Accurate informatization medicine regulation and control method and system for patients suffering from hemodialysis anemia

Abstract

The invention relates to the field of medicine informatization management, and discloses an informatization medicine accurate regulation and control method and system for hemodialysis anemia patients, and the method comprises the steps: randomly dividing the collected patient information into a research group and a control group, comparing and analyzing the treatment effect difference caused by the anemia index change of the two groups of patients, and determining the accuracy of the treatment effect. The anemia improvement effect is evaluated by analyzing the relationship between the anemia index level change before and after the adjustment of the drug dose and injection frequency of a research group patient, whether the drug regulation direction is correct or not is judged, and the drug dose and injection frequency are adjusted according to the anemia index level change in the body of the patient. According to the method, the drug dosage and the injection frequency are dynamically optimized, and the difference of patients in a research group and patients in a control group in the aspect of anemia index level improvement is analyzed based on a model prediction result, so that drug regulation is further tracked and monitored, the drug use process is accurately regulated, the treatment quality is improved, and the treatment cost is reduced. And the workload of medical staff is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of drug information management, and more specifically to an information-based precise drug control method and system for hemodialysis anemia patients. Background Art

[0002] To treat anemia, hemodialysis patients usually receive recombinant human EPO injections. Traditional EPO dosage adjustments are based on changes in hemoglobin levels, but such adjustments are often empirical and lack individualized precision. Excessive doses of EPO may lead to risks such as hypertension and thrombosis, while insufficient doses cannot effectively correct anemia. Therefore, monitoring and evaluating anemia in hemodialysis patients is an important part of treatment, which includes regular testing of hemoglobin, reticulocytes, iron status and other indicators, as well as adjusting treatment plans based on treatment response. Since the treatment of anemia in hemodialysis patients requires precise drug regulation and monitoring, the application of information management systems can improve treatment outcomes and ensure the accuracy and safety of drug use.

[0003] However, the above process still has the following disadvantages:

[0004] First, existing information-based medication management methods lack regular monitoring of key anemia indicators, making it impossible to make preliminary adjustments and dynamic optimization of medication dosage and frequency based on monitoring results. This results in an inability to timely understand a patient's anemia status and treatment response, leaving the precision of treatment in need of improvement.

[0005] Second, existing information-based drug management methods lack the ability to analyze the relationship between adjustments in drug dosage and injection frequency and changes in anemia indicators to assess the effectiveness of drug regulation and further determine the direction of drug regulation. This results in the inability to promptly detect adverse drug effects.

[0006] Third, the existing information-based drug management methods lack the ability to analyze the differences in anemia indicator improvement between the study group and the control group based on the prediction of each patient's anemia indicator improvement, resulting in the inability to track and monitor the subsequent drug regulation, making it impossible to further improve quality. Summary of the Invention

[0007] In order to overcome the above-mentioned defects of the prior art, the present invention provides an information-based drug precision control method and system for hemodialysis anemia patients to solve the problems existing in the above-mentioned background technology.

[0008] The present invention provides the following technical solution: an information-based precise drug control method for hemodialysis anemia patients, comprising:

[0009] S1: Used to collect basic information data of multiple patients and randomly divide them into a research group receiving information-based drug management and a control group receiving conventional treatment. The hemoglobin, ferritin, and transferrin saturation levels of the two groups of patients were regularly monitored and recorded.

[0010] S2: Based on a preliminary analysis of hemoglobin, ferritin, and transferrin saturation in the two groups of patients, the changes in anemia indicators in the two groups of patients were compared. Based on the comparison results, the differences in treatment effects were analyzed, and the drug dosage and injection frequency were preliminarily adjusted according to the analyzed differences in efficacy.

[0011] S3: Based on the analysis of the relationship between the adjustment of drug dosage and injection frequency and the changes in anemia index levels in the study group before and after the adjustment of drug dosage and injection frequency, the effect of drug regulation on anemia improvement was evaluated and whether the direction of drug regulation was correct was determined;

[0012] S4: Used to monitor the changes in anemia indicator levels in patients during drug regulation in real time. Based on the changes in anemia indicator levels in patients, it analyzes whether the adjustment of drug dosage in information management is reasonable and dynamically optimizes drug dosage and injection frequency.

[0013] S5: Build a prediction model based on patient characteristic parameters and historical data, and use the prediction model to predict the improvement of anemia indicators for each patient;

[0014] S6: Based on the prediction results, analyze the differences in the improvement of anemia index levels between the study group and the control group, and calculate the difference in the probability of improvement of anemia index levels between the two groups of patients for further tracking and monitoring of drug regulation.

[0015] Preferably, the S1 collects basic information of multiple patients, divides the patients into a study group and a control group using a random grouping method, implements information-based drug management treatment for patients in the study group, and patients in the control group receive conventional treatment. The hemoglobin, ferritin and transferrin saturation data of the two groups of patients after treatment are regularly monitored and recorded, and the hemoglobin, ferritin and transferrin saturation data of all patients before treatment are recorded.

[0016] Preferably, the S2 uses a test method to compare whether there is a significant difference in the baseline anemia index of the two groups of patients before treatment. If there is a significant difference, the difference needs to be processed and then the change in the anemia index is analyzed. If there is no significant difference, the change in the anemia index is directly compared. By regularly monitoring and comparing the changes in anemia indicators of the two groups of patients after treatment, the difference in the effect of information-based drug management on improving anemia treatment is analyzed, and the difference value of the treatment effect is calculated to determine whether the drug dosage and injection frequency of the study group need to be adjusted. If the analysis results show that there is a difference in the treatment effect of the two groups of patients, the drug dosage and injection frequency of the study group are preliminarily adjusted according to the difference.

[0017] Preferably, S3 is based on the preliminary adjustment results of the drug dosage and injection frequency based on the difference in therapeutic effects, collects the drug dosage, injection frequency and anemia index data before and after the adjustment, analyzes the relationship between the changes in the drug dosage, injection frequency and anemia index levels before and after the adjustment, and calculates the regulation effect evaluation coefficient, which is used to evaluate the effect of drug regulation on improving anemia, and then judges whether the direction of drug regulation is correct based on the regulation effect evaluation coefficient.

[0018] Preferably, the S4 uses an information management tool to monitor the changes in anemia indicators in the patient's body in real time and record the monitoring data, including the level fluctuations and trends of hemoglobin, ferritin and transferrin saturation. Based on the real-time monitoring data, the current drug dosage and injection frequency are analyzed to see whether they help maintain a stable anemia indicator level. If the monitoring data shows that the anemia indicator level has not reached the target or has an unstable trend, the drug dosage and injection frequency are appropriately increased or decreased according to the changes in the anemia indicator level.

[0019] Preferably, the S5 extracts patient characteristic parameters from the collected basic information data of the two groups of patients, including the patient's age, gender, dialysis age, underlying diseases, previous treatment records and drug response, and records the historical data of changes in anemia index levels of the two groups of patients over time, and uses a linear regression algorithm to establish a prediction model, wherein the drug dosage, injection frequency and patient characteristics are used as independent variables, and the change in anemia index level is used as the dependent variable to train the model, and the trained model is used to calculate the predicted value of each patient characteristic for the improvement of anemia indicators.

[0020] Preferably, the S6 analyzes the difference in the improvement of anemia index levels between the study group patients and the control group patients based on the predicted value of the improvement of anemia index based on each patient characteristic, and calculates the difference in the probability of improvement of anemia index levels of the two groups of patients, which is used to track and monitor the effect of the drug after regulation, and sends the difference analysis monitoring results to the terminal in real time for display.

[0021] To achieve the above objectives, the present invention provides the following technical solutions: an information-based precise drug control system for hemodialysis anemia patients, which implements the above-mentioned information-based precise drug control method for hemodialysis anemia patients, comprising:

[0022] Data collection module: used to collect basic information data of multiple patients and randomly divide them into a research group receiving information-based drug management and a control group receiving conventional treatment. The hemoglobin, ferritin, and transferrin saturation levels of the two groups of patients were regularly monitored and recorded.

[0023] Treatment effect analysis module: Based on the preliminary analysis of hemoglobin, ferritin and transferrin saturation of the two groups of patients, the changes in anemia indicators of the two groups of patients are compared. According to the comparison results, the difference in treatment effect is analyzed, and the drug dosage and injection frequency are preliminarily adjusted according to the analyzed difference in efficacy;

[0024] Drug regulation analysis module: Based on the analysis of the relationship between the adjustment of drug dosage and injection frequency and the changes in anemia index levels in the study group of patients before and after the adjustment, the effect of drug regulation on anemia improvement is evaluated to determine whether the direction of drug regulation is correct;

[0025] Regulation and Optimization Module: This module is used to monitor the changes in anemia levels in patients during drug regulation in real time. Based on the changes in anemia levels in patients, it analyzes whether the adjustment of drug dosage in information management is reasonable, and dynamically optimizes drug dosage and injection frequency.

[0026] Improvement effect prediction module: Build a prediction model based on patient characteristic parameters and historical data, and use the prediction model to predict the improvement of each patient's anemia indicators;

[0027] Improvement effect tracking module: Based on the prediction results, the differences in the improvement of anemia index levels between the research group and the control group are analyzed, and the difference in the probability of improvement of anemia index levels of the two groups of patients is calculated for further tracking and monitoring of drug regulation.

[0028] The technical effects and advantages of the present invention are as follows:

[0029] (1) Based on regular monitoring of key anemia indicators, preliminary adjustments and dynamic optimization of drug dosage and frequency are made according to the monitoring results, which helps to timely understand the patient's anemia status and treatment response, ensure the personalization and accuracy of the treatment plan, and help improve the treatment effect.

[0030] (2) Based on the analysis of the relationship between the adjustment of drug dosage and injection frequency and the changes in the level of anemia indicators, the effect of drug regulation is evaluated to determine whether the regulation direction is correct, which helps to more accurately evaluate the effect of drug regulation on improving anemia and provide guidance for the adjustment of subsequent treatment plans.

[0031] (3) Based on the patient's characteristic parameters and historical data, a prediction model is constructed to make personalized predictions on the improvement of anemia indicators for each patient, which helps to plan treatment plans in advance and improve the predictability and targeting of treatment. The differences in the improvement of anemia indicator levels between the study group and the control group are analyzed based on the prediction results, which helps to further track and monitor drug regulation, timely discover and solve problems, and achieve continuous improvement and optimization of treatment plans, thereby improving the quality of treatment and further reducing the workload of medical staff. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A diagram showing the steps of the method of the present invention.

[0033] Figure 2 This is a system structure diagram of the present invention.

[0034] Figure 3 This is an implementation flow chart of this embodiment. DETAILED DESCRIPTION

[0035] The technical solutions of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. In addition, the forms of the various structures described in the following embodiments are merely examples. The information-based drug precision control method and system for hemodialysis anemia patients involved in the present invention are not limited to the various structures described in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0036] like Figure 1 This embodiment provides an information-based precise drug control method for hemodialysis anemia patients, including:

[0037] S1: Used to collect basic information data of multiple patients and randomly divide them into a research group receiving information-based drug management treatment and a control group receiving conventional treatment. The hemoglobin, ferritin and transferrin saturation of the two groups of patients are regularly monitored and recorded.

[0038] In this embodiment, S1 collects basic information of multiple patients and divides the patients into a study group and a control group using a random grouping method. The patients in the study group are treated with information-based drug management, and the patients in the control group receive conventional treatment. The hemoglobin, ferritin, and transferrin saturation data of the two groups of patients after treatment are regularly monitored and recorded, and the hemoglobin, ferritin, and transferrin saturation data of all patients before treatment are recorded.

[0039] It should be noted that the inclusion criteria for the study subjects were: (1) age ≥18, regardless of gender; (2) maintenance hemodialysis treatment for ≥3 months; (3) regular hemodialysis, ≥10 hours per week; (4) complete clinical data and completion of routine blood tests at the blood purification center every month; exclusion criteria were: (1) acute kidney injury undergoing hemodialysis treatment; (2) malignant tumors or life expectancy <1 year; based on the inclusion and exclusion criteria, suitable patients were screened, informed consent was obtained from the patients, and basic information of the patients was collected. The patients were divided into the study group and the control group using a randomization procedure. The study group was set to implement information-based drug management treatment, and the control group was set to receive conventional treatment. A monitoring schedule was established, for example: baseline (before randomization), 1st month, 3rd month, and 6th month. After each monitoring time point, the hemoglobin, ferritin, and transferrin saturation of the two groups of patients were collected and recorded.

[0040] S2: Based on a preliminary analysis of the hemoglobin, ferritin, and transferrin saturation levels of the two groups of patients, the changes in anemia indicators of the two groups of patients were compared. Based on the comparison results, the differences in treatment effects were analyzed, and preliminary adjustments to the drug dosage and injection frequency were made based on the analyzed differences in efficacy.

[0041] In this embodiment, the S2 uses a test method to compare whether there is a significant difference in the baseline anemia index of the two groups of patients before treatment. If there is a significant difference, the difference needs to be processed and then the change in the anemia index is analyzed. If there is no significant difference, the change in the anemia index is directly compared. By regularly monitoring and comparing the changes in anemia indicators of the two groups of patients after treatment, the difference in the effect of information-based drug management on improving anemia treatment is analyzed, and the difference value of the treatment effect is calculated to determine whether the drug dosage and injection frequency of the study group need to be adjusted. If the analysis results show that there is a difference in the treatment effect of the two groups of patients, the drug dosage and injection frequency of the study group are preliminarily adjusted according to the difference.

[0042] It should be noted that by first analyzing whether there are differences in anemia indicators between the two groups of patients at baseline (before treatment), the independent sample t test was used to perform a balance test on the baseline indicators of the two groups of patients, and comparing whether there are significant differences in the baseline anemia indicators (hemoglobin, ferritin, transferrin saturation) of the two groups of patients before treatment. The specific calculation formula is: Where t represents the difference value of baseline anemia index, represents the mean value of each anemia index in the study group at baseline, represents the mean value of each anemia index in the control group at baseline, represents the variance of each anemia index in the study group at baseline, represents the variance of each anemia index in the control group at baseline, n1 represents the number of patients participating in the study group, and n2 represents the number of patients participating in the control group. Then determine the significance level α. According to the degrees of freedom and significance level, look up the t distribution table to obtain the critical t value. If the calculated t value is greater than the critical t value, it is considered that there is a significant difference between the two groups. The covariance analysis method can be used to adjust the baseline difference. If the calculated t value is less than or equal to the critical t value, it is considered that there is no significant difference between the two groups.

[0043] Based on the results of the baseline anemia index difference test, the changes in anemia indexes of the two groups of patients were compared and analyzed. By regularly monitoring and comparing the changes in anemia indexes of the two groups of patients after treatment, the differences in the therapeutic effects of information-based drug management on anemia improvement were analyzed, and the difference in treatment effect was calculated. The specific calculation formula is: Among them, A1 represents the average value of each anemia index of the study group before treatment, A2 represents the average value of each anemia index of the study group after treatment, B1 represents the average value of each anemia index of the control group before treatment, and B2 represents the average value of each anemia index of the control group after treatment. Use t-test or non-parametric test to compare whether the difference in the degree of improvement between the two groups is statistically significant. If there is no statistical significance, there is no need to adjust the drug dosage and injection frequency of the study group. If there is statistical significance, the corresponding adjustment operation is performed based on the calculated treatment effect difference value. By comparing the treatment effect difference value G with the preset treatment effect difference threshold λ, it is determined whether the drug dosage and injection frequency of the study group need to be adjusted. If the treatment effect difference value G is greater than the preset If the treatment effect difference threshold λ is greater than or equal to 0, and the treatment effect difference value G is greater than 0, it indicates that there is a significant difference in the treatment effect of the two groups of patients, and the effect of the experimental group is better than that of the control group. The drug dosage and injection frequency of the experimental group can be preliminarily adjusted. If the treatment effect difference value G is greater than the preset treatment effect difference threshold λ, and the treatment effect difference value G is less than or equal to 0, it indicates that the effect of the experimental group is significantly worse than that of the control group. The drug dosage and injection frequency of the experimental group must be adjusted to improve the treatment effect. If the treatment effect difference value G is less than or equal to the preset treatment effect difference threshold λ, it indicates that the current drug dosage and injection frequency settings of the experimental group are unreasonable, and the expected treatment goal has not been achieved. The drug dosage and injection frequency of the experimental group need to be adjusted.

[0044] S3: Based on the analysis of the relationship between the adjustment of drug dosage and injection frequency and the changes in anemia index levels before and after the adjustment of drug dosage and injection frequency in the study group patients, the effect of drug regulation on the improvement of anemia is evaluated, and whether the direction of drug regulation is correct is determined.

[0045] In this embodiment, S3 is based on the preliminary adjustment results of the drug dosage and injection frequency based on the difference in therapeutic effects, collects the drug dosage, injection frequency and anemia index data before and after the adjustment, analyzes the relationship between the changes in the drug dosage, injection frequency and anemia index levels before and after the adjustment, and calculates the regulation effect evaluation coefficient, which is used to evaluate the effect of drug regulation on improving anemia, and then judges whether the direction of drug regulation is correct based on the regulation effect evaluation coefficient.

[0046] It should be noted that the specific analysis method for the control effect evaluation coefficient is as follows:

[0047] Step 1: Collect the drug dose D1, injection frequency F1, and anemia index level I1 before adjustment, and the drug dose D2, injection frequency F2, and anemia index level I2 after adjustment;

[0048] Step 2: Calculate the drug dosage change rate △D, injection frequency change rate △F, and anemia index level change rate △I before and after adjustment. The specific expressions of △D, △F, and △I are:

[0049]

[0050]

[0051] Step 3: Calculate the regulatory effect evaluation coefficient by analyzing the comprehensive impact of changes in drug dosage and injection frequency on changes in anemia index levels. The specific calculation formula is:

[0052] If the control effect evaluation coefficient E is positive and ΔI is also positive, it indicates that the drug control direction is correct and the anemia index has improved. If the control effect evaluation coefficient E is negative or ΔI is negative, it indicates that the drug control direction may be incorrect and medical staff need to be reminded to adjust the treatment plan in time.

[0053] By analyzing the relationship between drug dosage, injection frequency and changes in anemia index levels before and after adjustment, it is helpful to clarify the causal relationship between drug regulation and anemia improvement, evaluate the effect of drug regulation on anemia improvement, and judge whether the direction of drug regulation is correct. This allows for timely adjustment of treatment plans, optimization of drug use, improvement of treatment effects, and avoidance of adverse reactions or poor efficacy caused by irrational drug use.

[0054] S4: It is used to monitor the changes in the anemia index levels of patients during drug regulation in real time. According to the changes in the anemia index levels of patients, it analyzes whether the adjustment of drug dosage in information management is reasonable, and dynamically optimizes the drug dosage and injection frequency.

[0055] In this embodiment, the S4 uses an information management tool to monitor the changes in anemia indicators in the patient's body in real time and record the monitoring data, including the level fluctuations and trends of hemoglobin, ferritin and transferrin saturation. Based on the real-time monitoring data, it analyzes whether the current drug dosage and injection frequency help maintain a stable anemia indicator level. If the monitoring data shows that the anemia indicator level has not reached the target or has an unstable trend, the drug dosage and injection frequency are appropriately increased or decreased according to the changes in the anemia indicator level.

[0056] It should be noted that by recording the patient's hemoglobin, ferritin and transferrin saturation levels, measurement time points, corresponding drug doses and injection frequency, the fluctuation value of anemia index levels was analyzed and calculated based on the hemoglobin, ferritin and transferrin saturation levels. The specific calculation formula is: Among them, Hb i Indicates the hemoglobin content of each measurement, Fe i Indicates the ferritin content of each measurement, TS i represents the transferrin saturation of each measurement, It represents the average hemoglobin content of all measurements. represents the average ferritin content of all measurements, represents the average transferrin saturation content of all measurements, N represents the number of measurements, w1, w2, and w3 represent weight coefficients respectively;

[0057] Linear regression or other time series analysis methods are used to analyze the changing trend of anemia indicator levels. The linear regression formula is Y = a + b × T + c, where Y represents the change in hemoglobin level, a represents the intercept, b represents the slope, T represents the time variable, and c represents the error term.

[0058] If the fluctuation value SD of the anemia index level is lower than the preset level threshold, and the trend analysis of the anemia index level shows that the anemia index level remains stable or shows an upward trend, it is considered that the current drug dosage and injection frequency are helpful in maintaining a stable anemia index level, and there is no need to adjust the drug dosage and injection frequency; if the fluctuation value SD of the anemia index level is higher than the preset level threshold, or the trend analysis of the anemia index level shows that the anemia index level is decreasing, it is necessary to further adjust the drug dosage and injection frequency.

[0059] S5: Build a prediction model based on patient characteristic parameters and historical data, and use the prediction model to predict the improvement of anemia indicators for each patient.

[0060] In this embodiment, the S5 extracts patient characteristic parameters from the collected basic information data of the two groups of patients, including the patient's age, gender, dialysis age, underlying diseases, previous treatment records and drug responses, and records the historical data of changes in the anemia index levels of the two groups of patients over time. A linear regression algorithm is used to establish a prediction model, in which the drug dosage, injection frequency and patient characteristics are used as independent variables, and the changes in the anemia index level are used as dependent variables to train the model. The trained model is used to calculate the predicted value of each patient characteristic for the improvement of the anemia index.

[0061] It should be specifically noted that the collected basic information data of the two groups of patients and the historical data of the changes in the anemia indicator levels of the two groups of patients over time were preprocessed, and then the features related to the changes in the anemia indicator levels were extracted from the preprocessed data to create a new feature data set, including drug dosage accumulation, length of treatment time, etc., and divided into training set, validation set and test set, and the linear regression model was selected as the prediction model, the training set was used to fit the linear regression model, cross-validation was used to evaluate the generalization ability of the model, and the test set was used to evaluate the performance of the model, and the extracted features related to the changes in the anemia indicator levels were used as the feature parameters of the prediction model input, and the model output the predicted value of each patient feature for the improvement of the anemia indicator.

[0062] S6: Based on the prediction results, analyze the differences in the improvement of anemia index levels between the study group and the control group, and calculate the difference in the probability of improvement of anemia index levels between the two groups of patients for further tracking and monitoring of drug regulation.

[0063] In this embodiment, the S6 analyzes the difference in the improvement of anemia index levels between the study group patients and the control group patients based on the predicted value of the improvement of anemia index based on each patient characteristic, and calculates the difference in the probability of improvement of anemia index levels of the two groups of patients, which is used to track and monitor the effect of the drug after regulation, and sends the difference analysis monitoring results to the terminal in real time for display.

[0064] It should be noted that for each patient, the improvement probability is calculated based on the predicted value of anemia index improvement. The specific calculation formula is: Among them, p j represents the predicted value of each patient characteristic for the improvement of anemia indicators, e represents a constant, and then the average improvement probability of the study group and the control group is calculated respectively. Based on the average improvement probability of the study group and the control group, the difference in the probability of improvement of anemia indicators between the two groups is calculated as

[0065] like Figure 2The embodiment shown provides an implementation system corresponding to the information-based drug precision regulation method for hemodialysis anemia patients, including a data collection module, a treatment effect analysis module, a drug regulation analysis module, a regulation optimization module, an improvement effect prediction module and an improvement effect tracking module. The data collection module is connected to the treatment effect analysis module, the treatment effect analysis module is connected to the drug regulation analysis module, the drug regulation analysis module is connected to the regulation optimization module, the regulation optimization module is connected to the improvement effect prediction module, and the improvement effect prediction module is connected to the improvement effect tracking module.

[0066] The data collection module is used to collect basic information data of multiple patients, and randomly divide the patients into a research group receiving information-based drug management treatment and a control group receiving conventional treatment, and regularly monitor and record the hemoglobin, ferritin and transferrin saturation of the two groups of patients;

[0067] The treatment effect analysis module performs a preliminary analysis of the hemoglobin, ferritin, and transferrin saturation of the two groups of patients, compares the changes in anemia indicators of the two groups of patients, analyzes the difference in treatment effect based on the comparison results, and makes preliminary adjustments to the drug dosage and frequency based on the analyzed difference in efficacy;

[0068] The drug regulation analysis module evaluates the effect of drug regulation on anemia improvement and determines whether the direction of drug regulation is correct by analyzing the relationship between drug dosage and injection frequency adjustment and anemia index level changes in the study group of patients before and after the adjustment.

[0069] The control optimization module is used to monitor the changes in the anemia indicator level in the patient during drug control in real time, analyze whether the adjustment of the drug dosage in the information management is reasonable according to the changes in the anemia indicator level in the patient, and dynamically optimize the drug dosage and injection frequency;

[0070] The improvement effect prediction module builds a prediction model based on patient characteristic parameters and historical data, and predicts the improvement of anemia indicators of each patient through the prediction model;

[0071] The improvement effect tracking module analyzes the differences in the improvement of anemia index levels between the study group and the control group based on the prediction results, and calculates the difference in the probability of improvement of anemia index levels between the two groups of patients for further tracking and monitoring of drug regulation.

[0072] like Figure 2 This embodiment provides an implementation process corresponding to an information-based precise drug control method for hemodialysis anemia patients, including:

[0073] Step 1: Randomly divide patients into a study group receiving information-based drug management and a control group receiving conventional treatment;

[0074] Step 2: Compare and analyze the changes in anemia indicators between the two groups of patients to analyze the difference in treatment effect and determine whether preliminary adjustments to drug dosage and injection frequency are needed;

[0075] Step 3: Analyze the relationship between the changes in anemia indicators before and after the adjustment of drug dosage and injection frequency in the study group, evaluate the effect of drug regulation on anemia improvement, and determine whether the direction of drug regulation is correct;

[0076] Step 4: Based on the changes in the patient's anemia indicator levels, analyze whether the adjustment of drug dosage in information management is reasonable, and dynamically optimize the drug dosage and injection frequency;

[0077] Step 5: Build a prediction model based on patient characteristic parameters and historical data, and output the prediction results of anemia indicator improvement;

[0078] Step 6: Analyze the differences in the improvement of anemia index levels between the study group and the control group, calculate the difference in the probability of improvement of anemia index levels between the two groups of patients, and track and monitor drug regulation.

[0079] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0080] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. An information-based precise drug control method for hemodialysis anemia patients, characterized by: include: S1: Used to collect basic information data of multiple patients and randomly divide them into a research group receiving information-based drug management and a control group receiving conventional treatment. The hemoglobin, ferritin, and transferrin saturation levels of the two groups of patients were regularly monitored and recorded. S2: Based on a preliminary analysis of hemoglobin, ferritin, and transferrin saturation in the two groups of patients, the changes in anemia indicators in the two groups of patients were compared. Based on the comparison results, the differences in treatment effects were analyzed, and the drug dosage and injection frequency were preliminarily adjusted according to the analyzed differences in efficacy. S3: Based on the analysis of the relationship between the adjustment of drug dosage and injection frequency and the changes in anemia index levels in the study group before and after the adjustment of drug dosage and injection frequency, the effect of drug regulation on anemia improvement was evaluated and whether the direction of drug regulation was correct was determined; S4: Used to monitor the changes in anemia indicator levels in patients during drug regulation in real time. Based on the changes in anemia indicator levels in patients, it analyzes whether the adjustment of drug dosage in information management is reasonable and dynamically optimizes drug dosage and injection frequency. S5: Build a prediction model based on patient characteristic parameters and historical data, and use the prediction model to predict the improvement of anemia indicators for each patient; S6: Based on the prediction results, analyze the differences in the improvement of anemia index levels between the study group and the control group, and calculate the difference in the probability of improvement of anemia index levels between the two groups of patients for further tracking and monitoring of drug regulation.

2. The information-based precise drug control method for hemodialysis anemia patients according to claim 1, characterized in that: The S1 collects basic information of multiple patients and divides the patients into a study group and a control group using a random grouping method. The patients in the study group are given information-based drug management treatment, while the patients in the control group receive conventional treatment. The hemoglobin, ferritin, and transferrin saturation data of the two groups of patients after treatment are regularly monitored and recorded, and the hemoglobin, ferritin, and transferrin saturation data of all patients before treatment are recorded.

3. The information-based precise drug control method for hemodialysis anemia patients according to claim 2, characterized in that: The S2 is to compare whether there is a significant difference in the baseline anemia index of the two groups of patients before treatment by using a test method. If there is a significant difference, the difference needs to be processed and then the change of anemia index is analyzed. If there is no significant difference, the change of anemia index is directly compared.

4. The information-based precise drug control method for hemodialysis anemia patients according to claim 3, characterized in that: The comparative analysis process of the changes in anemia indicators includes: regularly monitoring and comparing the changes in anemia indicators of the two groups of patients after treatment, analyzing the differences in the treatment effects of information-based drug management on anemia improvement, and calculating the difference in treatment effects to determine whether the drug dosage and injection frequency of the study group need to be adjusted. If the analysis results show that there are differences in the treatment effects of the two groups of patients, the drug dosage and injection frequency of the study group are preliminarily adjusted based on the differences.

5. The information-based precise drug control method for hemodialysis anemia patients according to claim 4, characterized in that: The S3 is based on the preliminary adjustment results of drug dosage and injection frequency based on the difference in treatment effect, collects drug dosage, injection frequency and anemia index data before and after adjustment, analyzes the relationship between drug dosage, injection frequency and anemia index level changes before and after adjustment, and calculates the regulation effect evaluation coefficient to evaluate the effect of drug regulation on improving anemia.

6. The information-based precise drug control method for hemodialysis anemia patients according to claim 5, characterized in that: The effect evaluation of the drug regulation on anemia improvement is to judge whether the drug regulation direction is correct through the regulation effect evaluation coefficient.

7. The information-based precise drug control method for hemodialysis anemia patients according to claim 6, characterized in that: The S4 uses an information management tool to monitor changes in anemia indicators in the patient's body in real time and record monitoring data, including fluctuations and trends in the levels of hemoglobin, ferritin, and transferrin saturation. Based on the real-time monitoring data, it analyzes whether the current drug dosage and injection frequency help maintain a stable anemia indicator level. If the monitoring data shows that the anemia indicator level has not reached the target or has an unstable trend, the drug dosage and injection frequency are appropriately increased or decreased according to the changes in the anemia indicator level.

8. The information-based precise drug control method for hemodialysis anemia patients according to claim 7, characterized in that: The S5 extracts patient characteristic parameters from the basic information data collected from the two groups of patients, including the patients' age, gender, dialysis age, underlying diseases, previous treatment records, and drug responses, and records historical data on changes in anemia indicator levels of the two groups of patients over time. A linear regression algorithm is used to establish a prediction model, in which drug dosage, injection frequency, and patient characteristics are used as independent variables, and changes in anemia indicator levels are used as dependent variables to train the model. The trained model is used to calculate the predictive value of each patient characteristic for improvement in anemia indicators.

9. The information-based precise drug control method for hemodialysis anemia patients according to claim 8, characterized in that: The S6 analyzes the difference in the improvement of anemia index levels between the study group patients and the control group patients based on the predicted value of the improvement of anemia index based on each patient characteristic, and calculates the difference in the probability of improvement of anemia index levels of the two groups of patients, which is used to track and monitor the effect of the drug after regulation, and sends the difference analysis monitoring results to the terminal in real time for display.

10. An information-based precise drug control system for hemodialysis anemia patients, implementing the information-based precise drug control method for hemodialysis anemia patients according to any one of claims 1 to 9, characterized in that: include: Data collection module: used to collect basic information data of multiple patients and randomly divide them into a research group receiving information-based drug management and a control group receiving conventional treatment. The hemoglobin, ferritin, and transferrin saturation levels of the two groups of patients were regularly monitored and recorded. Treatment effect analysis module: Based on the preliminary analysis of hemoglobin, ferritin and transferrin saturation of the two groups of patients, the changes in anemia indicators of the two groups of patients are compared. According to the comparison results, the difference in treatment effect is analyzed, and the drug dosage and injection frequency are preliminarily adjusted according to the analyzed difference in efficacy; Drug regulation analysis module: Based on the analysis of the relationship between the adjustment of drug dosage and injection frequency and the changes in anemia index levels in the study group of patients before and after the adjustment, the effect of drug regulation on anemia improvement is evaluated to determine whether the direction of drug regulation is correct; Regulation and Optimization Module: This module is used to monitor the changes in anemia levels in patients during drug regulation in real time. Based on the changes in anemia levels in patients, it analyzes whether the adjustment of drug dosage in information management is reasonable, and dynamically optimizes drug dosage and injection frequency. Improvement effect prediction module: Build a prediction model based on patient characteristic parameters and historical data, and use the prediction model to predict the improvement of each patient's anemia indicators; Improvement effect tracking module: Based on the prediction results, the differences in the improvement of anemia index levels between the research group and the control group are analyzed, and the difference in the probability of improvement of anemia index levels of the two groups of patients is calculated for further tracking and monitoring of drug regulation.

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