CN112349434A - Intelligent customer service system for inpatients - Google Patents
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- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
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Abstract
The invention discloses an intelligent customer service system for inpatients, which is characterized in that a patient firstly enters a chief complaint symptom in advance through a customer service system, the customer service system analyzes possible corresponding symptoms and corresponding departments according to a database after capturing the chief complaint symptom in a classified manner, and simultaneously provides a registrable doctor directory according to the scheduled visit time of the patient, thereby helping the patient to realize on-line accurate registration, the doctor fills in the electronic medical record after the patient visits the doctor, gives out a plurality of treatment schemes and enters the customer service system for keeping a file, the database in the customer service system retrieves the medicine and treatment means types in the database after obtaining the treatment schemes, calculates the total amount and the detailed cost of the patient in the treatment schemes, sends the total amount and the detailed cost to the financial processing module and generates a quotation to send to the patient, thus, the complete transparency of the medical cost is realized, and the treatment cost can be balanced by the patient according to the self condition before paying.
Description
Technical Field
The invention relates to the field of medical services, in particular to an intelligent customer service system for inpatients.
Background
Natural language processing is an important direction in the fields of computer science and artificial intelligence. It studies various theories and methods that enable efficient communication between humans and computers using natural language. Natural language processing is a science integrating linguistics, computer science and mathematics. Therefore, the research in the field relates to natural language, namely language used by people daily, so that the research is closely related to the research of linguistics, but has important difference, under the traditional pure manual mode, the processing of all user consultation depends on manual processing of customer service staff, great pressure is brought to the customer service staff under the condition of large consultation amount, meanwhile, the consultation of the users often has a lot of commonalities, under the condition, if only manual response is carried out, the working efficiency is low, the intelligent degree is low, the mental fatigue of the customer service staff is easily caused, the best response to the consultant cannot be ensured, and the requirement on the actual response basis of the customer service staff is high.
Particularly, in the use environment of a hospital, the patient can expect large consultation requirements before admission and during hospitalization, the workload of traditional manual customer service is extremely large, but if the number of the customer service personnel is simply increased, the good professional literacy of the customer service personnel cannot be guaranteed in the medical field needing sufficient knowledge, and therefore automatic customer service is urgently needed to be introduced into the use environment of the hospital.
Compared with traditional automatic customer service, the consultation requirement of the patient in the using environment of the hospital is higher for the professional requirement, the requirement of the consultation content is more detailed, particularly for inpatients, the treatment period is longer, the patient cannot visually obtain the treatment plan and the payment cost of the patient in the existing inpatient treatment process, the specific cost needing to be paid in the current treatment period is often known when the payment is carried out, medical disputes are easily caused due to the cost, meanwhile, the inpatient needs to be timely communicated with medical care personnel due to the longer doctor-patient coordination period, and an AI intelligent customer service system is needed to ensure that the appeal of the patient is timely fed back to a series of responsible persons such as an attending physician.
The Chinese patent with the publication number of CN201911313458.1 discloses a hospital appointment register system based on a WeChat applet, which comprises a user terminal, wherein the user terminal is loaded with the WeChat applet, a personal information interface is displayed in the WeChat applet, the user terminal is bidirectionally connected with a WeChat server through a communication protocol, the WeChat server is connected with a hospital server through a bidirectional communication cable, the hospital server is bidirectionally connected with a hospital computer terminal and a customer server terminal through the bidirectional communication cable, a register system interface is loaded in the hospital computer terminal, the register system interface and the personal information interface are connected through hyperlinks, the register system interface comprises a plurality of groups of department information buttons and artificial customer service buttons, the artificial customer service buttons and the customer server terminal are bidirectionally connected through the communication protocol, and the appointment register system realizes the appointment register function, but does not provide triage function for the patient before registration, and the accuracy of registration cannot be ensured.
Chinese patent publication No. CN104200294A discloses an outpatient service information management system, which includes: the clinic information database is used for storing the personal health information of the patient; the pre-hospital health information questionnaire analysis module is used for providing a pre-hospitalization health information questionnaire for the patient; the hospital diagnosis and treatment management module is used for managing the patient according to the pre-hospitalization advice generated by the pre-hospital health information questionnaire analysis module and all diagnosis and treatment information and treatment schemes generated in the hospital diagnosis and treatment process; the after-hospital health management module is used for providing follow-up health management suggestions for the patients according to the diagnosis and treatment information and the treatment schemes of the patients managed in the in-hospital diagnosis and treatment management module and monitoring the follow-up health management suggestions; the technical scheme realizes the functions of pre-diagnosis and triage before registration and treatment scheme suggestion for patients in the treatment process by providing health information questionnaires for the patients before hospitalization, and simultaneously realizes the cooperative effect of multiple departments of a hospital to a certain extent, but does not realize the on-line unified integration of the outpatient department, the financial department, the pharmacy and the residential department, and the intermediate entity handover link still needs the patients to carry out self-treatment, thereby causing inconvenience for the patients when hospitalization.
Disclosure of Invention
The purpose of the invention is as follows: the present invention aims to improve and innovate the above drawbacks and deficiencies in the prior art or the prior art, and aims to provide a medical intelligent customer service system, which is realized by the following design structure and technical scheme in order to solve the above problems and achieve the above object:
an intelligent customer service system for inpatients, comprising the steps of:
s1, a database is built in advance, department and physician name lists of a hospital and electronic medical records of a patient in a current period are recorded, an AI big data analysis component is configured in the database, symptom description and pathological classification in the electronic medical records are captured and summarized into a form corresponding to symptom representation and symptom department pre-diagnosis, the patient logs in a customer service system before hospitalizing, the chief complaint symptom and the preset hospitalizing time of the patient are recorded, keywords in the chief complaint symptom are captured by the system, and the keyword is compared in the form corresponding to the symptom representation and the symptom department pre-diagnosis through the AI big data analysis component to finish the diagnosis department pre-diagnosis classification of the patient;
s2, after the pre-diagnosis is finished, doctors with corresponding dates for sitting diagnosis are screened according to the scheduled hospitalizing time of the patient, the doctor list with vacant numbers is classified into a common number and an expert number, and a classification form with registration cost is generated and sent to the patient;
s3, selecting a proper doctor for online registration according to the requirement of the patient;
s4, when the patient goes to a hospital to see a doctor on the day of the scheduled date, after the doctor finishes the inquiry and corresponding detection, the doctor fills in an electronic medical record, gives out a plurality of treatment schemes and enters a customer service system to keep a file, an AI big data analysis component in the customer service system retrieves the database type medicines and treatment means types after obtaining the treatment schemes, calculates the total amount and the detail of the cost of the patient in the treatment schemes through a pricing table in the retrieval database, sends the total amount and the detail of the cost to a financial processing module, generates a quotation and sends the quotation to the patient, the patient selects and confirms the quotation by himself and then feeds the quotation back to the doctor terminal through the customer service system, and the doctor prints the generated quotation and sends the treatment schemes to a pharmacy and;
s5, after the patient finishes payment, the customer service system lists the treatment plan of the patient in a confirmation execution list and specifies a hospital bed, a pre-handling admission procedure and a dispatching management bed physician, the pharmacy distributes the medicine amount and a medicine taking time axis according to the treatment steps in the treatment plan in the confirmation execution list, and sends the first course of medicine to the department of the hospital and the corresponding management bed physician signs and confirms taking over;
s6, because the hospital bed is pre-designated and the admission procedures are pre-handled in S5, the patient can go directly to the hospital department to enter the hospital, and meanwhile, the first course of treatment of the medicine is taken in advance by the tube bed physician and the nurse in the ward corresponding to the bed, and the patient can directly start the treatment work after entering the hospital;
s7, the customer service system comprises a preset patient appeal feedback assembly, the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, a drug adverse reaction feedback module, a life appeal feedback module and an emergency feedback module, the hospitalization appeal feedback module is connected with a hospital entrance port, the treatment effect feedback module is connected with a tube bed doctor port and an attending doctor port, the drug adverse reaction feedback module is connected with a pharmacy port, the attending doctor port and a tube bed doctor port, the life appeal feedback module is connected with a ward nurse station port, and the emergency feedback module is connected with a ward nurse station port, an emergency room port, a tube bed doctor port and an attending doctor port;
and S8, after the single-stage treatment is completed, the financial processing module generates an electronic invoice and provides a customer service system to send the electronic invoice to the patient, and the patient selects the electronic invoice or mails a paper invoice through the financial processing module.
Preferably, the patient in S1 is a patient with an emergent emergency and a severe trauma, after the chief complaint symptom and the emergency demand are entered, the customer service system directly assigns a corresponding department doctor to follow the ambulance to receive a call to the patient after completing the triage procedure, and simultaneously the customer service system directly notifies the emergency department to prepare an emergency room and calls the on-duty doctor of the corresponding department to go to the emergency room for emergency consultation.
Preferably, after the single-stage treatment in S8 is completed, the customer service system sends the updated electronic medical record of the current stage to the patient, and the patient selects the electronic medical record or mails the paper medical record copy through the customer service system.
Preferably, the hospital housing port, the main doctor port and the tube bed doctor port in S7 are also reversely connected to the patient appeal feedback assembly, the medication condition, the biochemical detection index and the rehabilitation state of the patient are uploaded through the patient appeal feedback assembly every day, and the patient can know the treatment progress of the patient in real time through the patient appeal feedback assembly.
Preferably, in S5, the pharmacy sends the first course of medicine to the department of living, and the corresponding tube bed physician signs and confirms taking over, and after the medicine transfer and taking over of the subsequent batches are completed and confirmed bidirectionally by the pharmacy and the tube bed physician, the responsible persons of the corresponding batch are transferred and marked under the name of the tube bed physician in the customer service system.
Compared with the prior art, the invention has the following beneficial effects: (1) after the customer service system captures the chief complaint symptoms in a classified manner, the possible corresponding symptoms and the corresponding departments are obtained by performing comparison analysis on the form corresponding to the symptom characteristics and the disease department pre-diagnosis through an AI big data analysis component according to keywords in the captured chief complaint symptoms;
(2) before the patient is in the hospital, the customer service system pre-processes the procedure of pre-handling admission, so that the patient can directly enter the hospital and start a treatment process, thereby improving the treatment work efficiency;
(3) the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, an adverse drug reaction feedback module, a life appeal feedback module and an emergency feedback module, can realize real-time proposing and feedback obtaining of patient appeal, can enable a patient to be timely treated by medical staff when emergencies occur, avoids medical risks, can timely adjust a treatment scheme and a hospitalization nursing scheme according to patient feedback, and effectively improves patient satisfaction, so that good development of doctor-patient relationships is facilitated.
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FIG. 1 is a schematic view of the flow structure of the present invention;
FIG. 2 is a logic diagram of the algorithm of the step of pre-diagnosis and triage in the present invention.
Detailed Description
The invention will be further described with reference to the drawings, but the invention is not limited thereby within the scope of the embodiments described.
Example 1: an intelligent customer service system for inpatients, comprising the steps of:
s1, a database is built in advance, department and physician name lists of a hospital and electronic medical records of a patient in a current period are recorded, an AI big data analysis component is configured in the database, symptom description and pathological classification in the electronic medical records are captured and summarized into a form corresponding to symptom representation and symptom department pre-diagnosis, the patient logs in a customer service system before hospitalizing, the chief complaint symptom and the preset hospitalizing time of the patient are recorded, keywords in the chief complaint symptom are captured by the system, and the keyword is compared in the form corresponding to the symptom representation and the symptom department pre-diagnosis through the AI big data analysis component to finish the diagnosis department pre-diagnosis classification of the patient;
s2, after the pre-diagnosis is finished, doctors with corresponding dates for sitting diagnosis are screened according to the scheduled hospitalizing time of the patient, the doctor list with vacant numbers is classified into a common number and an expert number, and a classification form with registration cost is generated and sent to the patient;
s3, selecting a proper doctor for online registration according to the requirement of the patient;
s4, when the patient goes to a hospital to see a doctor on the day of the scheduled date, after the doctor finishes the inquiry and corresponding detection, the doctor fills in an electronic medical record, gives out a plurality of treatment schemes and enters a customer service system to keep a file, an AI big data analysis component in the customer service system retrieves the database type medicines and treatment means types after obtaining the treatment schemes, calculates the total amount and the detail of the cost of the patient in the treatment schemes through a pricing table in the retrieval database, sends the total amount and the detail of the cost to a financial processing module, generates a quotation and sends the quotation to the patient, the patient selects and confirms the quotation by himself and then feeds the quotation back to the doctor terminal through the customer service system, and the doctor prints the generated quotation and sends the treatment schemes to a pharmacy and a;
s5, after the patient finishes payment, the customer service system lists the treatment plan of the patient in a confirmation execution list and specifies a hospital bed, a pre-handling admission procedure and a dispatching management bed physician, the pharmacy distributes the medicine amount and a medicine taking time axis according to the treatment steps in the treatment plan in the confirmation execution list, and sends the first course of medicine to the department of the hospital and the corresponding management bed physician signs and confirms taking over;
s6, because the hospital bed is pre-designated and the admission procedures are pre-handled in S5, the patient can go directly to the hospital department to enter the hospital, and meanwhile, the first course of treatment of the medicine is taken in advance by the tube bed physician and the nurse in the ward corresponding to the bed, and the patient can directly start the treatment work after entering the hospital;
s7, the customer service system comprises a preset patient appeal feedback assembly, the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, a drug adverse reaction feedback module, a life appeal feedback module and an emergency feedback module, the hospitalization appeal feedback module is connected with a hospital entrance port, the treatment effect feedback module is connected with a tube bed doctor port and an attending doctor port, the drug adverse reaction feedback module is connected with a pharmacy port, the attending doctor port and a tube bed doctor port, the life appeal feedback module is connected with a ward nurse station port, and the emergency feedback module is connected with a ward nurse station port, an emergency room port, a tube bed doctor port and an attending doctor port;
and S8, after the single-stage treatment is completed, the financial processing module generates an electronic invoice and provides a customer service system to send the electronic invoice to the patient, and the patient selects the electronic invoice or mails a paper invoice through the financial processing module.
The advantages of this embodiment are: (1) after the customer service system captures the chief complaint symptoms in a classified manner, the possible corresponding symptoms and the corresponding departments are obtained by performing comparison analysis on the form corresponding to the symptom characteristics and the disease department pre-diagnosis through an AI big data analysis component according to keywords in the captured chief complaint symptoms;
(2) the complete transparentization of medical expenses is realized, and the treatment expenses can be balanced by patients according to self conditions before paying;
(3) the pharmacy is directly butted with a tube bed doctor, so that the medicine is not handed over by a patient, and the risk of medical accidents caused by medicine delivery errors due to patient errors is avoided;
(4) before the patient is in the hospital, the customer service system pre-processes the procedure of pre-handling admission, so that the patient can directly enter the hospital and start a treatment process, thereby improving the treatment work efficiency;
(5) the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, an adverse drug reaction feedback module, a life appeal feedback module and an emergency feedback module, can realize real-time proposing and feedback obtaining of patient appeal, can enable a patient to be timely treated by medical staff when emergencies occur, avoids medical risks, can timely adjust a treatment scheme and a hospitalization nursing scheme according to patient feedback, and effectively improves patient satisfaction, so that good development of doctor-patient relationships is facilitated.
Example 2: an intelligent customer service system for inpatients, comprising the steps of:
s1, pre-filing a database, recording the department and the name of the doctor in the department and the electronic medical record of the patient in the current period, an AI big data analysis component is configured in the database, the symptom description and the pathological classification in the electronic medical record are captured and summarized into a form corresponding to symptom characterization and disease department pre-diagnosis, the patient in S1 is a sudden emergency and severe trauma patient, after the chief complaint symptom and the emergency appeal are recorded, the system captures keywords in the chief complaint symptoms and compares the keywords in the form corresponding to the symptom characteristics and the disease department pre-diagnosis through an AI big data analysis component to finish the classification of the patient's clinic pre-diagnosis, the customer service system directly assigns a corresponding department doctor to take a doctor to the patient before following the ambulance after finishing the triage process, meanwhile, the customer service system can directly inform the emergency department of preparing an emergency room and summon the on-duty doctor of the corresponding department to go to the emergency room for emergency treatment and consultation;
s2, the emergency ambulance is connected to the patient' S heel car, and the doctor carries out the primary emergency treatment on the emergency ambulance;
s3, the emergency department doctor and the consultation doctor carry out emergency treatment after the patient enters the emergency room;
s4, completing first aid, after the vital signs of the patient are recovered to be normal and the personal cognitive ability can be recovered, after the inquiry and corresponding detection are completed, the doctor fills in an electronic medical record, gives out a plurality of treatment schemes and enters a customer service system to be kept, an AI big data analysis component in the customer service system retrieves the treatment schemes, then retrieves the types of medicines and treatment means in the database, calculates the total amount and the detailed cost of the patient in the treatment schemes through a pricing table in the retrieval database, then sends the total amount and the detailed cost to a financial processing module, generates a quotation and sends the quotation to the patient, the patient selects and confirms the quotation by himself and then feeds the quotation back to the doctor terminal through the customer service system, and the doctor prints the generated quotation and sends the treatment schemes to a pharmacy and a dwelling;
s5, after the patient finishes payment, the customer service system lists the treatment plan of the patient in a confirmation execution list and specifies a hospital bed, a pre-handling admission procedure and a dispatching management bed physician, the pharmacy distributes the medicine amount and a medicine taking time axis according to the treatment steps in the treatment plan in the confirmation execution list, and sends the first course of medicine to the department of the hospital and the corresponding management bed physician signs and confirms taking over;
s6, because the hospital bed is pre-designated and the admission procedures are pre-handled in S5, the patient can go directly to the hospital department to enter the hospital, and meanwhile, the first course of treatment of the medicine is taken in advance by the tube bed physician and the nurse in the ward corresponding to the bed, and the patient can directly start the treatment work after entering the hospital;
s7, the customer service system comprises a preset patient appeal feedback assembly, the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, a drug adverse reaction feedback module, a life appeal feedback module and an emergency feedback module, the hospitalization appeal feedback module is connected with a hospital entrance port, the treatment effect feedback module is connected with a tube bed doctor port and an attending doctor port, the drug adverse reaction feedback module is connected with a pharmacy port, the attending doctor port and a tube bed doctor port, the life appeal feedback module is connected with a ward nurse station port, and the emergency feedback module is connected with a ward nurse station port, an emergency room port, a tube bed doctor port and an attending doctor port;
and S8, after the single-stage treatment is completed, the financial processing module generates an electronic invoice and provides a customer service system to send the electronic invoice to the patient, and the patient selects the electronic invoice or mails a paper invoice through the financial processing module.
The embodiment has the advantages that the quick treatment and quick treatment of the emergency and serious trauma patients can be realized, the waiting period in the turnover link of the emergency patients is completely cancelled, and meanwhile, due to the existence of the preliminary triage of the emergency, if the hospital does not have the treatment conditions at present, the hospital can provide the preliminary emergency treatment and allocate the medical resources of other hospitals in time, so that the survival rate of the emergency and serious trauma patients is effectively improved.
Example 3: an intelligent customer service system for inpatients, comprising the steps of:
s1, a database is built in advance, department and physician name lists of a hospital and electronic medical records of a patient in a current period are recorded, an AI big data analysis component is configured in the database, symptom description and pathological classification in the electronic medical records are captured and summarized into a form corresponding to symptom representation and symptom department pre-diagnosis, the patient logs in a customer service system before hospitalizing, the chief complaint symptom and the preset hospitalizing time of the patient are recorded, keywords in the chief complaint symptom are captured by the system, and the keyword is compared in the form corresponding to the symptom representation and the symptom department pre-diagnosis through the AI big data analysis component to finish the diagnosis department pre-diagnosis classification of the patient;
s2, after the pre-diagnosis is finished, doctors with corresponding dates for sitting diagnosis are screened according to the scheduled hospitalizing time of the patient, the doctor list with vacant numbers is classified into a common number and an expert number, and a classification form with registration cost is generated and sent to the patient;
s3, selecting a proper doctor for online registration according to the requirement of the patient;
s4, when the patient goes to a hospital to see a doctor on the day of the scheduled date, after the doctor finishes the inquiry and corresponding detection, the doctor fills in an electronic medical record, gives out a plurality of treatment schemes and enters a customer service system to keep a file, an AI big data analysis component in the customer service system retrieves the database type medicines and treatment means types after obtaining the treatment schemes, calculates the total amount and the detail of the cost of the patient in the treatment schemes through a pricing table in the retrieval database, sends the total amount and the detail of the cost to a financial processing module, generates a quotation and sends the quotation to the patient, the patient selects and confirms the quotation by himself and then feeds the quotation back to the doctor terminal through the customer service system, and the doctor prints the generated quotation and sends the treatment schemes to a pharmacy and;
s5, after the patient finishes payment, the customer service system lists the treatment plan of the patient in a confirmation execution list and specifies a hospital bed, a pre-handling admission procedure and a dispatching management bed physician, the pharmacy distributes the medicine amount and a medicine taking time axis according to the treatment steps in the treatment plan in the confirmation execution list, and sends the first course of medicine to the department of the hospital and the corresponding management bed physician signs and confirms taking over;
s6, because the hospital bed is pre-designated and the admission procedures are pre-handled in S5, the patient can go directly to the hospital department to enter the hospital, and meanwhile, the first course of treatment of the medicine is taken in advance by the tube bed physician and the nurse in the ward corresponding to the bed, and the patient can directly start the treatment work after entering the hospital;
s7, the customer service system comprises a preset patient appeal feedback assembly, the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, a drug adverse reaction feedback module, a life appeal feedback module and an emergency feedback module, the hospitalization appeal feedback module is connected with a hospital resident port, the treatment effect feedback module is connected with a tube bed doctor port and a main doctor port, the drug adverse reaction feedback module is connected with a pharmacy port, a main doctor port and a tube bed doctor port, the life appeal feedback module is connected with a ward nurse station port, the emergency feedback module is connected with a ward nurse station port, an emergency room port, a tube bed doctor port and a main doctor port, the hospital resident hospital port, the main doctor port and the tube bed doctor port are also reversely connected to the patient appeal feedback assembly, and the medication condition of the patient is uploaded through the patient appeal feedback assembly every day, The patient can learn the treatment progress of the patient in real time through the patient appeal feedback component;
s8, after the single-stage treatment is completed, the financial processing module generates an electronic invoice and provides a customer service system to send the electronic invoice to a patient, the patient selects the electronic invoice or mails a paper invoice through the financial processing module, meanwhile, the customer service system sends the updated electronic medical record of the current stage to the patient, and the patient selects the electronic medical record or mails a paper medical record copy through the customer service system.
In actual operation, known and common disease types in the existing medical knowledge are recorded during prestoring of a database, obvious external symptoms of each disease are recorded, then various diseases and corresponding symptoms are classified according to departments, the symptoms are used as index items for department classification, after the symptoms are recorded by online pre-diagnosis of a patient, AI analysis is used for grabbing key words to search corresponding symptom index items in a contrast mode, and the corresponding departments for patient triage are obtained according to feedback search data. AI analysis captures keywords such as "cold: the data is matched with the input of a user and returned to the most relevant diseases and departments of the user, the data is in json format, then the marked disease description data is taken out from a database, description keywords of each disease are converted into vectors, and the vectors have the meaning of expressing one disease and are embedding the disease description.
The technical advantage of the technical scheme is that the patient can know the treatment state of the patient in real time, so that the anxiety of the patient can be effectively relieved, communication and cooperation among doctors and patients are facilitated, and the rehabilitation process of the patient is facilitated.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (5)
1. The utility model provides an intelligence customer service system to inpatient which characterized in that: the method comprises the following steps:
s1, a database is built in advance, department and physician name lists of a hospital and electronic medical records of a patient in a current period are recorded, an AI big data analysis component is configured in the database, symptom description and pathological classification in the electronic medical records are captured and summarized into a form corresponding to symptom representation and symptom department pre-diagnosis, the patient logs in a customer service system before hospitalizing, the chief complaint symptom and the preset hospitalizing time of the patient are recorded, keywords in the chief complaint symptom are captured by the system, and the keyword is compared in the form corresponding to the symptom representation and the symptom department pre-diagnosis through the AI big data analysis component to finish the diagnosis department pre-diagnosis classification of the patient;
s2, after the pre-diagnosis is finished, doctors with corresponding dates for sitting diagnosis are screened according to the scheduled hospitalizing time of the patient, the doctor list with vacant numbers is classified into a common number and an expert number, and a classification form with registration cost is generated and sent to the patient;
s3, selecting a proper doctor for online registration according to the requirement of the patient;
s4, when the patient goes to a hospital to see a doctor on the day of the scheduled date, after the doctor finishes the inquiry and corresponding detection, the doctor fills in an electronic medical record, gives out a plurality of treatment schemes and enters a customer service system to keep a file, an AI big data analysis component in the customer service system retrieves the database type medicines and treatment means types after obtaining the treatment schemes, calculates the total amount and the detail of the cost of the patient in the treatment schemes through a pricing table in the retrieval database, sends the total amount and the detail of the cost to a financial processing module, generates a quotation and sends the quotation to the patient, the patient selects and confirms the quotation by himself and then feeds the quotation back to the doctor terminal through the customer service system, and the doctor prints the generated quotation and sends the treatment schemes to a pharmacy and;
s5, the patient directly pays in line after obtaining the determined treatment and medication scheme, the customer service system after paying puts the treatment plan of the patient in a confirmation execution list and designates a hospital bed, a pre-handling admission procedure and a management bed assignment physician, the pharmacy distributes the medicine amount and a medicine taking time axis according to the treatment steps in the treatment plan in the confirmation execution list, and sends the first treatment course medicine to the department of the hospital and the corresponding management bed physician signs to confirm taking over;
s6, because the hospital bed is pre-designated and the admission procedures are pre-handled in S5, the patient can go directly to the hospital department to enter the hospital, and meanwhile, the first course of treatment of the medicine is taken in advance by the tube bed physician and the nurse in the ward corresponding to the bed, and the patient can directly start the treatment work after entering the hospital;
s7, the customer service system comprises a preset patient appeal feedback assembly, the patient appeal feedback assembly comprises a hospitalization appeal feedback module, a treatment effect feedback module, a drug adverse reaction feedback module, a life appeal feedback module and an emergency feedback module, the hospitalization appeal feedback module is connected with a hospital entrance port, the treatment effect feedback module is connected with a tube bed doctor port and an attending doctor port, the drug adverse reaction feedback module is connected with a pharmacy port, the attending doctor port and a tube bed doctor port, the life appeal feedback module is connected with a ward nurse station port, and the emergency feedback module is connected with a ward nurse station port, an emergency room port, a tube bed doctor port and an attending doctor port;
and S8, after the single-stage treatment is completed, the financial processing module generates an electronic invoice and provides a customer service system to send the electronic invoice to the patient, and the patient selects the electronic invoice or mails a paper invoice through the financial processing module.
2. An intelligent customer service system for inpatients according to claim 1, characterized in that: the patient in the S1 is a sudden emergency and serious trauma patient, after the chief complaint symptom and the emergency call are recorded, the customer service system directly assigns a corresponding department doctor to take a treatment to the patient along with the front of the ambulance after completing the triage process, and simultaneously, the customer service system directly informs the emergency department to prepare an emergency room and calls the on-duty doctor of the corresponding department to go to the emergency room for emergency treatment and consultation.
3. An intelligent customer service system for inpatients according to claim 1, characterized in that: and S8, after the single-stage treatment is completed, the customer service system sends the updated electronic medical records of the current stage to the patient, and the patient selects the electronic medical records or mails the paper medical record copies through the customer service system.
4. An intelligent customer service system for inpatients according to claim 1, characterized in that: and in the S7, the hospital staying port, the main doctor port and the tube bed doctor port are also reversely connected to the patient appeal feedback assembly, the medication condition, the biochemical detection index and the rehabilitation state of the patient are uploaded through the patient appeal feedback assembly every day, and the patient can know the treatment progress of the patient in real time through the patient appeal feedback assembly.
5. An intelligent customer service system for inpatients according to claim 1, characterized in that: s5, the pharmacy sends the first course of medicine to the department of living, and the first course of medicine is signed by the corresponding tube bed physician to confirm taking over, and after the medicine transfer and taking over of a plurality of subsequent batches are completed and confirmed in two ways by the pharmacy and the tube bed physician, the responsible persons of the corresponding batch of medicine are transferred in the customer service system and marked under the name of the tube bed physician.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107526934A (en) * | 2017-09-06 | 2017-12-29 | 青海大学附属医院 | A kind of medical service system |
| CN109585028A (en) * | 2018-11-29 | 2019-04-05 | 周立广 | A kind of intelligent analysis system and application method of medical treatment big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107526934A (en) * | 2017-09-06 | 2017-12-29 | 青海大学附属医院 | A kind of medical service system |
| CN109585028A (en) * | 2018-11-29 | 2019-04-05 | 周立广 | A kind of intelligent analysis system and application method of medical treatment big data |
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