CN111739598A - Data processing method, device, medium and electronic equipment - Google Patents
Data processing method, device, medium and electronic equipment Download PDFInfo
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- CN111739598A CN111739598A CN202010590933.6A CN202010590933A CN111739598A CN 111739598 A CN111739598 A CN 111739598A CN 202010590933 A CN202010590933 A CN 202010590933A CN 111739598 A CN111739598 A CN 111739598A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
Abstract
The invention provides a data processing method, which comprises the following steps: receiving a user request, wherein the user request comprises an identification of an access volume; calling follow-up access book data corresponding to the follow-up access book from a database according to the identification of the follow-up access book, wherein the follow-up access book data are structured data; receiving follow-up answers input by a user for the follow-up questionnaire data; generating the follow-up answer data based on the follow-up answer, wherein the follow-up answer data is structured data; and determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, wherein the follow-up medical data is structured data. The invention also provides a data processing device, a medium and an electronic device.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing method, an apparatus, a medium, and an electronic device.
Background
Currently, with the rapid development of big data, various data are generated, for example, medical data, questionnaire data, order data, insurance data, and the like. For example, questionnaire data and medical data are taken as examples. In the application scene of chronic disease follow-up, the follow-up management of the chronic disease (such as chronic hepatitis and diabetes) is to analyze the result of a questionnaire by surveying the data of the questionnaire, to make follow-up medical data and to analyze the follow-up report according to the treatment result. Provides medication guidance for patients with chronic diseases, and scientifically regulates the medication of the patients in time. Timely regulating the medication. The purposes of diagnosis and treatment of the disease condition, control of the disease condition and treatment of the patient are achieved. The information transmission is realized by adopting a questionnaire mode, but the questionnaire data has a large number of problems and various forms, and can be supported by a flexible and changeable structured data model. In the traditional model, a questionnaire question table is created by the question information of each questionnaire survey, and a question answer table is created by each questionnaire answer; when the questions in the questionnaire are changed, such as adding the questions, corresponding columns need to be added to the questionnaire answer table correspondingly, so that not only the database needs to be modified, but also the code program needs to be modified, and the working cost is increased.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present invention and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.
Disclosure of Invention
Embodiments of the present invention provide a data processing method, an apparatus, a medium, and an electronic device, so that data can support flattening, strong expansion, and diversification at least to some extent. The flattening is characterized by reducing the data hierarchy and reducing the complexity of the data; the strong expansion shows that the data is not limited by the hierarchy, and any hierarchy can be realized; diversification is represented as a form of problem that can implement a variety of styles.
Additional features and advantages of the invention will be set forth in the detailed description which follows, or may be learned by practice of the invention.
According to a first aspect of embodiments of the present invention, there is provided a data processing method, including: receiving a user request, wherein the user request comprises an identification of an access volume; calling follow-up access book data corresponding to the follow-up access book from a database according to the identification of the follow-up access book, wherein the follow-up access book data are structured data; receiving follow-up answers input by a user for the follow-up questionnaire data; generating the follow-up answer data based on the follow-up answer, wherein the follow-up answer data is structured data; and determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, wherein the follow-up medical data is structured data.
In some embodiments of the invention, the method further comprises: receiving a review physical examination index fed back by a user aiming at the follow-up medical data; generating review physical examination data based on the review physical examination index, wherein the review physical examination data is structured data; and determining whether to adjust the follow-up medical data according to a review physical examination index in the review physical examination data.
In some embodiments of the invention, determining whether to adjust the follow-up medical data based on a review physical indicator in the review physical data comprises: determining the current physical state of the user according to the numerical value and/or description of each of the review physical indicators; if the current physical state of the user is a first state, the follow-up medical data is not adjusted, or if the current physical state of the user is a second state, the follow-up medical data is adjusted, wherein the first state and the second state are different.
In some embodiments of the invention, if the current physical state of the user is a second state, adjusting the follow-up medical data comprises: if the current physical state of the user is a second state, determining a medicine name identifier and a medicine type identifier related to each physical examination index according to the identifier of each physical examination index in the physical examination indexes; adjusting the follow-up medical data according to a drug name identification and a drug type identification associated with the identification of each review physical indicator.
In some embodiments of the invention, determining the follow-up medical data of the user from the follow-up answer data and the follow-up questionnaire data comprises: determining a drug name identifier and a drug type identifier related to the identifier of each answer and the identifier of each question according to the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data; and calling the follow-up medical data of the user according to the medicine name identification and the medicine type identification.
In some embodiments of the invention, when adding a new question on the basis of the follow-up volume data, the method further comprises: receiving the new question and determining the type of the new question; and determining whether to generate a correlation answer or a choice answer according to the type of the new question.
In some embodiments of the present invention, determining whether to generate the associated answer or the choice answer according to the type of the new question comprises: if the type of the new question is a judgment type, generating a relevant associated answer based on the new question; or if the type of the new question is a choice type, generating a choice answer related to the new question based on the new question.
According to a second aspect of embodiments of the present invention, there is provided a data processing apparatus, including: the first receiving module is used for receiving a user request, wherein the user request comprises an identification of an access volume; the first calling module is used for calling the follow-up access book data corresponding to the follow-up access book from a database according to the identification of the follow-up access book, and the follow-up access book data are structured data; the second receiving module is used for receiving follow-up answers input by a user aiming at the follow-up questionnaire data; the first generation module generates the follow-up answer data based on the follow-up answer, wherein the follow-up answer data is structured data; the first determination module is used for determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, and the follow-up medical data is structured data.
In some embodiments of the invention, the apparatus further comprises: the third receiving module is used for receiving the review physical examination index fed back by the user aiming at the follow-up medical data; the second generation module is used for generating the review physical examination data based on the review physical examination index, wherein the review physical examination data is structured data; and the adjusting module is used for determining whether to adjust the follow-up medical data according to the review physical examination indexes in the review physical examination data.
In some embodiments of the invention, the adjusting module includes: a second determination module, configured to determine a current physical state of the user according to a numerical value and/or description of each of the review physical indicators; and a sub-module of the adjustment module, if the current physical state of the user is a first state, not adjusting the follow-up medical data, or if the current physical state of the user is a second state, adjusting the follow-up medical data, wherein the first state and the second state are different.
In some embodiments of the invention, the sub-module of the above-mentioned adjusting module is configured to: if the current physical state of the user is a second state, determining a medicine name identifier and a medicine type identifier related to each physical examination index according to the identifier of each physical examination index in the physical examination indexes; adjusting the follow-up medical data according to a drug name identification and a drug type identification associated with the identification of each review physical indicator.
In some embodiments of the invention, the first determining module includes: a medicine determining module, configured to determine, according to the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data, a medicine name identifier and a medicine type identifier related to the identifier of each answer and the identifier of each question; and the second calling module is used for calling the follow-up medical data of the user according to the medicine name identification and the medicine type identification.
In some embodiments of the invention, when adding a new question on the basis of the follow-up volume data, the apparatus further comprises: a fourth receiving module, configured to receive the new question and determine a type of the new question; and the third determining module is used for determining whether to generate a correlation answer or a choice answer according to the type of the new question.
In some embodiments of the invention, the third determining module is configured to: if the type of the new question is a judgment type, generating a relevant associated answer based on the new question; or if the type of the new question is a choice type, generating a choice answer related to the new question based on the new question.
According to a third aspect of embodiments of the present invention, there is provided an electronic apparatus, including: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out a data processing method as described in the first aspect of the embodiments above.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable medium, on which a computer program is stored, which when executed by a processor, implements the data processing method as described in the first aspect of the embodiments above.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
in the technical scheme provided by some embodiments of the present invention, a user request is received, where the user request includes an identifier of a follow-up access volume, follow-up access volume data corresponding to the identifier of the follow-up access volume is called from a database according to the follow-up access volume, the follow-up access volume data is structured data, a follow-up access answer input by a user for the follow-up access volume data is received, the follow-up access answer data is generated based on the follow-up access answer, the follow-up access answer data is structured data, follow-up medical data of the user is determined according to the follow-up access answer data and the follow-up access volume data, the follow-up medical data is structured data, and in this way, structured data (for example, follow-up access volume data, follow-up access answer data, and follow-up medical data) can be obtained, and the structured data supports being stored in a database in a behavioral unit, thereby realizing flattening of data, Strong expansion, and diversified effects.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
fig. 1 shows a schematic diagram of an exemplary system architecture to which a data processing method or a data processing apparatus of an embodiment of the present invention may be applied;
FIG. 2 schematically shows a flow diagram of a data processing method according to an embodiment of the invention;
FIG. 3 schematically shows a flow diagram of a data processing method according to another embodiment of the invention;
FIG. 4 schematically shows a flow diagram of a data processing method according to another embodiment of the invention;
FIG. 5 schematically shows a flow diagram of a data processing method according to another embodiment of the invention;
FIG. 6 schematically shows a flow diagram of a data processing method according to another embodiment of the invention;
FIG. 7 schematically shows a flow diagram of a data processing method according to another embodiment of the invention;
FIG. 8 schematically shows a flow diagram for generating structured data and applying structured data according to an embodiment of the invention;
9A-9D schematically illustrate diagrams of structured data according to embodiments of the invention;
FIG. 10 schematically shows a block diagram of a data processing apparatus according to an embodiment of the present invention;
FIG. 11 schematically shows a block diagram of a data processing apparatus according to another embodiment of the present invention;
FIG. 12 schematically shows a block diagram of a data processing apparatus according to another embodiment of the present invention;
FIG. 13 schematically shows a block diagram of a data processing apparatus according to another embodiment of the present invention;
FIG. 14 schematically shows a block diagram of a data processing apparatus according to another embodiment of the present invention;
FIG. 15 illustrates a schematic structural diagram of a computer system suitable for use with the electronic device to implement an embodiment of the invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations or operations have not been shown or described in detail to avoid obscuring aspects of the invention.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
Fig. 1 shows a schematic diagram of an exemplary system architecture to which a data processing method or a data processing apparatus of an embodiment of the present invention may be applied.
As shown in fig. 1, the system architecture 100 may include one or more of terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, server 105 may be a server cluster comprised of multiple servers, or the like.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may be various electronic devices having a display screen, including but not limited to smart phones, tablet computers, portable computers, desktop computers, and the like.
The server 105 may be a server that provides various services. For example, the server 105 may receive a user request from the terminal device 103 (or the terminal device 101 or 102), where the user request includes an identifier of a follow-up access volume, call, according to the identifier of the follow-up access volume, follow-up access volume data corresponding to the identifier of the follow-up access volume from a database, where the follow-up access volume data is structured data, receive a follow-up answer input by a user for the follow-up access volume data, generate the follow-up answer data based on the follow-up answer, where the follow-up answer data is structured data, determine, according to the follow-up answer data and the follow-up access volume data, the follow-up medical data of the user, and where the follow-up medical data is structured data, and in this way, structured data (e.g., follow-up access volume data, follow-up answer data, and follow-up medical data) may be obtained, and the structured data is stored in the database in a unit of a behavior, thereby realizing the effects of flattening, strong expansion and diversification of data.
In some embodiments, the data processing method provided by the embodiments of the present invention is generally executed by the server 105, and accordingly, the data processing apparatus is generally disposed in the server 105. In other embodiments, some terminals may have similar functionality as the server to perform the method. Therefore, the data processing method provided by the embodiment of the invention is not limited to be executed at the server side.
Fig. 2 schematically shows a flow chart of a data processing method according to an embodiment of the invention.
As shown in fig. 2, the data processing method may include steps S210 to S250.
In step S210, a user request is received, where the user request includes an identifier of an access volume.
In step S220, the follow-up access book data corresponding to the identification of the follow-up access book is called from the database, and the follow-up access book data is structured data.
In step S230, a follow-up answer input by a user for the follow-up questionnaire data is received.
In step S240, the follow-up answer data is generated based on the follow-up answer, and the follow-up answer data is structured data.
In step S250, determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, wherein the follow-up medical data is structured data.
The method can receive a user request, the user request comprises an identification of a follow-up access volume, the follow-up access volume data corresponding to the identification of the follow-up access volume is called from a database according to the identification of the follow-up access volume, the follow-up questionnaire data is structured data, follow-up answers input by a user aiming at the follow-up questionnaire data are received, the follow-up answer data are generated based on the follow-up answers, the follow-up answer data are structured data, determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, wherein the follow-up medical data is structured data, in this way, structured data (such as follow-up questionnaire data, follow-up answer data and follow-up medical data) can be obtained, and the structured data supports the storage in a database in a row unit, so that the effects of flattening, strong expansion and diversification of the data are achieved.
In an embodiment of the present invention, the user request may be initiated by a user on a terminal. For example, the user is a chronic patient, and at this time, the follow-up medical data for the chronic disease suffered by the user needs to be acquired, and in this case, the user needs to operate on the terminal to acquire the follow-up questionnaire data. When the terminal sends a user request to the server, the user request comprises an identification of a follow-up access volume related to a chronic disease suffered by the user, and the identification is used for calling the follow-up access volume data corresponding to the user from a database of the server.
In one embodiment of the invention, the follow-up access volume data corresponding to the follow-up access volume is called from the database according to the identification of the follow-up access volume, and the follow-up access volume data is structured data. For example, the identification of the follow-up questionnaire may be an identification associated with chronic pneumonia, and the follow-up questionnaire data of the corresponding chronic pneumonia may be called from the database according to the identification of the follow-up questionnaire associated with chronic pneumonia. The follow-up access volume data is structured data, namely is stored in the database in a row unit, so that the effects of flattening, strong expansion and diversification of the data can be realized, and the data is convenient to manage.
In one embodiment of the present invention, after the terminal receives the follow-up questionnaire data, the user may browse the follow-up questionnaire data on the terminal and input a follow-up answer according to a question in the follow-up questionnaire data. When the user finishes answering the questions in the follow-up questionnaire data, the follow-up answer data can be sent to a server, the server receives the follow-up answers input by the user aiming at the follow-up questionnaire data, the follow-up answer data is generated based on the follow-up answers, and the follow-up answer data is structured data. In this embodiment, the follow-up answer data may be generated according to a preset follow-up answer template based on the follow-up answer, where the template is structured data, that is, the follow-up answer data may be stored in the database in a row unit, so that effects of flattening, strong expansion, and diversification of the data may be achieved, and thus, the data may be managed conveniently.
In one embodiment of the invention, the follow-up medical data of the user is determined according to the follow-up answer data and the follow-up volume data, and the follow-up medical data is structured data. For example, a medication name identifier and a medication type identifier associated with the identifier of each answer and the identifier of each question in the follow-up answer data are determined from the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data, and the follow-up medical data of the user is invoked from the medication name identifier and the medication type identifier. In this embodiment, the patient may perform the auxiliary treatment according to the follow-up medical data, which is structured data, that is, the follow-up medical data is stored in the database in a row unit, so that the effects of flattening, strong expansion, and diversification of the data can be achieved, which is convenient for managing the data. In addition, in the present embodiment, the follow-up medical data may be added according to the follow-up volume data and the follow-up answer data. For example, when questions and answers are added to the follow-up questionnaire data, the relevant person may configure the follow-up medical data related to the questions and answers according to the added questions and answers, so as to call the follow-up medical data according to the follow-up questionnaire data and the follow-up answer data.
Fig. 3 schematically shows a flow chart of a data processing method according to another embodiment of the invention.
As shown in fig. 3, the method further includes steps S310 to S330.
In step S310, a review physical examination index fed back by the user for the follow-up medical data is received.
In step S320, the review physical examination data, which is structured data, is generated based on the review physical examination index.
In step S330, it is determined whether to adjust the follow-up medical data according to a review health indicator in the review health data.
The follow-up medical data can be determined whether to be adjusted or not according to the follow-up physical examination indexes in the follow-up physical examination data, so that the follow-up medical data can be adjusted in time, the patient is effectively prevented from continuously performing auxiliary treatment according to the fixed follow-up medical data, and the follow-up medical data can be automatically adjusted in the mode, so that the user experience can be improved.
In an embodiment of the invention, after a user receives treatment according to follow-up medical data for a period of time, the user can go to a hospital to perform a recheck according to contents to be rechecked in the follow-up medical data, when the user receives a recheck result provided by the hospital, the user can send the recheck result to the server through the terminal, at the moment, the server can receive a recheck physical examination index fed back by the user aiming at the follow-up medical data, generate the recheck physical examination data based on the recheck physical examination index, and then determine whether to adjust the follow-up medical data according to the recheck physical examination index in the recheck physical examination data, so that the server can automatically adjust the follow-up.
In one embodiment of the present invention, the review physical examination data is structured data, and the review physical examination data can be stored in the database in units of rows. For example, the review physical examination data is generated from a template of preset review physical examination data based on the review physical examination index. The template is structured data, so that the generated physical examination data can be structured data, namely, the effects of flattening, strong expansion and diversification of the data are realized, and the data are convenient to manage.
In one embodiment of the invention, patients with chronic disease may be treated and when patients are added to the treatment group, the various stages of the protocol are instituted. If the treatment period of the regimen is one year, the regimen is divided into four phases, each of which is three months. The server can select whether to adjust the treatment of the next stage according to the review physical examination indexes uploaded by the patient in the last stage. When the server obtains the condition of the patient is improved according to the information fed back by the patient, the existing established scheme can be kept for continuing the treatment without adjusting the follow-up medical data. When the doctor obtains the slow improvement of the patient's condition or finds that the patient is not suitable for a certain kind of medicine according to the information fed back by the patient, the follow-up medical data needs to be adjusted for the next stage of treatment.
Fig. 4 schematically shows a flow chart of a data processing method according to another embodiment of the invention.
As shown in fig. 4, the step S330 may include a step S410, a step S420, or a step S410, a step S430.
In step S410, the current physical state of the user is determined according to the numerical value and/or description of each of the review physical indicators.
In step S420, if the current physical state of the user is the first state, the follow-up medical data is not adjusted.
Or
In step S410, the current physical state of the user is determined according to the numerical value and/or description of each of the review physical indicators.
In step S430, if the current physical state of the user is a second state, the follow-up medical data is adjusted, wherein the first state and the second state are different.
The method may determine a current physical state of the user based on the values and/or descriptions of each of the review physical indicators and then determine whether to adjust the follow-up medical data based on the current physical state of the user. For example, if the current physical state of the user is a first state, the follow-up medical data is not adjusted, and if the current physical state of the user is a second state, the follow-up medical data is adjusted.
In one embodiment of the invention, the current physical state of the user may be determined based on the numerical value and/or description of each of the review physical indicators. For example, the physical examination indexes include blood pressure, blood sugar, chest CT, and the like. If the values of the blood pressure and the blood sugar are higher than the normal interval value, the chest inflammation aggravation is described in the examination report of the chest CT, at this time, the current physical state of the user can be determined as the state of illness not improving (namely, the second state) according to the information, and in this case, the follow-up medical data is adjusted according to the value and/or the description of each of the follow-up physical indexes. Conversely, if the values of blood pressure and blood glucose both trend toward normal interval values, and a reduction in chest inflammation is described in the examination report of the chest CT, then the current physical state of the user can be determined as a disease improvement (i.e., the first state) based on this information, in which case the follow-up medical data need not be adjusted based on the values and/or descriptions of each of the follow-up physical indicators.
Fig. 5 schematically shows a flow chart of a data processing method according to another embodiment of the invention.
As shown in fig. 5, the step S430 may include a step S510 and a step S520.
In step S510, if the current physical state of the user is the second state, the drug name identifier and the drug type identifier associated with each of the review physical indicators are determined according to the identifier of the review physical indicator.
In step S520, the follow-up medical data is adjusted according to the drug name identification and the drug type identification associated with the identification of each review body indicator.
The method can determine the medicine name identification and the medicine type identification related to each review physical examination index according to the identification of each review physical examination index in the review physical examination indexes, and adjust the follow-up medical data according to the medicine name identification and the medicine type identification related to the identification of each review physical examination index, so that the follow-up medical data can be adjusted in a targeted manner, and the adjusted follow-up medical data is more effective for patients.
In one embodiment of the present invention, when the current physical state of the user is the second state (i.e., the patient's condition is not improved), the drug name identifier and the drug type identifier associated with each of the review physical indicators can be determined according to the identifier of the review physical indicator. For example, the follow-up medical data is adjusted according to the medicine name identifier and the medicine type identifier related to the blood pressure identifier, the blood sugar identifier and the chest CT identifier, so that the follow-up medical data can be adjusted in a targeted manner, and the adjusted follow-up medical data is more effective for the patient.
Fig. 6 schematically shows a flow chart of a data processing method according to another embodiment of the invention.
As shown in fig. 6, the step S250 may specifically include a step S610 and a step S620.
In step S610, a drug name identifier and a drug type identifier associated with the identifier of each answer and the identifier of each question are determined according to the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data.
In step S620, the follow-up medical data of the user is called according to the drug name identifier and the drug type identifier.
The method can determine the medicine name identification and the medicine type identification related to the identification of each answer and the identification of each question according to the identification of each answer in the follow-up answer data and the identification of each question in the follow-up questionnaire data, and call the follow-up medical data of the user according to the medicine name identification and the medicine type identification, so that the follow-up medical data which is consistent with the illness state of the patient can be accurately called.
In one embodiment of the present invention, the drug name identification and the drug type identification associated with the identification of each answer and the identification of each question are determined from the identification of each answer in the follow-up answer data and the identification of each question in the follow-up questionnaire data. For example, the problems in follow-up questionnaire data are: is there hypertension? Is there hyperlipidemia? Is the chest painful? The answer corresponding thereto may include yes or no. In this case, the drug name identification and the drug type identification associated with the identification of each answer and the identification of each question may be determined from the identification of each question in the follow-up questionnaire data and each answer in the follow-up answer data.
Fig. 7 schematically shows a flow chart of a data processing method according to another embodiment of the invention.
When a new question is added on the basis of the follow-up access volume data, the method further includes step S710 and step S720, as shown in fig. 7 in detail.
In step S710, the new question is received and the type of the new question is determined.
In step S720, it is determined whether to generate a correlation answer or a choice answer according to the type of the new question.
The method can receive a new question, determine the type of the new question and then determine whether to generate a relevant answer or a choice answer according to the type of the new question, so that the answer of the new question can be quickly acquired, and new follow-up questionnaire data and new follow-up answer data can be generated based on a preset question template and a preset answer template.
In one embodiment of the invention, when a new question is added on the basis of the follow-up access volume data, the new question may be received, a unique question identifier may be generated on the basis of the new question, and the question type of the new question may be determined from the question identifier. For example, the question types may include a text type, a judgment type, and an option type. In the text-type question, an input box is generally configured to receive text input by a user when setting an answer. The judgment type question is generally set to "yes" and "no" when setting an answer. The question of option type is generally set to option A, B, C, D or the like when setting the answer.
In one embodiment of the present invention, determining whether to generate the associated answer or the answer to the choice according to the type of the new question includes generating associated answers (e.g., "yes" and "no") related to the new question based on the new question if the type of the new question is the judgment type. Or if the type of the new question is a choice type, generating answers to the choices (e.g., choices such as A, B, C, D) related to the new question based on the new question.
FIG. 8 schematically shows a flow diagram for generating structured data and applying structured data according to an embodiment of the invention.
As shown in fig. 8, generating structured data may include three flows of L1, L2, and L3.
Specifically, L1: and acquiring questionnaire excel data configured by developers, and generating an identifier of each questionnaire based on the questionnaire excel data. An identification of each question is generated based on the questions in each questionnaire. And traversing each question mark, searching out the mark of the superior question, setting the marks of the subordinate questions and the subordinate questions according to the mark of the superior question, and determining the question types and answer types of the subordinate questions based on the marks of the subordinate questions. For example, the question type may be a file type, a judgment type, an option type. The answer type may be a correlation answer, a choice answer. At this time, the follow-up questionnaire data may be generated based on the identifier of each questionnaire, the identifier of each question in each questionnaire, and the associated answer or the option answer, and the follow-up questionnaire data is structured data, which is specifically shown in fig. 9A.
L2: acquiring plan check item excel data, and generating an identifier of each check item based on the plan check item excel data. The review physical examination index in the follow-up medical data is generated based on the identifier of each examination item and is used for reference when the patient performs review after a period of time, and the review physical examination index data is structured data, which is specifically referred to fig. 9D.
L3: acquiring follow-up plan excel data, generating an identifier of each plan based on each plan in the follow-up plan excel data, searching the identifier of an examination item in each plan, and performing association binding on the identifier of the examination item, a follow-up stage and the follow-up plan to generate the follow-up medical data, wherein the follow-up medical data is structured data, the follow-up medical data can contain drug administration information of a patient and examination items required to be reviewed in each stage, and specific reference can be made to fig. 9C and 9D.
After the follow-up visit paper data and follow-up visit medical data are configured in the above mode. When using the follow-up questionnaire data and follow-up medical data, as in flow L4.
Specifically, L4: the patient receives the follow-up questionnaire data through the terminal, fills in the follow-up questionnaire on the terminal, sends a follow-up answer to the server through the terminal after the patient finishes filling in, and can generate follow-up answer data based on the follow-up answer, wherein the follow-up answer data is structured data, as shown in fig. 9B. And then matching the follow-up medical data of the patient according to the follow-up answer data and the follow-up questionnaire data, sending the follow-up medical data of the patient to the terminal, and after the patient fills in a medical report according to the follow-up medical data (for example, filling in a review physical examination index), sending the review physical examination index to the server through the terminal, wherein the server can determine whether to adjust the follow-up medical data according to the review physical examination index. In addition, a doctor can also receive follow-up answers of a patient, interpret a follow-up questionnaire and the follow-up answers, the doctor can manually select follow-up medical data suitable for the patient according to the interpretation result, after the patient fills a medical report according to the follow-up medical data (for example, filling a review physical examination index), the doctor can analyze the medical report and determine whether the patient needs to modify the follow-up medical data according to the analysis result, and if not, the doctor can perform treatment according to the original plan, namely, perform treatment according to the original follow-up medical data. If the medical report needs to be modified, the medical report is modified according to the numerical value and the description of the physical examination indexes of the reexamination in the medical report, and the diagnosis and treatment can be considered to be finished after the modification is finished.
Fig. 10 schematically shows a block diagram of a data processing device according to an embodiment of the present invention.
As shown in fig. 10, the data processing apparatus 200 includes a first receiving module 201, a first calling module 202, a second receiving module 203, a first generating module 204, and a first determining module 205.
Specifically, the first receiving module 201 is configured to receive a user request, where the user request includes an identifier of an access volume.
The first calling module 202 is configured to call, according to the identifier of the follow-up access volume, the follow-up access volume data corresponding to the identifier from a database, where the follow-up access volume data is structured data.
A second receiving module 203, configured to receive a follow-up answer input by a user for the follow-up questionnaire data.
A first generation module 204, configured to generate the follow-up answer data based on the follow-up answer, where the follow-up answer data is structured data.
A first determining module 205, configured to determine, according to the follow-up answer data and the follow-up questionnaire data, follow-up medical data of the user, where the follow-up medical data is structured data.
The data processing device 200 can receive a user request, the user request comprises an identification of a follow-up access book, follow-up access book data corresponding to the follow-up access book is called from a database according to the identification of the follow-up access book, follow-up answers input by a user aiming at the follow-up access book data are received, the follow-up answer data are generated based on the follow-up answers, the follow-up answer data are structured data, follow-up medical data of the user are determined according to the follow-up answer data and the follow-up access book data, the follow-up medical data are structured data, the structured data (such as the follow-up access book data, the follow-up answer data and the follow-up medical data) can be obtained in this way, the structured data support is stored in the database in a row unit, and accordingly flattening, strong expansion and data are achieved, And diversified effects.
According to an embodiment of the present invention, the data processing apparatus 200 may be used to implement the data processing method described in the embodiment of fig. 2.
Fig. 11 schematically shows a block diagram of a data processing device according to another embodiment of the present invention.
As shown in fig. 11, the data processing apparatus 200 further includes a third receiving module 206, a second generating module 207, and an adjusting module 208.
Specifically, the third receiving module 206 is configured to receive a review physical indicator fed back by the user for the follow-up medical data.
The second generating module 207 generates the review physical examination data based on the review physical examination index, wherein the review physical examination data is structured data.
An adjusting module 208, configured to determine whether to adjust the follow-up medical data according to a review health indicator in the review health data.
This data processing apparatus 200 can confirm whether to adjust follow-up medical data according to the check-up physical examination index in the check-up physical examination data, can in time adjust this follow-up medical data like this, effectively avoids the patient to last to carry out auxiliary treatment according to fixed follow-up medical data, and the adjustment follow-up medical data that is automatic with this mode can promote user experience.
According to an embodiment of the present invention, the data processing apparatus 200 may be used to implement the data processing method described in the embodiment of fig. 3.
Fig. 12 schematically shows a block diagram of a data processing device according to another embodiment of the present invention.
As shown in FIG. 12, the adjustment module 208 includes a second determination module 208-1 and a sub-module 208-2 of the adjustment module.
In particular, the second determination module 208-1 is configured to determine the current physical status of the user according to the numerical value and/or description of each of the review physical indicators.
The sub-module 208-2 of the adjustment module does not adjust the follow-up medical data if the current physical state of the user is a first state, or adjusts the follow-up medical data if the current physical state of the user is a second state, where the first state and the second state are different.
The adjustment module 208 may determine the current physical state of the user based on the values and/or descriptions of each of the review physical indicators and then determine whether to adjust the follow-up medical data based on the current physical state of the user. For example, if the current physical state of the user is a first state, the follow-up medical data is not adjusted, and if the current physical state of the user is a second state, the follow-up medical data is adjusted.
The adjustment module 208 may be used to implement the data processing method described in the embodiment of fig. 4 according to an embodiment of the present invention.
In some embodiments of the present invention, the sub-module 208-2 of the adjustment module is configured to: if the current physical state of the user is a second state, determining a medicine name identifier and a medicine type identifier related to each physical examination index according to the identifier of each physical examination index in the physical examination indexes; adjusting the follow-up medical data according to a drug name identification and a drug type identification associated with the identification of each review physical indicator.
Fig. 13 schematically shows a block diagram of a data processing device according to another embodiment of the present invention.
As shown in FIG. 13, the first determination module 205 includes a medication determination module 205-1 and a second recall module 205-2.
Specifically, the medication determination module 205-1 is configured to determine, according to the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data, a medication name identifier and a medication type identifier associated with the identifier of each answer and the identifier of each question.
A second calling module 205-2, configured to call the follow-up medical data of the user according to the drug name identifier and the drug type identifier.
The first determining module 205 determines a drug name identifier and a drug type identifier associated with the identifier of each answer and the identifier of each question according to the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data, and invokes the follow-up medical data of the user according to the drug name identifier and the drug type identifier, so that the follow-up medical data corresponding to the patient condition can be invoked accurately.
According to an embodiment of the present invention, the first determining module 205 may be used to implement the data processing method described in the embodiment of fig. 6.
Fig. 14 schematically shows a block diagram of a data processing device according to another embodiment of the present invention.
As shown in fig. 14, the data processing apparatus 200 further includes a fourth receiving module 209 and a third determining module 210.
Specifically, the fourth section receiving module 209 is configured to receive the new question and determine the type of the new question.
A third determining module 210, configured to determine whether to generate a relevant answer or a choice answer according to the type of the new question.
The data processing apparatus 200 may receive a new question and determine a type of the new question, and then determine whether to generate an associated answer or a choice answer according to the type of the new question, in such a manner that an answer to the new question may be quickly obtained, so as to subsequently generate new follow-up questionnaire data and new follow-up answer data based on a preset question template and a preset answer template.
According to an embodiment of the present invention, the data processing apparatus 200 may be used to implement the data processing method described in the embodiment of fig. 7.
In some embodiments of the present invention, the third determining module 210 is configured to: if the type of the new question is a judgment type, generating a relevant associated answer based on the new question; or if the type of the new question is a choice type, generating a choice answer related to the new question based on the new question.
For details that are not disclosed in the embodiments of the apparatus of the present invention, reference is made to the above-described embodiments of the data processing method of the present invention for details that are not disclosed in the embodiments of the apparatus of the present invention, since various modules of the data processing apparatus 200 of the exemplary embodiment of the present invention can be used to implement the steps of the exemplary embodiments of the data processing method described in the above-described fig. 2 to 7.
It is understood that the first receiving module 201, the first calling module 202, the second receiving module 203, the first generating module 204, the first determining module 205, the medication determining module 205-1, the second calling module 205-2, the third receiving module 206, the second generating module 207, the adjusting module 208, the second determining module 208-1, the sub-module 208-2 of the adjusting module, the fourth receiving module 209, and the third determining module 210 may be combined and implemented in one module, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present invention, at least one of the first receiving module 201, the first invoking module 202, the second receiving module 203, the first generating module 204, the first determining module 205, the medication determining module 205-1, the second invoking module 205-2, the third receiving module 206, the second generating module 207, the adjusting module 208, the second determining module 208-1, the sub-module of the adjusting module 208-2, the fourth receiving module 209, and the third determining module 210 may be at least partially implemented as a hardware circuit, such as Field Programmable Gate Arrays (FPGAs), Programmable Logic Arrays (PLAs), systems on a chip, systems on a substrate, systems on a package, Application Specific Integrated Circuits (ASICs), or in hardware or firmware, or in any other reasonable manner of integrating or packaging circuits, or in any suitable combination of software, hardware, and firmware. Alternatively, at least one of the first receiving module 201, the first calling module 202, the second receiving module 203, the first generating module 204, the first determining module 205, the medication determining module 205-1, the second calling module 205-2, the third receiving module 206, the second generating module 207, the adjusting module 208, the second determining module 208-1, the sub-module 208-2 of the adjusting module, the fourth receiving module 209, and the third determining module 210 may be at least partially implemented as a computer program module, which when executed by a computer, may perform the functions of the respective modules.
Referring now to FIG. 15, shown is a block diagram of a computer system 300 suitable for use in implementing an electronic device of an embodiment of the present invention. The computer system 300 of the electronic device shown in fig. 15 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 15, the computer system 300 includes a Central Processing Unit (CPU)301 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage section 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for system operation are also stored. The CPU301, ROM 302, and RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
The following components are connected to the I/O interface 305: an input portion 306 including a keyboard, a mouse, and the like; an output section 307 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. A drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 310 as necessary, so that a computer program read out therefrom is mounted into the storage section 308 as necessary.
In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 309, and/or installed from the removable medium 311. The above-described functions defined in the system of the present application are executed when the computer program is executed by the Central Processing Unit (CPU) 301.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to implement the data processing method as described in the above embodiments.
For example, the electronic device may implement the following as shown in fig. 2: in step S210, a user request is received, where the user request includes an identifier of an access volume. In step S220, the follow-up access book data corresponding to the identification of the follow-up access book is called from the database, and the follow-up access book data is structured data. In step S230, a follow-up answer input by a user for the follow-up questionnaire data is received. In step S240, the follow-up answer data is generated based on the follow-up answer, and the follow-up answer data is structured data. In step S250, determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, wherein the follow-up medical data is structured data.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (10)
1. A method of data processing, the method comprising:
receiving a user request, wherein the user request comprises an identification of an access volume;
calling follow-up access book data corresponding to the follow-up access book from a database according to the identification of the follow-up access book, wherein the follow-up access book data are structured data;
receiving follow-up answers input by a user for the follow-up questionnaire data;
generating the follow-up answer data based on the follow-up answer, wherein the follow-up answer data is structured data;
and determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, wherein the follow-up medical data is structured data.
2. The method of claim 1, further comprising:
receiving a review physical examination index fed back by a user aiming at the follow-up medical data;
generating review physical examination data based on the review physical examination index, wherein the review physical examination data is structured data;
and determining whether to adjust the follow-up medical data according to a review physical examination index in the review physical examination data.
3. The method of claim 1, wherein determining whether to adjust the follow-up medical data based on a review volume indicator in the review volume data comprises:
determining the current physical state of the user according to the numerical value and/or description of each of the review physical indicators;
if the current physical state of the user is a first state, the follow-up medical data is not adjusted, or if the current physical state of the user is a second state, the follow-up medical data is adjusted, wherein the first state and the second state are different.
4. The method of claim 1, wherein adjusting the follow-up medical data if the user's current physical state is a second state comprises:
if the current physical state of the user is a second state, determining a medicine name identifier and a medicine type identifier related to each physical examination index according to the identifier of each physical examination index in the physical examination indexes;
adjusting the follow-up medical data according to a drug name identification and a drug type identification associated with the identification of each review physical indicator.
5. The method of claim 1, wherein determining follow-up medical data for the user from the follow-up answer data and the follow-up questionnaire data comprises:
determining a drug name identifier and a drug type identifier related to the identifier of each answer and the identifier of each question according to the identifier of each answer in the follow-up answer data and the identifier of each question in the follow-up questionnaire data;
and calling the follow-up medical data of the user according to the medicine name identification and the medicine type identification.
6. The method of claim 1, wherein when adding a new question based on the follow-up questionnaire data, the method further comprises:
receiving the new question and determining the type of the new question;
and determining whether to generate a correlation answer or a choice answer according to the type of the new question.
7. The method of claim 6, wherein determining whether to generate the associated answer or the choice answer based on the type of the new question comprises:
if the type of the new question is a judgment type, generating a relevant associated answer based on the new question; or
And if the type of the new question is a choice type, generating a choice answer related to the new question based on the new question.
8. A data processing apparatus, characterized in that the apparatus comprises:
the first receiving module is used for receiving a user request, wherein the user request comprises an identification of an access volume;
the first calling module is used for calling the follow-up access book data corresponding to the follow-up access book from a database according to the identification of the follow-up access book, and the follow-up access book data are structured data;
the second receiving module is used for receiving follow-up answers input by a user aiming at the follow-up questionnaire data;
the first generation module generates the follow-up answer data based on the follow-up answer, wherein the follow-up answer data is structured data;
the first determination module is used for determining follow-up medical data of the user according to the follow-up answer data and the follow-up questionnaire data, and the follow-up medical data is structured data.
9. An electronic device, comprising:
one or more processors; and
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out a method according to any one of claims 1 to 7.
10. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method according to any one of claims 1 to 7.
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