CN111785343A - Follow-up method and device, electronic equipment and storage medium - Google Patents
Follow-up method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of artificial intelligence, and can be applied to an intelligent medical scene so as to promote the construction of an intelligent city. Provided are a follow-up method, a follow-up device, an electronic device and a storage medium, wherein the method comprises the following steps: determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target; determining the similarity of each feature and preset follow-up contents; according to the similarity, determining target follow-up contents corresponding to each feature from the preset follow-up contents; acquiring a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up; and performing follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode and preset fixed follow-up visit content. The invention can improve the comprehensiveness of the follow-up content and the follow-up efficiency. In addition, the application also relates to a block chain technology, and a follow-up result obtained by follow-up can be stored in the block chain.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a follow-up method, a follow-up device, electronic equipment and a storage medium.
Background
Currently, in order to provide continuous care or treatment for patients with chronic diseases, follow-up visits to patients are required to update the disease status of patients. However, in practice, it is found that the follow-up contents are generated according to the disease types and the disease degrees of patients, the follow-up contents are relatively single and not comprehensive, and the case data needs to be inquired during follow-up, which is not efficient.
Therefore, how to improve the comprehensiveness of the follow-up content and improve the follow-up efficiency is a technical problem that needs to be solved urgently.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a follow-up method, device, electronic device and storage medium, which can improve the comprehensiveness of the follow-up content and improve the follow-up efficiency.
A first aspect of the present invention provides a follow-up method, comprising:
determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target;
determining the similarity of each feature and preset follow-up contents;
according to the similarity, determining target follow-up contents corresponding to each feature from the preset follow-up contents;
acquiring a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up;
and performing follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode and preset fixed follow-up visit content.
In a possible implementation manner, the performing a follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode, and a preset fixed follow-up visit content includes:
if the follow-up mode is a follow-up of a questionnaire, generating a follow-up questionnaire according to the target follow-up content and the fixed follow-up content;
and sending the follow-up access volume to a first terminal of the follow-up target.
In a possible implementation manner, the performing a follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode, and a preset fixed follow-up visit content includes:
if the follow-up mode is telephone follow-up, generating telephone follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the telephone follow-up prompt message to a second terminal of a follow-up staff.
In a possible implementation manner, the performing a follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode, and a preset fixed follow-up visit content includes:
if the follow-up mode is voice follow-up, converting the target follow-up content and the fixed follow-up content into follow-up voice;
and sending the follow-up voice to a first terminal of the follow-up target.
In a possible implementation manner, the performing a follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode, and a preset fixed follow-up visit content includes:
if the follow-up mode is the reservation follow-up, generating reservation follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the reservation follow-up prompt message to a second terminal of a follow-up staff.
In a possible implementation manner, after the follow-up visit is performed on the follow-up target according to the target follow-up visit content, the follow-up visit manner, and preset fixed follow-up visit content, the follow-up visit method further includes:
obtaining follow-up results;
performing data processing on the follow-up result to obtain key data;
sending the key data to a preset third terminal of the doctor;
and when receiving the summary information returned by the third terminal, sending the summary information to the first terminal of the follow-up target.
In one possible implementation, the plurality of features includes a disease condition feature, a medication feature, and a course learning feature.
A second aspect of the present invention provides a follow-up apparatus comprising:
the determining module is used for determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target;
the determining module is further configured to determine similarity between each of the features and preset follow-up content;
the determining module is further configured to determine, according to the similarity, target follow-up content corresponding to each feature from the preset follow-up content;
the acquisition module is used for acquiring a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up;
and the follow-up module is used for carrying out follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode and the preset fixed follow-up visit content.
A third aspect of the invention provides an electronic device comprising a processor and a memory, the processor being configured to implement the method of follow-up when executing a computer program stored in the memory.
A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of follow-up.
By the technical scheme, the follow-up contents aiming at the current disease condition of the follow-up target can be determined through artificial intelligence according to various characteristics corresponding to the follow-up target, the comprehensiveness of the follow-up contents is improved, the follow-up contents are determined without the need of a follow-up person to specially inquire data such as historical cases of the follow-up target, the time is saved, the follow-up efficiency is improved, meanwhile, various follow-up modes are supported, the follow-up target can be conveniently selected by the person, the follow-up modes are used, the follow-up delay and the follow-up interruption caused by emergency are avoided to a certain extent, and the follow-up efficiency is also improved.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of a follow-up method disclosed in the present invention.
FIG. 2 is a functional block diagram of a preferred embodiment of a follow-up device disclosed in the present invention.
Fig. 3 is a schematic structural diagram of an electronic device implementing a follow-up method according to a preferred embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
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 invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
The follow-up method of the embodiment of the invention is applied to the electronic equipment, and can also be applied to a hardware environment formed by the electronic equipment and a server connected with the electronic equipment through a network, and the server and the electronic equipment are jointly executed. Networks include, but are not limited to: a wide area network, a metropolitan area network, or a local area network.
A server may refer to a computer system that provides services to other devices (e.g., electronic devices) in a network. A personal computer may also be called a server if it can externally provide a File Transfer Protocol (FTP) service. In a narrow sense, a server refers to a high-performance computer, which can provide services to the outside through a network, and compared with a common personal computer, the server has higher requirements on stability, security, performance and the like, and therefore, hardware such as a CPU, a chipset, a memory, a disk system, a network and the like is different from that of the common personal computer.
The electronic device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware thereof includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like. The electronic device may also include a network device and/or a user device. The network device includes, but is not limited to, a single network device, a server group consisting of a plurality of network devices, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network devices, wherein the Cloud Computing is one of distributed Computing, and is a super virtual computer consisting of a group of loosely coupled computers. The user device includes, but is not limited to, any electronic product that can interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device, for example, a personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), or the like.
Referring to fig. 1, fig. 1 is a flowchart illustrating a preferred embodiment of a follow-up method according to the present invention. The order of the steps in the flowchart may be changed, and some steps may be omitted. Wherein, the execution subject of the follow-up method can be an electronic device.
S11, determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target.
Wherein, the follow-up target can refer to a diabetic patient or other chronic disease patient needing medical staff to know the condition.
Wherein the plurality of characteristics includes disease condition characteristics, medication characteristics, and course learning characteristics.
Wherein, the disease condition characteristics include time points for measuring various indexes of the disease within a preset time range (such as within one week) and measurement results, such as blood sugar values. The medication characteristics include the number of times the medication is used and the time points, such as the number of times the insulin is injected and the time points, within a preset time range. Generally, hospitals organize courses to guide and train patients, and patients can better understand their condition, better cooperate with doctors' treatment and better participate in the treatment process by themselves by taking the courses, and the course learning characteristics include courses, time points and the like which are learned within a preset time range.
And S12, determining the similarity of each feature and the preset follow-up content.
In the embodiment of the invention, the feature can be converted into a feature vector, the follow-up content is converted into a follow-up vector, and a formula for calculating the similarity between the feature and the preset follow-up content is as follows, wherein x represents the feature vector corresponding to the feature, y represents the follow-up vector corresponding to the follow-up content, d (x, y) represents the distance between the feature vector and the follow-up vector, and sim (x, y) represents the similarity between the feature and the preset follow-up content. The smaller the distance, the greater the similarity.
And S13, determining target follow-up contents corresponding to each feature from the preset follow-up contents according to the similarity.
In the embodiment of the invention, the follow-up content with the maximum similarity with each characteristic is selected from the preset follow-up contents as the target follow-up content. I.e. the target follow-up content is most relevant to the situation of the patient (the follow-up target) itself.
S14, obtaining a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up.
In the embodiment of the invention, each patient can pre-select a follow-up mode according to the needs of the patient. The system maintains the follow-up mode of the latest choice of the patient.
S15, follow-up visit is carried out on the follow-up target according to the target follow-up visit content, the follow-up visit mode and the preset fixed follow-up visit content.
Specifically, the following procedure of performing the following visit on the following visit target according to the target following visit content, the following visit mode and the preset fixed following visit content includes:
if the follow-up mode is a follow-up of a questionnaire, generating a follow-up questionnaire according to the target follow-up content and the fixed follow-up content;
and sending the follow-up access volume to a first terminal of the follow-up target.
In this optional embodiment, a preset follow-up questionnaire template may be obtained, the fixed follow-up content and the target follow-up content are filled in the questionnaire template, a follow-up questionnaire is generated, and the follow-up questionnaire is sent to the first terminal of the patient. The patient may fill out a questionnaire on the fly to complete the follow-up.
Specifically, the following procedure of performing the following visit on the following visit target according to the target following visit content, the following visit mode and the preset fixed following visit content includes:
if the follow-up mode is telephone follow-up, generating telephone follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the telephone follow-up prompt message to a second terminal of a follow-up staff.
The telephone follow-up prompt message is used for prompting the follow-up staff to follow-up the follow-up target by using a telephone follow-up mode, and may include but is not limited to a follow-up time, telephone information of the follow-up target and the like.
In this optional embodiment, if the follow-up target selects a telephone follow-up mode, a telephone follow-up prompt message may be generated, and the target follow-up content, the fixed follow-up content, and the telephone follow-up prompt message may be sent to a second terminal of a follow-up person to prompt the follow-up person to follow-up the follow-up target in a telephone follow-up mode.
Specifically, the following procedure of performing the following visit on the following visit target according to the target following visit content, the following visit mode and the preset fixed following visit content includes:
if the follow-up mode is voice follow-up, converting the target follow-up content and the fixed follow-up content into follow-up voice;
and sending the follow-up voice to a first terminal of the follow-up target.
In this optional embodiment, if the follow-up target selects a voice follow-up mode, the target follow-up content and the fixed follow-up content may be converted into a follow-up voice, the follow-up voice is sent to the first terminal of the follow-up target, and when the follow-up target inputs voice information for the follow-up voice, the voice information may be stored in a database.
Specifically, the following procedure of performing the following visit on the following visit target according to the target following visit content, the following visit mode and the preset fixed following visit content includes:
if the follow-up mode is the reservation follow-up, generating reservation follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the reservation follow-up prompt message to a second terminal of a follow-up staff.
As an optional implementation manner, if the follow-up target selects a follow-up reservation manner, a follow-up reservation prompt message is generated, and the target follow-up content, the fixed follow-up content and the follow-up reservation prompt message are sent to a second terminal of a follow-up person to prompt the follow-up person to schedule time for follow-up visit on the follow-up target.
As an optional implementation manner, the follow-up target is followed up according to the target follow-up content, the follow-up mode and preset fixed follow-up content, and the method further includes:
obtaining follow-up results;
performing data processing on the follow-up result to obtain key data;
sending the key data to a preset third terminal of the doctor;
and when receiving the summary information returned by the third terminal, sending the summary information to the terminal equipment of the follow-up target.
In this alternative embodiment, the follow-up result may be text content or voice content, and the follow-up result may be used to perform data processing to obtain key data, such as filtering using a preset dictionary to obtain relevant content about diseases. And sending the key data to a third preset doctor terminal, and sending summary information to the terminal equipment of the follow-up target when receiving the summary information returned by the third terminal. Wherein the summary information may be a recommendation given by a physician.
It is emphasized that, in order to further ensure the privacy and security of the follow-up result, the follow-up result may also be stored in a node of a block chain.
In the method flow described in fig. 1, the follow-up content corresponding to the current disease condition of the follow-up target can be determined by artificial intelligence according to various characteristics corresponding to the follow-up target, the comprehensiveness of the follow-up content is improved, a follow-up person does not need to specially inquire data such as a historical case of the follow-up target to determine the follow-up content, time is saved, the follow-up efficiency is improved, meanwhile, various follow-up modes are supported, the follow-up target can be conveniently selected by the person, the follow-up modes are used, delay of follow-up due to an emergency and interruption of follow-up are avoided to a certain extent, and the follow-up efficiency is also improved.
FIG. 2 is a functional block diagram of a preferred embodiment of a follow-up device disclosed in the present invention.
Referring to fig. 2, the follow-up device 20 can be operated in an electronic device. The visiting device 20 may comprise a plurality of functional modules consisting of program code segments. The program code of the various program segments in the follow-up device 20 may be stored in a memory and executed by at least one processor to perform some or all of the steps of the follow-up method described in fig. 1.
In this embodiment, the visiting device 20 may be divided into a plurality of functional modules according to the functions performed by the visiting device. The functional module may include: a determination module 201, an acquisition module 202 and a follow-up module 203. The module referred to herein is a series of computer program segments capable of being executed by at least one processor and capable of performing a fixed function and is stored in memory.
The determining module 201 is configured to determine a follow-up target and determine a plurality of features corresponding to the follow-up target.
Wherein, the follow-up target can refer to a diabetic patient or other chronic disease patient needing medical staff to know the condition.
Wherein the plurality of characteristics includes disease condition characteristics, medication characteristics, and course learning characteristics.
Wherein, the disease condition characteristics include time points for measuring various indexes of the disease within a preset time range (such as within one week) and measurement results, such as blood sugar values. The medication characteristics include the number of times the medication is used and the time points, such as the number of times the insulin is injected and the time points, within a preset time range. Generally, hospitals organize courses to guide and train patients, and patients can better understand their condition, better cooperate with doctors' treatment and better participate in the treatment process by themselves by taking the courses, and the course learning characteristics include courses, time points and the like which are learned within a preset time range.
The determining module 201 is further configured to determine a similarity between each of the features and a preset follow-up content.
In the embodiment of the invention, the feature can be converted into a feature vector, the follow-up content is converted into a follow-up vector, and a formula for calculating the similarity between the feature and the preset follow-up content is as follows, wherein x represents the feature vector corresponding to the feature, y represents the follow-up vector corresponding to the follow-up content, d (x, y) represents the distance between the feature vector and the follow-up vector, and sim (x, y) represents the similarity between the feature and the preset follow-up content. The smaller the distance, the greater the similarity.
The determining module 201 is further configured to determine, according to the similarity, a target follow-up content corresponding to each feature from the preset follow-up contents.
In the embodiment of the invention, the follow-up content with the maximum similarity with each characteristic is selected from the preset follow-up contents as the target follow-up content. I.e. the target follow-up content is most relevant to the situation of the patient (the follow-up target) itself.
An obtaining module 202, configured to obtain a follow-up mode corresponding to the follow-up target, where the follow-up mode includes a phone follow-up, a questionnaire follow-up, a voice follow-up, and a reservation follow-up.
In the embodiment of the invention, each patient can pre-select a follow-up mode according to the needs of the patient. The system maintains the follow-up mode of the latest choice of the patient.
The follow-up module 203 is configured to perform follow-up on the follow-up target according to the target follow-up content, the follow-up mode, and a preset fixed follow-up content.
As an optional implementation manner, the following mode of the following access module 203, according to the target following access content, the following access mode, and the preset fixed following access content, is specifically:
if the follow-up mode is a follow-up of a questionnaire, generating a follow-up questionnaire according to the target follow-up content and the fixed follow-up content;
and sending the follow-up access volume to a first terminal of the follow-up target.
In this optional embodiment, a preset follow-up questionnaire template may be obtained, the fixed follow-up content and the target follow-up content are filled in the questionnaire template, a follow-up questionnaire is generated, and the follow-up questionnaire is sent to the first terminal of the patient. The patient may fill out a questionnaire on the fly to complete the follow-up.
As an optional implementation manner, the following mode of the following access module 203, according to the target following access content, the following access mode, and the preset fixed following access content, is specifically:
if the follow-up mode is telephone follow-up, generating telephone follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the telephone follow-up prompt message to a second terminal of a follow-up staff.
The telephone follow-up prompt message is used for prompting the follow-up staff to follow-up the follow-up target by using a telephone follow-up mode, and may include but is not limited to a follow-up time, telephone information of the follow-up target and the like.
In this optional embodiment, if the follow-up target selects a telephone follow-up mode, a telephone follow-up prompt message may be generated, and the target follow-up content, the fixed follow-up content, and the telephone follow-up prompt message may be sent to a second terminal of a follow-up person to prompt the follow-up person to follow-up the follow-up target in a telephone follow-up mode.
As an optional implementation manner, the following mode of the following access module 203, according to the target following access content, the following access mode, and the preset fixed following access content, is specifically:
if the follow-up mode is voice follow-up, converting the target follow-up content and the fixed follow-up content into follow-up voice;
and sending the follow-up voice to a first terminal of the follow-up target.
In this optional embodiment, if the follow-up target selects a voice follow-up mode, the target follow-up content and the fixed follow-up content may be converted into a follow-up voice, the follow-up voice is sent to the first terminal of the follow-up target, and when the follow-up target inputs voice information for the follow-up voice, the voice information may be stored in a database.
As an optional implementation manner, the following mode of the following access module 203, according to the target following access content, the following access mode, and the preset fixed following access content, is specifically:
if the follow-up mode is the reservation follow-up, generating reservation follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the reservation follow-up prompt message to a second terminal of a follow-up staff.
As an optional implementation manner, if the follow-up target selects a follow-up reservation manner, a follow-up reservation prompt message is generated, and the target follow-up content, the fixed follow-up content and the follow-up reservation prompt message are sent to a second terminal of a follow-up person to prompt the follow-up person to schedule time for follow-up visit on the follow-up target.
As an optional implementation manner, the obtaining module 202 is further configured to, by the follow-up module 203, obtain a follow-up result after the follow-up target is followed according to the target follow-up content, the follow-up manner, and preset fixed follow-up content;
the follow-up device 20 may further include:
the processing module is used for carrying out data processing on the follow-up result to obtain key data;
the sending module is used for sending the key data to a preset third terminal of the doctor;
the sending module is further configured to send the summary information to the first terminal of the follow-up target when receiving the summary information returned by the third terminal.
In this alternative embodiment, the follow-up result may be text content or voice content, and the follow-up result may be used to perform data processing to obtain key data, such as filtering using a preset dictionary to obtain relevant content about diseases. And sending the key data to a third preset doctor terminal, and sending summary information to the terminal equipment of the follow-up target when receiving the summary information returned by the third terminal. Wherein the summary information may be a recommendation given by a physician.
In the follow-up device 20 depicted in fig. 2, the follow-up content corresponding to the current disease condition of the follow-up target can be determined by artificial intelligence according to various characteristics corresponding to the follow-up target, so that the comprehensiveness of the follow-up content is improved, a follow-up person is not required to specially inquire data such as a historical case of the follow-up target to determine the follow-up content, the time is saved, the follow-up efficiency is improved, meanwhile, various follow-up modes are supported, the follow-up target can be conveniently selected by the person, the follow-up modes can be used, the follow-up delay and the follow-up interruption caused by an emergency situation are avoided to a certain extent, and the follow-up efficiency is also improved.
It is emphasized that, in order to further ensure the privacy and security of the follow-up result, the follow-up result may also be stored in a node of a block chain.
As shown in fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to a preferred embodiment of the present invention for implementing a follow-up method. The electronic device 3 comprises a memory 31, at least one processor 32, a computer program 33 stored in the memory 31 and executable on the at least one processor 32, and at least one communication bus 34.
Those skilled in the art will appreciate that the schematic diagram shown in fig. 3 is merely an example of the electronic device 3, and does not constitute a limitation of the electronic device 3, and may include more or less components than those shown, or combine some components, or different components, for example, the electronic device 3 may further include an input/output device, a network access device, and the like.
The electronic device 3 may also include, but is not limited to, any electronic product that can interact with a user through a keyboard, a mouse, a remote controller, a touch panel, or a voice control device, for example, a Personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game machine, an Internet Protocol Television (IPTV), an intelligent wearable device, and the like. The Network where the electronic device 3 is located includes, but is not limited to, the internet, a wide area Network, a metropolitan area Network, a local area Network, a Virtual Private Network (VPN), and the like.
The at least one Processor 32 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a transistor logic device, a discrete hardware component, etc. The processor 32 may be a microprocessor or the processor 32 may be any conventional processor or the like, and the processor 32 is a control center of the electronic device 3 and connects various parts of the whole electronic device 3 by various interfaces and lines.
The memory 31 may be used to store the computer program 33 and/or the module/unit, and the processor 32 may implement various functions of the electronic device 3 by running or executing the computer program and/or the module/unit stored in the memory 31 and calling data stored in the memory 31. The memory 31 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the electronic device 3, and the like. In addition, the memory 31 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, and the like.
With reference to fig. 1, the memory 31 of the electronic device 3 stores a plurality of instructions to implement a follow-up method, and the processor 32 executes the plurality of instructions to implement:
determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target;
determining the similarity of each feature and preset follow-up contents;
according to the similarity, determining target follow-up contents corresponding to each feature from the preset follow-up contents;
acquiring a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up;
and performing follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode and preset fixed follow-up visit content.
Specifically, the processor 32 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the instruction, which is not described herein again.
In the electronic device 3 depicted in fig. 3, the follow-up content corresponding to the current disease condition of the follow-up target can be determined by artificial intelligence according to various characteristics corresponding to the follow-up target, so that the comprehensiveness of the follow-up content is improved, a follow-up person does not need to specially inquire data such as a historical case of the follow-up target to determine the follow-up content, the time is saved, the follow-up efficiency is improved, meanwhile, various follow-up modes are supported, the follow-up target can be conveniently selected by the person, the various follow-up modes are used, the follow-up delay and the follow-up interruption caused by an emergency are avoided to a certain extent, and the follow-up efficiency is also improved.
The integrated modules/units of the electronic device 3 may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program code may be in source code form, object code form, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
Further, the computer usable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A follow-up method, comprising:
determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target;
determining the similarity of each feature and preset follow-up contents;
according to the similarity, determining target follow-up contents corresponding to each feature from the preset follow-up contents;
acquiring a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up;
and performing follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode and preset fixed follow-up visit content.
2. The follow-up method according to claim 1, wherein the follow-up of the follow-up target according to the target follow-up content, the follow-up mode and a preset fixed follow-up content comprises:
if the follow-up mode is a follow-up of a questionnaire, generating a follow-up questionnaire according to the target follow-up content and the fixed follow-up content;
and sending the follow-up access volume to a first terminal of the follow-up target.
3. The follow-up method according to claim 1, wherein the follow-up of the follow-up target according to the target follow-up content, the follow-up mode and a preset fixed follow-up content comprises:
if the follow-up mode is telephone follow-up, generating telephone follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the telephone follow-up prompt message to a second terminal of a follow-up staff.
4. The follow-up method according to claim 1, wherein the follow-up of the follow-up target according to the target follow-up content, the follow-up mode and a preset fixed follow-up content comprises:
if the follow-up mode is voice follow-up, converting the target follow-up content and the fixed follow-up content into follow-up voice;
and sending the follow-up voice to a first terminal of the follow-up target.
5. The follow-up method according to claim 1, wherein the follow-up of the follow-up target according to the target follow-up content, the follow-up mode and a preset fixed follow-up content comprises:
if the follow-up mode is the reservation follow-up, generating reservation follow-up prompt information;
and sending the target follow-up content, the fixed follow-up content and the reservation follow-up prompt message to a second terminal of a follow-up staff.
6. The follow-up method according to any one of claims 1 to 5, wherein after the follow-up target is followed according to the target follow-up content, the follow-up mode and a preset fixed follow-up content, the follow-up method further comprises:
obtaining follow-up results;
performing data processing on the follow-up result to obtain key data;
sending the key data to a preset third terminal of the doctor;
and when receiving the summary information returned by the third terminal, sending the summary information to the first terminal of the follow-up target.
7. The follow-up method according to any one of claims 1 to 5, wherein the plurality of characteristics includes a disease condition characteristic, a medication characteristic, and a course learning characteristic.
8. A follow-up device, characterized in that the follow-up device comprises:
the determining module is used for determining a follow-up target and determining a plurality of characteristics corresponding to the follow-up target;
the determining module is further configured to determine similarity between each of the features and preset follow-up content;
the determining module is further configured to determine, according to the similarity, target follow-up content corresponding to each feature from the preset follow-up content;
the acquisition module is used for acquiring a follow-up mode corresponding to the follow-up target, wherein the follow-up mode comprises telephone follow-up, questionnaire follow-up, voice follow-up and reservation follow-up;
and the follow-up module is used for carrying out follow-up visit on the follow-up target according to the target follow-up visit content, the follow-up visit mode and the preset fixed follow-up visit content.
9. An electronic device, characterized in that the electronic device comprises a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the follow-up method according to any of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores at least one instruction which, when executed by a processor, implements a follow-up method according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112489747A (en) * | 2020-12-14 | 2021-03-12 | 平安国际智慧城市科技股份有限公司 | Chronic patient supervision method, device, equipment and medium based on analysis model |
| CN113724810A (en) * | 2021-08-31 | 2021-11-30 | 平安国际智慧城市科技股份有限公司 | Data processing method, device, equipment and readable storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107145755A (en) * | 2017-05-16 | 2017-09-08 | 陈韵岱 | Cardiovascular chronic diseases management method based on Intelligent Decision Support Technology |
| CN109243549A (en) * | 2018-07-11 | 2019-01-18 | 腾讯科技（深圳）有限公司 | A kind of intelligent follow-up method, device and server |
-
2020
- 2020-07-17 CN CN202010693085.1A patent/CN111785343A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107145755A (en) * | 2017-05-16 | 2017-09-08 | 陈韵岱 | Cardiovascular chronic diseases management method based on Intelligent Decision Support Technology |
| CN109243549A (en) * | 2018-07-11 | 2019-01-18 | 腾讯科技（深圳）有限公司 | A kind of intelligent follow-up method, device and server |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112489747A (en) * | 2020-12-14 | 2021-03-12 | 平安国际智慧城市科技股份有限公司 | Chronic patient supervision method, device, equipment and medium based on analysis model |
| CN113724810A (en) * | 2021-08-31 | 2021-11-30 | 平安国际智慧城市科技股份有限公司 | Data processing method, device, equipment and readable storage medium |
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