Business data processing method, uploading method and device, equipment, and storage medium

Abstract

The present embodiment relates to the field of digital medical technology, and discloses a business data processing method, upload method, device, equipment, and storage medium. The business data processing method includes: collecting business data from the hospital side and obtaining supervision data from the supervision platform; extracting features from the supervision data to obtain general supervision standards, wherein the general supervision standards include: a general supervision field group and a standard type corresponding to each hospital side; performing status verification screening on the business data to obtain verification data, wherein the verification data includes completion data; classifying and processing the verification data according to the standard type to obtain classified data corresponding to each hospital side; and performing standardized packaging and processing on the classified data according to the general supervision field group to obtain a general data packet corresponding to each hospital side. The business data processing method of the embodiment of the present application reduces the difficulty of the supervision platform on medical data and facilitates the supervision of medical data by the supervision platform.

Description

Technical Field

[0001] The present application relates to the field of digital medical technology, and in particular to a business data processing method, uploading method and device, equipment, and storage medium. Background Art

[0002] During actual operations, Internet hospitals need to accept the supervision platform appointed by the National Health Commission to conduct operations such as license acceptance and business data monitoring.

[0003] However, since each hospital and regulatory platform have different names and codes for the same data, it increases the difficulty for the regulatory platform to supervise medical data, resulting in the inability of the regulatory platform to effectively supervise medical data, leading to inaccurate assessments of the current medical situation. Summary of the invention

[0004] The main purpose of the embodiments of the present disclosure is to propose a business data processing method, uploading method and device, equipment, and storage medium to reduce the difficulty of the supervision platform on medical data and facilitate the supervision platform on medical data.

[0005] To achieve the above purpose, a first aspect of an embodiment of the present disclosure provides a business data processing method, including:

[0006] Collect business data from the hospital side and obtain regulatory data from the regulatory platform;

[0007] Extract features from the supervision data to obtain a general supervision standard, wherein the general supervision standard includes: a general supervision field group and a standard type corresponding to each hospital end;

[0008] Performing status verification screening on the business data to obtain verification data, wherein the verification data includes completion data;

[0009] Classify and process the verification data according to the standard type to obtain the classification data corresponding to each hospital end;

[0010] The classified data is packaged in a standardized manner according to the regulatory common field group to obtain a common data packet corresponding to each hospital end.

[0011] In some embodiments, feature extraction is performed on regulatory data to obtain a general regulatory standard, including:

[0012] Extract semantic features from regulatory data to obtain data fields;

[0013] Perform frequency statistics on data fields to obtain field frequencies;

[0014] The data fields are filtered according to the field frequency to obtain the regulatory common field group.

[0015] In some embodiments, extracting features from regulatory data to obtain a common regulatory standard further includes:

[0016] Extract correlation features from regulatory data to obtain correlation feature vectors that represent the correlation between each hospital and the regulatory platform;

[0017] The hospital-side and regulatory data are matched according to the associated feature vectors to obtain the standard type of each hospital-side.

[0018] In some embodiments, the state verification filter includes a first type of state verification filter and a second type of state verification filter;

[0019] Perform status verification and screening on business data to obtain verification data, including:

[0020] Performing a first-class status check and screening on the business data using the first-class status code to obtain first-class check data;

[0021] The first-category verification data is subjected to second-category status verification screening using the second-category status code to obtain verification data, wherein the first-category status code and the second-category status code are different status codes.

[0022] To achieve the above purpose, a second aspect of an embodiment of the present disclosure proposes a method for uploading business data, including:

[0023] Obtaining a general data packet from the hospital, wherein the general data packet is a data packet processed according to any one of the methods in the first aspect of the embodiment;

[0024] Obtain the data upload rules of the regulatory platform and the mapping rules between the regulatory platform and the hospital side;

[0025] Integrate and process the common data packets based on the mapping rules and the data upload rules to obtain the data packets to be uploaded;

[0026] Upload the data package to be uploaded.

[0027] In some embodiments, the mapping rules include encryption rules and custom processing rules;

[0028] Based on the mapping rules, the common data packets are integrated and processed to obtain the data packets to be uploaded, including:

[0029] Performing customized processing on the general data packet according to the customized processing rule to obtain a customized data packet;

[0030] Convert and process the customized data packet based on the data upload rule to obtain a reassembled data packet;

[0031] The reassembled data packet is encrypted according to the encryption rule to obtain the data packet to be uploaded.

[0032] To achieve the above-mentioned purpose, a third aspect of an embodiment of the present disclosure provides a service data processing device, including:

[0033] Collection module, used to collect business data from the hospital;

[0034] The collection module is also used to obtain regulatory data from the regulatory platform;

[0035] An extraction module is used to extract features from the supervision data to obtain a general supervision standard, wherein the general supervision standard includes: a general supervision field group and a standard type corresponding to each hospital end;

[0036] A verification and screening module, used to perform status verification and screening on business data to obtain verification data, wherein the verification data includes completion data;

[0037] The classification module is used to classify the verification data according to the standard type to obtain the classification data corresponding to each hospital end;

[0038] The first processing module is used to perform standardized encapsulation processing on the classified data according to the regulatory general field group to obtain a general data packet corresponding to each hospital end.

[0039] To achieve the above purpose, a fourth aspect of an embodiment of the present disclosure provides a service data uploading device, including:

[0040] A second acquisition module is used to acquire a general data packet at the hospital, wherein the general data packet is a data packet processed by any one of the methods in the first aspect of the embodiment;

[0041] The third acquisition module is used to obtain the data upload rules of the supervision platform and the mapping rules between the supervision platform and the hospital side;

[0042] The second processing module is used to integrate and process the common data packets based on the mapping rules and the data upload rules to obtain the data packets to be uploaded;

[0043] The upload module is used to upload the data package to be uploaded.

[0044] To achieve the above-mentioned purpose, a fifth aspect of the embodiments of the present disclosure provides an electronic device, including:

[0045] at least one memory;

[0046] at least one processor;

[0047] at least one program;

[0048] The program is stored in the memory, and the processor executes at least one program to implement the business data processing method of the embodiment of the present disclosure, such as the first aspect mentioned above, to implement the business data uploading method of the embodiment of the present disclosure, such as the second aspect mentioned above.

[0049] To achieve the above-mentioned purpose, a sixth aspect of the embodiments of the present disclosure provides a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute:

[0050] Such as the business data processing method of the first aspect and the business data uploading method of the second aspect.

[0051] The business data processing method, uploading method and apparatus, equipment and storage medium proposed in the embodiments of the present disclosure extract features from the supervision data of the supervision platform to obtain a supervision general field group and a standard type for each hospital end, perform status verification screening on the business data to obtain verification data, and then classify the verification data according to the standard type to obtain classified data corresponding to each hospital end, and then perform standardized packaging processing on the classified data according to the supervision general field, and package the data of each hospital end into a general data packet to facilitate the supervision of the general data packet by the supervision platform, thereby reducing the difficulty of the supervision platform on medical data and facilitating the supervision of medical data by the supervision platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a flowchart of the business data processing method provided in an embodiment of the present application.

[0053] Figure 2 yes Figure 1 Flowchart of step S200 in FIG.

[0054] Figure 3 yes Figure 1 Another flowchart of step S200 in FIG.

[0055] Figure 4 yes Figure 1 Flowchart of step S300 in FIG.

[0056] Figure 5 It is a flowchart of the business data uploading method provided in an embodiment of the present application.

[0057] Figure 6 yes Figure 5 Flowchart of step S800 in FIG.

[0058] Figure 7 It is a module block diagram of the business data processing device provided in an embodiment of the present application.

[0059] Figure 8It is a module block diagram of the business data uploading device provided in an embodiment of the present application.

[0060] Fig. 9 It is a schematic diagram of the hardware structure of the electronic device provided by the embodiment of the present disclosure. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0062] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0063] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0064] First, some nouns involved in this application are analyzed:

[0065] Artificial intelligence (AI) is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. AI is a branch of computer science that attempts to understand the essence of intelligence and produce a new type of intelligent machine that can respond in a similar way to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing and expert systems. AI can simulate the information process of human consciousness and thinking. AI is also a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0066] Natural language processing (NLP): NLP uses computers to process, understand and apply human languages ​​(such as Chinese, English, etc.). NLP is a branch of artificial intelligence and an interdisciplinary subject between computer science and linguistics. It is often referred to as computational linguistics. Natural language processing includes grammatical analysis, semantic analysis, and text comprehension. Natural language processing is often used in technical fields such as machine translation, handwritten and printed character recognition, speech recognition and text-to-speech conversion, information retrieval, information extraction and filtering, text classification and clustering, public opinion analysis and opinion mining. It involves data mining related to language processing, machine learning, knowledge acquisition, knowledge engineering, artificial intelligence research, and linguistic research related to language computing.

[0067] Medical cloud refers to the use of cloud computing to create a cloud platform for medical and health services based on new technologies such as cloud computing, mobile technology, multimedia, 4G communications, big data, and the Internet of Things, combined with medical technology, to achieve the sharing of medical resources and the expansion of medical scope. Because of the application of cloud computing technology, medical cloud improves the efficiency of medical institutions and facilitates residents to seek medical treatment. For example, hospital appointment registration, electronic medical records, and medical insurance are all products of the combination of cloud computing and the medical field. Medical cloud also has the advantages of data security, information sharing, dynamic expansion, and overall layout.

[0068] Convolutional Neural Networks (CNN) are a type of feedforward neural networks (FNN) that include convolution calculations and have a deep structure. They are one of the representative algorithms of deep learning. Since convolutional neural networks can perform shift-invariant classification, they are also called "shift-invariant artificial neural networks (SIANN)". The artificial neurons of convolutional neural networks can respond to surrounding units within a part of the coverage range, and they perform well in large-scale image processing. With the introduction of deep learning theory and the improvement of numerical computing equipment, convolutional neural networks have developed rapidly and have been applied to fields such as computer vision and natural language processing.

[0069] Dubbo: Dubbo is an open source, high-performance service framework that enables applications to implement service output and input functions through high-performance remote procedure calls (RPCs), and can be seamlessly integrated with the Spring framework. It mainly includes Remoting, RPC, and the registry service center (Registry). Remoting is a network communication framework that implements the sync-over-async and request-response mechanisms. RPC is an abstraction of remote procedure calls that supports load balancing, disaster recovery, and clustering. The registry service center is used for service registration and service time publishing and subscription.

[0070] Message Queue (MQ) is a data structure of "first in, first out" in the basic data structure. It is generally used to solve problems such as application decoupling, asynchronous messages, and traffic peak shaving, and to achieve high performance, high availability, scalability, and eventual consistency architecture. MQ (Message Queue) message queue is a data structure of "first in, first out" in the basic data structure. It means putting the data (message) to be transmitted in the queue, and using the queue mechanism to realize message transmission - the producer generates the message and puts the message into the queue, and then the consumer processes it. Consumers can pull messages from the specified queue, or subscribe to the corresponding queue, and the MQ server will push messages to them.

[0071] Extensible Markup Language (XML) is a simple data storage language. It uses a series of simple tags to describe data, and these tags can be created in a convenient way. Although the space occupied by the extensible markup language is more than that of binary data, the extensible markup language is extremely simple and easy to master and use.

[0072] JavaScript Object Notation (JSON) is a lightweight data exchange format. It is based on a subset of ECMAScript (the js specification developed by the European Computer Association) and uses a text format that is completely independent of the programming language to store and represent data. The simplicity and clear hierarchical structure make JSON an ideal data exchange language. It is easy for people to read and write, and it is also easy for machines to parse and generate, and it effectively improves network transmission efficiency.

[0073] Bean is a software model that describes JAVA. Injecting beans into the interceptor can ensure the performance and robustness of the original system when processing data.

[0074] fastjson is a JSON parser and generator developed by a company engineer based on JAVA, which can be used to convert Java objects to their JSON representation. It can also be used to convert JSON strings to equivalent Java objects. fastjson can process arbitrary Java objects, including pre-existing objects without source code.

[0075] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0076] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0077] Based on this, the embodiments of the present application provide a business data processing method, an uploading method and corresponding devices, so as to reduce the difficulty of the supervision platform on medical data and facilitate the supervision platform on medical data.

[0078] The business data processing method and uploading method provided in the embodiments of the present application relate to the field of artificial intelligence technology. The business data processing method and uploading method provided in the embodiments of the present application can be applied to the terminal, can also be applied to the server side, and can also be software running in the terminal or the server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, or a smart watch, etc.; the server side can be configured as an independent physical server, or it can be configured as a server cluster or distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN) and big data and artificial intelligence platforms and other basic cloud computing services. Cloud servers; software can be applications that implement business data processing methods and uploading methods, but are not limited to the above forms.

[0079] Refer to the following Figure 1 , the specific processing process of the business data processing method in this application is introduced in detail.

[0080] like Figure 1 As shown, in the first aspect, some embodiments of the present application provide a business data processing method, including step S100, step S200, step S300, step S400 and step S500. These five steps are described in detail below. It should be understood that the business data processing method of the present application includes but is not limited to steps 100 to S500.

[0081] Step S100: Collecting business data from the hospital and obtaining supervision data from the supervision platform;

[0082] Specifically, in step S100, the business data includes various prescription data, registration data, filing data, various appointment data (such as registration appointment, doctor appointment, etc.), consultation data, fee data, etc. There are multiple supervision platforms, and the supervision data includes the type of data that each supervision platform needs to supervise and the coding and field of each supervision platform for a certain type of business data. For example, for prescription data, the code of the prescription data of supervision platform A is 0001, and the field is the prescription. The code of the prescription data of supervision platform B is 002, and the field is the pharmaceutical prescription. Business data and supervision data can be obtained through message queue (MQ) message monitoring or Dubbo service framework. Data can be obtained directly from the medical cloud server or by other means. This application does not make specific restrictions.

[0083] Step S200: extracting features from the supervision data to obtain a general supervision standard, wherein the general supervision standard includes: a general supervision field group and a standard type corresponding to each hospital end;

[0084] In step S200, the general regulatory standard refers to a regulatory standard applicable to all regulatory platforms and the type of data that needs to be regulated in each hospital. A general regulatory standard can be obtained by extracting the commonalities of all regulatory platforms. Alternatively, the regulatory standard of a certain regulatory platform C can be specified as the general regulatory standard, and other regulatory platforms can be changed according to the regulatory standard of the regulatory platform C. This application does not impose any specific restrictions on this.

[0085] Step S300: performing status verification screening on the business data to obtain verification data, wherein the verification data includes completion data;

[0086] Step S400: classify the verification data according to the standard type to obtain the classification data corresponding to each hospital end;

[0087] In step S400, the standard type refers to the types of business data that need to be supervised in the hospital. For example, the registration data of hospital A does not need to be supervised, but the registration data of hospital B needs to be supervised. The types of data supervised by different hospitals are different. The verification data is classified and screened by the standard type to obtain the classification data corresponding to each hospital.

[0088] Step S500: Standardize and encapsulate the classified data according to the regulatory common field group to obtain a common data packet corresponding to each hospital end.

[0089] In step S500, the standardized encapsulation process includes coding and filling. Coding refers to matching and encoding all business data with the supervision general field group, and encoding the business data into the general coding code in the supervision general field group. Filling refers to filling the required items. For example, the registration data of hospital A does not need to be supervised, but the registration data of hospital B needs to be supervised. Then, when the standardized encapsulation process obtains the general data packet, since there is the registration data of hospital B that needs to be supervised, the registration data is a required item in the general data packet, and the registration data of hospital A needs to be filled. It can be filled with an irrelevant data, such as 0.

[0090] In the related art, since each Internet hospital has different codes and names for the same type of data, different hospitals have different types of regulatory data that need to be regulated, and different regulatory platforms have different codes and names for the same type of data, there is no universal regulatory platform to achieve unified supervision of hospital business data, and setting up multiple regulatory platforms will cause waste of resources and increase in operating costs. Based on this, the embodiment of the present application provides a business data processing method, which performs status verification screening on business data to obtain verification data, and then classifies and processes the verification data according to standard types to obtain classified data corresponding to each hospital end, and then standardizes and encapsulates the classified data according to the general regulatory fields, and encapsulates the data on each hospital end into a universal data packet, so that the regulatory platform can supervise the universal data packet, which reduces the difficulty of the regulatory platform to supervise medical data, facilitates the regulatory platform to supervise medical data, avoids waste of resources, reduces operating costs, and improves regulatory efficiency.

[0091] Combine the following Figure 2 The process of determining the regulatory general field group in the above S200 is described in detail.

[0092] like Figure 2As shown, step S200 includes step S210, step S220 and step S230. The following is a detailed description of these three steps. It should be understood that step S200 in this application includes but is not limited to step S210, step S220 and step S230.

[0093] Step S210: extracting semantic features from the supervision data to obtain data fields;

[0094] Specifically, in step S210, semantic features of the regulatory data can be extracted through a neural network (for example, a convolutional neural network CNN, a recurrent neural network RNN, or a Transformer layer) to obtain data fields. Semantic features of the regulatory data can also be extracted by means of manual screening and comparison to obtain data fields, and this application does not impose specific restrictions on this. Among them, the data field refers to the name or code of the same business data in the regulatory data. For example: for a certain business data A, the name or code A1, A2 can both represent the business data A, then A1, A2 are different data fields of business data A. By extracting semantic features from the regulatory data, the names or codes representing the same business data in the regulatory data are extracted.

[0095] Step S220: Perform frequency statistics on the data fields to obtain the field frequency;

[0096] Specifically, in step S220, the data fields obtained in the above step S210 are subjected to frequency statistics to obtain field frequencies. The field frequency refers to the frequency of occurrence of each data field in different regulatory platforms. For example: for a certain business data A, the name or code A1 and A2 can both represent the business data A, then A1 and A2 are different data fields of the business data A. In regulatory platform a, the name or code of the business data is A1, in regulatory platform b, the name or code of the business data is A2, and in regulatory platform c, the name or code of the business data is A2. The frequency of the data fields that appear is subjected to frequency statistics, and the field frequency of A1 is 1 / 3, and the field frequency of A2 is 2 / 3. By performing frequency statistics on the data fields, the frequency of occurrence of different data fields can be obtained.

[0097] Step S230: Filter the data fields according to the field frequency to obtain a regulatory general field group.

[0098] Specifically, in step S230, the data fields obtained in step S210 are screened according to the field frequency obtained in step S220 to obtain a common regulatory field group. A data field is selected from different data fields of the same type of business data as a common data field for all regulatory platforms and hospital ends to obtain a common regulatory field group. In the data field, the data field with the highest field frequency can be selected as a common data field, or the data field with the highest field frequency can be selected as a common data field. This application does not impose specific restrictions on this. For example: for a certain business data A, the name or code A1 and A2 can both represent the business data A, then A1 and A2 are different data fields of business data A. In regulatory platform a, the name or code of the business data is A1, in regulatory platform b, the name or code of the business data is A2, and in regulatory platform c, the name or code of the business data is A2. The frequency of the data fields that appear is counted, and the field frequency of A1 is 1 / 3, and the field frequency of A2 is 2 / 3. In this embodiment, A2 is selected as the common data field of business data A, and common data fields of various different business data constitute a supervision common field group.

[0099] Combine the following Figure 3 The process of determining the standard type in the above step S200 is described in detail.

[0100] like Figure 3 As shown, step S200 includes but is not limited to step S240 and step S250. The following describes these two steps in detail. It should be understood that in this application, step S200 includes but is not limited to step S240 and step S250.

[0101] Step S240: extracting correlation features from the supervision data to obtain correlation feature vectors representing the correlation relationship between each hospital terminal and the supervision platform;

[0102] Specifically, in step S240, the correlation feature extraction of the supervision data can be performed by a neural network (for example: convolutional neural network CNN and recurrent neural network RNN) to obtain a correlation feature vector, or the correlation feature extraction of the supervision data can be performed by manual screening to obtain a correlation feature vector. Among them, the correlation feature vector represents the correlation relationship between each hospital end and the supervision platform, and the correlation feature vector can be represented by an M*N feature matrix, or it can be in other forms, and this application does not make specific restrictions on this. For example: a hospital end has four business data that need to be supervised by three different supervision platforms, among which business data A and business data B are supervised by supervision platform a, business data C is supervised by supervision platform b, and business data D is supervised by supervision platform c. The supervision data of all supervision platforms are subjected to correlation feature extraction to obtain a correlation feature vector. In this embodiment, the correlation feature vector is represented by an M*N feature matrix, and the correlation feature vector can be represented as a 4*3 feature matrix. The correlation feature vector represents the correlation relationship between the hospital end and the supervision platform.

[0103] Step S250: Matching the hospital side and the supervision data is performed according to the associated feature vector to obtain the standard type of each hospital side.

[0104] Specifically, in step S250, the hospital side and the regulatory data are matched according to the associated feature vector obtained in the above step S240 to obtain the standard type of each hospital side. The standard type refers to the type of the hospital side that needs to be supervised, and the type of data that needs to be supervised by the hospital side and the regulatory standards of the corresponding regulatory platform. For example: the business data D of a hospital side includes data d1, d2 and d3. The business data D is supervised by the regulatory platform k. However, in the regulatory platform k, only data d1 and d2 are supervised, and data d3 is not supervised. In this case, the standard type of the hospital side has been determined. The hospital side and the regulatory data are matched according to the associated feature vector to obtain the standard type of the hospital side.

[0105] Combine the following Figure 4 The verification process of the status verification screening in the above step S300 is introduced in detail.

[0106] like Figure 4 As shown, the state verification screening includes the first state verification screening and the second state verification screening, and step S300 includes step S310 and step S320. The following describes these two steps in detail, and it should be understood that in this application, step S300 includes but is not limited to step S310 and step S320.

[0107] Step S310: performing a first-category status check and screening on the business data using the first-category status code to obtain first-category check data;

[0108] Step S320: Perform a second-type status check screening on the first-type verification data using the second-type status code to obtain verification data, wherein the first-type status code and the second-type status code are different status codes.

[0109] Specifically, in the present application, the first type of status verification screening is business verification screening, and the second type of status verification screening is process verification screening. A process includes several business data, each business data is provided with a business status completion code, i.e., the first type of status code, and each process is provided with a process status completion code, i.e., the second type of status code. The unterminated business data is filtered by the business status completion code unique to each business data, and the process status completion code unique to the process is used to determine whether the entire process is completely completed. For example: in the consultation process, the consultation process includes consultation business, doctor consultation business, prescription business, payment business, etc. Each business is provided with a business status completion code to determine whether the business is completed, such as using the doctor's signature as the business status completion code of the doctor's consultation business. In the consultation process, the payment business can be used as the process status completion code, or the doctor's signature can be used as the process status completion code. The business data is verified and screened through the business status verification screening and the process status verification screening to obtain verification data. Among them, the verification data includes completion data and pending completion data, which realizes the screening and classification of business data, so as to facilitate the subsequent packaging and processing of business data. Among them, completed data means that the entire process has been completed, and pending data means that the individual business data in the entire process is in a completed state, but some individual businesses are still in an unfinished state.

[0110] Reference Figure 5 In the second aspect, the embodiment of the present application further provides a method for uploading business data, including step S600, step S700, step S800 and step S900. The four steps are described in detail below. It should be understood that the method for uploading business data of the present application includes but is not limited to step S600, step S700, step S800 and step S900.

[0111] Step S600: Acquire a general data packet from the hospital, wherein the general data packet is a general data packet processed by the business data processing method according to any one of the embodiments of the first aspect;

[0112] In step S600, a general data packet obtained by the business data processing method of the first aspect is obtained, and the general data packet is applicable to the regulatory standards of all regulatory platforms.

[0113] Step S700: Obtaining data upload rules of the supervision platform and mapping rules between the supervision platform and the hospital side;

[0114] Specifically, in step S700, since each regulatory platform and hospital is located in a different region, the relevant policies of each region are also different, resulting in differences in the data upload rules of the regulatory platform and the mapping rules between the regulatory platform and the hospital. Even if the universal data package is applicable to the regulatory standards of all regulatory platforms, the universal data package cannot be directly uploaded to the regulatory platform, and it is necessary to obtain the data upload rules of the regulatory platform and the mapping rules between the regulatory platform and the hospital.

[0115] Step S800: integrating and processing the common data packet based on the mapping rule and the data upload rule to obtain the data packet to be uploaded;

[0116] Step S900: Upload the data package to be uploaded.

[0117] In step S900, the data packet to be uploaded on the hospital side is uploaded to the corresponding supervision platform, so that the supervision platform can supervise the medical data on the hospital side. After uploading the data packet to be uploaded, the data packet to be uploaded can also be archived persistently. For example: upload the data packet to be uploaded to the medical cloud server, keep the data packet to be uploaded in the medical cloud server continuously, or keep the data packet to be uploaded locally, so as to facilitate the query, management, analysis, monitoring and statistics of the data later.

[0118] The business data uploading method of the embodiment of the present application not only uses a universal data package applicable to the regulatory standards of all regulatory platforms, but also takes into account the data uploading rules of regulatory platforms in different regions and the mapping rules between the regulatory platform and the hospital side, thereby facilitating the supervision of medical data and reducing the difficulty of supervision of medical data by the regulatory platform.

[0119] Combine the following Figure 6 The integration process of the above step S800 is described in detail.

[0120] like Figure 6 As shown, the mapping rules include encryption rules and custom processing rules, and step S800 includes step S810, step S820 and step S830. The following describes these three steps in detail. It should be understood that in this application, step S800 includes but is not limited to step S810, step S820 and step S830.

[0121] Step S810: performing custom processing on the general data packet according to the custom processing rule to obtain a custom data packet;

[0122] In step S810, due to regional differences, the policies of hospitals in different regions are different, and the regulatory policies of the regulatory platform for hospitals are also different. Therefore, it is necessary to process the general data packet according to these policies. Customized processing rules refer to the different policies on the hospital side and the regulatory policies of the regulatory platform. By customizing the general data packet, a customized data packet applicable to the policy is obtained, which facilitates the supervision of medical data by the regulatory platform and reduces the difficulty of supervision. Specifically, according to the customized interceptor bean, the general data packet can be customized from the perspective of the hospital according to the customized processing rules.

[0123] Step S820: converting the customized data packet based on the data upload rule to obtain a reassembled data packet;

[0124] Specifically, in step S820, regulatory platforms in different regions have different rules for uploading customized data packets. At the same time, some general data packets have been customized, which may cause the general data packets to not conform to the uploaded format type, etc. Therefore, it is necessary to convert the customized data packets according to the data upload rules. The conversion process includes but is not limited to changing the file type, adding or deleting special suffixes (such as CA signatures), changing the data format, etc. For example: some regulatory platforms need to upload data packets that contain CA signature information. At this time, the data packets that do not originally have CA signature information need to be processed to add CA signature information. For example, the customized data packet is in the form of bean+Json, but it may not be suitable for some regulatory platforms. By disassembling and reassembling the customized data packet, the customized data packet is converted into XML format, or fast+Json and other message modes to be compatible with the regulatory requirements of different regulatory platforms.

[0125] Step S830: Encrypt the reassembled data packet according to the encryption rule to obtain the data packet to be uploaded.

[0126] Specifically, in step S830, the encryption rules include but are not limited to different encryption methods such as symmetric encryption, asymmetric encryption and token verification. In addition, during the encryption process, the secret key, entry IP or token are dynamically configured according to the hospital side, and the secret keys of different hospitals are different to enhance the security of the data packets to be uploaded.

[0127] Reference Figure 7In the third aspect, some embodiments of the present application further provide a business data processing device, including a collection module 701, an extraction module 702, a verification and screening module 703, a classification module 704 and a first processing module 705. Among them: the collection module 701 is used to collect the business data of the hospital side, and is also used to obtain the supervision data of the supervision platform; the extraction module 702 is used to extract features from the supervision data to obtain the general supervision standard, wherein the general supervision standard includes: a general supervision field group and a standard type corresponding to each hospital side; the verification and screening module 703 is used to perform status verification and screening on the business data to obtain verification data, wherein the verification data includes completion data; the classification module 704 is used to classify the verification data according to the standard type to obtain the classified data corresponding to each hospital side; the first processing module 705 is used to perform standardized encapsulation processing on the classified data according to the general supervision field group to obtain a general data packet corresponding to each hospital side.

[0128] The embodiment of the present application provides a business data processing device, which performs status verification and screening on business data to obtain verification data, then classifies and processes the verification data according to standard types to obtain classified data corresponding to each hospital end, and then performs standardized packaging processing on the classified data according to the general supervision fields, and packages the data of each hospital end into a general data packet to facilitate the supervision of the general data packet by the supervision platform, thereby reducing the difficulty of the supervision platform in supervising medical data, facilitating the supervision of medical data by the supervision platform, avoiding waste of resources, reducing operating costs, and improving supervision efficiency.

[0129] It should be noted that the processing process of the business data processing device of the embodiment of the present application is consistent with the business data processing method in the first aspect mentioned above. For the specific processing process, please refer to the aforementioned business data processing method, which will not be repeated here.

[0130] Reference Figure 8 In the fourth aspect, the embodiment of the present application further proposes a business data uploading device, including a first acquisition module 801, a second acquisition module 802, a second processing module 803 and an uploading module 804. Among them: the first acquisition module 801 is used to obtain a general data packet from the hospital side, wherein the general data packet is a data packet processed according to any one of the business data processing methods in the first aspect; the second acquisition module 802 is used to obtain the data upload rules of the supervision platform and the mapping rules between the supervision platform and the hospital side; the second processing module 803 is used to integrate and process the general data packet based on the mapping rules and the data upload rules to obtain the data packet to be uploaded; the uploading module 804 is used to upload the data packet to be uploaded.

[0131] The business data uploading device of the embodiment of the present application not only uses a universal data packet applicable to the regulatory standards of all regulatory platforms, but also takes into account the data uploading rules of regulatory platforms in different regions and the mapping rules between the regulatory platform and the hospital side, thereby facilitating the supervision of medical data and reducing the difficulty of supervision of medical data by the regulatory platform.

[0132] It should be noted that the processing process of the business data uploading device in the embodiment of the present application is consistent with the business data uploading method in the aforementioned second aspect. For the specific processing process, please refer to the aforementioned data uploading method, which will not be repeated here.

[0133] The present disclosure also provides an electronic device, including:

[0134] at least one memory;

[0135] at least one processor;

[0136] at least one program;

[0137] The program is stored in the memory, and the processor executes at least one program to implement the business data processing method and business data uploading method of the present disclosure. The electronic device can be any intelligent terminal including a mobile phone, a tablet computer, a personal digital assistant (PDA), a car computer, etc.

[0138] Combine the following Fig. 9 The electronic device according to the embodiment of the present application is introduced in detail.

[0139] like Fig. 9 , Fig. 9 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0140] The processor 901 may be implemented by a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present disclosure;

[0141] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solution provided in the embodiments of this specification is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the business data processing method and the business data uploading method of the embodiments of this disclosure;

[0142] Input / output interface 903, used to implement information input and output;

[0143] Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized by wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.); and

[0144] A bus 905 that transmits information between various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0145] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0146] The embodiment of the present disclosure also provides a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned business data processing method and business data uploading method.

[0147] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0148] The embodiments described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0149] It can be understood by those skilled in the art that Figure 1-6 The technical solutions shown in the figure do not constitute a limitation on the embodiments of the present disclosure, and may include more or fewer steps than those shown in the figure, or a combination of certain steps, or different steps.

[0150] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0152] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0153] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0154] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0155] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0156] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0157] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store programs.

[0158] The preferred embodiments of the present disclosure are described above with reference to the accompanying drawings, but the scope of the rights of the present disclosure is not limited thereto. Any modification, equivalent substitution and improvement made by those skilled in the art without departing from the scope and essence of the present disclosure should be within the scope of the rights of the present disclosure.

Claims

1. A business data processing method, characterized in that: include: Collect business data from the hospital side and obtain regulatory data from the regulatory platform; Extracting features from the supervision data to obtain a general supervision standard, wherein the general supervision standard includes: a general supervision field group and a standard type corresponding to each hospital end; Performing status verification screening on the business data to obtain verification data; Classify the verification data according to the standard type to obtain classification data corresponding to each hospital end; Performing standardized encapsulation processing on the classified data according to the regulatory general field group to obtain a general data packet corresponding to each hospital end; The feature extraction of the regulatory data to obtain the general regulatory standard includes: Extracting semantic features from the regulatory data to obtain data fields; Performing frequency statistics on the data fields to obtain field frequencies; Filtering the data fields according to the field frequency to obtain the regulatory general field group; Extracting correlation features from the supervision data to obtain correlation feature vectors representing the correlation relationship between each hospital end and the supervision platform; The hospital side and the supervision data are matched according to the associated feature vector to obtain a standard type of each hospital side.

2. The method according to claim 1, characterized in that The state verification screening includes a first type of state verification screening and a second type of state verification screening; The performing status verification and screening on the business data to obtain verification data includes: Performing a first-class status check and screening on the business data using the first-class status code to obtain first-class check data; The first-category verification data is subjected to second-category status verification screening using a second-category status code to obtain the verification data, wherein the first-category status code and the second-category status code are different status codes.

3. A method for uploading business data, characterized in that: include: Acquire a general data packet from the hospital, wherein the general data packet is a data packet processed by the method according to any one of claims 1 to 2; Obtaining data upload rules of the supervision platform and mapping rules between the supervision platform and the hospital side; Integrate the common data packet based on the mapping rule and the data upload rule to obtain a data packet to be uploaded; Upload the data packet to be uploaded.

4. The method according to claim 3, characterized in that The mapping rules include encryption rules and customized processing rules; The integrating and processing the general data packet based on the mapping rule to obtain the data packet to be uploaded includes: Performing customized processing on the general data packet according to the customized processing rule to obtain a customized data packet; Converting the customized data packet based on the data upload rule to obtain a reassembled data packet; The reassembled data packet is encrypted according to the encryption rule to obtain a data packet to be uploaded.

5. A business data processing device, characterized in that: include: Collection module, used to collect business data from the hospital; The collection module is also used to obtain regulatory data from the regulatory platform; An extraction module is used to extract features from the supervision data to obtain a general supervision standard, wherein the general supervision standard includes: a general supervision field group and a standard type corresponding to each hospital end; A verification and screening module, used for performing status verification and screening on the business data to obtain verification data; A classification module, used for classifying the verification data according to the standard type to obtain classification data corresponding to each hospital end; A first processing module, configured to perform standardized encapsulation processing on the classified data according to the regulatory general field group, so as to obtain a general data packet corresponding to each hospital end; The extraction module is used to extract features from the regulatory data to obtain the general regulatory standards, including: Extracting semantic features from the regulatory data to obtain data fields; Performing frequency statistics on the data fields to obtain field frequencies; Filtering the data fields according to the field frequency to obtain the regulatory general field group; Extracting correlation features from the supervision data to obtain correlation feature vectors representing the correlation relationship between each hospital end and the supervision platform; The hospital side and the supervision data are matched according to the associated feature vector to obtain a standard type of each hospital side.

6. A business data uploading device, characterized in that: include: A first acquisition module, acquiring a common data packet at the hospital end, wherein the common data packet is a data packet processed according to the method according to any one of claims 1 to 2; A second acquisition module is used to acquire data upload rules of the supervision platform and mapping rules between the supervision platform and the hospital side; A second processing module, configured to integrate the common data packet based on the mapping rule and the data upload rule to obtain a data packet to be uploaded; The uploading module is used to upload the data package to be uploaded.

7. An electronic device, characterized in that: include: at least one memory; at least one processor; at least one program; The program is stored in the memory, and the processor executes at least one program to implement: The business data processing method according to any one of claims 1 to 2; or The business data uploading method as described in any one of claims 3 to 4.

8. A storage medium, the storage medium being a computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to cause a computer to execute: The business data processing method according to any one of claims 1 to 2; or The business data uploading method as described in any one of claims 3 to 4.

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