention.
Fig. 5 is a flow chart of detecting the ticket information according to the embodiment of the invention.
FIG. 6 is a flow chart of an analytical cleaning process according to an embodiment of the present invention.
Fig. 7 is a 3 σ law diagram of an embodiment of the present invention.
Fig. 8 is a flowchart of medical checklist information monitoring according to an embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and the specific embodiments.
Referring to fig. 1, a multi-dimensional electronic bill suspicious ticket comprehensive analysis monitoring method includes an electronic bill system, a rule engine, a data supervision and analysis platform and a database;
the electronic bill system is used for inputting bill information and performing bill information interaction with the rule engine and the database;
the rule engine is used for defining a suspicious bill monitoring rule, monitoring the bill information according to the suspicious bill monitoring rule and storing a monitoring result to the database;
and the data supervision and analysis platform reads and displays the monitoring result of the suspicious bill in the database.
Example one
Referring to fig. 1-3, the multi-dimensional electronic bill doubtful bill comprehensive analysis monitoring method is based on the above monitoring method, the bill types input by the electronic bill system include non-tax bills, round bills, donation bills, community bills and medical bills;
each piece of bill information comprises a piece of bill main information and a plurality of pieces of project information; the main bill information comprises the date of making a bill, the unit of making a bill, the type of the bill, the code of the bill, the amount of the bill, the payee and other extension information; the bill project information comprises project names and codes, project amount, project quantity and project detail information; each item of information of the bill information of the medical bill comprises a plurality of medical list information; the medical bill information reflects the specific charging condition of the medical bill.
The electronic bill system sends the bill information to the database; the electronic bill system sends the bill information except the medical list information to the rule engine;
the monitoring method further comprises an Extract-Transform-Load (ETL) service, wherein the ETL service comprises an analysis cleaning module and a medical inventory analysis module; and the ETL service reads the bill information of the medical bills in the database, and analyzes, cleans and monitors the bill information of the medical bills through an analyzing and cleaning module and a medical bill analysis module to obtain an analysis result. The medical inventory information monitoring data volume is large, the real-time requirement is not high, and the medical inventory information monitoring data volume can be analyzed and cleaned every day through an ETL service; the ETL service stores the analysis results to the database. The medical bill information has huge data volume, and if the medical bill information is sent to the rule engine together with other bill information, the load of the rule engine is increased, and the requirement on the rule engine is increased. In this embodiment, the medical list information is stored in the database in a json format, and the medical list information in the json format is analyzed and cleaned and then is monitored, so that the difficulty in data processing can be reduced.
The electronic bill system sends the bill information except the medical list information to the rule engine in real time. And the rule engine receives and monitors the bill information in real time, so that the aim of analyzing and early warning suspicious bills in real time is fulfilled.
Example two
Referring to fig. 4-5, in the multi-dimensional electronic bill suspicious ticket comprehensive analysis monitoring method, on the basis of the first embodiment, the rule engine includes a built-in rule module, and the built-in rule module monitors the bill information by using a built-in decision rule; the built-in judgment rule is specifically as follows:
the bill type is non-tax bill, the bill meeting any one of the following conditions is judged as suspicious bill,
the money carrier has the word of 'army' or 'armed police';
the sum of the orders is more than 100 ten thousand;
the bill type is the incoming and outgoing bill, the bill meeting any one of the following conditions is judged as the suspicious bill,
the sum of the orders is more than 1000 ten thousand;
the paying person carries the word of 'company' or 'enterprise', and the billing item includes the business fund paid by the administrative department, the special fund paid by the administrative department, the scientific research topic fund paid by the administrative department, the special fund paid by the administrative department or the scientific research topic fund paid by the administrative department;
the bill type is donation bill, the bill meeting any one of the following conditions is judged as suspicious bill,
the sum of the orders is more than 1000 ten thousand;
remarks or itemized bands "contribute" word;
the bill type is the community bill, the bill meeting the following conditions is judged as the suspicious bill,
the expense item is contained, and the sum of the expense item is more than 100 ten thousand.
The rule engine also comprises a self-defined rule module; the user-defined rule module is used for setting a user-defined judgment rule of the suspicious bill and monitoring bill information by using the user-defined judgment rule; the setting process of the self-defined judgment rule is as follows:
the name of the decision rule is defined to indicate a specific suspicious cause or to facilitate identification.
And selecting the bill type suitable for the judgment rule, wherein the name of the bill type is named according to the actual use name of the region. In this embodiment, the ticket types include a government non-tax income unified ticket, a social group unified ticket, an administrative institution capital exchange settlement ticket, a medical outpatient service charging ticket, a medical hospitalization charging ticket, a public utility donation unified ticket, a social insurance fund dedicated ticket, and the like.
Selecting a matching rule of the decision rule; the matching rules comprise any matching rule and all matching rules, each self-defined judging rule can comprise a plurality of sub-rules, when the matching rules are any matching rule, the bill information is matched with any sub-rule, and then the bill information is judged to be a suspicious bill, and when the matching rules are all matching rules, the bill information is matched with all sub-rules, and then the bill information is judged to be a suspicious bill.
Selecting monitoring indexes of the judgment rule, wherein the number of the monitoring indexes is at least one; the monitoring indexes comprise an opening amount and a face typeface; the face typeface comprises a payee, project information and other information;
setting a monitoring rule of the judgment rule corresponding to each monitoring index; when the monitoring index is the opening amount, the monitoring rule comprises a threshold value T1And the sum of the opening amount and the threshold value T1The relationship of (1); when the monitoring index is the face character, the monitoring rule comprises the vocabulary which is set to be contained in the face character, if the bill information contains the vocabulary, the bill information is judged to be suspicious
The method for monitoring the bill by the rule engine comprises the following steps:
step S1, inputting bill information;
step S2, judging whether monitoring is carried out through a built-in rule module, if so, executing step S3, and if not, executing step S8;
step S3, acquiring built-in judgment rules;
step S4, matching the bill information with unmatched built-in judgment rules;
step S5, whether the current rule is matched or not is judged, if yes, step S6 is executed, and if not, step S7 is executed;
step S6, marking the bill information;
step S7, judging whether the bill information matches all the built-in judgment rules, if yes, executing step S8, and if not, executing step S4;
step S8, judging whether monitoring is carried out through the self-defined rule module, if so, executing step S9, and if not, executing step S14;
step S9, obtaining a self-defined judgment rule;
step S10, matching the bill information with the unmatched self-defined judgment rule;
step S11, whether the current rule is matched or not is judged, if yes, step S12 is executed, and if not, step S13 is executed;
step S12, marking the bill information;
step S13, judging whether the bill information matches all self-defined judgment rules, if yes, executing step S14, and if not, executing step S10;
and step S14, ending the monitoring process and storing the suspicious bill judgment result in the database.
Whether the built-in rule module and the custom rule module are started or not is set through the rule engine, and the effect of selecting a monitoring mode is achieved. The internal rules and the custom rules can be formed to enable simultaneous shutdown or separate use for four monitoring modes.
The data supervision and analysis platform comprises a suspicious bill analysis and supervision module; and the suspicious bill analysis and supervision module reads a suspicious bill judgment result from the database and displays the suspicious bill judgment result.
EXAMPLE III
Referring to fig. 6-8, the method for comprehensively analyzing and monitoring suspicious medical tickets by using a multidimensional electronic ticket, based on the first embodiment, the analyzing and cleaning module for analyzing and cleaning medical data information includes the following steps:
step T1, acquiring medical list information;
step T2, preventing the medical list information from being stored;
step T3, analyzing the medical inventory information of json;
step T4, calculating the size of the json array;
step T5, obtaining the unresolved array elements;
step T5, analyzing the amount and price of the medical list information corresponding to the array elements, and converting the type of the medical list information into floating point numbers;
step T6, analyzing the codes and names of the medical list information corresponding to the array elements;
step T7, analyzing the item code and name of the medical list information corresponding to the array element;
step T8, analyzing the measurement units of the medical list information corresponding to the array elements;
step T9, saving the analyzed medical list information to a temporary table;
and step T10, judging whether all array elements are analyzed, if so, ending the analysis cleaning process, and if not, executing step T5.
The medical list analysis module monitors medical list information and comprises the following steps:
step G1, judging whether to monitor the medical list information for the first time, if so, executing step G2, and if not, executing step G5;
step G2, inquiring the medical inventory information of the past month;
g3, analyzing and cleaning the medical list information;
step G4, saving the medical list information analysis cleaning result to a temporary table;
step G5, inquiring the medical inventory information of the current day;
step G6, analyzing and cleaning the medical list information on the current day;
step G7, saving the medical list information analysis cleaning result of the current day to a temporary table;
step G8, circularly traversing all the charging items;
step G9, inquiring the charge items which are not inquired in the temporary table;
step G10, calculating the minimum value, the maximum value, the average value and the standard deviation sigma of the charging price of each data;
g11, judging and marking the abnormal data of the charging price;
step G12, judging whether all items in the temporary table have been inquired, if yes, executing step G13, and if not, executing step G9;
step G13, deleting the data of the first day in the temporary table;
and G14, finishing the monitoring of the medical list information and storing the result of the abnormal charge judgment of the medical list into the database. And calculating key data through the charging prices of different medical bill information under the same charging item, and monitoring the medical bill information charged abnormally according to the data.
In one embodiment of the invention, the medical list of abnormal charges is judged by 3 sigma law, and the data of the charge price different from the average value by more than 3 sigma is judged as abnormal charges.
The data supervision and analysis platform comprises a medical institution abnormal charging item supervision module; and the medical institution abnormal charging item supervision module reads and displays the medical institution abnormal charging judgment result from the database. The operator can visually know the medical list information of abnormal charges.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent structures made by using the contents of the specification and the drawings of the present invention or directly or indirectly applied to other related technical fields are included in the scope of the present invention.
Claims (10)
1. A multi-dimensional electronic bill suspicious ticket comprehensive analysis monitoring method is characterized by comprising an electronic bill system, a rule engine, a data supervision and analysis platform and a database;
the electronic bill system is used for inputting bill information and performing bill information interaction with the rule engine and the database;
the rule engine is used for defining a suspicious bill monitoring rule, monitoring bill information according to the suspicious bill monitoring rule and storing a monitoring result to the database;
and the data supervision and analysis platform reads and displays the monitoring result of the suspicious bill in the database.
2. The comprehensive analysis and monitoring method for suspicious tickets made by electronic bills of claim 1 is characterized in that the bill types input by the electronic bill system comprise non-tax bills, round-trip bills, donation bills, community bills and medical bills;
each piece of bill information comprises a piece of bill main information and a plurality of pieces of project information; each item of information of the bill information of the medical bill comprises a plurality of medical list information;
the electronic bill system sends the bill information to the database; the electronic bill system sends the bill information except the medical list information to the rule engine;
the monitoring method further comprises an ETL service, wherein the ETL service comprises an analysis cleaning module and a medical list analysis module; the ETL service reads the bill information of the medical bills in the database, and analyzes, cleans and monitors the bill information of the medical bills through an analyzing and cleaning module and a medical bill analyzing module to obtain an analysis result; the ETL service stores the analysis results to the database.
3. The method according to claim 2, wherein the electronic billing system sends the billing information to the rules engine in real time, except for medical checklist information.
4. The multi-dimensional electronic bill suspicious ticket comprehensive analysis monitoring method according to claim 3, wherein the rule engine comprises a built-in rule module, and the built-in rule module monitors bill information by using built-in decision rules; the built-in judgment rule is specifically as follows:
the bill type is non-tax bill, the bill meeting any one of the following conditions is judged as suspicious bill,
the money carrier has the word of 'army' or 'armed police';
the sum of the orders is more than 100 ten thousand;
the bill type is the incoming and outgoing bill, the bill meeting any one of the following conditions is judged as the suspicious bill,
the sum of the orders is more than 1000 ten thousand;
the paying person carries the word of 'company' or 'enterprise', and the billing item includes the business fund paid by the administrative department, the special fund paid by the administrative department, the scientific research topic fund paid by the administrative department, the special fund paid by the administrative department or the scientific research topic fund paid by the administrative department;
the bill type is donation bill, the bill meeting any one of the following conditions is judged as suspicious bill,
the sum of the orders is more than 1000 ten thousand;
remarks or itemized bands "contribute" word;
the bill type is the community bill, the bill meeting the following conditions is judged as the suspicious bill,
the expense item is contained, and the sum of the expense item is more than 100 ten thousand.
5. The multi-dimensional electronic bill suspicious ticket comprehensive analysis and monitoring method according to claim 4, wherein the rule engine further comprises a custom rule module; the user-defined rule module is used for setting a user-defined judgment rule of the suspicious bill and monitoring bill information by using the user-defined judgment rule; the setting process of the self-defined judgment rule is as follows:
defining the name of the decision rule;
selecting the bill type suitable for the judgment rule;
selecting a matching rule of the decision rule; the matching rules comprise any matching rule and all matching rules;
selecting monitoring indexes of the judgment rule, wherein the number of the monitoring indexes is at least 1; the monitoring indexes comprise an opening amount and a face typeface;
setting a monitoring rule of the judgment rule corresponding to each monitoring index; when the monitoring index is the opening amount, the monitoring rule comprises a threshold value T1And the sum of the opening amount and the threshold value T1The relationship of (1); and when the monitoring index is the face typeface, the monitoring rule comprises the vocabulary which is set to be contained in the face typeface.
6. The multi-dimensional electronic bill suspicious ticket comprehensive analysis monitoring method according to claim 5, wherein the rule engine monitoring the bills comprises the following steps:
step S1, inputting bill information;
step S2, judging whether monitoring is carried out through a built-in rule module, if so, executing step S3, and if not, executing step S8;
step S3, acquiring built-in judgment rules;
step S4, matching the bill information with unmatched built-in judgment rules;
step S5, whether the current rule is matched or not is judged, if yes, step S6 is executed, and if not, step S7 is executed;
step S6, marking the bill information;
step S7, judging whether the bill information matches all the built-in judgment rules, if yes, executing step S8, and if not, executing step S4;
step S8, judging whether monitoring is carried out through the self-defined rule module, if so, executing step S9, and if not, executing step S14;
step S9, obtaining a self-defined judgment rule;
step S10, matching the bill information with the unmatched self-defined judgment rule;
step S11, whether the current rule is matched or not is judged, if yes, step S12 is executed, and if not, step S13 is executed;
step S12, marking the bill information;
step S13, judging whether the bill information matches all self-defined judgment rules, if yes, executing step S14, and if not, executing step S10;
and step S14, ending the monitoring process and storing the suspicious bill judgment result in the database.
7. The multi-dimensional electronic bill suspicious ticket comprehensive analysis and monitoring method according to claim 6, wherein the data supervision and analysis platform comprises a suspicious ticket analysis supervision module; and the suspicious bill analysis and supervision module reads a suspicious bill judgment result from the database and displays the suspicious bill judgment result.
8. The comprehensive analysis and monitoring method for suspicious electronic bills according to claim 3, wherein the medical bill analysis module monitors medical bill information and comprises the following steps:
step G1, judging whether to monitor the medical list information for the first time, if so, executing step G2, and if not, executing step G5;
step G2, inquiring the medical inventory information of the past month;
g3, analyzing and cleaning the medical list information;
step G4, saving the medical list information analysis cleaning result to a temporary table;
step G5, inquiring the medical inventory information of the current day;
step G6, analyzing and cleaning the medical list information on the current day;
step G7, saving the medical list information analysis cleaning result of the current day to a temporary table;
step G8, circularly traversing all the charging items;
step G9, inquiring the charge items which are not inquired in the temporary table;
step G10, calculating the minimum value, the maximum value, the average value and the standard deviation sigma of the charging price of each data;
g11, judging and marking the abnormal data of the charging price;
step G12, judging whether all items in the temporary table have been inquired, if yes, executing step G13, and if not, executing step G9;
step G13, deleting the data of the first day in the temporary table;
and G14, finishing the monitoring of the medical list information and storing the result of the abnormal charge judgment of the medical list into the database.
9. The comprehensive analysis and monitoring method for suspicious electronic bills according to claim 8, characterized in that the data of the difference between the charged price and the average value by more than 3 σ is determined as abnormal charge.
10. The comprehensive analysis and monitoring method for suspicious electronic bills according to claim 8 or 9, wherein the data supervision and analysis platform comprises a medical institution abnormal charging project supervision module; and the medical institution abnormal charging item supervision module reads and displays the medical institution abnormal charging judgment result from the database.
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| CN202110831250.XA CN113590683A (en) | 2021-07-22 | 2021-07-22 | Multi-dimensional electronic bill suspicious ticket comprehensive monitoring and analyzing method |
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