CN114388115A - Customer online reservation intelligent management system based on interactivity - Google Patents

Customer online reservation intelligent management system based on interactivity Download PDF

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CN114388115A
CN114388115A CN202210041060.2A CN202210041060A CN114388115A CN 114388115 A CN114388115 A CN 114388115A CN 202210041060 A CN202210041060 A CN 202210041060A CN 114388115 A CN114388115 A CN 114388115A
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谭兴胜
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Yiwu Junyu Network Technology Co ltd
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    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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Abstract

The invention discloses an interactive-based intelligent client online appointment management system, which comprises an appointment consultation content publishing module, a patient condition database, an appointment inquiry case forming module, an appointment client type judging module, an old client type appointment management terminal and a new client type appointment management terminal, by taking the consultation interaction record of the consulting doctor in the consultation process as a starting point, evaluating the corresponding consultation interaction satisfaction coefficient of the consulting doctor, the method is used as a reference for the actual medical service quality corresponding to the consulting doctor, the defect that the platform automatic recommending consulting doctor cannot reflect the service quality of the consulting process of the consulting doctor is effectively overcome, the automatic recommending mode of the reservation platform is improved, the recommending value of the consulting doctor is improved, the medical consulting requirement of the reservation client for seeing a doctor is greatly met, and the consulting experience of the reservation client is favorably enhanced.

Description

Customer online reservation intelligent management system based on interactivity
Technical Field
The invention belongs to the technical field of client online reservation management, and particularly relates to an interactive-based client online reservation intelligent management system.
Background
With the development of social economy, people pay more and more attention to their own health, so that the medical needs are continuously increased, and the traditional offline medical inquiry mode often causes the phenomenon of 'difficult medical treatment' due to the unbalanced distribution of medical resources. In order to meet the ever-rising medical needs of people and relieve the phenomenon of 'difficult medical treatment', the traditional offline medical service mode is gradually changed, and online medical treatment and inquiry are born. The on-line medical inquiry breaks through the boundary line of the space by carrying out medical inquiry on line, and can greatly reduce the medical expense of people on the premise of solving the problem of the health of people, thereby gaining the favor and support of the people and gradually becoming an important way for the people to seek medical inquiry.
Along with more and more clients seeking medical advice on line, in order to avoid inconvenience in medical advice consultation caused by the fact that the same doctor is pricked and piled up in the same time period, many on-line medical advice platforms open an on-line appointment function. The client can issue the disease condition content, the appointment time and the appointment doctor to make an appointment inquiry through the online appointment inquiry platform, the appointment doctor can be actively appointed by the client or recommended by the platform, for the appointment client who does not actively appoint the appointment doctor in the appointment inquiry, the appointment of the appointment doctor is automatically recommended through the platform, and the platform automatic recommendation method generally comprises the steps of firstly determining the disease condition type according to the disease condition content issued in the disease condition consultation appointment corresponding to the current appointment client, then obtaining the number of appointment persons corresponding to each consulting doctor in the appointment time under the disease condition type, and further recommending according to the number of the appointment persons. The recommendation mode is too single, only can reflect the medical treatment heat of a consulting doctor, the service quality of the inquiry and consultation process of the consulting doctor cannot be reflected, and the most important appointment client is the service quality of the inquiry and consultation process of the consulting doctor, so that the value of the automatic recommendation mode of the platform is low, and the medical treatment and inquiry requirements of the appointed client are difficult to meet.
Disclosure of Invention
In view of the above defects of the prior art, the present application aims to provide an interactive-based intelligent client online appointment management system, which effectively solves the problem that the platform automatically recommends that a consulting doctor cannot reflect the quality of service in the consulting process of the consulting doctor by taking the consulting interaction record of the consulting doctor in the consulting process as a starting point to evaluate the consulting interaction satisfaction coefficient corresponding to the consulting doctor as the reference for the quality of actual medical service for the consulting doctor.
The invention is realized by the following technical scheme:
an intelligent client online appointment management system based on interactivity comprises an appointment consultation content publishing module, a disease database, an appointment inquiry case forming module, an appointment client type judging module, an old client type appointment management terminal and a new client type appointment management terminal;
the appointment consultation content publishing module is used for registering by a client on the online appointment inquiry platform and publishing the disease condition content and appointment time to be consulted through the online appointment inquiry platform;
the appointment inquiry case forming module is used for identifying the disease condition types of the disease conditions issued by the clients, extracting basic information registered by the clients from the online appointment inquiry platform, and forming an appointment inquiry case by the basic information of the clients, the disease condition types and the appointment time to serve as the current appointment inquiry case;
the client appointment type judging module is used for extracting client basic information and disease types from current appointment inquiry cases, calling all historical appointment inquiry cases of actively appointed appointment doctors stored in the online appointment inquiry platform, and further matching the client basic information and the disease types in the current appointment inquiry cases with the client basic information and the disease types corresponding to the called historical appointment inquiry cases respectively;
the old client type appointment management terminal is used for managing the appointment inquiry method corresponding to the old client type so as to recommend the appointed appointment consultation doctor of the old client type corresponding to the current appointment inquiry case, wherein the old client type appointment management terminal comprises an old client target history appointment inquiry case extraction module, an old client consultation interaction record acquisition module, an old client consultation interaction parameter acquisition module and an old client appointed appointment consultation doctor recommendation module;
the new client type appointment management terminal is used for managing the appointment inquiry mode corresponding to the new client type so as to recommend the appointed appointment consultation doctor of the new client type corresponding to the current appointment inquiry case, and comprises a new client reference history appointment inquiry case extraction module, a new client consultation interaction record acquisition module, a new client consultation interaction parameter acquisition module and a new client appointed appointment consultation doctor recommendation module.
As a further scheme of the invention, the specific method for determining the disease condition type comprises the following steps:
capturing disease part words from disease content needing consultation, which is issued by a client;
and acquiring the disease condition type corresponding to the disease condition content from the disease condition database by using the captured disease condition part words.
As a further aspect of the present invention, the customer basic information includes a customer name and a customer age.
As a further aspect of the present invention, the successful matching means that the basic information and the disease type of the client corresponding to a certain historical appointment inquiry case are consistent with the basic information and the disease type of the client in the current appointment inquiry case.
As a further scheme of the present invention, the old client target historical appointment inquiry case extraction module is configured to extract successfully matched historical appointment inquiry cases from all historical appointment inquiry cases of actively-designated appointment doctors, record the history appointment inquiry cases as target historical appointment inquiry cases, count the number of the extracted target historical appointment inquiry cases, and simultaneously obtain the appointment time corresponding to each entry mark historical appointment inquiry case, and number each entry mark historical appointment inquiry case sequentially as 1,2,.
As a further scheme of the present invention, the old customer consultation interaction record obtaining module is configured to obtain a consultation interaction record corresponding to each entry label history appointment inquiry case from the online appointment inquiry platform according to the number of each entry label history appointment inquiry case.
As a further scheme of the present invention, the old client consultation interaction parameter collecting module is configured to collect consultation interaction parameters from consultation interaction records corresponding to history appointment inquiry cases of each entry mark, where the consultation interaction parameters include a consultation interaction response rate, a consultation interaction degree of symptom, and a consultation interaction language lightness, and a specific collecting process corresponding to the consultation interaction response rate includes the following steps:
SR1, counting the number of the consultation interaction messages from the consultation interaction records corresponding to the historical appointment inquiry cases of the item labels, numbering the counted consultation interaction messages according to the sequence of the sending time points, and simultaneously acquiring the sending main bodies corresponding to the consultation interaction messages, wherein the sending main bodies are clients or doctors;
SR2, comparing the sending main bodies corresponding to the consultation interactive messages according to the numbering sequence corresponding to the consultation interactive messages, counting the number of the consultation interactive messages taking the sending main bodies corresponding to the historical appointment inquiry cases as clients and marking the number as Ki；
SR3 judging whether doctor replies to each consultation interactive message corresponding to client as sending subject, thereby counting the number of consultation interactive messages replied corresponding to each item mark historical appointment inquiry case, and recording the number as ki；
SR4 reaction of KiAnd kiSubstituting into a consultation interactive response rate calculation formula
Figure BDA0003470230640000041
Obtaining the consultation interactive response rate xi corresponding to each item label history appointment inquiry caseiThe consultation interactive response rate corresponding to the ith entry mark historical appointment inquiry case is expressed;
wherein the specific acquisition process corresponding to the consultation interaction symptom degree comprises the following steps:
ST1, obtaining a sending main body corresponding to each consultation interaction message in the consultation interaction records corresponding to each item label history appointment inquiry case according to the SR1 method, and forming a consultation interaction message set with the sending main body corresponding to each item label history appointment inquiry case as a client and a consultation interaction message set with the sending main body as a doctor from the sending main body;
ST2, extracting disease characteristics of the consultation interactive message set corresponding to the client as the sending subject;
ST3, extracting the content of the disease treatment measures of the consultation interactive message set corresponding to the doctor as the sending subject;
ST4, matching the disease characteristics corresponding to the historical appointment inquiry cases of the item labels with the disease treatment measure contents through a disease database, analyzing the consultation interactive symptom corresponding to the historical appointment inquiry cases of the item labels, and recording the consultation interactive symptom as etai；
The specific acquisition process corresponding to the language lightness for consultation and interaction comprises the following steps:
SM1 obtaining consultation interactive message set with the corresponding sending subject as doctor for each item label historical appointment inquiry case according to the ST1 method, and counting the number of the consultation interactive messages in the set, and recording as Xi；
SM2 extracting the non-civilized words in the set according to the serial number sequence, selecting the information capable of extracting the non-civilized words, recording the selected information as the information, counting the number of the information as xi；
SM3, recording the corresponding serial number of each non-civilized consultation interactive message, which can be recorded as 1,2, aij；
SM4 according to Xi、xiHexix-ijCalculating the language lightness for consultation interaction corresponding to each item label history appointment inquiry case
Figure BDA0003470230640000051
σiThe language brightness for consultation interaction corresponding to the ith entry mark historical appointment inquiry case is expressed.
As a further scheme of the present invention, the recommendation module for the old client appointed appointment consultation doctor is configured to analyze consultation interaction parameters corresponding to historical appointment inquiry cases of each entry label, so as to recommend the appointed appointment consultation doctor corresponding to the current appointment inquiry case, and the specific operation method is as follows:
the method comprises the following steps: extracting consultation doctor names from consultation interaction records corresponding to historical appointment inquiry cases of the item labels;
step two: according to the consultation interaction parameters corresponding to the historical appointment inquiry cases of the item labels, the consultation interaction satisfaction coefficient corresponding to the historical appointment inquiry cases of the item labels is counted
Figure BDA0003470230640000052
Figure BDA0003470230640000053
The consultation interactive satisfaction coefficient corresponding to the ith entry mark historical appointment inquiry case is expressed;
step three: comparing the names of consulting doctors corresponding to the historical appointment inquiry cases of the entry labels, judging whether the same consulting doctors exist or not, if so, removing the duplicate of the same consulting doctors, counting to obtain the number of consulting doctors existing in all the target historical appointment inquiry cases, and determining an average consultation interaction satisfaction coefficient corresponding to each consulting doctor;
step four: and acquiring the number of the appointment doctors of each consulting doctor at the appointment time, evaluating the consulting value degree corresponding to each consulting doctor according to the average consulting interactive satisfaction coefficient corresponding to each consulting doctor and the number of the appointment doctors at the appointment time, and screening out the consulting doctor with the largest consulting value degree as the appointed appointment consulting doctor of the current appointment inquiry case corresponding to the old client type.
As a further scheme of the present invention, the new client reference historical appointment inquiry case extraction module is configured to extract a historical appointment inquiry case corresponding to a disease condition type from all historical appointment inquiry cases on the online appointment inquiry platform according to the disease condition type corresponding to a current appointment inquiry case, record the extracted historical appointment inquiry case as a reference historical appointment inquiry case, and number the reference historical appointment inquiry cases according to a sequence of appointment times, where the reference historical appointment inquiry cases are sequentially labeled as 1 ', 2 ',. 1 ', i ',. n '.
Compared with the prior art, the invention has the following advantages:
(1) the invention extracts the matched historical appointment inquiry case from all historical appointment inquiry cases stored in the online appointment inquiry platform according to the disease condition types in the current appointment inquiry case, further performs consultation interactive record acquisition on the extracted historical appointment inquiry case, simultaneously performs consultation doctor name acquisition and consultation interactive parameter acquisition on the consultation interactive record, performs comprehensive analysis on the consultation interactive record to obtain the average consultation interactive satisfaction coefficient corresponding to each consultation doctor in the matched historical appointment inquiry case, evaluates the consultation value degree corresponding to each consultation doctor according to the average consultation interactive satisfaction coefficient corresponding to each consultation doctor and the number of the appointment persons at the appointment time, and thus performs consultation doctor recommendation with the largest consultation value degree, the comprehensive recommendation of the consulting doctors of the corresponding booking clients of the booking doctors which are not initiatively appointed is realized, the automatic recommendation mode of the booking platform is perfected, the defect that the consulting doctors automatically recommended by the platform cannot reflect the service quality of the consulting process of the consulting doctors is effectively overcome, the recommendation value of the consulting doctors is improved, the medical inquiry requirements of the booking clients for seeing a doctor are greatly met, and the inquiry and consultation experience of the booking clients is favorably enhanced.
(2) According to the invention, the client type of the current appointment client is judged in the process of comprehensively recommending the appointment clients corresponding to the appointment clients of the unspecified appointment doctors, and then the targeted recommendation is carried out according to the client type corresponding to the current appointment client, so that the recommendation flexibility of the appointment clients is improved, the problem of low recommendation fitting degree caused by the fact that a uniform recommendation mode is adopted to recommend the appointment clients of all the unspecified appointment doctors is avoided, and the targeted recommendation is beneficial to improving the recommendation effect.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a schematic view of a module connection structure according to the present invention;
FIG. 2 is a schematic diagram of the connection structure of the old client type reservation management terminal of the present invention;
fig. 3 is a schematic view of a connection structure of a new client type reservation management terminal according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an interactive-based intelligent client online appointment management system includes an appointment consultation content publishing module, a disease database, an appointment inquiry case constructing module, an appointment client type judging module, an old client type appointment management terminal and a new client type appointment management terminal.
The system comprises a reservation consultation content publishing module, a reservation inquiry case composing module, a reservation client type judging module and a new client type reservation management terminal, wherein the reservation consultation content publishing module is connected with the reservation inquiry case composing module, the reservation inquiry case composing module is connected with the reservation client type judging module, and the reservation client type judging module is respectively connected with the old client type reservation management terminal and the new client type reservation management terminal.
The appointment consultation content publishing module is used for registering by the client on the online appointment inquiry platform and publishing the disease condition content and appointment time needing to be consulted through the online appointment inquiry platform.
The appointment inquiry case composition module is used for identifying the types of the disease states issued by clients, and the specific method comprises the following steps:
capturing disease part words from disease contents which are issued by a client and need to be consulted, wherein the disease part words comprise eyes, arms, mouths, bellies and the like;
the captured disease part words are obtained from the disease database to obtain disease types corresponding to the disease contents, the specific obtaining mode is to compare the captured disease part words with a plurality of disease part words corresponding to various disease types in the disease database, if the comparison between the captured disease part words and a certain disease part word corresponding to a certain disease type is successful, the disease type corresponding to the disease contents is the disease type, and the mentioned disease types are eye diseases, limb diseases, oral diseases, abdominal epidemic diseases and the like.
The appointment inquiry case forming module is used for extracting basic information registered by a client from the online appointment inquiry platform, wherein the basic information of the client comprises the name of the client and the age of the client, and further forming an appointment inquiry case by using the basic information of the client, the disease condition type and the appointment time as the current appointment inquiry case.
The client appointment type judging module is used for extracting client basic information and disease types from the current appointment inquiry case, and calls all historical appointment inquiry cases of the actively appointed appointment doctors stored in the online appointment inquiry platform, further, the client basic information and the disease state type in the current appointment inquiry case are respectively matched with the client basic information and the disease state type corresponding to each called historical appointment inquiry case, if the client basic information and the disease state type corresponding to a certain historical appointment inquiry case are consistent with the client basic information and the disease state type in the current appointment inquiry case, the matching is successful, at the moment, whether the history appointment inquiry record successfully matched exists is judged, if the history appointment inquiry case successfully matched exists, the client corresponding to the current appointment inquiry case is the old client type, otherwise, the client corresponding to the current appointment inquiry case is the new client type.
According to the embodiment of the invention, the client type of the current appointment client is judged in the process of comprehensively recommending the appointment clients corresponding to the unspecified appointment doctors, and then the targeted recommendation is carried out according to the client type corresponding to the current appointment client, so that the recommendation flexibility of the consultation clients is improved, the problem of low recommendation fitting degree caused by the fact that a unified recommendation mode is adopted to recommend all the appointment clients of the unspecified appointment doctors is avoided, and the targeted recommendation is favorable for improving the recommendation effect.
The illness state database is used for storing a plurality of illness state part words corresponding to various illness state types, storing applicable illness states corresponding to various medicines and storing suitable examination item sets corresponding to various illness state characteristics under the illness state types
Referring to fig. 2, the old client type appointment management terminal is used for managing the appointment inquiry method corresponding to the old client type, so as to recommend the appointed appointment consulting doctor of the current appointment inquiry case corresponding to the old client type, wherein the old client type appointment management terminal comprises an old client target history appointment inquiry case extraction module, an old client consultation interaction record acquisition module, an old client consultation interaction parameter acquisition module and an old client appointed appointment consultation doctor recommendation module.
The old client target historical appointment inquiry case extraction module is used for extracting successfully matched historical appointment inquiry cases from all historical appointment inquiry cases of actively appointed appointment doctors, recording the historical appointment inquiry cases as target historical appointment inquiry cases, counting the number of the extracted target historical appointment inquiry cases, simultaneously acquiring the appointment time corresponding to each entry mark historical appointment inquiry case, and sequentially numbering the entry mark historical appointment inquiry cases into 1,2, 1, i, n according to the numbering basis.
The old client consultation interactive record acquisition module is used for acquiring consultation interactive records corresponding to the historical appointment inquiry cases of the item labels from the online appointment inquiry platform according to the serial numbers of the historical appointment inquiry cases of the item labels.
The old client consultation interaction parameter acquisition module is used for acquiring consultation interaction parameters from consultation interaction records corresponding to the historical appointment inquiry cases of the item labels, wherein the consultation interaction parameters comprise consultation interaction reply rate, consultation interaction symptom degree and consultation interaction language lightness, and the specific acquisition process corresponding to the consultation interaction reply rate executes the following steps:
SR1, counting the number of the consultation interaction messages from the consultation interaction records corresponding to the historical appointment inquiry cases of the item labels, numbering the counted consultation interaction messages according to the sequence of the sending time points, and simultaneously acquiring the sending main bodies corresponding to the consultation interaction messages, wherein the sending main bodies are clients or doctors;
SR2, comparing the sending main bodies corresponding to the consultation interactive messages according to the numbering sequence corresponding to the consultation interactive messages, counting the number of the consultation interactive messages taking the sending main bodies corresponding to the historical appointment inquiry cases as clients and marking the number as Ki；
SR3 judging whether doctor replies to each consultation interactive message corresponding to client as sending subject, thereby counting the number of consultation interactive messages replied corresponding to each item mark historical appointment inquiry case, and recording the number as ki；
SR4 reaction of KiAnd kiSubstituting into a consultation interactive response rate calculation formula
Figure BDA0003470230640000101
Obtaining the consultation interactive response rate xi corresponding to each item label history appointment inquiry caseiThe consultation interactive response rate, k, corresponding to the ith entry mark historical appointment inquiry caseiNumber of consultation interactive messages, K, expressed as the number of responses corresponding to the ith entry mark historical appointment inquiry caseiThe number of the consultation interactive messages with the sending main body as the client is represented as the number of the ith entry mark historical appointment inquiry cases, wherein the larger the number of the consultation interactive messages which are correspondingly replied by a certain entry mark historical appointment inquiry record is, the larger the consultation interactive replying rate is.
Wherein the specific acquisition process corresponding to the consultation interaction symptom degree comprises the following steps:
ST1, obtaining a sending main body corresponding to each consultation interaction message in the consultation interaction records corresponding to each item label history appointment inquiry case according to the SR1 method, and forming a consultation interaction message set with the sending main body corresponding to each item label history appointment inquiry case as a client and a consultation interaction message set with the sending main body as a doctor from the sending main body;
ST2, extracting disease characteristics of the consultation interactive message sets corresponding to the clients as the sending subjects respectively, wherein the disease characteristics comprise fever, pain, acupuncturing pain, dizziness, swelling and pain and the like;
ST3, extracting the content of the disease treatment measures for the consultation interactive message set with the sending subject corresponding to the doctor;
ST4, matching the disease characteristics corresponding to each item label historical appointment inquiry case with the disease treatment measure content through a disease database, wherein the specific matching method comprises the following steps:
the first step is as follows: judging the types of the extracted disease treatment measures, wherein the types of the disease treatment measures are a medication type and an inspection type, if the types of the disease treatment measures are the medication type, acquiring the names of medicines from the extracted contents of the disease treatment measures, and if the types of the disease treatment measures are the inspection type, acquiring the names of inspection items from the extracted contents of the disease treatment measures;
the second step is that: if the type of a disease treatment measure corresponding to a certain entry mark historical appointment inquiry record is a medication type, extracting an applicable disease corresponding to the medicine name from a disease database by using the acquired medicine name, further matching the applicable disease with the disease characteristic corresponding to the entry mark historical appointment inquiry record, recording the corresponding consultation interaction of the entry mark historical appointment inquiry case as the symptom epsilon if the matching is successful, and recording the corresponding consultation interaction of the entry mark historical appointment inquiry case as the symptom epsilon' if the matching is failed;
the third step: if the disease treatment measure type corresponding to a certain entry label history appointment inquiry record is an inspection type, comparing the disease characteristics corresponding to the entry label history appointment inquiry record with a proper inspection item set corresponding to various disease characteristics of the disease type in a disease database, screening a proper inspection item set corresponding to the entry label history appointment inquiry record, comparing the inspection item name corresponding to the entry label history appointment inquiry record with the inspection item name in the proper inspection item set corresponding to the entry label history appointment inquiry record, if the comparison is successful, recording the consultation interaction corresponding to the entry label history appointment inquiry case as a symptom degree beta, and if the matching is failed, recording the consultation interaction corresponding to the entry label history appointment inquiry case as a symptom degree beta'.
Consult interaction pairs corresponding to historical appointment inquiry cases of all item labels analyzed from the item labelsDegree of disease, recorded as ηiWherein etaiThe value of (A) can be epsilon or epsilon 'or beta'.
The specific acquisition process corresponding to the language lightness for consultation and interaction comprises the following steps:
SM1 obtaining consultation interactive message set with the corresponding sending subject as doctor for each item label historical appointment inquiry case according to the ST1 method, and counting the number of the consultation interactive messages in the set, and recording as Xi；
SM2 extracting the non-civilized words in the set according to the serial number sequence, selecting the information capable of extracting the non-civilized words, recording the selected information as the information, counting the number of the information as xi；
SM3, recording the corresponding serial number of each non-civilized consultation interactive message, which can be recorded as 1,2, aijThe method for determining the non-civilization indexes comprises the steps of firstly counting the number of non-civilization vocabularies in each item label history appointment inquiry case corresponding to each non-civilization consultation interactive message, and then comparing the number with the number range of the non-civilization vocabularies corresponding to the set various non-civilization indexes to obtain the non-civilization indexes of each item label history appointment inquiry case corresponding to each non-civilization consultation interactive message;
SM4 according to Xi、xiHexix-ijCalculating the language lightness for consultation interaction corresponding to each item label history appointment inquiry case
Figure BDA0003470230640000121
σiLanguage lightness, x for consultation interaction expressed as corresponding to the ith entry label historical appointment inquiry caseiShowing the number of non-civilized consultation interactive information, X, corresponding to the ith entry mark historical appointment inquiry caseiThe number of consultation interactive messages, chi, of which the corresponding sending main body is the doctor is represented as the ith item mark historical appointment inquiry caseijMarking History Prep for ith entryThe inquiry case corresponds to the non-civilization index of the jth non-civilized consultation interactive message, wherein the larger the quantity of the non-civilized consultation interactive information and the non-civilization index corresponding to a certain entry mark history reservation inquiry case is, the smaller the consultation interactive civilization degree corresponding to the entry mark history reservation inquiry case is.
The old client appointed appointment consultation doctor recommendation module is used for analyzing consultation interaction parameters corresponding to historical appointment consultation cases of each entry label so as to recommend appointed appointment consultation doctors corresponding to current appointment consultation cases, and the specific operation method is as follows:
the method comprises the following steps: extracting consultation doctor names from consultation interaction records corresponding to historical appointment inquiry cases of the item labels;
step two: according to the consultation interaction parameters corresponding to the historical appointment inquiry cases of the item labels, the consultation interaction satisfaction coefficient corresponding to the historical appointment inquiry cases of the item labels is counted
Figure BDA0003470230640000131
Figure BDA0003470230640000132
The consultation interactive satisfaction coefficient corresponding to the ith entry mark historical appointment inquiry case is expressed;
step three: comparing the names of consulting doctors corresponding to the historical appointment inquiry cases of the entry marks, judging whether the same consulting doctors exist or not, if the same consulting doctors exist, removing the duplicate of the same consulting doctors, counting to obtain the number of consulting doctors existing in all the target historical appointment inquiry cases, numbering the counted consulting doctors, respectively marking the consulting doctors as 1,2, 1, d, u, and determining the average consultation interaction satisfaction coefficient corresponding to each consulting doctor as psidIf only one target historical appointment inquiry case corresponding to a certain consulting doctor is available, the average consultation interactive satisfaction coefficient corresponding to the consulting doctor is the consultation interactive satisfaction coefficient corresponding to the target historical appointment inquiry case, and if more than one target historical appointment inquiry case corresponding to the certain consulting doctor is available, all target historical appointments corresponding to the consulting doctor are preset by the consulting doctorCalculating the mean value of the consultation interactive satisfaction coefficients of the inquiry cases, wherein the mean consultation interactive satisfaction coefficient corresponding to the consulting doctor is the mean value calculation result;
step four: acquiring the number of the appointment persons of each consulting doctor at the appointment time and recording as ydThereby evaluating the consulting value degree corresponding to each consulting doctor according to the average consulting interactive satisfaction coefficient corresponding to each consulting doctor and the number of the appointment persons at the appointment time
Figure BDA0003470230640000141
χdAnd the consulting value degree is expressed as the consulting value degree corresponding to the d-th consulting doctor, wherein the larger the average consulting interaction satisfaction coefficient is, the fewer the number of the reserved persons in the reserving time is, and the higher the consulting value degree is, and the consulting doctor with the largest consulting value degree is screened out from the consulting value degrees and serves as the appointed reserving consulting doctor of the current reserving inquiry case corresponding to the old client type.
Referring to fig. 3, the new client type appointment management terminal is used for managing an appointment inquiry method corresponding to the new client type, so as to recommend a designated appointment consulting doctor of the current appointment inquiry case corresponding to the new client type, wherein the new client type appointment management terminal comprises a new client reference history appointment inquiry case extraction module, a new client consultation interaction record acquisition module, a new client consultation interaction parameter acquisition module and a new client appointed appointment consultation doctor recommendation module.
The new client reference historical appointment inquiry case extraction module is used for extracting historical appointment inquiry cases corresponding to the disease types from all historical appointment inquiry cases on the online appointment inquiry platform according to the disease types corresponding to the current appointment inquiry cases, wherein the mentioned historical appointment inquiry cases comprise the historical appointment inquiry cases of an actively appointed appointment doctor, the extracted historical appointment inquiry cases are marked as reference historical appointment inquiry cases, and meanwhile, the reference historical appointment inquiry cases are numbered according to the sequence of appointment time and are marked as 1 ', 2',. i ',. n'.
And the new client consultation interaction record acquisition module is used for acquiring consultation interaction records corresponding to all the reference history appointment inquiry cases from the online appointment inquiry platform according to the serial numbers of all the reference history appointment inquiry cases.
The new client consultation interaction parameter acquisition module is used for acquiring consultation interaction parameters from consultation interaction records corresponding to all reference historical appointment inquiry cases, and the specific acquisition process refers to the acquisition process corresponding to the old client consultation interaction parameter acquisition module.
The new client appointed appointment consultation doctor recommendation module is used for analyzing consultation interaction parameters corresponding to all reference historical appointment consultation cases so as to recommend appointed appointment consultation doctors corresponding to current appointed consultation cases, and the specific operation method refers to the operation method corresponding to the old client appointed appointment consultation doctor recommendation module.
The embodiment of the invention forms the current appointment inquiry case by the disease condition content released by the client on the online appointment inquiry platform, extracts the matched historical appointment inquiry case from all the historical appointment inquiry cases stored in the online appointment inquiry platform according to the disease condition type in the current appointment inquiry case, further performs consultation interaction record acquisition on the extracted historical appointment inquiry case, simultaneously performs consultation doctor name acquisition and consultation interaction parameter acquisition on the consultation interaction record, performs comprehensive analysis on the consultation interaction record to obtain the average consultation interaction satisfaction coefficient corresponding to each consultation doctor in the matched historical appointment inquiry case, estimates the consultation value degree corresponding to each consultation doctor according to the average consultation interaction satisfaction coefficient corresponding to each consultation doctor and the number of the appointment persons at the appointment time, and thus performs consultation doctor recommendation with the maximum consultation value degree, the comprehensive recommendation of the consulting doctors of the corresponding booking clients of the booking doctors which are not initiatively appointed is realized, the automatic recommendation mode of the booking platform is perfected, the defect that the consulting doctors automatically recommended by the platform cannot reflect the service quality of the consulting process of the consulting doctors is effectively overcome, the recommendation value of the consulting doctors is improved, the medical inquiry requirements of the booking clients for seeing a doctor are greatly met, and the inquiry and consultation experience of the booking clients is favorably enhanced.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.

Claims (9)

1. An intelligent management system for client online reservation based on interactivity is characterized in that: the system comprises a reservation consultation content publishing module, a disease database, a reservation inquiry case forming module, a reservation client type judging module, an old client type reservation management terminal and a new client type reservation management terminal;
the appointment consultation content publishing module is used for registering by a client on the online appointment inquiry platform and publishing the disease condition content and appointment time to be consulted through the online appointment inquiry platform;
the appointment inquiry case forming module is used for identifying the disease condition types of the disease conditions issued by the clients, extracting basic information registered by the clients from the online appointment inquiry platform, and forming an appointment inquiry case by the basic information of the clients, the disease condition types and the appointment time to serve as the current appointment inquiry case;
the client appointment type judging module is used for extracting client basic information and disease types from current appointment inquiry cases, calling all historical appointment inquiry cases of actively appointed appointment doctors stored in the online appointment inquiry platform, and further matching the client basic information and the disease types in the current appointment inquiry cases with the client basic information and the disease types corresponding to the called historical appointment inquiry cases respectively;
the old client type appointment management terminal is used for managing the appointment inquiry method corresponding to the old client type so as to recommend the appointed appointment consultation doctor of the old client type corresponding to the current appointment inquiry case, wherein the old client type appointment management terminal comprises an old client target history appointment inquiry case extraction module, an old client consultation interaction record acquisition module, an old client consultation interaction parameter acquisition module and an old client appointed appointment consultation doctor recommendation module;
the new client type appointment management terminal is used for managing the appointment inquiry mode corresponding to the new client type so as to recommend the appointed appointment consultation doctor of the new client type corresponding to the current appointment inquiry case, and comprises a new client reference history appointment inquiry case extraction module, a new client consultation interaction record acquisition module, a new client consultation interaction parameter acquisition module and a new client appointed appointment consultation doctor recommendation module.
2. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the specific method for determining the disease category comprises the following steps:
capturing disease part words from disease content needing consultation, which is issued by a client;
and acquiring the disease condition type corresponding to the disease condition content from the disease condition database by using the captured disease condition part words.
3. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the customer basic information includes a customer name and a customer age.
4. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the successful matching means that the client basic information and the disease condition type corresponding to a certain historical appointment inquiry case are consistent with the client basic information and the disease condition type in the current appointment inquiry case.
5. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the old client target historical appointment inquiry case extraction module is used for extracting successfully matched historical appointment inquiry cases from all historical appointment inquiry cases of actively appointed appointment doctors, recording the historical appointment inquiry cases as target historical appointment inquiry cases, counting the number of the extracted target historical appointment inquiry cases, simultaneously acquiring the appointment time corresponding to each item historical appointment inquiry case, and sequentially numbering the item historical appointment inquiry cases into 1,2, 1, i, n.
6. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the old client consultation interactive record acquisition module is used for acquiring consultation interactive records corresponding to the historical appointment inquiry cases of the items from the online appointment inquiry platform according to the serial numbers of the historical appointment inquiry cases of the items.
7. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the old client consultation interaction parameter acquisition module is used for acquiring consultation interaction parameters from consultation interaction records corresponding to the historical appointment inquiry cases of the item labels, wherein the consultation interaction parameters comprise consultation interaction reply rate, consultation interaction symptom degree and language brightness for consultation interaction, and the specific acquisition process corresponding to the consultation interaction reply rate executes the following steps:
SR1: counting the number of the consultation interactive messages from the consultation interactive records corresponding to the historical appointment inquiry cases of the item labels, numbering the counted consultation interactive messages according to the sequence of sending time points, and simultaneously acquiring a sending main body corresponding to the consultation interactive messages, wherein the sending main body is a client or a doctor;
SR2: comparing the sending main bodies corresponding to the consultation interactive messages according to the number sequence corresponding to the consultation interactive messages, counting the number of the consultation interactive messages taking the sending main bodies corresponding to the historical appointment inquiry cases as clients and marking the number as Ki；
SR3: judging whether the doctor replies to each consultation interactive message corresponding to the client as the sending main body, thereby counting the number of consultation interactive messages corresponding to each item label history appointment inquiry case and recording the number as ki；
SR4: will KiAnd kiSubstituting into a consultation interactive response rate calculation formula
Figure FDA0003470230630000031
Obtaining the consultation interactive response rate xi corresponding to each item label history appointment inquiry caseiThe consultation interactive response rate corresponding to the ith entry mark historical appointment inquiry case is expressed;
wherein the specific acquisition process corresponding to the consultation interaction symptom degree comprises the following steps:
ST1: obtaining a sending main body corresponding to each consultation interactive message in the consultation interactive records corresponding to each item label history appointment inquiry case according to the SR1 method, and forming a consultation interactive message set with the sending main body corresponding to each item label history appointment inquiry case as a client and a consultation interactive message set with the sending main body as a doctor from the sending main body;
ST2: extracting disease condition characteristics of a consultation interaction message set corresponding to a client as a sending main body;
ST3: extracting the content of disease treatment measures from a consultation interactive message set corresponding to the doctor as a sending subject;
ST4: matching the disease characteristics corresponding to the historical appointment inquiry cases of the item labels with the disease treatment measure contents through a disease database, analyzing the consultation interactive symptom degree corresponding to the historical appointment inquiry cases of the item labels, and recording the consultation interactive symptom degree as etai；
The specific acquisition process corresponding to the language lightness for consultation and interaction comprises the following steps:
SM1: obtaining a consultation interactive message set with the corresponding sending main body of each item label historical appointment inquiry case as a doctor according to the ST1 method, and counting the number of the consultation interactive messages in the set and recording as Xi；
SM2: sequentially extracting the non-civilized words from each consultation interactive message in the set according to the serial number sequence, selecting the consultation interactive messages capable of extracting the non-civilized words, recording the selected consultation interactive messages as the non-civilized consultation interactive messages, and counting the non-civilized consultation interactive messagesNumber of messages, denoted as xi；
SM3: recording the corresponding serial number of each non-civilized consultation interactive message, which can be recorded as 1,2, a, j, a, m, determining the non-civilized index of each item history reservation inquiry case corresponding to each non-civilized consultation interactive message, which is recorded as χij；
SM4: according to Xi、xiHexix-ijCalculating the language lightness for consultation interaction corresponding to each item label history appointment inquiry case
Figure FDA0003470230630000041
σiThe language brightness for consultation interaction corresponding to the ith entry mark historical appointment inquiry case is expressed.
8. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the old client appointed appointment consultation doctor recommendation module is used for analyzing consultation interaction parameters corresponding to historical appointment consultation cases of all the entry labels so as to recommend appointed appointment consultation doctors corresponding to current appointment consultation cases, and the specific operation method is as follows:
the method comprises the following steps: extracting consultation doctor names from consultation interaction records corresponding to historical appointment inquiry cases of the item labels;
step two: according to the consultation interaction parameters corresponding to the historical appointment inquiry cases of the item labels, the consultation interaction satisfaction coefficient corresponding to the historical appointment inquiry cases of the item labels is counted
Figure FDA0003470230630000051
Figure FDA0003470230630000052
The consultation interactive satisfaction coefficient corresponding to the ith entry mark historical appointment inquiry case is expressed;
step three: comparing the names of consulting doctors corresponding to the historical appointment inquiry cases of the entry labels, judging whether the same consulting doctors exist or not, if so, removing the duplicate of the same consulting doctors, counting to obtain the number of consulting doctors existing in all the target historical appointment inquiry cases, and determining an average consultation interaction satisfaction coefficient corresponding to each consulting doctor;
step four: and acquiring the number of the appointment doctors of each consulting doctor at the appointment time, evaluating the consulting value degree corresponding to each consulting doctor according to the average consulting interactive satisfaction coefficient corresponding to each consulting doctor and the number of the appointment doctors at the appointment time, and screening out the consulting doctor with the largest consulting value degree as the appointed appointment consulting doctor of the current appointment inquiry case corresponding to the old client type.
9. The intelligent management system for client online booking based on interactivity of claim 1, wherein: the new client reference historical appointment inquiry case extraction module is used for extracting historical appointment inquiry cases corresponding to the types of the diseases from all historical appointment inquiry cases on the online appointment inquiry platform according to the types of the diseases corresponding to the current appointment inquiry cases, recording the extracted historical appointment inquiry cases as reference historical appointment inquiry cases, and numbering the reference historical appointment inquiry cases according to the sequence of appointment time, wherein the reference historical appointment inquiry cases are marked as 1 ', 2 ',.i ', i ', n '.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115346654A (en) * 2022-07-14 2022-11-15 赵盛 Intelligent service system based on internet
CN115862831A (en) * 2023-03-02 2023-03-28 山东远程分子互联网医院有限公司 Intelligent online appointment diagnosis and treatment management system and method

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115346654A (en) * 2022-07-14 2022-11-15 赵盛 Intelligent service system based on internet
CN115862831A (en) * 2023-03-02 2023-03-28 山东远程分子互联网医院有限公司 Intelligent online appointment diagnosis and treatment management system and method

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