Chronic kidney disease hemodialysis whole process quality control method and system

Abstract

The invention discloses a chronic kidney disease hemodialysis whole-process quality control method and system, and the method and system remarkably reduce the time cost of medical care in manual tracking of patient indexes, repeated checking of medical records and coordinated communication through long-term trend monitoring, thereby optimizing the clinical working process and improving the treatment efficiency. Obtaining test results of related test indexes of hemodialysis of the patient from a medical test information system; acquiring historical treatment information of the patient from the HIS system; classifying the historical treatment information according to treatment items; classifying test results according to corresponding treatment items; for each treatment item, integrated analysis is carried out by integrating the associated inspection indexes and historical treatment information; based on the classification of the test results, comprehensively analyzing the conclusion and the historical treatment information, and generating a treatment scheme through a preset clinical rule base; and performing structured output on the generated treatment scheme according to the treatment items, wherein the structured output comprises treatment item names, specific suggestions, drug doses and drug administration routes.

Description

Technical Field

[0001] The present invention relates to a method and system for quality control of the entire process of hemodialysis for chronic kidney disease. Background Art

[0002] Epidemiological surveys show that chronic kidney disease has become one of the major diseases threatening public health worldwide, and its prevalence is still rising. As the disease progresses, chronic kidney disease may eventually progress to end-stage kidney disease. Hemodialysis is a common renal replacement therapy for treating end-stage kidney disease, which removes metabolic wastes, toxins, and excess water from the blood through diffusion, convection, filtration, etc., so as to achieve the purpose of prolonging the survival cycle of patients. It is reported that currently, the number of patients receiving maintenance hemodialysis in China has exceeded 9 million. The "Standard Operating Procedures for Blood Purification" (2021 edition) points out that medical quality control indicators are the yardsticks for evaluating the medical quality of hemodialysis, and the medical quality and safety of hemodialysis are directly related to the health and life of patients. Therefore, hemodialysis centers should regularly evaluate medical quality control indicators to continuously improve medical quality. In view of this, the "Standard Operating Procedures for Blood Purification" (2021 edition) has clearly stipulated the medical quality management indicators for hemodialysis patients and their detection frequencies. For example, blood routine, blood biochemistry, etc. are examined once every 3 months, and C-reactive protein, serum ferritin, intact parathyroid hormone, etc. are monitored once every 6 months.

[0003] Maintenance hemodialysis patients need to regularly review relevant biochemical indicators to monitor the changes in their conditions, helping medical staff to promptly understand the patients' situations and adjust treatment plans. However, in clinical practice, due to the large number of outpatient dialysis patients and limited medical staff, problems such as increased management difficulty, failure to conduct regular reviews in a timely manner, and failure to adjust treatment plans in a timely manner after the review results are available occur frequently, seriously affecting the dialysis quality of patients.

[0004] Currently, the method used in clinical practice for managing the test results of outpatient hemodialysis patients is as follows: The responsible doctor or nurse reminds the patient of the need to review relevant biochemical indicators according to the schedule. After the patient completes the examination, the test results are printed and discussed with the doctor, and then the responsible doctor adjusts the treatment plan according to the test results.

[0005] However, the current management method has the following deficiencies:

[0006] 1. Even if the responsible doctor or nurse reminds the patient of the review, there are still some patients with poor compliance who fail to review on time.

[0007] 2. The patient fails to communicate with the doctor in a timely manner after obtaining the test results, resulting in delays in adjusting the treatment plan.

[0008] 3. The test data that can only be obtained once at a time prevents the responsible doctors and nurses from viewing the changing trends of each indicator in recent years, which affects the comprehensive assessment of the patient's condition.

[0009] 4. For the abnormal indicators that need to be rechecked after adjusting the treatment plan, the lack of intelligent reminder function causes patients to fail to conduct necessary rechecks in a timely manner, thus affecting the control of the condition.

[0010] 5. There is a lack of an effective communication platform between medical staff and patients, and real-time communication and management of test results cannot be achieved through an intelligent platform.

[0011] 6. The test results of patients fail to be promptly feedback by doctors and nurses, resulting in a decline in patient compliance and affecting the harmony of the doctor-patient relationship. Summary of the Invention

[0012] The present invention proposes a method and system for quality control of the whole process of hemodialysis for chronic kidney disease. Through long-term trend monitoring, the time costs of medical staff in manually tracking patient indicators, repeatedly checking medical records, and coordinating communication are significantly reduced, thereby optimizing the clinical workflow and improving the treatment efficiency.

[0013] In the first aspect, a method for quality control of the whole process of hemodialysis for chronic kidney disease includes: obtaining the test results of the test indicators related to the hemodialysis of the patient from the medical test information system; obtaining the historical treatment information of the patient from the HIS system; classifying the historical treatment information according to the treatment items; classifying the test results according to the corresponding treatment items and determining whether they are within the normal range; for each treatment item, integrating the associated test indicators and historical treatment information for comprehensive analysis, and the comprehensive analysis includes: identifying the linkage relationship between the test indicators under the same treatment item; comparing the causal relationship between the previous treatment adjustment and the change of the test indicators; based on the classification of the test results, the conclusion of the comprehensive analysis, and the historical treatment information, generating a treatment plan through a preset clinical rule library; and structuring and outputting the generated treatment plan according to the treatment items, and the structured output includes the name of the treatment item, specific suggestions, drug dosage, and administration route.

[0014] Second aspect, a quality control system for the entire process of hemodialysis for chronic kidney disease, comprising: a data acquisition module configured to obtain the test results of the test indicators related to the patient's hemodialysis from the medical test information system and obtain the patient's historical treatment information from the HIS system; a data analysis and evaluation module configured to: classify the historical treatment information according to the treatment items, classify the test results according to the corresponding treatment items, and determine whether they are within the normal range. For each treatment item, integrate the associated test indicators and historical treatment information for comprehensive analysis. The comprehensive analysis includes: identifying the linkage relationship between the test indicators under the same treatment item; comparing the causal relationship between the past treatment adjustments and the changes in the test indicators; and a treatment plan generation module configured to generate a treatment plan based on the classification of the test results, the comprehensive analysis conclusion, and the historical treatment information, and structurally output the generated treatment plan according to the treatment items. The structural output includes the treatment item name, specific suggestions, drug dosage, and administration route.

[0015] Third aspect, a computer system, comprising: a processor; a memory including one or more computer program modules; wherein, the one or more computer program modules are stored in the memory and configured to be executed by the processor, and the one or more computer program modules include instructions for implementing the quality control method for the entire process of hemodialysis for chronic kidney disease as described above.

[0016] Fourth aspect, a computer-readable storage medium for storing non-temporary computer-readable instructions, which can implement the quality control method for the entire process of hemodialysis for chronic kidney disease when the non-temporary computer-readable instructions are executed by a computer. Description of the Drawings

[0017] Figure 1 is a flowchart of the quality control method for the entire process of hemodialysis for chronic kidney disease provided by an embodiment of the present invention.

[0018] Figure 2 is a block diagram of the quality control system for the entire process of hemodialysis for chronic kidney disease provided by an embodiment of the present invention. Detailed Embodiments

[0019] Figure 1 Displays a flowchart of the quality control method for the entire process of hemodialysis for chronic kidney disease. This method is implemented through a computer software system and can perform quality control and comprehensive management on the entire treatment cycle of chronic kidney disease patients. The following will elaborate on the specific steps of this method in detail.

[0020] Step 1, Patient Identification and Data Acquisition

[0021] Precisely identify the patient through the patient's name and ID number, and obtain data from the following systems:

[0022] Medical testing information system (such as Ruimei testing system): Obtain data on test results related to maintenance hemodialysis for patients within a specific time period (such as the last 3 months or 1 year), including hemoglobin, blood calcium, blood phosphorus, parathyroid hormone [PTH], etc.).

[0023] HIS system (Hospital Information System): Obtain the patient's historical treatment information, including past medication records (such as EPO preparations, iron agents, calcium mimetics, etc.), dialysis parameters, complication management records, etc.

[0024] Note: The Ruimei testing system supports seamless docking with systems such as HIS, LIMS, and PACS to achieve real-time sharing of test data. Data collection must comply with medical data security specifications (such as HIPAA or the Domestic Personal Information Protection Law) to ensure patient privacy.

[0025] Step 2, Data analysis and evaluation

[0026] 2.1 Classify historical treatment information by treatment item (complication type)

[0027] Classify the patient's past treatment information obtained from the HIS system according to the treatment item (complication type). For example: Treatment related to renal anemia (corresponding to the hemoglobin [Hb] index): Dosage, medication frequency, and efficacy evaluation of ESAs (erythropoietin); Iron supplementation (such as dosage and course of intravenous iron or oral iron); Transfusion records (such as number of transfusions and hemoglobin recovery).

[0028] Treatment related to mineral and bone metabolism disorders (corresponding to blood calcium, blood phosphorus, parathyroid hormone [PTH] indices): Types of phosphate binders (such as calcium carbonate, sevelamer) and dosage adjustment records; Dosage and efficacy of active vitamin D (such as calcitriol, alfacalcidol); Usage records and adverse reaction conditions of calcium mimetics (such as cinacalcet). Treatment of other complications (such as cardiovascular diseases, infections, etc., expand the classification according to actual test items).

[0029] Example: If the patient's current hemoglobin is 85 g / L (lower than the normal value of 110 g / L), the system will automatically associate their past ESA dosage adjustment records, iron supplementation, and transfusion history and classify them into the "Treatment related to renal anemia" category.

[0030] 2.2 Divide the test results into levels according to the indicators associated with the treatment items

[0031] The test results obtained from the medical testing information system (such as the Ruimei testing system) are classified according to their corresponding treatment items (complication types) and judged whether they are within the normal range.

[0032] Classification and Association of Test Results:

[0033] Test indicators related to renal anemia: hemoglobin (Hb), serum ferritin (SF), transferrin saturation (TSAT). Test indicators related to mineral and bone metabolism: serum calcium, serum phosphorus, parathyroid hormone (PTH), serum magnesium, urinary calcium / phosphorus excretion rate. Test indicators related to other complications: extended according to treatment items (e.g., for cardiovascular diseases, attention should be paid to blood lipids, BNP, etc.).

[0034] Division of Test Result Levels:

[0035] Normal range: conforms to the reference values given in the clinical guidelines (e.g., hemoglobin ≥ 110 g / L). Abnormal range: Low: below the normal lower limit (e.g., serum phosphorus < 0.8 mmol / L). High: above the normal upper limit (e.g., PTH > 600 pg / mL).

[0036] Example: If the patient's current PTH is 800 pg / mL (exceeding the standard), the system automatically classifies it into the "Test indicators related to abnormal mineral and bone metabolism" and marks it as "High".

[0037] 2.3 Comprehensive Analysis of Multiple Indicators (associated by treatment items)

[0038] For each treatment item, a comprehensive analysis is performed and a standardized conclusion label is output through the following steps: First, the linkage relationship between the test indicators under the same treatment item is identified. For example, in the "treatment of abnormal mineral and bone metabolism", the blood phosphorus level is analyzed to see whether it is positively correlated with the parathyroid hormone (PTH) concentration (e.g., whether the PTH increase exceeds the threshold for every 0.5mmol / L increase in blood phosphorus); in the "treatment of renal anemia", the correlation between ferritin level and hemoglobin concentration is evaluated (e.g., whether hemoglobin does not reach the target value when ferritin is <100ng / mL). Secondly, the causal relationship between previous treatment adjustments and changes in test indicators is compared. For example, if the dose of erythropoietin stimulators (ESAs) is increased by 20% within 3 months, analyze whether hemoglobin is simultaneously increased to the target range (e.g., 10-11g / dL); if the dose of phosphate binders is increased from 0.6g / meal to 1.2g / meal, verify whether the blood phosphorus level drops to the target range (e.g., <1.78mmol / L). At the same time, potential risk patterns are automatically marked. For example, when serum ferritin is <100ng / mL and transferrin saturation is <20% for 3 months but intravenous iron is not supplemented, it is marked as "uncorrected iron deficiency"; if PTH is >600pg / mL (normal range: 150-300pg / mL) for 6 consecutive months but calcimimetics such as cinacalcet are not started, it is marked as "delayed start of calcimimetics"; if the phosphate binder dose is <the minimum value recommended by the guidelines (such as calcium carbonate <0.6g / meal) and blood phosphorus continues to exceed the standard, it is marked as "inadequate phosphate binder dose". Finally, based on the above analysis, standardized conclusion labels are output (such as "insufficient iron reserves or inflammatory effects" and "inadequate phosphate binder dose"), and key data basis is marked (such as "PTH continues to be >600pg / mL (average of the past 6 months)") to ensure that the conclusion is directly related to the treatment project and provide an accurate basis for the generation of subsequent plans.

[0039] 2.4 Analysis of test trends (by treatment item)

[0040] Automatically generate trend charts of test indicators associated with each treatment item in a specific time period (such as the past three years) for patients to assist doctors in judging long-term trends. For example, trends related to renal anemia: monthly hemoglobin change trend, associated ESA dose adjustment records; correlation analysis between iron supplementation and hemoglobin recovery. Trends related to mineral and bone metabolism: quarterly change curves of blood phosphorus and PTH, comparing the time points of active vitamin D or calcimimetic use; correlation analysis between blood calcium and phosphate binder doses.

[0041] Step 3: Personalized treatment plan generation

[0042] 3.1 Suggestions for Rule Engine-Driven Solutions

[0043] Based on the test result classification and level division results in Step 2.2, the comprehensive analysis conclusions in Step 2.3 (such as "iron deficiency not corrected"), and historical treatment information (such as drug intolerance records), a preliminary plan is automatically generated through a preset clinical rule base (such as the KDIGO guidelines or hospital customized plans).

[0044] Here is an example of rule matching: If "hemoglobin < 100g / L" + "sufficient iron reserve (SF ≥ 100ng / mL and TSAT ≥ 20%)" → recommend "increase the ESA dose by 20%". If "PTH > 600pg / mL" + "no history of using calcium mimetics" + "normal blood calcium" → recommend "initiate cinacalcet at 5mg / day".

[0045] In addition, suggestions conflicting with the patient's contraindications are automatically excluded (such as not recommending if allergic to calcium mimetics).

[0046] 3.2 Plan integration and push

[0047] The generated plan is structured and output according to treatment items. The structured output includes the treatment item name, specific suggestions, drug dosage, and administration route. For example, for the treatment plan of renal anemia: ESA dose adjustment, intravenous iron supplement plan. For the treatment plan of minerals and bone metabolism: phosphorus binder dose adjustment, combination of active vitamin D and calcium mimetics.

[0048] Each suggestion is marked with the source of the basis (such as "based on the 2020 updated version of the KDIGO guidelines"), and key data support is listed (such as "due to continuous PTH > 600pg / mL (average value in the past 3 months)"). In addition, the test trend chart is associated with the treatment suggestions. For example, the time node of ESA dose adjustment is marked on the hemoglobin trend chart (such as "after the dose increase in June 2023, the hemoglobin increased from 9.5g / dL to 11.2g / dL"), visually showing the causal relationship between the treatment effect and the adjustment.

[0049] Step 4, Manual review and plan confirmation

[0050] Doctor's operation: Review the plan by treatment item category and adjust the suggestions in combination with the patient's clinical manifestations (such as symptoms, complications). For example: If the patient is allergic to calcium mimetics, the doctor can manually replace it with other drugs (such as an alternative plan to reduce PTH).

[0051] Nurse's operation: Check the drug dosage and administration route (such as intravenous injection or oral administration) to ensure there are no conflicts.

[0052] In addition, after being confirmed by the doctor, the plan is automatically synchronized to the HIS system to generate an electronic medical order. The treatment plan is pushed to the patient side through the hospital system or text message (such as adjusted drugs, next dialysis parameters, etc.).

[0053] As Figure 2 ,the present invention proposes a quality control system for the whole process of hemodialysis for chronic kidney disease, realizing closed-loop management from inspection and monitoring to treatment adjustment. The system includes a data acquisition module, a data analysis and evaluation module, and a treatment plan generation module.

[0054] The data acquisition module identifies the patient: using the patient's name and ID number for precise matching, obtaining maintenance hemodialysis-related test result data (such as hemoglobin, blood phosphorus, PTH, etc.) within a specific time period from the medical laboratory information system (such as Ruimei laboratory system), and extracting the patient's historical treatment information from the hospital information system (HIS), including past medication records (such as EPO preparations, iron agents, calcium mimetics), dialysis parameters (such as blood flow rate, ultrafiltration volume), complication management records, etc.

[0055] The data is then processed by the data analysis and evaluation module: this module includes a treatment information processing module, a test result processing module, an analysis module, and a visualization module.

[0056] The treatment information processing module classifies the past treatment information in the HIS system according to treatment items (complication types). For example, classifying ESA dose adjustment and blood transfusion records as "treatment for renal anemia", and phosphorus binder use and active vitamin D dose as "treatment for mineral and bone metabolism disorders".

[0057] The test result processing module classifies the test results according to treatment items (such as hemoglobin associated with renal anemia, PTH associated with mineral metabolism), and judges whether it is within the normal range based on clinical reference values (such as blood phosphorus < 1.78 mmol / L is normal, > 2.0 mmol / L is abnormal).

[0058] The analysis module conducts a comprehensive analysis for each treatment item by integrating its associated test indicators and historical treatment information: identifying the correlation between test indicators (such as whether there is a positive correlation between elevated blood phosphorus and elevated PTH); comparing past treatment adjustments (such as changes in ESA dose) with changes in test indicators (such as whether hemoglobin increases after dose upregulation); automatically marking potential risk patterns (such as insufficient iron reserves but no iron supplementation, persistent PTH exceeding the standard without using calcium mimetics), and outputting standardized conclusion labels (such as "uncorrected iron deficiency", "insufficient dose of phosphorus binder").

[0059] The visualization module simultaneously generates a trend chart of test indicators for a specific time period of the patient (such as the past three years) (such as quarterly change curves of hemoglobin, PTH), assisting doctors in intuitively judging the long-term trend.

[0060] Based on the above analysis results, the treatment plan generation module automatically generates preliminary treatment suggestions in combination with a preset clinical rule library (such as the KDIGO guidelines or hospital-customized plans): generate a structured plan classified by treatment items. For example, the renal anemia treatment plan may include the adjustment of ESA doses (such as an increase of 20%), and the intravenous iron supplementation plan (such as 1000 mg per month); the treatment plan for minerals and bone metabolism may involve the adjustment of phosphate binder doses (such as increasing calcium carbonate to 1.5 g / day), and the combination of active vitamin D and calcium mimetics (such as cinacalcet 5 mg / day). The source of the suggestion (such as "based on the updated version of the KDIGO guidelines in 2020") will be marked in the plan, and the key data basis will be listed (such as "due to the continuous PTH > 600 pg / mL (average value in the past 3 months)"). In addition, the system marks the key treatment nodes in the trend chart (such as the corresponding relationship between the ESA dose adjustment time point and the change in hemoglobin), enhancing the visual relevance of the analysis.

[0061] In the clinical operation process, the doctor reviews the plan classified by treatment items and makes adjustments in combination with the patient's clinical manifestations (such as symptoms and complications) (for example, when the patient is allergic to calcium mimetics, manually replace it with sildenafil-like drugs). The nurse checks the drug dosage, administration route (such as intravenous injection or oral administration), and dialysis parameter settings to ensure there are no conflicts. After being confirmed by the doctor, the plan is automatically synchronized to the HIS system to generate an electronic medical order, and is pushed to the patient end through the hospital system or text message, informing the adjusted drugs, dialysis parameters, and the next review time, improving patient compliance. The entire process forms a closed loop from data collection, analysis, plan generation to execution feedback, effectively improving the standardization and personalization level of hemodialysis treatment.

[0062] The present invention also provides an embodiment of a computer. The computer includes a processor and a memory. The memory is used to store non-temporary computer-readable instructions (such as one or more computer program modules). The processor is used to run the non-temporary computer-readable instructions, and when the non-temporary computer-readable instructions are run by the processor, one or more steps in the above-mentioned full-process quality control method for hemodialysis of chronic kidney disease can be executed. The memory and the processor can be interconnected through a bus system and / or other forms of connection mechanisms.

[0063] For example, the processor can be a central processing unit (CPU), a graphics processing unit (GPU), or other forms of processing units with data processing capabilities and / or program execution capabilities. For example, the central processing unit (CPU) can be of the X86 or ARM architecture, etc. The processor can be a general-purpose processor or a dedicated processor, and can control other components in the computer to execute the desired functions.

[0064] For example, the memory may include any combination of one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, erasable programmable read-only memory (EPROM), compact disc read-only memory (CD-ROM), USB memory, flash memory, etc. One or more computer program modules may be stored on the computer-readable storage media, and the processor may run one or more computer program modules to implement various functions of the computer.

[0065] The present invention also provides an embodiment of a computer-readable storage medium for storing non-temporary computer-readable instructions, which can implement one or more steps in the above-mentioned quality control method for the entire process of hemodialysis for chronic kidney disease when executed by a computer. When the quality control method and system for the entire process of hemodialysis for chronic kidney disease provided by the embodiments of the present application are implemented in the form of software and sold or used as an independent product, they can be stored in a computer-readable storage medium. For the relevant description of the storage medium, reference can be made to the corresponding description of the memory in the computer above, and details will not be elaborated here.

[0066] The method / system of the present invention can automatically remind patients to regularly undergo routine examinations and recheck abnormal indicators. After the patient's test results are generated, they will be immediately fed back to the responsible doctor and nurse, and a final treatment plan will be synchronously generated for the doctor and patient to view, ensuring the timeliness of information transmission.

[0067] The responsible doctor and nurse can comprehensively view the dynamic change trend charts of the patient's various indicators through the system (such as the long-term trends of key indicators such as hemoglobin and PTH), and combine the treatment adjustment nodes (such as changes in drug dosage and optimization of dialysis parameters) to intuitively evaluate the patient's disease progression and treatment effect.

[0068] The patient's test results can quickly obtain feedback from the medical staff team, clarify the subsequent treatment direction, thereby enhancing the patient's trust and cooperation with the treatment plan, promoting doctor-patient communication, and reducing contradictions caused by information delay or misunderstanding.

[0069] Through automated data integration and analysis, the system significantly reduces the time cost for medical staff to manually track patient indicators, repeatedly check medical records, and communicate and coordinate, enabling medical staff resources to be more focused on decision-making for complex conditions and patient care.

[0070] Through precise adjustment of treatment plans and long-term trend monitoring, the system can effectively delay the progression of chronic kidney disease, extend the dialysis survival period (dialysis age) of patients, reduce the risk of complications at the same time, and ultimately improve the overall quality of life of patients.

Claims

1. A quality control method for the whole process of hemodialysis in chronic kidney disease, characterized in that including: Obtaining the test results of the test indicators related to the patient's hemodialysis from the medical test information system; Obtaining the patient's historical treatment information from the HIS system; Classifying the historical treatment information according to the treatment items; Classifying the test results according to the corresponding treatment items and determining whether they are within the normal range; For each treatment item, integrating its associated test indicators and historical treatment information for comprehensive analysis. The comprehensive analysis includes: identifying the linkage relationship between test indicators under the same treatment item; comparing the causal relationship between previous treatment adjustments and changes in test indicators; Generating a treatment plan through a preset clinical rule base based on the classification of test results, comprehensive analysis conclusions, and historical treatment information; Structurally outputting the generated treatment plan according to the treatment items. The structural output includes the treatment item name, specific suggestions, drug dosage, and administration route.

2. The method according to claim 1, wherein Marking potential risk patterns during the comprehensive analysis process.

3. The method according to claim 1, characterized in that Generating a trend chart of the test indicators associated with each treatment item for a specific period of the patient.

4. The method according to claim 3, wherein Marking the source basis for each treatment suggestion in the plan, listing data support, and associating the trend chart of the test indicators with the treatment suggestions.

5. A quality control system for the entire process of hemodialysis in chronic kidney disease, characterized in that, including: A data collection module configured to obtain the test results of the test indicators related to the patient's hemodialysis from the medical test information system and obtain the patient's historical treatment information from the HIS system; A data analysis and evaluation module configured to: classify the historical treatment information according to the treatment items, classify the test results according to the corresponding treatment items and determine whether they are within the normal range, and for each treatment item, integrate its associated test indicators and historical treatment information for comprehensive analysis. The comprehensive analysis includes: identifying the linkage relationship between test indicators under the same treatment item; comparing the causal relationship between previous treatment adjustments and changes in test indicators; and A treatment plan generation module configured to generate a treatment plan through a preset clinical rule base based on the classification of test results, comprehensive analysis conclusions, and historical treatment information, and structurally output the generated treatment plan according to the treatment items. The structural output includes the treatment item name, specific suggestions, drug dosage, and administration route.

6. The system according to claim 5, characterized in that Marking potential risk patterns during the comprehensive analysis process.

7. The system according to claim 5, characterized in that Generating a trend chart of the test indicators associated with each treatment item for a specific period of the patient.

8. The system according to claim 8, characterized in that Marking the source basis for each treatment suggestion in the plan, listing data support, and associating the trend chart of the test indicators with the treatment suggestions.

9. A computer system, characterized in that, including: A processor; A memory including one or more computer program modules; Wherein, the one or more computer program modules are stored in the memory and configured to be executed by the processor, and the one or more computer program modules include instructions for implementing the chronic kidney disease hemodialysis full-process quality control method according to any one of claims 1-4.

10. A computer-readable storage medium for storing non-transitory computer-readable instructions, characterized in that, When the non-temporary computer-readable instructions are executed by a computer, they can implement the chronic kidney disease hemodialysis full-process quality control method according to any one of claims 1-4.

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