Disclosure of Invention
In view of the foregoing, it is desirable to provide a medical data monitoring method, apparatus, computer device, and storage medium capable of effectively monitoring medical data in a multidimensional manner.
A medical data monitoring method, the method comprising:
acquiring a data monitoring request, and acquiring medical data according to the data monitoring request;
dividing the medical data into a plurality of medical data according to a plurality of dimensions;
each medical data is aggregated according to a preset time interval, and medical indexes corresponding to various medical data are obtained;
Generating a medical message according to medical indexes corresponding to the plurality of medical data through a preset private protocol;
and sending the medical message to a webpage application server, so that the webpage application server analyzes the medical message according to the preset private protocol to obtain medical indexes corresponding to various medical data.
In one embodiment, the plurality of medical data includes first medical data and second medical data, the plurality of dimensions includes a time dimension and an attribute dimension, and the dividing the medical data into the plurality of medical data according to the plurality of dimensions includes:
dividing the medical data into current medical data and non-current medical data according to a time dimension;
dividing the current medical data into second medical data and third medical data according to attribute dimensions;
and taking the third medical data and the non-current medical data as first medical data.
In one embodiment, the aggregating each medical data according to the preset time interval to obtain the medical indexes corresponding to the plurality of medical data includes:
extracting label data corresponding to each medical label from each medical data according to a preset time interval and a plurality of medical labels;
summarizing the extracted label data to obtain summarized data corresponding to each medical data;
And aggregating the summarized data corresponding to each medical data to obtain medical indexes corresponding to various medical data.
In one embodiment, the generating, by the preset private protocol, the medical message according to the medical indexes corresponding to the plurality of medical data includes:
acquiring a specific field corresponding to the data monitoring request based on a preset private protocol, wherein the preset private protocol is an application layer protocol obtained after optimization processing based on a transmission control protocol;
Acquiring message configuration information corresponding to the preset private protocol, wherein the message configuration information comprises header format information corresponding to the specific field;
Optimizing the specific field according to the header format information to obtain a specific optimized field with specific byte number;
And generating a message header according to the specific optimized field, taking medical indexes corresponding to various medical data as a message body, and generating a medical message according to the message header and the message body.
In one embodiment, the plurality of medical data includes first medical data and second medical data, the method further comprising:
storing the medical indexes corresponding to the first medical data into a relational database and storing the medical indexes corresponding to the second medical data into a time sequence database;
when a data query request of a webpage application server is received, extracting a corresponding target index from the relational database and the time sequence database according to the data query request;
Generating a target message according to the target index, and sending the target message to a webpage application server according to a preset private protocol.
A medical data monitoring device, the device comprising:
The communication module is used for acquiring a data monitoring request and acquiring medical data according to the data monitoring request;
The dividing module is used for dividing the medical data into a plurality of medical data according to a plurality of dimensions;
The aggregation module is used for aggregating each medical data according to a preset time interval to obtain medical indexes corresponding to various medical data;
the generation module is used for generating medical messages according to medical indexes corresponding to the plurality of medical data through a preset private protocol;
The communication module is further used for sending the medical message to a webpage application server, so that the webpage application server analyzes the medical message according to the preset private protocol to obtain medical indexes corresponding to various medical data.
In one embodiment, the partitioning module is further configured to partition the medical data into current medical data and non-current medical data according to a time dimension, partition the current medical data into second medical data and third medical data according to an attribute dimension, and use the third medical data and the non-current medical data as the first medical data.
In one embodiment, the aggregation module is further configured to extract tag data corresponding to each medical tag from each medical data according to a preset time interval and a plurality of medical tags, aggregate the extracted tag data to obtain aggregate data corresponding to each medical data, and aggregate the aggregate data corresponding to each medical data to obtain medical indexes corresponding to a plurality of medical data.
A computer device comprising a memory storing a computer program executable on the processor and a processor implementing the steps of the method embodiments described above when the computer program is executed by the processor.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the various method embodiments described above.
According to the medical data monitoring method, the medical data monitoring device, the computer equipment and the storage medium, the medical data are divided into a plurality of medical data according to the plurality of dimensions, each medical data is respectively aggregated according to the preset time interval, unnecessary repeated data processing operation can be reduced in a multi-dimensional mode, and the effectiveness of medical indexes is improved. Medical messages are generated according to medical indexes corresponding to various medical data through a preset private protocol, and the medical messages are sent to a webpage application server. Medical data can be effectively monitored in a multi-dimensional manner.
Detailed Description
The present application 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 application 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 application.
The medical data monitoring method provided by the application can be applied to an application environment shown in figure 1. Wherein web application server 102 communicates with job server 104 over a network. Job server 104 obtains the data monitoring request sent by web application server 102. The job server 104 acquires medical data according to the data monitoring request. The job server 104 divides the medical data into a plurality of medical data according to a plurality of dimensions. The job server 104 aggregates each medical data according to the preset time interval to obtain a medical index corresponding to each medical data. The job server 104 generates a medical message according to medical indexes corresponding to various medical data through a preset private protocol. The job server 104 sends the medical message to the web application server 102, so that the web application server 102 analyzes the medical message according to a preset private protocol to obtain medical index data corresponding to various medical data. The web application server 102 and the job server 104 may be implemented as separate servers or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, a medical data monitoring method is provided, and the method is applied to the job server in fig. 1 for illustration, and includes the following steps:
step 202, acquiring a data monitoring request, and acquiring medical data according to the data monitoring request.
The operation server acquires a data monitoring request sent by the webpage application server, wherein the data monitoring request is used for monitoring medical data so as to know the settlement condition of medical insurance. The webpage application server is used for receiving medical data monitored by the operation server. The job server obtains medical data according to the data monitoring request. The medical data may include disease data, time of stay, age, and the like. The medical data may be acquired in various ways, and may be acquired in GP (Green Plum) databases according to a data monitoring request, or may be acquired in a data queue system according to a data monitoring request.
Step 204, the medical data is divided into a plurality of medical data according to a plurality of dimensions.
And 206, aggregating each type of medical data according to a preset time interval to obtain medical indexes corresponding to various medical data.
The job server divides the medical data according to a plurality of dimensions. The dividing means may divide the medical data according to a preset dividing order among the plurality of dimensions. After the division in multiple dimensions, multiple medical data are obtained.
The job server calls a distributed task scheduling platform, and the job server is started according to a preset time interval through the distributed task scheduling platform to aggregate each medical data. The preset time intervals corresponding to the different kinds of medical data may be different. For example, the preset time interval may be 10mins or 24 hours. The operation server can aggregate each type of medical data according to the preset time interval and the medical label to obtain medical indexes corresponding to each type of medical data, and further obtain medical labels corresponding to a plurality of types of medical data. The medical label may include an annual cumulative settlement count, a current settlement count, annual cumulative medical resource data, current medical resource data, annual cumulative consumption data, current consumption data, annual cumulative record number, current newly added record number, disease name within a preset time period, patient burden within a preset time period, current patient burden, age distribution within a preset time period, number of visits, amount of visits, and the like. Wherein the number of notes may be registration data generated when the medical data is generated. The medical index may be a specific value corresponding to the medical label. Each medical data may correspond to a plurality of medical tags.
Step 208, generating a medical message according to medical indexes corresponding to various medical data through a preset private protocol.
The job server is preset with a preset private protocol. The preset private protocol may be an application layer protocol for data transmission service obtained by optimizing an application layer protocol based on a transmission control protocol. The preset private protocol is used for defining the message and the transmission mode which are mutually transmitted between the operation server and the webpage application server. The preset private protocol may be simply referred to as a private protocol. For example, the private protocol obtained after the optimization process can redefine the information such as the message structure and the message format corresponding to the various messages respectively. The multiple messages can comprise a login message, a medical message, an authentication message, a verification message and the like, and the structures of the multiple messages can be the same or different. Compared with the traditional application layer protocol, the optimized private protocol can simplify the message structure, and reduce the data volume of the message on the premise of not losing data, thereby effectively saving flow resources in the process of transmitting the message. The proprietary protocol may enable communication between servers based on a transmission control protocol. The transmission control protocol may be one of a plurality of transmission layer communication protocols.
The job server may obtain a specific field corresponding to the data monitoring request based on a proprietary protocol. The specific field may be a specified field included in the message structure defined by the private protocol after the optimization process. The operation server obtains message configuration information corresponding to the private protocol. The message configuration information may include message structure information and message format information, and the message structure information may include header structure information and message body structure information. Correspondingly, the message format information may include header format information and message format information. The operation server generates a message header according to the message configuration information, takes medical indexes corresponding to various medical data as a message body, and generates a medical message according to the message header and the message body.
Step 210, the medical message is sent to the web application server, so that the web application server analyzes the medical message according to the preset private protocol to obtain medical index data corresponding to various medical data.
The job server may send the generated medical message to the web application server through a communication channel between the job server and the web application server. The communication channel between the job server and the web application server may be connected according to a transport layer transmission control protocol corresponding to the private protocol. Specifically, the web application server is provided with the same private protocol as the job server, and the web application server can analyze the medical message according to the private protocol. The webpage application server can analyze the message header of the medical message to obtain version information in the message header, further determine a private protocol of a corresponding version according to the version information, and analyze the medical message through the private protocol with the same version. The webpage application server can determine the real index part in the message body according to the length of the medical index, avoid omission of index data and ensure the effectiveness of index data transmission. The webpage application server can respond to the operation corresponding to the request according to the request type, and route and forward the data according to the data monitoring request, so that communication with the operation server is realized, and further medical data is effectively monitored in a multi-dimensional mode.
In this embodiment, the job server divides the medical data into a plurality of medical data according to a plurality of dimensions, and aggregates each medical data according to a preset time interval, so that unnecessary repeated data processing operations can be reduced in a multi-dimensional manner, and the effectiveness of the medical index can be improved. The operation server generates medical messages according to medical indexes corresponding to various medical data through a preset private protocol and sends the medical messages to the webpage application server. Medical data can be effectively monitored in a multi-dimensional manner.
In one embodiment, as shown in FIG. 3, the step of dividing the medical data into a plurality of medical data according to a plurality of dimensions includes:
Step 302, medical data is divided into current medical data and non-current medical data according to a time dimension.
Step 304, the current medical data is divided into second medical data and third medical data according to the attribute dimension.
And 306, taking the third medical data and the non-current medical data as the first medical data.
The plurality of medical data includes first medical data and second medical data, the plurality of dimensions includes a time dimension and an attribute dimension, and dividing the medical data into the plurality of medical data according to the plurality of dimensions includes dividing the medical data into current medical data and non-current medical data according to the time dimension, dividing the current medical data into second medical data and third medical data according to the attribute dimension, and taking the third medical data and the non-current medical data as the first medical data.
The job server may divide the medical data into first medical data and second medical data according to a plurality of dimensions. The first medical data may include current medical data that is not frequently invoked as well as non-current medical data. The second medical data may include frequently recalled current medical data. Specifically, the job server divides the medical data into current medical data and non-current medical data according to a time dimension of the plurality of dimensions. The job server divides the current medical data into second medical data and third medical data according to the attribute dimension. The second medical data may include frequently invoked medical data. The third medical data may include medical data that is not frequently invoked. The attribute dimension may include attribute information of the medical data. The job server in turn takes the third medical data and the non-current medical data as the first medical data, thereby dividing the medical data into the first medical data and the second medical data. For example, when the attribute information of the current medical data is age, then the current medical data belongs to the third medical data. When the attribute information of the current medical data is a disease, the current medical data belongs to the second medical data.
In this embodiment, the job server divides the medical data into the first medical data and the second medical data according to the time dimension and the attribute dimension, and can convert the complex medical data into the simple medical data, so that aggregation is performed for each medical data respectively, and repeated operation during data aggregation is avoided. The method is further beneficial to improving the effectiveness of the medical indexes, so that the medical data is effectively monitored in a multi-dimensional mode.
In one embodiment, the step of aggregating each medical data according to the preset time interval to obtain the medical index corresponding to each medical data comprises the steps of extracting label data corresponding to each medical label from each medical data according to the preset time interval and a plurality of medical labels, summarizing the extracted label data to obtain summarized data corresponding to each medical data, and aggregating the summarized data corresponding to each medical data to obtain the medical index corresponding to a plurality of medical data.
The job server divides the medical data into a plurality of medical data. The plurality of medical data may include first medical data and second medical data. The first medical data may include current medical data that is not frequently invoked as well as non-current medical data. The second medical data may include frequently recalled current medical data. The preset time intervals for the job server to aggregate the plurality of medical data may be different. For example, the time interval for aggregating the first medical treatment may be 24 hours and the time interval for aggregating the second medical treatment data may be 10 minutes. The operation server extracts label data corresponding to each medical label from each medical data according to a preset time interval and a plurality of medical labels. Each medical data may correspond to a plurality of medical tags. For example, when the medical label is a visit, the job server may extract the visit from the medical data.
And the operation server gathers the extracted label data to obtain summarized data corresponding to each medical data. The operation server further arranges the summarized data corresponding to each medical data according to a preset sequence, and aggregates the arranged summarized data into one piece of data to obtain the medical index corresponding to each medical data. The operation server obtains the medical indexes corresponding to the plurality of medical data according to the medical indexes corresponding to each medical data. The medical index may be a specific value corresponding to the medical label. The medical index corresponding to the first medical data may include annual accumulated accounting personnel times, annual accumulated medical resource data, annual accumulated consumption data, annual accumulated record number, disease name in a preset time period, patient burden in a preset time period, age distribution in a preset time period, and the like. The medical indexes corresponding to the second medical data may include current settlement times, current medical resource data, current consumption data, current newly added record number, current patient burden, visit times, visit amount, and the like.
In this embodiment, the job server extracts the label data corresponding to each medical label from each medical data according to the preset time interval and the plurality of medical labels, so that the dynamic medical data can be processed in time. The operation server gathers and aggregates the label data, so that medical indexes corresponding to various medical data can be known, and effective monitoring of the medical data can be realized.
In one embodiment, generating the medical message according to the medical indexes corresponding to the plurality of medical data through the preset private protocol comprises the steps of acquiring a specific field corresponding to a data monitoring request based on the preset private protocol, acquiring message configuration information corresponding to the preset private protocol, wherein the message configuration information comprises header format information corresponding to the specific field, optimizing the specific field according to the header format information to obtain a specific optimized field with a specific byte number, generating a message header according to the specific optimized field, taking the medical indexes corresponding to the plurality of medical data as a message body, and generating the medical message according to the message header and the message body.
After the job server obtains the data monitoring request, the job server can analyze the data monitoring request according to the private protocol to obtain the request type corresponding to the data monitoring request. The request type may be marked with a corresponding type identification. The task type to which the data monitoring request corresponds may be one of a plurality of specific fields. The operation server can acquire medical data according to the data monitoring request, and acquire medical indexes after dividing and aggregating the medical data. The medical index may be text data uploaded to the job server by the user, and the text data may be a single character or a character string composed of a plurality of characters. The job server may count the data length corresponding to the medical index. For example, when the medical index is a character string, the job server may count the number of characters included in the character string. When the medical index is binary format data, the operation server can count the bit number of the binary data and determine the index length corresponding to the medical index.
The private protocol can be updated according to the actual service requirement, and the private protocol of the corresponding version is obtained after updating. After the private protocol is updated for a plurality of times, the private protocol corresponding to a plurality of versions can be obtained. The job server may obtain version information of the private protocol corresponding to the data monitoring request, where the version information may include a version identifier for marking the version information of the private protocol. The job server may obtain, according to the private protocol, a plurality of specific fields corresponding to the data monitoring request, where the specific fields include a request type corresponding to the data monitoring request, an index length corresponding to the medical index, and version information corresponding to the private protocol. In the conventional application layer protocol, the message structure also includes a large number of fields such as a request method, an application name, a uniform resource locator, and a connection attribute. Compared with the traditional message header, the specific fields acquired based on the private protocol only comprise partial fields, and unnecessary fields are removed, so that the data volume of the medical message is effectively reduced, and the communication resources of the operation server during the transmission of the medical message are saved.
The job server can obtain the message configuration information corresponding to the private protocol of the data monitoring request. The message configuration information corresponding to the private protocol records the configuration information of the messages corresponding to different request types. The job server may optimize the specific fields according to header format information in the message configuration information. Specifically, the job server may read field format information corresponding to each of the plurality of specific fields from the header format information, and optimize the corresponding specific field according to the field format information. The field format information may describe a data format required for a specific field. For example, the job server may optimize a particular field according to field format information, converting the particular field into binary format data. The field format information may also be recorded with the optimized data size corresponding to the specific field. The field format information may include the number of bytes occupied after optimizing the corresponding specific field, and the number of bytes occupied by each specific field may be fixed. And the job server optimizes the corresponding specific field according to the field format information to obtain the specific optimized field with specific byte number. Compared with the traditional mode, the method simplifies the number of bytes occupied by the specific field, effectively reduces the data volume of the medical message and reduces the communication cost of the operation server.
The job server can splice a plurality of optimized specific optimized fields according to the header structure information in the message configuration information to generate a message header. The specific optimization field of the message header may include and only includes the optimized request type, the indicator length, and the version information. The job server may obtain the serialization model and input the medical data into the serialization model. The serialization model may be a data processing model that the job server builds and trains according to a data serialization protocol. The data serialization Protocol may be a Protocol Buffer Protocol, which defines an efficient structured data exchange format, and the job server may establish a serialization model according to the Protocol Buffer Protocol. The operation server can call the serialization model to carry out serialization processing on the input medical indexes, convert the medical indexes into target indexes in binary formats corresponding to the message format information, and package the target indexes to obtain message bodies of the medical messages. After the operation server transmits the medical message to the webpage application server, the webpage application server can obtain a message body by analyzing the medical message, and perform deserialization processing on target indexes in the message body according to message format information corresponding to a private protocol, so as to obtain medical indexes uploaded by the operation server. Compared with the character string in the XML format, the binary format target index of the same data content has smaller data volume, the transmission speed in the transmission process is faster, and the communication resource consumed in the medical message transmission is reduced. Even if the network environment is poor, the smaller medical message can reduce the retransmission times, ensure the effectiveness of medical index transmission and reduce the communication cost. Moreover, the webpage application server can deserialize and restore the medical indexes only according to the message format information corresponding to the private protocol, so that the safety of the medical indexes is effectively improved.
In this embodiment, the job server obtains a specific field corresponding to the data monitoring request according to a preset private protocol, where the private protocol is an application layer protocol obtained after performing optimization processing. The operation server optimizes the specific fields according to the header format information in the message configuration information to obtain specific optimized fields with specific byte numbers, and generates the medical message according to the specific optimized fields and the medical indexes. The operation server sends the medical message to the webpage application server, so that the webpage application server analyzes the medical message to obtain medical indexes. The medical message is packaged according to the private protocol, and even if the medical message is leaked or intercepted, the medical message cannot be analyzed under the condition that the private protocol does not exist, so that the safety of medical indexes in the medical message is effectively improved. Compared with the traditional application layer protocol which comprises a message header structure with a large number of fields, each field comprises a large amount of data, in the embodiment, the structure of the message header is simplified, unnecessary fields are removed by acquiring part of specific fields, the specific fields are correspondingly optimized, bytes occupied by the fields are reduced, the data volume of the generated medical message is reduced, the communication resources consumed by the operation server when the medical message is transmitted are effectively reduced, and the communication cost of the operation server is reduced.
In one embodiment, the specific fields acquired by the job server may include a request type corresponding to the data monitoring request, an index length corresponding to the medical index, and version information corresponding to the private protocol. The operation server optimizes the specific fields according to the field format information corresponding to the specific fields respectively to obtain specific optimized fields in binary format, wherein the specific optimized fields comprise specific byte numbers, the optimized request type occupies 2 bytes, the optimized version information occupies 2 bytes, and the optimized index length occupies 4 bytes. The operation server optimizes the specific field through the message format information, can unify the data format of the specific field, simplifies the specific field, and obtains the specific optimized field with less bytes, and compared with the traditional message field, the operation server occupies a large number of bytes, thereby effectively reducing the data quantity contained in the specific field.
In one embodiment, the job server may also pre-process the medical index before encapsulating the medical index into a message body. Wherein, the operation server can adopt one or more of a plurality of pretreatment modes to process the medical index. For example, the preprocessing method of the job server may be compression processing of the medical index, encryption processing of the medical index, or a combination of compression processing and encryption processing.
Specifically, after the operation server counts the medical indexes to obtain the corresponding index lengths, the index lengths corresponding to the medical indexes can be compared with the preset values. The preset value may be a length value preset by the user according to actual requirements. When the index length is smaller than or equal to the preset value, the operation server can directly generate a message body according to the medical index. When the index length is greater than a preset value, the operation server can call a preset compression algorithm to compress the medical index, and a message body is generated according to the compressed medical index with smaller data volume. The preset compression algorithm may be one or more of a plurality of compression algorithms. For example, the compression algorithm may include an LZW (Lempel-Ziv-Welch Encoding) algorithm, a Huffman compression algorithm, and the like. The operation server compresses the medical indexes through a compression algorithm, so that the data volume of the corresponding message body is reduced, the communication resources consumed when the operation server transmits the medical message are reduced, and the communication cost of the operation server is reduced. The job server may also encrypt the medical index. The medical index subjected to the encryption processing may be a compressed medical index or an uncompressed medical index. The operation server can acquire a plurality of encryption algorithms to encrypt the medical indexes, and generates a corresponding message body according to the encrypted medical indexes. For example, the encryption algorithm may be an ECC (Elliptic curve cryptography, elliptic encryption algorithm) algorithm, may encrypt according to the AES (Advanced Encryption Standard ) standard, and may also invoke a combination of multiple encryption algorithms to encrypt the medical index.
In this embodiment, the job server may perform preprocessing on the medical index before generating the message body according to the medical index. The operation server compresses the medical indexes by calling a compression algorithm, and generates a message body according to the compressed medical indexes, so that the data volume of the corresponding message body is reduced, the communication resources consumed when the operation server transmits the medical messages are reduced, and the communication cost of the operation server is reduced. The operation server encrypts the medical indexes by calling an encryption algorithm, and generates a message body according to the encrypted medical indexes, so that even if the medical message is leaked or intercepted, the data in the message body cannot be decrypted, and the safety of the medical indexes in the medical message is effectively improved.
In one embodiment, the plurality of medical data comprises first medical data and second medical data, the method further comprises the steps of storing medical indexes corresponding to the first medical data in a relational database and storing medical indexes corresponding to the second medical data in a time sequence database, when a data query request of a webpage application server is received, extracting corresponding target indexes in the relational database and the time sequence database according to the data query request, generating a target message according to the target indexes, and sending the target message to the webpage application server according to a preset private protocol.
The operation server aggregates each type of medical data according to the preset time interval to obtain medical indexes corresponding to various medical data, and then the medical indexes can be stored. The medical index may include a medical index corresponding to the first medical data and a medical index corresponding to the second medical data. Specifically, the job server stores the medical index corresponding to the first medical data in the relational database, and stores the medical index corresponding to the second medical data in the time sequence database. For example, the relational database may be a mysql database or a postgresql database. The timing database may be pipelinedb database. The job server receives a data query request sent by the webpage application server. The data query request may be that the terminal sends the data query request to a web application server, which forwards the data query request to the job server. The webpage application server can receive a data query request sent by the terminal through the load balancer, and call the reverse proxy server according to the data query request to distribute the data query request to the job server. For example, the load balancer may be F5 and the reverse proxy may be nginnx.
The job server analyzes the data query request to obtain request parameters. And the job server extracts corresponding target indexes from the relational database and the time sequence database according to the request parameters. The operation server generates a target message according to the extracted target index, and then sends the target message to the webpage application server according to the private protocol. The webpage application server analyzes the medical message according to the private protocol to obtain medical indexes corresponding to various medical data. And the webpage application server further sends the medical index obtained through analysis to the terminal for display. For example, the displayed medical index corresponding to the first medical data may include an annual cumulative settlement count, annual cumulative medical resource data, annual cumulative consumption data, an annual cumulative record count, a disease name within a preset time period, a patient burden within a preset time period, an age distribution within a preset time period, and the like. Wherein the preset time period may be one week. The medical indexes corresponding to the displayed second medical data can comprise current settlement times, current medical resource data, current consumption data, current newly added record quantity, current patient burden, visit times, visit amount and the like.
In this embodiment, the job server stores the medical index corresponding to the first medical data in the relational database and stores the medical index corresponding to the second medical data in the time series database. Because the medical index corresponding to the first medical data does not need to be frequently called and possibly exists among a plurality of forms, the data query is performed among the plurality of forms. The relational database can establish association with the associated field, and when certain field data is modified, the field data associated with the relational database can be correspondingly and automatically modified, so that the consistency of the data can be ensured, and the accuracy of data query is further improved. In addition, the relational database is low cost. The medical indexes corresponding to the second medical data are the data which are frequently called at present, the data query frequency is high, and the time sequence database can reduce the query delay so as to ensure that the data query efficiency is improved.
It should be understood that, although the steps in the flowcharts of fig. 2 to 3 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-3 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
In one embodiment, as shown in FIG. 4, a medical data monitoring apparatus is provided, comprising a communication module 402, a partitioning module 404, an aggregation module 406, and a generation module 408, wherein:
The communication module 402 is configured to obtain a data monitoring request, and obtain medical data according to the data monitoring request.
The partitioning module 404 is configured to partition the medical data into a plurality of medical data according to a plurality of dimensions.
And the aggregation module 406 is configured to aggregate each type of medical data according to a preset time interval, so as to obtain medical indexes corresponding to multiple types of medical data.
The generating module 408 is configured to generate, according to the medical indexes corresponding to the multiple medical data, a medical message by using a preset private protocol.
The communication module 402 is further configured to send the medical message to a web application server, so that the web application server parses the medical message according to a preset private protocol to obtain medical indexes corresponding to multiple medical data.
In one embodiment, the partitioning module 404 is further configured to partition the medical data into current medical data and non-current medical data according to a time dimension, partition the current medical data into second medical data and third medical data according to an attribute dimension, and regard the third medical data and the non-current medical data as the first medical data.
In one embodiment, the aggregation module 406 is further configured to extract tag data corresponding to each medical tag from each medical data according to a preset time interval and a plurality of medical tags, aggregate the extracted tag data to obtain aggregate data corresponding to each medical data, and aggregate the aggregate data corresponding to each medical data to obtain medical indexes corresponding to a plurality of medical data.
In one embodiment, the generating module 408 is further configured to obtain a specific field corresponding to the data monitoring request based on a preset private protocol, where the preset private protocol is an application layer protocol obtained after optimization based on a transmission control protocol, obtain message configuration information corresponding to the preset private protocol, where the message configuration information includes header format information corresponding to the specific field, optimize the specific field according to the header format information to obtain a specific optimized field with a specific byte number, generate a message header according to the specific optimized field, and use medical indexes corresponding to multiple medical data as a message body, and generate a medical message according to the message header and the message body.
In one embodiment, the apparatus further comprises:
and the storage module is used for storing the medical indexes corresponding to the first medical data into the relational database and storing the medical indexes corresponding to the second medical data into the time sequence database.
And the extraction module is used for extracting corresponding target indexes from the relational database and the time sequence database according to the data query request when the data query request of the webpage application server is received.
The communication module 402 is further configured to generate a target message according to the target indicator, and send the target message to the web application server according to a preset private protocol.
For specific limitations of the medical data monitoring device, reference may be made to the above limitations of the medical data monitoring method, which are not repeated here. The various modules in the medical data monitoring device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store medical metrics. The network interface of the computer device is used to communicate with an external job server via a network connection. The computer program is executed by a processor to implement a medical data monitoring method.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor implementing steps in various method embodiments when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps in the respective method embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.