Grading and classifying management system based on cardiology department coronary heart disease drug library

Abstract

A grading and classification management system based on a cardiology department coronary heart disease drug library particularly relates to the technical field of drug grading and classification management and comprises a data collecting and processing module, a grading and classification module, a data analysis module and an analysis visualization module. Classification data of all medicines for treating the coronary heart disease in the department of cardiology is classified and collected, and the grading and classifying module sequentially calculates and outputs the curative effect evaluation value YWLi of the ith medicine, the classification grade index DJi of the ith medicine and the optimization adjustment coefficient DTi of the ith medicine of all the medicines. And the data analysis module is used for calculating and outputting optimization adjustment coefficients DTi of the ith medicine for all the medicines, arranging the optimization adjustment coefficients DTi of the ith medicine, and carrying out optimization adjustment of grading and classification management on the ith medicine which is lower than a median value, so that real-time updating of side effects, comprehensive consideration of medicine interaction and individual differences and dynamic adjustment of classification and classification management are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of drug classification management, and specifically to a classification management system based on a coronary heart disease drug library in the department of cardiology. Background Art

[0002] With the rapid development of information technology, the medical field is gradually realizing informatization and intelligentization. In the treatment of coronary heart disease in the department of cardiology, the selection and management of drugs are gradually relying on advanced computer systems and database technologies. Moreover, the informatized and intelligent management system can greatly improve the efficiency and accuracy of drug treatment, and provide more scientific and systematic medication suggestions for doctors.

[0003] In order to better manage the coronary heart disease drug library, it is also necessary to classify and manage drugs. There are some problems and deficiencies in the implementation of this system in the current prior art. First, the relevant parameters of drug side effects are not updated in a timely and accurate manner, resulting in the calculation results of drug efficacy deviating from the actual situation. Second, the interaction between drugs and individual differences of patients are not fully considered, resulting in inaccurate classification levels. Finally, the calculation for guiding the adjustment of the drug library lacks a unified adjustment management standard, thus affecting the stability and reliability of the system.

[0004] Therefore, the technical personnel in this field provide a classification management system based on a coronary heart disease drug library in the department of cardiology to solve the problems raised in the above background art. Summary of the Invention

[0005] The technical problem solved by the present invention is to provide a classification management system based on a coronary heart disease drug library in the department of cardiology to achieve the purpose of real-time updating of side effects, comprehensively considering drug interactions and individual differences, and dynamically adjusting classification management.

[0006] To solve the above problems, the present invention provides the following technical solutions: A classification management system based on a coronary heart disease drug library in the department of cardiology, including a data collection and processing module, a classification module, a data analysis module, and an analysis visualization module, characterized in that: The data collection and processing module classifies and collects the classification data of all kinds of drugs used to treat coronary heart disease in the department of cardiology within a current period of time, and transmits it to the classification module; The classification module sequentially calculates and outputs the efficacy evaluation value YWL of the i-th drug among all kinds of drugs i , the classification level index DJ of the i-th drug i , the optimization adjustment coefficient DT of the i-th drug i ; The data analysis module uses the optimization adjustment coefficient DT of the i-th drug calculated and output for all kinds of drugsi Arrange them and optimize and adjust the hierarchical classification management of the i-th drug with a low value below the median value; The analysis visualization module displays the results of all drug arrangements and optimization adjustments; Among them, the hierarchical classification module includes a unit for judging the pros and cons of drug efficacy, a unit for dividing drug classification levels, and a unit for guiding the adjustment of the drug library; When calculating the efficacy evaluation value YWL of the i-th drug i It includes the input of regularly updated data on the adverse reactions of patients in a current period of time.

[0007] Furthermore: The hierarchical classification module cooperates with the data collection and processing module to regularly update the side effects of all drugs to reflect the adverse reaction feedback of patients in a current period of time, which usually includes the following steps: Data collection: Collect the number of various adverse reactions F that occur in patients during the process of taking the i-th drug, and the total number of people n who take the i-th drug in a current period of time; Data analysis: Statistically analyze the collected number of adverse reactions F and the total number of people n, and use the calculation formula of FZ i =F / n to calculate the incidence of adverse reactions of all drugs; Index update: Update FZ according to the analysis and calculation results i to reflect the current situation of adverse reactions.

[0008] Furthermore: The calculation formula of the unit for judging the pros and cons of drug efficacy is as follows: ; Among them: YWL i is the efficacy evaluation value of the i-th drug; YF i is the content of the i-th drug component, and YF i reflects the content of the active ingredient used for therapeutic effect in the i-th drug; J i is the dose of the i-th drug, and J i reflects the dose marked on the medicine box and recommended for single-dose administration of the i-th drug; JB i is the standard deviation of the dose of the i-th drug, and JB i reflects the degree of fluctuation of the dose in the actual quality; FZ i is the side effect index of the i-th drug; In it, the dose J of the i-th drug i remains fixed, and the standard deviation JB of the dose of the i-th drugi There are fluctuating changes, and is a comprehensive consideration of the recommended dose and its fluctuations. Therefore, the square root calculation is for the standard deviation JB of the dose of the i-th drug i after the fluctuating effect is generated and the dose J of the i-th drug i and the weakening of the sum.

[0009] Furthermore: The calculation formula of the drug classification level division unit is as follows: ; Where: DJ i is the classification level index of the i-th drug; ZB i is the treatment cost of the i-th drug; YWL max is the maximum value of drug efficacy evaluation, YWL max reflects the maximum value of the calculated output of the efficacy evaluation value YWL of the i-th drug among all drugs for treating coronary heart disease in cardiology; i of the maximum value; The result of the division represents the recommended dose required per unit of active ingredient, that is, the dose efficiency of the drug.

[0010] Furthermore: The calculation formula of the guidance drug library adjustment unit is as follows: ; T=(ZB avg / ZB i )×a; Where: DT i is the optimization adjustment coefficient of the i-th drug; YF avg is the average component content of the drug, YF avg reflects the average degree of component content among all drugs for treating coronary heart disease in cardiology; ZB avg is the average treatment cost of the drug, ZB avg reflects the average degree of treatment cost among all drugs for treating coronary heart disease in cardiology; T is a regulatory factor used to adjust the influence of the treatment cost on the optimization adjustment coefficient DT of the i-th drug i ; a is an adjustment coefficient, and its value range is {0.2 - 0.8}, which is proportioned in the value range of {0.2 - 0.8} according to the high and low order of the calculation of the optimization adjustment coefficient DT of the i-th drug for all drugs in the previous time i , and its arrangement: The value of the i-th drug with a high arrangement tends to 0.8; The value of the i-th drug with a low rank tends to 0.2.

[0011] Furthermore: The guiding drug library adjustment unit calculates and outputs the i-th drug optimization adjustment coefficient DT for all types of drugs, classifies and grades them according to the magnitude arranged from left to right in descending order of values, and based on the setting that the low values below the median need to be adjusted, analyzes each i-th drug one by one, and the specific analysis is as follows: i Perform calculation and output, and classify and grade according to the magnitude arranged from left to right in descending order of values. And based on the setting that the low values below the median need to be adjusted, analyze each i-th drug one by one. The specific analysis is as follows: If the i-th drug efficacy evaluation value YWL of the i-th drug among all types of drugs i is at a low value, it indicates that the efficacy of the i-th drug is insufficient, and the composition and dosage of the i-th drug are optimized and adjusted according to the dosage fluctuation and side effect conditions; If the i-th drug classification level index DJ of the i-th drug among all types of drugs i is continuously at a low value for a long time, it indicates that the treatment cost of the drug is high and the efficacy is poor, and the drug classification needs to be adjusted and alternative drugs need to be searched for.

[0012] Furthermore: The standard deviation JB of the i-th drug dosage i has the following calculation formula: ; ; Where: J k is the drug dosage of the k-th person, and J k reflects the actual dosage of taking the i-th drug once within a current period of time; J avg is the average drug dosage, and J avg reflects the average degree of the actual dosages of taking the i-th drug once by n patients within a current period of time.

[0013] Furthermore: The content YF of the i-th drug component i is measured by using analytical instruments such as high performance liquid chromatography, gas chromatography, and mass spectrometry. These devices can accurately measure the concentration of specific chemical components in the drug, so as to obtain the content of the active ingredient. The specific implementation method is as follows: Sample preparation: Extract the active ingredient from the i-th drug preparation, and the extraction includes steps of dissolution, filtration, and concentration; Instrument analysis: Inject the sample of the i-th drug preparation after extraction and treatment into the analytical instrument, and perform separation and detection using specific chromatographic and mass spectrometric conditions; Data processing: Calculate the content of the active ingredient according to the signal output by the instrument through data processing software.

[0014] Furthermore, the devices used by the data collection and processing module include a database management system and network devices; The devices used by the hierarchical classification module include a computer, a server, and data processing software; The devices used by the data analysis module include data analysis software; The devices used by the analysis visualization module include a display.

[0015] The effects of the above solution are as follows: 1. The database management system of the present invention has established a drug side effect database and achieved real-time docking with clinical data. By regularly collecting and analyzing the medication feedback and adverse reactions of patients over a certain period of time, it can timely update the i-th drug side effect index FZ of the i-th drug i , so as to ensure that the calculation result of the i-th drug efficacy evaluation value YWL i is more accurate and reliable.

[0016] 2. In the calculation of the i-th drug efficacy evaluation value YWL of the present invention i , the difference between the recommended drug dose standard and the individual dose fluctuation of the patient existing in the i-th drug dose J i and the i-th drug dose standard deviation JB i is introduced to more comprehensively evaluate the efficacy and safety of the drug, which helps to more accurately determine the classification level of the drug and provide more scientific medication advice.

[0017] 3. According to the result of the i-th drug optimization adjustment coefficient DT of the guiding drug library adjustment unit i , the drug library can be dynamically adjusted and optimized. For drugs with a relatively low median, if the i-th drug efficacy evaluation value YWL i is low, its efficacy can be optimized by adjusting the active ingredient content and recommended dose. If the i-th drug classification level index DJ i is low for a long time, an alternative drug needs to be found. This cyclic optimization mechanism helps to continuously optimize the management of the drug library and improve the drug treatment effect and economy.

[0018] In addition, the arrangement of all drugs and the results of optimization adjustment are displayed in the form of charts, which is convenient to intuitively understand the status and trend of the drug library. At the same time, the system also provides an intelligent decision support function, and provides personalized medication advice and management solutions according to the evaluation results and management requirements of the drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flowchart of the method of this hierarchical classification management system; Figure 2It is a schematic diagram of the overall structure module of this hierarchical classification management system; Figure 3 It is a schematic diagram of the structure of the hierarchical classification management module in the present invention; Figure 4 It is the optimization adjustment coefficient DT of the i-th drug among all drugs in the present invention i Arrangement schematic diagram. Specific implementation mode

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely introduced in conjunction with the accompanying drawings in the embodiments of the present invention.

[0021] Example 1, please refer to Figures 1 - 4 , A hierarchical classification management system based on a coronary heart disease drug library in cardiology department, including a data collection and processing module, a hierarchical classification module, a data analysis module, and an analysis visualization module, characterized in that: The data collection and processing module classifies and collects the classification data of all drugs used to treat coronary heart disease in cardiology department within a current period of time, and transmits it to the hierarchical classification module; The hierarchical classification module sequentially calculates and outputs the efficacy evaluation value YWL of the i-th drug among all drugs i , The classification level index DJ of the i-th drug i , The optimization adjustment coefficient DT of the i-th drug i ; The data analysis module arranges the optimization adjustment coefficient DT of the i-th drug calculated and output for all drugs, and performs optimization adjustment on the hierarchical classification management of the i-th drug with a low value below the median; i The analysis visualization module displays the arrangement and optimization adjustment results of all drugs; Among them, the hierarchical classification module includes a unit for judging the pros and cons of drug efficacy, a unit for dividing drug classification levels, and a unit for guiding drug library adjustment; When calculating the efficacy evaluation value YWL of the i-th drug , It includes the input of regularly updated data on the adverse reaction feedback of patients within a current period of time; i The devices used by the data collection and processing module include a database management system and network devices; The devices used by the hierarchical classification module include a computer, a server, and data processing software; The devices used by the data analysis module include data analysis software; The devices used by the analysis visualization module include a monitor.

[0022] ​In this embodiment, through the cooperation among modules, units, and devices, and the clear calculation purposes of the unit for judging the quality of drug efficacy, the unit for classifying drug grades, and the unit for guiding the adjustment of the drug library, they jointly constitute the core algorithm of the hierarchical classification management system for the coronary heart disease drug library in the department of cardiology. The design and application of these formulas help to be more scientific and reasonable when selecting drugs, and at the same time provide strong support for the optimization and adjustment of the drug library.

[0023] Please refer to Figures 1 - 4 , the calculation formula of the unit for judging the quality of drug efficacy is as follows: ; Wherein: YWL i is the evaluation value of the efficacy of the i-th drug; YF i is the content of the i-th drug component, and YF i reflects the content of the active ingredient used for therapeutic effects in the i-th drug; J i is the dose of the i-th drug, and J i reflects the dose marked on the medicine box and recommended for single use of the i-th drug; JB i is the standard deviation of the dose of the i-th drug, and JB i reflects the degree of fluctuation of the dose in the actual quality; FZ i is the side effect index of the i-th drug; In, the dose J of the i-th drug i is fixed, and the standard deviation JB of the dose of the i-th drug i has fluctuating changes, while is a comprehensive consideration of the recommended dose and its fluctuation. Therefore, the square root calculation is to weaken the sum of the standard deviation JB of the dose of the i-th drug i after the fluctuating effect and the dose J of the i-th drug i ; The calculation formula of the standard deviation JB of the dose of the i-th drug i is as follows: ; ; Wherein: J k is the drug dose of the k-th person, and J k reflects the actual dose of taking the i-th drug once within a current period of time; J avg is the average drug dose, and J avg reflects the average degree of the actual doses of taking the i-th drug once by n patients within a current period of time; Content YF of the i-th drug ingredient i It is measured by using analytical instruments such as high performance liquid chromatography, gas chromatography and mass spectrometry. These devices can accurately measure the concentration of specific chemical components in the drug, so as to obtain the content of the active ingredient. The specific implementation method is as follows: Sample preparation: Extract the active ingredient from the i-th drug preparation. The extraction includes steps of dissolution, filtration and concentration; Instrument analysis: Inject the sample of the i-th drug preparation after extraction and treatment into the analytical instrument, and use specific chromatographic and mass spectrometric conditions for separation and detection; Data processing: Calculate the content of the active ingredient according to the signal output by the instrument through data processing software.

[0024] This embodiment first The calculation part of the square root operation is used to represent the "comprehensive" effect. Especially when dealing with fluctuating data, the purpose of this calculation part is to evaluate the drug effect under the content of unit active ingredient. By dividing the content YF of the i-th drug ingredient i by the comprehensive value of the recommended dose and its fluctuation, an index reflecting the drug efficiency can be obtained. The higher this index is, the higher the efficiency of the active ingredient of the drug is within the given dose fluctuation range. Thus, combined with the overall formula of the calculation part which comprehensively evaluates the actual efficacy of the drug by subtracting the side effect index from the unit active ingredient efficiency, aiming to obtain an index that can accurately reflect the quality of the drug efficacy, providing a basis for the classification and management of drugs; In this algorithm unit, the evaluation value YWL of the i-th drug efficacy i not only considers the active ingredient and recommended dose of the drug, but also introduces the dose standard deviation to reflect the dose fluctuation, and at the same time deducts the influence of side effects, so as to more comprehensively and accurately evaluate the drug efficacy; This algorithm unit can judge the quality of the drug efficacy according to the size of the evaluation value YWL of the i-th drug efficacy i so as to be more scientific and reasonable when selecting drugs. A drug with a high evaluation value YWL of the i-th drug efficacy i usually means better efficacy, less side effects, and the evaluation value YWL of the i-th drug efficacy i can be used as one of the indicators for drug screening and optimization. By adjusting the content of the active ingredient, recommended dose, etc. of the drug, the evaluation value YWL of the i-th drug efficacy i value can be increased, so as to improve the efficacy and safety of the drug.

[0025] Please refer to Figures 1 - 4 , and the calculation formula of the drug classification and grading unit is as follows: ; Wherein: DJ i is the classification level index of the i-th drug; ZB i is the treatment cost of the i-th drug; YWL max is the maximum value of drug efficacy evaluation, and YWL max reflects the maximum value of the efficacy evaluation value YWL of the i-th drug calculated and output among all drugs for treating coronary heart disease in cardiology; i of; The result of the division represents the recommended dose required per unit of active ingredient, that is, the dose efficiency of the drug.

[0026] In this embodiment, first In the calculation part, the result of the division represents the recommended dose required per unit of active ingredient, that is, the dose efficiency of the drug. Adding this result to the treatment cost ZB of the i-th drug i is a comprehensive consideration of the drug dose efficiency and cost. The calculation part combines two important factors, the drug treatment cost and the dose efficiency, evaluates the drug from the economic and drug utilization perspectives, and then multiplies it by the efficacy evaluation value YWL of the i-th drug i to combine the drug efficacy evaluation index with this comprehensive consideration, thereby obtaining a drug classification level index that takes into account both efficacy and cost and dose efficiency; The calculation part then considers the influence of the ratio of the efficacy evaluation value YWL of the i-th drug i to the maximum value of drug efficacy evaluation YWL max on the treatment cost ZB of the i-th drug i where starting from the relativity of drug efficacy, the calculation part considers the influence of the drug's position in the overall efficacy level on the cost, and subtracting this part of the influence can combine the influence between the cost and efficacy of the i-th drug to calculate the classification level index DJ of the i-th drug i ; In this algorithm unit, the classification level index DJ of the i-th drug i subdivides drugs into different levels by comprehensively considering multiple factors such as drug efficacy, treatment cost, and the ratio of active ingredient to recommended dose, which helps to more accurately match the needs of patients when choosing drugs. The classification level index DJ of the i-th drug i with a high value usually means better performance in terms of efficacy, treatment cost, and safety, so it can be used as an important basis for optimizing drug selection; This algorithm unit can reduce the medical costs of patients and improve the utilization efficiency of medical resources while ensuring the treatment effect by giving priority to drugs with a higher classification level index DJ of the i-th drug. i For drugs with a high classification level index DJ, while ensuring the treatment effect, it can reduce the medical costs of patients and improve the utilization efficiency of medical resources.

[0027] Please refer to Figures 1 - 4 , and the calculation formula for guiding the drug library adjustment unit is as follows: ; T = (ZB avg / ZB i ) × a; Where: DT i is the optimization adjustment coefficient of the i-th drug; YF avg is the average component content of the drug. YF avg reflects the average degree of component content among all drugs for treating coronary heart disease in cardiology; ZB avg is the average treatment cost of the drug. ZB avg reflects the average degree of treatment cost among all drugs for treating coronary heart disease in cardiology; T is the adjustment factor used to adjust the influence of the treatment cost on the optimization adjustment coefficient DT i of the i-th drug; a is the adjustment coefficient, and its value range is {0.2 - 0.8}. It is proportioned in the value range of {0.2 - 0.8} according to the high and low order of calculating the optimization adjustment coefficient DT i of the i-th drug for all drugs in the previous calculation and arranging them: The value of the i-th drug with a high ranking tends to 0.8; The value of the i-th drug with a low ranking tends to 0.2.

[0028] In this embodiment, first In the calculation part, under the square root is also to emphasize the influence of dose fluctuation on the drug effect. This result is divided by the difference of i to consider the difference between the unit effective component and the average effective component on the optimization adjustment coefficient DT i of the i-th drug under the comprehensive effect of dose and its fluctuation. The higher this ratio, the greater the optimization space for the effective component content of the drug relative to the average level within the dose fluctuation range. The calculation part starts from the drug component difference and dose factors to provide a basis for judging the optimization adjustment requirements of the drug in the drug library, and then the result of the calculation part is combined with the classification level index DJ iMultiply and add to classify the classification level index DJ of the i-th drug i Combined with this optimization and adjustment requirement based on dose fluctuation and active ingredient difference, a coefficient that comprehensively reflects the optimization and adjustment requirement of the drug is obtained. The higher this coefficient, the greater the optimization and adjustment requirement of the drug in the drug library. It should be noted that, compared with the classification level index DJ of the i-th drug i Multiplying and then adding can ensure that when calculating the drug optimization and adjustment coefficient, both the comprehensive characteristics of the drug itself, that is, reflected by the classification level index DJ of the i-th drug i are considered, and the differences in ingredient content and treatment cost compared with other drugs are also considered, that is the calculation part, so as to provide an accurate basis for the hierarchical classification management and dynamic adjustment of the drug library. Removing the addition part will destroy this logical integrity, making the calculation result unable to accurately reflect the true state of the drug in the drug library and the required adjustment direction and degree; In the calculation part, the treatment cost ZB of the i-th drug i divided by the sum represents the comprehensive consideration of the treatment cost of the drug relative to the average cost and the adjustment factor T. Multiplying this result by the classification level index DJ of the i-th drug i is to combine the classification level index DJ of the i-th drug i with this optimization and adjustment requirement based on treatment cost and adjustment factor, The calculation part starts from the perspective of drug cost, and the introduction of the adjustment factor T is to adjust the influence degree of the treatment cost on the optimization and adjustment coefficient DT of the i-th drug i so that it better meets the requirements in practical applications, and this calculation part aims to reflect the optimization and adjustment requirement of the drug in terms of treatment cost; In this algorithm unit, the optimization and adjustment coefficient DT of the i-th drug i can be used as one of the important indicators for the hierarchical classification management of the drug library. By sorting the values of the optimization and adjustment coefficient DT of the i-th drug i , drugs that need optimization and adjustment can be identified, thereby guiding the management and update of the drug library. When multiple drugs are used in combination, by comparing the C values of the optimization and adjustment coefficients DT of different drugs i of the i-th drug, the drug combination can be optimized to improve the overall treatment effect and safety. Among them, for drugs with low values of the optimization and adjustment coefficient DT of the i-th drug i , the values of the optimization and adjustment coefficient DT of the i-th drug can be increased by developing new drugs and improving existing drugs i , thereby promoting the continuous innovation and development of drugs.

[0029] Please refer to Figures 1 - 4, instruct the drug library adjustment unit to optimize and adjust the DT of the i-th drug among all drugs i Perform calculation and output, classify and grade them according to the magnitude arranged from left to right by the value, and based on the setting that the low values below the median need to be adjusted, analyze each i-th drug one by one, and the specific analysis is as follows: If for the i-th drug among all drugs, the therapeutic effect evaluation value YWL of the i-th drug i is at a low value, it indicates that the therapeutic effect of the i-th drug is insufficient, and the composition and dosage of the i-th drug are optimized and adjusted according to the dosage fluctuation and side effect conditions; If for the i-th drug among all drugs, its classification grade index DJ of the i-th drug i has been at a low value for a long time, it indicates that the treatment cost of the drug is high and the therapeutic effect is poor, and the drug classification needs to be adjusted and alternative drugs need to be searched.

[0030] This algorithm unit can continuously improve the therapeutic effect evaluation value YWL of the i-th drug by continuously adjusting and optimizing the content of the active ingredient and the recommended dosage parameter of the drug i , thereby improving the therapeutic effect and safety of the drug, and the formed cyclic influence mechanism makes the management of the drug library more dynamic and flexible, can adjust and optimize the drug combination in a timely manner according to actual needs, improve the efficiency and effect of drug management. In addition, by continuously optimizing the management of the drug library and the drug combination, the overall medical quality can be improved, the medical risks and economic burdens of patients can be reduced, and the satisfaction and sustainability of medical services can be enhanced; Specifically, by classifying and grading the drugs and outputting the DT of the i-th drug for each drug i , the drugs suitable for patients can be selected more quickly and accurately. This classification and grading method makes the drug selection process more systematic and standardized, reduces the subjectivity and uncertainty of doctors in drug selection. At the same time, focusing on and optimizing the drugs with relatively low median can further improve the pertinence and effectiveness of drug selection; For the drugs with low therapeutic effect evaluation value YWL of the i-th drug i , by increasing the content of the active ingredient and adjusting the recommended dosage, the therapeutic effect of the drug can be significantly improved. This optimization strategy not only improves the treatment effect of the drug, but also reduces the treatment failure and patient pain caused by poor drug efficacy. At the same time, this also provides new ideas and methods for drug research and development, and helps to promote the progress and innovation of drug research and development; For the long-term classification grade index DJ of the i-th drug iFor drugs with low efficacy, that is, drugs with high treatment costs and poor efficacy, alternative drugs are sought to reduce costs and improve efficacy, thereby alleviating the economic burden on patients. This alternative strategy not only helps to achieve the rational use of drugs, but also promotes the optimal allocation of medical resources. At the same time, it also provides a reference basis for drug policy formulation, contributing to the reform and improvement of the medical system; In summary, optimizing drug classification and grading and comprehensively applying the strategies mentioned above have significant beneficial effects on the selection and treatment effect of drugs for coronary heart disease in the cardiology department. The implementation of this strategy not only improves the drug selection efficiency and efficacy, but also reduces the treatment cost, enhances patient satisfaction and safety, and promotes the progress and innovation of medical technology. Therefore, this strategy is worthy of wide promotion and application in the medical field.

[0031] Example 2. Please refer to Figures 1 - 4 , the classification and grading module, in cooperation with the data collection and processing module, needs to regularly update the side effects of all drugs to reflect the adverse reaction feedback of patients during a certain period. This generally includes the following steps: Data collection: Collect the number of various adverse reactions F that occur in patients during the process of taking the i-th drug, and the total number of people n taking the i-th drug during a certain period; Data analysis: Statistically analyze the number of adverse reactions F and the total number of people n collected, and use the calculation formula of FZ i =F / n to calculate the incidence of adverse reactions of all drugs; Index update: According to the analysis and calculation results, update FZ i to reflect the current adverse reaction situation.

[0032] In this embodiment, regularly updating the side effect index FZ i of the i-th drug can ensure the accuracy and timeliness of drug safety assessment. With the continuous accumulation of new data, the understanding of drug side effects will be deeper, enabling a more accurate assessment of drug risks. The drug vigilance system aims to monitor the safety issues of drugs during use. Regularly updating the side effect index FZ i of the i-th drug helps to detect and report new and serious side effects in a timely manner, thus promoting the improvement of the drug vigilance system; For drugs under research or optimization, regularly updating the side effect index FZ i of the i-th drug can provide key safety information to help make more informed decisions. And by regularly updating the side effect index FZ i of the i-th drug, medical institutions can more accurately evaluate the safety risks of different drugs, thereby optimizing the allocation of medical resources; In summary, the side effect index FZ of the i-th drugi The regular updates have multiple beneficial effects, including improving the accuracy of drug safety assessment, promoting the improvement of the pharmacovigilance system, supporting drug R & D and optimization, enhancing patient confidence and compliance, and optimizing the allocation of medical resources. These beneficial effects together promote the safety and effectiveness of drug use.

[0033] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the scope defined by the claims.

Claims

1. A hierarchical classification management system based on a coronary heart disease drug library for the Department of Cardiology, comprising a data collection and processing module, a hierarchical classification module, a data analysis module, and an analysis visualization module, characterized in that: The data collection and processing module classifies and collects the classification data of all types of drugs used to treat coronary heart disease in the Department of Cardiology within a current period of time, and transmits it to the hierarchical classification module; The hierarchical classification module sequentially calculates and outputs the efficacy evaluation value YWL of the i-th drug for all drugs i , the classification level index DJ of the i-th drug i , the optimization adjustment coefficient DT of the i-th drug i ; The data analysis module arranges the optimization adjustment coefficients DT of the i-th drug calculated and output for all drugs, and optimizes and adjusts the classification management of the i-th drug with a low value below the median; i ​ The analysis visualization module displays the results of arranging and optimizing all drugs; Among them, the hierarchical classification module includes a unit for judging the pros and cons of drug efficacy, a unit for dividing drug classification levels, and a unit for guiding the adjustment of the drug library; When calculating the efficacy evaluation value YWL of the i-th drug i it includes the input of regularly updated data on the adverse reaction feedback of patients during a current period of time.

2. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 1, wherein: The hierarchical classification module cooperates with the data collection and processing module to regularly update the side effects of all types of drugs to reflect the adverse reaction feedback of patients in the current period of time, including the following steps: Data collection: Collect the number of various adverse reactions F that occur during the use of the i-th drug by patients, and the total number of people n who use the i-th drug in the current period of time; Data analysis: Statistically analyze the number of adverse reactions F and the total number of people n collected, and use the calculation formula of FZ i = F / n to calculate the incidence rate of adverse reactions of all drugs; Index update: Based on the analysis calculation results, update FZ i to reflect the current adverse reaction situation.

3. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 2, wherein: The calculation formula of the unit for judging the pros and cons of drug efficacy is as follows: ； Among them: YWL i is the evaluation value of the efficacy of the i-th drug; YF i is the content of the i-th drug component, YF i reflects the content of the active ingredient used for therapeutic effect in the i-th drug; J i is the dose of the i-th drug, J i reflects the dose of the i-th drug labeled and recommended for single use on the medicine box; JB i is the standard deviation of the i-th drug dose, JB i reflecting the degree of fluctuation of the dose in the actual quality; FZ i is the side effect index of the i-th drug; the dose J of the i-th drug in i is fixed, and the standard deviation JB of the dose of the i-th drug i has fluctuating changes, while is calculated as a weakening of the sum of the standard deviation JB of the dose of the i-th drug i after the fluctuating effect is generated and the dose J of the i-th drug i and.

4. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 3, characterized in that: The calculation formula of the unit for dividing drug classification levels is as follows: ； Among them: DJ i is the classification level index of the i-th drug; ZB i is the treatment cost of the i-th drug; YWL max Is the maximum value for drug efficacy evaluation, YWL max Among all drugs for treating coronary heart disease in cardiology, calculate and output the maximum value of the efficacy evaluation value YWL of the i-th drug i ; The result of the division represents the recommended dose required for the unit active ingredient, that is, the dose efficiency of the drug.

5. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 4, wherein: The calculation formula of the unit for guiding the adjustment of the drug library is as follows: ； T = (ZB avg / ZB i ) × a; Among them: DT i Optimization adjustment coefficient for the i-th drug; YF avg is the average component content of the drug, YF avg reflects the average degree of component content in all drugs for treating coronary heart disease in the department of cardiology; ZB avg is the average treatment cost of drugs, ZB avg reflecting the average level of treatment costs among all drugs for treating coronary heart disease in the cardiology department; T is a regulatory factor used to adjust the impact of the treatment cost on the optimization adjustment coefficient DT of the i-th drug i ; a is an adjustment coefficient, and its value range is {0.2 - 0.8}, which is based on the optimized adjustment coefficient DT of the i-th drug calculated for all drugs in the previous time i , and perform a ratio matching in the value range {0.2 - 0.8} according to the high - low order of their arrangement: The value of the i-th drug with a high ranking tends to be 0.8; The value of the i-th drug with a low ranking tends to be 0.

2.

6. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 5, characterized in that: The guiding drug library adjustment unit calculates and outputs the optimization adjustment coefficient DT of the i-th drug among all drugs, classifies them hierarchically according to the magnitude arranged from left to right in descending order of values, and analyzes each i-th drug one by one based on the setting that low values below the median need to be adjusted. The analysis is as follows: i And based on the setting that low values below the median need to be adjusted, each i-th drug is analyzed one by one. The analysis is as follows: If the evaluation value YWL of the i-th drug in all drugs is i at a low value, it indicates that the efficacy of the i-th drug is insufficient, and the composition and dosage of the i-th drug are optimized and adjusted according to the dose fluctuation and side effects; If the classification level index DJ of the i-th drug among all drugs is i constantly at a low value for a long time, it indicates that the treatment cost of the drug is high and the efficacy is poor, and it is necessary to adjust the drug classification and find alternative drugs.

7. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 3, wherein: The standard deviation JB of the i-th drug dose i is calculated as follows: ； ； Among them: J k is the drug dose for the k-th person, J k reflects the actual dose of taking the i-th drug once during the current period of time; J avg is the average drug dose, J avg reflects the average degree of the single and actual doses of the i-th drug taken by n patients during a current period of time.

8. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 3, characterized in that: The content YF of the i-th drug component i It is measured by using analytical instruments such as high performance liquid chromatography, gas chromatography, and mass spectrometry. These devices accurately measure the concentration of specific chemical components in the drug to obtain the content of the active ingredient. The specific implementation method is as follows: Sample preparation: Extract the active ingredient from the i-th drug preparation, and the extraction includes steps of dissolution, filtration, and concentration; Instrument analysis: Inject the sample of the processed i-th drug preparation into the analysis instrument, and perform separation and detection using specific chromatographic and mass spectrometric conditions; Data processing: Calculate the content of the active ingredient according to the signal output by the instrument through data processing software.

9. The hierarchical classification management system based on the coronary heart disease drug library in the department of cardiology according to claim 1, characterized in that: The devices used by the data collection and processing module include a database management system and network devices; The devices used by the hierarchical classification module include a computer, a server, and data processing software; The devices used by the data analysis module include data analysis software; The devices used by the analysis visualization module include a display.

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