A postpartum first-aid drill digital simulation method and system and a storage medium

Abstract

The application provides a postpartum first-aid drill digital simulation method and system and a storage medium. The method comprises the following steps: generating a corresponding operation mode identifier according to user operation, and starting a corresponding postpartum hemorrhage first-aid process engine; generating an initial first-aid scene through the postpartum hemorrhage first-aid process engine, and assigning role permissions of each participating role, and loading corresponding operation instruction buttons according to the role permissions; generating operation instructions based on button trigger actions, and performing role permission, precondition and normative verification on the operation instructions; when the verification is passed, executing the business logic corresponding to the operation instructions, updating the dynamic disease parameter, advancing the postpartum hemorrhage scene script, and generating a new postpartum hemorrhage scene state; in the drill process, collecting first-aid operation data of the participating roles in the new postpartum hemorrhage scene state, and generating a quantitative evaluation report through a multi-dimensional weighted scoring model. The application improves the process standardization and automation control level of the postpartum hemorrhage first-aid drill.

Description

Technical Field

[0001] This invention relates to the field of intelligent simulation technology, and in particular to a digital simulation method, system and storage medium for postpartum emergency drills. Background Technology

[0002] Postpartum hemorrhage resuscitation generally follows the core principles of "early identification, rapid emergency call, targeted hemostasis based on the cause, volume resuscitation, and multidisciplinary collaboration." Currently, postpartum hemorrhage resuscitation skills training and emergency drills mainly rely on the following two traditional models: First, there are paper-based emergency plans and procedure manuals. Medical staff learn the rescue procedures by reading and memorizing the key points on their own. This method lacks interactivity and real-time guidance, and in actual operation, problems such as omissions in procedures, reversals of steps, and delays in medication timing are prone to occur. Moreover, it is difficult to provide differentiated training for different causes of the disease.

[0003] Second, there are offline centralized simulation exercises. This model requires advance coordination of venues, mannequins, participants, and supervising experts, resulting in high organizational costs and low frequency of implementation, making it difficult to meet the routine training needs of medical staff. Furthermore, the exercise process relies on manual supervision and scoring, which is highly subjective and inconsistent in standards, making it difficult to achieve standardized and data-driven management throughout the entire process. Summary of the Invention

[0004] This invention provides a digital simulation method, system, and storage medium for postpartum emergency drills to address the problems existing in related technologies. The technical solution is as follows: In a first aspect, embodiments of the present invention provide a digital simulation method for postpartum emergency drills, comprising: In response to user login and mode selection operations, a corresponding operation mode identifier is generated, resource isolation and scheduling are performed according to the operation mode identifier, and the postpartum hemorrhage emergency process engine corresponding to the operation mode identifier is started. The initial emergency scenario is generated through the postpartum hemorrhage emergency process engine, and the role permissions of each participating role are assigned. The corresponding operation instruction buttons are loaded and displayed according to the role permissions. In response to the triggering of the operation instruction button by the participating role, the generated operation instruction is received and the operation instruction is verified. The verification includes role permission verification, precondition verification and standardization verification based on the preset SOP rule base. If the verification passes, execute the business logic corresponding to the operation instruction, update the dynamic condition parameters including bleeding volume and vital signs, and advance the postpartum hemorrhage scenario script based on the updated condition parameters to generate and display a new postpartum hemorrhage scenario status. During the exercise, real-time data on emergency procedures performed by participating roles under new postpartum hemorrhage scenarios was collected, and a quantitative assessment report was generated based on the emergency procedure data through a multi-dimensional weighted scoring model.

[0005] In one implementation, the operation mode identifier includes a training mode identifier, an assessment mode identifier, and a clinical emergency assistance mode identifier; When the operation mode is identified as the training mode, the postpartum hemorrhage emergency procedure engine is set to support operation rollback, prompts, pause, and re-execution. When the operation mode is identified as the assessment mode, the postpartum hemorrhage emergency process engine is set to prohibit operation rollback and prompts, and triggers the timing, automatic scoring and operation trajectory recording functions. When the operation mode is identified as the clinical emergency support mode, the workflow engine is set to have no workflow restrictions and triggers guideline, medication and operation reminder functions, while also connecting with the medical record system in real time. The training mode identifier and the assessment mode identifier both include a single-person training sub-identifier and a multi-person collaboration sub-identifier.

[0006] In one implementation, when the operation mode identifier includes a multi-user collaboration sub-identifier, it further includes: Start the collaborative service so that all participating roles can share the same process state; The received operation instructions are synchronized to the front end of all participating roles in real time through the WebSocket protocol and a distributed state machine, and an audio and video communication channel is established. After any participating role completes its operation command, it automatically advances to the next collaborative scenario based on the updated disease parameters, and synchronizes the new scenario status to the front end of all participating roles.

[0007] In one implementation, dynamic disease parameters are updated using a time-based physiological driving model; the physiological driving model includes: The vital signs dynamic simulation module uses a physiological dynamics closed-loop control algorithm combined with a hysteresis mathematical model to simulate the pathophysiological changes of postpartum hemorrhage and hemorrhagic shock, and generates corresponding vital signs indicators in real time based on the pathophysiological changes. The vital signs indicators include systolic blood pressure, diastolic blood pressure, heart rate, blood oxygen saturation, respiratory rate, pulse, and shock index; the shock index is calculated in real time according to the ratio of heart rate to systolic blood pressure. The bleeding volume quantification simulation module simulates three bleeding rate modes—slow oozing, rapid bleeding, and fulminant hemorrhage—as well as three bleeding types—continuous bleeding, paroxysmal bleeding, and intermittent bleeding—by controlling the output rate and on / off rhythm of the controllable flow output device. The disease grading and automatic evolution module uses a finite state machine combined with a rule engine to preset four levels of postpartum hemorrhage, including Level 1 mild, Level 2 moderate, Level 3 severe, and Level 4 critical. It also configures the blood loss percentage threshold, core vital sign parameter range, and outcome logic for each level.

[0008] In one implementation, the outcome logic of the disease grading and automatic evolution module includes: Without effective intervention, the disease severity is automatically graded according to a fixed timeline, gradually worsening. Upon receiving a valid operation command, the condition reversal logic is triggered, causing the current condition level to shift to a lower level and updating the dynamic condition parameters. Different operation commands correspond to different rates of change in condition parameters. Among them, the rate of reduction in bleeding corresponding to uterine massage is greater than the rate of reduction in bleeding corresponding to oxytocin administration, and the rate of decrease in shock index corresponding to blood transfusion is greater than the rate of decrease in shock index corresponding to fluid resuscitation.

[0009] In one implementation, the SOP rule base is a standardized emergency procedure knowledge base pre-set based on clinical guidelines for postpartum hemorrhage. The knowledge base has a three-tiered process for the early warning period, treatment period, and critical period, and has configured exclusive treatment branch processes for the four major causes of postpartum hemorrhage, clarifying the core operations, medication dosages and contraindications for each stage.

[0010] In one implementation, it further includes: A timeout reminder mechanism is set up for preset key operations. When the corresponding operation instruction is not received within the preset time threshold, a timeout reminder message is generated and pushed to the front end. Key operations include establishing intravenous access, administering oxytocin, uterine massage, and calling for blood transfusion. The system will automatically pop up a list of physical consumables and equipment based on the current situation, indicating the location and quantity to be used.

[0011] In one implementation, the multi-dimensional weighted scoring model includes: The data acquisition layer is used to extract specified indicators from emergency medical operation data. These indicators include compliance identifiers for each operation instruction, execution timestamps for each operation instruction, deviations from the standard time sequence for each operation instruction, number of times an operator exceeded their authority, and the number of key steps completed. The dimensionality stratification is used to calculate scores for specified dimensions based on the output of the data acquisition layer. These specified dimension scores include operational accuracy score, operational timing score, time responsiveness score, role compliance score, and clinical integrity score. The weighted calculation layer is used to calculate the basic total score based on the scores of the specified dimensions according to preset weights. The deduction correction layer is used to deduct from the base total score based on the violations found in the verification results, thus generating the final total score.

[0012] Secondly, embodiments of the present invention provide a digital simulation system for postpartum emergency drills, which executes the digital simulation method for postpartum emergency drills as described above, including: The mode management module is used to generate corresponding operation mode identifiers based on user login and mode selection, and to perform resource isolation and scheduling based on the operation mode identifiers; The process engine module is used to generate an initial emergency response scenario based on the operation mode identifier and assign role permissions to each participating role. The operation verification module is used to verify the received operation instructions. The verification includes role and permission verification, precondition verification, and standardization verification based on the preset SOP rule base. The scenario update module is used to execute the business logic corresponding to the verified operation instructions, update the dynamic condition parameters including bleeding volume and vital signs, and advance the postpartum hemorrhage scenario script based on the updated condition parameters, generating and displaying the new postpartum hemorrhage scenario status. The data acquisition and scoring module is used to collect real-time data on the emergency procedures performed by participating roles in new postpartum hemorrhage scenarios during the exercise. Based on the emergency procedure data, a quantitative assessment report is generated through a multi-dimensional weighted scoring model.

[0013] Thirdly, embodiments of the present invention provide a computer-readable storage medium that stores a computer program, wherein when the computer program is run on a computer, the methods in any of the above-described embodiments are executed.

[0014] The advantages or beneficial effects of the above technical solutions include at least the following: This invention solves the resource interference problem between different modes by generating operation mode identifiers and performing resource isolation scheduling. Based on role-based permissions, operation buttons are dynamically loaded. Combined with triple verification of role permissions, preconditions, and SOP rule base, unauthorized access, incorrect sequence, and missing steps can be intercepted in real time, overcoming the process chaos caused by traditional reliance on memory. After successful verification, bleeding volume and vital signs are dynamically updated, and the scenario script is advanced, allowing the patient's condition to move in real-time with the operation, solving the problem of traditional simulated patient condition changes not being able to respond dynamically. Simultaneously, operation data is collected in real time and a quantitative assessment report is automatically generated through a multi-dimensional weighted scoring model, eliminating subjective differences in human scoring, significantly reducing human error, improving the real-time verification and dynamic linkage of emergency operations, and achieving objective and standardized assessment.

[0015] The above overview is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the invention will become readily apparent from the accompanying drawings and the following detailed description. Attached Figure Description

[0016] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the various drawings denote the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments disclosed in the invention and should not be construed as limiting the scope of the invention.

[0017] Figure 1 This is a flowchart illustrating the digital simulation method for postpartum emergency drills of the present invention. Detailed Implementation

[0018] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0019] Example 1 This embodiment provides a digital simulation method for postpartum emergency drills. This method achieves comprehensive optimization of postpartum hemorrhage emergency drills through intelligent and information technology, and significantly reduces human error through intelligent digital simulation.

[0020] like Figure 1 As shown, the digital simulation method for postpartum emergency drills in this embodiment specifically includes: Step S1: In response to user login and mode selection operations, generate a corresponding operation mode identifier, perform resource isolation and scheduling according to the operation mode identifier, and start the postpartum hemorrhage emergency process engine corresponding to the operation mode identifier.

[0021] Users install and open the postpartum hemorrhage emergency drill app via mobile smart devices (such as smartphones or tablets). First-time users are required to authenticate their identity. The backend server stores authorized medical staff account information. After the user enters their employee ID and password, the frontend sends the login credentials to the backend for verification. Upon successful authentication, the server returns the user's permission information (such as resident physician, attending physician, midwife, etc.) and redirects the user to the mode selection interface.

[0022] The mode selection interface displays several selectable modes, including: Training Mode - Single Person Training, Training Mode - Multi-Person Collaboration, Assessment Mode - Single Person Training, Assessment Mode - Multi-Person Collaboration, and Clinical Emergency Assistance Mode. Each mode is accompanied by a brief description of its functions. For example, the Training Mode is labeled "Undoable, Hints Available, Pauseable, Repeatable," the Assessment Mode is labeled "No Undoable, No Hints, Timed Scoring," and the Clinical Emergency Assistance Mode is labeled "No Process Restrictions, Real-Time Guideline Reminders."

[0023] When a user clicks on a specific mode in the postpartum hemorrhage emergency drill app, the front end generates a JSON-formatted operation mode identifier (mode) field. Specifically, the mapping relationship defined by the front end is shown in Table 1.

[0024] Table 1 Front-end defined pattern encoding Functional Scenarios Mode identifier Training Mode - Single Player Training TRAIN_SINGLE Training Mode - Multi-person Collaboration TRAIN_MULTI Assessment Mode - Individual Training EXAM_SINGLE Assessment Mode - Multi-person Collaboration EXAM_MULTI Clinical emergency support mode CLINIC_EMERGENCY The frontend encapsulates the mode field along with the user token into the header or body of the HTTP request and sends it to the backend API gateway.

[0025] If `mode` is the training mode identifier (i.e., "TRAIN_SINGLE" or "TRAIN_MULTI"), the postpartum hemorrhage emergency response engine started in the backend is configured to support operation rollback, prompts, pause, and repetition. Specifically, the engine maintains an operation history stack, allowing users to roll back to any previous step; when a user's operation does not conform to the specifications, the engine pushes a prompt message to the frontend without deducting points; users can pause the exercise at any time and continue later; the same scenario can be repeated multiple times. If `mode` is "TRAIN_SINGLE" (single-person training sub-identifier), the engine only maintains the state of a single user, and all operation instructions are completed independently by that user; if `mode` is "TRAIN_MULTI" (multi-person collaboration sub-identifier), the engine additionally starts a collaboration service module, using the WebSocket protocol to synchronize the states of multiple roles and assign independent permissions to each role.

[0026] If the mode is set to the assessment mode identifier (i.e., "EXAM_SINGLE" or "EXAM_MULTI"), the postpartum hemorrhage emergency response engine started in the backend is set to disable operation rollback and prompts, while automatically triggering timing, automatic scoring, and operation trajectory recording functions. Specifically, the engine disables the rollback button, preventing users from going back to the previous step; all operational errors are no longer prompted but are directly recorded as deduction items; the timer starts automatically from the start of the exercise, and operations that exceed the time limit are marked; the engine records every user's operation command, timestamp, and snapshot of the patient's condition parameters in real time, forming a complete operation trajectory. If the mode is "EXAM_SINGLE" (single-person training sub-identifier), scoring generates an individual report only for a single user; if the mode is "EXAM_MULTI" (multi-person collaboration sub-identifier), the engine activates the collaboration service, allowing all participating roles to share the same process status, and ultimately generates a two-tiered report of team total score and individual score.

[0027] Sharing the same process state means that the backend creates a unique process instance for each exercise, and all participating roles are bound to the same instance, sharing the same process state and patient parameters. When any role executes an operation command, the backend broadcasts the command and updated patient parameters to the frontends of all other roles in real time via the WebSocket protocol, ensuring synchronized interface updates. Simultaneously, the system establishes an independent WebRTC audio and video channel to support real-time voice communication between roles. After the operation command is executed, the postpartum hemorrhage emergency process engine automatically determines whether the scenario transition conditions are met based on the updated patient parameters. If so, it advances to the next collaborative scenario and synchronously pushes the new scenario state to all frontends, achieving "synchronized operation, patient-driven, and consistent interface" multi-person collaborative exercises.

[0028] If the mode is set to Clinical Emergency Assistance Mode (i.e., "CLINIC_EMERGENCY"), the backend-driven workflow engine is set to have no workflow restrictions, meaning that operations are not required to be performed in a fixed order, and users can freely jump to any rescue step. Simultaneously, the engine triggers real-time guide push notifications, medication and operation reminders: after the user enters patient data, the system automatically matches a standardized rescue procedure and displays the currently recommended operation steps, medication dosages, and precautions on the interface. Furthermore, the engine connects in real-time with the hospital's medical record system via the HL7 / FHIR interface, automatically reading the patient's basic information, vital signs, and laboratory results, and writing back key treatment records from the drills to the medical record system to assist in real-world clinical rescue decisions.

[0029] This embodiment generates a corresponding operation mode identifier based on the mode selected by the user, and performs differentiated resource scheduling and process engine configuration accordingly, effectively avoiding resource interference between different modes and realizing seamless switching and precise adaptation of multiple scenarios on the same platform.

[0030] Step S2: Generate an initial emergency scenario through the postpartum hemorrhage emergency process engine, assign role permissions to each participating role, and load and display the corresponding operation instruction buttons according to the role permissions.

[0031] After completing mode selection and engine startup, this embodiment enters the scenario generation stage of the emergency response process engine. Specifically, based on the exercise parameters selected by the user (such as bleeding volume, etiology type, and scenario difficulty), the rule engine automatically generates an initial emergency response scenario that conforms to clinical logic, and assigns corresponding operation permissions and responsibility lists to each participant according to preset role templates.

[0032] The "initial emergency scenario" is a structured dataset used to fully describe the patient's condition at the start of the exercise. Specifically, it includes initial condition data (cumulative blood loss, systolic / diastolic blood pressure, heart rate, blood oxygen saturation, respiratory rate, shock index, and other vital signs), cause-related text (such as "soft uterus with indistinct outline, suggesting uterine atony"), scenario difficulty level (general, severe, or refractory, corresponding to postpartum hemorrhage grades I to IV), initial scenario description text (such as "30 minutes after vaginal delivery, continuous heavy vaginal bleeding, totaling 1200ml, heart rate 125 beats / min, blood pressure 85 / 50mmHg"), and the simulated human state and blood accumulation effect in the visualization interface.

[0033] First, after the user selects a mode, the front-end displays a scenario parameter configuration interface. Parameters include preset bleeding volume (can be manually entered or a range selected, such as 500ml, 1000ml, 1500ml, or over 2000ml, or randomly generated), bleeding rate (three levels: slow oozing, rapid bleeding, and fulminant hemorrhage), comorbidity options (whether it's preeclampsia, anemia, coagulation disorders, etc.), and etiological tendency (can specify one of uterine atony, placental factors, soft tissue injury, or coagulation disorders, or select random / mixed). After the user confirms the parameters, the front-end encapsulates these parameters into JSON format and sends them, along with the operation mode identifier, to the back-end.

[0034] It should be explained that slow bleeding can be defined as continuous, slow bleeding, with a blood loss of approximately 100-200 mL per hour, and relatively stable vital signs. Rapid bleeding can be defined as a bleeding rate >150 mL / min or a cumulative blood loss that rapidly reaches 1000-2000 mL, with significant deterioration of vital signs. Burst hemorrhage can be defined as a blood loss of >2000 mL in a short period of time, which can be referenced in FIGO's criteria for "massive postpartum hemorrhage" (>2500 mL or shock).

[0035] After receiving the parameters, the backend calls the pre-built postpartum hemorrhage scenario rule engine (based on Drools or a self-developed decision tree). The rule engine automatically determines the scenario difficulty level (general, severe, refractory) according to a composite algorithm model based on three weight factors: bleeding volume, bleeding rate, and complications, and generates initial condition data, which includes bleeding volume, vital signs, and etiology prompt text.

[0036] Once generated, the backend combines the initial patient data, difficulty level, and other information into a complete initial emergency scenario data package and returns it to the frontend. The frontend then displays the amount of bleeding, vital signs, and cause-of-illness information in the top area of ​​the interface.

[0037] The system also includes standard role templates for postpartum hemorrhage emergency care, including a commander, obstetrician (surgeon / assistant), midwife, anesthesiologist, circulating nurse, laboratory liaison, and blood transfusion liaison. The system automatically assigns role permissions based on the user's authentication information upon login and the current exercise mode (single / multi-person).

[0038] In single-user training mode, the current user automatically gains access to all roles. The front-end control panel displays all available operation command buttons (such as uterine massage, medication, blood transfusion, suturing, etc.), but the system will still record in the background which operations should belong to which role for subsequent role compliance scoring.

[0039] In multi-user collaborative mode, the system assigns operation permissions only to the user's pre-defined role based on their login account (e.g., the account "Dr. Zhang" is bound to the role of an obstetrician). The front-end operation panel only loads the instruction buttons within the scope of that role's responsibilities. For example, an obstetrician can see instructions such as uterine massage, oxytocin administration, and uterine packing, while a midwife can only see instructions such as monitoring vital signs, establishing intravenous access, and recording blood loss. The overall command role also has additional instructions such as calling for blood transfusions, initiating critical care procedures, and making ICU transfer decisions.

[0040] At the same time, the system generates a unique list of responsibilities for each role, which is displayed in a pop-up window or sidebar. For example, the responsibilities of a midwife include establishing two or more intravenous access lines, recording blood loss every 15 minutes, preparing and administering oxytocin as prescribed by the doctor, and assisting the doctor with uterine massage, ensuring a clear division of labor.

[0041] Step S3: In response to the triggering of the operation instruction button by the participating role, receive the generated operation instruction, and verify the operation instruction. The verification includes role permission verification, precondition verification, and standardization verification based on the preset SOP rule base.

[0042] When a participant clicks an operation instruction button during the exercise, the front end immediately captures the triggering event and generates an operation instruction. The front end then sends the operation instruction to the backend server via a WebSocket long connection or an HTTP request.

[0043] After receiving the operation instruction, the backend enters the verification process, which includes three verification steps that are executed sequentially and are indispensable: role and permission verification, precondition verification, and standardization verification based on the pre-set SOP rule base.

[0044] The role permission verification process is as follows: The backend first extracts the role ID and instruction ID from the operation command and queries the permission list of that role in the current process instance. This permission list is pre-assigned in step S2 according to user identity and training mode and stored in Redis cache in key-value pairs. The backend determines whether the instruction ID exists in the current role's permission list. For example, the obstetrician's permission list includes instructions such as "uterine massage," "oxytocin application," and "uterine packing," but does not include "record bleeding" (this instruction belongs to the midwife's permission). If a role attempts to trigger an instruction that is not in its permission list (such as the obstetrician clicking "record bleeding"), the backend immediately returns an error code, refuses to execute, and handles it differently according to the current operation mode: In training mode, the frontend pops up a message saying "You are not authorized to perform this operation; this operation belongs to the midwife's responsibility"; in assessment mode, the frontend does not pop up a message, but the backend records an "unauthorized operation" violation in the background and deducts the corresponding points. After the role permission verification is passed, the precondition verification begins.

[0045] Precondition validation ensures that the execution order of operation instructions conforms to clinical logic, preventing users from skipping necessary steps. The system predefines precondition expressions for each operation instruction, written in SpEL or a custom scripting language, and stores them in a rule configuration table. For example, the precondition for the "Oxytocin Application" instruction is "Intravenous access established"; the precondition for the "Blood Transfusion" instruction is "Blood type crossmatch completed and intravenous access established"; and the precondition for the "Uterine Massage" instruction is "Uterine atony confirmed by palpation." Before executing an instruction, the backend reads the condition variables in the current process status (these variables are updated during the execution of preceding operations) and checks whether the preconditions are met. If the conditions are not met, the backend refuses to execute and returns the specific reason. For example, if a user clicks "Oxytocin Application" but the system detects that the "Intravenous Access Established" flag is false, the frontend will prompt "Please establish intravenous access first" in training mode, and the backend will record an "incorrect sequence" violation in assessment mode. After the precondition validation passes, the instruction proceeds to the SOP rule base for standardization validation.

[0046] The Standard Operating Procedure (SOP) rule base is a standardized emergency response knowledge base based on clinical guidelines for postpartum hemorrhage (such as the "Guidelines for the Prevention and Management of Postpartum Hemorrhage (2023)"). Specifically, it transforms the guideline content into a set of computer-executable "if-then" rules, managed by the Drools rule engine. The SOP rule base has a three-tiered process: warning, treatment, and critical stages, with dedicated treatment branches configured for the four major causes of postpartum hemorrhage, clearly defining the core operations, medication dosages, and contraindications for each stage. Each rule in the SOP rule base includes triggering conditions (such as medication timing, contraindications, and dosage range) and violation actions (such as marking errors and deducting points). The backend inputs the current operation command along with the process context (such as the patient's current blood loss, vital signs, medication records, and operation timeline) into the Drools rule engine. The engine matches all rules that meet the conditions and returns the verification results. If any violation rule is matched, the backend will handle it according to the operation mode: in training mode, the frontend will display a warning message (such as "Oxytocin dosage exceeds the recommended maximum single dose"); in assessment mode, the backend will record the violation type and deduction score, but will not interrupt the execution of the instruction (unless the rule is marked as "blocking"). If no violation rule is matched, the SOP verification will pass.

[0047] If any verification fails in assessment mode, the backend will mark the operation as "invalid operation" or "violation operation" and record the corresponding deduction item in the scoring engine according to the preset deduction rules, but will not update the disease parameters or advance the plot. The front-end interface will remain unchanged and display a prompt that the operation is invalid (no prompt will be displayed in assessment mode, only the backend will record it).

[0048] Only when role permission verification, precondition verification, and SOP rule base standardization verification all pass will the backend continue to execute subsequent steps—that is, execute the business logic corresponding to the operation instruction, update dynamic disease parameters, and advance the scenario script.

[0049] Step S4: If the verification passes, execute the business logic corresponding to the operation instruction, update the dynamic condition parameters including bleeding volume and vital signs, and advance the postpartum hemorrhage scenario script based on the updated condition parameters to generate and display a new postpartum hemorrhage scenario status.

[0050] In this embodiment, the backend predefines a business logic processor for each type of operation instruction. Upon receiving a verified operation instruction, the backend locates the corresponding processor using the instruction ID and calls its execution method, passing in the context of the current process instance (including current patient condition parameters, operation timestamp, role information, etc.). The processor executes the corresponding calculation logic based on the operation type (e.g., hemostasis, medication administration, volume resuscitation), including adjusting bleeding rate, modifying uterine tension, recording drug onset time and duration of effect, and outputting updated patient condition parameter variables.

[0051] After the business logic is executed, the backend calls the physiologically driven model to update dynamic patient parameters. The physiologically driven model includes a dynamic simulation module for vital signs, which uses a dynamic simulation algorithm combined with a first- or second-order hysteresis mathematical model to simulate the pathophysiological changes of postpartum hemorrhage-induced shock. Based on these pathophysiological changes, it generates corresponding vital signs in real time, including systolic blood pressure, diastolic blood pressure, heart rate, oxygen saturation, respiratory rate, pulse, and shock index. The shock index is calculated in real time based on the ratio of heart rate to systolic blood pressure, used to quantitatively assess circulatory function status.

[0052] The physiological driving model also includes a blood loss quantification simulation module. This module simulates three bleeding rate modes—slow oozing, rapid bleeding, and fulminant hemorrhage—by controlling the output rate and on / off rhythm of a controllable flow output device. It also simulates three bleeding types: continuous bleeding, paroxysmal bleeding, and intermittent bleeding, ensuring the simulation closely reflects clinical reality. The controllable flow output device employs a micro-peristaltic pump and solenoid valve closed-loop flow control technology, combined with a high-precision weighing sensor to collect blood loss in real time, enabling precise control of bleeding rate and automatic calculation of blood loss.

[0053] The physiologically driven model also includes a disease grading and automatic evolution module, which operates independently according to a preset outcome logic. This module uses a finite state machine combined with a rule engine to monitor the current disease grading and the effectiveness of intervention operations in real time. For example, when the system detects that there are no effective intervention operation records for a continuous period of time (e.g., 10 consecutive minutes), the disease grading and automatic evolution module automatically advances the disease grading according to a fixed time axis: at each preset deterioration time threshold (e.g., 5 minutes), the disease grading shifts to a higher level, for example, automatically evolving from level 1 mild to level 2 moderate, then to level 3 severe, and level 4 critical, accompanied by a gradual increase in bleeding and synchronous deterioration of vital signs according to a lagging mathematical model, to simulate the natural course of the disease caused by the lack of timely treatment in real clinical practice.

[0054] Conversely, when the disease grading and automatic evolution module receives a valid operation command that has passed verification, it triggers the disease reversal logic. The core of the reversal logic is to calculate the rate of change of disease parameters based on the operation type and shift the current disease grading to a lower level. Specifically, different operation commands correspond to different rates of change of disease parameters. For example, uterine massage can directly stimulate uterine contractions, and its corresponding rate of reduction in bleeding is set to decrease the bleeding rate by 40% to 60% per minute, with a rapid and direct effect; while oxytocin application requires blood circulation to take effect, and its corresponding rate of reduction in bleeding is relatively slower, approximately 15% to 25% per minute. Therefore, under the same initial bleeding conditions, the rate of reduction in bleeding brought about by uterine massage is significantly greater than that brought about by oxytocin application.

[0055] The disease grading and automatic evolution module dynamically adjusts the rate of change of disease parameters based on the type of operation instruction, and determines whether the downgrade threshold is met according to the transition conditions of the finite state machine. For example, when the bleeding volume drops below the current grade's blood loss percentage threshold and the shock index is below 0.9, the disease grade reverses from Grade III (severe) to Grade II (moderate), and the front-end interface simultaneously updates the disease prompts and pushes the "patient's condition has improved" information.

[0056] Through the above-mentioned outcome logic, a precise simulation of the evolution of postpartum hemorrhage is achieved, supporting both natural deterioration without intervention and differentiated reversal under effective intervention, significantly improving the realism and teaching value of simulation training.

[0057] The three modules work together: the bleeding volume quantification simulation module outputs the current bleeding rate and cumulative bleeding volume based on operation instructions and business logic; the vital signs dynamic simulation module calculates and updates various vital signs indicators based on bleeding volume and operation intervention effects using a lag mathematical model; and the disease grading and automatic evolution module determines the current disease level based on real-time updated bleeding volume and vital signs, and automatically advances or reverses the disease grading according to preset outcome logic.

[0058] Subsequently, the backend calls the process engine's evaluation function to determine whether the node transfer conditions of the scenario script are met based on the updated condition parameters (including bleeding volume, shock index, uterine tension, etc.). Script node transfer conditions are related to thresholds for condition parameters, such as cumulative bleeding reaching a certain value, shock index exceeding a preset limit, or changes in uterine tension. If the transfer conditions are met, the process engine automatically switches the current script node to the next node and executes a node entry action (such as pushing a system notification). If the condition improves, reverse transfer is also supported. For cases where node transfer is not triggered but condition parameters change significantly, the process engine updates the internal variables of the current node and triggers corresponding events (such as alarm events).

[0059] Finally, the backend packages the new scenario status data, including the current node name, node description text, the latest snapshot of patient parameters, and the animation commands required for the visualization interface. This scenario status data is pushed to the frontend of all participating roles via the WebSocket protocol. Upon receiving the new scenario status, the frontend refreshes the vital signs panel, bleeding volume display, cause indication area, 3D simulator status, and process progress bar on the interface. It also automatically unlocks the next batch of available operation command buttons based on the expected operation list of the new node, thus completing the complete closed loop of "operation - patient condition update - scenario progression - interface refresh".

[0060] Step S5: During the exercise, real-time data on the emergency procedures performed by the participating roles in the new postpartum hemorrhage scenario is collected, and a quantitative assessment report is generated based on the emergency procedure data through a multi-dimensional weighted scoring model.

[0061] Throughout the exercise, the backend system collected emergency operation data in real time from each participating role in a real-time event-driven manner, which included the operation instruction ID, operation name, triggering role ID, operation timestamp, current scenario node ID, verification result, and snapshots of patient parameters before and after the operation (including cumulative blood loss, systolic blood pressure, diastolic blood pressure, heart rate, blood oxygen saturation, shock index, etc.).

[0062] During the exercise, the backend system configured timeout thresholds for preset key operations (including establishing intravenous access, administering oxytocin, uterine massage, and calling for blood transfusion). If the corresponding operation instruction was not received after the preset time threshold, the system generated a timeout reminder message and pushed it to the frontend via WebSocket. In training mode, only a reminder was given without deducting points, while in assessment mode, the violation was recorded and points were deducted. Simultaneously, the system automatically displayed a list of corresponding physical consumables and equipment based on the current scenario, indicating the simulated storage location and required quantity of each consumable. The list was dynamically updated with each scenario node, and users could select items that had been used; the system recorded the time of use.

[0063] After the drill, the backend automatically triggers a quantitative evaluation process, inputting the emergency medical operation data into a multi-dimensional weighted scoring model. In this embodiment, the multi-dimensional weighted scoring model includes: The data acquisition layer is used to extract specified indicators from emergency medical operation data. These indicators include compliance identifiers for each operation instruction, execution timestamps for each operation instruction, deviations from the standard time sequence for each operation instruction, number of times an operator exceeded their authority, and the number of key steps completed. The dimensionality stratification is used to calculate scores for specified dimensions based on the output of the data acquisition layer. These specified dimension scores include operational accuracy score, operational timing score, time responsiveness score, role compliance score, and clinical integrity score. The weighted calculation layer assigns different weights to each specified dimension. For example, the weight for operational accuracy is 35%, the weight for operational timing is 25%, the weight for time responsiveness is 20%, the weight for role compliance is 10%, and the weight for clinical integrity is 10%. The base total score is obtained by summing the weights according to the preset weights. The deduction correction layer is used to deduct points from the base total score based on violations found in the verification results, generating a final total score. For example, if a violation involves a critical step omission (such as failure to establish intravenous access within the specified time, failure to administer oxytocin, or failure to initiate blood transfusion), 20 points will be deducted directly. If there is an error in the order of operations (such as failure to complete cross-matching before blood transfusion), 10 points will be deducted for each instance. The lower limit of the final total score after deductions is 0 points. All deductions are accompanied by specific operation timestamps and reasons for violations, facilitating subsequent traceability.

[0064] After scoring is completed, a quantitative assessment report is automatically generated. The report is output in both HTML and PDF formats, and includes basic information about the exercise (trainee name, exercise scenario, total time), final total score and grade (Excellent / Good / Pass / Fail), radar charts of scores in five specified dimensions, a detailed timeline of operations (marking the correct / incorrect / timeout / unauthorized status of each operation), a timeline comparison chart of key steps (displaying the actual operation timeline alongside the standard timeline), and clinical evaluation suggestions (improvement suggestions automatically generated based on violation records).

[0065] For multi-person collaborative exercises, the report also generates a two-tiered structure of team total score and individual score. For example, the team total score is calculated based on the process completion rate (the percentage of key steps completed) and the role cooperation rate (the average interval between operation instructions, the total number of unauthorized operations, etc.); the individual score is calculated separately based on the accuracy, timing and compliance of each role's operation.

[0066] Finally, the system packages and stores the complete operation log, patient parameter snapshot sequence, and assessment report into a cloud database, generating a unique replay link. Users can use this link to replay the entire exercise step-by-step on the web using a timeline slider, viewing the interface status before and after each operation, changes in patient parameters, and system prompts, enabling detailed replay analysis. For offline exercise scenarios, the above data will be temporarily stored in the mobile terminal's local database and automatically synchronized to the cloud once the network is restored, ensuring no data loss.

[0067] This embodiment addresses the shortcomings of existing postpartum hemorrhage rescue and drill techniques by comprehensively optimizing postpartum hemorrhage emergency drills through intelligent and information-based technologies. Compared to traditional techniques and existing general medical training tools, it has the following outstanding advantages: 1. Standardized management of the emergency response process significantly reduces human error. This method, through built-in guidelines and process node triggering algorithms, guides medical staff to complete the treatment according to the standards throughout the process, eliminating problems such as process omissions, reversed steps, and medication errors. It transforms subjective human control into standardized system management, effectively shortens the emergency response time, firmly grasps the golden window for postpartum hemorrhage rescue, and reduces clinical rescue risks.

[0068] 2. Constructing highly realistic dynamic scenarios enhances the practicality and relevance of drills. Unlike traditional single-drill models, this method can simulate various complex and critical postpartum hemorrhage scenarios, recreating the real-life situation of sudden changes in clinical condition. This overcomes the drawbacks of drills being merely perfunctory, strengthens medical staff's emergency decision-making and emergency response capabilities, and ensures that the drill content is highly aligned with clinical rescue, rapidly improving practical skills.

[0069] 3. Establish a multi-person collaborative closed-loop system to optimize team collaboration efficiency. Through multi-role division of labor, real-time command scheduling, and information synchronization, it solves the problems of unclear division of labor and lagging communication in traditional drills, clarifies the responsibilities of each position, and achieves "unified command, division of labor and cooperation, and efficient linkage," thereby improving the collaborative rescue capabilities of multidisciplinary teams. It is especially suitable for the routine collaborative training of obstetric emergency teams.

[0070] 4. Establish a quantitative assessment and data traceability mechanism to achieve precise training and improvement. This method automatically records operational data throughout the entire process, replaces subjective manual assessment with objective quantitative scoring, accurately identifies weak links in operations, and, in conjunction with review and traceability functions, achieves closed-loop training of "practice-assessment-rectification-improvement," significantly improving the effectiveness and efficiency of drills and training while reducing training costs.

[0071] 5. Lightweight and mobile-adaptable for convenient routine drills. Designed based on a mobile app, it eliminates the need for dedicated venues and large equipment, supports offline drills and fragmented training, and adapts to the routine drill needs of medical institutions at all levels, especially grassroots hospitals. It solves the problems of insufficient drill resources and organizational difficulties at the grassroots level, comprehensively improves the postpartum hemorrhage emergency response capabilities of obstetric medical staff at the grassroots level, and narrows the gap in medical emergency response levels between urban and rural areas.

[0072] 6. This method offers dual practical applications, balancing drills and clinical use. It can be used not only for specialized emergency drills but also as an emergency support tool in clinical situations involving sudden postpartum hemorrhage. It quickly matches procedures and provides operational guidance, achieving a dual function of "training + clinical application." Compared to single-function training software, it has a wider range of applications and higher technical value.

[0073] 7. Cloud-based updates and data management ensure the timeliness and traceability of technology. The knowledge base is updated in real time in the cloud to ensure that process standards are synchronized with the latest clinical guidelines; exercise data is stored in the cloud, which facilitates unified management by medical institutions, assessment of medical staff skills, and provides data support for clinical emergency quality control, helping to continuously improve the quality of obstetric emergency care.

[0074] Example 2 This embodiment provides a digital simulation system for postpartum emergency drills, executing the digital simulation method for postpartum emergency drills as described in Embodiment 1. This system adopts a three-layer architecture of "front-end mobile APP + back-end cloud database + intelligent algorithm engine," and its core includes at least five collaborative modules: The mode management module is used to generate operation mode identifiers (training / assessment / clinical assistance, including single / multi-person sub-identifiers) based on user login and mode selection, and to perform resource isolation and scheduling based on the identifiers. In multi-person collaborative mode, operation synchronization and audio / video communication are achieved through WebSocket.

[0075] The process engine module is used to start the corresponding engine according to the operation mode identifier, generate the initial emergency scenario (including bleeding volume, vital signs, etiology prompts), assign role permissions, and call the built-in standardized emergency process knowledge base (based on clinical guidelines, including a three-level ladder process and etiology branches).

[0076] The operation verification module performs triple verification of operation instructions based on role permissions, preconditions, and SOP rule base. It sets timeout reminders for critical operations (establishing intravenous access, administering oxytocin, uterine massage, and calling for blood transfusion) and pops up a consumables list according to the scenario.

[0077] The scenario update module is used to execute business logic, update disease parameters such as bleeding volume and vital signs, and advance the scenario script through a physiological driving model (including vital sign simulation, bleeding volume quantification, and automatic evolution of disease grading) to generate new scenario states.

[0078] The data collection and scoring module is used to collect operational data in real time. After the exercise, it automatically generates a quantitative evaluation report through a multi-dimensional weighted scoring model. It supports single-person reports and multi-person collaborative two-level reports, and provides review playback.

[0079] In this embodiment, multiple modules of the system work together: after the mode management completes the scheduling, the process engine generates a scenario; after the operation verification is passed, the scenario is updated to execute the business and update the patient's condition; the data collection and scoring record the entire process and generate a report, realizing the standardization and closed-loop management of postpartum hemorrhage emergency drills.

[0080] It should be noted that the functions of each module in the system of this embodiment can be found in the corresponding descriptions in the above methods, and will not be repeated here.

[0081] Example 3 This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method provided in Embodiment 1 of this invention.

[0082] This invention also provides a chip, which includes a processor for calling and executing instructions stored in a memory, causing a communication device on which the chip is installed to perform the method provided in this invention.

[0083] This invention also provides a chip, including: an input interface, an output interface, a processor, and a memory. The input interface, output interface, processor, and memory are connected through an internal connection path. The processor is used to execute code in the memory. When the code is executed, the processor is used to execute the method provided in this invention.

[0084] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. General-purpose processors can be microprocessors or any conventional processor. It is worth noting that the processor can be a processor supporting the Advanced Reduced Instruction Set Computing (RISC) machine (ARM) architecture.

[0085] Further, optionally, the aforementioned memory may include read-only memory and random access memory, and may also include non-volatile random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0086] In the above embodiments, implementation can be achieved, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another.

[0087] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0088] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0089] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in the present invention, and these should all be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A digital simulation method for postpartum emergency drills, characterized in that, include: In response to user login and mode selection operations, a corresponding operation mode identifier is generated, resource isolation and scheduling are performed according to the operation mode identifier, and the postpartum hemorrhage emergency process engine corresponding to the operation mode identifier is started. The postpartum hemorrhage emergency process engine generates an initial emergency scenario, assigns role permissions to each participating role, and loads and displays corresponding operation instruction buttons according to the role permissions. In response to the triggering of the operation instruction button by the participating role, the generated operation instruction is received and the operation instruction is verified, including role permission verification, precondition verification and standardization verification based on the preset SOP rule base. If the verification passes, the business logic corresponding to the operation instruction is executed to update the dynamic condition parameters including bleeding volume and vital signs, and the postpartum hemorrhage scenario script is advanced based on the updated condition parameters to generate and display a new postpartum hemorrhage scenario status. During the exercise, real-time data on emergency procedures performed by participating roles under new postpartum hemorrhage scenarios were collected, and a quantitative assessment report was generated based on the emergency procedure data through a multi-dimensional weighted scoring model.

2. The digital simulation method for postpartum emergency drills according to claim 1, characterized in that, The operation mode identifiers include training mode identifiers, assessment mode identifiers, and clinical emergency assistance mode identifiers; When the operation mode identifier is the training mode identifier, the postpartum hemorrhage emergency process engine is set to support operation rollback, prompting, pausing and re-execution; When the operation mode is identified as the assessment mode, the postpartum hemorrhage emergency process engine is set to prohibit operation rollback and prompts, and triggers the timing, automatic scoring and operation trajectory recording functions. When the operation mode is identified as the clinical emergency assistance mode, the process engine is set to have no process restrictions and triggers the guidelines, medication and operation reminder functions, while simultaneously connecting with the medical record system in real time. The training mode identifier and the assessment mode identifier both include a single-person training sub-identifier and a multi-person collaboration sub-identifier.

3. The digital simulation method for postpartum emergency drills according to claim 2, characterized in that, When the operation mode identifier includes the multi-user collaboration sub-identifier, it also includes: Start the collaborative service so that all participating roles can share the same process state; The received operation instructions are synchronized to the front end of all participating roles in real time through the WebSocket protocol and a distributed state machine, and an audio and video communication channel is established. After any participating role completes its operation command, it automatically advances to the next collaborative scenario based on the updated disease parameters, and synchronizes the new scenario status to the front end of all participating roles.

4. The digital simulation method for postpartum emergency drills according to claim 1, characterized in that, The dynamic disease parameters are updated using a time-based physiological driving model; The physiological driving model includes: The vital signs dynamic simulation module uses a physiological dynamics closed-loop control algorithm combined with a hysteresis mathematical model to simulate the pathophysiological changes of postpartum hemorrhage and hemorrhagic shock, and generates corresponding vital signs indicators in real time based on the pathophysiological changes. The vital signs indicators include systolic blood pressure, diastolic blood pressure, heart rate, blood oxygen saturation, respiratory rate, pulse, and shock index; the shock index is calculated in real time according to the ratio of heart rate to systolic blood pressure. The bleeding volume quantification simulation module simulates three bleeding rate modes—slow oozing, rapid bleeding, and fulminant hemorrhage—as well as three bleeding types—continuous bleeding, paroxysmal bleeding, and intermittent bleeding—by controlling the output rate and on / off rhythm of the controllable flow output device. The disease grading and automatic evolution module uses a finite state machine combined with a rule engine to preset four levels of postpartum hemorrhage, including Level 1 mild, Level 2 moderate, Level 3 severe, and Level 4 critical. It also configures the blood loss percentage threshold, core vital sign parameter range, and outcome logic for each level.

5. The digital simulation method for postpartum emergency drills according to claim 4, characterized in that, The outcome logic of the disease grading and automatic evolution module includes: Without effective intervention, the disease severity is automatically graded according to a fixed timeline, gradually worsening. Upon receiving a valid operation command, the condition reversal logic is triggered, causing the current condition level to shift to a lower level and updating the dynamic condition parameters. Different operation commands correspond to different rates of change in condition parameters. Among them, the rate of reduction in bleeding corresponding to uterine massage is greater than the rate of reduction in bleeding corresponding to oxytocin administration, and the rate of decrease in shock index corresponding to blood transfusion is greater than the rate of decrease in shock index corresponding to fluid resuscitation.

6. The digital simulation method for postpartum emergency drills according to claim 1, characterized in that, The SOP rule base is a standardized emergency procedure knowledge base pre-set based on the clinical guidelines for postpartum hemorrhage. It has a three-tiered procedure for the early warning period, treatment period, and critical period, and has configured exclusive treatment branch procedures for the four major causes of postpartum hemorrhage, clearly defining the core operations, medication dosages and contraindications for each stage.

7. The digital simulation method for postpartum emergency drills according to claim 1, characterized in that, Also includes: A timeout reminder mechanism is set for preset key operations. When the corresponding operation instruction is not received within the preset time threshold, a timeout reminder message is generated and pushed to the front end. The key procedures include establishing intravenous access, administering oxytocin, uterine massage, and calling for a blood transfusion. The system will automatically pop up a list of physical consumables and equipment based on the current situation, indicating the location and quantity to be used.

8. The digital simulation method for postpartum emergency drills according to claim 1, characterized in that, The multi-dimensional weighted scoring model includes: The data acquisition layer is used to extract specified indicators from the emergency operation data. The specified indicators include compliance identifiers of each operation instruction, execution timestamps of each operation instruction, deviation values ​​of each operation instruction from the standard timing, number of times the role exceeded its authority, and number of key steps completed. The dimensionality stratification is used to calculate scores for specified dimensions based on the output of the data acquisition layer. These specified dimension scores include operational accuracy score, operational timing score, time responsiveness score, role compliance score, and clinical integrity score. A weighted calculation layer is used to calculate a basic total score based on the scores of the specified dimensions according to preset weights; The deduction correction layer is used to deduct from the base total score based on the violations found in the verification results, thus generating the final total score.

9. A digital simulation system for postpartum emergency drills, characterized in that, The method for digital simulation of postpartum emergency drills as described in any one of claims 1 to 8 includes: The mode management module is used to generate corresponding operation mode identifiers based on user login and mode selection operations, and to perform resource isolation and scheduling based on the operation mode identifiers; The process engine module is used to generate an initial emergency response scenario based on the operation mode identifier and assign role permissions to each participating role. The operation verification module is used to verify the received operation instructions, including role and permission verification, precondition verification, and standardization verification based on the preset SOP rule base. The scenario update module is used to execute the business logic corresponding to the verified operation instructions, update the dynamic condition parameters including bleeding volume and vital signs, and advance the postpartum hemorrhage scenario script based on the updated condition parameters to generate and display a new postpartum hemorrhage scenario status. The data acquisition and scoring module is used to collect data on emergency procedures performed by participating roles in new postpartum hemorrhage scenarios in real time during the exercise. Based on the emergency procedure data, a quantitative evaluation report is generated through a multi-dimensional weighted scoring model.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the digital simulation method for postpartum emergency drills as described in any one of claims 1 to 8.

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