CN109243549A - A kind of intelligent follow-up method, device and server - Google Patents
A kind of intelligent follow-up method, device and server Download PDFInfo
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- G10L15/00—Speech recognition
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- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
- G10L2015/0631—Creating reference templates; Clustering
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Abstract
The present invention provides a kind of intelligent follow-up method, device and servers, and the method includes obtaining target follow-up method, target follow-up template and target follow-up trigger condition；First filter is generated according to the target follow-up trigger condition and the first attribute field, is gathered according to first filter inquiry to follow-up patient；The second filter is generated according to target follow-up method and the second attribute field, target follow-up feedback client set is inquired according to second filter；Each target follow-up feedback client into target follow-up feedback client set issues target follow-up template, and receives the Follow-up results of the target follow-up feedback client feedback.The present invention is carried out the automatic distributing of follow-up template by customization follow-up element, based on follow-up element and collects three key steps of Follow-up results automatically, is realized the whole-course automation of follow-up process, to promote follow-up efficiency, is mitigated doctors and patients' burden.
Description
Technical field
The present invention relates to computer field more particularly to a kind of intelligent follow-up methods, device and server.
Background technique
Existing hospital's follow-up system is to provide the service of notice to patient around phone, short message mode mostly, is not had substantially
There is the function of collecting data, and notifies service substantially also based on questionnaire survey, it cannot be by problem and the data for needing be collected into
It is effectively associated with, follow-up can not be embodied and be really worth.
In addition, follow-up is interacted with papery questionnaire or text as main means, user experience is poor, and Follow-up results are difficult
To carry out digitlization and structuring processing, therefore, it is difficult to carry out Correlative data analysis based on Follow-up results.
Summary of the invention
In order to solve the above-mentioned technical problem, the invention proposes a kind of intelligent follow-up method, device and servers.The present invention
Specifically realized with following technical solution:
In a first aspect, a kind of intelligent follow-up method, comprising:
Supervise client defines follow-up element and the follow-up element is transmitted to Following-up Service device, and the follow-up is wanted
Element includes follow-up method, follow-up template and follow-up trigger condition；
The Following-up Service device obtains target follow-up element corresponding with follow-up instruction, and the target follow-up element includes mesh
Mark follow-up method, target follow-up template and target follow-up trigger condition；
The Following-up Service device generates first filter, root according to the target follow-up trigger condition and the first attribute field
It inquires according to the first filter and gathers to follow-up patient, first attribute field is that target follow-up trigger condition is corresponding
Attribute field；
The Following-up Service device generates the second filter according to target follow-up method and the second attribute field, according to described the
Described to inquire target follow-up feedback client set in follow-up patient set, second attribute field is tow filtrator
The corresponding attribute field of target follow-up method；
Client is fed back in each target follow-up of the Following-up Service device into target follow-up feedback client set
Target follow-up template is issued, and receives the Follow-up results of the target follow-up feedback client feedback..
Second aspect, a kind of intelligent follow-up method, comprising:
Target follow-up element corresponding with follow-up instruction is obtained, the target follow-up element includes target follow-up method, mesh
Mark follow-up template and target follow-up trigger condition；
First filter is generated according to the target follow-up trigger condition and the first attribute field, according to first filtering
Device inquiry is gathered to follow-up patient, and first attribute field is the corresponding attribute field of target follow-up trigger condition；
The second filter is generated according to target follow-up method and the second attribute field, is inquired according to second filter
Client set is fed back in target follow-up, and second attribute field is the corresponding attribute field of target follow-up method；
Each target follow-up feedback client into target follow-up feedback client set issues target follow-up mould
Plate, and receive the Follow-up results of the target follow-up feedback client feedback.
The third aspect, a kind of intelligent follow-up device, comprising:
Target follow-up element obtains module, for obtaining corresponding with follow-up instruction target follow-up element, the target with
Visiting element includes target follow-up method, target follow-up template and target follow-up trigger condition；
Gather to follow-up patient and obtain module, for being generated according to the target follow-up trigger condition and the first attribute field
First filter is gathered according to first filter inquiry to follow-up patient, and first attribute field is target follow-up touching
The corresponding attribute field of clockwork spring part；
Target follow-up feeds back client and obtains module, for generating second according to target follow-up method and the second attribute field
Filter inquires target follow-up feedback client set according to second filter, and second attribute field is target
The corresponding attribute field of follow-up method；
Follow-up module, for each target follow-up feedback client hair into target follow-up feedback client set
Cloth target follow-up template, and receive the Follow-up results of the target follow-up feedback client feedback.
Client is fed back in fourth aspect, a kind of intelligent follow-up system, including Supervise client, Following-up Service device and follow-up
End；
The Supervise client includes follow-up element definition module, the follow-up element definition module, for defining
The follow-up element is simultaneously transmitted to Following-up Service device by follow-up element, the follow-up element include follow-up method, follow-up template and
Follow-up trigger condition；
The Following-up Service device includes:
Target follow-up element obtains module, for obtaining corresponding with follow-up instruction target follow-up element, the target with
Visiting element includes target follow-up method, target follow-up template and target follow-up trigger condition；
Gather to follow-up patient and obtain module, for being generated according to the target follow-up trigger condition and the first attribute field
First filter is gathered according to first filter inquiry to follow-up patient, and first attribute field is target follow-up touching
The corresponding attribute field of clockwork spring part；
Target follow-up feeds back client and obtains module, for generating second according to target follow-up method and the second attribute field
Filter inquires target follow-up feedback client set according to second filter, and second attribute field is target
The corresponding attribute field of follow-up method；
Follow-up module, for each target follow-up feedback client hair into target follow-up feedback client set
Cloth target follow-up template, and receive the Follow-up results of the target follow-up feedback client feedback.
5th aspect, a kind of computer readable storage medium, for storing program, described program is for realizing above-mentioned one kind
Intelligent follow-up method.
6th aspect, a kind of server, the server is for running a kind of above-mentioned intelligent follow-up device.
The present invention provides a kind of intelligent follow-up method, device and server, have it is following the utility model has the advantages that
(1) automatic distributing of follow-up template is carried out by customization follow-up element, based on follow-up element and collects follow-up automatically
As a result three key steps, realize the whole-course automation of follow-up process, to promote follow-up efficiency, mitigate doctors and patients' burden.
(2) voice follow-up is supported, to promote Patient Experience；It supports the analysis for Follow-up results, is doctor and patient
Guidance is provided.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is a kind of intelligent follow-up method implementation environment schematic diagram provided in an embodiment of the present invention；
Fig. 2 is a kind of intelligent follow-up method flow chart provided in an embodiment of the present invention；
Fig. 3 is checking method flow chart provided in an embodiment of the present invention；
Fig. 4 is the schematic diagram of Supervise client provided in an embodiment of the present invention；
Fig. 5 is follow-up template schematic diagram provided in an embodiment of the present invention；
Fig. 6 is the particular content schematic diagram of some patient data provided in an embodiment of the present invention；
Fig. 7 is the curve graph provided in an embodiment of the present invention obtained according to the patient data；
Fig. 8 is the variation tendency schematic diagram of survival rate within a certain period of time provided in an embodiment of the present invention；
Fig. 9 is a kind of Follow-up results processing method flow chart provided in an embodiment of the present invention；
Figure 10 (1) is stringent extraction result schematic diagram provided in an embodiment of the present invention；
Figure 10 (2) is fuzzy extraction result schematic diagram provided in an embodiment of the present invention；
Figure 11 is a kind of intelligent follow-up device block diagram provided in an embodiment of the present invention；
Figure 12 is Follow-up results processing module block diagram provided in an embodiment of the present invention；
Figure 13 is the structural block diagram of server provided in an embodiment of the present invention.
Specific embodiment
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The model that the present invention protects all should belong in member's every other embodiment obtained without making creative work
It encloses.
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to
Step or unit those of is clearly listed, but may include be not clearly listed or for these process, methods, product
Or other step or units that equipment is intrinsic.
Referring to Fig. 1, the embodiment of the invention provides a kind of intelligent follow-up method implementation environment schematic diagrames.The implementation environment packet
It includes: Supervise client 101, Following-up Service device 102 and follow-up feedback client 103.
Wherein, follow-up client 101 is communicated with the Following-up Service device 102, Supervise client 101 for set with
Visit mode, follow-up template and follow-up trigger condition, and setting result is transmitted to Following-up Service device, the Following-up Service device according to
The setting result carries out follow-up to follow-up feedback client 103.
Follow-up feedback client 103 is communicated with the Following-up Service device 102, and the follow-up feedback client 103 receives institute
State Following-up Service device 102 publication follow-up template, and to the Following-up Service device 102 feed back Follow-up results, in order to it is described with
It visits server 102 to receive and manage the Follow-up results, and Follow-up results is shown in Supervise client 101.
In conclusion follow-up client is realized in implementation environment of the embodiment of the present invention using Following-up Service device 102 as bridge
Information mutual communication between end 101 and follow-up feedback client 103.
The follow-up client 101 can have an one or more, the follow-up feedback client 103 can also have one or
Multiple, the Following-up Service device 102 can be independent computer equipment or Distributed Computer System.
The follow-up client 101 and Following-up Service device 102 and between can by wireless network or cable network into
Row communication, the Following-up Service device 102 and follow-up feedback client 103 between can by carrier network, wireless network or
Person's cable network communicates.
The embodiment of the present invention provides a kind of intelligent follow-up method, the intelligent follow-up method with Supervise client 101,
The intelligent follow-up system that Following-up Service device 102 and follow-up feedback client 103 are constituted is executing subject, as shown in Figure 2, comprising:
S101. Supervise client defines follow-up element and the follow-up element is transmitted to Following-up Service device, described
Follow-up element includes follow-up method, follow-up template and follow-up trigger condition.
It specifically, can be management object, different Supervise clients with follow-up client in the Following-up Service device
The corresponding different follow-up element in end.One Supervise client corresponds to one or more groups of follow-up elements, each group of follow-up element
It include three aspect content of follow-up method, follow-up template and follow-up trigger condition.
Follow-up template is set for the ease of Supervise client, it can be in the Following-up Service device in the embodiment of the present invention
One template library of middle maintenance is stored with common template in the template library.It is stored in template library in Following-up Service device common
The corresponding template of illness.If some doctor needs to set follow-up template for the patient with certain disease, can directly inquire
Whether the disease corresponding template is had existed in template library, and if it exists, then can directly be used, it is of course also possible to it
It is used after modifying.If the corresponding template of the disease is not present in template library, need to re-establish follow-up template.
Follow-up method can be wechat, short message, phone；Follow-up trigger condition can be based on data-triggered, be based on state
It is triggered with temporal joint.
By taking medical system as an example, two Supervise clients customize follow-up element to Following-up Service device if it exists, specifically
Customized content are as follows:
Supervise client identification: 001；
Physician names " Zhang San "；
Doctor's position: Cardiological attending physician；
Follow-up element 1: follow-up method: wechat follow-up；Follow-up template: hypertension follow-up template；Follow-up trigger condition: it is based on
Data-triggered；
Follow-up element 2: follow-up method: Effect of follow-up visit by telephone；Follow-up template: cerebral thrombosis follow-up template；Follow-up trigger condition: it is based on
State and temporal joint triggering.
Follow-up client identification: 002；
Physician names: " Li Si "；
Doctor's position: Respiratory Medicine archiater；
Follow-up element 3: follow-up method: wechat follow-up；Follow-up template: Bronchopneumonia follow-up template；Follow-up trigger condition:
It is triggered based on state and temporal joint.
Hypertension follow-up template can be used existing template in template library, and cerebral thrombosis follow-up template and Bronchopneumonia
Follow-up template needs doctor to be customized.It can be based on data-triggered and trigger follow-up when certain item data meets trigger condition, than
Such as, if high pressure when patient assessment is greater than 150, follow-up is triggered.It is if can be patient based on state and temporal joint triggering
Inpatient then triggers follow-up after preset time after patient discharge.
In above-mentioned customized content, Following-up Service device stores two Supervise client identifications, and corresponding storage follow-up
Management client essential information and related follow-up element.The Supervise client essential information includes mark, physician names
With doctor's position.
S102. it is instructed in response to follow-up, the Following-up Service device obtains target follow-up corresponding with follow-up instruction and wants
Element, the target follow-up element include target follow-up method, target follow-up template and target follow-up trigger condition.
Specifically, the follow-up instruction can be issued by Supervise client, can also be pressed by the Following-up Service device
It is automatically generated according to preset rules.
S103. the Following-up Service device generates the first filtering according to the target follow-up trigger condition and the first attribute field
Device inquires in the Following-up Service device according to the first filter and gathers to follow-up patient, first attribute field
For the corresponding attribute field of target follow-up trigger condition.
S104. the Following-up Service device generates the second filter according to target follow-up method and the second attribute field, according to
Second filter is described to inquire target follow-up feedback client set, second attribute in follow-up patient set
Field is the corresponding attribute field of target follow-up method.
Specifically, the Supervise client can be at any time to Following-up Service device typing patient information, the follow-up clothes
Business device carries out unified record and management to patient information, and the specific object field that the patient information includes can be according to reality
It needs to be customized.
For example, patient information includes following fields:
Whether patient's title, patient's WeChat ID, patient's telephone number, conditions of patients diagnosis, conditions of patients data, patient live
Institute, length of patient stay, patient discharge's time.A record corresponding to above-mentioned patient information are as follows: " jully ",
" wx2465255 ", " hypertension ", " high pressure 160, low pressure 90 ", "No", " null ", " null ".
If what is carried in follow-up instruction is follow-up element 1, the first attribute field is conditions of patients data, the second attribute word
Section is " patient's WeChat ID ", and the content of first filter can be the mesh of conditions of patients data mesohigh > 150, the second filter
Be inquire the WeChat ID of target follow-up feedback client, final realize issues follow-up template by way of wechat follow-up
And acquire the purpose of Follow-up results.
S105. to the target follow-up feedback client set in each target follow-up feedback client publication target with
Template is visited, and receives the Follow-up results of the target follow-up feedback client feedback.
In a feasible embodiment, in order to guarantee the accuracy of Follow-up results, Follow-up results can also be carried out
Audit should include target Supervise client in follow-up instruction in order to be audited, the target Supervise visitor
Family end is for auditing Follow-up results, and the patient information should include that follow-up is in progress, the checking method such as Fig. 3 institute
Show, comprising:
S201. the Follow-up results of patient are fed back to target Supervise client by Following-up Service device.
S202. the target Supervise client is obtained for the auditing result of Follow-up results.
If S203. audit passes through, by the Follow-up results typing Following-up Service device, and update the follow-up of the patient into
Exhibition.
If S204. audit does not pass through, follow-up template is issued to target follow-up feedback client again, until audit is logical
It crosses.
In one preferred embodiment, the Following-up Service device supports the customized display word of Supervise client
Section, i.e. Following-up Service device are management object with Supervise client, and different Supervise clients can show different field
Content.The Following-up Service device, which can also be in progress to the follow-up of each patient, to be recorded, and is believed according to follow-up progress patient
Breath carries out classification and shows.Referring to FIG. 4, it illustrates the schematic diagrames of Supervise client.It can be with when carrying out page presentation
The data value for supporting the last follow-up to be collected into.
In one preferred embodiment, the Following-up Service device supports the customized each data of Supervise client
Incidence relation between field, and support screening function.The first field is such as carried out subordinate relation with the second field to be associated with, then
When Supervise client is shown, the second field is automatically associated to behind the first field, so that the first field contents
Display adjacent with the second field contents.
In a preferred embodiment, Supervise client can be with customized follow-up template, customized content packet
The sequence of the problem of asking a question to user and problem is included, it, can be with custom option if problem is multiple-choice question.It is preferred real at one
It applies in mode, human-computer dialogue machine people can be used in the Following-up Service device, will be in follow-up template in a manner of interactive
Appearance is transmitted to follow-up feedback client.As shown in figure 5, human-computer dialogue machine people thinks that patient inquires according to the time started, obtains and suffer from
Person's reply content, and certain fields of the auto-associating into patient information.
The Follow-up results of the Following-up Service device record each time, and support self-defining data analysis model.
It can divide using single patient as research object using some attribute and time as data in the Data Analysis Model
Variable is analysed, such as is analyzed according to the change curve that follow-up year/number carries out a certain index.Referring to FIG. 6, it illustrates to certain
The particular content of a patient data, referring to FIG. 7, it illustrates the curve graphs obtained according to the patient data.
The Data Analysis Model can also be made using some Disease group as research object with a certain index and time
For data situational variables, such as a certain index changes with time tendency chart, and the index is that the synthesis of Disease group refers to
The expression of the statistical indicators such as average value weighted average can be used in mark.
For example, can be according to indexs such as survival rate, rehabilitation rate, the death rates of statistics Disease group, and shown.
Referring to FIG. 8, it illustrates the variation tendencies of survival rate within a certain period of time.
When being shown, the Following-up Service device support shows each attribute by various figures, such as
Histogram, line chart, cake chart also support to be shown according to various timing nodes, for example, can choose monthly, season, year
It shows.
In next preferred embodiment, the Following-up Service device can be automatically analyzed Follow-up results, and will
Follow-up results statistical result relevant to follow-up content is matched, and recommends therapeutic scheme Xiang doctor according to matching result.
In one preferred embodiment, the Following-up Service device supports the Follow-up results of acquisition speech form, and energy
It is enough Follow-up results to be identified and are extracted automatically so that obtain processed structuring Follow-up results.In order to reach above-mentioned mesh
, the embodiment of the present invention discloses a kind of Follow-up results processing method, as shown in Figure 9, comprising:
S301. text is converted for voice based on default speech recognition algorithm.
The default speech recognition algorithm includes training speech recognition modeling, and identifies language according to the speech recognition modeling
The training method of sound, the speech recognition modeling includes:
P1. training voice signal is determined.
P2. sound source label corresponding with training voice signal is determined.
Sound source label is used to extract the reference object of the intonation feature of training voice signal as speech recognition modeling,
In, speech recognition modeling can extract the intonation feature of trained voice signal.
P3. semantic label corresponding with training voice signal is determined.
Semantic label is used to extract the reference object of the semantic feature of training voice signal as speech recognition modeling,
In, speech recognition modeling can also extract the semantic feature of trained voice signal.
P4. according to training voice signal, sound source label and semantic label training speech recognition modeling.
Training sample include training voice signal, with the corresponding sound source label of training voice signal and with train voice signal
Corresponding semantic label.Trained target is to be carried out repeatedly by multiple training samples to the target component in speech recognition modeling
Training adjusts the parameter value of target component so that the semanteme and training language that speech recognition modeling identifies training voice signal
The error of semanteme represented by the corresponding semantic label of sound signal is minimum.
Preferably, when according to training voice signal, sound source label and semantic label training speech recognition modeling, Ke Yixian
Framing is carried out to training voice signal according to time dimension, obtains multiframe voice signal.By framing operation to training voice letter
It number is pre-processed, training voice signal can be divided into smaller unit, restrain training process quickly, speech recognition
Model can also more accurately identify shorter voice signal when identifying targeted voice signal.
S302. the keyword in the text is extracted based on predetermined keyword library.
Specifically, the field supported in the keyword and random server is corresponding.For example it for hypertensive patient, answers
When whether the data such as storage high pressure, low pressure, and record have the tingle phenomenon of dizzy phenomenon, four limbs；It, should for cardiac
The data such as heart rate, pulse are stored, therefore, high pressure, low pressure, heart rate, pulse, dizzy phenomenon, the tingle phenomenon of four limbs are keyword,
It is recorded in keywords database.
Specifically, extraction can strictly be extracted or obscure by extracting keyword, in stringent extract, it is necessary to complete with keyword
It can unanimously be extracted entirely；And in fuzzy extract, as long as identical as keyword senses can be extracted.Figure 10
(1) stringent extract as a result, Figure 10 (2) shows fuzzy extraction result is shown.
S303. the number and grammatical term for the character in the text are extracted.
The grammatical term for the character includes but is not limited to: it yes or not, it is no, and have, does not have, without etc..
S304. keyword, number and grammatical term for the character are ranked up according to its sequence in the text, obtain target character
String.
By taking the follow-up for some hypertensive patient as an example, target string are as follows: 160 low pressure of high pressure, 90 heart rate 85 is without a head
Phenomenon of swooning is without the tingle phenomenon of four limbs.
S305. the Follow-up results indicated in the form of key-value pair are obtained according to target string.
With key-value pair identify Follow-up results be a kind of structural data, can be directly entered random server or
It is shown in Supervise client.
Further, if the Following-up Service device is unable to get legal follow-up knot after handling for Follow-up results
Fruit does not such as analyze Effective Numerical, can feed back the good fixed words art of preset in advance, such as " please providing data again ", so as to
Follow-up results are acquired again.In addition, the Following-up Service device can also to the Follow-up results of all previous acquisition and this obtain with
It visits result and carries out comprehensive analysis, and provide automatically and pre- examine information.For example the data value that this follow-up semanteme parses is higher than last time
Follow-up value, machine can automatically reply patient: " continuing with take XX medicine ", can guarantee that Patient Experience is more preferable, mitigates simultaneously in this way
The burden of doctor terminal reaches best follow-up effect.
The embodiment of the present invention can realize the automatic distributing of follow-up template using Following-up Service device as bridge, Follow-up results
Automation collection and processing, and voice is supported to input, so that the Experience Degree for perceiving level to user is promoted, while can make to cure
Raw follow-up work is more efficient, supports while compare and analyze with disease historical data, with the same data of people, with
And therapeutic scheme guidance is provided based on the analysis results, the value of big data is given full play to, follow-up overall process is held automatically
It goes, the connection between doctors and patients is more natural, smooth, and Follow-up Value is higher.
The embodiment of the present invention provides a kind of intelligent follow-up device, as shown in figure 11, comprising:
Target follow-up element obtains module 401, for obtaining target follow-up element corresponding with follow-up instruction, the target
Follow-up element includes target follow-up method, target follow-up template and target follow-up trigger condition；
Gather to follow-up patient and obtain module 402, for according to the target follow-up trigger condition and the first attribute field
Generate first filter, according to the first filter inquiry to follow-up patient gather, first attribute field be target with
Visit the corresponding attribute field of trigger condition；
Target follow-up feeds back client and obtains module 403, for being generated according to target follow-up method and the second attribute field
Second filter inquires target follow-up feedback client set according to second filter, and second attribute field is
The corresponding attribute field of target follow-up method；
Follow-up module 404 feeds back client for each target follow-up into target follow-up feedback client set
End publication target follow-up template, and receive the Follow-up results of the target follow-up feedback client feedback.
Follow-up results processing module 405, the Follow-up results processing module 405 is as shown in figure 12, comprising:
Text conversion unit 4051, for converting text for voice based on default speech recognition algorithm；
Keyword extracting unit 4052, for extracting the keyword in the text based on predetermined keyword library；
Number and grammatical term for the character extraction unit 4053, for extracting number and grammatical term for the character in the text；
Sequencing unit 4054, for keyword, number and grammatical term for the character to be ranked up according to its sequence in the text,
Obtain target string；
Generation unit 4055, the Follow-up results for obtaining indicating in the form of key-value pair according to target string.
The embodiment of the present invention also provides a kind of intelligent follow-up system, including Supervise client, Following-up Service device and with
Visit feedback client；
The Supervise client includes follow-up element definition module, the follow-up element definition module, for defining
The follow-up element is simultaneously transmitted to Following-up Service device by follow-up element, the follow-up element include follow-up method, follow-up template and
Follow-up trigger condition；
The Following-up Service device includes:
Target follow-up element obtains module, for obtaining corresponding with follow-up instruction target follow-up element, the target with
Visiting element includes target follow-up method, target follow-up template and target follow-up trigger condition；
Gather to follow-up patient and obtain module, for being generated according to the target follow-up trigger condition and the first attribute field
First filter is gathered according to first filter inquiry to follow-up patient, and first attribute field is target follow-up touching
The corresponding attribute field of clockwork spring part；
Target follow-up feeds back client and obtains module, for generating second according to target follow-up method and the second attribute field
Filter inquires target follow-up feedback client set according to second filter, and second attribute field is target
The corresponding attribute field of follow-up method；
Follow-up module, for each target follow-up feedback client hair into target follow-up feedback client set
Cloth target follow-up template, and receive the Follow-up results of the target follow-up feedback client feedback.
A kind of the device of the invention intelligent follow-up device as described in the examples and a kind of intelligent follow-up system with side
Method embodiment is based on similarly inventive concept.
The embodiments of the present invention also provide a kind of storage medium, the storage medium can be used for saving for realizing implementation
The program code for needing to use in example.Optionally, in the present embodiment, above-mentioned storage medium can be located at computer network
At least one network equipment in multiple network equipments.Optionally, in the present embodiment, above-mentioned storage medium may include but not
It is limited to: USB flash disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access
Memory), the various media that can store program code such as mobile hard disk, magnetic or disk.
Specifically, Figure 13 is a kind of server architecture schematic diagram provided in an embodiment of the present invention, and the server architecture can
For running a kind of intelligent follow-up method device.The server 800 can generate bigger difference because configuration or performance are different
It is different, it may include one or more central processing units (central processing units, CPU) 822 (for example, one
A or more than one processor) and memory 832, storage Jie of one or more storage application programs 842 or data 844
Matter 830 (such as one or more mass memory units).Wherein, memory 832 and storage medium 830 can be of short duration deposit
Storage or persistent storage.The program for being stored in storage medium 830 may include one or more modules (diagram is not shown), often
A module may include to the series of instructions operation in server.Further, central processing unit 822 can be set to
Storage medium 830 communicates, and the series of instructions operation in storage medium 830 is executed on server 800.Server 800 may be used also
To include one or more power supplys 826, one or more wired or wireless network interfaces 850, one or one with
Upper input/output interface 858, and/or, one or more operating systems 841, such as Windows ServerTM, Mac OS
XTM, UnixTM, LinuxTM, FreeBSDTM etc..What step performed by above method embodiment can be shown based on the Figure 13
Server architecture.
It should be understood that the sequencing of the embodiments of the present invention is for illustration only, the excellent of embodiment is not represented
It is bad.
Those of ordinary skill in the art will appreciate that realizing that all or part of the steps of above-described embodiment can pass through hardware
It completes, relevant hardware can also be instructed to complete by program, the program can store in a kind of computer-readable
In storage medium, storage medium mentioned above can be read-only memory, disk or CD etc..
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (13)
1. a kind of intelligent follow-up method characterized by comprising
Supervise client defines follow-up element and the follow-up element is transmitted to Following-up Service device, the follow-up element packet
Include follow-up method, follow-up template and follow-up trigger condition；
The Following-up Service device obtains target follow-up element corresponding with follow-up instruction, the target follow-up element include target with
Visit mode, target follow-up template and target follow-up trigger condition；
The Following-up Service device generates first filter according to the target follow-up trigger condition and the first attribute field, according to institute
It states first filter and inquires and gather to follow-up patient, first attribute field is the corresponding attribute of target follow-up trigger condition
Field；
The Following-up Service device generates the second filter according to target follow-up method and the second attribute field, according to second mistake
For filter described to inquire target follow-up feedback client set in follow-up patient set, second attribute field is target
The corresponding attribute field of follow-up method；
Each target follow-up feedback client publication of the Following-up Service device into target follow-up feedback client set
Target follow-up template, and receive the Follow-up results of the target follow-up feedback client feedback.
2. it is issued the method according to claim 1, wherein the follow-up is instructed by Supervise client, or
It is automatically generated by the Following-up Service device according to preset rules.
3. the method according to claim 1, wherein in the Following-up Service device with follow-up client be management pair
As, different Supervise client corresponds to different follow-up elements, a Supervise client correspond to it is one or more groups of with
Visit element.
4. the method according to claim 1, wherein having the category of incidence relation in Supervise client
The property adjacent display of field.
5. a kind of intelligent follow-up method characterized by comprising
Obtain corresponding with follow-up instruction target follow-up element, the target follow-up element include target follow-up method, target with
Visit template and target follow-up trigger condition；
First filter is generated according to the target follow-up trigger condition and the first attribute field, is looked into according to the first filter
It askes and gathers to follow-up patient, first attribute field is the corresponding attribute field of target follow-up trigger condition；
The second filter is generated according to target follow-up method and the second attribute field, target is inquired according to second filter
Client set is fed back in follow-up, and second attribute field is the corresponding attribute field of target follow-up method；
Each target follow-up feedback client into target follow-up feedback client set issues target follow-up template, and
Receive the Follow-up results of the target follow-up feedback client feedback.
6. according to the method described in claim 5, it is characterized in that, further including carrying out follow-up by self-defining data analysis model
Interpretation of result；
Using single patient as research object in the Data Analysis Model, using some attribute and time as data situational variables；
Or,
Using some Disease group as research object, using some attribute and time as data situational variables.
7. and automatic according to the method described in claim 5, it is characterized in that, further include acquiring the Follow-up results of speech form
Follow-up results are handled so that obtain being capable of processed structuring Follow-up results.
8. the method according to the description of claim 7 is characterized in that Follow-up results processing method includes:
Text is converted by voice based on default speech recognition algorithm；
The keyword in the text is extracted based on predetermined keyword library；
Extract the number and grammatical term for the character in the text；
Keyword, number and grammatical term for the character are ranked up according to its sequence in the text, obtain target string；
The Follow-up results indicated in the form of key-value pair are obtained according to target string.
9. a kind of intelligent follow-up device characterized by comprising
Target follow-up element obtains module, and for obtaining target follow-up element corresponding with follow-up instruction, the target follow-up is wanted
Element includes target follow-up method, target follow-up template and target follow-up trigger condition；
Gather to follow-up patient and obtain module, for generating first according to the target follow-up trigger condition and the first attribute field
Filter is gathered according to first filter inquiry to follow-up patient, and first attribute field is that target follow-up triggers item
The corresponding attribute field of part；
Target follow-up feeds back client and obtains module, for generating the second filtering according to target follow-up method and the second attribute field
Device inquires target follow-up feedback client set according to second filter, and second attribute field is target follow-up
The corresponding attribute field of mode；
Follow-up module issues mesh for each target follow-up feedback client into target follow-up feedback client set
Follow-up template is marked, and receives the Follow-up results of the target follow-up feedback client feedback.
10. device according to claim 9, which is characterized in that further include Follow-up results processing module, the Follow-up results
Processing module includes:
Text conversion unit, for converting text for voice based on default speech recognition algorithm；
Keyword extracting unit, for extracting the keyword in the text based on predetermined keyword library；
Number and grammatical term for the character extraction unit, for extracting number and grammatical term for the character in the text；
Sequencing unit obtains target for keyword, number and grammatical term for the character to be ranked up according to its sequence in the text
Character string；
Generation unit, the Follow-up results for obtaining indicating in the form of key-value pair according to target string.
11. a kind of intelligent follow-up system, which is characterized in that feed back visitor including Supervise client, Following-up Service device and follow-up
Family end；
The Supervise client includes follow-up element definition module, the follow-up element definition module, for defining follow-up
The follow-up element is simultaneously transmitted to Following-up Service device by element, and the follow-up element includes follow-up method, follow-up template and follow-up
Trigger condition；
The Following-up Service device includes:
Target follow-up element obtains module, and for obtaining target follow-up element corresponding with follow-up instruction, the target follow-up is wanted
Element includes target follow-up method, target follow-up template and target follow-up trigger condition；
Gather to follow-up patient and obtain module, for generating first according to the target follow-up trigger condition and the first attribute field
Filter inquires according to the first filter and gathers to follow-up patient, and first attribute field is target follow-up triggering
The corresponding attribute field of condition；
Target follow-up feeds back client and obtains module, for generating the second filtering according to target follow-up method and the second attribute field
Device inquires target follow-up feedback client set according to second filter, and second attribute field is target follow-up
The corresponding attribute field of mode；
Follow-up module issues mesh for each target follow-up feedback client into target follow-up feedback client set
Follow-up template is marked, and receives the Follow-up results of the target follow-up feedback client feedback.
12. a kind of computer readable storage medium, for storing program, which is characterized in that described program is wanted for realizing right
Seek a kind of intelligent follow-up method in 5.
13. a kind of server, which is characterized in that the server is for running a kind of intelligent follow-up dress as claimed in claim 9
It sets.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110400613A (en) * | 2019-06-10 | 2019-11-01 | 南京医基云医疗数据研究院有限公司 | A kind of follow-up patient screening method, apparatus, readable medium and electronic equipment |
| CN111785343A (en) * | 2020-07-17 | 2020-10-16 | 平安国际智慧城市科技股份有限公司 | Follow-up method and device, electronic equipment and storage medium |
| CN112365940A (en) * | 2020-10-16 | 2021-02-12 | 零氪科技（北京）有限公司 | System and method for screening subjects |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101206755A (en) * | 2007-08-07 | 2008-06-25 | 广东医卫互动信息科技有限公司 | Intelligent follow-up method for hospital |
| CN104184778A (en) * | 2013-05-27 | 2014-12-03 | 中山爱科数字科技股份有限公司 | Short message and telephone follow-up system for hospital |
| US20160034657A1 (en) * | 2014-07-31 | 2016-02-04 | Specialist On Call, Inc. | Remote medical evaluation |
| CN105989235A (en) * | 2015-02-17 | 2016-10-05 | 西部天使（北京）健康科技有限公司 | Network follow-up method and system |
| US20160294757A1 (en) * | 2015-03-31 | 2016-10-06 | Salesforce.Com, Inc. | Automatic generation of dynamically assigned conditional follow-up tasks |
| CN106453619A (en) * | 2016-11-17 | 2017-02-22 | 中国医学科学院生物医学工程研究所 | Intelligent cardiovascular disease follow-up system based on network |
| CN106682439A (en) * | 2016-12-30 | 2017-05-17 | 广州慧扬信息系统科技有限公司 | Investigational follow-up based medical record screening method |
| CN106886687A (en) * | 2017-04-21 | 2017-06-23 | 上海市肺科医院 | A kind of case history follow-up system |
| CN107315906A (en) * | 2017-06-01 | 2017-11-03 | 北京瑞启医药信息科技有限公司 | The method and system of the automatic follow-up of chronic are realized based on chat robots |
| CN107341251A (en) * | 2017-07-10 | 2017-11-10 | 江西博瑞彤芸科技有限公司 | A kind of extraction and the processing method of medical folk prescription and keyword |
| CN107564571A (en) * | 2017-08-30 | 2018-01-09 | 浙江宁格医疗科技有限公司 | A kind of structured electronic patient record generation method and its corresponding storage facilities and mobile terminal based on phonetic entry |
-
2018
- 2018-07-11 CN CN201810759154.7A patent/CN109243549B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101206755A (en) * | 2007-08-07 | 2008-06-25 | 广东医卫互动信息科技有限公司 | Intelligent follow-up method for hospital |
| CN104184778A (en) * | 2013-05-27 | 2014-12-03 | 中山爱科数字科技股份有限公司 | Short message and telephone follow-up system for hospital |
| US20160034657A1 (en) * | 2014-07-31 | 2016-02-04 | Specialist On Call, Inc. | Remote medical evaluation |
| CN105989235A (en) * | 2015-02-17 | 2016-10-05 | 西部天使（北京）健康科技有限公司 | Network follow-up method and system |
| US20160294757A1 (en) * | 2015-03-31 | 2016-10-06 | Salesforce.Com, Inc. | Automatic generation of dynamically assigned conditional follow-up tasks |
| CN106453619A (en) * | 2016-11-17 | 2017-02-22 | 中国医学科学院生物医学工程研究所 | Intelligent cardiovascular disease follow-up system based on network |
| CN106682439A (en) * | 2016-12-30 | 2017-05-17 | 广州慧扬信息系统科技有限公司 | Investigational follow-up based medical record screening method |
| CN106886687A (en) * | 2017-04-21 | 2017-06-23 | 上海市肺科医院 | A kind of case history follow-up system |
| CN107315906A (en) * | 2017-06-01 | 2017-11-03 | 北京瑞启医药信息科技有限公司 | The method and system of the automatic follow-up of chronic are realized based on chat robots |
| CN107341251A (en) * | 2017-07-10 | 2017-11-10 | 江西博瑞彤芸科技有限公司 | A kind of extraction and the processing method of medical folk prescription and keyword |
| CN107564571A (en) * | 2017-08-30 | 2018-01-09 | 浙江宁格医疗科技有限公司 | A kind of structured electronic patient record generation method and its corresponding storage facilities and mobile terminal based on phonetic entry |
Non-Patent Citations (3)
| Title |
|---|
| HARAN BURRI: "Remote follow-up and continuous remote monitoring, distinguished", 《EP EUROPACE》 * |
| 李姗姗: "远程院后患者随访平台的设计与实现", 《中国优秀博硕士学位论文全文数据库(硕士) 信息科技辑(月刊)》 * |
| 王坤亮等: "患者复查随访提示程序设计及实现", 《医疗卫生装备》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110400613A (en) * | 2019-06-10 | 2019-11-01 | 南京医基云医疗数据研究院有限公司 | A kind of follow-up patient screening method, apparatus, readable medium and electronic equipment |
| CN111785343A (en) * | 2020-07-17 | 2020-10-16 | 平安国际智慧城市科技股份有限公司 | Follow-up method and device, electronic equipment and storage medium |
| CN112365940A (en) * | 2020-10-16 | 2021-02-12 | 零氪科技（北京）有限公司 | System and method for screening subjects |
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