CN118072904B - Intelligent inspection method and system for on-line medical prescription medication - Google Patents
Intelligent inspection method and system for on-line medical prescription medication Download PDFInfo
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- 239000003814 drug Substances 0.000 title claims abstract description 62
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- 238000000034 method Methods 0.000 title claims abstract description 33
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- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 115
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- 238000004364 calculation method Methods 0.000 claims description 26
- 238000007405 data analysis Methods 0.000 claims description 15
- 230000015654 memory Effects 0.000 claims description 14
- 230000005856 abnormality Effects 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 10
- 208000037919 acquired disease Diseases 0.000 claims description 4
- 238000001647 drug administration Methods 0.000 claims description 3
- 208000024891 symptom Diseases 0.000 claims description 3
- 230000002159 abnormal effect Effects 0.000 abstract description 5
- 208000008589 Obesity Diseases 0.000 description 2
- 206010037888 Rash pustular Diseases 0.000 description 2
- 208000025865 Ulcer Diseases 0.000 description 2
- 206010052428 Wound Diseases 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 2
- 230000036772 blood pressure Effects 0.000 description 2
- 230000036760 body temperature Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 208000035475 disorder Diseases 0.000 description 2
- 235000020824 obesity Nutrition 0.000 description 2
- 229940126532 prescription medicine Drugs 0.000 description 2
- 208000029561 pustule Diseases 0.000 description 2
- 210000000697 sensory organ Anatomy 0.000 description 2
- 231100000397 ulcer Toxicity 0.000 description 2
- 208000027691 Conduct disease Diseases 0.000 description 1
- 238000012550 audit Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
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- G—PHYSICS
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- 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
- G16H20/13—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 delivered from dispensers
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- G—PHYSICS
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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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
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
The invention discloses an intelligent inspection method and system for on-line medical prescription medication, which belong to the field of medical health care, wherein the invention analyzes the treatment effect of a prescription according to the condition change data of other patients using the prescription historically, performs the matching analysis of the medical prescription and the condition of the patient according to the obtained condition similar analysis result and the treatment effect analysis result, performs the abnormal early warning of the medical prescription according to the obtained matching analysis result of the medical prescription and the condition of the patient, performs the accurate analysis of the matching degree of the medical prescription and the condition of the patient according to the analysis of the matching condition of the patient similar to the condition of other patients and the condition of the patient, improves the intelligent inspection accuracy of the medical prescription, and avoids the accident situation of the patient caused by the wrong prescription.
Description
Technical Field
The invention belongs to the field of medical health care, and particularly relates to an intelligent inspection method and system for on-line medical prescription medication.
Background
In the process of the patient in the physical hospital, the doctor and the patient are in face-to-face inquiry, the doctor grasps the condition of the patient in more detail, and the prescription made by the doctor has stronger pertinence; in the medicine taking stage, the patient needs to take medicine from a hospital pharmacy, and a doctor in the pharmacy can audit the prescription medicine, so that the medicine taking safety of the patient is ensured. In the on-line medical inquiry scene, only diagnosis and prescription making can be performed, and the patient has a plurality of choices in the medicine taking link: the medicine can be taken through various ways such as an internet pharmacy, an entity pharmacy and the like, so that the link of checking the prescription by a pharmacy doctor is omitted, the medicine taking risk of a patient is increased, and the prescription medicine checking in an online medical scene is particularly important;
In the prior art, when the medication inspection is performed, the condition of a patient is not analyzed by matching conditions of other patients similar to the condition of the patient, and then the matching degree of the medical prescription and the condition of the patient cannot be accurately analyzed, so that the intelligent inspection accuracy of the medical prescription is reduced, the condition that the patient is unexpected due to the fact that the wrong prescription is easily opened is easily caused, and the problems exist in the prior art (for example, in the invention patent with the issued publication numbers of CN113674858A and CN 111128333A);
In order to solve the problems, the application designs an intelligent inspection method and system for the on-line medical prescription medication.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent inspection method and system for the medicine of an online medical prescription, which are used for acquiring medical prescription data, acquiring patient disease data, acquiring disease change data of other patients who use the prescription in a history manner, acquiring disease data of the patients and disease change data of other patients who use the prescription in a history manner to conduct disease similarity analysis of the patients, analyzing treatment effects of the prescription according to the disease change data of other patients who use the prescription in the history manner, conducting matching analysis of the medical prescription and the patient disease according to the acquired disease similarity analysis result and the treatment effect analysis result, conducting abnormal early warning of the medical prescription according to the acquired matching analysis result of the medical prescription and the patient disease, conducting accurate analysis of matching degree of the medical prescription and the patient disease, improving intelligent inspection accuracy of the medical prescription, and avoiding unexpected situations of the patients caused by wrong prescription.
In order to achieve the above purpose, the present invention provides the following technical solutions: an intelligent inspection method for on-line medical prescription medication comprises the following specific steps:
acquiring medical prescription data, and simultaneously acquiring patient condition data and patient condition change data of other patients who use the prescription in history;
acquiring patient condition data and historical patient condition change data of other patients using the prescription to perform patient condition similarity analysis;
Analyzing the treatment effect of the prescription according to the disease change data of other patients using the prescription historically;
Matching analysis of the medical prescription and the patient's illness state is carried out by obtaining the illness state similarity analysis result and the treatment effect analysis result;
and carrying out abnormal early warning on the medical prescription according to the analysis result of the matching of the medical prescription obtained by analysis and the illness state of the patient.
The method for acquiring the medical prescription data and the patient condition data simultaneously, and acquiring the condition change data of other patients who use the prescription historically comprises the following specific steps:
s11, acquiring medical prescription data to be checked, and simultaneously acquiring patient disease data, wherein the medical prescription data comprises medicine type and content data, the patient disease data is patient affected part information and patient body constitution information, the body constitution information comprises blood pressure, body temperature, obesity degree and heart rate information of the patient in the treatment process, the patient affected part information comprises the position of an affected part and disease data of the affected part, and the position of the affected part is divided according to body structures and is specifically divided into: limbs, head, five sense organs, and heart, etc., where the condition data is the area of the condition and the condition manifestations, such as: ulcers, pustules, wounds, and the like;
S12, acquiring other patient condition change data using the medical prescription from a historical patient medication database, wherein the patient condition change data is physical constitution information change data after the patient takes the quantitative medication and condition data when the other patient using the medical prescription takes the medication.
It should be specifically noted that the patient condition similarity analysis performed by acquiring patient condition data and patient condition change data of other patients who use the prescription historically includes the following specific contents:
S21, acquiring information of an affected part of a patient and physical constitution information of the patient, and simultaneously acquiring the information of the affected part and the physical constitution information of other patients using a medical prescription when the medicine is prescribed;
S22, substituting the information of the affected part of the patient and the information of the affected part of the other patients during the medicine opening into an information analysis coefficient calculation formula of the affected part to calculate an information analysis coefficient of the affected part, wherein the information analysis coefficient calculation formula of the affected part of the patient and the z-th other patients during the medicine opening is as follows: wherein m () is the number of set elements in brackets, w is the set of the positions of the affected parts of the patient, Is the set formed by the positions of the affected parts of the z-th other patients when the medicine is taken, s is the area of the affected part of the patient corresponding to the same position of the affected part of the z-th other patients,Is the area of the affected part of the z-th other patient corresponding to the same position of the affected part of the patient,For the number of identical manifestations of the disorder in the patient and the z-th other patient,Sum of the number of symptoms for the patient and the z other patient;
s23, substituting body constitution information of a patient and body constitution information of other patients using a medical prescription during drug administration into a body constitution analysis coefficient calculation formula to calculate a body constitution analysis coefficient, wherein the body constitution analysis coefficient calculation formula of the patient and the z-th other patients using the medical prescription is as follows: wherein n is the type of physical constitution information, T is the time of patient's visit, For using the data of the ith physical fitness information at the time t of the visit of the z-th other patient of the medical prescription,Data of the ith physical constitution information of the patient at the time of the visit t, dt is time integral,Is the maximum value of the safety range of the ith body constitution information,Is the minimum value of the safety range of the ith body constitution information,The duty ratio coefficient of the ith body constitution information;
s24, multiplying the calculated body constitution analysis coefficient by a set body constitution ratio to obtain a first product, multiplying the obtained affected part information analysis coefficient by the set affected part information ratio to obtain a second product, and adding the obtained first product and the second product to obtain a disease condition similarity analysis value;
The added value of the information ratio of the affected part and the physical constitution ratio is 1.
It should be specifically noted that the treatment effect analysis of the prescription according to the disease change data of other patients who use the prescription historically includes the following specific steps:
s31, acquiring disease condition change data of other patients after one period of history use of the prescription;
S32, substituting acquired disease change data of other patients after one period of history use of the prescription into a disease change data analysis value calculation formula to calculate a disease change data analysis coefficient, wherein the disease change data analysis coefficient calculation formula of the z-th other patient is as follows: wherein, the method comprises the steps of, wherein, For the average value of the set time length of the ith physical constitution information data before one cycle of the prescription for the historic z-th patient,For the average value of the set time length of the ith physical constitution information data after one cycle of the use of the prescription for the historic z-th patient,Is the median of the safety range of the ith physical constitution information data.
The method for matching the medical prescription with the patient's condition by obtaining the result of the similar condition analysis and the result of the treatment effect analysis comprises the following steps:
S41, acquiring corresponding histories of other patients using the prescription, wherein the disease similarity analysis value is greater than or equal to a set disease similarity analysis threshold, setting the other patients as similar patients, and acquiring a disease similarity analysis value and a disease change data analysis coefficient of the similar patients;
s42, substituting the disease similarity analysis value and the disease change data analysis coefficient of the similar patient into a prescription matching value calculation formula to calculate a prescription matching value, wherein the prescription matching value calculation formula is as follows: wherein m is the number of similar patients, Analyzing coefficients for disease change data of the jth other patient,Is the disease similarity analysis value of the j other patients.
The specific content of the medical prescription abnormality early warning according to the analysis result of the matching of the medical prescription and the patient condition obtained by the analysis is as follows:
comparing the calculated prescription matching value with a set prescription matching threshold, if the obtained prescription matching value is larger than or equal to the set prescription matching threshold, the medical prescription is matched with the patient's illness state, if the obtained prescription matching value is smaller than the set prescription matching threshold, the medical prescription is not matched with the patient's illness state, and a medical staff is issued with an early warning of the medical prescription not matched with the patient's illness state.
It should be noted that, the ratio coefficient of the ith body constitution information, the body constitution ratio, the affected part information ratio, the disease similarity analysis threshold value and the prescription matching threshold value are as follows: acquiring at least five thousand groups of medical prescription misplacement and misplacement data, patient disease data and disease change data of other patients who use the prescription historically, substituting the patient disease data and the disease change data of other patients who use the prescription historically into a prescription matching value calculation formula to calculate a prescription matching value, importing the calculated prescription matching value and medical prescription misplacement judgment result into fitting software, and outputting the ratio coefficient of the ith body constitution information, the body constitution ratio, the affected part information ratio, the disease similarity analysis threshold and the prescription matching threshold which accord with the highest judgment accuracy.
An online medical prescription medication intelligent inspection system is realized based on the online medical prescription medication intelligent inspection method, and specifically comprises the following steps:
The data acquisition module is used for acquiring medical prescription data, acquiring patient disease data and acquiring disease change data of other patients who use the prescription in history;
The disease similarity analysis module is used for acquiring disease data of the patient and disease change data of other patients who use the prescription historically to carry out disease similarity analysis of the patient;
The treatment effect analysis module is used for analyzing the treatment effect of the prescription according to the disease change data of other patients who use the prescription historically;
the matching analysis module is used for carrying out matching analysis on the medical prescription and the patient disease by obtaining a disease similarity analysis result and a treatment effect analysis result;
the medical prescription abnormality early warning module is used for carrying out medical prescription abnormality early warning according to the analysis result of the matching of the medical prescription obtained by analysis and the illness state of the patient;
the control module is used for controlling the operation of the data acquisition module, the illness state similarity analysis module, the treatment effect analysis module, the matching analysis module and the medical prescription abnormality early warning module.
An electronic device, comprising: a processor and a memory, wherein the memory stores a computer program for the processor to call;
the processor executes the intelligent inspection method for the on-line medical prescription medication by calling the computer program stored in the memory.
A computer readable storage medium storing instructions that, when executed on a computer, cause the computer to perform an online medical prescription medication intelligent inspection method as described above.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, medical prescription data is acquired, meanwhile, patient condition data is acquired, patient condition data of other patients using the prescription historically are acquired, patient condition similarity analysis is performed on the patient condition data and patient condition change data of other patients using the prescription historically, treatment effect analysis is performed on the prescription according to the patient condition change data of other patients using the prescription historically, medical prescription and patient condition matching analysis is performed according to the acquired medical prescription and patient condition matching analysis result, abnormal medical prescription early warning is performed according to the analyzed medical prescription and patient condition matching analysis result, accurate analysis of matching degree is performed on the medical prescription and patient condition by analyzing the patient condition matching condition of other patients similar to the patient condition, intelligent examination accuracy of the medical prescription is improved, and accidents of patients caused by incorrect prescription are avoided.
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 schematic diagram of the overall flow of an intelligent inspection method for on-line medical prescription medication of the present invention;
FIG. 2 is a flow chart of a process for analyzing patient condition similarity by acquiring patient condition data and historical patient condition change data of other patients using the prescription in an intelligent inspection method for on-line medical prescription medication according to the present invention;
FIG. 3 is a schematic diagram of the overall framework of an intelligent inspection system for on-line medical prescription medication according to the present invention.
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.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Example 1
Referring to fig. 1-2, an embodiment of the present invention is provided: the technical problems solved by the embodiment are as follows: in the prior art, when the medication inspection is performed, the condition of a patient is similar to the matching conditions of other patients and the condition of the patient, so that the accurate analysis of the matching degree of the medical prescription and the condition of the patient cannot be performed, the intelligent inspection accuracy of the medical prescription is reduced, and the accident situation of the patient is caused by the fact that the wrong prescription is easily generated;
An intelligent inspection method for on-line medical prescription medication comprises the following specific steps:
acquiring medical prescription data, and simultaneously acquiring patient condition data and patient condition change data of other patients who use the prescription in history;
The present step is specifically described herein: s11, acquiring medical prescription data to be checked, and simultaneously acquiring patient disease data, wherein the medical prescription data comprises medicine type and content data, the patient disease data is patient affected part information and patient body constitution information, the body constitution information comprises blood pressure, body temperature, obesity degree and heart rate information of the patient in the treatment process, the patient affected part information comprises affected part position and affected part disease data, and the patient affected part position is divided according to body structure, wherein the specific division is as follows: limbs, head, five sense organs, and heart, etc., where the condition data is the area of the condition and the condition manifestations, such as: ulcers, pustules, wounds, and the like;
It should be noted that, the patient information is only calculated and used in the internal system of the hospital, and the external personnel cannot obtain the patient information in a hacking mode or the like, and meanwhile, the information such as any name is not involved, so that the privacy problem is not required to be considered;
The above steps are implemented by codes:
# acquisition of medical prescription data
def get_medical_prescription_data(patient_id):
# Acquisition of medical prescription data from medical System
prescription_data = medical_system.get_prescription_data(patient_id)
return prescription_data
# Acquisition of patient condition data
def get_patient_health_data(patient_id):
Obtaining patient condition data from a health record system
health_data = health_records_system.get_health_data(patient_id)
return health_data
# Main program
if __name__ == "__main__":
patient_id = "12345"
# Acquisition of medical prescription data
prescription_data = get_medical_prescription_data(patient_id)
drugs = prescription_data.get("drugs")
# Acquisition of patient condition data
patient_health_data = get_patient_health_data(patient_id)
condition = patient_health_data.get("condition")
body_physique = patient_health_data.get("body_physique")
Printing the acquired data #
Print (' medicine type and content data: "drugs)
Print ('affected part information:', condition)
Print ('body constitution information:', body_ physique)
S12, acquiring disease condition change data of other patients using the medical prescription from a historical patient medication database, wherein the disease condition change data of the patients are physical constitution information change data of the patients after taking quantitative medicines and disease condition data of the other patients using the medical prescription during the medicine taking;
acquiring patient condition data and historical patient condition change data of other patients using the prescription to perform patient condition similarity analysis;
The present step is specifically described herein: s21, acquiring information of an affected part of a patient and physical constitution information of the patient, and simultaneously acquiring the information of the affected part and the physical constitution information of other patients using a medical prescription when the medicine is prescribed;
S22, substituting the information of the affected part of the patient and the information of the affected part of the other patients during the medicine opening into an information analysis coefficient calculation formula of the affected part to calculate an information analysis coefficient of the affected part, wherein the information analysis coefficient calculation formula of the affected part of the patient and the z-th other patients during the medicine opening is as follows: wherein m () is the number of set elements in brackets, w is the set of the positions of the affected parts of the patient, Is the set formed by the positions of the affected parts of the z-th other patients when the medicine is taken, s is the area of the affected part of the patient corresponding to the same position of the affected part of the z-th other patients,Is the area of the affected part of the z-th other patient corresponding to the same position of the affected part of the patient,For the number of identical manifestations of the disorder in the patient and the z-th other patient,Sum of the number of symptoms for the patient and the z other patient;
s23, substituting body constitution information of a patient and body constitution information of other patients using a medical prescription during drug administration into a body constitution analysis coefficient calculation formula to calculate a body constitution analysis coefficient, wherein the body constitution analysis coefficient calculation formula of the patient and the z-th other patients using the medical prescription is as follows: wherein n is the type of physical constitution information, T is the time of patient's visit, For using the data of the ith physical fitness information at the time t of the visit of the z-th other patient of the medical prescription,Data of the ith physical constitution information of the patient at the time of the visit t, dt is time integral,Is the maximum value of the safety range of the ith body constitution information,Is the minimum value of the safety range of the ith body constitution information,The duty ratio coefficient of the ith body constitution information;
s24, multiplying the calculated body constitution analysis coefficient by a set body constitution ratio to obtain a first product, multiplying the obtained affected part information analysis coefficient by the set affected part information ratio to obtain a second product, and adding the obtained first product and the second product to obtain a disease condition similarity analysis value;
the added value of the information ratio of the affected part and the physical constitution ratio is 1;
Analyzing the treatment effect of the prescription according to the disease change data of other patients using the prescription historically;
The present step is specifically described herein: s31, acquiring disease condition change data of other patients after one period of history use of the prescription;
S32, substituting acquired disease change data of other patients after one period of history use of the prescription into a disease change data analysis value calculation formula to calculate a disease change data analysis coefficient, wherein the disease change data analysis coefficient calculation formula of the z-th other patient is as follows: wherein, the method comprises the steps of, wherein, For the average value of the set time length of the ith physical constitution information data before one cycle of the prescription for the historic z-th patient,For the average value of the set time length of the ith physical constitution information data after one cycle of the use of the prescription for the historic z-th patient,The median value of the safety range of the ith body constitution information data is set;
Matching analysis of the medical prescription and the patient's illness state is carried out by obtaining the illness state similarity analysis result and the treatment effect analysis result;
The present step is specifically described herein: s41, acquiring corresponding histories of other patients using the prescription, wherein the disease similarity analysis value is greater than or equal to a set disease similarity analysis threshold, setting the other patients as similar patients, and acquiring a disease similarity analysis value and a disease change data analysis coefficient of the similar patients;
s42, substituting the disease similarity analysis value and the disease change data analysis coefficient of the similar patient into a prescription matching value calculation formula to calculate a prescription matching value, wherein the prescription matching value calculation formula is as follows: wherein m is the number of similar patients, Analyzing coefficients for disease change data of the jth other patient,A disease similarity analysis value for the j other patient;
Performing medical prescription abnormality early warning according to the analysis result of the matching of the medical prescription obtained by analysis and the patient condition;
The present step is specifically described herein:
comparing the calculated prescription matching value with a set prescription matching threshold, if the obtained prescription matching value is larger than or equal to the set prescription matching threshold, the medical prescription is matched with the patient's illness state, if the obtained prescription matching value is smaller than the set prescription matching threshold, the medical prescription is not matched with the patient's illness state, and a medical staff is issued with an early warning of the medical prescription not matched with the patient's illness state.
It should be noted that, the ratio coefficient of the ith body constitution information, the body constitution ratio, the affected part information ratio, the disease similarity analysis threshold value and the prescription matching threshold value are as follows: acquiring at least five thousand groups of medical prescription misplacement and misplacement data, patient disease data and disease change data of other patients who use the prescription historically, substituting the patient disease data and the disease change data of other patients who use the prescription historically into a prescription matching value calculation formula to calculate a prescription matching value, importing the calculated prescription matching value and medical prescription misplacement judgment result into fitting software, and outputting the values of an ith physical constitution information duty factor, physical constitution duty ratio, affected part information duty ratio, disease similarity analysis threshold and prescription matching threshold which accord with the highest judgment accuracy;
It should be noted that the technical effects achieved by this embodiment are as follows: acquiring medical prescription data, acquiring patient disease condition change data of other patients using the prescription in a history mode, acquiring patient disease condition data and patient disease condition change data of other patients using the prescription in a history mode, performing disease condition similarity analysis on the prescription according to the patient disease condition change data of other patients using the prescription in a history mode, performing medical prescription and patient disease condition matching analysis through acquiring disease condition similarity analysis results and treatment effect analysis results, performing medical prescription abnormal early warning according to the medical prescription and patient disease condition matching analysis results obtained through analysis, performing accurate analysis on the matching degree of the medical prescription and the patient disease condition through analyzing the matching condition of other patients similar to the patient disease condition, improving the intelligent inspection accuracy of the medical prescription, and avoiding accidents of patients caused by wrong prescription.
Example 2
As shown in fig. 3, an on-line medical prescription medication intelligent inspection system is implemented based on the above-mentioned on-line medical prescription medication intelligent inspection method, and specifically includes: the data acquisition module is used for acquiring medical prescription data, acquiring patient disease data and acquiring disease change data of other patients who use the prescription in history;
The disease similarity analysis module is used for acquiring disease data of the patient and disease change data of other patients who use the prescription historically to carry out disease similarity analysis of the patient;
The treatment effect analysis module is used for analyzing the treatment effect of the prescription according to the disease change data of other patients who use the prescription historically;
the matching analysis module is used for carrying out matching analysis on the medical prescription and the patient disease by obtaining a disease similarity analysis result and a treatment effect analysis result;
the medical prescription abnormality early warning module is used for carrying out medical prescription abnormality early warning according to the analysis result of the matching of the medical prescription obtained by analysis and the illness state of the patient;
the control module is used for controlling the operation of the data acquisition module, the illness state similarity analysis module, the treatment effect analysis module, the matching analysis module and the medical prescription abnormality early warning module.
Example 3
The present embodiment provides an electronic device including: a processor and a memory, wherein the memory stores a computer program for the processor to call;
The processor executes an online medical prescription medication intelligent inspection method as described above by invoking a computer program stored in the memory.
The electronic device may have a relatively large difference due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, where at least one computer program is stored in the memories, and the computer program is loaded and executed by the processors to implement an online medical prescription medication intelligent inspection method provided by the above method embodiment.
Example 4
The present embodiment proposes a computer-readable storage medium having stored thereon an erasable computer program;
The computer program, when run on a computer device, causes the computer device to perform an online medical prescription medication intelligent inspection method as described above.
For example, the computer readable storage medium can be Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), compact disk Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM), magnetic tape, floppy disk, optical data storage device, and the like.
Claims (6)
1. An intelligent inspection method for on-line medical prescription medication is characterized by comprising the following specific steps:
acquiring medical prescription data, and simultaneously acquiring patient condition data and patient condition change data of other patients who use the prescription in history;
acquiring patient condition data and historical patient condition change data of other patients using the prescription to perform patient condition similarity analysis;
Analyzing the treatment effect of the prescription according to the disease change data of other patients using the prescription historically;
Matching analysis of the medical prescription and the patient's illness state is carried out by obtaining the illness state similarity analysis result and the treatment effect analysis result;
Performing medical prescription abnormality early warning according to the analysis result of the matching of the medical prescription obtained by analysis and the patient condition;
The patient condition similarity analysis of the acquired patient condition data and the patient condition change data of other patients historically using the prescription comprises the following specific contents:
S21, acquiring information of an affected part of a patient and physical constitution information of the patient, and simultaneously acquiring the information of the affected part and the physical constitution information of other patients using a medical prescription when the medicine is prescribed;
S22, substituting the information of the affected part of the patient and the information of the affected part of the other patients during the medicine opening into an information analysis coefficient calculation formula of the affected part to calculate an information analysis coefficient of the affected part, wherein the information analysis coefficient calculation formula of the affected part of the patient and the z-th other patients during the medicine opening is as follows: wherein m () is the number of set elements in brackets, w is the set of the positions of the affected parts of the patient, Is the set formed by the positions of the affected parts of the z-th other patients when the medicine is taken, s is the area of the affected part of the patient corresponding to the same position of the affected part of the z-th other patients,Is the area of the affected part of the z-th other patient corresponding to the same position of the affected part of the patient,For the number of identical manifestations of the disorder in the patient and the z-th other patient,Sum of the number of symptoms for the patient and the z other patient;
s23, substituting body constitution information of a patient and body constitution information of other patients using a medical prescription during drug administration into a body constitution analysis coefficient calculation formula to calculate a body constitution analysis coefficient, wherein the body constitution analysis coefficient calculation formula of the patient and the z-th other patients using the medical prescription is as follows: wherein n is the type of physical constitution information, T is the time of patient's visit, For using the data of the ith physical fitness information at the time t of the visit of the z-th other patient of the medical prescription,Data of the ith physical constitution information of the patient at the time of the visit t, dt is time integral,Is the maximum value of the safety range of the ith body constitution information,Is the minimum value of the safety range of the ith body constitution information,The duty ratio coefficient of the ith body constitution information;
s24, multiplying the calculated body constitution analysis coefficient by a set body constitution ratio to obtain a first product, multiplying the obtained affected part information analysis coefficient by the set affected part information ratio to obtain a second product, and adding the obtained first product and the second product to obtain a disease condition similarity analysis value;
The treatment effect analysis of the prescription according to the disease change data of other patients using the prescription historically comprises the following specific steps:
s31, acquiring disease condition change data of other patients after one period of history use of the prescription;
S32, substituting acquired disease change data of other patients after one period of history use of the prescription into a disease change data analysis value calculation formula to calculate a disease change data analysis coefficient, wherein the disease change data analysis coefficient calculation formula of the z-th other patient is as follows: wherein, the method comprises the steps of, wherein, For the average value of the set time length of the ith physical constitution information data before one cycle of the prescription for the historic z-th patient,For the average value of the set time length of the ith physical constitution information data after one cycle of the use of the prescription for the historic z-th patient,The median value of the safety range of the ith body constitution information data is set;
the matching analysis of the medical prescription and the patient disease by obtaining the disease similarity analysis result and the treatment effect analysis result comprises the following specific steps:
S41, acquiring corresponding histories of other patients using the prescription, wherein the disease similarity analysis value is greater than or equal to a set disease similarity analysis threshold, setting the other patients as similar patients, and acquiring a disease similarity analysis value and a disease change data analysis coefficient of the similar patients;
s42, substituting the disease similarity analysis value and the disease change data analysis coefficient of the similar patient into a prescription matching value calculation formula to calculate a prescription matching value, wherein the prescription matching value calculation formula is as follows: wherein m is the number of similar patients, Analyzing coefficients for disease change data of the jth other patient,Is the disease similarity analysis value of the j other patients.
2. The intelligent inspection method for on-line medical prescription medication according to claim 1, wherein the steps of acquiring medical prescription data and patient condition data, and acquiring condition change data of other patients who use the prescription historically include the following specific steps:
s11, acquiring medical prescription data to be checked, and acquiring patient condition data, wherein the medical prescription data comprises medicine type and content data, and the patient condition data is affected part information of a patient and physical constitution information of the patient;
S12, acquiring other patient condition change data using the medical prescription from a historical patient medication database, wherein the patient condition change data is physical constitution information change data after the patient takes the quantitative medication and condition data when the other patient using the medical prescription takes the medication.
3. The intelligent inspection method for on-line medical prescription medication according to claim 1, wherein the medical prescription abnormality pre-warning is performed according to the analysis result of the matching of the medical prescription and the patient's condition, which is characterized in that the specific contents are as follows:
comparing the calculated prescription matching value with a set prescription matching threshold, if the obtained prescription matching value is larger than or equal to the set prescription matching threshold, the medical prescription is matched with the patient's illness state, if the obtained prescription matching value is smaller than the set prescription matching threshold, the medical prescription is not matched with the patient's illness state, and a medical staff is issued with an early warning of the medical prescription not matched with the patient's illness state.
4. An on-line medical prescription medication intelligent inspection system realized based on the on-line medical prescription medication intelligent inspection method according to any one of claims 1-3, characterized in that it specifically comprises:
The data acquisition module is used for acquiring medical prescription data, acquiring patient disease data and acquiring disease change data of other patients who use the prescription in history;
The disease similarity analysis module is used for acquiring disease data of the patient and disease change data of other patients who use the prescription historically to carry out disease similarity analysis of the patient;
The treatment effect analysis module is used for analyzing the treatment effect of the prescription according to the disease change data of other patients who use the prescription historically;
the matching analysis module is used for carrying out matching analysis on the medical prescription and the patient disease by obtaining a disease similarity analysis result and a treatment effect analysis result;
the medical prescription abnormality early warning module is used for carrying out medical prescription abnormality early warning according to the analysis result of the matching of the medical prescription obtained by analysis and the illness state of the patient;
the control module is used for controlling the operation of the data acquisition module, the illness state similarity analysis module, the treatment effect analysis module, the matching analysis module and the medical prescription abnormality early warning module.
5. An electronic device, comprising: a processor and a memory, wherein the memory stores a computer program for the processor to call;
-wherein the processor performs an intelligent inspection method for the administration of an on-line medical prescription according to any one of claims 1-3 by invoking a computer program stored in the memory.
6. A computer readable storage medium storing instructions which, when executed on a computer, cause the computer to perform an on-line medical prescription medication intelligent inspection method according to any one of claims 1-3.
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