CN112735555A - Rare disease data acquisition and reporting method and system - Google Patents
Rare disease data acquisition and reporting method and system Download PDFInfo
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Abstract
The invention discloses a rare disease data acquisition and reporting method and a rare disease data acquisition and reporting system, wherein diagnosis conclusions input by a doctor client in an HIS (medical advanced system), an electronic medical record system and a medical record system are obtained according to a set time interval, diagnosis keywords are extracted from the diagnosis conclusions, the diagnosis keywords are matched with rare disease nouns in a rare disease dictionary, and if the matching is successful, an electronic filling card of rare diseases is sent to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client; the hospital client side checks the authenticity, consistency and accuracy of the data of the received electronic filling card, analyzes the electronic filling card if the check is passed, and uploads the analyzed data to a provincial platform data center; and uploading the provincial platform data center to a national platform data center.
Description
Technical Field
The application relates to the technical field of rare disease data processing, in particular to a rare disease data acquisition and reporting method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
In the process of implementing the present application, the inventors found that the following technical problems exist in the prior art:
with the progress and rapid development of medical diagnosis and treatment level and diagnosis technology, the national attention to rare diseases brings a place of high importance, according to the definition of the world health organization to rare diseases, the disease is the disease with the number of ill people accounting for 0.65 per thousand to 1 per thousand of the total population, the small number of rare patients and the relative dispersion of the patients are the biggest fundamental obstacles for the diagnosis, treatment, clinical test and research of rare diseases; to realize the integration of patient information which is scattered in each medical institution and can not meet the requirements of clinical trial quantity, the establishment of a data centralized platform is required to form the collaborative and effective sharing of case resource information.
Rare case information at the hospital end is dispersed in each system in the prior art, related information of rare cases is acquired, only rare case information registration cards are filled in manually, Excel data are exported through a case system and then manually entered, and no method and system for data collection of a data concentration platform exist, so that incomplete information filling, illegible handwriting recognition, information registration card loss, time-consuming and tedious data statistics and rare manpower and time waste can often occur.
Disclosure of Invention
In order to overcome the defects of the prior art, the application provides a rare disease data acquisition and reporting method and system;
in a first aspect, the application provides a rare disease data acquisition and reporting method;
the rare disease data acquisition and reporting method comprises the following steps:
acquiring diagnosis conclusions input by a doctor client in an HIS (medical science and technology system), an electronic medical record system and/or a medical record system according to a set time interval, extracting diagnosis keywords from the diagnosis conclusions, matching the diagnosis keywords with rare disease terms in a pre-constructed rare disease dictionary, and if matching is successful, sending a rare disease electronic filling card to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client;
the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card, if the data authenticity check, the data consistency check and the data accuracy check are passed, the hospital client analyzes the rare disease electronic filling card, stores the analyzed data into a hospital client data center database, and finally uploads the data to a provincial platform data center by the hospital client;
and the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center.
In a second aspect, the application provides a rare disease data acquisition and reporting system;
rare disease data acquisition and reporting system includes: the system comprises a doctor client, a hospital client, a provincial platform data center and a national platform data center;
acquiring diagnosis conclusions input by a doctor client in an HIS (medical science and technology system), an electronic medical record system and/or a medical record system according to a set time interval, extracting diagnosis keywords from the diagnosis conclusions, matching the diagnosis keywords with rare disease terms in a pre-constructed rare disease dictionary, and if matching is successful, sending a rare disease electronic filling card to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client;
the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card, if the data authenticity check, the data consistency check and the data accuracy check are passed, the hospital client analyzes the rare disease electronic filling card, stores the analyzed data into a hospital client data center database, and finally uploads the data to a provincial platform data center by the hospital client;
and the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center.
Compared with the prior art, the beneficial effects of this application are:
the method comprises the steps that rare disease information is collected through a hospital client, and is reported to a provincial data center server, and then is reported to a national rare disease data center server through the provincial data center server; the centralized collection and management of rare disease data can be realized, the labor cost reported by doctors in hospitals is saved, and the real-time property, the reporting efficiency and the data accuracy of rare disease reporting are improved;
by arranging the rare disease electronic filling and writing card, the work intensity of filling of doctors can be saved, and the speed and the integrity of rare disease information acquisition are improved;
according to the method and the device, integrity verification, data authenticity verification, data consistency verification and data accuracy verification are set, so that the integrity, authenticity, consistency and accuracy of rare disease information collection can be guaranteed.
According to the application, after the analyzed data are encrypted, the data are uploaded to a national platform data center, the safety in the rare disease data transmission process can be guaranteed, and privacy disclosure of a patient is avoided.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a flow chart of a method of the first embodiment;
FIG. 2 is a diagram of a system architecture according to a second embodiment.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and it should be understood that the terms "comprises" and "comprising", and any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
Example one
The embodiment provides a rare disease data acquisition and reporting method;
as shown in fig. 1, the rare disease data acquisition and reporting method includes:
s101: acquiring diagnosis conclusions input by a doctor client in an HIS (medical science and technology system), an electronic medical record system and/or a medical record system according to a set time interval, extracting diagnosis keywords from the diagnosis conclusions, matching the diagnosis keywords with rare disease terms in a pre-constructed rare disease dictionary, and if matching is successful, sending a rare disease electronic filling card to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client;
s102: the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card, if the data authenticity check, the data consistency check and the data accuracy check are passed, the hospital client analyzes the rare disease electronic filling card, stores the analyzed data into a hospital client data center database, and finally uploads the data to a provincial platform data center by the hospital client;
s103: and the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center.
Further, the step S101: acquiring a diagnosis conclusion input by a doctor client in an HIS system, an electronic medical record system and/or a medical record system according to a set time interval; the method comprises the following specific steps: actively polling a diagnosis conclusion input by a doctor client in an HIS system or an electronic medical record system according to a set time interval, and marking the case as polled when the case is found to be polled once; for the polled case, the data is not included in the screening range in the next polling process, and the polling efficiency is improved.
In the active polling process, if it is found that polling is not finished yet, but the polling time exceeds a set time range (for example, the polling time threshold set by the HIS system is 30 seconds, the set time range is 20 seconds), polling is suspended, a case currently being polled is temporarily stored, and after the HIS system allows to continue polling, polling is continued only from the temporarily stored case without starting polling from the first case, so that long-time interference on the operation of the HIS system is avoided.
It should be understood that through active polling, careless omission that doctors forget to report rare disease information in time due to busy work or lack of experience can be avoided, and the work intensity of the doctors is also reduced.
Further, the step S101: extracting diagnosis keywords from the diagnosis conclusion; the method comprises the following specific steps:
s101a 1: a doctor client acquires and stores a diagnosis conclusion input by a doctor in the HIS system to generate a case view;
s101a 2: the method comprises the steps that cases in case views are analyzed one by one, different descriptions possibly appear in case information for the same diagnosis, a doctor client removes punctuation marks appearing in the diagnosis by using a regular expression, then word segmentation is carried out, words after word segmentation are all input into a pre-trained neural network model, and diagnosis keywords are output.
Further, the training step of the pre-trained neural network model comprises:
constructing a training set, wherein the training set is a diagnosis record corresponding to a plurality of known diagnosis keywords;
preprocessing a training set, wherein the preprocessing refers to that known diagnosis keywords are used as labels, and each diagnosis record is subjected to punctuation removal and word segmentation processing to obtain a plurality of words corresponding to each diagnosis record; taking each vocabulary as a node, if any two vocabularies have adjacent occurrence conditions in the diagnostic record, connecting two nodes corresponding to the two vocabularies, taking the times of simultaneous occurrence as the weight of the connection, and establishing an undirected weighted graph; representing the undirected weighted graph as an adjacency matrix; obtaining the vector representation of each node in the undirected weighted graph, and carrying out weighted summation on the vector representations of all the nodes to obtain the final vector representation of the undirected weighted graph;
and inputting the final vector representation of the undirected weighted graph into a neural network model, training the neural network model by taking the known diagnosis keywords as labels of the neural network model, and stopping training when the loss function of the neural network model reaches the minimum value to obtain the trained neural network model.
It should be understood that the undirected weighted graph can not only represent the relationship among various words in the diagnosis record, but also extract the structural features in the diagnosis record, and the undirected weighted graph can express the features of one diagnosis record more clearly without the final vector representation.
The diagnosis keywords are medical nouns. For example: albinism, acromegaly, phenylketonuria, mitochondrial disease.
Further, the step S101: matching the diagnosis keywords with the rare disease names in a pre-constructed rare disease dictionary, wherein the pre-constructed rare disease dictionary comprises the following specific construction steps:
s101b 1: classifying the rare diseases;
s101b 2: arranging the rare disease full name, short name and ICD codes according to the national rare disease catalogue;
s101b 3: and constructing a rare disease database dictionary table according to rare disease classification, rare disease full name, rare disease short name and ICD codes.
Further, the step S101: matching the diagnosis keywords with the rare disease name words in a pre-constructed rare disease dictionary, wherein the matching refers to:
the diagnosis keywords are completely matched with the rare disease dictionary full-name; the diagnosis keywords are completely matched with rare diseases for short; the diagnosis keywords are in full-scale fuzzy matching with the rare disease dictionary; and/or, the diagnosis keywords are fuzzy matched with the rare disease dictionary.
It should be understood that the above 4 matching rules ensure that the doctor client does not miss the acquisition of the rare case diagnosis, and prevent the report missing of the rare case.
Further, the step S101: the rare disease electronic filling card is sent to a doctor client, the rare disease electronic filling card belongs to a prefabricated electronic filling card, options in the rare disease electronic filling card are set in advance by a hospital client, and basic information of a patient in the rare disease electronic filling card is obtained by directly calling the basic information from an HIS (Hospital information system).
It should be understood that the options in the rare disease electronic fill-write card are set in advance by the hospital client, the basic information of the patient in the rare disease electronic fill-write card is obtained by directly calling from the HIS system, and the above operations are all in view of saving the working time of the doctor and in view of ensuring the accuracy and the integrity of the rare disease information collection.
Further, the step S101: receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; the method comprises the following specific steps:
receiving rare disease information input by a doctor client in a rare disease electronic fill-write card;
judging whether a missing item exists in the rare disease electronic filling and writing card, if so, returning the filling requirement of the missing item, and reminding a doctor to fill in; and if the missing item does not exist, allowing the current rare disease electronic filling card to be stored and uploaded.
Further, the step S101: uploading the completely filled rare disease electronic filling card to a hospital client, wherein the uploading encrypts rare disease information in the transmission process to prevent information leakage in the transmission process, and the specific encryption steps are as follows:
serializing case information; and according to a secret key agreed in advance, DES encryption is carried out on the serialized rare disease information.
It will be appreciated that by encrypting the rare disease information, the privacy of the patient may be protected. The private data of the patient are prevented from being leaked by hacker attack.
Further, the S102: the hospital client side carries out data authenticity verification, data consistency verification and data accuracy verification on the received rare disease electronic filling card; the method comprises the following specific steps:
the hospital client side carries out data authenticity verification on the received rare disease electronic filling card: the identity card number of the patient is called and matched with the identity card number in the public security identity card inquiry server, if the identity card number is matched with the corresponding personnel, the authenticity verification is successful, and otherwise, the authenticity verification is failed;
the hospital client side carries out data consistency check on the received rare disease electronic filling card: matching the basic data of the patient in the rare disease electronic filling and writing card with the basic data of the current patient in an HIS system, an electronic medical record system and/or a medical record system one by one, wherein if the matching is successful, the data consistency verification is successful, otherwise, the data consistency verification is failed;
the hospital client side carries out data accuracy verification on the received rare disease electronic filling card: the CT detection result data of the patient in the rare disease electronic fill-write card is matched with the actual CT image identification data, if the matching is successful, the data accuracy verification is successful, and otherwise, the data accuracy verification is failed.
It should be understood that, according to the method, data integrity check, data authenticity check, data consistency check and data accuracy check are carried out on the rare disease electronic filling and writing card once, and it can be guaranteed that data which are finally uploaded to the provincial platform data center are accurate, real and complete.
Further, the S102: the hospital client analyzes the rare disease electronic fill-write card and stores the analyzed data into a hospital client data center database; the specific storage steps comprise:
the hospital client analyzes the rare disease electronic filling card to obtain the identity card number of the patient; and judging whether the current data is stored once or not according to the diagnosis name and the identification number, if so, rejecting the current data, and if not, storing the current data.
If the case information does not have the identification number, whether the current data is stored once or not is judged according to the diagnosis name and the (hospitalization number/case number), if so, the current data is removed, and if not, the current data is stored.
It will be appreciated that this avoids repeated reporting of data.
Further, the S102: finally, the hospital client uploads the data to a provincial platform data center; the data of an internal network is transmitted to an external network through a gateway interface; the gateway interface data transmission mode here is:
s1021: a Web server communicating with the provincial platform data center is built on a hospital front-end processor to ensure that the Web server is communicated with an internal network and an external network;
s1022: the Web server receives request information sent by a hospital client in a webservice mode;
s1023: the Web server receives data analyzed by the rarely-seen electronic fill-write card of the hospital client in a webservice mode, performs DES encryption according to a secret key agreed in advance, and then sends the data to the provincial platform data center.
The province platform data center judges the received data at first, ensures that the data cannot repeatedly enter the province platform data center, ensures the quality of the province platform data center data, saves the storage space of a province platform data center server, saves the data auditing time of a province platform data center manager, saves the hardware cost and saves the social and manpower cost.
Further, the step S103: the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center; the method comprises the following specific steps:
s1031: encrypting the data analyzed by the electronic case fill-write card, wherein the encryption comprises the encryption of index items and the encryption of dictionary information;
for example: sex: for male, after encryption, it is
"qu_RADIO_ff80808168e9cfd101690996ff6d0535":
"ff80808168e9cfd101690996ff6d0536"；
S1032: converting the encrypted electronic medical record filling card into a json format character string;
s1033: and transmitting the json format character string to a national platform data center in a webservice transmission mode.
This application fills in the card through the electron, can effectively save doctor's time, fills in the initiative of card through filling in the electron and reminds, can avoid the doctor to forget to fill in, fills in the option of card through the electron, can save doctor's time, fills in the setting of card through the electron, can improve doctor's work efficiency, has also improved the degree of accuracy that the rare disease filled in data, avoids the doctor to rely on the experience of self to fill in less or neglected to fill in data.
Example two
The embodiment provides a rare disease data acquisition and reporting system;
as shown in fig. 2, the rare disease data collecting and reporting system includes: the system comprises a doctor client, a hospital client, a provincial platform data center and a national platform data center;
acquiring diagnosis conclusions input by a doctor client in an HIS (medical science and technology system), an electronic medical record system and/or a medical record system according to a set time interval, extracting diagnosis keywords from the diagnosis conclusions, matching the diagnosis keywords with rare disease terms in a pre-constructed rare disease dictionary, and if matching is successful, sending a rare disease electronic filling card to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client;
the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card, if the data authenticity check, the data consistency check and the data accuracy check are passed, the hospital client analyzes the rare disease electronic filling card, stores the analyzed data into a hospital client data center database, and finally uploads the data to a provincial platform data center by the hospital client;
and the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center.
It should be understood that the details of the working steps of the devices of the doctor client, the hospital client, the provincial platform data center and the national platform data center are the same as those in the first embodiment, and are not described herein again.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. The rare disease data acquisition and reporting method is characterized by comprising the following steps:
acquiring diagnosis conclusions input by a doctor client in an HIS (medical science and technology system), an electronic medical record system and/or a medical record system according to a set time interval, extracting diagnosis keywords from the diagnosis conclusions, matching the diagnosis keywords with rare disease terms in a pre-constructed rare disease dictionary, and if matching is successful, sending a rare disease electronic filling card to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client;
the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card, if the data authenticity check, the data consistency check and the data accuracy check are passed, the hospital client analyzes the rare disease electronic filling card, stores the analyzed data into a hospital client data center database, and finally uploads the data to a provincial platform data center by the hospital client; and the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center.
2. The method as claimed in claim 1, wherein the diagnosis conclusion inputted by the doctor client in the HIS system, the electronic medical record system and/or the medical record system is obtained according to the set time interval; the method comprises the following specific steps: actively polling a diagnosis conclusion input by a doctor client in an HIS system or an electronic medical record system according to a set time interval, and marking the case as polled when the case is found to be polled once; for the polled case, the data is not included in the screening range in the next polling process, and the polling efficiency is improved.
3. The method of claim 1, wherein diagnostic keywords are extracted from the diagnostic findings; the method comprises the following specific steps:
a doctor client acquires and stores a diagnosis conclusion input by a doctor in the HIS system to generate a case view; the method comprises the steps that cases in case views are analyzed one by one, different descriptions possibly appear in case information for the same diagnosis, a doctor client removes punctuation marks appearing in the diagnosis by using a regular expression, then word segmentation is carried out, words after word segmentation are all input into a pre-trained neural network model, and diagnosis keywords are output.
4. The method of claim 3, wherein the training step of the pre-trained neural network model comprises:
constructing a training set, wherein the training set is a diagnosis record corresponding to a plurality of known diagnosis keywords;
preprocessing a training set, wherein the preprocessing refers to that known diagnosis keywords are used as labels, and each diagnosis record is subjected to punctuation removal and word segmentation processing to obtain a plurality of words corresponding to each diagnosis record; taking each vocabulary as a node, if any two vocabularies have adjacent occurrence conditions in the diagnostic record, connecting two nodes corresponding to the two vocabularies, taking the times of simultaneous occurrence as the weight of the connection, and establishing an undirected weighted graph; representing the undirected weighted graph as an adjacency matrix; obtaining the vector representation of each node in the undirected weighted graph, and carrying out weighted summation on the vector representations of all the nodes to obtain the final vector representation of the undirected weighted graph;
and inputting the final vector representation of the undirected weighted graph into a neural network model, training the neural network model by taking the known diagnosis keywords as labels of the neural network model, and stopping training when the loss function of the neural network model reaches the minimum value to obtain the trained neural network model.
5. The method of claim 1, wherein the matching of the diagnosis keyword with the rare disease name word in a pre-constructed rare disease dictionary, wherein the pre-constructed rare disease dictionary comprises the steps of:
classifying the rare diseases;
arranging the rare disease full name, short name and ICD codes according to the national rare disease catalogue;
constructing a rare disease database dictionary table according to rare disease classification, rare disease full name, rare disease short name and ICD codes;
alternatively, the first and second electrodes may be,
matching the diagnosis keywords with the rare disease name words in a pre-constructed rare disease dictionary, wherein the matching refers to:
the diagnosis keywords are completely matched with the rare disease dictionary full-name; the diagnosis keywords are completely matched with rare diseases for short; the diagnosis keywords are in full-scale fuzzy matching with the rare disease dictionary; and/or, the diagnosis keywords are fuzzy matched with the rare disease dictionary.
6. The method as claimed in claim 1, wherein the rare disease electronic filling card is sent to the doctor client, wherein the rare disease electronic filling card belongs to a prefabricated electronic filling card, options in the rare disease electronic filling card are set in advance by the hospital client, and basic information of a patient in the rare disease electronic filling card is obtained by directly calling from the HIS;
receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; the method comprises the following specific steps:
receiving rare disease information input by a doctor client in a rare disease electronic fill-write card;
judging whether a missing item exists in the rare disease electronic filling and writing card, if so, returning the filling requirement of the missing item, and reminding a doctor to fill in; if the missing item does not exist, the current rare disease electronic filling and writing card is allowed to be stored and uploaded;
alternatively, the first and second electrodes may be,
uploading the completely filled rare disease electronic filling card to a hospital client, wherein the uploading encrypts rare disease information in the transmission process to prevent information leakage in the transmission process, and the specific encryption steps are as follows:
serializing case information; and according to a secret key agreed in advance, DES encryption is carried out on the serialized rare disease information.
7. The method as set forth in claim 1, wherein the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card; the method comprises the following specific steps:
the hospital client side carries out data authenticity verification on the received rare disease electronic filling card: the identity card number of the patient is called and matched with the identity card number in the public security identity card inquiry server, if the identity card number is matched with the corresponding personnel, the authenticity verification is successful, and otherwise, the authenticity verification is failed;
the hospital client side carries out data consistency check on the received rare disease electronic filling card: matching the basic data of the patient in the rare disease electronic filling and writing card with the basic data of the current patient in an HIS system, an electronic medical record system and/or a medical record system one by one, wherein if the matching is successful, the data consistency verification is successful, otherwise, the data consistency verification is failed;
the hospital client side carries out data accuracy verification on the received rare disease electronic filling card: the CT detection result data of the patient in the rare disease electronic fill-write card is matched with the actual CT image identification data, if the matching is successful, the data accuracy verification is successful, and otherwise, the data accuracy verification is failed.
8. The method of claim 1, wherein the hospital client parses the rare disease electronic fill-write card and stores the parsed data in a hospital client data center database; the specific storage steps comprise:
the hospital client analyzes the rare disease electronic filling card to obtain the identity card number of the patient; judging whether the current data is stored once or not according to the diagnosis name and the identity card number, if so, rejecting the current data, and if not, storing the current data;
if the case information does not have the identification number, judging whether the current data is stored once according to the diagnosis name, the hospitalization number and the case number, if so, rejecting the current data, and if not, storing the current data.
9. The method of claim 1, wherein the hospital client is last uploaded to a provincial platform data center; the data of an internal network is transmitted to an external network through a gateway interface; the gateway interface data transmission mode here is:
a Web server communicating with the provincial platform data center is built on a hospital front-end processor to ensure that the Web server is communicated with an internal network and an external network;
the Web server receives request information sent by a hospital client in a webservice mode;
the Web server receives data analyzed by the hospital client rare disease electronic fill-write card in a webservice mode, performs DES encryption according to a secret key agreed in advance, and then sends the data to a provincial platform data center;
alternatively, the first and second electrodes may be,
the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center; the method comprises the following specific steps:
encrypting the data analyzed by the electronic case fill-write card, wherein the encryption comprises the encryption of index items and the encryption of dictionary information;
converting the encrypted electronic medical record filling card into a json format character string;
and transmitting the json format character string to a national platform data center in a webservice transmission mode.
10. Rare disease data acquisition and reporting system, characterized by includes: the system comprises a doctor client, a hospital client, a provincial platform data center and a national platform data center;
acquiring diagnosis conclusions input by a doctor client in an HIS (medical science and technology system), an electronic medical record system and/or a medical record system according to a set time interval, extracting diagnosis keywords from the diagnosis conclusions, matching the diagnosis keywords with rare disease terms in a pre-constructed rare disease dictionary, and if matching is successful, sending a rare disease electronic filling card to the doctor client; receiving rare disease information input by a doctor client in a rare disease electronic fill-write card; carrying out data integrity verification on the filled electronic filling card; uploading the completely filled rare disease electronic filling and writing card to a hospital client;
the hospital client performs data authenticity check, data consistency check and data accuracy check on the received rare disease electronic filling card, if the data authenticity check, the data consistency check and the data accuracy check are passed, the hospital client analyzes the rare disease electronic filling card, stores the analyzed data into a hospital client data center database, and finally uploads the data to a provincial platform data center by the hospital client; and the provincial platform data center encrypts the analyzed data and uploads the encrypted data to the national platform data center.
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