CN111553799B - Data processing method and system based on medical insurance data - Google Patents
Data processing method and system based on medical insurance data Download PDFInfo
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Abstract
The embodiment of the invention provides a data processing method based on medical insurance data, which comprises the following steps: acquiring basic data of a plurality of users from a source database, and acquiring corresponding medical insurance associated data based on the basic data; extracting a plurality of first data from the basic data and the medical insurance related data, and generating a first result according to the plurality of first data; extracting a plurality of second data from the basic data and the medical insurance related data to an independent target database; settling the plurality of second data according to a preset rule and the first result to generate a second result; inserting a second result in the target database into the source database, and generating an annual knot rotation form according to the second result. The embodiment of the invention also provides a data processing system based on the medical insurance data. And the read-write separation processing is realized through the source database and the target database, so that the consumption of the performance of the database is reduced. The present invention also relates to blockchain techniques, which may store the medical insurance data in blockchain nodes.
Description
Technical Field
Embodiments of the present invention relate to the field of computers, and in particular, to a data processing method, system, computer device and computer readable storage medium based on medical insurance data.
Background
With the development of social medical services and the wide development of medical insurance systems in the national range, medical insurance is increasingly important for people. And due to the importance of medical insurance, corresponding processing needs to be performed on medical insurance data.
However, large-scale data processing may cause consumption of database performance, and even cause problems such as system jam and slow running. For example, when the medical insurance departments make a year-to-year transfer, the data of a large number of paramedics needs to be processed, which causes a large consumption of the performance of databases and application programs, slows down the real-time medical trade time, and even causes deadlock of a cumulative information table of the medical insurance and a user medical account table, thus affecting the service of the whole medical insurance core system.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a data processing method, system, computer device and computer readable storage medium based on medical insurance data, which are used for solving the problems of high database performance consumption, medical system blocking and slow operation caused by large-scale data processing.
The embodiment of the invention solves the technical problems through the following technical scheme:
a data processing method based on medical insurance data, comprising:
acquiring basic data of a plurality of users from a source database, and acquiring medical insurance associated data corresponding to the plurality of users based on the basic data of the plurality of users;
extracting a plurality of first data from the basic data and the medical insurance related data, and generating a first result according to the plurality of first data;
extracting a plurality of second data from the basic data and the medical insurance related data to an independent target database;
settling the plurality of second data according to a preset rule and the first result to generate a second result;
inserting a second result in the target database into the source database, and generating an annual knot rotation form according to the second result.
Further, the plurality of first data includes: first class data, second class data, and third class data;
the extracting a plurality of first data from the base data and the medical insurance-related data includes:
acquiring a corresponding first type form, an independent second type form and an independent third type form according to the basic data;
generating an accumulated annual value on the first type of forms according to preset settlement time, and acquiring a target first type of forms according to the accumulated annual value;
extracting a plurality of first type data from the target first type form, acquiring a plurality of second type data from the independent second type form, and acquiring a plurality of third type data from the independent third type form.
Further, the target first type forms comprise a current year first type form and a new year first type form; generating an accumulated annual value on the first type of forms according to the preset settlement time, and acquiring the target first type of forms according to the accumulated annual value further comprises:
acquiring target first time data and target second time data from the medical insurance related data according to a time sequence;
when the first time data is earlier than the preset settlement time and the second time data is later than the settlement time, generating a current annual value and a new annual value;
and acquiring a first type of current annual form according to the current annual value, and acquiring a first type of new annual form according to the new annual value.
Further, the second data includes fourth type data and fifth type data;
the extracting a plurality of second data from the base data and the medical insurance association data into a target database further includes:
extracting corresponding medical insurance type data from the basic data;
classifying users based on the medical insurance type data to obtain at least one user set, wherein the user set comprises at least one user with the same medical insurance type;
and extracting fourth type data and fifth type data in corresponding medical insurance associated data to a target database according to the medical insurance type corresponding to the user set.
Further, the first outcome comprises a medical insurance account crediting and crediting outcome, and the second outcome comprises a new year prescripting outcome; the settling of the plurality of second data according to the preset rule and the first result, and generating a second result further includes:
acquiring a corresponding first preset rule according to the medical insurance type corresponding to the user set;
and settling the plurality of second data based on the medical insurance account scoring results, and generating new year pre-scoring results.
Further, before extracting the plurality of second data from the basic data and the medical insurance related data into the target database, the method further includes:
acquiring current time and generating corresponding current serial number data for the medical insurance related data based on the current time;
inserting a second result in the target database into the source database, and generating an annual change form according to the second result, wherein the method further comprises the following steps:
acquiring current serial number data corresponding to medical insurance associated data;
and adding a random code at the tail of the current serial number data to generate the online serial number data.
Further, the basic data and the medical insurance related data in the source database are stored in the blockchain node, and before the basic data of a plurality of users are obtained from the source database, the method further comprises the steps of:
and acquiring target overall regional data from a source database in the blockchain node, and acquiring basic data of a plurality of users based on the target overall regional data.
To achieve the above object, an embodiment of the present invention further provides a data processing system based on medical insurance data, including:
the acquisition module is used for acquiring a plurality of basic data of a plurality of users from the source database and acquiring medical insurance associated data corresponding to the plurality of users based on the basic data of the plurality of users;
the first generation module is used for extracting a plurality of first data from the basic data and the medical insurance related data and generating a first result according to the plurality of first data;
the extraction module is used for extracting a plurality of second data from the basic data and the medical insurance related data to an independent target database;
the second generation module is used for settling the plurality of second data according to a preset rule and the first result and generating a second result;
and the third generation module is used for inserting a second result in the target database into the source database and generating an annual knot conversion form according to the second result.
To achieve the above object, an embodiment of the present invention further provides a computer device including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the data processing method based on medical insurance data as described above when the computer program is executed.
To achieve the above object, an embodiment of the present invention also provides a computer-readable storage medium having stored therein a computer program executable by at least one processor to cause the at least one processor to perform the steps of the data processing method based on medical insurance data as described above.
The data processing method, the system, the computer equipment and the computer readable storage medium based on the medical insurance data provided by the embodiment of the invention acquire the basic data and the medical insurance associated data of a plurality of users from a source database; generating a first result according to the base data and a plurality of first data in the medical insurance related data; extracting a plurality of second data in the basic data and the medical insurance related data into an independent target database; in a target database, settling the plurality of second data according to a preset rule and the first result to obtain a second result; finally, inserting a second result in the target database into the source database and generating an annual knot transfer form; according to the embodiment of the invention, the read-write separation processing is realized through the source database and the target database, so that the consumption of the performance of the database can be effectively reduced, the utilization rate of resources is improved, and the efficiency is improved when the medical insurance year is changed; and the medical insurance core system is beneficial to normal operation of service.
The invention will now be described in more detail with reference to the drawings and specific examples, which are not intended to limit the invention thereto.
Drawings
FIG. 1 is a flowchart illustrating a method for data processing based on medical insurance data according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps for extracting a plurality of first data in a data processing method based on medical insurance data according to a first embodiment of the present invention;
FIG. 3 is a flowchart illustrating steps for obtaining a target first type of form in a data processing method based on medical insurance data according to a first embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps for extracting a plurality of second data from a target database in a data processing method based on medical insurance data according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating steps for generating a second result in a data processing method based on medical insurance data according to an embodiment of the present invention;
FIG. 6 is a flowchart illustrating steps for generating online serial number data in a data processing method based on medical insurance data according to an embodiment of the present invention;
FIG. 7 is a schematic diagram illustrating a program module of a data processing system based on medical insurance data according to a second embodiment of the present invention;
fig. 8 is a schematic hardware structure of a computer device according to a third embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that the description of "first", "second", etc. in this disclosure is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implying an indication of the number of technical features being indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. The technical solutions between the embodiments may be combined with each other, but it is necessary to base the implementation on the basis of those skilled in the art that when the combination of technical solutions contradicts or cannot be implemented, it should be considered that the combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.
Example 1
Referring to FIG. 1, a flow chart of steps of a data processing method based on medical insurance data according to an embodiment of the present invention is shown. It will be appreciated that the flow charts in the method embodiments are not intended to limit the order in which the steps are performed. The following description is exemplary with a computer device as an execution subject, and specifically follows:
as shown in fig. 1, the data processing method based on medical insurance data may be applied to the processing of the medical insurance year change, and specifically may include the following steps S100 to S500, where:
step S100, basic data of a plurality of users are obtained from a source database, and medical insurance associated data corresponding to the plurality of users are obtained based on the basic data of the plurality of users.
Specifically, the basic data of the user includes: the ginseng insurance id (name, identity card, age, employment status, retirement status, etc.), the medical insurance account id, etc. The user's medical insurance association data includes, but is not limited to: annual fund accumulation data, account debiting data (debiting years, current annual debiting amount, past annual conversion amount, past annual interest amount, etc.), account expenditure data (spending years, current annual personal account payment accumulation data, past annual personal account payment accumulation data), medical insurance base data (medical insurance type data, medical insurance place data, etc.), preset annual account debiting standard data, etc. Wherein the annual fund accumulation data includes: the total annual value, the maximum payment limit amount exceeding the total fund, the total number of times of total addition (hospitalization, prescribed illness, home sickbed), the clinic doctor insurance expense accumulation, the clinic pay line accumulation, the clinic self-negative accumulation, the public attendant pay, the prescribed doctor insurance accumulation, the prescribed doctor self-negative accumulation, the prescribed doctor pay line accumulation, the hospitalization doctor insurance accumulation, the hospitalization pay line accumulation, the hospitalization self-negative accumulation, the home sickbed doctor insurance accumulation, the home sickbed self-negative accumulation, the total fund accumulated payment, the general doctor subsidy accumulated payment, the public attendant subsidy payment amount accumulation, the special payment amount accumulation, the labor model payment amount accumulation, the clinic total fund accumulated payment, the civil subsidy payment accumulation, the major subsidy payment accumulation, the annual hospitalization times, the clinic times, the prescribed doctor times, the home sickbed build times, the self-negative accumulation, the medicine store purchase times, the medicine purchase times and the like.
In an exemplary embodiment, the base data and the healthcare associated data in the source database are stored at a blockchain node of a blockchain. The method further comprises the steps of acquiring target medical insurance overall regional data from the source database in the blockchain node before acquiring the basic data of the plurality of users from the source database, and acquiring the basic data of the plurality of users based on the target medical insurance overall regional data.
Step S200, extracting a plurality of first data from the basic data and the medical insurance related data, and generating a first result according to the plurality of first data.
Specifically, the plurality of first data includes: first class data, second class data, and third class data. The first type of data is annual fund accumulated data, the second type of data is account crediting data, and the third type of data is account expenditure data. The first outcome includes a medical insurance account crediting payout outcome.
In an exemplary embodiment, referring to fig. 2, a flowchart illustrating steps for extracting a plurality of first data in a data processing method based on medical insurance data according to an embodiment of the present invention is shown, specifically as follows:
step 201, obtaining a corresponding first type form, an independent second type form and an independent third type form according to the basic data.
Specifically, the first type of forms are user medical treatment accumulation forms, the independent second type of forms are independent account drawing forms, and the independent third type of forms are independent account expenditure forms.
Further, the user's underlying data and medical insurance-related data include data of past years as well as new years. The annual fund accumulation data in the annual medical insurance related data of the user and the annual fund accumulation data in the annual medical insurance related data are integrated in the same medical accumulation form of the user in one-to-one correspondence, so that inquiry and settlement are facilitated.
The independent account drawing form and the independent account expenditure form can be understood that the account drawing data are stored in the account drawing form, the account expenditure data are stored in the account expenditure form, the two forms are independently designed, when the drawing settlement is needed, only the account drawing form is required to be called, and when the expenditure settlement is needed, only the account expenditure form is required to be called. Forms are less likely to be generated than if the credited data and the paid data of the account were located in the same form, even in the event of a deadlock in the medical system in which they are located.
Step S202, generating an accumulated annual value on the first type form according to the preset settlement time, and acquiring a target first type form according to the accumulated annual value.
Specifically, the target first type forms comprise a current year first type form and a new year first type form. That is, the current annual first type form is the current annual user medical accumulated form, and the new annual first type form is the new annual user medical accumulated form.
In an exemplary embodiment, referring to fig. 3, step S202 may further include:
step S2021, acquiring target first time data and target second time data from the medical insurance related data according to a time sequence.
The first time data of the target is target admission time data, and the second time data of the target is target discharge time data.
In step S2022, when the first time data is earlier than the preset settlement time and the second time data is later than the settlement time, a current year value and a new year value are generated.
Step S2023, obtaining a current first category form according to the current year value, and obtaining a new first category form according to the new year value.
Step S203, extracting a plurality of first type data from the target first type form, obtaining a plurality of second type data from the independent second type form, and obtaining a plurality of third type data from the independent third type form.
For example, since the medical insurance related data is stored in the source database before settlement, and the outpatient settlement time data and the discharge settlement time data of most users are before the preset settlement time, the corresponding current annual accumulated annual value can be generated according to the preset settlement time, and the accumulated data of the current annual users can be directly taken from the current annual user accumulated form.
When the time period from the time of admission to the time of discharge of the user is detected to contain preset settlement time, corresponding current annual value and new annual value can be respectively obtained according to the time of admission to the time of discharge; taking accumulated data of the current annual users from the accumulated form of the current annual users according to the current annual values; the method comprises the steps of taking the accumulated data of the new year users from the accumulated form of the new year users according to the new year values, and settling according to corresponding hospitalization rules, so that the non-stop settlement of the cross-year can be realized, and the accumulated data of the new year are taken through the new year settlement without additional processing in program development.
And step S300, extracting a plurality of second data from the basic data and the medical insurance related data to an independent target database.
Specifically, the second data includes fourth-type data and fifth-type data. The fourth type of data is medical basic data, and the fifth type of data is standard data. The medical base data includes: user basic data of normal incumbent personnel, user basic data of normal retirement personnel, participation data of incumbent normal payment personnel, participation data of retirement normal personnel and the like; the debiting standard data includes new year account debiting standard data.
In an exemplary embodiment, a separate target database may be understood as the target database being separate from the source database.
In an exemplary embodiment, referring to fig. 4, step S300 may further include steps S01 to S303, which are specifically as follows:
step S301 extracts corresponding medical insurance type data from the basic data.
Specifically, the medical insurance type data comprises rural cooperative medical insurance, town resident basic medical insurance and town employee basic medical insurance.
Step S302, classifying users based on the medical insurance type data to obtain at least one user set, wherein the user set comprises at least one user with the same medical insurance type.
Step S303, fourth-class data and fifth-class data in corresponding medical insurance associated data are extracted to a target database according to the medical insurance type corresponding to the user set.
And step S400, settling the plurality of second data according to the preset rule and the first result, and generating a second result.
Specifically, the second outcome includes a new year prescription outcome.
Illustratively, extracting a plurality of second data from the base data and the medical insurance association data into the target database further includes: and acquiring the current time and generating corresponding current serial number data for the medical insurance related data based on the current time.
In an exemplary embodiment, referring to fig. 5, a flowchart illustrating steps for generating a second result in a data processing method based on medical insurance data according to an embodiment of the present invention is shown, specifically as follows:
step S401, acquiring a corresponding first preset rule according to the medical insurance type corresponding to the user set.
Step S402, settling the second data based on the medical insurance expense entering result, and generating a new year pre-drawing result.
For example, when the medical insurance type is rural cooperative medical insurance, acquiring a corresponding first budget formula; when the medical insurance type is basic medical insurance of urban residents, acquiring a corresponding second budget drawing formula; and when the medical insurance type is basic medical insurance of the town staff, acquiring a corresponding third budget drawing formula.
And S500, inserting a second result in the target database into the source database, and generating an annual knot transformation form according to the second result.
In an exemplary embodiment, referring to fig. 6, before inserting the second result in the target database into the source database and generating the annual rotation form according to the second result, the method further includes:
step S501, current serial number data corresponding to medical insurance association data is obtained.
Step S502, adding a random code at the end of the current serial number data to generate the online serial number data.
Specifically, the second result includes online serial number data, when the second result in the target database is inserted into the source database, due to the difference between the online serial number data and the current serial number data, the situation of data collision is avoided, and the continuity of the data is ensured.
In an exemplary embodiment, the method further includes a check-out of the current annual medical insurance account, including: the current annual income total amount is settled based on account income data, and the current annual expenditure total amount is settled based on account expenditure data; adjusting the annual value to obtain an annual account deposit form, and extracting an annual interest amount from the annual account deposit form; and crediting the current annual medical insurance account amount based on the current annual total amount credited, the current annual total amount paid, and the last annual interest amount.
The existing treatment method for the medical insurance year transfer usually needs to stop external service of the medical insurance core system and the medical insurance date settlement system, even can require the in-hospital patients of all hospitals to be forcedly discharged, and after the related matters of the medical insurance year transfer are completed, the medical insurance date settlement and the service of the medical insurance core system are provided for the outside, and the in-hospital patients need to be re-admitted and the in-hospital doctor order information is re-uploaded. According to the embodiment of the invention, through the integrated form of the accumulated data of the user medical insurance years, the sub-form processing of the data of the user medical insurance and the expenditure data is realized, and the read-write separation is realized based on the data interaction of the source database and the target database interface. And the medical insurance core system is beneficial to normal operation of service.
Example two
With continued reference to FIG. 7, a program module of the data processing system of the present invention based on medical insurance data is shown. In this embodiment, the data processing system 20 based on medical insurance data may include or be divided into one or more program modules, one or more program modules being stored in a storage medium and executed by one or more processors to accomplish the present invention and may implement the data processing method based on medical insurance data described above. Program modules depicted in the embodiments of the present invention are directed to a series of computer program instruction segments capable of performing particular functions in a particular manner, as opposed to programs themselves, that are adapted to describe the execution of data processing system 20 on a storage medium based on medical insurance data. The following description will specifically describe functions of each program module of the present embodiment:
the acquiring module 600 is configured to acquire basic data of a plurality of users from a source database, and acquire medical insurance associated data corresponding to the plurality of users based on the basic data of the plurality of users.
The first generating module 610 is configured to extract a plurality of first data from the base data and the medical insurance related data, and generate a first result according to the plurality of first data.
In an exemplary embodiment, the plurality of first data includes a first type of data, a second type of data, and a third type of data. The first generating module 610 is further configured to: acquiring a corresponding first type form, an independent second type form and an independent third type form according to the basic data; generating an accumulated annual value on the first type of forms according to preset settlement time, and acquiring a target first type of forms according to the accumulated annual value; extracting a plurality of first type data from the target first type form, acquiring a plurality of second type data from the independent second type form, and acquiring a plurality of third type data from the independent third type form.
In an exemplary embodiment, the target first type of form includes a current year first type of form and a new year first type of form; the obtaining of the target first type form may further include obtaining target first time data and target second time data from the medical insurance related data according to a time sequence; when the first time data is earlier than the preset settlement time and the second time data is later than the settlement time, generating a current annual value and a new annual value; and acquiring a first type of current annual form according to the current annual value, and acquiring a first type of new annual form according to the new annual value.
The extracting module 620 is configured to extract a plurality of second data from the basic data and the medical insurance related data into an independent target database.
In an exemplary embodiment, the extraction module 620 is further configured to: extracting corresponding medical insurance type data from the basic data; classifying users based on the medical insurance type data to obtain at least one user set, wherein the user set comprises at least one user with the same medical insurance type; and extracting fourth type data and fifth type data in corresponding medical insurance associated data to a target database according to the medical insurance type corresponding to the user set.
And a second generating module 630, configured to settle the plurality of second data according to a preset rule and the first result, and generate a second result.
In an exemplary embodiment, the first outcome comprises a medical insurance account scratch out outcome and the second outcome comprises a new year pre-scratch outcome. The second generating module 630 is further configured to: acquiring a corresponding first preset rule according to the medical insurance type corresponding to the user set; and settling the plurality of second data based on the medical insurance account scoring results, and generating new year pre-scoring results.
And a third generating module 640, configured to insert a second result in the target database into the source database, and generate an annual knot rotation form according to the second result.
Example III
Referring to fig. 8, a hardware architecture diagram of a computer device according to a third embodiment of the present invention is shown. In this embodiment, the computer device 2 is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction. The computer device 2 may be a rack server, a blade server, a tower server, or a rack server (including a stand-alone server, or a server cluster made up of multiple servers), or the like. As shown in FIG. 8, the computer device 2 includes, but is not limited to, at least a memory 21, a processor 22, a network interface 23, and a data processing system 20 based on medical insurance data, which are communicatively coupled to each other via a system bus. Wherein:
in this embodiment, the memory 21 includes at least one type of computer-readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the memory 21 may be an internal storage unit of the computer device 2, such as a hard disk or a memory of the computer device 2. In other embodiments, the memory 21 may also be an external storage device of the computer device 2, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the computer device 2. Of course, the memory 21 may also include both internal storage units of the computer device 2 and external storage devices. In this embodiment, the memory 21 is typically used to store an operating system and various types of application software installed on the computer device 2, such as program codes of the data processing system 20 based on medical insurance data in the second embodiment. Further, the memory 21 may be used to temporarily store various types of data that have been output or are to be output.
The processor 22 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 22 is typically used to control the overall operation of the computer device 2. In this embodiment, the processor 22 is configured to execute the program code stored in the memory 21 or process data, for example, execute the data processing system 20 based on the medical insurance data, so as to implement the data processing method based on the medical insurance data of the above embodiment.
The network interface 23 may comprise a wireless network interface or a wired network interface, which network interface 23 is typically used for establishing a communication connection between the computer apparatus 2 and other electronic devices. For example, the network interface 23 is used to connect the computer device 2 to an external terminal through a network, establish a data transmission channel and a communication connection between the computer device 2 and the external terminal, and the like. The network may be an Intranet (Intranet), the Internet (Internet), a global system for mobile communications (Global System of Mobile communication, GSM), wideband code division multiple access (Wideband Code Division Multiple Access, WCDMA), a 4G network, a 5G network, bluetooth (Bluetooth), wi-Fi, or other wireless or wired network.
It is noted that fig. 8 only shows a computer device 2 having components 20-23, but it is understood that not all of the illustrated components are required to be implemented, and that more or fewer components may alternatively be implemented.
In this embodiment, the data processing system 20 based on medical insurance data stored in the memory 21 may also be divided into one or more program modules, which are stored in the memory 21 and executed by one or more processors (the processor 22 in this embodiment) to complete the present invention.
For example, FIG. 7 illustrates a schematic diagram of a program module for implementing a second embodiment of the data processing system 20 based on medical insurance data, where the data processing system 20 based on medical insurance data may be divided into an obtaining module 600, a first generating module 610, an extracting module 620, a second generating module 630, and a third generating module 640. Program modules depicted herein, being indicative of a sequence of computer program instruction segments, which can perform particular functions, are better suited to describing the execution of the data processing system 20 based on medical data than programs in the computer device 2. The specific functions of the program modules 600-640 are described in detail in the second embodiment, and are not described herein.
Example IV
The present embodiment also provides a computer-readable storage medium such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor, performs the corresponding functions. The computer readable storage medium of the present embodiment is configured to store the data processing system 20 based on medical insurance data, and when executed by a processor, implement the data processing method based on medical insurance data of the above embodiment.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A data processing method based on medical insurance data, comprising:
acquiring basic data of a plurality of users from a source database, and acquiring medical insurance associated data corresponding to the plurality of users based on the basic data of the plurality of users;
extracting a plurality of first data from the basic data and the medical insurance related data, and generating a first result according to the plurality of first data;
extracting a plurality of second data from the basic data and the medical insurance related data to an independent target database;
settling the plurality of second data according to a preset rule and the first result to generate a second result;
inserting a second result in the target database into the source database, and generating an annual knot transfer form according to the second result;
the plurality of first data includes: first class data, second class data, and third class data; the first type of data is annual fund accumulated data, the second type of data is account crediting data, and the third type of data is account expenditure data;
the first result includes a medical insurance account crediting expenditure result;
the second data comprises fourth class data and fifth class data; the fourth type of data is medical basic data, and the fifth type of data is standard data;
the second outcome includes new year pre-drawn outcomes.
2. The method for processing data based on medical insurance data according to claim 1, wherein,
the extracting a plurality of first data from the base data and the medical insurance-related data includes:
acquiring a corresponding first type form, an independent second type form and an independent third type form according to the basic data;
generating an accumulated annual value on the first type of forms according to preset settlement time, and acquiring a target first type of forms according to the accumulated annual value;
extracting a plurality of first type data from the target first type form, acquiring a plurality of second type data from the independent second type form, and acquiring a plurality of third type data from the independent third type form.
3. The method for processing data based on medical insurance data according to claim 2, wherein said target first type forms include a current first type form and a new first type form; generating an accumulated annual value on the first type of forms according to the preset settlement time, and acquiring the target first type of forms according to the accumulated annual value further comprises:
acquiring target first time data and target second time data from the medical insurance related data according to a time sequence;
when the first time data is earlier than the preset settlement time and the second time data is later than the settlement time, generating a current annual value and a new annual value;
and acquiring a first type of current annual form according to the current annual value, and acquiring a first type of new annual form according to the new annual value.
4. The method for processing data based on medical insurance data according to claim 1, wherein,
the extracting a plurality of second data from the base data and the medical insurance association data into a target database further includes:
extracting corresponding medical insurance type data from the basic data;
classifying users based on the medical insurance type data to obtain at least one user set, wherein the user set comprises at least one user with the same medical insurance type;
and extracting fourth type data and fifth type data in corresponding medical insurance associated data to a target database according to the medical insurance type corresponding to the user set.
5. The method of claim 4, wherein the first outcome comprises a medical insurance account scratch out outcome and the second outcome comprises a new year pre-scratch outcome; the settling of the plurality of second data according to the preset rule and the first result, and generating a second result further includes:
acquiring a corresponding first preset rule according to the medical insurance type corresponding to the user set;
and settling the plurality of second data based on the medical insurance account scoring results, and generating new year pre-scoring results.
6. The method of claim 5, further comprising, prior to extracting a plurality of second data from the base data and the healthcare associated data into a target database:
acquiring current time and generating corresponding current serial number data for the medical insurance related data based on the current time;
inserting a second result in the target database into the source database, and generating an annual change form according to the second result, wherein the method further comprises the following steps:
acquiring current serial number data corresponding to medical insurance associated data;
and adding a random code at the tail of the current serial number data to generate the online serial number data.
7. The data processing method based on medical insurance data according to claim 2, wherein the basic data and the medical insurance related data in the source database are stored in a blockchain node, and further comprising, before the basic data of the plurality of users is obtained from the source database:
and acquiring target overall regional data from a source database in the blockchain node, and acquiring basic data of a plurality of users based on the target overall regional data.
8. A data processing system based on medical insurance data, comprising:
the acquisition module is used for acquiring a plurality of basic data of a plurality of users from the source database and acquiring medical insurance associated data corresponding to the plurality of users based on the basic data of the plurality of users;
the first generation module is used for extracting a plurality of first data from the basic data and the medical insurance related data and generating a first result according to the plurality of first data;
the extraction module is used for extracting a plurality of second data from the basic data and the medical insurance related data to an independent target database;
the second generation module is used for settling the plurality of second data according to a preset rule and the first result and generating a second result;
the third generation module is used for inserting a second result in the target database into the source database and generating an annual knot conversion form according to the second result;
the plurality of first data includes: first class data, second class data, and third class data; the first type of data is annual fund accumulated data, the second type of data is account crediting data, and the third type of data is account expenditure data;
the first result includes a medical insurance account crediting expenditure result;
the second data comprises fourth class data and fifth class data; the fourth type of data is medical basic data, and the fifth type of data is standard data;
the second outcome includes new year pre-drawn outcomes.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the data processing method based on medical insurance data as claimed in any of claims 1 to 7 when the computer program is executed by the processor.
10. A computer-readable storage medium, in which a computer program is stored, the computer program being executable by at least one processor to cause the at least one processor to perform the steps of the medical insurance data based data processing method according to any of claims 1 to 7.
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