CN115620877A - Method, system, equipment and storage medium for uploading medical data to cloud platform - Google Patents
Method, system, equipment and storage medium for uploading medical data to cloud platform Download PDFInfo
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Abstract
The application provides the technical field of data acquisition, in particular to a method, a system, equipment and a storage medium for uploading medical data to a cloud platform, which comprise the following steps: acquiring medical data through a UI (user interface) of a distributed medical system; sending the medical data to a preset kafka message queue; according to the kafka message queue, consuming the medical data in batches to obtain consumed resource data and file data; and uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port. Through the use of the big data ecological component kafka distributed message queue, the handling of mass data acquisition is improved, the acquisition efficiency performance is improved, the acquired data are all stored in the kafka, and then the consumption service is used for batch consumption storage.
Description
Technical Field
The application relates to the technical field of data acquisition, in particular to a method, a system, equipment and a storage medium for uploading medical data to a cloud platform.
Background
The traditional acquisition tool only supports the acquisition of service data, DICOM images and reports, the illegal service data has no interface query, so that the reason why the illegal service data is illegal is unknown, the complementary acquisition and state verification of the DICOM images are not supported, and the DICOM images omitted in the middle acquisition have no way to be known and have no interface view.
And a distributed and highly available technical architecture design is not used, and once an acquisition program is abnormal, data acquisition cannot be carried out.
The information middleware is not used, the acquisition is too slow or cannot be supported due to massive business data and images, the acquisition efficiency is not high, and the like.
Only supports active collection, actively fetches data from a database in a polling mode, and cannot support the other side to push data.
Disclosure of Invention
In view of the problems, the present application is proposed to provide a medical data upload cloud platform method, system, device and storage medium that overcome or at least partially solve the problems, comprising:
a method for uploading medical data to a cloud platform, the method being used for collecting the medical data in combination with an interface and uploading the medical data to the cloud platform, and comprising:
acquiring medical data through a UI (user interface) of a distributed medical system; wherein the medical data comprises resource data and file data;
sending the medical data to a preset kafka message queue;
according to the kafka message queue, consuming the medical data in batches to obtain consumed resource data and file data;
and uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port.
Further, the method for performing data interaction with a service system and/or a third-party system through a unified data resource interface provided by the resource service port specifically includes:
when a service request of a service system is received, the UI interface for interaction is sent to the service system through a unified data resource interface provided by the resource service port according to the service request; and/or, when a service request of the third-party system is received, the UI interface for interaction is sent to the service system through the uniform data resource interface provided by the resource service port according to the service request;
and receiving service data and/or outputting request data through the UI.
Further, the step of acquiring medical data through the UI interface of the distributed medical system includes:
reading the medical data through a UI (user interface) of a distributed medical system, and processing the medical data in a structuralized mode, wherein the medical data comprises ultrasonic data, radiation data, endoscope data and pathological data of a PACS (picture archiving and communication system);
and acquiring the medical data after structured processing and/or receiving the pushed medical data after structured processing.
Further, the step of sending the medical data to a preset kafka message queue includes:
according to a preset scheduling rule, the resource data and the file data are scheduled in a distributed mode; specifically, receiving pushed resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; and/or; inquiring and collecting resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; the resource data comprises service data, process data and log data; the file data comprises report file data and image file data
And sending the resource data and the file data which are distributed and scheduled to a preset kafka message queue.
Further, the step before acquiring the medical data through the UI interface of the distributed medical system further includes:
deploying at least 2 sets of acquisition service points for transmitting the medical data, wherein the communication modes supported by the acquisition service points comprise Restful, kafak, micro-service, SFTP, FTP and Dicom;
and establishing the medical data with unified standards according to preset standards, wherein the unified standards comprise unified standards of medical digital image communication basic data sets, health information data metadirectories, health information data metadomain codes, electronic medical record basic data sets, examination and inspection records, health organization (organization) classification and codes.
Further, the step of consuming the medical data in batch according to the kafka message queue to obtain consumed resource data and file data includes:
checking the resource data and the file data in batch according to the kafka message queue;
and encrypting the file data after the verification is finished.
Further, the step of uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port includes:
carrying out validity verification on the received resource data and file data;
when the verification is passed, storing the data into a corresponding normal data table;
and when the data attribute in the normal data table is in a multi-mechanism mode, uploading the resource data and the service data to an ES + Base cloud database for distributed storage, or uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
Further, the method also comprises the following steps:
if the verification fails, storing the data into a corresponding abnormal data table;
and when the data attribute in the abnormal data table is in a multi-mechanism mode, uploading the resource data and the service data to an ES + Base cloud database for distributed storage, or uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
A medical data uploading cloud platform system for collecting medical data in combination with an interface and uploading the medical data to a cloud platform, comprising:
the data acquisition module is used for acquiring medical data through a distributed medical system UI interface; wherein the medical data comprises resource data and file data;
the queue management module is used for sending the medical data to a preset kafka message queue;
the data consumption module is used for consuming the medical data in batches according to the kafka message queue to obtain consumed resource data and file data;
and the data storage module is used for uploading the resource data to the distributed storage end through a preset resource service port and uploading the file data to the distributed storage end through a preset file service port.
An apparatus comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of the medical data upload cloud platform method as described above.
A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a medical data upload cloud platform method as described above.
The application has the following advantages:
in the embodiment of the application, medical data are acquired through a UI (user interface) of a distributed medical system; inserting the medical data into a preset kafka message queue; bulk consuming the medical data including resource data and file data according to the kafka message queue; and receiving resource data and file data through a preset resource service port and a preset file service port, and correspondingly uploading the resource data and the service data to a distributed storage terminal. Through the use of the big data ecological component kafka distributed message queue, the throughput of mass data acquisition is improved, the acquisition efficiency performance is improved, the acquired data are all stored in kafka, and then the consumption service is used for batch consumption storage.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings needed to be used in the description of the present application will be briefly introduced below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.
Fig. 1 is a flowchart illustrating steps of a method for uploading medical data to a cloud platform according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a medical data uploading cloud platform system according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
In any of the embodiments of the present application, PACS (Picture Archiving and Communication Systems, meaning image Archiving and Communication Systems), UI (User Interface), and DICOM (Digital Imaging and Communication in Medicine) are provided.
Referring to fig. 1, a method for uploading medical data to a cloud platform according to an embodiment of the present application is shown;
the method is used for collecting medical data in combination with an interface and uploading the medical data to a cloud platform, and comprises the following steps:
s110, acquiring medical data through a UI (user interface) of the distributed medical system; wherein the medical data comprises resource data and file data;
s120, sending the medical data to a preset kafka message queue;
s130, consuming the medical data in batches according to the kafka message queue to obtain consumed resource data and file data;
s140, uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port.
In the embodiment of the application, medical data are acquired through a distributed medical system UI interface; wherein the medical data comprises resource data and file data; sending the medical data to a preset kafka message queue; according to the kafka message queue, consuming the medical data in batches to obtain consumed resource data and file data; and uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port. Through the use of the big data ecological component kafka distributed message queue, the handling of mass data acquisition is improved, the acquisition efficiency performance is improved, the acquired data are all stored in the kafka, and then the consumption service is used for batch consumption storage.
A method for uploading medical data to the cloud platform in the present exemplary embodiment will be further described below.
Acquiring medical data through a distributed medical system UI interface as described in step S110; wherein the medical data comprises resource data and file data.
In an embodiment of the present application, a specific process of "acquiring medical data through a distributed medical system UI interface" in step S110 may be further described in conjunction with the following description.
Reading the medical data through a UI (user interface) of a distributed medical system, and processing the medical data in a structured mode, wherein the medical data comprises ultrasonic, radiation, endoscope and pathological data of a PACS (picture archiving and communication system); the structured data enables various data to have a uniform format, and high efficiency is improved.
Acquiring the medical data after structured processing and/or receiving the medical data after pushed structured processing according to the following steps.
It should be noted that the invention can support 2 docking modes, actively collect, receive and push, and enable hospitals to have more choices.
As an example, the step of acquiring medical data through the UI interface further includes: deploying at least 2 sets of acquisition service points for transmitting the medical data, wherein the communication modes supported by the acquisition service points comprise Restful, kafak, micro-service, SFTP, FTP and Dicom; the application supports various communication modes such as Restful, kafak, microservice, SFTP, FTP, dicom and the like.
And establishing the medical data with unified standards according to preset standards, wherein the unified standards comprise unified standards of medical digital image communication basic data sets, health information data metadirectories, health information data metadomain codes, electronic medical record basic data sets, examination and inspection records, health organization (organization) classification and codes. The method is characterized in that business data standardization is carried out by referring to national standards and health industry standards (WS 538-2017 medical digital image communication basic data sets, WS363-2011 health information data element catalogs, WS364-2011 health information data element value domain codes, WS445.4 electronic medical record basic data sets, fourth part inspection check records, WS 218-2002 health organization (organization) classification and codes, GB/T2260-2007 administrative division codes of the people's republic of China and GB/T12402-2000 economic type codes), and the problems of inconsistent business data value domains and difficult butt joint of various manufacturers are solved.
Transmitting the medical data to a preset kafka message queue as described in the step S120.
It should be noted that, in the present application, a big data medium price kafka message queue is used to meet the cloud requirement of massive medical data.
In an embodiment of the present application, the specific process of "sending the medical data to the preset kafka message queue" in step S120 may be further described in conjunction with the following description.
According to a preset scheduling rule, the resource data and the file data are scheduled in a distributed mode; specifically, receiving pushed resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; and/or; inquiring and collecting resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; the resource data comprises service data, process data and log data; the file data comprises report file data and image file data;
and sending the resource data and the file data which are distributed and scheduled to a preset kafka message queue as described in the following steps.
It should be noted that, in the present application, xxl-jobs distributed scheduling tasks are used to establish corresponding acquisition tasks for active acquisition, and the special effect of the scheduling framework is used to implement high availability of acquisition services, load balancing, and the like, so as to solve the problems that once an acquisition server is down, the services will not be available, and the like, such as: and 2 sets of collection services are deployed, 1 set of downtime is allowed, 3 sets of services are deployed, 2 sets of abnormal downtime are allowed, and the like, so that the high availability of the services is greatly ensured.
As an example, the resource data and the file data are distributively scheduled according to a preset scheduling rule;
receiving pushed resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; and/or; inquiring and collecting resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; the resource data comprises service data, process data and log data; the file data includes report file data and image file data.
And as shown in the step S130, the medical data is consumed in batch according to the kafka message queue, and consumed resource data and file data are obtained.
In an embodiment of the present application, the specific process of "batch consuming the medical data according to the kafka message queue, and obtaining consumed resource data and file data" in step S130 may be further described with reference to the following description.
Batch checking the resource data and the file data according to the kafka message queue as described in the following steps; and encrypting the file data after the verification is finished.
The method has the functions of state verification and automatic complementary acquisition of the report file and the image file. Specifically, the method comprises the following steps: inquiring whether the state of the check data is not equal to the uploaded data, and acquiring the image quantity of the JSON index and comparing the image quantity in the table informing the completion of the image; if equal, the status is changed to upload complete. The state of inequality is changed into uploading; if the uploading time is not equal to the current time and is less than 3 days, performing supplementary acquisition; if not, and the uploading time is more than the current time for 3 days, the state is changed into the uploading exception and the log is dropped.
In step S140, the resource data is uploaded to the distributed storage end through a preset resource service port, and the file data is uploaded to the distributed storage end through a preset file service port.
In an embodiment of the present application, a specific process of "uploading the resource data to the distributed storage end through the preset resource service port and uploading the file data to the distributed storage end through the preset file service port" in step S140 may be further described with reference to the following description.
Carrying out validity verification on the received resource data and file data as described in the following steps; when the verification is passed, storing the data into a corresponding normal data table; and when the data attribute in the normal data table is in a multi-mechanism mode, uploading the resource data and the service data to an ES + Base cloud database for distributed storage, or uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
In an embodiment of the application, when the verification fails, the data is stored in a corresponding abnormal data table; and when the data attribute in the abnormal data table is in a multi-mechanism mode, uploading the resource data and the service data to an ES + Base cloud database for distributed storage, or uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
It should be noted that, the data resource service designs two modes, a single hospital mode and a multi-hospital mode. Data of a single hospital goes to the cloud, considering that the data size is small and the hospital does not give too many servers, es and mysql are adopted for storage, and a multi-hospital mode is as follows: for example, the data of an area or an urban medical institution is cloud, the data volume is huge, distributed storage es and hbase are adopted to support dynamic expansion, and the search and word segmentation retrieval of massive data are realized by using an elastic search engine.
In an embodiment of the application, the data interaction between the unified data resource interface provided by the resource service port and the service system and the third-party system is performed, specifically, the data interaction between the unified data resource interface and the service system is performed through the service system.
The method and the device support active collection through tasks, and also support a mode that a Restful interface receives third-party push, so that interaction between service data and DICOM (digital imaging and communications in medicine) files and between report files is performed, and the problem of data docking of different manufacturers is solved.
It should be noted that in the present application, by collecting the task UI interface, all tasks can be managed through the interface, and the execution state, the execution log, and the like of each task can be checked through the interface; and through the abnormal data UI interface, the data which is not uploaded can be checked and reported through the interface, the data which is not uploaded by the image and the abnormal data information which is not passed through the verification can be checked and collected manually through the interface, such as the abnormal data checking of the report file, the abnormal data checking of the image file and the abnormal data checking of the service.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
Referring to fig. 2, a medical data uploading cloud platform system provided in an embodiment of the present application is shown;
the method specifically comprises the following steps:
a data acquisition module 210, configured to acquire medical data through a distributed medical system UI interface; wherein the medical data comprises resource data and file data;
the queue management module 220 is used for sending the medical data to a preset kafka message queue;
the data consumption module 230 is configured to consume the medical data in batches according to the kafka message queue to obtain consumed resource data and file data;
and the data storage module 240 is configured to upload the resource data to the distributed storage end through a preset resource service port, and upload the file data to the distributed storage end through a preset file service port.
In an embodiment of the present application, the data obtaining module 210 includes:
the structural sub-module reads the medical data through a UI (user interface) of the distributed medical system and structurally processes the medical data, wherein the medical data comprises ultrasonic, radiation, endoscope and pathological data of the PACS;
and the data acquisition submodule acquires the medical data after the structured processing and/or receives the pushed medical data after the structured processing.
In an embodiment of the present application, the queue management module 220 includes:
the scheduling submodule is used for scheduling the resource data and the file data in a distributed mode according to a preset scheduling rule; specifically, receiving pushed resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; and/or; inquiring and collecting resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; the resource data comprises service data, process data and log data; the file data comprises report file data and image file data;
and the data sending submodule is used for sending the resource data and the file data which are distributed and scheduled to a preset kafka message queue.
In an embodiment of the present application, the data consuming module 230 includes:
the verification submodule is used for verifying the resource data and the file data in batch according to the kafka message queue;
and the encryption sub-module is used for encrypting the file data after the verification is finished.
In an embodiment of the present application, the data storage module 240 includes:
the verification submodule is used for carrying out validity verification on the received resource data and the received file data;
the first judgment submodule is used for storing the verification result into a corresponding normal data table when the verification is passed;
and the first uploading storage submodule is used for uploading the resource data and the service data to an ES + Base cloud database for distributed storage when the data attribute in the normal data table is in a multi-mechanism mode, and otherwise, uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
Further comprising:
the second judgment submodule is used for storing the data into a corresponding abnormal data table if the verification fails;
and the second uploading storage submodule is used for uploading the resource data and the service data to an ES + Base cloud database for distributed storage when the data attribute in the abnormal data table is in a multi-mechanism mode, and otherwise, uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
In an embodiment of the present application, the method further includes:
and the business number system module is used for performing data interaction with the business system and the third-party system through the uniform data resource interface provided by the resource service port, and particularly, the business system is passed through.
In an embodiment of the present application, the method further includes:
the system deployment module is used for deploying at least 2 sets of acquisition service points for transmitting the medical data, wherein the communication modes supported by the acquisition service points comprise Restful, kafak, microservice, SFTP, FTP and Dicom;
and the data structure module is used for establishing the medical data with unified standards according to preset standards, wherein the unified standards comprise unified standards of medical digital image communication basic data sets, health information data metadirectories, health information data metadomain codes, electronic medical record basic data sets, examination and inspection records, health organization (organization) classification and codes.
Referring to fig. 3, a computer device of a method for uploading medical data to a cloud platform according to the present application is shown, which may specifically include the following:
the computer device 12 described above is embodied in the form of a general purpose computing device, and the components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 that couples various system components including the memory 28 and the processing unit 16.
The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory 30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (commonly referred to as "hard drives"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42, with the program modules 42 configured to carry out the functions of embodiments of the application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules 42, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally perform the functions and/or methodologies of the embodiments described herein.
The processing unit 16 executes programs stored in the memory 28 to execute various functional applications and data processing, for example, to implement a method for uploading medical data to a cloud platform provided in an embodiment of the present application.
That is, the processing unit 16 implements, when executing the program, the following: acquiring medical data through a UI (user interface) of a distributed medical system; wherein the medical data comprises resource data and file data; sending the medical data to a preset kafka message queue; according to the kafka message queue, consuming the medical data in batches to obtain consumed resource data and file data; and uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port.
In an embodiment of the present application, there is also provided a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements a method for uploading medical data to a cloud platform as provided in all embodiments of the present application.
That is, the program when executed by the processor implements: acquiring medical data through a UI (user interface) of a distributed medical system; wherein the medical data comprises resource data and file data; sending the medical data to a preset kafka message queue; according to the kafka message queue, consuming the medical data in batches to obtain consumed resource data and file data; and uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the operator's computer, partly on the operator's computer, as a stand-alone software package, partly on the operator's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the operator's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "include", "including" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device including a series of elements includes not only those elements but also other elements not explicitly listed or inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or terminal apparatus that comprises the element.
The foregoing has outlined rather broadly the principles and embodiments of the present application, and the detailed description of the embodiments has been presented to aid in the understanding of the methods and principles of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method for uploading medical data to a cloud platform, wherein the method is used for collecting the medical data in combination with an interface and uploading the medical data to the cloud platform, and comprises the following steps:
acquiring medical data through a UI (user interface) of a distributed medical system; wherein the medical data comprises resource data and file data;
sending the medical data to a preset kafka message queue;
according to the kafka message queue, consuming the medical data in batches to obtain consumed resource data and file data;
and uploading the resource data to a distributed storage end through a preset resource service port, and uploading the file data to the distributed storage end through a preset file service port.
2. The method according to claim 1, further comprising performing data interaction with a business system and/or a third-party system through a unified data resource interface provided by the resource service port, specifically including:
when a service request of a service system is received, the UI interface for interaction is sent to the service system through a unified data resource interface provided by the resource service port according to the service request; and/or, when a service request of the third-party system is received, the UI interface for interaction is sent to the service system through the uniform data resource interface provided by the resource service port according to the service request;
and receiving service data and/or outputting request data through the UI.
3. The method of claim 1, wherein the step of obtaining medical data via a distributed medical system UI interface comprises:
reading the medical data through a UI (user interface) of a distributed medical system, and processing the medical data in a structuralized mode, wherein the medical data comprises ultrasonic data, radiation data, endoscope data and pathological data of a PACS (picture archiving and communication system);
and acquiring the medical data after structured processing and/or receiving the pushed medical data after structured processing.
4. The method of claim 1, wherein said step of sending said medical data to a pre-defined kafka message queue comprises:
according to a preset scheduling rule, the resource data and the file data are scheduled in a distributed mode; specifically, receiving pushed resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; and/or; inquiring and collecting resource data and file data according to a preset task scheduling mechanism and a time sequence, and generating an SM3 value according to the file data; the resource data comprises service data, process data and log data; the file data comprises report file data and image file data;
and sending the resource data and the file data which are distributed and scheduled to a preset kafka message queue.
5. The method of claim 1, wherein the step prior to obtaining medical data via the distributed medical system UI interface further comprises:
deploying at least 2 sets of acquisition service points for transmitting the medical data, wherein the communication modes supported by the acquisition service points comprise Restful, kafak, micro-service, SFTP, FTP and Dicom;
and establishing the medical data with unified standards according to preset standards, wherein the unified standards comprise unified standards of medical digital image communication basic data sets, health information data metadirectories, health information data metadomain codes, electronic medical record basic data sets, examination and inspection records, health mechanism classification and codes.
6. The method of claim 1, wherein said step of bulk consuming said medical data to obtain consumed resource data and file data according to said kafka message queue comprises:
checking the resource data and the file data in batch according to the kafka message queue;
and encrypting the file data after the verification is finished.
7. The method according to claim 1, wherein the step of uploading the resource data to the distributed storage end through a preset resource service port and uploading the file data to the distributed storage end through a preset file service port comprises:
carrying out validity verification on the received resource data and file data;
when the verification is passed, storing the data into a corresponding normal data table;
and when the data attribute in the normal data table is in a multi-mechanism mode, uploading the resource data and the service data to an ES + Base cloud database for distributed storage, or uploading the resource data and the service data to the ES + MySQL cloud database for distributed storage.
8. A medical data uploading cloud platform system, wherein the system is used for collecting medical data in combination with an interface and uploading the medical data to a cloud platform, and comprises:
the data acquisition module is used for acquiring medical data through a UI (user interface) of the distributed medical system; wherein the medical data comprises resource data and file data;
the queue management module is used for sending the medical data to a preset kafka message queue;
the data consumption module is used for consuming the medical data in batches according to the kafka message queue to obtain consumed resource data and file data;
and the data storage module is used for uploading the resource data to the distributed storage end through a preset resource service port and uploading the file data to the distributed storage end through a preset file service port.
9. An apparatus comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, the computer program when executed by the processor implementing the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117198474A (en) * | 2023-11-06 | 2023-12-08 | 天河超级计算淮海分中心 | Medical image data real-time acquisition method, system, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117198474A (en) * | 2023-11-06 | 2023-12-08 | 天河超级计算淮海分中心 | Medical image data real-time acquisition method, system, electronic equipment and storage medium |
| CN117198474B (en) * | 2023-11-06 | 2024-03-01 | 天河超级计算淮海分中心 | Medical image data real-time acquisition method, system, electronic equipment and storage medium |
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