A multi-role task coordination system for peritoneal dialysis management of kidney disease

Abstract

The application provides a kidney disease peritoneal dialysis management multi-role task cooperation system, relates to the technical field of cooperation management, and comprises a treatment event chain construction module, a volume abnormality evidence package construction module, a cooperative task dependency graph generation module, a task node state judgment module and a prescription issuing gating module; the treatment event chain construction module binds the body weight, blood pressure, ultrafiltration volume, dialysate in-out volume, peritoneal dialysis prescription execution record, diet record and medication record uploaded by the patient end to the same treatment cycle according to the treatment time; the volume abnormality evidence package construction module generates a volume management abnormality evidence package when the body weight, blood pressure and ultrafiltration volume meet the preset correlation condition; the cooperative task dependency graph generation module generates multi-role tasks; the task node state judgment module generates a task locking state table; and the prescription issuing gating module controls the adjustment of prescription writing into the patient end execution queue according to the task locking state table.

Description

Technical Field

[0001] This invention relates to the field of collaborative management technology, and in particular to a multi-role task collaborative system for the management of peritoneal dialysis for kidney disease. Background Technology

[0002] Existing peritoneal dialysis management systems primarily focus on patient information management, follow-up records, dialysis prescription maintenance, laboratory indicator input, and remote monitoring. Data such as weight, blood pressure, ultrafiltration volume, and dialysate inflow / outflow are collected from the patient's end or the peritoneal dialysis device and uploaded to the hospital. Doctors or nurses can then view abnormal alerts, adjust prescriptions, or schedule follow-ups on the management platform. Some systems can also incorporate rules or models to provide alerts regarding dialysis adequacy and complication risks.

[0003] However, in home-based automated peritoneal dialysis scenarios, patients need to connect a large volume of dialysis fluid and complete the fluid exchange according to a preset procedure before nighttime treatment. Abnormalities often involve simultaneous doctor judgment, nurse follow-up, nutritionist dietary intervention, pharmacist medication verification, and family supervision. Existing systems typically only generate abnormality records or alerts for a single healthcare provider, failing to automatically break down "sudden drop in ultrafiltration volume accompanied by weight gain and elevated blood pressure" into multi-role tasks and track their completion status. This may result in doctors adjusting prescriptions without nurses simultaneously verifying the operation, and nutritionists failing to restrict sodium and water intake in a timely manner, thus affecting the closed loop of volume management. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-role task collaboration system for the management of peritoneal dialysis in nephropathy, aiming to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A multi-role task collaboration system for peritoneal dialysis management of renal disease, the system comprising: The treatment event chain construction module is used to sort the patient's weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record according to the treatment time, and bind the data within the same treatment cycle to the same patient identifier to generate a peritoneal dialysis treatment event chain; The volume abnormality evidence package construction module is used to extract the trends of weight change, blood pressure change, ultrafiltration volume change, peritoneal dialysis prescription execution, dietary intake, and medication administration within a continuous treatment cycle based on the peritoneal dialysis treatment event chain, and generate a volume management abnormality evidence package when the preset correlation conditions are met, such as weight increase, blood pressure increase, and ultrafiltration volume decrease. The collaborative task dependency graph generation module is used to generate doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks and drug risk review tasks based on the capacity management abnormal evidence package, and to configure input data items, output data items, locking conditions and unlocking conditions for each task to generate a collaborative task dependency graph. The task node status determination module is used to determine whether the output data items of each task satisfy the input data items of subsequent tasks according to the collaborative task dependency graph, and to generate a task lock status table when the output data items are missing, the task is not completed, or there are conflicts between the output data items. The conflict between the output data items includes generating at least one of the following: operation conflict identifier, dietary evidence missing identifier, or medication evidence missing identifier. The prescription issuance gating module is used to determine whether the prescription is ready for issuance based on the task lock status table and the prescriptions generated by the doctor's prescription adjustment task. When there is a locked state, an incomplete state, or a conflict state, the prescription is marked as a prescription to be confirmed and is prohibited from being written to the patient's execution queue. When there is no locked state, incomplete state, or conflict state, the prescription is marked as a prescription that can be issued and is allowed to be written to the patient's execution queue. The conflict state includes at least one of the following: operation conflict identifier, dietary evidence missing identifier, and medication evidence missing identifier.

[0006] The above-described solution of the present invention has at least the following beneficial effects: This invention uses a treatment event chain construction module to group patient-uploaded data such as weight, blood pressure, ultrafiltration volume, dialysate inflow and outflow, peritoneal dialysis prescription execution records, dietary records, and medication records into the same treatment cycle according to treatment time, and bind them to the same patient identifier. This allows the monitoring data, prescription execution data, dietary data, and medication data generated separately during home peritoneal dialysis to form a continuous peritoneal dialysis treatment event chain, avoiding the need for volume abnormality judgment to rely solely on a single uploaded data or a single abnormality prompt.

[0007] Based on the peritoneal dialysis treatment event chain, the volume abnormality evidence package construction module extracts the trends of weight change, blood pressure change, ultrafiltration volume change, peritoneal dialysis prescription execution, dietary intake, and medication administration within a continuous treatment cycle. When weight increase, blood pressure increase, and ultrafiltration volume decrease meet the preset correlation conditions, a volume management abnormality evidence package is generated. This enables the abnormal result corresponding to "sudden drop in ultrafiltration volume accompanied by weight increase and blood pressure increase" to establish a data correlation with prescription execution, dietary intake, and medication records, providing the same abnormal event basis for subsequent multi-role processing.

[0008] Furthermore, the collaborative task dependency graph generation module generates doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks based on the capacity management anomaly evidence package. It also configures input data items, output data items, locking conditions, and unlocking conditions for each task, so that capacity management anomalies are no longer just anomaly records or reminders for a single medical staff, but are transformed into a collaborative task structure with role division and dependency relationships.

[0009] After the collaborative task dependency graph is formed, the task node status determination module determines whether there are missing output data items, incomplete tasks, or conflicts between output data items based on the output data items of each task, and generates a task lock status table. This allows the processing status of nurse operation verification, nutritional intake confirmation, and drug risk review to serve as the basis for judgment before prescription adjustment and issuance, preventing the doctor's prescription adjustment results from becoming detached from the processing results of other roles.

[0010] Finally, the prescription issuance gating module determines whether the prescription is ready for issuance based on the task lock status table and the prescriptions generated by the doctor's prescription adjustment task. If a locked, incomplete, or conflicting state exists, the prescription is marked as a prescription pending confirmation and prohibited from being written to the patient's execution queue. If no locked, incomplete, or conflicting state exists, the prescription is marked as a prescription that can be issued and allowed to be written to the patient's execution queue. This makes the writing status of the prescription subject to the completion status and conflicting state of multiple roles' tasks, reducing the risk that the prescription will directly enter the patient's execution queue when operation verification, sodium and water intake confirmation, or volume-related medication review is not completed. Attached Figure Description

[0011] Figure 1 This is an architecture diagram of a multi-role task collaboration system for peritoneal dialysis management of kidney disease, provided by an embodiment of the present invention. Detailed Implementation

[0012] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0013] like Figure 1 As shown, embodiments of the present invention propose a multi-role task collaboration system for peritoneal dialysis management of renal disease, the system comprising: The treatment event chain construction module is used to sort the patient's weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record according to the treatment time, and bind the data within the same treatment cycle to the same patient identifier to generate a peritoneal dialysis treatment event chain; The volume abnormality evidence package construction module is used to extract the trends of weight change, blood pressure change, ultrafiltration volume change, peritoneal dialysis prescription execution, dietary intake, and medication administration within a continuous treatment cycle based on the peritoneal dialysis treatment event chain, and generate a volume management abnormality evidence package when the preset correlation conditions are met, such as weight increase, blood pressure increase, and ultrafiltration volume decrease. The collaborative task dependency graph generation module is used to generate doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks and drug risk review tasks based on the capacity management abnormal evidence package, and to configure input data items, output data items, locking conditions and unlocking conditions for each task to generate a collaborative task dependency graph. The task node status determination module is used to determine whether the output data items of each task satisfy the input data items of subsequent tasks according to the collaborative task dependency graph, and to generate a task lock status table when the output data items are missing, the task is not completed, or there are conflicts between the output data items. The conflict between the output data items includes generating at least one of the following: operation conflict identifier, dietary evidence missing identifier, or medication evidence missing identifier. The prescription issuance gating module is used to determine whether the prescription is ready for issuance based on the task lock status table and the prescriptions generated by the doctor's prescription adjustment task. When there is a locked state, an incomplete state, or a conflict state, the prescription is marked as a prescription to be confirmed and is prohibited from being written to the patient's execution queue. When there is no locked state, incomplete state, or conflict state, the prescription is marked as a prescription that can be issued and is allowed to be written to the patient's execution queue. The conflict state includes at least one of the following: operation conflict identifier, dietary evidence missing identifier, and medication evidence missing identifier.

[0014] In this embodiment of the invention, the treatment event chain construction module binds the patient's weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record into a peritoneal dialysis treatment event chain according to the treatment time, so that the detection data, prescription execution data, diet data and medication data within the same treatment cycle are associated under the same patient identifier.

[0015] The volume abnormality evidence package construction module extracts the trends of weight change, blood pressure change, ultrafiltration volume change, peritoneal dialysis prescription execution, dietary intake, and medication use within a continuous treatment cycle based on the peritoneal dialysis treatment event chain. When weight increase, blood pressure increase, and ultrafiltration volume decrease simultaneously meet preset correlation conditions, a volume management abnormality evidence package is generated, so that the volume abnormality result data corresponds with prescription execution, dietary intake, and medication records.

[0016] The collaborative task dependency graph generation module generates doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks based on the capacity management anomaly evidence package. It also configures input data items, output data items, locking conditions, and unlocking conditions for each task, so that the processing results of different roles participate in the issuance control of prescription adjustment in the form of a collaborative task dependency graph.

[0017] The task node status determination module generates a task lock status table when output data items are missing, tasks are incomplete, or there are conflicts between output data items. The prescription issuance gating module controls the issuance status of the adjusted prescriptions according to the task lock status table. Adjusted prescriptions with locked, incomplete, or conflicting statuses are marked as pending confirmation prescriptions and prohibited from being written to the patient's execution queue. Adjusted prescriptions without locked, incomplete, or conflicting statuses are marked as issueable prescriptions and allowed to be written to the patient's execution queue. This avoids adjusted prescriptions from directly entering the patient's execution queue when operation verification, diet confirmation, or medication review is not closed.

[0018] In a preferred embodiment of the present invention, the preset correlation condition is used to generate a capacity management anomaly evidence package when weight gain, blood pressure increase, and ultrafiltration volume decrease meet the preset correlation condition, including: Read the peritoneal dialysis treatment event chain under the same patient identifier, and extract the weight record, blood pressure record and ultrafiltration volume record within the continuous treatment cycle from the peritoneal dialysis treatment event chain; According to the starting boundary of the treatment cycle, the weight records, blood pressure records and ultrafiltration volume records within the continuous treatment cycle are arranged in sequence; The weight record of the current treatment cycle is compared with the weight record of the previous treatment cycle. When the weight record of the current treatment cycle is higher than the weight record of the previous treatment cycle, a weight gain status is generated. The blood pressure record of the current treatment cycle is compared with the blood pressure record of the previous treatment cycle. When the blood pressure record of the current treatment cycle is higher than the blood pressure record of the previous treatment cycle, an elevated blood pressure state is generated. The ultrafiltration volume record of the current treatment cycle is compared with the ultrafiltration volume record of the previous treatment cycle. When the ultrafiltration volume record of the current treatment cycle is lower than the ultrafiltration volume record of the previous treatment cycle, a state of reduced ultrafiltration volume is generated. When a patient with the same identity and within the same continuous treatment cycle simultaneously exhibits a state of weight gain, a state of blood pressure increase, and a state of decreased ultrafiltration volume, it is determined that the preset association conditions are met, and the corresponding treatment cycle is written into the abnormal treatment cycle field of the capacity management abnormal evidence package. The preset association conditions are formed by the system based on the combination of an increasing trend in weight, an increasing trend in blood pressure, and a decreasing trend in ultrafiltration volume, and are bound and saved with the same patient identifier, the same continuous treatment cycle, and the volume management abnormal evidence package construction module.

[0019] In a preferred embodiment of the present invention, the collaborative task dependency graph generation module includes: The task input field generation unit is used to generate prescription execution input fields, diet intake input fields, medication review input fields, and volume anomaly input fields based on the peritoneal dialysis prescription execution fragment, diet intake fragment, medication fragment, weight change trend, blood pressure change trend, and ultrafiltration volume change trend in the volume management anomaly evidence package, respectively. The task node record construction unit is used to configure the prescription execution input field as the input data item for the nurse operation verification task, the dietary intake input field as the input data item for the nutrition intake confirmation task, the medication review input field as the input data item for the drug risk review task, and the volume anomaly input field as the input data item for the doctor prescription adjustment task, based on the prescription execution input field, dietary intake input field, medication review input field, and volume anomaly input field. It constructs task node records for the doctor prescription adjustment task, nurse operation verification task, nutrition intake confirmation task, and drug risk review task, respectively. The task node record includes a node identifier, role identifier, input data item, output data item, locking condition, and unlocking condition. The task node relationship generation unit is used to generate parallel verification relationships, pre-issuance confirmation relationships, and prescription gating relationships based on the data source relationships between task node records. Among them, parallel verification relationships are formed between nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks; pre-issuance confirmation relationships are formed between nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks and the adjusted prescriptions generated by doctor prescription adjustment tasks; and prescription gating relationships are formed between doctor prescription adjustment tasks and prescription issuance gating modules. The task locking rule generation unit is used to configure the output data items of nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks as the unlocking conditions for the adjusted prescriptions generated by the doctor's prescription adjustment tasks to enter the prescription issuance gating module, based on the pre-issuance confirmation relationship and prescription gating relationship. It also configures output data item missing, output data item conflict, and task incompleteness as locking conditions to generate a task locking rule set. The collaborative task dependency graph generation unit is used to write task node records, parallel verification relationships, pre-issuance confirmation relationships, prescription gating relationships, and task locking rule sets into the same graph structure to generate a collaborative task dependency graph.

[0020] In this embodiment of the invention, the collaborative task dependency graph generation module converts the peritoneal dialysis prescription execution fragment, dietary intake fragment, medication fragment, weight change trend, blood pressure change trend, and ultrafiltration volume change trend in the volume management anomaly evidence package into prescription execution input fields, dietary intake input fields, medication review input fields, and volume anomaly input fields, respectively, so that data from different sources first form configurable task inputs. Each input field is further written into the task node records of nurse operation verification tasks, nutrition intake confirmation tasks, drug risk review tasks, and doctor prescription adjustment tasks, so that each role task has a clear data source, input data items, and output data items. After the parallel verification relationship, pre-departure confirmation relationship, and prescription gating relationship are written into the same graph structure, the output data items of nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks become the conditions for adjusting prescriptions to enter the prescription delivery gating module, preventing prescription adjustments from entering the delivery process separately from operation, dietary, and medication verification results.

[0021] In a preferred embodiment of the present invention, the task input field generation unit includes: Read the peritoneal dialysis prescription execution fragments, dietary intake fragments, medication fragments, weight change trends, blood pressure change trends, and ultrafiltration volume change trends that are bound to the same patient identifier in the abnormality evidence package of volume management; Write the prescription execution time, fluid exchange completion status, dialysate usage record, and equipment execution record from the peritoneal dialysis prescription execution segment into the prescription execution input field; Write the water intake, salt intake, intake time, and nutritionist confirmation status from the dietary intake segment into the dietary intake input field. Write the volume-related medication name, medication time, medication status, and pharmacist review status from the medication segment into the medication review input field; Write the trends of weight change, blood pressure change, and ultrafiltration rate change into the capacity anomaly input field; The prescription execution input field, diet intake input field, medication review input field, and volume anomaly input field are bound and saved to the same volume management anomaly evidence package.

[0022] In a preferred embodiment of the present invention, the task node record construction unit includes: Node identifiers are generated for tasks such as doctor's prescription adjustment, nurse's operation verification, nutritional intake confirmation, and drug risk review. The roles of doctor, nurse, nutritionist, and pharmacist are written into the role identifiers of the corresponding task node records. Write the prescription execution input field into the input data item of the nurse operation verification task, write the dietary intake input field into the input data item of the nutrition intake confirmation task, write the medication review input field into the input data item of the medication risk review task, and write the volume abnormality input field into the input data item of the doctor's prescription adjustment task. Set the output data item of the nurse operation verification task to the operation consistency result or operation inconsistency result; set the output data item of the nutrition intake confirmation task to the sodium and water intake confirmed result or sodium and water intake unconfirmed result; set the output data item of the drug risk review task to the volume-related medication confirmed result or volume-related medication unconfirmed result; set the output data item of the doctor prescription adjustment task to the prescription issuance request or prescription temporary storage request. Write the missing output data item, conflicting output data item, and incomplete task into the locking conditions of the corresponding task node record; write the output data items returned by the nurse operation verification task, nutrition intake confirmation task, and drug risk review task into the unlocking conditions of the corresponding task node record. Write the node identifier, role identifier, input data items, output data items, locking conditions, and unlocking conditions into the same task node record table to form task node records for doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks.

[0023] In a preferred embodiment of the present invention, the task node relationship generation unit includes: Read the task node records of doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks, and identify the input data items and output data items in each task node record; Write nurse operation verification tasks, nutrition intake confirmation tasks, and medication risk review tasks into the same parallel verification relationship record, so that the verification tasks corresponding to the prescription execution input field, diet intake input field, and medication review input field can receive the processing results of the corresponding roles respectively. Write the output data items of the nurse operation verification task, nutrition intake confirmation task, and drug risk review task with the adjusted prescription generated by the doctor's prescription adjustment task into the same pre-issuance confirmation relationship record, so that the adjusted prescription is associated with the output data items of the nurse operation verification task, nutrition intake confirmation task, and drug risk review task before entering the prescription issuance gating module. Write the doctor's prescription adjustment task and the prescription issuance gating module into the same prescription gating relationship record, so that the adjusted prescription generated by the doctor's prescription adjustment task can be used as the processing object of the prescription issuance gating module. Write the parallel verification relationship, the pre-issuance confirmation relationship, and the prescription gating relationship into the task relationship table, and save the task relationship table in association with the task node record table.

[0024] In a preferred embodiment of the present invention, the task locking rule generation unit includes: Read the pre-issuance confirmation relationship record to obtain the association between the nurse operation verification task, nutrition intake confirmation task, and drug risk review task and the adjusted prescription generated by the doctor's prescription adjustment task; Write the consistent or inconsistent operation results returned by the nurse operation verification task, the confirmed or unconfirmed sodium and water intake results returned by the nutrition intake confirmation task, and the confirmed or unconfirmed volume-related medication results returned by the drug risk review task into the unlocking conditions for adjusting prescriptions to enter the prescription issuance gating module. Read the prescription gating relationship record and associate the adjusted prescription generated by the doctor's prescription adjustment task with the prescription issuance gating module, so that the prescription issuance gating module can read the unlocking conditions corresponding to the adjusted prescription; Write the situation where the nurse operation verification task, nutrition intake confirmation task, or drug risk review task fails to return output data items into the task incomplete locking condition; write the situation where the output data items should have been returned but were not written into the output data items into the output data item missing locking condition; write the situation where different output data items form operation conflict indicators, dietary evidence missing indicators, or medication evidence missing indicators into the output data item conflict locking condition. Write the unlocking conditions, task incomplete locking conditions, missing output data item locking conditions, and output data item conflict locking conditions into the same task locking rule table to generate a task locking rule set.

[0025] In a preferred embodiment of the present invention, the task node status determination module includes: The task output set generation unit is used to receive the output data items returned by the doctor's prescription adjustment task, the nurse's operation verification task, the nutrition intake confirmation task, and the drug risk review task, respectively, and generate the task output set according to the collaborative task dependency graph. The cause label writing unit is used to write the output data items of the nurse operation verification task into the operation cause label, the output data items of the nutrition intake confirmation task into the diet cause label, the output data items of the drug risk review task into the medication cause label, and the output data items of the doctor prescription adjustment task into the prescription request label, based on the task output set, to generate a cause label set. The task completion status generation unit is used to generate the completion status or incomplete status of the doctor's prescription adjustment task, nurse's operation verification task, nutrition intake confirmation task and drug risk review task according to the writing status of the output data items of each task in the task output set, forming a task completion status set. The gating identifier generation unit is used to generate an operation conflict identifier based on a set of cause labels. When the operation cause label shows an inconsistency between the peritoneal dialysis prescription execution record and the patient's actual operation, and the prescription request label includes a prescription issuance request, an operation conflict identifier is generated. When the diet cause label shows that sodium and water intake is not confirmed, and the prescription request label includes a prescription issuance request, a diet evidence deficiency identifier is generated. When the medication cause label shows that volume-related medication is not confirmed, and the prescription request label includes a prescription issuance request, a medication evidence deficiency identifier is generated. When the operation cause label shows that the peritoneal dialysis prescription execution record is consistent with the patient's actual operation, the diet cause label shows that sodium and water intake is confirmed, the medication cause label shows that volume-related medication is confirmed, and the prescription request label includes a prescription issuance request, a prescription release support identifier is generated. At least one of the operation conflict identifier, diet evidence deficiency identifier, and medication evidence deficiency identifier constitutes a conflict state. The task lock status table generation unit is used to generate a task lock status table by writing the task node identifier, conflict source node, lock reason, unlock required task, operation conflict identifier, dietary evidence missing identifier, medication evidence missing identifier, prescription release support identifier, lock status, incomplete status and prescription gating status into the same table entry based on the task completion status set, operation conflict identifier, dietary evidence missing identifier, medication evidence missing identifier and prescription release support identifier.

[0026] In this embodiment of the invention, the task node status determination module receives the output data items returned by each role in the collaborative task dependency graph, and writes the output data items of different roles into operation reason tags, diet reason tags, medication reason tags, and prescription request tags, respectively, so that the operation verification results, diet confirmation results, medication review results, and prescription request results are converted into a unified tag set. The task completion status set is used to provide the task incomplete status, and the gating identifier generation unit is used to provide operation conflict identifiers, diet evidence missing identifiers, medication evidence missing identifiers, and prescription release support identifiers, so that task incompleteness, operation inconsistency, unconfirmed sodium intake, and unconfirmed volume-related medication can be written into the task lock status table. The task lock status table writes the conflict source node, lock reason, unlocking required task, and prescription gating status into the same table entry, so that the prescription issuance gating module can read the clear blocking reason and release condition.

[0027] In a preferred embodiment of the present invention, the reason tag writing unit includes: Read the task node identifier, role identifier, output data items, and return time from the task output set; When the role identifier corresponds to the nurse role and the task node identifier corresponds to the nurse operation verification task, read the output data item of the nurse operation verification task and write the operation consistency result or operation inconsistency result into the operation reason label. When the role identifier corresponds to the nutritionist role and the task node identifier corresponds to the nutrition intake confirmation task, read the output data item of the nutrition intake confirmation task and write the sodium and water intake confirmed result or sodium and water intake unconfirmed result into the dietary reason label. When the role identifier corresponds to the pharmacist role and the task node identifier corresponds to the drug risk review task, read the output data item of the drug risk review task and write the confirmed result of volume-related medication or the unconfirmed result of volume-related medication into the medication reason label. When the role identifier corresponds to the doctor role and the task node identifier corresponds to the doctor's prescription adjustment task, read the output data item of the doctor's prescription adjustment task and write the prescription issuance request or prescription temporary storage request into the prescription request tag. By binding operation reason tags, dietary reason tags, medication reason tags, and prescription request tags to the same patient identifier, the same volume management abnormal evidence package, and the same collaborative task dependency graph, a set of reason tags is generated.

[0028] In a preferred embodiment of the present invention, the task completion status generation unit includes: Read the task node records of doctor prescription adjustment task, nurse operation verification task, nutrition intake confirmation task and drug risk review task in the collaborative task dependency graph, and read the task node identifier and output data item in the task output set. Match the task node identifiers in the collaborative task dependency graph with the task node identifiers in the task output set; When the task node identifier of the doctor's prescription adjustment task has a corresponding record in the task output set, and the corresponding record contains a prescription issuance request or a prescription temporary storage request, the doctor's prescription adjustment task is written to the completion status. When the task node identifier of the nurse's operation verification task has a corresponding record in the task output set, and the corresponding record contains either a consistent operation result or an inconsistent operation result, the nurse's operation verification task is written to the completion status. When the task node identifier of the nutrition intake confirmation task has a corresponding record in the task output set, and the corresponding record contains either a confirmed sodium intake result or an unconfirmed sodium intake result, the nutrition intake confirmation task will be written to the completion status. When the task node identifier of the drug risk review task has a corresponding record in the task output set, and the corresponding record contains either a confirmed result for volume-related medication or an unconfirmed result for volume-related medication, the drug risk review task will be written to the completion status. When the task node identifier of a doctor's prescription adjustment task, nurse's operation verification task, nutrition intake confirmation task, or drug risk review task does not have a corresponding record in the task output set, or the corresponding record does not contain the corresponding output data item for the task, the corresponding task will be written to the incomplete status. The task node identifiers, completion status, and output data item writing status of the doctor's prescription adjustment task, nurse operation verification task, nutrition intake confirmation task, and drug risk review task are bound to the same patient identifier to form a task completion status set.

[0029] In a preferred embodiment of the present invention, the prescription disbursement gating module includes: The prescription version binding unit is used to bind the adjusted prescription, the capacity management abnormal evidence package, the task lock status table and the prescription generation time generated by the doctor's prescription adjustment task. The capacity management abnormal evidence package and the task lock status table are used as the gating benchmark data for the adjusted prescription to generate prescription gating records. The gating status set reading unit is used to read the operation conflict flag, dietary evidence missing flag, medication evidence missing flag, locked status, incomplete status and prescription release support flag from the task lock status table according to the prescription gating record, and generate a gating status set; The prescription writing interception unit is used to write the adjusted prescription into the doctor's pending prescription list, prevent the adjusted prescription from being written into the patient's execution queue, and generate a prescription interception result when there are operation conflict indicators, missing dietary evidence indicators, missing medication evidence indicators, locked status, or incomplete status in the gating status set. The prescription release result generation unit is used to mark the adjusted prescription as a prescription that can be issued when there are no operation conflict flags, dietary evidence missing flags, medication evidence missing flags, locked status and incomplete status in the gating status set, and there is a prescription release support flag, based on the gating status set. The prescription that can be issued is written into the patient-side execution queue and a prescription release result is generated. The prescription issuance status update unit is used to update the prescription issuance status adjustment in the prescription gating record based on the prescription interception result or prescription release result; and after the operation conflict flag, dietary evidence missing flag, medication evidence missing flag, locked status or incomplete status in the task lock status table are released, the task lock status table is reread and the prescription issuance status adjustment in the prescription gating record is updated.

[0030] In this embodiment of the invention, the prescription issuance gating module binds the adjusted prescription generated by the doctor's prescription adjustment task, the capacity management anomaly evidence package, the task lock status table, and the prescription generation time into a prescription gating record, thus maintaining the association between the adjusted prescription and its corresponding capacity anomaly evidence and task lock status. The gating status set reading unit reads the operation conflict identifier, dietary evidence missing identifier, medication evidence missing identifier, lock status, incomplete status, and prescription release support identifier from the task lock status table, ensuring that prescription issuance judgment is based on the current task lock status. When any blocking status exists, the adjusted prescription is written to the doctor's pending prescription list and prevented from being written to the patient's execution queue; when no blocking status exists and a prescription release support identifier exists, the adjusted prescription is marked as an issueable prescription and written to the patient's execution queue. After the task lock status changes, the task lock status table is reread and the prescription gating record is updated, ensuring that the issuance status of the adjusted prescription is updated synchronously with changes in operation, dietary, and medication verification results.

[0031] In a preferred embodiment of the present invention, the prescription release result generation unit includes: Read the prescription adjustment, patient identification, and prescription generation time from the prescription gating record, and read the operation conflict indicator, missing dietary evidence indicator, missing medication evidence indicator, locked status, incomplete status, and prescription release support indicator from the gating status set; If no operation conflict flag, missing dietary evidence flag, missing medication evidence flag, locked status, or incomplete status is read in the gating status set, and a prescription release support flag is read, the prescription status field of the adjusted prescription will be written as a prescription that can be issued. The adjusted prescriptions that are written as available prescriptions are bound to the patient identifier, prescription generation time, and prescription gating record to generate a patient-side execution queue write record; Write the record to the patient-side execution queue so that the patient-side execution queue stores prescriptions that can be issued; The prescription adjustment, patient identification, prescription generation time, prescription release support identification, and patient-side execution queue write record are written into the same prescription release result record to generate a prescription release result.

[0032] In a preferred embodiment of the present invention, the capacity anomaly evidence package construction module includes: The abnormal treatment cycle identification unit is used to identify treatment cycles in which weight gain, blood pressure increase and ultrafiltration volume decrease simultaneously, based on the peritoneal dialysis treatment event chain, as abnormal treatment cycles. The evidence time window generation unit is used to generate a pre-evidence time window and a post-evidence time window based on the start time and end time of the abnormal treatment cycle. The pre-evidence time window corresponds to the continuous treatment cycle before the abnormal treatment cycle, and the post-evidence time window corresponds to the continuous treatment cycle after the abnormal treatment cycle. The cause-side evidence field generation unit is used to extract peritoneal dialysis prescription execution fragments, dietary intake fragments, and medication fragments from the peritoneal dialysis treatment event chain based on the prior evidence time window, and write them into the operation evidence field, dietary evidence field, and medication evidence field, respectively. The results-side evidence field generation unit is used to extract the trends of weight change, blood pressure change, and ultrafiltration volume change from the peritoneal dialysis treatment event chain based on the post-evidence time window, and write them into the volume abnormality results field. The role-task input mapping unit is used to generate role-task mapping relationships based on the operation evidence field, diet evidence field, medication evidence field, and volume anomaly result field. The operation evidence field is mapped to the input data item for the nurse operation verification task, the diet evidence field is mapped to the input data item for the nutrition intake confirmation task, the medication evidence field is mapped to the input data item for the drug risk review task, and the volume anomaly result field is mapped to the input data item for the doctor prescription adjustment task. The abnormal evidence package for volume management is a unit used to bind abnormal treatment cycles, pre-existing evidence time windows, post-existing evidence time windows, operational evidence fields, dietary evidence fields, medication evidence fields, volume abnormality result fields, and role task mapping relationships to the same patient identifier, thereby generating an abnormal evidence package for volume management.

[0033] In this embodiment of the invention, the volume anomaly evidence package construction module first identifies abnormal treatment cycles in the peritoneal dialysis treatment event chain where weight gain, blood pressure increase, and ultrafiltration volume decrease occur simultaneously. Then, based on the abnormal treatment cycles, it generates pre-evidence time windows and post-evidence time windows, allowing for the extraction of data on the cause and result of the abnormality according to the treatment cycle. The peritoneal dialysis prescription execution segment, dietary intake segment, and medication segment within the pre-evidence time window are written into the operation evidence field, dietary evidence field, and medication evidence field, respectively. The weight change trend, blood pressure change trend, and ultrafiltration volume change trend within the post-evidence time window are written into the volume anomaly result field, ensuring that the volume anomaly evidence package simultaneously includes both cause-side and result-side evidence. The role-task input mapping relationship maps the operation evidence field, dietary evidence field, medication evidence field, and volume anomaly result field to nurse operation verification tasks, nutrition intake confirmation tasks, drug risk review tasks, and doctor prescription adjustment tasks, respectively, enabling the subsequent collaborative task dependency graph to generate corresponding role tasks according to the evidence fields.

[0034] In a preferred embodiment of the present invention, the abnormal treatment cycle identification unit includes: Read the peritoneal dialysis treatment event chain under the same patient identifier, and extract multiple treatment cycles arranged in order of start boundary from the peritoneal dialysis treatment event chain; Read the weight, blood pressure and ultrafiltration volume records for each treatment cycle, and read the weight, blood pressure and ultrafiltration volume records for adjacent treatment cycles; The weight record of the current treatment cycle is compared with the weight record of the previous treatment cycle. If the weight record of the current treatment cycle is higher than the weight record of the previous treatment cycle, the current treatment cycle is recorded as a weight gain state. The blood pressure record of the current treatment cycle is compared with the blood pressure record of the previous treatment cycle. If the blood pressure record of the current treatment cycle is higher than that of the previous treatment cycle, the current treatment cycle is recorded as having elevated blood pressure. The ultrafiltration volume record of the current treatment cycle is compared with the ultrafiltration volume record of the previous treatment cycle. If the ultrafiltration volume record of the current treatment cycle is lower than that of the previous treatment cycle, the current treatment cycle is written to the ultrafiltration volume reduction state. If a patient experiences weight gain, blood pressure increase, and ultrafiltration decrease simultaneously within the same treatment cycle, that treatment cycle is defined as an abnormal treatment cycle. Record the abnormal treatment cycle, patient identification, weight gain status, blood pressure increase status, and ultrafiltration decrease status in the same abnormal treatment cycle record.

[0035] In a preferred embodiment of the present invention, the evidence time window generation unit includes: Read the abnormal treatment cycle records and extract the start time, end time and patient identifier corresponding to the abnormal treatment cycle from the abnormal treatment cycle records; Read the peritoneal dialysis treatment event chain based on the patient identifier, and read the start and end boundaries of each treatment cycle in the peritoneal dialysis treatment event chain; Treatment cycles whose end boundary is earlier than the start time of the abnormal treatment cycle and which are adjacent to and consecutive to the abnormal treatment cycle are written into the prior evidence time window. Treatment cycles whose start boundary is later than the end time of the abnormal treatment cycle and which are adjacent to and consecutive to the abnormal treatment cycle are written into the post-evidence time window. Arrange the treatment cycles in the pre-evidence time window according to the order of their start boundaries and write them into the pre-evidence time window record; Arrange the treatment cycles in the post-evidence time window according to the order of their start boundaries and write them into the post-evidence time window record; Abnormal treatment cycles, records of prior evidence time windows, and records of subsequent evidence time windows are linked to the same patient identifier.

[0036] In a preferred embodiment of the present invention, the cause-side evidence field generation unit includes: Read the start and end times of treatment from the pre-existing evidence time window, and read the peritoneal dialysis treatment event chain bound to the same patient identifier; Based on the start and end times of the pre-existing evidence time window, treatment cycles within the pre-existing evidence time window are selected from the peritoneal dialysis treatment event chain. Read the peritoneal dialysis prescription execution fragment from the selected treatment cycles and write the peritoneal dialysis prescription execution fragment into the operation evidence field; Read dietary intake segments from the selected treatment cycles and write the dietary intake segments into the dietary evidence field; Read medication fragments from the selected treatment cycles and write them into the medication evidence field; The operation evidence field, diet evidence field, and medication evidence field are bound and saved to the same patient identifier, the same abnormal treatment cycle, and the same prior evidence time window.

[0037] In a preferred embodiment of the present invention, the result-side evidence field generation unit includes: Read the start and end times of treatment from the post-evidence time window, and read the peritoneal dialysis treatment event chain bound to the same patient identifier; Based on the start and end times of treatment within the post-evidence time window, treatment cycles within the post-evidence time window are selected from the peritoneal dialysis treatment event chain. Read the weight, blood pressure and ultrafiltration records from the selected treatment cycles and arrange them in chronological order according to the treatment cycle. The weight change trend is generated based on the weight records in adjacent treatment cycles, the blood pressure change trend is generated based on the blood pressure records in adjacent treatment cycles, and the ultrafiltration volume change trend is generated based on the ultrafiltration volume records in adjacent treatment cycles. Write the trends in weight change, blood pressure change, and ultrafiltration rate change into the volume anomaly results field. The abnormal volume result field is bound and saved with the same patient identifier, the same abnormal treatment cycle, and the same subsequent evidence time window.

[0038] In a preferred embodiment of the present invention, the treatment event chain construction module includes: The treatment cycle boundary generation unit is used to generate the start and end boundaries of each treatment cycle based on the start and end times of fluid exchange and the dialysate inflow and outflow records in the peritoneal dialysis prescription execution record. The treatment cycle data merging unit is used to merge data such as weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution records, dietary records, and medication records into the same treatment cycle when the start and end times of fluid exchange are on two separate calendar days. When the start and end times of fluid exchange are on the same calendar day, the unit merges the data such as weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution records, dietary records, and medication records into the same treatment cycle, generating merged treatment cycle data. The cycle data integrity identifier generation unit is used to check whether there are any missing data such as weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution records, diet records, or medication records within the same treatment cycle based on the merged data of the treatment cycle, and to generate a cycle data missing identifier when missing data is found. The patient cycle data binding unit is used to bind weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record, medication record and cycle data missing identifier within the same treatment cycle to the same patient identifier, thereby generating patient cycle binding data; The treatment event chain unit is used to bind data according to the patient cycle and arrange them sequentially according to the start boundary of the treatment cycle to generate a peritoneal dialysis treatment event chain.

[0039] In this embodiment of the invention, the treatment event chain construction module generates the start and end boundaries of each treatment cycle based on the start and end times of fluid exchange and the dialysate inflow / outflow records in the peritoneal dialysis prescription execution record, ensuring that the treatment cycle is not divided solely based on calendar days. The treatment cycle data merging unit merges the weight, blood pressure, ultrafiltration volume, dialysate inflow / outflow, peritoneal dialysis prescription execution record, diet record, and medication record of the two calendar days into the same treatment cycle when the treatment spans two calendar days. When the treatment does not span two calendar days, it merges the data within the same calendar day into the same treatment cycle, enabling both nighttime and daytime peritoneal dialysis data to form merged treatment cycle data. After the cycle data missing identifier and the merged treatment cycle data are jointly bound to the same patient identifier, the peritoneal dialysis treatment event chain can retain the data integrity status of each treatment cycle, providing a consistent data foundation for the volume management abnormal evidence package construction module to extract continuous treatment cycle data.

[0040] In a preferred embodiment of the present invention, the treatment cycle boundary generation unit includes: Read the peritoneal dialysis prescription execution record under the same patient identifier, and extract the start time of fluid exchange, end time of fluid exchange, and dialysate inflow / outflow records from the peritoneal dialysis prescription execution record; Write the start time of fluid change to the start boundary of the corresponding treatment cycle, and write the end time of fluid change to the end boundary of the corresponding treatment cycle. The dialysate inflow and outflow records are linked to the start and end boundaries, so that the dialysate inflow and outflow records belong to the treatment cycle defined by the start and end times of the fluid change. When there are multiple peritoneal dialysis prescription execution records under the same patient identifier, the start time and end time of each peritoneal dialysis prescription execution record are read separately, and the start and end boundaries of multiple treatment cycles are generated according to the order of the start time of the start time of the start time. The patient identification, peritoneal dialysis prescription execution record, start boundary, end boundary, and dialysate inflow / outflow record should be written into the same treatment cycle boundary record.

[0041] In a preferred embodiment of the present invention, the treatment cycle data merging unit includes: Read the patient identifier, start boundary, end boundary, start fluid change time, and end fluid change time from the treatment cycle boundary record; When the start and end times of fluid exchange are on two separate calendar days, read the weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record, and medication record corresponding to the same patient identifier on the calendar day of the start and end of fluid exchange. The weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record read within two calendar days are merged into the same treatment cycle according to the start and end boundaries. When the start and end times of fluid exchange are on the same calendar day, read the weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record corresponding to the same patient identifier within that calendar day; The weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record read within the same natural day are grouped into the same treatment cycle according to the start and end boundaries. Patient identification, start boundary, end boundary, weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record, and medication record are entered into the same treatment cycle and merged into the data.

[0042] In a preferred embodiment of the present invention, the treatment event chain forming unit includes: Read the patient cycle binding data under the same patient identifier, and extract the start boundary, end boundary, weight, blood pressure, ultrafiltration volume, dialysate intake and output volume, peritoneal dialysis prescription execution record, diet record, medication record and cycle data missing identifier from the patient cycle binding data; Based on the start boundary of the treatment cycle, the patient cycle binding data under the same patient identifier is arranged in chronological order; The cycle binding data of each group of patients after arrangement is written into the corresponding treatment event node. The treatment event node includes patient identifier, start boundary, end boundary, weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record, medication record and cycle data missing identifier. Connect adjacent treatment event nodes according to the order of their start boundaries to form a sequence of consecutive treatment event nodes under the same patient identifier; Write the sequence of continuous treatment event nodes into the peritoneal dialysis treatment event chain, and bind and save the peritoneal dialysis treatment event chain with the same patient identifier.

[0043] In a preferred embodiment of the present invention, the gate identification generation unit includes: The tag combination generation subunit is used to generate an operation prescription tag combination by combining the operation reason tag with the prescription request tag, a diet prescription tag combination by combining the diet reason tag with the prescription request tag, and a medication prescription tag combination by combining the medication reason tag with the prescription request tag, based on the operation reason tag, diet reason tag, medication reason tag, and prescription request tag. The gating decision queue generation subunit is used to identify whether the prescription request tag contains a prescription issuance request based on the combination of operation prescription tag, diet prescription tag, and medication prescription tag; when the prescription request tag contains a prescription issuance request, the combination of operation prescription tag, diet prescription tag, and medication prescription tag is written into the gating decision queue; when the prescription request tag does not contain a prescription issuance request, the operation reason tag, diet reason tag, and medication reason tag are written into the non-gating record area. The gating restriction identifier generation subunit is used to generate an operation conflict identifier when the operation prescription label combination shows that the peritoneal dialysis prescription execution record is inconsistent with the patient's actual operation, a diet prescription label combination shows that sodium and water intake is not confirmed, and a medication prescription label combination shows that volume-related medication is not confirmed. Note that labels in non-gated record areas do not generate operation conflict identifiers, diet evidence missing identifiers, or medication evidence missing identifiers. The identifier source relationship generation subunit is used to generate gating restriction identifier source relationships based on operation conflict identifiers, missing dietary evidence identifiers, and missing medication evidence identifiers. Among them, the operation conflict identifier is bound to the task node identifier of the nurse operation verification task, the missing dietary evidence identifier is bound to the task node identifier of the nutrition intake confirmation task, and the missing medication evidence identifier is bound to the task node identifier of the drug risk review task. The release support identifier generation subunit is used to generate a prescription release support identifier based on the gating judgment queue when the operation prescription label combination shows that the peritoneal dialysis prescription execution record is consistent with the patient's actual operation, the diet prescription label combination shows that sodium and water intake has been confirmed, the medication prescription label combination shows that volume-related medication has been confirmed, and the prescription request label contains a prescription issuance request. The gating identifier result output subunit is used to output the operation conflict identifier, the missing dietary evidence identifier, the missing medication evidence identifier, and the prescription release support identifier to the task lock status table generation unit based on the gating restriction identifier source relationship and the prescription release support identifier.

[0044] In this embodiment of the invention, the gating identifier generation unit combines the operation reason label, diet reason label, and medication reason label with the prescription request label to form operation prescription label combination, diet prescription label combination, and medication prescription label combination, respectively. This ensures that operation, diet, and medication results only enter the gating judgment queue when the prescription request label contains a prescription issuance request. When the prescription request label does not contain a prescription issuance request, the operation reason label, diet reason label, and medication reason label are written to the non-gating record area, and no operation conflict identifier, diet evidence missing identifier, or medication evidence missing identifier is generated, thus distinguishing ordinary records from prescription issuance restrictions. The label combinations in the gating judgment queue are used to generate operation conflict identifiers, diet evidence missing identifiers, medication evidence missing identifiers, or prescription release support identifiers. After binding the restriction identifiers with the corresponding role task nodes, they are output to the task lock status table generation unit, enabling the reason for prescription issuance blocking to be traced back to the nurse operation verification task, nutrition intake confirmation task, or drug risk review task.

[0045] In a preferred embodiment of the present invention, the task lock status table generation unit includes: The lock reason set generation sub-unit is used to generate a lock reason set by writing the operation conflict identifier into the operation conflict lock reason, the missing diet evidence identifier into the diet evidence missing lock reason, the missing medication evidence identifier into the medication evidence missing lock reason, and the incomplete status into the task incomplete lock reason, based on the operation conflict identifier, the missing diet evidence identifier, the missing medication evidence identifier, and the incomplete status. The unlock task relationship generation subunit is used to generate the unlock task relationship between the lock reason and the unlock task required for unlocking based on the lock reason set. Among them, the operation conflict lock reason corresponds to the nurse operation verification task and returns the operation consistency result; the lack of dietary evidence lock reason corresponds to the nutrition intake confirmation task and returns the sodium water intake confirmed result; the lack of medication evidence lock reason corresponds to the drug risk review task and returns the volume-related medication confirmed result; and the task incomplete lock reason corresponds to the task returning the output data item. The lock-holding state generation subunit is used to write the current lock state of the corresponding task node as a valid lock state and write the current prescription gating state as a prohibited issuance state when the unlocking task has not returned the corresponding confirmation result, based on the unlocking task relationship. The unlock update status generation subunit is used to update the current lock status bound to the corresponding lock reason to the unlock status when the unlock required task returns the corresponding confirmation result, based on the unlock task relationship, and generate the current prescription gating status based on the unlock status of the remaining lock reasons in the lock reason set. The task lock status table entry generation sub-unit is used to write the task node identifier, conflict source node, lock reason, unlock required task, operation conflict identifier, missing dietary evidence identifier, missing medication evidence identifier, lock status, incomplete status, prescription release support identifier, and prescription gating status into the same task lock status table entry based on the lock reason set, unlock task relationship, current lock status, current prescription gating status, and prescription release support identifier.

[0046] In this embodiment of the invention, the task lock status table generation unit writes the operation conflict identifier, the dietary evidence missing identifier, the medication evidence missing identifier, and the incomplete status into the corresponding lock reason set, and configures a corresponding unlocking task for each lock reason, so that operation conflict, dietary evidence missing, medication evidence missing, and task incompleteness all have a definite release source. After the nurse operation verification task returns an operation consistency result, the nutrition intake confirmation task returns a sodium water intake confirmed result, the drug risk review task returns a volume-related medication confirmed result, or the corresponding task returns an output data item, the corresponding lock status is updated to the unlocked status. The current lock status and the current prescription gating status are written into the same task lock status table entry, so that the prescription issuance gating module can read the prohibited issuance status or the unlocked gating status according to the unlocking status of the lock reason.

[0047] In a preferred embodiment of the present invention, the locking reason set generation subunit includes: The task lock status table generation unit reads the operation conflict flag, the missing dietary evidence flag, the missing medication evidence flag, and the incomplete status received by the task lock status table generation unit. When an operation conflict identifier is read, the operation conflict identifier, the corresponding task node identifier, and the conflict source node are written into the operation conflict locking reason; When a missing food evidence flag is read, the missing food evidence flag, the corresponding task node flag, and the conflict source node are written into the reason for locking the missing food evidence. When a missing medication evidence flag is read, the missing medication evidence flag, the corresponding task node flag, and the conflict source node are written into the reason for locking the missing medication evidence. When an incomplete status is read, the incomplete status, the corresponding task node identifier, and the task node that has not returned output data items are written into the task incomplete lock reason; The reasons for locking the operation conflict, lack of dietary evidence, lack of medication evidence, and incomplete task are bound to the same patient identifier and the same task lock status table to generate a set of lock reasons.

[0048] In a preferred embodiment of the present invention, the unlocking task relationship generation subunit includes: Read the lock reason set for operation conflict lock reason, missing dietary evidence lock reason, missing medication evidence lock reason, and task incomplete lock reason; When there is an operation conflict lock reason in the lock reason set, bind the operation conflict lock reason to the nurse operation verification task, and write the operation consistency result returned by the nurse operation verification task into the corresponding unlocking task; When there is a reason for locking due to lack of dietary evidence in the set of reasons for locking, the reason for locking due to lack of dietary evidence is bound to the nutrition intake confirmation task, and the result of sodium and water intake being confirmed is returned by the nutrition intake confirmation task and written into the corresponding unlocking task. When there is a reason for missing medication evidence in the set of reasons for locking, the reason for missing medication evidence is bound to the drug risk review task, and the drug risk review task returns the confirmed medication results related to the capacity and writes them into the corresponding unlocking task. If there is a lock reason for task incomplete in the lock reason set, read the task node identifier corresponding to the lock reason for task incomplete, and write the task return output data item corresponding to the task node identifier to the corresponding unlocking task. Write the reason for locking, the task required for unlocking, the corresponding task node identifier, and the patient identifier into the same unlocking task relationship record to generate an unlocking task relationship.

[0049] In a preferred embodiment of the present invention, the locking and holding state generation subunit includes: Read the locking reason, unlocking required task, corresponding task node identifier, and patient identifier from the unlocking task relationship; Read the task output data items of the task required to unlock, and determine whether the task required to unlock has returned the corresponding confirmation result; When the nurse operation verification task corresponding to the operation conflict lock reason does not return an operation consistency result, the current lock status of the task node corresponding to the operation conflict lock reason is written as a valid lock status. When the nutritional intake confirmation task corresponding to the reason for missing dietary evidence does not return a result confirming sodium and water intake, the current locking status of the task node corresponding to the reason for missing dietary evidence is written as a valid locking status. When the drug risk review task corresponding to the reason for missing medication evidence does not return the confirmed medication result related to the volume, the current locking status of the task node corresponding to the reason for missing medication evidence is written as a valid locking status. When the task corresponding to the reason for the task not being completed does not return any output data items, the current lock status of the task node corresponding to the reason for the task not being completed is written as a valid lock status. When the current locking state of any task node is a valid locking state, the current prescription gating state is written to the prohibited issuance state; The effective lock status, the prohibited distribution status, the reason for the lock, the corresponding task node identifier, and the patient identifier are bound and saved.

[0050] In a preferred embodiment of the present invention, the unlock update state generation subunit includes: Read the locking reason, unlocking required task, corresponding task node identifier, and patient identifier from the unlocking task relationship; Read the task output data items of the task required to unlock, and determine whether the task required to unlock has returned the corresponding confirmation result; When the nurse's operation verification task corresponding to the operation conflict lock reason returns the operation consistent result, the current lock status bound to the operation conflict lock reason will be updated to the unlocked status. When the nutrition intake confirmation task corresponding to the reason for the lack of dietary evidence returns the result that sodium and water intake has been confirmed, the current lock status bound to the reason for the lack of dietary evidence will be updated to the unlocked status. When the drug risk review task corresponding to the reason for the missing medication evidence lock returns the result that the medication related to the capacity has been confirmed, the current lock status bound to the reason for the missing medication evidence lock will be updated to the unlocked status. When the task corresponding to the reason for the task not being completed returns the output data item, the current lock status bound to the reason for the task not being completed will be updated to the unlocked status; Read the current locking status corresponding to each locking reason in the locking reason set; If there are still locking reasons in the set of locking reasons that are currently in a valid locking state, write the current prescription gating state to a prohibited issuance state. If there is no locking reason in the set of locking reasons that is currently in a valid locking state, the current prescription gating state is written as an allowed issuance state; The unlock status, current prescription gating status, reason for locking, corresponding task node identifier, and patient identifier are bound and saved.

[0051] In a preferred embodiment of the present invention, the task lock status table entry generation subunit includes: Read the lock reason set for operation conflict lock reason, missing dietary evidence lock reason, missing medication evidence lock reason, and task incomplete lock reason; Read the locking reason, unlocking required task, corresponding task node identifier, and patient identifier from the unlocking task relationship; Read the current lock status bound to the lock reason, and read the current prescription gating status; Read the prescription release support identifier; Write the corresponding task node identifier into the task node identifier field of the task lock status table entry; Write the source task node corresponding to the locking reason into the conflict source node field of the task lock status table; Write the reasons for locking due to operational conflicts, missing dietary evidence, missing medication evidence, or incomplete tasks into the Lock Reason field of the Task Lock Status table. Write the unlocking task corresponding to the lock reason into the unlocking task field of the task lock status table; Write the operation conflict flag, the missing dietary evidence flag, and the missing medication evidence flag into the corresponding flag field in the task lock status table. Write the current lock status to the lock status field of the task lock status table entry; Write the incomplete status corresponding to the reason for the task not being locked into the incomplete status field of the task lock status table; Write the prescription release support identifier into the prescription release support identifier field in the task lock status table entry; Write the current prescription gating status to the prescription gating status field in the task lock status table entry; Bind and save the patient identifier to the task lock status entry, and generate the task lock status entry.

[0052] In a preferred embodiment of the present invention, the prescription version binding unit includes: The prescription gating record generation subunit is used to generate prescription gating records based on the adjusted prescriptions generated by the doctor's prescription adjustment task, the capacity management abnormal evidence package, the task lock status table, and the prescription generation time. The capacity management abnormal evidence package and the task lock status table bound in the prescription gating record are determined as the gating baseline data. The current gating data reading subunit is used to read the gating baseline data in the prescription gating record before adjusting the prescription writing execution queue at the patient end, based on the prescription gating record, and to read the current capacity management abnormal evidence package and the current task lock status table bound to the same patient identifier, and generate the current gating data; The gating data consistency result generation subunit is used to verify the consistency between the capacity management anomaly evidence package in the gating baseline data and the current capacity management anomaly evidence package based on the gating baseline data and the current gating data, and to verify the consistency between the task lock status table in the gating baseline data and the current task lock status table, and generate gating data consistency result or gating data mismatch result. The gated data mismatch re-gating subunit is used to mark the adjusted prescription as a prescription to be confirmed, clear the prescription to be issued prescription mark of the adjusted prescription, and generate a re-gating state based on the gated data mismatch result. The re-gating state is used to update the prescription issuance status of the adjusted prescription to a prescription to be confirmed state. The gating data consistency maintenance subunit is used to maintain the adjusted prescription in the prescription issuance decision process of the prescription issuance gating module based on the gating data consistency result.

[0053] In this embodiment of the invention, the prescription version binding unit binds the adjusted prescription generated by the doctor's prescription adjustment task, the capacity management anomaly evidence package, the task lock status table, and the prescription generation time into a prescription gating record, and determines the capacity management anomaly evidence package and the task lock status table at the time of binding as the gating baseline data. Before the adjusted prescription is written into the patient's execution queue, the system reads the current capacity management anomaly evidence package and the current task lock status table under the same patient identifier and performs consistency verification with the gating baseline data. When the gating baseline data is inconsistent with the current gating data, the adjusted prescription is marked as a prescription pending confirmation, the prescription can be issued mark is cleared, and the prescription issuance status is updated to a pending confirmation status; when the gating baseline data is consistent with the current gating data, the adjusted prescription remains in the issuance judgment process, thereby preventing the adjusted prescription from entering the patient's execution queue based on the changed capacity management anomaly evidence package or task lock status table.

[0054] In a preferred embodiment of the present invention, the gated data consistency result generation subunit includes: Read the gate control baseline data from the prescription gate control record, and extract the capacity management anomaly evidence package and task lock status table from the gate control baseline data; Read the current gating data and extract the current capacity management anomaly evidence package and the current task lock status table from the current gating data; The capacity management anomaly evidence package in the gating baseline data is compared with the current capacity management anomaly evidence package. The field comparison includes the comparison of abnormal treatment cycles, weight change trends, blood pressure change trends, ultrafiltration volume change trends, peritoneal dialysis prescription execution segments, dietary intake segments, and medication segments. The task lock status table in the gating baseline data is compared with the current task lock status table. The field comparison includes the comparison of task node identifier, conflict source node, lock reason, unlock required task, operation conflict identifier, missing dietary evidence identifier, missing medication evidence identifier, prescription release support identifier, lock status, incomplete status and prescription gating status. When the field comparison results of the capacity management anomaly evidence package in the gating baseline data are consistent with those of the current capacity management anomaly evidence package, and the field comparison results of the task lock status table in the gating baseline data are consistent with those of the current task lock status table, a gating data consistency result is generated. When the field comparison results of the capacity management anomaly evidence package in the gating baseline data are inconsistent with those of the current capacity management anomaly evidence package, or when the field comparison results of the task lock status table in the gating baseline data are inconsistent with those of the current task lock status table, a gating data mismatch result is generated.

[0055] In a preferred embodiment of the present invention, the gated data mismatch gated subunit includes: Read the gating data mismatch results, and read the adjustment prescriptions, prescription gating records, and patient identifiers corresponding to the gating data mismatch results; Write the prescription status field of the adjusted prescription as a prescription pending confirmation; When a prescription adjustment contains a prescription-issuing flag, delete the prescription-issuing flag from the prescription adjustment. Write the prescription issuance status of the adjusted prescription to "pending confirmation" and write the "pending confirmation" status to the prescription gating record; Bind the gated data mismatch result, the prescription to be confirmed, the status to be confirmed, and the prescription gated record to the same patient identifier to generate a re-gated status; The prescription adjustment, re-gating status, prescription gating record, and gating data mismatch results are written to the doctor's pending prescription list, and the prescription adjustment is prevented from being written to the patient's execution queue.

[0056] In a preferred embodiment of the present invention, the gating data consistency maintenance subunit includes: Read the gating data consistency result, and read the adjustment prescription, prescription gating record and patient identifier corresponding to the gating data consistency result; Write the consistent results of the gating data into the prescription gating record to maintain the correspondence between the prescription gating record and the current capacity management abnormal evidence package and the current task lock status table; Keep the current prescription status field and the current prescription issuance status unchanged when adjusting the prescription; The results of adjusting prescriptions, prescription gating records, and gating data consistency are sent to the gating status set reading unit of the prescription issuance gating module; The gating status set reading unit continues to read the operation conflict flag, dietary evidence missing flag, medication evidence missing flag, locked status, incomplete status and prescription release support flag from the task lock status table.

[0057] In a preferred embodiment of the present invention, the prescription writing interception unit includes: The queue write condition set generation sub-unit is used to identify whether the adjusted prescription has a prescription that can be issued based on the prescription gating record, task lock status table and prescription issuance status, and generate the queue write condition set. The execution queue whitelist generation subunit is used to write the adjusted prescription into the patient-side execution queue whitelist based on the queue writing condition set. When the adjusted prescription has a prescription-issuable flag and there are no operation conflict flags, dietary evidence missing flags, medication evidence missing flags, locked status, or incomplete status in the task lock status table, the adjusted prescription is written into the patient-side execution queue whitelist. The patient-side execution queue whitelist is used as an allowable condition for the adjusted prescription to be written into the patient-side execution queue. The patient-side execution queue whitelist is used for the prescription release result generation unit to call and does not directly trigger the adjustment prescription to be written into the patient-side execution queue. The pending prescription interception result generation subunit is used to generate a pending prescription interception result and prevent the adjustment prescription from being written to the patient's execution queue based on the queue writing condition set when the adjusted prescription has a pending prescription mark, or when there is an operation conflict mark, a missing dietary evidence mark, a missing medication evidence mark, a locked status, or an incomplete status in the task lock status table. The patient-side task execution blocking subunit is used to prevent the generation of patient-side execution tasks based on the prescription to be confirmed when the prescription adjustment is not written into the patient-side execution queue whitelist, based on the prescription confirmation interception result. The original prescription protection result generation subunit is used to maintain the original peritoneal dialysis prescription in the patient's execution queue based on the prescription interception result to be confirmed, and to prohibit the adjustment of prescriptions that cover the original peritoneal dialysis prescription, thereby generating the original prescription protection result. The doctor-side pending confirmation record generation sub-unit is used to write the adjusted prescriptions that are blocked from being written into the patient-side execution queue, the corresponding prescription gating records, and the corresponding locking reasons into the doctor-side pending confirmation prescription list based on the pending confirmation prescription interception results and the original prescription protection results.

[0058] In this embodiment of the invention, the prescription writing interception unit generates a queue writing condition set based on the prescription gating record, task lock status table, and prescription issuance status of the adjusted prescription, and identifies whether the adjusted prescription has a prescription issuance mark. If the adjusted prescription has a prescription issuance mark and there are no operation conflict markers, dietary evidence missing markers, medication evidence missing markers, locked status, or incomplete status in the task lock status table, the adjusted prescription is written into the patient-side execution queue whitelist, which serves as an allowable condition before writing into the patient-side execution queue. If the adjusted prescription has a prescription pending confirmation mark, or if there is a blocking status in the task lock status table, the adjusted prescription is prevented from being written into the patient-side execution queue. The patient-side execution task is not generated, the original peritoneal dialysis prescription in the patient-side execution queue is maintained, and the doctor-side prescription pending confirmation list records the adjusted prescription, prescription gating record, and locking reason that were prevented from being written.

[0059] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A multi-role task collaboration system for peritoneal dialysis management of renal disease, characterized in that, The system includes: The treatment event chain construction module is used to sort the patient's weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record and medication record according to the treatment time, and bind the data within the same treatment cycle to the same patient identifier to generate a peritoneal dialysis treatment event chain; The volume abnormality evidence package construction module is used to extract the trends of weight change, blood pressure change, ultrafiltration volume change, peritoneal dialysis prescription execution, dietary intake, and medication administration within a continuous treatment cycle based on the peritoneal dialysis treatment event chain, and generate a volume management abnormality evidence package when the preset correlation conditions are met, such as weight increase, blood pressure increase, and ultrafiltration volume decrease. The collaborative task dependency graph generation module is used to generate doctor prescription adjustment tasks, nurse operation verification tasks, nutrition intake confirmation tasks and drug risk review tasks based on the capacity management abnormal evidence package, and to configure input data items, output data items, locking conditions and unlocking conditions for each task to generate a collaborative task dependency graph. The task node status determination module is used to determine whether the output data items of each task satisfy the input data items of subsequent tasks according to the collaborative task dependency graph, and to generate a task lock status table when the output data items are missing, the task is not completed, or there are conflicts between the output data items. The conflict between the output data items includes generating at least one of the following: operation conflict identifier, dietary evidence missing identifier, or medication evidence missing identifier. The prescription issuance gating module is used to determine whether the prescription is ready for issuance based on the task lock status table and the prescriptions generated by the doctor's prescription adjustment task. When there is a locked state, an incomplete state, or a conflict state, the prescription is marked as a prescription to be confirmed and is prohibited from being written to the patient's execution queue. When there is no locked state, incomplete state, or conflict state, the prescription is marked as a prescription that can be issued and is allowed to be written to the patient's execution queue. The conflict state includes at least one of the following: operation conflict identifier, dietary evidence missing identifier, and medication evidence missing identifier.

2. The multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 1, characterized in that, The collaborative task dependency graph generation module includes: The task input field generation unit is used to generate prescription execution input fields, diet intake input fields, medication review input fields, and volume anomaly input fields based on the peritoneal dialysis prescription execution fragment, diet intake fragment, medication fragment, weight change trend, blood pressure change trend, and ultrafiltration volume change trend in the volume management anomaly evidence package, respectively. The task node record construction unit is used to configure the prescription execution input field as the input data item for the nurse operation verification task, the dietary intake input field as the input data item for the nutrition intake confirmation task, the medication review input field as the input data item for the drug risk review task, and the volume anomaly input field as the input data item for the doctor prescription adjustment task, based on the prescription execution input field, dietary intake input field, medication review input field, and volume anomaly input field. It constructs task node records for the doctor prescription adjustment task, nurse operation verification task, nutrition intake confirmation task, and drug risk review task, respectively. The task node record includes a node identifier, role identifier, input data item, output data item, locking condition, and unlocking condition. The task node relationship generation unit is used to generate parallel verification relationships, pre-issuance confirmation relationships, and prescription gating relationships based on the data source relationships between task node records. Among them, parallel verification relationships are formed between nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks; pre-issuance confirmation relationships are formed between nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks and the adjusted prescriptions generated by doctor prescription adjustment tasks; and prescription gating relationships are formed between doctor prescription adjustment tasks and prescription issuance gating modules. The task locking rule generation unit is used to configure the output data items of nurse operation verification tasks, nutrition intake confirmation tasks, and drug risk review tasks as the unlocking conditions for the adjusted prescriptions generated by the doctor's prescription adjustment tasks to enter the prescription issuance gating module, based on the pre-issuance confirmation relationship and prescription gating relationship. It also configures output data item missing, output data item conflict, and task incompleteness as locking conditions to generate a task locking rule set. The collaborative task dependency graph generation unit is used to write task node records, parallel verification relationships, pre-issuance confirmation relationships, prescription gating relationships, and task locking rule sets into the same graph structure to generate a collaborative task dependency graph.

3. The multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 1, characterized in that, The task node status determination module includes: The task output set generation unit is used to receive the output data items returned by the doctor's prescription adjustment task, the nurse's operation verification task, the nutrition intake confirmation task, and the drug risk review task, respectively, and generate the task output set according to the collaborative task dependency graph. The cause label writing unit is used to write the output data items of the nurse operation verification task into the operation cause label, the output data items of the nutrition intake confirmation task into the diet cause label, the output data items of the drug risk review task into the medication cause label, and the output data items of the doctor prescription adjustment task into the prescription request label, based on the task output set, to generate a cause label set. The task completion status generation unit is used to generate the completion status or incomplete status of the doctor's prescription adjustment task, nurse's operation verification task, nutrition intake confirmation task and drug risk review task according to the writing status of the output data items of each task in the task output set, forming a task completion status set. The gating identifier generation unit is used to generate an operation conflict identifier based on a set of cause labels. When the operation cause label shows an inconsistency between the peritoneal dialysis prescription execution record and the patient's actual operation, and the prescription request label includes a prescription issuance request, an operation conflict identifier is generated. When the diet cause label shows that sodium and water intake is not confirmed, and the prescription request label includes a prescription issuance request, a diet evidence deficiency identifier is generated. When the medication cause label shows that volume-related medication is not confirmed, and the prescription request label includes a prescription issuance request, a medication evidence deficiency identifier is generated. When the operation cause label shows that the peritoneal dialysis prescription execution record is consistent with the patient's actual operation, the diet cause label shows that sodium and water intake is confirmed, the medication cause label shows that volume-related medication is confirmed, and the prescription request label includes a prescription issuance request, a prescription release support identifier is generated. At least one of the operation conflict identifier, diet evidence deficiency identifier, and medication evidence deficiency identifier constitutes a conflict state. The task lock status table generation unit is used to generate a task lock status table by writing the task node identifier, conflict source node, lock reason, unlock required task, operation conflict identifier, dietary evidence missing identifier, medication evidence missing identifier, prescription release support identifier, lock status, incomplete status and prescription gating status into the same table entry based on the task completion status set, operation conflict identifier, dietary evidence missing identifier, medication evidence missing identifier and prescription release support identifier.

4. The multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 3, characterized in that, The prescription issuance gating module includes: The prescription version binding unit is used to bind the adjusted prescription, the capacity management abnormal evidence package, the task lock status table and the prescription generation time generated by the doctor's prescription adjustment task. The capacity management abnormal evidence package and the task lock status table are used as the gating benchmark data for the adjusted prescription to generate prescription gating records. The gating status set reading unit is used to read the operation conflict flag, dietary evidence missing flag, medication evidence missing flag, locked status, incomplete status and prescription release support flag from the task lock status table according to the prescription gating record, and generate a gating status set; The prescription writing interception unit is used to write the adjusted prescription into the doctor's pending prescription list, prevent the adjusted prescription from being written into the patient's execution queue, and generate a prescription interception result when there are operation conflict indicators, missing dietary evidence indicators, missing medication evidence indicators, locked status, or incomplete status in the gating status set. The prescription release result generation unit is used to mark the adjusted prescription as a prescription that can be issued when there are no operation conflict flags, dietary evidence missing flags, medication evidence missing flags, locked status and incomplete status in the gating status set, and there is a prescription release support flag, based on the gating status set. The prescription that can be issued is written into the patient-side execution queue and a prescription release result is generated. The prescription issuance status update unit is used to update the prescription issuance status adjustment in the prescription gating record based on the prescription interception result or prescription release result; and after the operation conflict flag, dietary evidence missing flag, medication evidence missing flag, locked status or incomplete status in the task lock status table are released, the task lock status table is reread and the prescription issuance status adjustment in the prescription gating record is updated.

5. A multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 1, characterized in that, The capacity anomaly evidence package construction module includes: The abnormal treatment cycle identification unit is used to identify treatment cycles in which weight gain, blood pressure increase and ultrafiltration volume decrease simultaneously, based on the peritoneal dialysis treatment event chain, as abnormal treatment cycles. The evidence time window generation unit is used to generate a pre-evidence time window and a post-evidence time window based on the start time and end time of the abnormal treatment cycle. The pre-evidence time window corresponds to the continuous treatment cycle before the abnormal treatment cycle, and the post-evidence time window corresponds to the continuous treatment cycle after the abnormal treatment cycle. The cause-side evidence field generation unit is used to extract peritoneal dialysis prescription execution fragments, dietary intake fragments, and medication fragments from the peritoneal dialysis treatment event chain based on the prior evidence time window, and write them into the operation evidence field, dietary evidence field, and medication evidence field, respectively. The results-side evidence field generation unit is used to extract the trends of weight change, blood pressure change, and ultrafiltration volume change from the peritoneal dialysis treatment event chain based on the post-evidence time window, and write them into the volume abnormality results field. The role-task input mapping unit is used to generate role-task mapping relationships based on the operation evidence field, diet evidence field, medication evidence field, and volume anomaly result field. The operation evidence field is mapped to the input data item for the nurse operation verification task, the diet evidence field is mapped to the input data item for the nutrition intake confirmation task, the medication evidence field is mapped to the input data item for the drug risk review task, and the volume anomaly result field is mapped to the input data item for the doctor prescription adjustment task. The abnormal evidence package for volume management is a unit used to bind abnormal treatment cycles, pre-existing evidence time windows, post-existing evidence time windows, operational evidence fields, dietary evidence fields, medication evidence fields, volume abnormality result fields, and role task mapping relationships to the same patient identifier, thereby generating an abnormal evidence package for volume management.

6. A multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 1, characterized in that, The treatment event chain construction module includes: The treatment cycle boundary generation unit is used to generate the start and end boundaries of each treatment cycle based on the start and end times of fluid exchange and the dialysate inflow and outflow records in the peritoneal dialysis prescription execution record. The treatment cycle data merging unit is used to merge data such as weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution records, dietary records, and medication records into the same treatment cycle when the start and end times of fluid exchange are on two separate calendar days. When the start and end times of fluid exchange are on the same calendar day, the unit merges the data such as weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution records, dietary records, and medication records into the same treatment cycle, generating merged treatment cycle data. The cycle data integrity identifier generation unit is used to check whether there are any missing data such as weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution records, diet records, or medication records within the same treatment cycle based on the merged data of the treatment cycle, and to generate a cycle data missing identifier when missing data is found. The patient cycle data binding unit is used to bind weight, blood pressure, ultrafiltration volume, dialysate intake and output, peritoneal dialysis prescription execution record, diet record, medication record and cycle data missing identifier within the same treatment cycle to the same patient identifier, thereby generating patient cycle binding data; The treatment event chain unit is used to bind data according to the patient cycle and arrange them sequentially according to the start boundary of the treatment cycle to generate a peritoneal dialysis treatment event chain.

7. A multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 3, characterized in that, The gate identification generation unit includes: The tag combination generation subunit is used to generate an operation prescription tag combination by combining the operation reason tag with the prescription request tag, a diet prescription tag combination by combining the diet reason tag with the prescription request tag, and a medication prescription tag combination by combining the medication reason tag with the prescription request tag, based on the operation reason tag, diet reason tag, medication reason tag, and prescription request tag. The gating decision queue generation subunit is used to identify whether the prescription request tag contains a prescription issuance request based on the combination of operation prescription tag, diet prescription tag, and medication prescription tag; when the prescription request tag contains a prescription issuance request, the combination of operation prescription tag, diet prescription tag, and medication prescription tag is written into the gating decision queue; when the prescription request tag does not contain a prescription issuance request, the operation reason tag, diet reason tag, and medication reason tag are written into the non-gating record area. The gating restriction identifier generation subunit is used to generate an operation conflict identifier when the operation prescription label combination shows that the peritoneal dialysis prescription execution record is inconsistent with the patient's actual operation, a diet prescription label combination shows that sodium and water intake is not confirmed, and a medication prescription label combination shows that volume-related medication is not confirmed. Note that labels in non-gated record areas do not generate operation conflict identifiers, diet evidence missing identifiers, or medication evidence missing identifiers. The identifier source relationship generation subunit is used to generate gating restriction identifier source relationships based on operation conflict identifiers, missing dietary evidence identifiers, and missing medication evidence identifiers. Among them, the operation conflict identifier is bound to the task node identifier of the nurse operation verification task, the missing dietary evidence identifier is bound to the task node identifier of the nutrition intake confirmation task, and the missing medication evidence identifier is bound to the task node identifier of the drug risk review task. The release support identifier generation subunit is used to generate a prescription release support identifier based on the gating judgment queue when the operation prescription label combination shows that the peritoneal dialysis prescription execution record is consistent with the patient's actual operation, the diet prescription label combination shows that sodium and water intake has been confirmed, the medication prescription label combination shows that volume-related medication has been confirmed, and the prescription request label contains a prescription issuance request. The gating identifier result output subunit is used to output the operation conflict identifier, the missing dietary evidence identifier, the missing medication evidence identifier, and the prescription release support identifier to the task lock status table generation unit based on the gating restriction identifier source relationship and the prescription release support identifier.

8. A multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 3, characterized in that, The task lock status table generation unit includes: The lock reason set generation sub-unit is used to generate a lock reason set by writing the operation conflict identifier into the operation conflict lock reason, the missing diet evidence identifier into the diet evidence missing lock reason, the missing medication evidence identifier into the medication evidence missing lock reason, and the incomplete status into the task incomplete lock reason, based on the operation conflict identifier, the missing diet evidence identifier, the missing medication evidence identifier, and the incomplete status. The unlock task relationship generation subunit is used to generate the unlock task relationship between the lock reason and the unlock task required for unlocking based on the lock reason set. Among them, the operation conflict lock reason corresponds to the nurse operation verification task and returns the operation consistency result; the lack of dietary evidence lock reason corresponds to the nutrition intake confirmation task and returns the sodium water intake confirmed result; the lack of medication evidence lock reason corresponds to the drug risk review task and returns the volume-related medication confirmed result; and the task incomplete lock reason corresponds to the task returning the output data item. The lock-holding state generation subunit is used to write the current lock state of the corresponding task node as a valid lock state and write the current prescription gating state as a prohibited issuance state when the unlocking task has not returned the corresponding confirmation result, based on the unlocking task relationship. The unlock update status generation subunit is used to update the current lock status bound to the corresponding lock reason to the unlock status when the unlock required task returns the corresponding confirmation result, based on the unlock task relationship, and generate the current prescription gating status based on the unlock status of the remaining lock reasons in the lock reason set. The task lock status table entry generation sub-unit is used to write the task node identifier, conflict source node, lock reason, unlock required task, operation conflict identifier, missing dietary evidence identifier, missing medication evidence identifier, lock status, incomplete status, prescription release support identifier, and prescription gating status into the same task lock status table entry based on the lock reason set, unlock task relationship, current lock status, current prescription gating status, and prescription release support identifier.

9. A multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 4, characterized in that, The prescription version binding unit includes: The prescription gating record generation subunit is used to generate prescription gating records based on the adjusted prescriptions generated by the doctor's prescription adjustment task, the capacity management abnormal evidence package, the task lock status table, and the prescription generation time. The capacity management abnormal evidence package and the task lock status table bound in the prescription gating record are determined as the gating baseline data. The current gating data reading subunit is used to read the gating baseline data in the prescription gating record before adjusting the prescription writing execution queue at the patient end, based on the prescription gating record, and to read the current capacity management abnormal evidence package and the current task lock status table bound to the same patient identifier, and generate the current gating data; The gating data consistency result generation subunit is used to verify the consistency between the capacity management anomaly evidence package in the gating baseline data and the current capacity management anomaly evidence package based on the gating baseline data and the current gating data, and to verify the consistency between the task lock status table in the gating baseline data and the current task lock status table, and generate gating data consistency result or gating data mismatch result. The gated data mismatch re-gating subunit is used to mark the adjusted prescription as a prescription to be confirmed, clear the prescription to be issued prescription mark of the adjusted prescription, and generate a re-gating state based on the gated data mismatch result. The re-gating state is used to update the prescription issuance status of the adjusted prescription to a prescription to be confirmed state. The gating data consistency maintenance subunit is used to maintain the adjusted prescription in the prescription issuance decision process of the prescription issuance gating module based on the gating data consistency result.

10. A multi-role task collaboration system for peritoneal dialysis management of renal disease according to claim 4, characterized in that, The prescription writing interception unit includes: The queue write condition set generation sub-unit is used to identify whether the adjusted prescription has a prescription that can be issued based on the prescription gating record, task lock status table and prescription issuance status, and generate the queue write condition set. The execution queue whitelist generation subunit is used to write the adjusted prescription into the patient-side execution queue whitelist based on the queue writing condition set. When the adjusted prescription has a prescription-issuable flag and there are no operation conflict flags, dietary evidence missing flags, medication evidence missing flags, locked status, or incomplete status in the task lock status table, the adjusted prescription is written into the patient-side execution queue whitelist. The patient-side execution queue whitelist is used as an allowable condition for the adjusted prescription to be written into the patient-side execution queue. The patient-side execution queue whitelist is used for the prescription release result generation unit to call and does not directly trigger the adjustment prescription to be written into the patient-side execution queue. The pending prescription interception result generation subunit is used to generate a pending prescription interception result and prevent the adjustment prescription from being written to the patient's execution queue based on the queue writing condition set when the adjusted prescription has a pending prescription mark, or when there is an operation conflict mark, a missing dietary evidence mark, a missing medication evidence mark, a locked status, or an incomplete status in the task lock status table. The patient-side task execution blocking subunit is used to prevent the generation of patient-side execution tasks based on the prescription to be confirmed when the prescription adjustment is not written into the patient-side execution queue whitelist, based on the prescription confirmation interception result. The original prescription protection result generation subunit is used to maintain the original peritoneal dialysis prescription in the patient's execution queue based on the prescription interception result to be confirmed, and to prohibit the adjustment of prescriptions that cover the original peritoneal dialysis prescription, thereby generating the original prescription protection result. The doctor-side pending confirmation record generation sub-unit is used to write the adjusted prescriptions that are blocked from being written into the patient-side execution queue, the corresponding prescription gating records, and the corresponding locking reasons into the doctor-side pending confirmation prescription list based on the pending confirmation prescription interception results and the original prescription protection results.

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