CN117238440A - Intelligent medicine distribution system and method - Google Patents
Intelligent medicine distribution system and method Download PDFInfo
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Abstract
The application provides an intelligent medicine distribution system and method, and relates to the technical field of medicine distribution of doctors and patients. Through remote on-line inquiry at the patient end and remote on-line diagnosis at the doctor end, the doctor end sets up an electronic prescription according to a diagnosis result, carries out intelligent examination on the electronic prescription, distributes the examined electronic prescription to corresponding pharmacy for dispensing, distributes and tracks the prepared medicine, can meet the remote at-home medicine taking requirement of the patient, improves medicine distribution speed and efficiency, reasonably distributes resources and reduces the hospital doctor pressure. The intelligent medicine distribution system and the intelligent medicine distribution method can enable hospitals to timely master the medicine effect of home patients through feedback, evaluation or re-diagnosis after inquiry and medicine dispensing of the patients, quickly and accurately master the recovery condition of the patients after diagnosis, and improve the satisfaction degree of the patients.
Description
Technical Field
The application relates to the technical field of medicine distribution, in particular to an intelligent medicine distribution system and method.
Background
The traditional medicine taking mode mainly comprises the steps that after a patient is in a hospital and is subjected to doctor treatment, the doctor issues an electronic bill of medicine prescription, and a hospital pharmacy accepts and checks and passes. After the patient pays at the pharmacy, the patient queues up for taking the medicine at the pharmacy window. There are some obvious problems with this approach: patients need to visit the hospital personally and queue to take medicine, which is inconvenient for most patients, especially for the old and the weak chronic patients. In addition, the medical effect of most home patients after diagnosis cannot be accurately mastered in time by hospital doctors, so that the recovery condition of the home patients cannot be tracked.
Based on this, the present application has been proposed.
Disclosure of Invention
The application aims to provide an intelligent medicine distribution system and method, which are used for meeting the requirements of patients on remote home visit and medicine taking and improving medicine distribution speed and efficiency.
In order to achieve the above purpose, the present application provides the following technical solutions:
the application provides an intelligent medicine distribution system in a first aspect, which comprises a consultation subsystem, a first intelligent medicine distribution subsystem and a second intelligent medicine distribution subsystem, wherein the consultation subsystem is used for remote online consultation at a patient end and remote online diagnosis at a doctor end;
the prescription subsystem is used for opening an electronic prescription according to the diagnosis result by a doctor end and intelligently auditing the electronic prescription;
a pharmacy subsystem for assigning audited electronic prescriptions to corresponding pharmacy prescriptions;
the delivery subsystem is used for delivering and tracking the prepared medicines;
and the re-diagnosis subsystem is used for feeding back, evaluating or re-diagnosing after the patient inquires and dispenses.
The present application provides in a second aspect a method of intelligent drug delivery, comprising:
remote on-line inquiry at the patient end and remote on-line diagnosis at the doctor end;
the doctor end opens an electronic prescription according to the diagnosis result and intelligently checks the electronic prescription;
assigning the electronic prescriptions which pass the verification to corresponding pharmacy for dispensing;
distributing and tracking the prepared medicines;
the patient is fed back, evaluated or re-diagnosed after the inquiry and dosage.
Compared with the prior art, the technical scheme has the following advantages:
(1) According to the intelligent medicine distribution system and method, through remote online consultation at the patient end and remote online diagnosis at the doctor end, the doctor end sets up an electronic prescription according to a diagnosis result, intelligently reviews the electronic prescription, distributes the electronic prescription which passes the examination to a corresponding pharmacy for dispensing, distributes and tracks the prepared medicine, can meet the remote medicine taking requirement of the patient in home, improves the medicine distribution speed and efficiency, reasonably distributes resources and reduces the pressure of hospital consultation.
(2) The intelligent medicine distribution system and the intelligent medicine distribution method can enable hospitals to timely master the medicine effect of home patients through feedback, evaluation or re-diagnosis after inquiry and medicine dispensing of the patients, quickly and accurately master the recovery condition of the patients after diagnosis, and improve the satisfaction degree of the patients.
(3) According to the intelligent medicine distribution system and method, a patient carries out online consultation, a doctor issues a prescription online, the doctor checks and passes the prescription, automatic dispensing is carried out, and the patient is distributed through block chain logistics.
(4) The intelligent medicine distribution system and method provided by the application have the advantages that the patient tracks the medicine dispensing and delivering process in the whole course;
(5) The intelligent medicine distribution system and method of the application track the quality of medicines and ensure the medication safety.
(6) According to the intelligent medicine distribution system and method, through feedback information of the medicine effect of the patient, the system identifies the patient with unsatisfactory medicine effect and prompts the specialist to carry out re-diagnosis treatment.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of a smart drug delivery system according to embodiment 1 of the present application;
FIG. 2 is a flow chart of a smart drug delivery method according to embodiment 1 of the present application;
FIG. 3 is a block diagram of a query subsystem according to embodiment 2 of the present application;
FIG. 4 is a block diagram of a prescription subsystem according to embodiment 2 of the present application;
FIG. 5 is a block diagram of a pharmacy subsystem according to embodiment 2 of the application;
FIG. 6 is a block diagram of a distribution subsystem according to embodiment 2 of the present application;
FIG. 7 is a block diagram of a review subsystem according to embodiment 2 of the present application;
FIG. 8 is a flowchart of a smart drug delivery method according to embodiment 2 of the present application;
FIG. 9 is a flowchart of the auditing of the intelligent auditing module according to embodiment 3 of the present application;
fig. 10 is a flowchart of the review subsystem of embodiment 3 of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
Referring to fig. 1, a smart medicine dispensing system of the present embodiment includes
The inquiry subsystem is used for remote online inquiry at the patient end and remote online diagnosis at the doctor end;
the prescription subsystem is used for opening an electronic prescription according to the diagnosis result by a doctor end and intelligently auditing the electronic prescription;
a pharmacy subsystem for assigning audited electronic prescriptions to corresponding pharmacy prescriptions;
the delivery subsystem is used for delivering and tracking the prepared medicines;
and the re-diagnosis subsystem is used for feeding back, evaluating or re-diagnosing after the patient inquires and dispenses.
Referring to fig. 2, a smart medicine distribution method of the present embodiment includes
Remote on-line inquiry at the patient end and remote on-line diagnosis at the doctor end;
the doctor end opens an electronic prescription according to the diagnosis result and intelligently checks the electronic prescription;
assigning the electronic prescriptions which pass the verification to corresponding pharmacy for dispensing;
distributing and tracking the prepared medicines;
the patient is fed back, evaluated or re-diagnosed after the inquiry and dosage.
Example 2
Referring to fig. 3, in an intelligent medicine distribution system of the present embodiment, a query subsystem includes
The patient end inquiry module is used for establishing personal health files for the patient, uploading symptom description texts and remotely carrying out on-line inquiry;
and the doctor end diagnosis module is used for remotely diagnosing the patient by a doctor and comprehensively diagnosing the patient description illness state, patient medical record data and detection results.
Referring to fig. 4, in a smart medicine dispensing system of the present embodiment, a prescription subsystem includes
The prescription issuing module is used for issuing an electronic prescription for the patient according to the diagnosis result by a doctor;
the intelligent auditing module is used for auditing the electronic prescription issued by the doctor; returning failed information to the electronic prescription which is failed in the verification and attaching verification comments to a prescription issuing module to require a doctor to modify the prescription;
and the electronic signature module is used for attaching an electronic signature to the electronic prescription passing the verification.
Referring to fig. 5, in an intelligent medicine distribution system of the present embodiment, a pharmacy subsystem includes
The prescription receiving and processing module is used for receiving the electronic prescriptions which pass the verification and reading information on the electronic prescriptions;
the expense settlement module is used for settling expense according to the read information of the electronic prescription;
the identification code generation module is used for generating a unique identification code for the patient end to scan and identify the cost and the patient identity information;
the payment management module is used for paying and managing the fees after the patient scanning code identification;
the address management module is used for matching and managing the addresses of the patients after the prescription cost payment of the patients is completed;
and the dispensing management module is used for dispatching the electronic prescription dispensing task list to the corresponding dispensing point.
Referring to fig. 6, in a smart medicine dispensing system of the present embodiment, the dispensing subsystem includes
The medicine delivery module is used for delivering the medicines according to the addresses of the corresponding patients after the medicines are dispensed at the corresponding dispensing points and releasing a transportation logistics bill;
the logistics transportation module is used for receiving logistics transportation bill and implementing logistics transportation task;
and the medicine tracing and tracking module is used for endowing the medicine after the medicine is dispensed with a unique tracing code and tracing the whole course.
Referring to fig. 7, in an intelligent medicine distribution system of the present embodiment, the review subsystem includes
The return visit investigation module is used for carrying out satisfaction return visit investigation on the patients after the medicine is dispensed and taken, and collecting feedback information of the patients;
the feedback information evaluation module is used for performing satisfaction evaluation on the feedback information to at least obtain two evaluation results of satisfaction and dissatisfaction;
the review queue opening module is used for forming a review request queue for the patient information with unsatisfactory evaluation results and sending the review request queue to a doctor end;
the re-diagnosis window opening module is used for informing the patient to open the remote re-diagnosis window in response to the re-diagnosis request by the doctor end and providing on-line re-diagnosis service for the patient.
Referring to fig. 8, a smart medicine distribution method of the present embodiment specifically includes:
s110, patient terminal inquiry, patient establishes personal health file, uploads symptom description text, and remote on-line inquiry. The method comprises the following steps: the remote patient logs in a hospital appointment registering system at a user side APP, establishes a personal health file and uploads a symptom description text. The personal health record at least comprises patient name, sex, age, ID card number, contact phone number, home address information, home-to-person contact information and historical disease information. The symptoms of the disease include the occurrence time, the incidence degree (such as heatstroke symptoms: general weakness, dizziness, vomiting, tinnitus, blackness of eyes), the possible cause of the disease, and the like. The patient selects the department and doctor reserves the outpatient time. The household remote patient logs in the hospital registration clinic system, and after system authentication, the intelligent medicine distribution system of the embodiment of the application is transferred.
S120, doctor end diagnosis, namely, doctor diagnosis for the patient remotely, and comprehensive diagnosis for the patient description illness state, patient medical record data and detection results. The method comprises the following steps: and the intelligent medical APP doctor end embedding module opens a remote consultation window mode according to the reserved time to diagnose the disease of the patient. The doctor firstly inquires the occurrence condition and the disease degree of the patient in detail, and if necessary, carries out remote examination, including medical technology examination and result test. In the remote mode, the doctor side recommends the patient to the medical community hospital closest to the home address or other medical institutions for medical technical examination and laboratory, and all examination data are shared by the medical community hospital. The doctor end performs comprehensive analysis, evaluation and judgment on the medical technology examination and test data.
S210, prescribing, namely prescribing the patient by a doctor according to the diagnosis result. The method comprises the following steps: after diagnosis is completed, a doctor side calls a prescription setting module in the distribution subsystem to set a prescription for a patient, wherein the content comprises the name, sex, age, identification card number, disease diagnosis information, medicine name, total amount, medicine duration, daily medicine dosage and the like of the patient. After the prescription content is completely issued, an electronic signature module is started to give an electronic signature to a doctor. And uploading the signed prescription form, and waiting for the verification of the intelligent auditing module in a data queue mode.
S220, an intelligent auditing party audits the electronic prescription issued by the doctor; and returning the failed information to the electronic prescription which is failed in the verification and attaching the verification comments to the prescription issuing step, so that a doctor is required to modify the prescription. The method comprises the following steps: the intelligent auditing module responds to an electronic prescription auditing request sent by a doctor, and examines the contents of the disease name, symptom characteristics, medicine name, total quantity, medicine duration, daily dosage and the like described by the prescription one by one. If the verification fails, the intelligent verification module sends information to the APP doctor end, and informs the verification failure information and the additional failed reason text information.
S230, the electronic signature is attached to the electronic prescription passing the verification. The method comprises the following steps: if the verification is passed, the electronic prescription list waits for the electronic signature module to electronically sign a pharmacist, and the prescription file which passes the verification and is signed is uploaded to a pharmacy subsystem to form a task request queue for requesting the dispensing treatment.
S310, receiving and processing the prescription, receiving the electronic prescription which passes the verification, and reading information on the electronic prescription. The method comprises the following steps: the server of the medicine house system responds to the request, starts the prescription receiving and processing module, reads the data such as the name, total dosage and daily dosage of the traditional Chinese medicine of the electronic prescription, links and inquires the medicine database, and inquires the medicine cost in the medicine knowledge base.
S320, fee settlement is carried out according to the read information of the electronic prescription. The method comprises the following steps: and automatically calculating the current expense data of the patient according to the read traditional Chinese medicine name and total dosage data of the electronic prescription.
S330, generating an identification code, namely generating a unique identification code by using the expense and the patient identity information for identification of the patient end scanning code. The method comprises the following steps: and reading the personal information data of the patient to form a two-dimension code for payment, wherein the two-dimension code comprises personal identity of the patient and mobile phone number information. The two-dimension code picture is transmitted to the patient end through the doctor end in a linked manner, the patient end payment request is transmitted, and meanwhile, a prompt short message is transmitted to the patient mobile phone: patient, ", hello-! Please enter the mobile phone APP terminal to pay the drug cost in time. The early recovery of health-! * Hospital.
And S340, payment management, namely, payment and management are carried out after the patient is identified by the scanning code, namely, the patient responds to the payment request and pays the fee.
S350, address management, namely matching and managing the patient addresses after the prescription charge payment of the patient is completed. The method comprises the following steps: the patient inputs a dispensing address where the medication can be received, identifies the address, stores, and even matches the dispensing point.
S410, dispensing management, namely assigning an electronic prescription dispensing task list to a corresponding dispensing point.
S510, delivering the medicine, and delivering the medicine according to the address of the corresponding patient after dispensing at the corresponding dispensing point, and releasing a transportation logistics bill.
S520, carrying out logistics transportation, accepting logistics transportation bill, and implementing logistics transportation task.
Example 3
In the smart drug delivery system of the present embodiment, the pharmacy subsystem further includes a dispensing time estimating and querying module, and in the smart drug delivery method, there are the following differences from embodiment 2:
referring to fig. 9, in the intelligent drug delivery system and method of the present embodiment, an intelligent auditor adopts a prescription artificial intelligence algorithm to audit drugs online S220. Extracting and converting the prescription text data and the health file text data of the HIS system of the hospital to form a structured prescription medical record data warehouse;
generating a prescription word vector for the structured prescription medical record data by using a word2vec algorithm;
establishing a prescription word vector model by utilizing a BiLSTM neural network, and inputting the prescription word vector into the model for training;
extracting and converting the online target prescription text and related health file text data to form structured target prescription medical record data;
generating a sentence word vector to be detected for the structured target prescription medical record data by using a word2vec algorithm;
inputting the sentence word vector to be tested into a prescription word vector model for similarity comparison, and if the similarity is greater than or equal to a set threshold value, indicating that the prescription audit is passed; if the similarity is lower than the set threshold, the prescription verification fails.
The specific method comprises the following steps:
s221, the API of the medicine delivery system is connected with the HIS system of the hospital, and the HIS system server is used for transmitting the approved prescription data to the medicine delivery system database at intervals of half an hour, wherein the satisfaction value=2, and the patient health file data is queried by the patient identity ID link. The patient health record records information such as personal health basic condition, disease history, genetic history, disease dynamics, preventive care and the like. And performing word segmentation analysis on the unstructured text of the prescription and the health file.
S222, matching the hospital medicine knowledge base with the disease knowledge base, if the problem that the medicine names and the disease names of the individual prescriptions or the health files are not matched occurs, returning to the HIS system to manually examine and modify.
S223, a structured prescription medical record data warehouse, namely a star-shaped prescription medical record data warehouse, is established, and comprises a prescription data total table, an outpatient time dimension table, a patient client dimension table, a disease dimension table and a medicine dimension table, wherein the prescription data total table comprises a time ID, a patient ID, a disease ID, a medicine amount, a daily dose and a curative effect condition (2 represents satisfaction, 1 represents general-1 represents dissatisfaction and 0 represents no); the time dimension table comprises time ID, date, year, month and week; the patient dimension table comprises patient ID, name, gender, age, mobile phone number, occupation, home address, family member name and telephone contact information; the disease maintenance table comprises disease ID, disease name, classification, department and doctor of clinic; the medicine dimension table comprises medicine ID, medicine name, category, expiration date and manufacturer.
S224, the word2vec algorithm is used for converting the total list of prescription text data into a word vector A1, converting the disease dimension table text data into a word vector B1 and converting the medicine dimension table text data into a word vector B2.
S225, a prescription medical record data training sample set is established, a prescription similarity examination model is trained, 80% is a training set, 20% is a testing set, and the prescription medical record data is identified (passed or failed) according to two categories. And inputting the word vector A1 and the word vector B2 into the BiLSTM neural network model in parallel for offline classification training.
S226, inputting an online target prescription text, and analyzing the prescription and related health record unstructured data to form structured target prescription medical record data. The target prescription data set comprises a prescription data summary table, an outpatient time dimension table, a patient client dimension table, a disease dimension table and a medicine dimension table. Since the doctor prescribes the patient after diagnosis, and the target prescription is received by the patient, the patient is satisfied with the prescription content, namely, the 'curative effect condition' is satisfied at the moment, and input 2. If the patient is not satisfied with the actual curative effect result after the medication, the information is fed back in a satisfaction survey condition table, and the system stores the patient dissatisfied text data-1 in a prescription medical record data warehouse to update a database. The word2vec algorithm is used for converting the total table of target prescription text data into word vectors AA1, converting the disease dimension table text data into word vectors BB1, converting the medicine dimension table text data into word vectors BB2, and inputting the word vectors into the BiLSTM neural network model in parallel for prescription similarity comparison, examination and classification.
S227, judging whether the similarity is equal to or greater than a threshold. If the similarity is greater than or equal to the set threshold, the auditing is passed, otherwise, the auditing fails.
S228, if the verification passes, automatically giving an electronic signature to a pharmacist, and sending a pharmacy end to prepare for entering a dispensing process;
and S229, if the auditing is failed, giving data with the similarity of the corresponding word vector lower than the set threshold value for the prescription text which is failed in the auditing, wherein the data comprises the contents of the data total table of the prescription text, the disease dimension table and/or the medicine dimension table mismatch, and feeding back the modification at the doctor end. Namely, the training model can display the unmatched content of the matched word vector, give out the reason of the auditing failure and return to the doctor end for rectifying and modifying reasons: the total table is not matched, or the disease dimension table is not matched, or the medicine dimension table is not matched.
S410, dispensing management, namely assigning an electronic prescription dispensing task list to a corresponding dispensing point. The method comprises the following steps: after the patient finishes scanning and paying the expense, the dispensing subsystem receives response information, forms a time stamp and block data such as personal identity information of the patient, a mobile phone number, a medicine name, a medicine duration, daily dose and the like, generates dispensing block data according to the time stamp by the electronic prescription bill data, enters a dispensing block chain system, uploads the block data and broadcasts, and a dispensing point (an in-hospital dispensing node or an out-hospital dispensing node or a cooperated pharmacy) of the dispensing block chain system receives the broadcast and responds, acquires the prescription bill task in a contract rule mode or a competition priority mode and finishes dispensing.
The block chain link point alliance of the dispensing subsystem takes a dispensing subsystem of a hospital pharmacy as a management node, and invites the dispensing department of the hospital pharmacy, the dispensing department of an external pharmacy, an external pharmacy and a medicine producer to be added as nodes. The management node is responsible for making contract rules, and in view of the fact that the pharmacy and dispensing department of the home bears main dispensing tasks, the management node sets priority rights to the pharmacy and dispensing node based on the responsibility to the medication safety of patients and the trust to the pharmacy and dispensing department of the home, and can authorize access, process or not process all prescription block data, and the grade is the highest grade. Other nodes are used as auxiliary dispensing function nodes, and when the dispensing node of the hospital cannot process or cannot process the dispensing task due to busy, the dispensing task can be obtained through a competition rule.
The management node sends two public KEYs KEY A and KEY B to the home dispensing node, wherein KEY A has priority access rights compared with KEY B. The home node leaves the public KEY a and forwards KEY B to other nodes.
Before broadcasting the blockchain information, the hospital pharmacy distribution system encrypts the personal identity information of the patient, the mobile phone number and other information.
The management node signs an acknowledgement of the block data to be sent before broadcasting the request information in the blockchain. The self-hospital dispensing node holds the KEY A and accesses the data information preferentially to determine whether to schedule dispensing processing, and if not, the dispensing processing is abandoned. Any node holding the public KEY B will obtain access rights and perform dispensing work.
S420, estimating and inquiring the dispensing time, estimating the expected completion time of prescription dispensing and the expected dispensing time of medicines, and inquiring by patients.
S510', carrying out drug delivery according to the addresses of the corresponding patients after dispensing at the corresponding dispensing points, and issuing a transportation logistics bill.
S530, tracing and tracking the medicine, namely endowing a unique tracing code to the medicine after dispensing, and tracing and tracking the whole course, so as to ensure medication safety. The medicine tracking comprises the functions of medicine manufacturers, logistics carriers, patient user identities, patient home addresses and the like.
S520', receiving a logistics transportation bill and implementing logistics transportation tasks.
The method comprises the following steps: after the medicine dispensing is finished, generating time stamp logistics transportation block data to log in a logistics block chain system and uploading block data; and a certain logistics transport manufacturer platform node of the logistics block chain system receives the broadcast and responds, obtains a logistics transport bill in a contract rule mode or a competition priority mode, implements a logistics transport task and tracks logistics information.
And a certain Node in the blockchain dispensing alliance obtains a dispensing information sheet through a contract, returns information after dispensing is completed, and automatically generates a logistics data block with a time stamp. The logistics data block also comprises patient name, identity information, mobile phone number, communication address, medicine name, medicine consumption, prescription unit name, prescription address and telephone contact way.
The Node prescription (a pharmacy of a home, a pharmacy of an outer hospital, a pharmacy of a pharmacy, or a pharmaceutical factory) logs in and sends medicine logistics transportation broadcast to a logistics block chain alliance, after a certain logistics Node in the alliance acquires a logistics bill in a fair competition rule mode, the logistics bill information is analyzed, the logistics bill is arranged to be delivered to a task, and a logistics Node electronic commerce platform sends a delivery single number short message to a patient mobile phone to prompt the patient and responds to a prescription dispensing logistics request.
The patient user can log in the logistics platform to inquire by tracking the logistics distribution process; the hospital delivery system can inquire the medicine logistics condition through the AP I interface dispensing node system.
And S610, performing a return visit survey, performing satisfaction return visit survey on the patients after the medicine is dispensed and taken, and collecting feedback information of the patients.
S620, feedback information evaluation, namely performing satisfaction evaluation on the feedback information, and at least obtaining two evaluation results of satisfaction and dissatisfaction.
S630, the review queue is opened, and a review request queue is formed for the patient information with unsatisfactory evaluation results and is sent to the doctor end.
And S640, updating prescription data, automatically evaluating the medication feedback information of the patient by adopting a weighted evaluation algorithm, presetting a satisfaction threshold to distinguish satisfaction, general satisfaction and dissatisfaction results, and storing the general satisfaction or dissatisfaction results in a prescription medical record data warehouse by adopting text data representation to update a database.
Referring to fig. 10, S610, S620, S630, S640 specifically include:
s611, after the patient takes the medicine, logging in an APP patient end or scanning a prescription two-dimensional code.
S612, filling in an input medicine use condition satisfaction evaluation questionnaire, wherein the evaluation content comprises 1) medicine transportation conditions (5 points are very satisfactory, 4 points are basically satisfactory, 3 points are more satisfactory, 2 points are less satisfactory, and 1 point is not satisfactory); 2) Drug use (5 points satisfactory, 4 points substantially satisfactory, 3 points satisfactory, 2 points less satisfactory, 1 point less satisfactory); 3) Symptom treatment effect (5 points satisfactory, 4 points substantially satisfactory, 3 points satisfactory, 2 points less satisfactory, 1 point less satisfactory); 4) Supplement comments.
S621, evaluating the patient satisfaction feedback data. The evaluation method sets a weight value for the evaluation content according to the importance degree, for example, the weight of the drug transportation condition is 0.1, the weight of the drug use condition is 0.3, the weight of the symptom treatment recovery condition is 0.5, and the weight of other supplementary opinions is 0.1. Patient satisfaction actual score ofWherein b i Representing the score of the attribute evaluation of the subentry, w i For the weight value, the weight value cumulative sum is equal to 1. The system presets satisfaction threshold K1, K2 (K1)>K2 If the actual score of patient satisfaction is greater than the equal threshold K1, no further processing is required (no review is required); if the actual score of the patient satisfaction is smaller than the threshold value K1 and larger than K2, the general patient satisfaction text data 1 is stored in a prescription medical record data warehouse, and the database is updated without further processing (without review); if the actual score of the patient satisfaction is smaller than the set threshold K2, the patient dissatisfaction text data-1 is stored in a prescription medical record data warehouse, and the database is updated.
S622, for the dissatisfied text data-1 of the patient, namely the dissatisfied result, inquiring the prescription medical record data warehouse system according to the patient identity ID and mainly treating the doctor to generate request information, forming a time queue in the doctor-side processing area and waiting for processing.
S631, the doctor responds to and prepares to re-diagnose the patient according to the processing time sequence. The doctor end or A I doctor voice assistant automatically links to call the patient to establish a remote post-diagnosis review window. Providing on-line review service for patients.
S641, if the patient' S condition changes, the doctor can re-prescribe, and after the doctor passes the examination, the intelligent examination subsystem enters the pharmacy dispensing and transporting process. After receiving the new medicine, the patient can take the medicine satisfactorily. The system updates patient prescription medical record data.
In this specification, each embodiment is mainly described in the specification as a difference from other embodiments, and the same similar parts between the embodiments are referred to each other.
The intelligent medicine distribution system and the intelligent medicine distribution method provided by the application are described in detail. The principles and embodiments of the present application have been described herein with reference to specific examples, the description of which is intended only to facilitate an understanding of the method of the present application and its core ideas. It should be noted that it will be apparent to those skilled in the art that various modifications and adaptations of the application can be made without departing from the principles of the application and these modifications and adaptations are intended to be within the scope of the application as defined in the following claims.
Claims (10)
1. An intelligent medicine distribution system, comprising
The inquiry subsystem is used for remote online inquiry at the patient end and remote online diagnosis at the doctor end;
the prescription subsystem is used for opening an electronic prescription according to the diagnosis result by a doctor end and intelligently auditing the electronic prescription;
a pharmacy subsystem for assigning audited electronic prescriptions to corresponding pharmacy prescriptions;
the delivery subsystem is used for delivering and tracking the prepared medicines;
and the re-diagnosis subsystem is used for feeding back, evaluating or re-diagnosing after the patient inquires and dispenses.
2. The smart drug delivery system of claim 1, wherein the interrogation subsystem comprises
The patient end inquiry module is used for establishing personal health files for the patient, uploading symptom description texts and remotely carrying out on-line inquiry;
and the doctor end diagnosis module is used for remotely diagnosing the patient by a doctor and comprehensively diagnosing the patient description illness state, patient medical record data and detection results.
3. The smart drug delivery system of claim 1, wherein the prescription subsystem comprises
The prescription issuing module is used for issuing an electronic prescription for the patient according to the diagnosis result by a doctor;
the intelligent auditing module is used for auditing the electronic prescription issued by the doctor; returning failed information to the electronic prescription which is failed in the verification and attaching verification comments to a prescription issuing module to require a doctor to modify the prescription;
and the electronic signature module is used for attaching an electronic signature to the electronic prescription passing the verification.
4. The smart drug delivery system of claim 1, wherein the pharmacy subsystem comprises
The prescription receiving and processing module is used for receiving the electronic prescriptions which pass the verification and reading information on the electronic prescriptions;
the expense settlement module is used for settling expense according to the read information of the electronic prescription;
the identification code generation module is used for generating a unique identification code for the patient end to scan and identify the cost and the patient identity information;
the payment management module is used for paying and managing the fees after the patient scanning code identification;
the address management module is used for matching and managing the addresses of the patients after the prescription cost payment of the patients is completed;
the dispensing management module is used for dispatching an electronic prescription dispensing task list to a corresponding dispensing point;
and the medicine dispensing time prediction and query module is used for estimating the predicted completion time of prescription and medicine dispensing and the predicted dispensing time of medicines and providing for the query of patients.
5. The smart drug delivery system of claim 1, wherein the delivery subsystem comprises
The medicine delivery module is used for delivering the medicines according to the addresses of the corresponding patients after the medicines are dispensed at the corresponding dispensing points and releasing a transportation logistics bill;
the logistics transportation module is used for receiving logistics transportation bill and implementing logistics transportation task;
and the medicine tracing and tracking module is used for endowing the medicine after the medicine is dispensed with a unique tracing code and tracing the whole course.
6. The smart drug delivery system of any one of claims 1-5, wherein the review subsystem comprises
The return visit investigation module is used for carrying out satisfaction return visit investigation on the patients after the medicine is dispensed and taken, and collecting feedback information of the patients;
the feedback information evaluation module is used for performing satisfaction evaluation on the feedback information to at least obtain two evaluation results of satisfaction and dissatisfaction;
the review queue opening module is used for forming a review request queue for the patient information with unsatisfactory evaluation results and sending the review request queue to a doctor end;
the re-diagnosis window opening module is used for informing the patient to open the remote re-diagnosis window in response to the re-diagnosis request by the doctor end and providing on-line re-diagnosis service for the patient.
7. The intelligent drug delivery system according to claim 3, wherein the intelligent auditing module adopts a prescription artificial intelligence algorithm to audit drugs on line, and specifically comprises:
extracting and converting the prescription text data and the health file text data of the HIS system of the hospital to form a structured prescription medical record data warehouse;
generating a prescription word vector for the structured prescription medical record data by using a word2vec algorithm;
establishing a prescription word vector model by utilizing a BiLSTM neural network, and inputting the prescription word vector into the model for training;
extracting and converting the online target prescription text and related health file text data to form structured target prescription medical record data;
generating a sentence word vector to be detected for the structured target prescription medical record data by using a word2vec algorithm;
inputting the sentence word vector to be tested into a prescription word vector model for similarity comparison, and if the similarity is greater than or equal to a set threshold value, indicating that the prescription audit is passed; if the similarity is lower than the set threshold, the prescription audit is failed, data corresponding to the word vector similarity lower than the set threshold is provided, and the data comprises contents of mismatching of a prescription text data table, a disease dimension table and/or a medicine dimension table, and the modification is fed back to a doctor.
8. The smart drug delivery system of claim 4, wherein the dispensing management module employs a blockchain to dispense an electronic prescription dispensing job ticket, comprising: generating prescription block data from electronic prescription list data according to a time stamp, entering the prescription block chain system, uploading the block data and broadcasting, receiving and responding to the broadcast at a certain prescription point of the prescription block chain system, acquiring a prescription list task in a contract rule mode or a competition priority mode, and completing the prescription;
the medicine delivery module and the logistics transportation tracking module adopt block chain delivery and transportation, and specifically comprise: after the medicine dispensing is finished, generating time stamp logistics transportation block data to log in a logistics block chain system and uploading block data; and a certain logistics transport manufacturer platform node of the logistics block chain system receives the broadcast and responds, obtains a logistics transport bill in a contract rule mode or a competition priority mode, implements a logistics transport task and tracks logistics information.
9. The intelligent drug delivery system according to claim 6, wherein the patient medication feedback information is automatically evaluated using a weighted evaluation algorithm, a satisfaction threshold is preset to distinguish between satisfaction, general satisfaction, and dissatisfaction, and the general satisfaction or dissatisfaction results are stored in the prescription medical record data repository using textual data representation, and the database is updated.
10. A smart medicine dispensing method using the system of any one of the above 1 to 9, comprising:
remote on-line inquiry at the patient end and remote on-line diagnosis at the doctor end;
the doctor end opens an electronic prescription according to the diagnosis result and intelligently checks the electronic prescription;
assigning the electronic prescriptions which pass the verification to corresponding pharmacy for dispensing;
distributing and tracking the prepared medicines;
the patient is fed back, evaluated or re-diagnosed after the inquiry and dosage.
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| CN202311156016.7A CN117238440A (en) | 2023-09-07 | 2023-09-07 | Intelligent medicine distribution system and method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117558400A (en) * | 2024-01-12 | 2024-02-13 | 天津医科大学总医院 | Prescription auditing method and system based on feedback information |
| CN117711593A (en) * | 2024-02-05 | 2024-03-15 | 苏州绿华科技有限公司 | Intelligent pharmacy medicine inlet and outlet management system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117558400A (en) * | 2024-01-12 | 2024-02-13 | 天津医科大学总医院 | Prescription auditing method and system based on feedback information |
| CN117558400B (en) * | 2024-01-12 | 2024-03-15 | 天津医科大学总医院 | Prescription auditing method and system based on feedback information |
| CN117711593A (en) * | 2024-02-05 | 2024-03-15 | 苏州绿华科技有限公司 | Intelligent pharmacy medicine inlet and outlet management system |
| CN117711593B (en) * | 2024-02-05 | 2024-04-19 | 苏州绿华科技有限公司 | Intelligent pharmacy medicine inlet and outlet management system |
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