CN109360621B - NLP-based prescription drug compliance management method and management system - Google Patents
NLP-based prescription drug compliance management method and management system Download PDFInfo
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- G—PHYSICS
- 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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- G—PHYSICS
- 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
- G16H70/00—ICT specially adapted for the handling or processing of medical references
- G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
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- G—PHYSICS
- 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
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
Abstract
The invention discloses a prescription drug compliance management method and a management system based on NLP, wherein the management method comprises the following steps: s1, obtaining user information of a patient and prescription and/or medical advice information; s2, initiating an artificial intelligent telephone to the patient according to the user information of the patient; s3, responding to the fact that the patient is connected with the artificial intelligent telephone, inquiring whether the patient follows a prescription and/or medical advice treatment, and if yes, executing S4; s4, inquiring whether the patient has adverse drug reactions, and if not, executing S5; and S5, repeatedly executing S2-S3 after the preset time is reached. The invention is based on natural language processing technology, carries out voice interaction with the patient or the contact person thereof, analyzes the feedback, can clearly know the key reason influencing the treatment compliance of the patient, screens the problem of the feedback of the patient, generates a report and sends the report to the attending doctor.
Description
Technical Field
The invention relates to the field of medical health systems, in particular to a prescription drug compliance management method and a management system based on NLP.
Background
The issue of patient compliance has been a problem in the medical field worldwide. "medication compliance" refers to the consistency of patient medication with the physician's prescription and order, whereas from a medication therapy perspective, medication compliance refers to the extent to which a patient has performed a medication therapy regimen. The drug compliance is directly related to the effect of disease treatment, such as hypoglycemic drugs, anticoagulant drugs and the like, and the missed or repeated administration of the drugs can cause serious reactions even endangering the life of a patient. However, the current status of drug compliance in China is great, and the main reasons for poor drug compliance of patients are as follows:
first, memory decline: most of patients with chronic diseases who need to take the medicine for a long time are old people, and the condition of memory deterioration is obvious, so that the condition of missed taking or repeated taking of the medicine is easy to occur;
secondly, irregular life: middle-aged and teenager patients often cause non-compliance of medication due to large working and learning pressure, irregular life and other reasons, especially some special employees such as frequent-going personnel, field workers, drivers, students and the like, and are very easy to forget to take medicine on time due to frequent change of living environment, large learning or working pressure and busy work;
third, too high a therapeutic expectation: because patients feel very painful, the expectation on the treatment of the medicines is very high, and the treatment effect of the medicines is required to be quick, so that some patients have great proficiency in increasing the dosage of the medicines, increasing the taking times or increasing the varieties of the treatment medicines, and the adverse reaction of the medicines is increased or even serious adverse reaction events are caused;
fourth, medical knowledge and consciousness insufficiency: the patient does not know the medical knowledge, listens and says or understands the side effects of the medicines in the specification one by one, so that the patient has psychological resistance to taking and injecting the medicines, especially has excessive worry about the side effects of the medicines, and the patient does not follow the prescription and advice of a doctor to carry out medicine treatment and is free from stopping the medicine or reducing the dosage;
fifth, medical personnel lack effective communication with the patient: due to the lack of manpower of medical care personnel and professional pharmacists, the patient lacks effective communication, and the patient cannot clearly take the medicine. In particular, pharmacists have long targeted the main tasks of providing patients with safe, effective, accurate and error-free medicines, and have not paid attention to providing relevant information of medicines and lacked medication guidance for patients. The prescription management method provides that when the medicine is delivered to the patient, medication delivery and guidance including the usage, dosage, cautionary matters and the like of each medicine are carried out according to the medicine instruction or the prescription usage. However, in actual work, pharmacists only pay attention to whether the drugs are correctly dispensed, and often neglect medication delivery, thereby affecting the drug compliance of patients.
In conclusion, the factors influencing the compliance of the medicine are numerous and relate to patients, medical staff, society, families and the like. To solve this problem, the traditional solution relies on doctors, nurses, pharmacists to explain the prescriptions and orders of patients, and to learn the compliance of the medication by means of regular manual telephone communication or the patient's arrival at the hospital for a follow-up visit, and to educate and intervene the patients who are not compliant. However, the method has extremely high requirements on manpower, and is difficult to be widely applied in a real environment with serious shortage of manpower.
Disclosure of Invention
In order to solve the problems of the prior art, the invention provides a prescription drug compliance management method and a management system based on NLP (non line of sight), which help business personnel to quickly and accurately locate information to be found from mass data of a data warehouse through semantic search based on natural language, and the technical scheme is as follows:
in one aspect, the present invention provides a method for managing compliance with prescribed medications based on NLP, comprising:
s1, obtaining user information of a patient and prescription and/or medical order information;
s2, initiating an artificial intelligent telephone to the patient according to the user information of the patient;
s3, responding to the fact that the patient is connected with the artificial intelligent telephone, inquiring whether the patient follows a prescription and/or medical advice treatment, and if yes, executing S4;
s4, inquiring whether the patient has adverse drug reactions, and if not, executing S5;
and S5, repeatedly executing S2-S3 after the preset time is reached.
Further, inquiring whether the patient has the adverse drug reaction in S4, and if so, executing S6;
s6, evaluating whether intervention or prescription adjustment is needed, if not, executing S5, wherein the evaluation process comprises the following steps: the patient presents a symptom statement associated with the adverse drug reaction, the assessment result is that intervention or prescription adjustment is required, otherwise the assessment result is that intervention or prescription adjustment is not required.
Further, in S6, it is evaluated whether intervention or prescription adjustment is required, and if so, S7 is executed;
and S7, generating a reminding message to the attending doctor, wherein the reminding message comprises the identity of the patient, prescription and/or medical advice information, the symptom description of the adverse drug reactions proposed by the patient and the condition that the patient follows the prescription and/or medical advice for treatment.
Further, in S3 the patient is asked whether the prescription and/or the prescribed treatment is to be complied with, if not, S8 and S9 are performed;
s8, inquiring the reason why the patient does not follow the prescription and/or order for treatment;
s9, obtaining feedback of the patient, judging whether the feedback of the patient can be answered or not, and if the feedback of the patient cannot be answered, executing S6; determining whether the patient's feedback can be answered comprises: analyzing whether the patient provides instructions related to the treatment plan, and if so, judging that the feedback of the patient is not solvable.
Further, it is determined in S9 whether the feedback of the patient is solvable, and if yes, S10 and S11 are performed;
s10, obtaining a solution matched with the feedback of the patient from a pre-established knowledge base;
and S11, inquiring whether the patient receives the solution or not, and if so, executing S6.
Further, the patient is asked whether to receive the solution in S11, and if not, S8 and S9 are executed.
Further, before obtaining the user information of the patient and the prescription and/or medical order information in S1, the method further includes:
the method comprises the steps of pre-recording user information of a patient and prescription and/or medical order information of the patient in a system database, wherein the user information of the patient comprises a contact telephone.
Further, before executing S5, the method further includes: a record of the patient's treatment is generated.
On the other hand, the invention also provides a prescription drug compliance management system based on NLP, which comprises a server, a database and an artificial intelligent telephone module integrated with the natural language processing module and the knowledge base module, wherein the database and the artificial intelligent telephone module are both connected with the server;
the database is used for establishing a medical record, and the medical record comprises user information of a patient and prescription and/or medical order information of the patient;
the knowledge base is used for establishing a question base, and the question base comprises answers matched with the feedback questions;
the natural language processing module is used for analyzing and identifying feedback semantics of the patient by using a natural language processing technology in an artificial intelligent telephone call initiated to the patient.
Further, the system also includes one or more doctor clients communicatively connected to the server.
The technical scheme provided by the invention has the following beneficial effects:
a. by adopting an active voice calling technology, the voice calling is actively carried out on the patient and the contact person thereof, and the management effect on the patient with low treatment adaptability is better;
b. the system based on natural language processing can collect and analyze the feedback of the patient in a large scale, and can clearly know key reasons and factors influencing the treatment compliance of the patient through analysis, so that doctors can intervene or adjust treatment schemes in a targeted manner;
c. the system based on natural language processing performs voice interaction with a patient or a contact person of the patient, analyzes feedback, screens problems, generates a report and sends the report to a main doctor, replaces a mode of depending on manpower in the prior art solution, obviously improves efficiency and reduces cost;
d. the system based on natural language processing has the advantages that the patient or the contact person does not need to learn how to operate, extra equipment purchasing and the like, and compared with the existing solution, the system is low in use threshold and more convenient to popularize.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a NLP-based prescription medication compliance management method provided by an embodiment of the present invention;
fig. 2 is a block diagram of a NLP-based prescription medication compliance management system provided by an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
It is noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present invention, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In one embodiment of the present invention, there is provided a NLP-based prescription medication compliance management method, see fig. 1, comprising the following process:
s1, obtaining user information of a patient and prescription and/or medical order information.
The basis of the medication adherence management method/system of the present invention is the prescription and/or order prescribed by the patient's attending physician. Prescriptions and orders generally include: the name of the drug (including its generic or trade name), the method of use of the drug (e.g., the period of use, dosage, route of administration (oral, injectable, topical, etc.) of the drug), the precautions for use of the drug (e.g., possible side effects of the drug, contraindications for use of the drug in combination with other drugs, etc.), lifestyle and precautions (e.g., limiting salt intake, sugar intake, etc., such as smoking cessation, alcohol withdrawal, etc., such as regular exercise, etc.), and other activities prescribed and prescribed by the patient to be performed.
The manner in which the prescription and/or medical order is obtained is as follows: the patient can input the prescription and/or medical order which is provided by the main doctor for the patient in the system by himself or the prescription and/or medical order which is provided by the patient who has made a diagnosis for himself or herself in the system by other personnel such as the doctor himself or an authorized nurse, preferably, the user information of the patient and the prescription and/or medical order information of the patient are pre-recorded in the system database, the user information of the patient comprises a contact telephone, and then the prescription and/or medical order of the patient is directly derived from the database.
And S2, initiating an artificial intelligent telephone to the patient according to the user information of the patient.
After the prescription or the medical order of the patient is obtained, the system calls the telephone of the patient or the contact person of the patient, realizes the voice communication interaction between the computer and the patient through an artificial intelligent natural language processing technology, inquires the patient or the contact person of the patient for questions, records feedback content according to the voice feedback of the patient or the contact person of the patient, and performs voice feedback. In the prior art, there is an internet application such as WeChat/APP to remind the message, but this kind of mode needs to set up the warning of taking medicine at WeChat or APP, register patient's the time point of taking medicine and medicine cycle by patient or family members, the software program carries out the alarm clock according to the medicine taking time of setting for, weChat, APP information or SMS remind to take medicine, and because old patient uses the smart mobile phone rate low, a lot of old people can not use, the study difficulty, it is high to use the threshold, and still rely on the patient to know including setting up the action of taking medicine and reminding, if the patient can not or unwilling to set up, still can't effectively reach the target of managing the medicine compliance.
And S3, responding to the fact that the patient connects the artificial intelligent telephone, inquiring whether the patient follows the prescription and/or the medical order treatment, if yes, executing S4, and if not, executing S8 and S9.
Specifically, querying the patient for compliance with the prescription and/or order treatment includes:
inquiring whether to use the medicine prescribed in the prescription or the medical order according to the prescription and/or the medical order;
inquiring whether the period \ dosage \ method for using the medicine is consistent with the prescription or the medical order according to the prescription and/or the medical order;
inquiring whether other medicines are used simultaneously during the period of using the medicines according to the prescription and/or the order;
inquiring whether to perform diet control, exercise rehabilitation and the like according to the prescription and/or the medical order.
If the patient does not follow one or more of the prescription and/or medical order, S8 is entered, and if the prescription and/or medical order is fully complied with S4 is entered.
And S4, inquiring whether the patient has the adverse drug reaction, if not, executing S5, and if so, executing S6.
Specifically, the patients are asked whether adverse reactions caused by the drugs exist, and the adverse reactions can be exemplified by referring to common adverse reactions in the drug instruction in the inquiry process.
And S5, repeatedly executing S2-S3 after the preset time is reached.
If the compliance of the treatment is good, no possible adverse reaction is fed back, the patient can enter S2 again according to the prescription and/or the doctor' S order and the preset interval time, the patient is called by using an artificial intelligent telephone regularly, and the specific period of the communication with the telephone again is set and adjusted according to the disease of the patient, the quality scheme, the patient himself or the requirements of the attending doctor.
And S6, evaluating whether the prescription needs to be intervened or adjusted, if so, executing S7, and if not, executing S5.
According to the voice feedback of the patient or the contact person thereof in the previous step, the system carries out voice analysis, and according to the content of the feedback, the system judges whether the treatment compliance or the treatment scheme thereof needs to be intervened or adjusted by a doctor or not according to the prescription and/or the medical order of the patient and whether the patient feeds back the possible adverse reaction, and the judgment standard comprises the following steps:
inquiring whether a patient himself carries out a treatment scheme and a life style according to a prescription and/or a medical order, if the patient himself uses the medicine on time, and if the patient himself puts forward problems related to the prescription and/or the medical order, such as discomfort after taking the medicine, if the patient himself puts forward a symptom description related to the adverse drug reaction (the patient actively puts forward the description of the adverse drug reaction, which is a main basis for obtaining an evaluation result needing intervention), the evaluation result is that the prescription needs to be intervened or adjusted, otherwise, the evaluation result is that the prescription does not need to be intervened or adjusted.
And S7, generating a reminding message to the attending doctor, wherein the reminding message comprises the identity of the patient, prescription and/or medical advice information, the symptom description of the adverse drug reactions proposed by the patient and the condition that the patient follows the prescription and/or medical advice for treatment.
And S6, if the system judges that the treatment compliance of the patient needs to be intervened by the attending doctor, the system records the feedback of the patient or the contact person thereof, generates a key attention reminding report (electronic document) and sends the key attention reminding report to the attending doctor of the patient recorded in the system.
S8, inquiring the reason why the patient does not follow the prescription and/or order for treatment.
Specifically, the system asks the patient or his contacts by voice for the reason why the prescription or order was not performed.
S9, obtaining feedback of the patient, judging whether the feedback of the patient can be answered or not, if not, executing S6, and if so, executing S10 and S11.
After the system voice inquiry, the voice feedback of the patient or the contact person is recorded and analyzed, and whether the feedback can be solved or given guidance by the system is judged, wherein the judgment standard is as follows:
the process of determining whether the patient's feedback can be answered comprises: analyzing whether the feedback of the patient is related to the subjective will of the patient, such as not wanting to take a medicine, not wanting to limit salt or sugar intake, etc., and judging that the feedback of the patient or the contact person is that the system can answer, the step goes to S10. Otherwise, the patient is analyzed whether to provide instructions related to the treatment regimen, i.e. whether the disease diagnosis is related to the treatment regimen itself, such as possible adverse drug reactions, ineffective treatment regimen, disease progression or occurrence of other symptoms, and if so, the feedback of the patient is judged to be unresolvable, and S6 is entered.
And S10, obtaining a solution matched with the feedback of the patient from a pre-established knowledge base.
If the system can answer the question according to the judgment of S9, the step 10 is entered, the system reminds, educates and answers the question by voice according to the feedback of the patient or the contact person of the patient, and the step 11 is entered after the completion.
And S11, inquiring whether the patient receives the answer or not, if so, executing S6, and if not, executing S8 and S9.
In a preferred embodiment of the present invention, before performing S5, the method further includes: and (3) generating a record of the treatment condition of the patient, specifically, recording the time and content of telephone voice communication, recording the communication content in the system in an electronic text form, and generating a record of the treatment compliance of the patient.
In another aspect, the present invention further provides a NLP-based prescription medication compliance management system, referring to fig. 2, the system includes a server, a database, and an artificial intelligence phone module integrated with the server, wherein the artificial intelligence phone module includes a natural language processing module and a knowledge base module, and the database and the artificial intelligence phone module are both connected to the server;
the database is used for establishing a medical record, and comprises user information of a patient and prescription and/or medical order information of the patient;
the knowledge base is used for establishing a question base, and the question base comprises answers matched with the feedback questions;
the natural language processing module is used for analyzing and identifying feedback semantics of the patient by using a natural language processing technology in an artificial intelligent telephone call initiated to the patient.
Preferably, the system further comprises one or more doctor clients communicatively connected to the server.
The operation process of the prescription medication compliance management system based on NLP provided in the embodiment of the present invention refers to the prescription medication compliance management method based on NLP provided in the above embodiment, and the operation process is not repeated in this system embodiment.
The invention actively initiates a medicine compliance inquiry call to the patient based on a mature NLP technology, is not limited to a smart phone client, analyzes feedback through voice interaction with the patient or a contact person thereof, screens problems, generates a report and sends the report to an attending doctor, relieves the pressure of shortage of medical manpower resources, is beneficial to improving the medicine compliance of the patient, and thus improves the medicine treatment effect.
It will be apparent to those skilled in the art that various changes and modifications may be made in the invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.
Claims (9)
1. A NLP-based prescription medication adherence management method, comprising:
s1, obtaining user information of a patient and prescription and/or medical advice information;
s2, initiating an artificial intelligent telephone to the patient according to the user information of the patient;
s3, responding to the fact that the patient connects the artificial intelligent telephone, inquiring whether the patient follows a prescription and/or medical advice treatment, and if yes, executing S4;
s4, inquiring whether the patient has adverse drug reactions, and if not, executing S5; s5, after the preset time is reached, repeatedly executing S2-S3; if the drug has adverse reaction, executing S6;
s6, evaluating whether intervention or prescription adjustment is needed, if not, executing S5, wherein the evaluation process comprises the following steps: the patient proposes a symptom instruction related to the adverse drug reaction, the evaluation result is that intervention or prescription adjustment is needed, and S7 is executed;
s7, sending a reminding message to a doctor client of a main doctor, wherein the reminding message comprises patient identity, prescription and/or medical advice information, symptom description of adverse drug reactions proposed by the patient and patient compliance with the prescription and/or medical advice treatment conditions, and the doctor passively receives the reminding message without actively initiating inquiry to the patient; and then the doctor intervenes or adjusts the treatment scheme according to the passively received reminding message.
2. The NLP-based prescription medication adherence management method according to claim 1, wherein if the patient does not present symptom explanation related to adverse drug reaction in step S6, the result of the evaluation is that no intervention or prescription adjustment is required.
3. The NLP-based prescription medication adherence management method according to claim 1, wherein the patient is asked in S3 whether to comply with the prescription and/or the medical order treatment, if not, S8 and S9 are executed;
s8, inquiring the reason why the patient does not follow the prescription and/or order for treatment;
s9, obtaining feedback of a patient, judging whether the feedback of the patient can be answered or not, and if the feedback of the patient cannot be answered, executing S6; determining whether the patient's feedback can be answered comprises: analyzing whether the patient provides instructions related to the treatment plan, and if so, judging that the feedback of the patient is not solvable.
4. The NLP-based prescription medication adherence management method of claim 3, wherein in S9 it is judged whether the feedback of the patient is solvable, if yes, S10 and S11 are performed;
s10, obtaining a solution matched with the feedback of the patient from a pre-established knowledge base;
and S11, inquiring whether the patient receives the solution or not, and if so, executing S6.
5. The NLP-based prescription medication adherence management method of claim 4, wherein the patient is asked whether to accept the solution in S11, and if not, S8 and S9 are performed.
6. The NLP-based prescription medication adherence management method according to claim 1, wherein the obtaining of the user information of the patient and the prescription and/or order information in S1 further comprises:
the method comprises the steps of pre-recording user information of a patient and prescription and/or medical order information of the patient in a system database, wherein the user information of the patient comprises a contact telephone.
7. The NLP-based prescription medication adherence management method of claim 2, further comprising before executing S5: a record of the patient's treatment is generated.
8. An NLP-based prescription drug compliance management system is characterized by comprising a server, a database and an artificial intelligent telephone module integrated with the natural language processing module and the knowledge base module, wherein the database and the artificial intelligent telephone module are both connected with the server;
the database is used for establishing a medical record, and comprises user information of a patient and prescription and/or medical order information of the patient;
the knowledge base is used for establishing a question base, and the question base comprises answers matched with the feedback questions;
the natural language processing module is used for analyzing and identifying feedback semantics of a patient by using a natural language processing technology in an artificial intelligent telephone call initiated to the patient so as to evaluate whether the prescription needs to be intervened or adjusted, if the prescription needs to be intervened or adjusted, a reminding message is sent to a doctor client of a main doctor, the reminding message comprises patient identity, prescription and/or medical advice information, symptom description of adverse drug reactions proposed by the patient and treatment conditions of compliance of the patient with the prescription and/or medical advice, and the doctor passively receives the reminding message without actively initiating inquiry to the patient; so that the doctor can intervene or adjust the treatment plan according to the passively received reminding message.
9. The NLP-based prescription medication adherence management system of claim 8, further comprising one or more doctor clients communicatively connected with the server.
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