CN109243549B - Intelligent follow-up method and device and server - Google Patents
Intelligent follow-up method and device and server Download PDFInfo
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Abstract
The invention provides an intelligent follow-up method, an intelligent follow-up device and a server, wherein the method comprises the steps of obtaining a target follow-up mode, a target follow-up template and a target follow-up trigger condition; generating a first filter according to the target follow-up trigger condition and a first attribute field, and inquiring a set of patients to be followed up according to the first filter; generating a second filter according to the target follow-up mode and a second attribute field, and inquiring a target follow-up feedback client set according to the second filter; and issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set, and receiving a follow-up visit result fed back by the target follow-up visit feedback client. According to the follow-up visit system and the follow-up visit method, the follow-up visit key elements are customized, the follow-up visit template is automatically distributed based on the follow-up visit key elements, and the follow-up visit results are automatically collected, so that the whole process automation of the follow-up visit process is realized, the follow-up visit efficiency is improved, and the burden of doctors and patients is reduced.
Description
Technical Field
The invention relates to the field of computers, in particular to an intelligent follow-up method, an intelligent follow-up device and a server.
Background
Most of the existing hospital follow-up systems provide notification services for patients in a telephone and short message mode, basically have no function of collecting data, and the notification services basically mainly take questionnaire survey, so that problems and data needing to be collected cannot be effectively associated, and the real follow-up value cannot be reflected.
In addition, the follow-up visit is mainly performed by a paper questionnaire or character interaction, so that the user experience is poor, and the follow-up visit result is difficult to be digitalized and structured, so that the relevant data analysis based on the follow-up visit result is difficult.
Disclosure of Invention
In order to solve the technical problem, the invention provides an intelligent follow-up method, an intelligent follow-up device and a server. The invention is realized by the following technical scheme:
in a first aspect, a method of intelligent follow-up, comprising:
the follow-up visit management client defines follow-up visit elements and transmits the follow-up visit elements to a follow-up visit server, wherein the follow-up visit elements comprise a follow-up visit mode, a follow-up visit template and follow-up visit triggering conditions;
the follow-up server acquires a target follow-up element corresponding to a follow-up instruction, wherein the target follow-up element comprises a target follow-up mode, a target follow-up template and a target follow-up trigger condition;
the follow-up server generates a first filter according to the target follow-up triggering condition and a first attribute field, and queries a set of patients to be followed up according to the first filter, wherein the first attribute field is an attribute field corresponding to the target follow-up triggering condition;
the follow-up server generates a second filter according to a target follow-up mode and a second attribute field, a target follow-up feedback client set is inquired in the set of patients to be followed up according to the second filter, and the second attribute field is an attribute field corresponding to the target follow-up mode;
and the follow-up server issues a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receives a follow-up visit result fed back by the target follow-up visit feedback client. .
In a second aspect, a method of intelligent follow-up, comprising:
acquiring a target follow-up element corresponding to a follow-up instruction, wherein the target follow-up element comprises a target follow-up mode, a target follow-up template and a target follow-up trigger condition;
generating a first filter according to the target follow-up triggering condition and a first attribute field, and inquiring a set of patients to be followed up according to the first filter, wherein the first attribute field is an attribute field corresponding to the target follow-up triggering condition;
generating a second filter according to the target follow-up mode and a second attribute field, and inquiring a target follow-up feedback client set according to the second filter, wherein the second attribute field is an attribute field corresponding to the target follow-up mode;
and issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set, and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
In a third aspect, an intelligent follow-up device, comprising:
the system comprises a target follow-up visit element acquisition module, a target follow-up visit element acquisition module and a target follow-up visit element processing module, wherein the target follow-up visit element acquisition module is used for acquiring a target follow-up visit element corresponding to a follow-up visit instruction, and the target follow-up visit element comprises a target follow-up visit mode, a target follow-up visit template and a target follow-up visit trigger condition;
a to-be-followed patient set acquisition module, configured to generate a first filter according to the target follow-up trigger condition and a first attribute field, and query a to-be-followed patient set according to the first filter, where the first attribute field is an attribute field corresponding to the target follow-up trigger condition;
the target follow-up visit feedback client acquisition module is used for generating a second filter according to a target follow-up visit mode and a second attribute field, and inquiring a target follow-up visit feedback client set according to the second filter, wherein the second attribute field is an attribute field corresponding to the target follow-up visit mode;
and the follow-up module is used for issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
In a fourth aspect, an intelligent follow-up visit system comprises a follow-up visit management client, a follow-up visit server and a follow-up visit feedback client;
the follow-up visit management client comprises a follow-up visit element definition module, wherein the follow-up visit element definition module is used for defining a follow-up visit element and transmitting the follow-up visit element to a follow-up visit server, and the follow-up visit element comprises a follow-up visit mode, a follow-up visit template and a follow-up visit triggering condition;
the follow-up server includes:
the system comprises a target follow-up visit element acquisition module, a target follow-up visit element acquisition module and a target follow-up visit element processing module, wherein the target follow-up visit element acquisition module is used for acquiring a target follow-up visit element corresponding to a follow-up visit instruction, and the target follow-up visit element comprises a target follow-up visit mode, a target follow-up visit template and a target follow-up visit trigger condition;
a to-be-followed patient set acquisition module, configured to generate a first filter according to the target follow-up trigger condition and a first attribute field, and query a to-be-followed patient set according to the first filter, where the first attribute field is an attribute field corresponding to the target follow-up trigger condition;
the target follow-up visit feedback client acquisition module is used for generating a second filter according to a target follow-up visit mode and a second attribute field, and inquiring a target follow-up visit feedback client set according to the second filter, wherein the second attribute field is an attribute field corresponding to the target follow-up visit mode;
and the follow-up module is used for issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
In a fifth aspect, a computer-readable storage medium stores a program for implementing an intelligent follow-up method as described above.
In a sixth aspect, a server is used for operating an intelligent follow-up device as described above.
The invention provides an intelligent follow-up method, an intelligent follow-up device and a server, which have the following beneficial effects:
(1) by customizing the follow-up factors, automatically distributing the follow-up templates based on the follow-up factors and automatically collecting follow-up results, the whole-process automation of the follow-up process is realized, so that the follow-up efficiency is improved, and the burden of doctors and patients is reduced.
(2) Voice follow-up is supported, so that the experience of a patient is improved; supports the analysis of follow-up results and provides guidance for doctors and patients.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic diagram of an implementation environment of an intelligent follow-up method according to an embodiment of the present invention;
FIG. 2 is a flow chart of an intelligent follow-up method provided by an embodiment of the invention;
FIG. 3 is a flow chart of an auditing method provided by an embodiment of the present invention;
fig. 4 is a schematic diagram of a follow-up management client according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of a follow-up template provided by an embodiment of the present invention;
FIG. 6 is a diagram illustrating details of a patient data set provided by an embodiment of the present invention;
FIG. 7 is a graph derived from the patient data provided by an embodiment of the present invention;
fig. 8 is a graph illustrating a variation trend of the survival rate over a certain period of time according to an embodiment of the present invention;
fig. 9 is a flowchart of a follow-up result processing method according to an embodiment of the present invention;
FIG. 10(1) is a schematic diagram of strict extraction results provided in the embodiment of the present invention;
fig. 10(2) is a schematic diagram of a fuzzy extraction result according to an embodiment of the present invention;
FIG. 11 is a block diagram of an intelligent follow-up device according to an embodiment of the present invention;
FIG. 12 is a block diagram of a follow-up result processing module according to an embodiment of the present invention;
fig. 13 is a block diagram of a server according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Referring to fig. 1, an embodiment of the present invention provides an implementation environment schematic diagram of an intelligent follow-up method. The implementation environment includes: a follow-up management client 101, a follow-up server 102 and a follow-up feedback client 103.
The follow-up visit management client 101 is in communication with the follow-up visit server 102, and the follow-up visit management client 101 is used for setting a follow-up visit mode, a follow-up visit template and a follow-up visit triggering condition and transmitting a setting result to the follow-up visit server, and the follow-up visit server performs follow-up visit on the follow-up visit feedback client 103 according to the setting result.
The follow-up feedback client 103 is in communication with the follow-up server 102, and the follow-up feedback client 103 receives a follow-up template issued by the follow-up server 102 and feeds back a follow-up result to the follow-up server 102, so that the follow-up server 102 receives and manages the follow-up result and displays the follow-up result on the follow-up management client 101.
In summary, in the embodiment of the present invention, the follow-up server 102 is used as a bridge to implement information intercommunication between the follow-up client 101 and the follow-up feedback client 103.
The number of the follow-up clients 101 may be one or more, the number of the follow-up feedback clients 103 may be one or more, and the follow-up server 102 may be a stand-alone computer device or a distributed computer system.
The follow-up client 101 and the follow-up server 102 can communicate with each other through a wireless network or a wired network, and the follow-up server 102 and the follow-up feedback client 103 can communicate with each other through an operator network, a wireless network or a wired network.
An embodiment of the present invention provides an intelligent follow-up method, where an intelligent follow-up system composed of a follow-up management client 101, a follow-up server 102, and a follow-up feedback client 103 is used as an execution subject, and as shown in fig. 2, the intelligent follow-up method includes:
s101, a follow-up visit management client defines follow-up visit elements and transmits the follow-up visit elements to a follow-up visit server, wherein the follow-up visit elements comprise a follow-up visit mode, a follow-up visit template and follow-up visit triggering conditions.
Specifically, the follow-up server may use a follow-up client as a management object, and different follow-up management clients correspond to different follow-up elements. One follow-up visit management client corresponds to one or more groups of follow-up visit elements, and each group of follow-up visit elements comprise contents of a follow-up visit mode, a follow-up visit template and a follow-up visit triggering condition.
In order to facilitate the follow-up management client to set a follow-up template, in the embodiment of the present invention, a template library may be maintained in the follow-up server, and the template library stores common templates. The template library in the follow-up server stores templates corresponding to common diseases. If a doctor needs to set a follow-up template for a patient with a certain disease, the doctor can directly inquire whether the template corresponding to the disease already exists in the template library, and if so, the doctor can directly use the template, and certainly, the doctor can also use the template after modifying the template. If the template corresponding to the disease does not exist in the template library, the follow-up template needs to be established again.
The follow-up mode can be WeChat, short message and telephone; the follow-up trigger condition may be a data-based trigger, a state-and-time-based joint trigger.
Taking a medical system as an example, if two follow-up management clients customize follow-up factors to a follow-up server, the specific customized content is as follows:
follow-up management client identification: 001;
doctor name Zhang III;
the doctor positions: a cardiologist attending physician;
follow-up element 1: the follow-up mode comprises the following steps: WeChat follow-up; follow-up template: a hypertension follow-up template; follow-up trigger conditions: triggering based on the data;
follow-up element 2: the follow-up mode comprises the following steps: a telephone follow-up; follow-up template: cerebral thrombosis follow-up template; follow-up trigger conditions: jointly triggering based on state and time.
Follow-up client identification: 002;
doctor name: "Lisi";
the doctor positions: the respiratory medical chief and ren doctor;
follow-up element 3: the follow-up mode comprises the following steps: WeChat follow-up; follow-up template: bronchopneumonia follow-up template; follow-up trigger conditions: jointly triggering based on state and time.
The hypertension follow-up template can use the existing template in a template library, and the cerebral thrombosis follow-up template and the bronchopneumonia follow-up template need a doctor to customize. The data-based trigger may be to trigger a follow-up visit when certain data satisfies a trigger condition, for example, if the high pressure at the time of patient visit is greater than 150. The combined state and time based trigger may be a preset time post-discharge trigger visit for the patient if the patient is an in-patient.
In the customized content, the follow-up server stores two follow-up management client identifiers and correspondingly stores basic information of the follow-up management client and relevant follow-up elements. The follow-up visit management client side basic information comprises identification, doctor name and doctor position.
S102, responding to a follow-up instruction, the follow-up server obtains a target follow-up element corresponding to the follow-up instruction, and the target follow-up element comprises a target follow-up mode, a target follow-up template and a target follow-up trigger condition.
Specifically, the follow-up instruction may be sent by a follow-up management client, or may be automatically generated by the follow-up server according to a preset rule.
S103, the follow-up server generates a first filter according to the target follow-up trigger condition and a first attribute field, a set of patients to be followed up is inquired in the follow-up server according to the first filter, and the first attribute field is an attribute field corresponding to the target follow-up trigger condition.
And S104, the follow-up server generates a second filter according to a target follow-up mode and a second attribute field, and queries a target follow-up feedback client set in the set of patients to be followed up according to the second filter, wherein the second attribute field is an attribute field corresponding to the target follow-up mode.
Specifically, the follow-up management client can enter patient information into the follow-up server at any time, the follow-up server performs unified recording and management on the patient information, and specific attribute fields included in the patient information can be customized according to actual needs.
For example, the patient information includes the following fields:
patient name, patient micro-signal, patient phone number, patient condition diagnosis, patient condition data, whether the patient is hospitalized, the time the patient is hospitalized, and the time the patient is discharged. One record corresponding to the patient information is: "july", "wx 2465255", "hypertension", "high pressure 160, low pressure 90", "no", "null".
If the follow-up visit command carries a follow-up visit element 1, the first attribute field is patient condition data, the second attribute field is patient micro-signals, the content of the first filter can be that the high pressure in the patient condition data is more than 150, and the second filter aims to inquire out micro-signals of a target follow-up visit feedback client, so that the purposes of issuing a follow-up visit template and collecting follow-up visit results in a micro-signal follow-up visit mode are finally achieved.
And S105, issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set, and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
In a possible embodiment, in order to ensure the accuracy of the follow-up result, the follow-up result may also be reviewed, and in order to enable the review, the follow-up instruction should include a target follow-up management client, where the target follow-up management client is used to review the follow-up result, and the patient information should include follow-up progress, where the review method is shown in fig. 3 and includes:
s201, the follow-up server feeds back follow-up results of the patient to the target follow-up management client.
S202, obtaining an auditing result of the target follow-up visit management client for a follow-up visit result.
S203, if the examination is passed, the follow-up result is recorded into a follow-up server, and the follow-up progress of the patient is updated.
And S204, if the audit is not passed, the follow-up visit template is released to the target follow-up visit feedback client again until the audit is passed.
In a preferred embodiment, the follow-up server supports the follow-up management client to customize the display field, that is, the follow-up server takes the follow-up management client as a management object, and different follow-up management clients can display different field contents. The follow-up server can also record the follow-up progress of each patient and display the information of the patients in a classified manner according to the follow-up progress. Referring to fig. 4, a schematic diagram of a follow-up management client is shown. The data value collected by the latest follow-up visit can be supported when the page is displayed.
In a preferred embodiment, the follow-up server supports the follow-up management client to customize the association relationship between the data fields, and supports the screening function. If the first field and the second field are associated in an affiliation manner, when the follow-up visit management client displays, the second field is automatically associated behind the first field, so that the content of the first field and the content of the second field are displayed adjacently.
In a preferred embodiment, the follow-up visit management client can customize the follow-up visit template, the customized content comprises questions asked for the user and the sequence of the questions, and if the questions are choice questions, the options can be customized. In a preferred embodiment, the follow-up server may transmit the contents of the follow-up template to the follow-up feedback client in a man-machine conversation manner using a man-machine conversation robot. As shown in fig. 5, the human-machine dialog robot asks the patient for the start time, gets the patient reply content, and automatically associates to certain fields in the patient information.
The follow-up server records follow-up results of each time and supports a user-defined data analysis model.
The data analysis model can take a single patient as a research object, and take a certain attribute and time as data analysis variables, for example, the change curve analysis of a certain index is carried out according to the follow-up years/times. Please refer to fig. 6, which shows details of a patient data, and fig. 7, which shows a graph obtained from the patient data.
The data analysis model may also use a disease patient population as a research object, and a certain index and time as data analysis variables, such as a time-varying trend graph of a certain index, which is a comprehensive index of the disease patient population and may be represented by statistical indexes such as a mean weighted average.
For example, the index of survival rate, recovery rate, death rate, etc. of the disease patient population can be counted and displayed. Please refer to fig. 8, which shows the variation trend of the survival rate in a certain period of time.
When displaying, the follow-up server supports displaying each attribute through various graphs, such as a bar chart, a broken line chart and a pie chart, and also supports displaying according to various time nodes, such as displaying according to months, seasons and years.
In a next preferred embodiment, the follow-up server may automatically analyze the follow-up result, match the follow-up result with a statistical result related to the follow-up content, and recommend a treatment plan to the doctor according to the matching result.
In a preferred embodiment, the follow-up server supports the acquisition of follow-up results in the form of speech and is able to automatically recognize and extract the follow-up results to obtain structured follow-up results that can be processed. In order to achieve the above object, an embodiment of the present invention discloses a method for processing a follow-up result, as shown in fig. 9, including:
s301, converting the voice into a text based on a preset voice recognition algorithm.
The preset voice recognition algorithm comprises a training voice recognition model, and voice is recognized according to the voice recognition model, and the training method of the voice recognition model comprises the following steps:
and P1, determining a training voice signal.
And P2, determining a sound source label corresponding to the training voice signal.
The sound source label is used as a reference target for extracting the tone features of the training speech signal by the speech recognition model, wherein the speech recognition model can extract the tone features of the training speech signal.
And P3, determining semantic labels corresponding to the training voice signals.
The semantic tag is used as a reference target of the speech recognition model for extracting the semantic features of the training speech signal, wherein the speech recognition model can also extract the semantic features of the training speech signal.
And P4, training the voice recognition model according to the training voice signal, the sound source label and the semantic label.
The training samples include training speech signals, sound source labels corresponding to the training speech signals, and semantic labels corresponding to the training speech signals. The training target is to train the target parameter in the speech recognition model for multiple times through multiple training samples, and adjust the parameter value of the target parameter to minimize the error between the semantic meaning obtained by the speech recognition model for the training speech signal recognition and the semantic meaning represented by the semantic label corresponding to the training speech signal.
Preferably, when the speech recognition model is trained according to the training speech signal, the sound source label and the semantic label, the training speech signal may be framed according to a time dimension to obtain a multi-frame speech signal. The training voice signals are preprocessed through framing operation, the training voice signals can be divided into smaller units, the training process can be converged more quickly, and the shorter voice signals can be recognized more accurately by the voice recognition model when the target voice signals are recognized.
S302, extracting keywords in the text based on a preset keyword library.
Specifically, the keywords correspond to fields supported in the random server. For example, for a hypertensive patient, data such as high pressure and low pressure should be stored, and whether dizziness and numbness of limbs occur or not is recorded; for a patient with heart disease, data such as heart rate and pulse should be stored, so that high pressure, low pressure, heart rate, pulse, dizziness and numbness of limbs are all keywords and are recorded in a keyword library.
Specifically, the extracted keywords can be strictly extracted or extracted in a fuzzy manner, and when the keywords are strictly extracted, the keywords can be extracted only if the keywords are completely consistent; in the fuzzy extraction, the keyword can be extracted as long as the keyword has the same meaning. Fig. 10(1) shows the strict extraction result, and fig. 10(2) shows the fuzzy extraction result.
And S303, extracting the numbers in the text and judging words.
The decision words include, but are not limited to: yes, no, etc.
S304, the keywords, the numbers and the judgment words are sequenced according to the sequence of the keywords, the numbers and the judgment words in the text, and a target character string is obtained.
Taking the follow-up visit for a certain hypertensive patient as an example, the target character string is: the high pressure 160, low pressure 90, heart rate 85, no dizziness and no limb numbness.
S305, obtaining follow-up results expressed in a key value pair mode according to the target character strings.
The follow-up result identified by the key value pair is a structured data which can be directly entered into a random server or displayed on a follow-up management client.
Further, if the follow-up server processes the follow-up result and cannot obtain a legal follow-up result, if no effective numerical value is analyzed, a preset fixed telephone operation, such as "please provide data again", can be fed back to collect the follow-up result again. In addition, the follow-up server can comprehensively analyze the follow-up results obtained from the previous times and the follow-up results obtained at this time, and can automatically give out the pre-diagnosis information. For example, the data value analyzed by the follow-up semantics at this time is higher than the last follow-up value, and the machine can automatically reply to the patient that 'please continue to take XX medicine', so that better experience of the patient can be ensured, the burden on the doctor side is reduced, and the best follow-up effect is achieved.
According to the embodiment of the invention, the follow-up server is taken as a bridge, automatic distribution of follow-up templates and automatic acquisition and processing of follow-up results are realized, and voice input is supported, so that the experience degree of a user perception layer is improved, the follow-up work of doctors is more efficient, the simultaneous comparison and analysis of historical data of the same disease and the same data of the same person are supported, the treatment scheme guidance is given according to the analysis result, the value of big data is fully exerted, the whole follow-up process can be automatically executed, the connection between doctors and patients is more natural and smooth, and the follow-up value is higher.
An embodiment of the present invention provides an intelligent follow-up device, as shown in fig. 11, including:
a target follow-up visit element obtaining module 401, configured to obtain a target follow-up visit element corresponding to a follow-up visit instruction, where the target follow-up visit element includes a target follow-up visit mode, a target follow-up visit template, and a target follow-up visit trigger condition;
a to-be-followed patient set acquisition module 402, configured to generate a first filter according to the target follow-up trigger condition and a first attribute field, and query a to-be-followed patient set according to the first filter, where the first attribute field is an attribute field corresponding to the target follow-up trigger condition;
a target follow-up visit feedback client acquisition module 403, configured to generate a second filter according to a target follow-up visit mode and a second attribute field, and query a target follow-up visit feedback client set according to the second filter, where the second attribute field is an attribute field corresponding to the target follow-up visit mode;
a follow-up module 404, configured to issue a target follow-up template to each target follow-up feedback client in the target follow-up feedback client set, and receive a follow-up result fed back by the target follow-up feedback client.
A follow-up result processing module 405, where the follow-up result processing module 405, as shown in fig. 12, includes:
the text conversion unit 4051 is configured to convert the speech into a text based on a preset speech recognition algorithm;
a keyword extraction unit 4052, configured to extract keywords in the text based on a preset keyword library;
a numeral and judgment word extracting unit 4053, configured to extract numerals and judgment words in the text;
the sorting unit 4054 is configured to sort the keywords, the numbers, and the determination words according to the order of the keywords, the numbers, and the determination words in the text, so as to obtain a target character string;
the generating unit 4055 is configured to obtain a follow-up result expressed in the form of a key-value pair according to the target character string.
The embodiment of the invention also provides an intelligent follow-up visit system, which comprises a follow-up visit management client, a follow-up visit server and a follow-up visit feedback client;
the follow-up visit management client comprises a follow-up visit element definition module, wherein the follow-up visit element definition module is used for defining a follow-up visit element and transmitting the follow-up visit element to a follow-up visit server, and the follow-up visit element comprises a follow-up visit mode, a follow-up visit template and a follow-up visit triggering condition;
the follow-up server includes:
the system comprises a target follow-up visit element acquisition module, a target follow-up visit element acquisition module and a target follow-up visit element processing module, wherein the target follow-up visit element acquisition module is used for acquiring a target follow-up visit element corresponding to a follow-up visit instruction, and the target follow-up visit element comprises a target follow-up visit mode, a target follow-up visit template and a target follow-up visit trigger condition;
a to-be-followed patient set acquisition module, configured to generate a first filter according to the target follow-up trigger condition and a first attribute field, and query a to-be-followed patient set according to the first filter, where the first attribute field is an attribute field corresponding to the target follow-up trigger condition;
the target follow-up visit feedback client acquisition module is used for generating a second filter according to a target follow-up visit mode and a second attribute field, and inquiring a target follow-up visit feedback client set according to the second filter, wherein the second attribute field is an attribute field corresponding to the target follow-up visit mode;
and the follow-up module is used for issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
The intelligent follow-up device and the intelligent follow-up system in the device embodiment of the invention are based on the same inventive concept as the method embodiment.
Embodiments of the present invention also provide a storage medium, which can be used to store program codes used in implementing the embodiments. Optionally, in this embodiment, the storage medium may be located in at least one network device of a plurality of network devices of a computer network. Optionally, in this embodiment, the storage medium may include but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Specifically, fig. 13 is a schematic diagram of a server structure provided in an embodiment of the present invention, where the server structure may be used to operate an intelligent follow-up method apparatus. The server 800, which may vary significantly depending on configuration or performance, may include one or more Central Processing Units (CPUs) 822 (e.g., one or more processors) and memory 832, one or more storage media 830 (e.g., one or more mass storage devices) storing applications 842 or data 844. Memory 832 and storage medium 830 may be, among other things, transient or persistent storage. The program stored in the storage medium 830 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Still further, a central processor 822 may be provided in communication with the storage medium 830 for executing a series of instruction operations in the storage medium 830 on the server 800. The server 800 may also include one or more power supplies 826, one or more wired or wireless network interfaces 850, one or more input-output interfaces 858, and/or one or more operating systems 841, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc. The steps performed by the above-described method embodiment may be based on the server structure shown in fig. 13.
It should be noted that: the sequence of the above embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (13)
1. An intelligent follow-up method, comprising:
the follow-up visit management client defines follow-up visit elements and transmits the follow-up visit elements to a follow-up visit server, wherein the follow-up visit elements comprise a follow-up visit mode, a follow-up visit template and follow-up visit triggering conditions;
the follow-up server acquires a target follow-up element corresponding to a follow-up instruction, wherein the target follow-up element comprises a target follow-up mode, a target follow-up template and a target follow-up trigger condition; the target follow-up trigger condition is based on data trigger or combined trigger based on state and time;
the follow-up server determines a first attribute field corresponding to the target follow-up triggering condition according to the target follow-up triggering condition; generating a first filter according to the target follow-up trigger condition and the first attribute field, and inquiring a set of patients to be followed up according to the first filter;
the follow-up server determines a second attribute field corresponding to the target follow-up mode according to the target follow-up mode; generating a second filter according to the target follow-up mode and the second attribute field, and inquiring a target follow-up feedback client side set in the set of patients to be followed up according to the second filter;
and the follow-up server issues a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receives a follow-up visit result fed back by the target follow-up visit feedback client.
2. The method according to claim 1, wherein the follow-up instruction is issued by a follow-up management client or automatically generated by the follow-up server according to a preset rule.
3. The method of claim 1, wherein the follow-up server takes the follow-up client as a management object, different follow-up management clients correspond to different follow-up elements, and one follow-up management client corresponds to one or more groups of follow-up elements.
4. The method of claim 1, wherein the attribute fields with association are displayed adjacent to each other in the follow-up management client.
5. An intelligent follow-up method, comprising:
acquiring a target follow-up element corresponding to a follow-up instruction, wherein the target follow-up element comprises a target follow-up mode, a target follow-up template and a target follow-up trigger condition; the target follow-up visit triggering condition is based on data triggering or based on state and time combined triggering;
determining a first attribute field corresponding to the target follow-up trigger condition according to the target follow-up trigger condition; generating a first filter according to the target follow-up trigger condition and the first attribute field, and querying a set of patients to be followed up according to the first filter;
determining a second attribute field corresponding to the target follow-up mode according to the target follow-up mode; generating a second filter according to the target follow-up mode and the second attribute field, and inquiring a target follow-up feedback client set according to the second filter;
and issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set, and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
6. The method of claim 5, further comprising performing follow-up results analysis via a custom data analysis model;
in the data analysis model, a single patient is taken as a research object, and certain attribute and time are taken as data analysis variables; or the like, or, alternatively,
a certain disease patient population is taken as a research object, and a certain attribute and time are taken as data analysis variables.
7. The method of claim 5, further comprising collecting follow-up results in the form of speech and automatically processing the follow-up results to obtain structured follow-up results that can be processed.
8. The method of claim 7, wherein the follow-up result processing method comprises:
converting the voice into a text based on a preset voice recognition algorithm;
extracting keywords in the text based on a preset keyword library;
extracting numbers and judging words in the text;
sequencing the keywords, the numbers and the judgment words according to the sequence of the keywords, the numbers and the judgment words in the text to obtain a target character string;
and obtaining follow-up results expressed in the form of key value pairs according to the target character strings.
9. An intelligent follow-up device, comprising:
the system comprises a target follow-up visit element acquisition module, a target follow-up visit element acquisition module and a target follow-up visit element processing module, wherein the target follow-up visit element acquisition module is used for acquiring a target follow-up visit element corresponding to a follow-up visit instruction, and the target follow-up visit element comprises a target follow-up visit mode, a target follow-up visit template and a target follow-up visit trigger condition; the target follow-up trigger condition is based on data trigger or combined trigger based on state and time;
a to-be-followed patient set acquisition module, configured to determine, according to the target follow-up triggering condition, a first attribute field corresponding to the target follow-up triggering condition; generating a first filter according to the target follow-up trigger condition and the first attribute field, and querying a set of patients to be followed up according to the first filter;
the target follow-up visit feedback client acquisition module is used for determining a second attribute field corresponding to the target follow-up visit mode according to the target follow-up visit mode; generating a second filter according to the target follow-up mode and the second attribute field, and inquiring a target follow-up feedback client set according to the second filter;
and the follow-up module is used for issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
10. The apparatus of claim 9, further comprising a follow-up result processing module, the follow-up result processing module comprising:
the text conversion unit is used for converting the voice into a text based on a preset voice recognition algorithm;
a keyword extraction unit, configured to extract keywords in the text based on a preset keyword library;
the digital and judgment word extracting unit is used for extracting the numbers and the judgment words in the text;
the sequencing unit is used for sequencing the keywords, the numbers and the judgment words according to the sequence of the keywords, the numbers and the judgment words in the text to obtain a target character string;
and the generating unit is used for obtaining follow-up results expressed in the form of key value pairs according to the target character strings.
11. An intelligent follow-up system is characterized by comprising a follow-up management client, a follow-up server and a follow-up feedback client;
the follow-up visit management client comprises a follow-up visit element definition module, wherein the follow-up visit element definition module is used for defining a follow-up visit element and transmitting the follow-up visit element to a follow-up visit server, and the follow-up visit element comprises a follow-up visit mode, a follow-up visit template and a follow-up visit triggering condition;
the follow-up server includes:
the system comprises a target follow-up visit element acquisition module, a target follow-up visit element acquisition module and a target follow-up visit element processing module, wherein the target follow-up visit element acquisition module is used for acquiring a target follow-up visit element corresponding to a follow-up visit instruction, and the target follow-up visit element comprises a target follow-up visit mode, a target follow-up visit template and a target follow-up visit trigger condition; the target follow-up trigger condition is based on data trigger or combined trigger based on state and time;
a to-be-followed patient set acquisition module, configured to determine, according to the target follow-up triggering condition, a first attribute field corresponding to the target follow-up triggering condition; generating a first filter according to the target follow-up trigger condition and the first attribute field, and querying a set of patients to be followed up according to the first filter;
the target follow-up visit feedback client acquisition module is used for determining a second attribute field corresponding to the target follow-up visit mode according to the target follow-up visit mode; generating a second filter according to the target follow-up mode and the second attribute field, and inquiring a target follow-up feedback client set according to the second filter;
and the follow-up module is used for issuing a target follow-up visit template to each target follow-up visit feedback client in the target follow-up visit feedback client set and receiving a follow-up visit result fed back by the target follow-up visit feedback client.
12. A computer-readable storage medium storing a program for implementing an intelligent follow-up method according to any one of claims 5 to 8.
13. A server, characterized in that the server is adapted to run an intelligent follow-up device according to claim 9 or 10.
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| 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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