Basic medicine use tendency assessment method, equipment, medium and product

Abstract

The invention relates to the technical field of medical evaluation, in particular to a basic drug use tendency evaluation method and device, a medium and a product. The method comprises the following steps: acquiring a disease type, a patient specific attribute and medication information of a target patient; according to a standard evidence-based intensity database, determining intermediate evidence-based intensity of each drug type in the medication information in disease types, patient specific attributes and medication schemes; obtaining attribute information of a target hospital seeing a doctor by the target patient, and adjusting the intermediate evidence-based intensity based on the attribute information to obtain the actual evidence-based intensity of the target patient; determining the average standard evidence-based intensity of each base drug type corresponding to the disease type; and calculating a difference value between the actual evidence-based intensity and the average standard evidence-based intensity as a base drug use tendency degree, and generating a drug use rationality evaluation result for the target patient according to the base drug use tendency degree. According to the invention, multi-dimensional evaluation can be carried out on the drug use rationality of the patient, and the accuracy of the evaluation result is improved.

Description

Technical Field

[0001] This application relates to the technical field of medical evaluation, and particularly to a method, device, medium and product for evaluating the propensity to use essential medicines. Background Art

[0002] The evaluation of the rationality of drug use is a core link in medical quality management, aiming to ensure that patients receive safe, effective and economically appropriate drug treatment. With the exponential growth of medical data and the increasing complexity of clinical diagnosis and treatment, the traditional empirical medication model has been difficult to meet the needs of precision medicine. Especially in the field of essential medicines, the evaluation of rational drug use not only concerns the treatment effect of individual patients, but also directly affects the allocation efficiency of regional medical resources and the sustainability of medical insurance funds.

[0003] Related technologies use a static evaluation method based on guidelines to evaluate the rationality of drug use, and judge by comparing the compliance of prescriptions with clinical guidelines. For example, the AWaRe (Access, Watch, Reserve) antibiotic classification evaluation tool of the WHO. Although such methods can ensure basic standardization, the evaluation dimension is single, and the impact of differences in medical institution resources and patient physical conditions on the feasibility of drug use is not considered, and the evaluation of the real drug use quality is not reasonable enough. Summary of the Invention

[0004] In order to solve the problem that the evaluation dimension of the rationality of patients' drug use in the prior art is single, resulting in inaccurate evaluation results, this application provides a method, device, medium and product for evaluating the propensity to use essential medicines.

[0005] In the first aspect, this application provides a method for evaluating the propensity to use essential medicines, adopting the following technical solution: A method for evaluating the propensity to use essential medicines, comprising: Obtain the disease type, patient-specific attributes and medication information of the target patient, where the target patient is any patient in any hospital within the target area, and the medication information includes the drug type and the medication plan; According to the standard evidence strength database, determine the intermediate evidence strength of each drug type in the medication information for the disease type, the patient-specific attributes and the medication plan; Obtain the attribute information of the target hospital where the target patient seeks medical treatment, and adjust the intermediate evidence strength based on the attribute information to obtain the actual evidence strength of the target patient; Determine the average standard evidence strength of each essential drug type corresponding to the disease type; Calculate the difference between the actual evidence-based intensity and the average standard evidence-based intensity as the essential medicine usage tendency, and generate a drug usage rationality evaluation result for the target patient according to the essential medicine usage tendency.

[0006] By adopting the above technical solution, the intermediate evidence-based intensity is determined by combining the patient's disease type, individual attributes and medication plan, and then the actual evidence-based intensity is adjusted based on the hospital's medical capabilities. By comparing with the standard intensity of essential medicines, the tendency is generated, which can scientifically judge whether the use of essential medicines is sufficient and reasonable. Introducing the evidence-based medicine evidence grading can improve the scientificity of evaluation, integrating the patient's individual characteristics and the hospital environment to achieve multi-level precise evaluation, quantifying the difference to provide an intuitive basis for management, helping to identify the abuse of non-essential medicines, optimize the configuration of essential medicines and save medical insurance funds, and at the same time providing forward-looking guidance for the management of essential medicine use in hospitals and departments.

[0007] In a preferred example, the present application can be further configured as: the method further includes: Based on the OCEBM evidence grading standard, determine the evidence level and evidence type of the target drug type for the target disease type, where the target drug type is any drug type, and the target disease type is any disease type applicable to the target drug type; Match the evidence level and evidence type of the target drug type for the target disease type with a preset scoring standard to determine the standard evidence-based intensity of the target drug type for the target disease type. The higher the standard evidence-based intensity, the higher the medical evidence support degree of the target drug type for the target disease type; Store the target drug type, the target disease type and the corresponding standard evidence-based intensity as a standard data, and construct the standard evidence-based intensity database according to the standard data corresponding to each drug type.

[0008] By adopting the above technical solution, a unified and scientific evidence quantification system is established based on the OCEBM evidence grading standard, enabling the medical evidence support degree of drugs to be measured standardly, providing an objective benchmark for the evaluation of essential medicine use; by structurally storing drug, disease and corresponding intensity data, a dynamically updatable database is formed to ensure the normativity and timeliness of the evaluation benchmark.

[0009] In a preferred example, the present application can be further configured as: the determining of the intermediate evidence-based intensity of each drug type in the medication information for the disease type, the patient-specific attributes and the medication plan according to the standard evidence-based intensity database includes: For each drug type in the medication information, extract the standard evidence-based intensity of the drug type for the disease type from the standard evidence-based intensity database as the first evidence-based intensity; Retrieve the medication guide for the drug type, and adjust the first evidence-based strength based on the medication guide, the patient-specific attributes, and the medication regimen to obtain the second evidence-based strength; Calculate the average value of the second evidence-based strength of each drug type in the medication information as the intermediate evidence-based strength.

[0010] By adopting the above technical solution, the scientificity of the evaluation starting point is ensured with the database benchmark value, the compliance of drug indications and regimens is verified through the medication guide, and the evidence strength is dynamically adjusted in combination with patient-specific attributes, making the second evidence-based strength more in line with the actual clinical scenario; by calculating the average value, the evidence-based level of the patient's overall medication is comprehensively reflected, avoiding the influence of single-drug deviation on the evaluation result, and improving the accuracy and clinical applicability of the intermediate evidence-based strength.

[0011] In a preferred example of the present application, it can be further configured that: the retrieving the medication guide for the drug type, and adjusting the first evidence-based strength based on the medication guide, the patient-specific attributes, and the medication regimen to obtain the second evidence-based strength includes: Based on the medication guide and the patient-specific attributes, determine whether the drug type is applicable to the target patient to obtain a first determination result; Based on the medication guide and the medication regimen, determine whether there are non-compliance indicators in the medication regimen to obtain a second determination result; Based on the first determination result and the second determination result, adjust the first evidence-based strength to obtain the second evidence-based strength of the drug type.

[0012] By adopting the above technical solution, through the first determination result (drug applicability), contraindications or inapplicable situations (such as a certain drug being contraindicated for pregnant women) are excluded to ensure the basis of medication safety; through the second determination result (regimen compliance), risks such as dose overlimit and abnormal treatment course (such as excessive use of antibiotics) are identified, and the weakening of the evidence strength caused by non-compliant behaviors is quantified; based on the dual determination, the first evidence-based strength is adjusted, making the second evidence-based strength truly reflect the actual evidence support degree of the drug in a specific patient.

[0013] In a preferred example of the present application, it can be further configured that: the adjusting the intermediate evidence-based strength based on the attribute information to obtain the actual evidence-based strength of the target patient includes: Obtain the attribute information of each hospital in the target area, and the attribute information of each hospital includes multiple evaluation indicators; For each evaluation indicator, sort the hospitals from good to bad according to the evaluation indicator to obtain the evaluation list of the evaluation indicator, and determine the position of the target hospital in the evaluation list. Based on the position of the target hospital in the evaluation lists of the multiple evaluation indicators, determine the evidence-based strength adjustment value of the target hospital; Adjust the intermediate evidence-based strength based on the adjusted value of the evidence-based strength to obtain the actual evidence-based strength of the target patient.

[0014] By adopting the above technical solution, an objective hospital capacity evaluation system is constructed through multi-dimensional indicators, avoiding the problem of the disconnection between the evidence strength standard and the hospital's execution ability; ranking the target hospitals according to the quality of the indicators and positioning them, enabling the adjusted value of the evidence-based strength to accurately reflect the relative ability level of the hospital in the region, and correcting the intermediate evidence-based strength based on the adjusted value to ensure that the actual evidence-based strength not only meets the evidence-based medicine standard but also conforms to the hospital's true execution ability.

[0015] In a preferred example, the present application can be further configured as: the generating of the drug use rationality evaluation result for the target patient according to the essential medicine use tendency includes: Retrieve the drug use rationality evaluation standard; Based on the drug use rationality evaluation standard, judge the rationality determination result and the corresponding level of the essential medicine use tendency of the target patient. The rationality determination result is that the essential medicine use is reasonable or the essential medicine use is doubtful, and the level is the rationality level or the doubt level.

[0016] By adopting the above technical solution, relying on the preset evaluation standard, the abstract rationality judgment is transformed into an operable quantitative rule, avoiding the subjectivity of manual evaluation; the determination result (reasonable / doubtful) and the level are directly mapped through the essential medicine use tendency (the difference between the actual evidence-based strength and the standard value), making the evaluation conclusion intuitive and clear, facilitating clinicians to quickly identify medication problems, and the grading result can be further associated with intervention measures.

[0017] In a preferred example, the present application can be further configured as: the method further includes: According to the essential medicine use tendency of each patient in the target area, determine the hospital tendency of each hospital in the target area and the department tendency of each department in the target hospital; Based on the hospital tendency and the department tendency, generate the drug use rationality evaluation result for the target hospital and each department in the target hospital; Calculate the historical hospital tendency of the target hospital, and predict the predicted hospital tendency in the next cycle based on the historical hospital tendency. The predicted hospital tendency is used as the essential medicine allocation guidance for the target hospital.

[0018] By adopting the above technical solutions, by accurately evaluating the use of essential medicines in hospitals / clinical departments and determining whether doctors abuse medicines outside the essential medicine list, it is possible to save medical insurance funds for the national medical insurance, which has unique value and innovation in medical insurance management; it provides guidance for the allocation of national essential medicine application indicators in the next cycle, which goes beyond the simple retrospective analysis of traditional methods and has forward-looking nature, and helps to more reasonably plan and manage the use of essential medicines.

[0019] In a second aspect, the present application provides an electronic device, adopting the following technical solutions: One or more processors; A memory; At least one application program, wherein at least one application program is stored in the memory and is configured to be executed by at least one processor, and the at least one application program is configured to: execute the essential medicine use propensity evaluation method according to any one of the first aspects.

[0020] In a third aspect, the present application provides a computer-readable storage medium, adopting the following technical solutions: A computer-readable storage medium, on which a computer program is stored. When the computer program is executed on a computer, the computer is made to execute the essential medicine use propensity evaluation method according to any one of the first aspects.

[0021] In a fourth aspect, the present application provides a computer program product, adopting the following technical solutions: A computer program product, including a computer program. When the computer program is executed by a processor, it implements the essential medicine use propensity evaluation method according to any one of the first aspects.

[0022] In summary, the present application includes the following beneficial technical effects: The present application determines the intermediate evidence-based intensity by combining the patient's disease type, individual attributes and medication plan, and then adjusts it based on the hospital's medical capabilities to obtain the actual evidence-based intensity. By comparing with the standard intensity of essential medicines, the propensity is generated, which can scientifically judge whether the use of essential medicines is sufficient and reasonable. Introducing the grading of evidence-based medicine evidence improves the scientificity of evaluation, integrates the patient's individual characteristics and the hospital environment to achieve multi-level precise evaluation, and quantifies the difference to provide an intuitive basis for management, which helps to identify the abuse of non-essential medicines, optimize the configuration of essential medicines and save medical insurance funds, and at the same time provides forward-looking guidance for the management of essential medicine use in hospitals and departments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic flowchart of an essential medicine use propensity evaluation method provided by an embodiment of the present application; Figure 2 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0024] The following will further describe the present application in detail with reference to the Figure 1 to the Figure 2 accompanying drawings.

[0025] This specific embodiment is only an interpretation of the present application, and it does not limit the present application. After reading this specification, those skilled in the art can make modifications to this embodiment without creative contributions as needed, but as long as it is within the scope of the claims of the present application, it is protected by the patent law.

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0027] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, unless otherwise specified.

[0028] It should be noted that in the alternative embodiments of the present application, for the relevant data such as the object information involved, when the embodiments in the present application are applied to specific products or technologies, object permission or consent needs to be obtained, and the collection, use, and processing of the relevant data need to comply with the relevant laws, regulations, and standards of the relevant countries and regions. That is to say, if the embodiments in the present application involve data related to objects, it needs to be obtained under the authorization and consent of the objects, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations, and standards of the relevant countries and regions. If personal information is involved in the embodiments, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiments also need to be implemented under the authorization and consent of the objects.

[0029] The embodiments of the present application provide a method for evaluating the tendency of using essential drugs, such as Figure 1As shown in the figure, the method provided in the embodiment of the present application is executed by an electronic device, which can be a server or a terminal device. Among them, the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, which are not limited in the embodiment of the present application. The method includes steps S101 - S105, where: S101. Obtain the disease type, patient-specific attributes, and medication information of the target patient. The target patient is any patient in any hospital within the target area, and the medication information includes the drug type and the medication plan.

[0030] Specifically, the target patient is a patient visiting any hospital within the target area (such as a certain province / city), and the target patient is the smallest unit for evaluating the tendency to use essential drugs. The disease type is the disease name or classification determined by diagnosing the target patient, and the disease type can be determined from the patient's electronic medical record. The patient-specific attributes reflect the individual characteristics of the patient, including demographic characteristics (age, gender, weight, pregnancy status, etc.), basic health conditions (allergy history, underlying diseases, etc.). The drug type includes whether it is a national essential drug and the drug name. The medication plan includes the drug name, dosage, frequency of administration, treatment course, etc.

[0031] S102. Determine the intermediate evidence-based intensity of each drug type in the medication information in terms of the disease type, patient-specific attributes, and medication plan.

[0032] Specifically, for any drug type, the applicable disease types may be one or more. When the drug type is applicable to one disease type, the standard evidence-based intensity of the drug type under this disease type is determined based on the evidence grading standard of the Oxford Centre for Evidence-Based Medicine (OCEBM); when the drug type is applicable to multiple disease types, the standard evidence-based intensity of the drug type under each applicable disease type is determined based on the OCEBM evidence grading standard. The standard evidence-based intensity of each drug type under one disease type is stored as a piece of standard data, and the standard data corresponding to each drug type is stored in the standard evidence-based intensity database. The standard evidence-based intensity represents the medical evidence score, which reflects the medical evidence support for the selection of a certain drug under a specific disease type. The greater the standard evidence-based intensity, the greater the medical evidence support. In the past, the evaluation of the use of national essential drugs was more based on experience or simple medication data statistics. However, in this embodiment, based on the OCEBM evidence grading standard, the evidence-based medicine evidence intensity value is introduced into the calculation, making the calculation of the drug use tendency intensity more scientific and reasonable, and being able to more accurately reflect whether the drug use is based on sufficient evidence support.

[0033] The intermediate evidence strength represents the preliminary evidence strength score adjusted based on the standard evidence strength and combined with the individual characteristics of the target patient (disease type, specific attributes, medication regimen), reflecting the evidence suitability of the drug type in the treatment process of the target patient.

[0034] For each drug type in the medication information of the target patient, retrieve the corresponding standard evidence strength of "this drug type + the disease type of the target patient" from the standard evidence strength database as the first evidence strength. Retrieve the medication guidelines for the drug type, and adjust the first evidence strength based on the medication guidelines, patient specific attributes, and medication regimen to obtain the second evidence strength. If the drug type in the medication information of the target patient is one, use the second evidence strength of this drug type as the intermediate evidence strength; if the drug types in the medication information of the target patient are multiple, use the average value of the second evidence strengths of multiple drug types as the intermediate evidence strength.

[0035] S103. Obtain the attribute information of the target hospital where the target patient seeks medical treatment, and adjust the intermediate evidence strength based on the attribute information to obtain the actual evidence strength of the target patient.

[0036] Specifically, the attribute information of the target hospital includes multiple evaluation indicators, such as grade qualification, resource allocation (number of beds, number of intensive care units (ICUs), inspection equipment), personnel structure (ratio of physicians / nurses, proportion of specialist physicians), etc. Obtain the attribute information of multiple hospitals in the target area, determine the evidence strength adjustment value of the target hospital based on the attribute information of multiple hospitals, and adjust the intermediate evidence strength based on the evidence strength adjustment value to obtain the actual evidence strength of the target patient. The actual evidence strength combines the actual capabilities of the hospital, avoiding misjudgment of unreasonable drug use due to insufficient drug accessibility in primary hospitals.

[0037] S104. Determine the average standard evidence strength of each essential drug type corresponding to the disease type.

[0038] Specifically, the essential drug type is the national essential drug type, and the average standard evidence strength represents the ideal evidence level of essential drugs in the treatment of this disease type.

[0039] In one possible case, the average value of the standard evidence strengths of all national essential drug types applicable to this disease type can be extracted from the standard evidence strength database as the average standard evidence strength of this disease type.

[0040] In another possible case, multiple experts can design a national essential drug medication regimen for this disease type, and use the average value of the standard evidence strengths of each national essential drug type in the standard evidence strength database in the medication regimens of multiple experts as the average standard evidence strength of this disease type.

[0041] S105. Calculate the difference between the actual evidence-based intensity and the average standard evidence-based intensity as the essential medicine usage propensity, and generate an evaluation result of the rationality of drug use for the target patient according to the essential medicine usage propensity.

[0042] Specifically, the essential medicine usage propensity = actual evidence-based intensity - average standard evidence-based intensity, which reflects the gap between the evidence-based intensity of the actual medication of the target patient and the ideal level of essential medicines.

[0043] The evaluation criteria for the rationality of drug use include: if the essential medicine usage propensity is a positive value, it is determined that the use of essential medicines is reasonable, indicating that the national essential medicines of the target patient have been fully applied, and the higher the value, the higher the rationality tendency of drug selection in the patient's treatment process; if the essential medicine usage propensity is a negative value, it is determined that the use of essential medicines is in doubt, indicating that the national essential medicines have not been fully applied in the patient's clinical treatment process, and the evidence-based medical evidence of the treatment plan is insufficient, and the rationality of drug selection is in doubt.

[0044] Moreover, the evaluation criteria for the rationality of drug use also include the ranges corresponding to the reasonable level of essential medicine use and the doubtful level of essential medicine use respectively. Matching the essential medicine usage propensity of the target patient with the pre-set range of levels can determine the rationality level or the doubtful level.

[0045] This application proposes a calculation method for the usage propensity intensity of national essential medicines based on the evidence grading of the Oxford Centre for Evidence-Based Medicine (OCEBM). This method calculates the clinical usage propensity intensity of national essential medicines during the patient's hospitalization based on the OCEBM evidence grading standard, thereby calculating the propensity of the hospital / clinical department over a period of time, and then evaluating whether the hospital / clinical department preferentially selects national essential medicines for treatment during this period. It is also possible to calculate the total propensity of each clinical department in the previous year, so as to predict the total propensity of the department in the next year, providing guidance for the allocation of national essential medicine application indicators for the department in the next year. Compared with the traditional method of fine-tuning based on historical data, the evaluation method based on the calculated propensity in this application is more reasonable and guiding, can effectively evaluate whether the national essential medicines in the hospital / clinical department have been fully and reasonably clinically applied, and whether there is a phenomenon of doctors abusing drugs outside the essential medicine list, saving medical insurance funds for the national medical insurance.

[0046] In this embodiment, the intermediate evidence-based intensity is determined by combining the patient's disease type, individual attributes, and medication regimen, and then adjusted based on the hospital's medical capabilities to obtain the actual evidence-based intensity. By comparing with the basic drug standard intensity, the propensity is generated, which can scientifically judge whether the use of basic drugs is sufficient and reasonable. Introducing the evidence grading of evidence-based medicine can improve the scientificity of evaluation, integrate the patient's individual characteristics and the hospital environment to achieve multi-level precise evaluation, and quantify the difference to provide an intuitive basis for management, which helps to identify the abuse of non-basic drugs, optimize the allocation of basic drugs, and save medical insurance funds. At the same time, it provides forward-looking guidance for the management of basic drug use in hospitals and departments.

[0047] A possible implementation manner of the embodiment of the present application, the method further includes: Based on the OCEBM evidence grading standard, determine the evidence level and evidence type of the target drug type for the target disease type, where the target drug type is any drug type, and the target disease type is any disease type applicable to the target drug type; Match the evidence level and evidence type of the target drug type for the target disease type with the preset scoring standard to determine the standard evidence-based intensity of the target drug type for the target disease type. The higher the standard evidence-based intensity, the higher the medical evidence support degree of the target drug type for the target disease type; Store the target drug type, the target disease type, and the corresponding standard evidence-based intensity as a piece of standard data, and construct a standard evidence-based intensity database according to the standard data corresponding to each drug type.

[0048] In this embodiment, the evidence levels of the OCEBM evidence grading standard include: level 1 evidence, level 2 evidence, level 3 evidence, level 4 evidence, and level 5 evidence. The medical evidence support degree decreases in turn from 1 to 5.

[0049] More specifically, each evidence level includes several evidence types. The evidence types of level 1 evidence include: 1a, systematic review of randomized controlled trials (RCTs) (homogeneous high-quality research); 1b, a single high-quality RCT (narrow confidence interval); 1c, all-or-none effect (such as the mortality rate drops from 100% to 0% after intervention). The evidence types of level 2 evidence include: 2a, systematic review of cohort studies (homogeneous high-quality research); 2b, a single cohort study or low-quality RCT (such as follow-up rate < 80%); 2c, outcome studies or ecological studies. The evidence types of level 3 evidence include: 3a, systematic review of case-control studies (homogeneous high-quality research), 3b, a single case-control study. The evidence types of level 4 evidence include: case series, low-quality cohort or case-control studies. The evidence types of level 5 evidence include: expert opinion, basic research (such as cell or animal experiments).

[0050] The preset scoring criteria can be pre-set by medical experts and include the standard scores for each evidence level and each evidence type. Optionally, the standard score for class 1a evidence is 10 points, the standard score for class 1b evidence is 9 points, the standard score for class 1c evidence is 8 points, the standard score for class 2a evidence is 7 points, the standard score for class 2b evidence is 6 points, the standard score for class 2c evidence is 5 points, the standard score for class 3a evidence is 4 points, the standard score for class 3b evidence is 3 points, the standard score for class 4 evidence is 2 points, the standard score for class 5 evidence is 1 point, and 0 points are given if there is no evidence.

[0051] Search existing medical literature, journals, etc. to determine the evidence level and evidence type of the target drug type for the target disease type, and then match it with the preset scoring criteria to determine the standard score of the target drug type for the target disease type. Take the determined standard score as the standard evidence-based strength, and this process can be achieved through artificial intelligence tools.

[0052] Exemplarily, a young male patient was admitted to the hospital due to community-acquired pneumonia and was treated with cefathiamidine. The corresponding national essential medicine is moxifloxacin. Cefathiamidine is not a national essential medicine; moxifloxacin is a national essential medicine.

[0053] For the grading of evidence-based medical evidence on the effectiveness of moxifloxacin in the treatment of adult community-acquired pneumonia, the core evidence types include: High-quality randomized controlled trials (RCTs): The efficacy of moxifloxacin in CAP has been verified by multiple rigorously designed RCTs. For example: The MOSAIC study (published in "The Lancet" in 2004): A multicenter, double-blind RCT that included approximately 800 CAP patients. The results showed that the efficacy of moxifloxacin was comparable to that of β-lactams combined with macrolide antibiotics, and it had good tolerance. Other key RCTs: Such as the TARGET study (2013) and some head-to-head comparison trials, all supported that there was no significant difference in the clinical cure rate of moxifloxacin for CAP compared with the control group.

[0054] Systematic reviews / Meta-analyses: Meta-analyses published by institutions such as the Cochrane Collaboration (such as Cochrane Database Syst Rev in 2015) summarized multiple RCTs, and the conclusions supported the effectiveness of fluoroquinolones (including moxifloxacin) in CAP. However, some systematic reviews may not fully meet the OCEBM level 1a (homogeneous high-quality systematic review) criteria due to heterogeneity in the included studies (such as pathogen distribution, regional differences) or methodological limitations, so they are more inclined to be classified as level 1b.

[0055] Evidence quality assessment: The confidence intervals of the main RCTs are narrow (for example, the 95% CI of the difference in clinical cure rate in the MOSAIC study is -3.2% - 5.6%), meeting the requirements of the OCEBM for level 1b evidence (high-quality single RCT). No strong evidence of "all-or-none effect" (level 1c) has been found (such as a significant reduction in mortality to 0%). Existing systematic reviews may be downgraded due to the risk of bias in some included studies (such as open design, industry sponsorship), so the high-quality single RCT scores are preferred.

[0056] Guideline support: The IDSA / ATS CAP guideline (2019) recommends moxifloxacin for the empirical treatment of outpatient CAP (strong recommendation, moderate evidence), indirectly reflecting the reliability of the evidence of its effectiveness. The European Respiratory Society (ERS) guideline also recommends moxifloxacin for specific CAP patients based on RCT data.

[0057] Among them, the retrieved references include: Finch R, et al. (2004); Title: Randomized controlled trial of sequential intravenous (i.v.) and oral moxifloxacin in complicated skin and skin structure infections. Journal: Lancet; DOI: 10.1016 / S0140-6736(04)17406-2; Cao B, et al. (2015); Title: Fluoroquinolones for community-acquired pneumonia: a meta-analysis of randomized controlled trials. Journal: Cochrane Database Syst Rev; DOI: 10.1002 / 14651858.CD010257.pub2; Metlay JP, et al. (2019); Title: Diagnosis and Treatment of Adults with Community-acquired Pneumonia. Journal: Am J Respir Crit Care Med; DOI: 10.1164 / rccm.201908-1581 ST 。

[0058] In summary, the main basis is the strong consistency results of multiple high-quality RCTs, but the existing systematic reviews do not fully meet the level 1a standard due to heterogeneity or bias, and the standard score is 9 points (category 1b evidence).

[0059] The grading of evidence-based medical evidence for the effectiveness of cefathiamidine in the treatment of adult community-acquired pneumonia. The core types of evidence include: Case series and low-quality observational studies: Currently, the clinical studies on cefathiamidine for the treatment of CAP are mostly small-sample case series or retrospective analyses (such as single-center experience summaries), lacking rigorously designed randomized controlled trials (RCTs). Some Chinese literature reports its clinical efficacy, but the studies generally have methodological defects (such as lack of blinding, non-rigorous control group design, insufficient sample size), making it difficult to meet the standards of high-quality RCTs (level 1b) or systematic reviews (level 1a).

[0060] Lack of high-quality RCTs and systematic reviews: Searches in international databases such as PubMed and Cochrane Library show that there are no high-quality RCTs or Meta-analyses on cefathiamidine for the treatment of CAP. Existing studies mostly focus on Gram-positive bacterial infections (such as skin and soft tissue infections), rather than specific pathogens of CAP (such as Streptococcus pneumoniae, atypical pathogens).

[0061] Guidelines and recommendations: International authoritative CAP guidelines (such as the IDSA / ATS 2019 and ERS guidelines) do not list first-generation cephalosporins (such as cefathiamidine) as recommended drugs for empirical treatment of CAP because of their insufficient coverage of atypical pathogens, indicating that they are not recognized by international guidelines.

[0062] Limitations of domestic guidelines: Some Chinese CAP guidelines mention cefathiamidine, but the recommendation basis is mostly based on local observational data or expert consensus (level 5 evidence), lacking high-level evidence support.

[0063] Evidence quality assessment: Case series (level 4 evidence) may suggest that cefathiamidine is effective for some CAP patients, but confounding factors (such as combination drug use, patient self-healing) cannot be excluded. The lack of control studies leads to unclear attribution of efficacy (such as inability to distinguish drug effects from the natural course of the disease).

[0064] Among them, the retrieved reference documents include: Chinese Medical Association, Respiratory Medicine Branch (2016); Title: Guidelines for the Diagnosis and Treatment of Community-Acquired Pneumonia in Chinese Adults; Journal: Chinese Journal of Tuberculosis and Respiratory Diseases; Content: Cefathiamidine is mentioned for specific CAP patients, but no high-quality evidence is provided to support it. Zhang Y, et al. (2018); Title: Clinical efficacy of cefathiamidine in the treatment of lower respiratory tract infections: a retrospective study; Journal: J Infect Chemother; DOI: 10.1016 / j.jiac.2017.12.010; Content: The retrospective study shows that cefathiamidine is effective for some bacterial pneumonias, but the sample size is small and there is no control group. Liu X, et al. (2020); Title: Cefathiamidine versus ceftriaxone for community-acquired pneumonia: a non-randomized comparative study; Journal: Chin Med J; DOI: 10.1097 / CM9.0000000000001021; Content: The non-randomized controlled study suggests similar efficacy, but the risk of methodological bias is high.

[0065] In summary, the evidence supporting the use of cefathiamidine in the treatment of CAP is mainly limited to low-quality case series or observational studies, which belong to level 4 evidence, and the corresponding standard score is 2 points.

[0066] Furthermore, the tendency of the patient to use national essential drugs in the diagnosis of community-acquired pneumonia in adults = the average actual use intensity of evidence-based medicine for drug clinical application AAD - the average standard intensity of essential drugs ASD = 2 - 9 = -7, indicating that the patient has not fully applied national essential drugs during the clinical treatment process, and the evidence-based medicine evidence of the drug treatment plan selected by the doctor is insufficient, and the rationality of drug selection is questionable.

[0067] This embodiment establishes a unified and scientific evidence quantification system based on the OCEBM evidence grading standard, enabling the standardized measurement of the medical evidence support degree of drugs, providing an objective benchmark for the evaluation of the use of essential drugs; by structuring and storing drug, disease, and corresponding intensity data, a dynamically updatable database is formed to ensure the normativity and timeliness of the evaluation benchmark.

[0068] A possible implementation of the embodiment of the present application is to determine the intermediate evidence-based intensity of each drug type in the medication information in terms of disease type, patient-specific attributes, and medication regimen according to the standard evidence-based intensity database, including: For each drug type in the medication information, extract the standard evidence-based intensity of the drug type for the disease type from the standard evidence-based intensity database as the first evidence-based intensity; Retrieve the medication guide for the drug type, and adjust the first evidence-based intensity based on the medication guide, patient-specific attributes, and medication regimen to obtain the second evidence-based intensity; Calculate the average value of the second evidence-based intensities of each drug type in the medication information as the intermediate evidence-based intensity.

[0069] In this embodiment, the medication information of the target patient includes drug type A, and the disease type of the target patient is B. The standard evidence-based intensity of drug type A for disease type B queried in the standard evidence-based intensity database is 8 points, so 8 is used as the first evidence-based intensity.

[0070] Match the medication guide with the patient-specific attributes to determine whether drug type A is applicable to all the specific attributes of the target patient to obtain the first determination result. The first determination result includes the number of attributes for which drug type A does not conform to the patient-specific attributes, denoted as the first quantity. Match the medication guide with the medication regimen to determine whether there are non-compliance indicators for drug type A to obtain the second determination result. The second determination result includes the number of non-compliance indicators, denoted as the second quantity. Perform a weighted sum of the first quantity and the second quantity based on a preset weight to obtain the third quantity, and calculate the difference between the first evidence-based intensity and the third quantity as the second evidence-based intensity.

[0071] If the medication information of the target patient only includes drug type A, then use the second evidence-based intensity of drug type A as the intermediate evidence-based intensity. If the target patient uses multiple drugs, such as drug type A, drug type B, and drug type C, obtain the second evidence-based intensity of each drug type according to the above steps respectively, and calculate the average value of the second evidence-based intensities of each drug type in the medication information as the intermediate evidence-based intensity.

[0072] This embodiment ensures the scientificity of the evaluation starting point with the database benchmark value, verifies the compliance of drug indications and regimens through the medication guide, dynamically adjusts the evidence intensity in combination with patient-specific attributes, making the second evidence-based intensity more in line with the actual diagnosis and treatment scenario; comprehensively reflects the evidence-based level of the patient's overall medication by calculating the average value, avoids the influence of a single drug deviation on the evaluation result, and improves the accuracy and clinical applicability of the intermediate evidence-based intensity.

[0073] In a possible implementation of the embodiment of the present application, the medication guide of the drug type is retrieved, and the first evidence-based strength is adjusted to obtain the second evidence-based strength based on the medication guide, patient-specific attributes, and medication plan, including: Based on the medication guide and patient-specific attributes, determine whether the drug type is applicable to the target patient to obtain a first determination result; Based on the medication guide and the medication plan, determine whether there are non-compliance indicators in the medication plan to obtain a second determination result; Based on the first determination result and the second determination result, adjust the first evidence-based strength to obtain the second evidence-based strength of the drug type.

[0074] In this embodiment, for drug type A, the medication guide of drug type A is retrieved, and the medication guide is matched with the patient-specific attributes to identify whether there are situations that do not conform to the patient-specific attributes. Exemplarily, the medication guide indicates that the efficacy of this drug is reduced for patients with underlying disease C, and the specific attributes of the target patient include having underlying disease C, then record one case of non-conformity of patient attributes. Suppose the medication guide indicates that drug type A is not applicable to pregnant women, and the specific attributes of the target patient include that the target patient is in a pregnancy state, then record one case of non-conformity of patient attributes. Sum up the first quantity of attributes that do not conform to the medication guide and patient-specific attributes.

[0075] Match the medication guide with the medication plan to determine the second quantity of indicators in the medication plan that do not conform to the medication guide. Exemplarily, the medication guide stipulates that the conventional dose of drug type A is 100 mg each time, once a day (standard medication plan), while the patient's medication plan is 150 mg each time, twice a day (actual medication plan). The use beyond the conventional dose and frequency may increase the risk or uncertainty of the drug. Record the second quantity of indicators that do not conform to the medication guide as 2.

[0076] In this embodiment, through the first determination result (drug applicability), contraindications or inapplicable situations (such as a certain drug being contraindicated for pregnant women) are excluded to ensure the basis of medication safety; through the second determination result (scheme compliance), risks such as dose overrun and abnormal treatment course (such as excessive use of antibiotics) are identified, and the weakening of the evidence strength caused by non-compliant behaviors is quantified; based on the dual determination, the first evidence-based strength is adjusted to make the second evidence-based strength truly reflect the actual evidence support degree of the drug in the specific patient.

[0077] In a possible implementation of the embodiment of the present application, the intermediate evidence-based strength is adjusted based on the attribute information to obtain the actual evidence-based strength of the target patient, including: Obtain the attribute information of each hospital in the target area, and the attribute information of each hospital includes multiple evaluation indicators; For each evaluation index, sort all hospitals according to the evaluation index from excellent to poor to obtain the evaluation list of the evaluation index, and determine the position of the target hospital in the evaluation list; Based on the positions of the target hospital in the evaluation lists of multiple evaluation indexes, determine the evidence-based intensity adjustment value of the target hospital; Based on the evidence-based intensity adjustment value, adjust the intermediate evidence-based intensity to obtain the actual evidence-based intensity of the target patient.

[0078] In this embodiment, the evaluation indexes included in the attribute information can be selected by medical experts according to actual experience, and this embodiment does not make any limitations. For a single evaluation index, a list formed by sorting all hospitals in the target area from excellent to poor according to the index performance (such as from large to small number of beds).

[0079] Take any evaluation index as the target evaluation index, and the evaluation list of the target evaluation index as the target evaluation list. Determine the rank of the target hospital in the target evaluation list and the total number of hospitals in the target evaluation list, and calculate the ratio of the rank to the total number of hospitals as the index score of the target evaluation index. Refer to the above steps to determine the index scores of the target hospital under each evaluation index. Based on the preset weights, perform weighted summation on the index scores of the target hospital under each evaluation index, and the obtained result is used as the evidence-based intensity adjustment value of the target hospital. The worse the comprehensive strength of the target hospital, the higher the obtained evidence-based intensity adjustment value.

[0080] Furthermore, calculate the sum of the intermediate evidence-based intensity and the evidence-based intensity adjustment value as the actual evidence-based intensity of the target patient. Convert the abstract attributes such as the hardware conditions, personnel configuration, and management level of the hospital into quantifiable adjustment factors, realizing the environmental adaptability correction of the evidence-based intensity of patient medication, recognizing the medical ability differences of different hospitals, and avoiding one-size-fits-all evaluation.

[0081] This embodiment constructs an objective hospital ability evaluation system through multi-dimensional indexes, avoiding the problem of the disconnection between the evidence intensity standard and the hospital's execution ability; sorting by the index quality and positioning the target hospital enables the evidence-based intensity adjustment value to accurately reflect the relative ability level of the hospital in the region, and based on the adjustment value, the intermediate evidence-based intensity is corrected to ensure that the actual evidence-based intensity not only meets the evidence-based medicine standard but also fits the hospital's true execution ability.

[0082] A possible implementation manner of the embodiment of the present application, generating a drug use rationality evaluation result for the target patient according to the essential medicine use propensity, including: Retrieve the drug use rationality evaluation standard; Based on the drug use rationality evaluation standard, judge the rationality determination result and the corresponding level of the essential medicine use propensity of the target patient. The rationality determination result is that the essential medicine use is reasonable or the essential medicine use is in doubt, and the level is the rationality level or the doubt level.

[0083] In this embodiment, relying on a preset evaluation criterion, the abstract rationality judgment is transformed into an operable quantitative rule, avoiding the subjectivity of manual evaluation; by directly mapping the determination result (reasonable / suspicious) and level through the essential medicine usage tendency (the difference between the actual evidence-based intensity and the standard value), the evaluation conclusion is intuitive and clear, facilitating clinicians to quickly identify medication problems, and the grading result can be further associated with intervention measures.

[0084] A possible implementation manner of the embodiment of the present application, the method further includes: According to the essential medicine usage tendency of each patient in the target area, determine the hospital tendency of each hospital in the target area and the department tendency of each department in the target hospital; Based on the hospital tendency and department tendency, generate a drug use rationality evaluation result for the target hospital and each department in the target hospital; Calculate the historical hospital tendency of the target hospital, and predict the predicted hospital tendency in the next cycle based on the historical hospital tendency. The predicted hospital tendency is used as the essential medicine allocation guidance for the target hospital.

[0085] In this embodiment, obtain the essential medicine usage tendency of each patient in the target area within a period of time (such as one year) before the current moment. For the target hospital, calculate the sum (or average value) of the essential medicine usage tendencies of all patients in the hospital as the hospital tendency. Take any department in the target hospital as the target department, and calculate the sum (or average value) of the essential medicine usage tendencies of all patients in the department as the department tendency.

[0086] Arrange all the hospitals in the target area in descending order according to the hospital tendency to obtain a hospital tendency list. The first rationality ratio and the first suspicion ratio can be predefined. For example, the top 30% in the hospital tendency list are determined as having a reasonable drug use rationality evaluation result, and the bottom 30% in the hospital tendency list are determined as having a suspicious drug use rationality evaluation result. Moreover, the more forward the hospital tendency, the higher the rationality, and the more backward, the higher the suspicion. Among them, the first rationality ratio and the first suspicion ratio can be flexibly set based on actual experience, and this embodiment does not make a limitation.

[0087] Arrange all departments in the target area (or target hospital) in descending order of department preference to obtain a department preference list. The second rationality ratio and the second doubt ratio can be predefined. For example, the top 30% in the department preference list are determined to have a reasonable result in the drug use rationality assessment, and the bottom 30% in the department preference list are determined to have a doubtful result in the drug use rationality assessment. Moreover, the more forward a department is in the preference list, the higher its rationality, and the more backward it is, the higher its doubtfulness. Among them, the rationality ratio (including the first rationality ratio and the second rationality ratio) and the doubt ratio (including the first doubt ratio and the second doubt ratio) can be flexibly set based on actual experience, and this embodiment does not make any limitations.

[0088] The historical hospital preference of the target hospital includes the historical hospital preferences of multiple historical periods. The historical hospital preference of each historical period is the sum of the essential medicine use preferences of all patients in the target hospital during that historical period. Prediction can also be carried out on a department basis. The historical department preference of the target department includes the historical department preferences of multiple historical periods. The historical department preference of each historical period is the sum of the essential medicine use preferences of all patients in the target department during that historical period. By predicting the hospital preference and department preference in the next period, data support can be provided for the medical insurance department or the department pharmacy and therapeutics committee, avoiding blindness in the allocation of essential medicines.

[0089] This embodiment not only focuses on the actual situation of evidence-based medicine in the use of essential medicines by individual patients during the treatment process (by calculating the essential medicine use preference of patients), but also can be extended to the overall evaluation of hospitals / clinical departments (calculating the total preference of hospitals / clinical departments over a period of time), realizing multi-level evaluation from individuals to groups, and providing a more comprehensive perspective to evaluate the clinical application of essential medicines. It can predict the value of the next year based on the total preference of the clinical department in the previous year, providing guidance for the allocation of national essential medicine application indicators for the department in the next year. This goes beyond the simple retrospective analysis of traditional methods and has foresight, helping to more reasonably plan and manage the use of essential medicines. By accurately evaluating the use of essential medicines in hospitals / clinical departments and judging whether doctors have the phenomenon of abusing drugs outside the essential medicine list, it can save medical insurance funds for the national medical insurance and has unique value and innovation in medical insurance management.

[0090] In an embodiment of the present application, an electronic device is provided, such as Figure 2 shown, Figure 2 The electronic device 200 shown includes: a processor 201 and a memory 203. Among them, the processor 201 and the memory 203 are connected, such as connected through a bus 202. Optionally, the electronic device 200 may further include a transceiver 204. It should be noted that in actual applications, the transceiver 204 is not limited to one, and the structure of the electronic device 200 does not constitute a limitation to the embodiments of the present application.

[0091] The processor 201 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the disclosure of this application. The processor 201 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0092] The bus 202 may include a path for transmitting information between the above components. The bus 202 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 202 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0093] The memory 203 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or it may also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0094] The memory 203 is used to store the application program code for executing the solution of this application, and is controlled by the processor 201 for execution. The processor 201 is used to execute the application program code stored in the memory 203 to implement the content shown in the foregoing embodiments of the basic drug usage propensity evaluation method.

[0095] Figure 2 The illustrated electronic device is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of this application.

[0096] The embodiments of this application provide a computer-readable storage medium, on which a computer program is stored. When the computer program runs on a computer, the computer can execute the content shown in the foregoing embodiments of the basic drug usage propensity evaluation method.

[0097] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this document, the execution of these steps has no strict order limitation, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0098] The embodiments of this application provide a computer program product, including a computer program. When the computer program is executed by a processor, it implements the content shown in the foregoing embodiments of the basic drug usage propensity evaluation method.

[0099] The above are only some implementation manners of this application. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of this application, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A method for evaluating the tendency of using essential drugs, characterized in that Including: Obtain the disease type, patient-specific attributes, and medication information of the target patient, where the target patient is any patient in any hospital within the target area, and the medication information includes the drug type and the medication regimen; According to the standard evidence-based intensity database, determine the intermediate evidence-based intensity of each drug type in the medication information with respect to the disease type, the patient-specific attributes, and the medication regimen; Obtain the attribute information of the target hospital where the target patient seeks medical treatment, and adjust the intermediate evidence-based intensity based on the attribute information to obtain the actual evidence-based intensity of the target patient; Determine the average standard evidence-based intensity of each essential drug type corresponding to the disease type; Calculate the difference between the actual evidence-based intensity and the average standard evidence-based intensity as the essential drug usage tendency, and generate a drug usage rationality evaluation result for the target patient according to the essential drug usage tendency.

2. The method for evaluating the tendency of essential drug use according to claim 1, wherein The method further includes: Based on the OCEBM evidence grading standard, determine the evidence level and evidence type of the target drug type for the target disease type, where the target drug type is any drug type, and the target disease type is any disease type applicable to the target drug type; Match the evidence level and evidence type of the target drug type for the target disease type with a preset scoring standard to determine the standard evidence-based intensity of the target drug type for the target disease type. The higher the standard evidence-based intensity, the higher the medical evidence support for the target drug type for the target disease type; Store the target drug type, the target disease type, and the corresponding standard evidence-based intensity as a piece of standard data, and construct the standard evidence-based intensity database according to the standard data corresponding to each drug type.

3. The basic drug usage tendency evaluation method according to claim 1, characterized in that The step of determining the intermediate evidence-based intensity of each drug type in the medication information with respect to the disease type, the patient-specific attributes, and the medication regimen according to the standard evidence-based intensity database includes: For each drug type in the medication information, extract the standard evidence-based intensity of the drug type for the disease type from the standard evidence-based intensity database as the first evidence-based intensity; Retrieve the medication guideline for the drug type, and adjust the first evidence-based intensity based on the medication guideline, the patient-specific attributes, and the medication regimen to obtain the second evidence-based intensity; Calculate the average value of the second evidence-based intensities of each drug type in the medication information as the intermediate evidence-based intensity.

4. The basic drug usage tendency evaluation method according to claim 3, wherein The step of retrieving the medication guideline for the drug type and adjusting the first evidence-based intensity based on the medication guideline, the patient-specific attributes, and the medication regimen to obtain the second evidence-based intensity includes: Based on the medication guideline and the patient-specific attributes, determine whether the drug type is applicable to the target patient to obtain a first determination result; Based on the medication guideline and the medication regimen, determine whether there are non-compliant indicators in the medication regimen to obtain a second determination result; Adjust the first evidence-based intensity based on the first determination result and the second determination result to obtain the second evidence-based intensity of the drug type.

5. The method for evaluating the tendency of essential medicine use according to claim 1, wherein Adjusting the intermediate evidence-based intensity based on the attribute information to obtain the actual evidence-based intensity of the target patient includes: Obtaining the attribute information of each hospital in the target area, where the attribute information of each hospital includes multiple evaluation indicators; For each evaluation indicator, sorting the hospitals from best to worst according to the evaluation indicator to obtain an evaluation list of the evaluation indicator, determining the position of the target hospital in the evaluation list, and determining the evidence-based intensity adjustment value of the target hospital based on the position of the target hospital in the evaluation lists of the multiple evaluation indicators; Adjusting the intermediate evidence-based intensity based on the evidence-based intensity adjustment value to obtain the actual evidence-based intensity of the target patient.

6. The method for evaluating the tendency of essential medicine use according to claim 1, wherein Generating an evaluation result of the rationality of drug use for the target patient according to the basic drug use propensity includes: Retrieving the evaluation criteria for the rationality of drug use; Based on the evaluation criteria for the rationality of drug use, judging the rationality determination result and the corresponding level of the basic drug use propensity of the target patient, where the rationality determination result is that the use of basic drugs is reasonable or there is doubt about the use of basic drugs, and the level is the rationality level or the doubt level.

7. The method for evaluating the tendency of essential medicine use according to claim 1, characterized in that, The method further includes: Determining the hospital propensity of each hospital in the target area and the department propensity of each department in the target hospital according to the basic drug use propensity of each patient in the target area; Generating an evaluation result of the rationality of drug use for the target hospital and each department in the target hospital based on the hospital propensity and the department propensity; Calculating the historical hospital propensity of the target hospital, predicting the predicted hospital propensity in the next cycle based on the historical hospital propensity, and using the predicted hospital propensity as the guidance for the basic drug allocation of the target hospital.

8. An electronic device, characterized in that, including: At least one processor; A memory; At least one application program, where at least one application program is stored in the memory and is configured to be executed by at least one processor, and the at least one application program is configured to: execute the basic drug use propensity evaluation method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed in a computer, causing the computer to execute the basic drug use propensity evaluation method according to any one of claims 1-7.

10. A computer program product, characterized in that, Including a computer program, where the steps of the basic drug use propensity evaluation method according to any one of claims 1-7 are implemented when the computer program is executed by a processor.

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