Automatic allocation method and system for nursing tasks of obstetrics and gynecology department

Abstract

The invention relates to the technical field of resource scheduling, in particular to an automatic allocation method and system for nursing tasks in the obstetrics and gynecology department, and the method comprises the following steps: obtaining task data and counting dense levels, extracting action information and patient states, judging task performability, and generating personnel capability mapping in combination with a completion condition and a shift task amount; and generating an automatic allocation scheme according to the priority and the personnel number. In the invention, through multi-dimensional extraction and correlation analysis of task density, operation elements, patient states and personnel performance, accurate identification of task execution conditions and operation adaptation grade division are realized, and action sorting and matching assignment are completed in combination with personnel capabilities and task priorities. The integrating degree between tasks and personnel and the feasibility of path execution in the allocation process are enhanced, the task completion efficiency and stability are improved, and the response speed of nursing task allocation, the reasonable degree of resource utilization and the coordination level of the whole process are further promoted.

Description

Technical Field

[0001] This invention relates to the field of resource scheduling technology, and in particular to an automated method and system for allocating obstetric and gynecological nursing tasks. Background Technology

[0002] Resource scheduling technology involves management and optimization methods for the efficient allocation and coordination of manpower, equipment, and tasks under limited resource conditions. It is primarily applied in industries such as healthcare, transportation, logistics, and manufacturing. Its core aspects include task and resource matching strategies, scheduling rule setting, real-time task tracking, priority ranking, and personnel capability assessment. Through dynamic analysis of resource attributes and task requirements, it achieves orderly resource allocation and improved utilization efficiency, making it an important component of modern intelligent management systems. Traditional obstetrics and gynecology nursing task allocation refers to the process in medical institutions where, based on nursing staff shift schedules, professional skills, patient conditions, and medical orders, head nurses or nursing managers assign nursing tasks to specific nursing staff manually or through simple rule-based computer systems, using experience or pre-set paper or electronic schedules. This method typically relies on nursing task lists, duty rosters, and patient condition classification tables for decision-making and allocation.

[0003] In practice, existing technologies mainly rely on fixed shift schedules and general task lists for task allocation, failing to flexibly match tasks based on their complexity, patients' physiological state, or changes in staff capabilities. During periods of high-intensity work or when patients' conditions fluctuate drastically, uneven task load distribution, imbalanced staff allocation, and task execution interruptions often occur. This is especially true when multiple nursing actions are performed in coordination, making it difficult to achieve precise matching between tasks and manpower, leading to operational delays, repetitive work, or decreased efficiency, further affecting resource allocation efficiency and the controllability of nursing quality. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing an automated method for assigning obstetric and gynecological nursing tasks.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an automated allocation method for obstetric and gynecological nursing tasks, comprising the following steps:

[0006] S1: Obtain nursing task data for each time period, extract the total number of tasks, time consumption, and time period combination, calculate the offset between the patient's current time and the admission and postoperative registration time, and count whether multiple nursing staff perform tasks at the same time to generate a density level result.

[0007] S2: Call the task records in the density level results, break down the task actions, extract the execution time, contact area and stability requirements, and structure the information, add task and patient numbers, and generate nursing task action sorting results;

[0008] S3: Call the nursing task action sorting results, extract the patient's uterine contraction performance, lying position control, recovery days and incision site, compare with the requirements of the task action, judge the feasibility based on the touch area and control difficulty, and generate an executable status list;

[0009] S4: Call the action items marked as executable in the list of executable statuses, extract the task completion time, patient score and interruption status, and generate a task execution capability mapping table for nursing staff in combination with the number of tasks per shift;

[0010] S5: Based on the nursing staff task execution capability mapping table, according to feasibility and records, and arranged by priority and nursing staff number, generate an automated nursing task allocation scheme.

[0011] As a further aspect of the present invention, the density level results include total task count, task time distribution, time period offset analysis, and nursing staff collaboration frequency; the nursing task action organization results include action execution duration index, body contact area range, operation stability requirement level, task number label, and patient number label; the executable status list includes uterine contraction intensity level, lying posture control ability, recovery time assessment, incision site classification, and action execution adaptation level; the nursing staff task execution ability mapping table includes task completion time record, patient score data, interruption occurrence, and shift task completion amount; and the automated nursing task allocation scheme includes action priority sorting, nursing staff number identification, task sequence number, and task assignment record.

[0012] As a further aspect of the present invention, the step of obtaining the density level result is as follows:

[0013] S101: Based on the nursing task record data within each time period, extract the total number of tasks as the task frequency value, calculate the time difference between the start and end of the task, obtain the time consumed by the task, and combine the task frequency value and the task time consumption data to obtain the nursing task density.

[0014] S102: Call the nursing task density, collect the patient's current time, admission time, and postoperative registration time, calculate the time difference and use it as the patient's hospitalization duration and postoperative duration, compare it with the nursing task density value for each time period, determine the deviation range, and generate the nursing task deviation degree.

[0015] S103: Call the nursing task offset, count whether multiple nurses participate in the same nursing task in each time period, mark the cross-operation of multiple personnel, combine the nursing task offset, nursing task density value and cross-operation mark, calculate and obtain the nursing task time period density value, classify all time period density values, and obtain the density level result.

[0016] As a further aspect of the present invention, the step of obtaining the nursing task action organization result is as follows:

[0017] S201: Call the regional task records marked in the density level results, decompose each record, extract the nursing actions of each nursing task, split the action content, collect the actual start and end time of each action and calculate the time difference to obtain the action execution duration data.

[0018] S202: Call the action execution time data, collect the body area code and hand action number of each nursing action, obtain the body area range and operation stability level corresponding to the action, align and integrate the three items, calculate and obtain the action structure stability value, merge the three information items of action structure stability value, execution time and contact range, and generate a nursing action structure data table.

[0019] S203: Based on the nursing action structure data table, supplement each nursing action record with corresponding task number and patient number fields, call the task primary key and patient primary key in the task record as unique corresponding items for nested operation, complete the data field matching, and obtain the nursing task action sorting results.

[0020] As a further aspect of the present invention, the step of obtaining the executable state list is as follows:

[0021] S301: Call the action and patient correspondence information in the nursing task action data, extract four items for each patient: uterine contraction performance, degree of controllability of lying position, number of recovery days and incision site, and match and integrate them with the corresponding task number field to generate a set of patient status parameters.

[0022] S302: Based on the patient status parameter set, extract the contact points and stability requirements in the nursing actions, compare the contact points with the incision position, determine whether the contact range coincides with the surgical area, and map and compare the stability requirements with the degree of controllability of the lying position to obtain the matching status of the actions in the patient's state and generate the nursing action matching interval.

[0023] S303: Based on the nursing action matching interval, classify the actions according to whether they simultaneously meet the area and control conditions, assign executable level labels according to the matching situation, and combine the results by patient number and action number to obtain an executable status list.

[0024] As a further aspect of the present invention, the step of obtaining the nursing staff task execution ability mapping table is as follows:

[0025] S401: Call the action number marked as executable in the list of executable statuses, match the nursing staff records to extract the completion time, patient score and interruption status of the corresponding task, aggregate the three data items by action number and classify them into the nursing staff field to generate a set of nursing action performance indicators;

[0026] S402: Based on the set of nursing action performance indicators, retrieve the number of tasks completed by nursing staff in the same shift, summarize them by nursing staff number, and combine the number of tasks completed with the aforementioned performance set according to the corresponding fields to generate a task completion information group within the shift.

[0027] S403: Based on the task completion information group within the shift, each matching data item is supplemented into the corresponding task field according to the nurse's number, and the action number, task completion performance, and shift task quantity are combined and labeled to obtain the current task execution ability mapping table of the nurse.

[0028] As a further aspect of the present invention, the step of obtaining the automated nursing task allocation scheme is as follows:

[0029] S501: Call the personnel and action combination in the current task execution capability mapping table of the nursing staff, extract the executable status mark of each action, and call the task time and patient score fields in the completion record to sort all executable actions in descending order of score value and generate an action score sorting list.

[0030] S502: Based on the action scoring sorting list, extract the sorted action number and the corresponding nursing staff number, set the priority order according to the combination relationship between the score value and the task completion time, arrange all combinations according to priority, and generate the action priority allocation order.

[0031] S503: Based on the priority allocation order of the actions, assign the sorting number to the task sequence number and add an assignment identifier field. Add the above two items to the original personnel task field to obtain the nursing task automated allocation scheme.

[0032] An automated task allocation system for obstetric and gynecological nursing includes:

[0033] The task intensity assessment module collects task time and nursing staff information, calculates the time consumed by each task and classifies it into the corresponding time period, subtracts the deviation between the patient's current time and the admission and postoperative time to obtain the deviation, determines whether multiple people are performing nursing tasks at the same time in the same period, integrates the judgment conditions, and generates the intensity level result.

[0034] The action feature extraction module calls the tasks marked in the dense level results for the time period, breaks down the actions and extracts the execution time, contact part and operation stability of each item, merges the three action contents and adds the task number and patient number to generate the nursing task action sorting results;

[0035] The adaptation analysis module calls the nursing task action sorting results, extracts the corresponding patient's uterine contraction status, lying position control, recovery days and incision site, compares the action touch area with the operation requirements, determines whether the execution conditions are met, and generates an executable status list.

[0036] The capability mapping generation module calls the executable actions in the executable status list, extracts the time consumption, score and interruption information of the corresponding tasks of the nursing staff, counts the number of tasks completed in the shift and combines the data according to the action number to generate the current task execution capability mapping table of the nursing staff.

[0037] The sequence scheduling and assignment module calls the action and personnel combination in the current task execution capability mapping table of the nursing staff, and combines the action executability, time consumption and score sorting to establish task number and assignment record according to priority, and generate an automated nursing task allocation scheme.

[0038] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0039] In this invention, by extracting and analyzing the multidimensional relationships between task density, operational elements, patient status, and personnel performance, the precise identification of task execution conditions and the classification of operational suitability levels are achieved. By combining personnel capabilities and task priority, action sequencing and matching assignment are completed, enhancing the compatibility between tasks and personnel and the feasibility of path execution during the allocation process, improving the efficiency and stability of task completion, and further promoting the response speed of nursing task assignment, the rationality of resource utilization, and the coordination level of the overall process. Attached Figure Description

[0040] Figure 1 This is a flowchart of the main steps of the present invention;

[0041] Figure 2 This is a flowchart of the present invention, S1.

[0042] Figure 3 This is a flowchart of the S2 process of the present invention;

[0043] Figure 4 This is a flowchart of the S3 process of the present invention;

[0044] Figure 5 This is a flowchart of the S4 process of the present invention;

[0045] Figure 6 This is a flowchart of the S5 process of the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0047] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0048] Please see Figure 1 An automated method for assigning obstetric and gynecological nursing tasks includes the following steps:

[0049] S1: Obtain nursing task record data within each time period, extract the total number of tasks and calculate the time consumed by each task, combine the content by time period for judgment, collect the patient's current time and compare the offset after subtracting the admission and postoperative registration time, count whether multiple nursing staff jointly perform nursing tasks in the same time period, merge the above judgments, and generate the density level result.

[0050] S2: Call the task record corresponding to the marked area in the density level result, split the task action and extract the action execution time, body contact area range and hand operation stability requirements of each action, merge the three information and record each nursing action in a structured way, add task number and patient number fields to create a corresponding table, and generate nursing task action sorting results.

[0051] S3: Call up the corresponding information of actions and patients in the nursing task action sorting results, extract uterine contraction performance, lying position controllability, recovery days and incision site for each patient, compare with the operation requirements in the task action, judge the feasibility based on the touch area and control difficulty, mark the execution plan according to whether the operation conditions are met, and generate an executable status list.

[0052] S4: Call the action items marked as executable in the executable status list, extract the task completion time, patient score and interruption status by comparing with the nursing staff record, and call the number of tasks completed within the shift. Combine and summarize each matching content by action number, add it to the personnel task field, and generate a mapping table of the current task execution ability of the nursing staff.

[0053] S5: Call the personnel and action combination in the current task execution capability mapping table of nursing staff, sort all actions according to whether the action can be executed and combined with the time and score records in the personnel completion record, arrange them according to priority and nursing staff number, supplement the task sequence number and assignment record content, and generate an automated nursing task allocation scheme.

[0054] The intensity level results include total task count, task time distribution, time period offset analysis, and nursing staff collaboration frequency. The nursing task action organization results include action execution time index, body contact area range, operation stability requirement level, task number label, and patient number label. The executable status list includes uterine contraction intensity level, lying position control ability, recovery time assessment, incision site classification, and action execution adaptation level. The nursing staff task execution ability mapping table includes task completion time record, patient score data, interruption occurrence, and shift task completion volume. The automated nursing task allocation scheme includes action priority sorting, nursing staff number identification, task sequence number, and task assignment record.

[0055] Please see Figure 2 The steps to obtain the density level results are as follows:

[0056] S101: Based on the nursing task record data within each time period, extract the total number of tasks as the task frequency value, calculate the time difference between the start and end of the task, obtain the time consumed by the task, and combine the task frequency value and the task time consumption data to obtain the nursing task density.

[0057] First, the day is divided into several fixed-length time periods, for example, each time period is 30 minutes long, resulting in 48 time periods from 00:00 to 24:00. For each time period, the system queries task record data to collect information on all nursing tasks recorded within that time period. Each task record typically includes fields such as task number, task start time, task end time, task performer, and patient number. The task frequency value is calculated by determining the number of times each task number appears within that time period. For example, in the time period from 07:30 to 08:00, if task number "A" appears 3 times and "B" appears once, then the frequency value for task "A" is 3, and for task "B" it is 1. After frequency statistics are completed, the time taken for each task record is calculated by subtracting the start time from the end time, in minutes. For example, if the three records for task "A" take 12 minutes, 15 minutes, and 13 minutes respectively, then the average time for task "A" is (12+15+13) / 3 = 13.33 minutes. The time record for task "B" is 16 minutes. Combining the frequency value of each task with its average time indicates the workload of that task within that time period. For instance, if task "A" has a frequency of 3, an average time of 13.33 minutes, and a total workload of 40 minutes; and task "B" has a frequency of 1, a total time of 16 minutes, then the total time for all nursing tasks in that time period is 56 minutes. This value can serve as an indicator of the density of nursing tasks during that time period. Through the above process, the system can complete data statistics for each of the 48 time periods throughout the day, thus providing a quantitative basis for nursing task scheduling.

[0058] S102: Call the nursing task density, collect the patient's current time, admission time, and postoperative registration time, calculate the time difference and use it as the patient's hospital stay and postoperative duration, compare it with the nursing task density value for each time period, determine the deviation range, and generate the nursing task deviation degree.

[0059] After obtaining the nursing task density for each time period, the system needs to retrieve the patient's basic time information to further analyze the matching of nursing resource usage for the current patient. First, the system extracts the patient's admission time and post-operative registration time from the electronic medical record and compares them with the current system time to calculate the length of hospital stay and post-operative duration. For example, if the current system time is 10:00 AM on July 14, 2025, and a patient's admission time is 8:00 AM on July 11, 2025, then the length of hospital stay is 72 hours; if the post-operative registration time is 8:00 AM on July 13, 2025, then the length of post-operative duration is 50 hours. Next, it needs to determine whether the patient's status for the current nursing task is post-operative care or routine inpatient care. If it is post-operative care, the post-operative duration is used as the offset comparison benchmark; if it is routine care, the length of hospital stay is used. Then, considering the task type to which the nursing task belongs, the system is consulted to check the average time difference recorded for the same type of task in historical patients. For example, if the average occurrence time of a certain type of postoperative drainage task in past cases is 24 hours post-surgery, and the current patient's actual postoperative time is 50 hours, then the offset is 26 hours. This offset value represents the difference between the nursing task and the patient's current nursing timeliness, and can be used to determine whether the task was executed too early or too late. This type of offset analysis can be performed on nursing tasks for all time periods. The system ultimately generates a sequence of nursing task offsets for each time period, which is used to subsequently correlate task density and cross-task situations to form an overall evaluation value.

[0060] S103: Utilize nursing task offset to determine if multiple nurses participate in the same nursing task within each time period, marking overlapping tasks performed by multiple nurses. Combine the nursing task offset, nursing task density value, and overlapping task markers using the following formula:

[0061] ;

[0062] The system calculates and obtains the intensity value of nursing tasks during different time periods, categorizes all time period intensity values, and obtains the intensity level results.

[0063] in, This represents the intensity value of nursing tasks during specific time periods. This represents the time spent on the j-th nursing task. Represents task frequency value, Represents the total number of tasks in the current time period. This represents the difference between the current patient's hospital stay and post-operative time. This represents the average time difference for this type of task. This represents a marker indicating overlapping work among multiple nursing staff; it is positive when present and zero when absent. This is a non-zero constant used to stabilize the output of this item;

[0064] Before invoking the nursing task offset, it is necessary to first obtain the nursing task time schedule data table, which records the start time, nurse ID, and task type of each nursing task. This data is then divided into hourly time periods and tasks are categorized. Next, all tasks within each time period are traversed, and the nurse IDs involved in each task are retrieved. If multiple nurses perform the same task ID, the timestamp and participant records for that task are extracted, and a cross-task marker is set. Conversely Then, the time taken for this task With task frequency value Multiply the results, sum them up, and calculate the total number of tasks within that time period. The first part of the value is obtained by dividing the summation result by the number of tasks, and then the difference in patient hospitalization or postoperative time is calculated. And retrieve the historical average time difference for similar tasks. The difference between the two is taken, the square root is taken, and then the result is added to the previous result. Finally, the result is multiplied by the cross-operation marker value plus a small constant. (For example, take) This allows us to obtain the nursing task intensity value corresponding to that time period. In actual implementation, if statistics are collected for a ward between 08:00 and 09:00 and it is found that task A was performed by two nurses, A001 and A004, with the same recorded task ID, then an overlap in tasks is considered to exist. If the task durations are 12 minutes and 8 minutes respectively, and the task frequencies are 2 times / day and 3 times / day respectively, then the product of the two is 24 and 24, which adds up to 48. If there are a total of 5 tasks during this period, then... Assuming the patient's postoperative time is 20 hours, and the historical average time difference for the corresponding task category is 15 hours, , The cross marker is 1, and the result is calculated as follows: Then, this value is categorized in the task density classification rules. If the density is greater than 10, it is classified as "high density". Then, this period is marked as a high density operation segment.

[0065] Formula explanation and calculation:

[0066] formula:

[0067] ;

[0068] Parameter description:

[0069] : No. The time taken for each nursing task (in minutes) is obtained by comparing the start and end times in the nursing task recording system.

[0070] : No. The frequency value of each nursing task (unit: times / day) is obtained by matching the task type with the hospital's standard nursing plan.

[0071] The total number of nursing tasks within the current statistical period (unit: items) is obtained from the number of tasks within the period in the statistical task record;

[0072] The difference between the patient's current hospitalization or postoperative time (in hours) is obtained by subtracting the surgery or admission record time from the current system time.

[0073] The average time difference (in hours) for this type of nursing task in history is calculated from the average value of this task category in the historical statistics table;

[0074] Cross-task marker for nursing tasks: 1 if multiple people are involved in the same task, 0 otherwise;

[0075] Small, stable values, typically ranging from... The interval is used to ensure stable output of the formula;

[0076] This represents the sum of the products of time and frequency of all nursing tasks within the current time period, used to reflect the intensity of the task load;

[0077] Used to determine whether the patient's current nursing care tasks are fluctuating within the expected time frame;

[0078] The offset is standardized so that it has the same dimension when superimposed with the preceding term.

[0079] The numerical substitution and calculation process is as follows:

[0080] Assumption:

[0081] Task 1: minute, times / day;

[0082] Task 2: minute, times / day;

[0083] , Hour, Hour;

[0084] ,

[0085] Then we have:

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] Explanation of calculation results:

[0093] The results indicate that the intensity value of the nursing task during this period was approximately 11.95. According to the system's intensity grading standard definition: 0–5: low density, 5–10: medium density, 10: high density.

[0094] If this value falls into the high-density level, it indicates that there is a concentration of resources and frequent overlapping of tasks in the nursing assignments during this period.

[0095] Table example:

[0096] Table 1 Nursing Task Parameter Values ​​Table

[0097] Task number Time taken (minutes) Frequency (times / day) Any two people participate Time difference (hours) Average time difference (hours) 1 12 2 yes 20 15 2 8 3 yes - -

[0098] Table 1 lists the parameter data for the two nursing tasks selected in actual operation, which have been used in the aforementioned formula calculation.

[0099] Explanation of the formula's innovations:

[0100] The advantage of the formula is that it expresses the task density by weighted summation of nursing task time and frequency. At the same time, by standardizing the time difference offset and combining it with the product of cross-task markers, it comprehensively reflects the rationality of nursing task distribution and the degree of manpower overlap, so that the density assessment results have multi-dimensional quantitative characteristics, which is conducive to subsequent time period classification and resource reallocation.

[0101] Please see Figure 3 The steps for obtaining the results of the nursing task action organization are as follows:

[0102] S201: Call the regional task records marked in the density level results, decompose each record, extract the nursing actions of each nursing task, split the action content, collect the actual start and end time of each action and calculate the time difference to obtain the action execution duration data.

[0103] First, all task data for areas with a density level of "high" is read. After extracting the task list using the nursing task number field, each task record is processed item by item. The action chain information contained in the task field is broken down into independent nursing action nodes, and a mapping relationship is established with the original task number. Then, for each nursing action node, its execution record data is read, and the start and end time fields are extracted. These two times are then converted to minute-based timestamps. For example, a start time "08:00" is converted to 480 minutes, and an end time "08:03" is converted to 483 minutes, with a time difference of 3 minutes (180 seconds). This time difference is recorded as the execution duration of the action. If the start time is later than the end time, it is considered a cross-day execution, and a correction is performed after 24 hours. For example, if the start time is "23:55", the result is... If the end time is "00:05", it will be converted to 1435 minutes and 5 minutes, then corrected to 1435 and 1465, with a difference of 30 minutes, or 1800 seconds. Repeat this process to process all action nodes, and summarize and organize the execution duration, nursing action number, assigned task number, and executor number of each action to form a structured "action execution record set". This record set serves as the basis for subsequent action structure evaluation. At the same time, if the action execution time field is missing during the data extraction process, it will be marked as uncalcifiable and skipped until the information is supplemented and then reintroduced into the processing flow. Each record in this execution duration dataset must include the action number, execution start time, execution end time, and the calculated duration value in seconds, and will be automatically synchronized to the nursing action structure data table every time the data is updated to complete this step.

[0104] S202: Retrieve action execution time data, collect the body area code and hand action number contacted by each nursing action, obtain the corresponding body area range and operational stability level, align and integrate these three items using the following formula:

[0105] ;

[0106] The motion structure stability value is obtained through calculation. The three pieces of information, namely motion structure stability value, execution time, and contact range, are merged to generate a nursing motion structure data table.

[0107] in, This represents the stability value of the nursing action structure. Represents the area of ​​body contact. This represents the total execution time of the action. This represents the level of hand operation stability. This represents the set of constraint offset values ​​for the k-th auxiliary constraint factor involved in the action. For limiting factor weights, This is the baseline level value for the factor;

[0108] In the process of retrieving action execution time data, the start and end times of each action in the nursing record are first extracted, and the difference is calculated to obtain the total execution time. For example, if Nurse A is turning a patient over, and the record shows a start time of 08:05:00 and an end time of 08:06:30, then the execution time is 90 seconds, or 1.5 minutes. The process then proceeds to the second data collection step: for each action, the code of the body area touched is obtained, and the specific body area area is converted using a code dictionary. For example, if the code is B03, the system sets the corresponding area as the "back area," with a standard area of ​​0.42m². The third step is to collect hand movement numbers and call the standard database to map the numbers to the operation stability level. If the number is H07, the corresponding stability level is 4, with a level range of 1–5, where 1 represents completely unstable and 5 represents extremely high stability. Then, a set of auxiliary constraint factors related to the action is called, with each constraint factor having a weight. Compared with the benchmark level value If an action involves two limiting factors, Z1 and Z2, which are the height of the nursing bed and the patient's cooperation, respectively, and the height of the nursing bed is set to 110cm, the corresponding weights are... benchmark value The patient's cooperation level was assessed as "good," which was then converted to... benchmark value Then the set of restricted offset values ​​is Then the area value and Multiplication, that is The product is Then divide it by the sum of hand stability and limit offset values. The final result is:

[0109] ;

[0110] The results are used to construct an action structure data table and further analyze it in conjunction with execution time and contact range.

[0111] The formula explanation and calculation process are as follows:

[0112] The formula is:

[0113] ;

[0114] The parameter explanation and acquisition process are as follows:

[0115] The area of ​​the body contact corresponding to the nursing action (unit: m²) is obtained by looking up the area of ​​the corresponding area of ​​the action code in a table;

[0116] Total execution time of the action (unit: minutes), calculated from the difference between the start time and the end time of the action;

[0117] : Hand operation stability level, with a value range of 1–5, and the level is defined by looking up a table based on the action number;

[0118] : Represents the set of constraint offset values ​​of all constraint factors involved in the action. It is calculated as the sum of the weights of each factor minus the baseline level value. k is the index variable for traversing all auxiliary constraint factors.

[0119] The multiplication sign indicates the product of the area of ​​the region and the square root of the execution time, with dimensions of... ;

[0120] : Represents the square root operation of time, used to compress the offset caused by high time values;

[0121] Parameter assignment and calculation logic:

[0122] ;

[0123] ;

[0124] ;

[0125] ;

[0126] ;

[0127] ;

[0128] ;

[0129] ;

[0130] ;

[0131] The final calculated stability value of the motion structure is as follows:

[0132] ;

[0133] The parameter value data table is shown below:

[0134] Table 2 Nursing Action Structure Parameters

[0135] Nursing Action Number Area Code Area (m²) Action duration (min) Stability level Limitation factor 1 (weight / benchmark) Limitation factor 2 (weight / benchmark) A101 B03 0.42 1.5 4 3.2 / 2.0 2.8 / 2.0

[0136] Table 2 lists the structural parameter values ​​for nursing action A101, which are used for the calculation demonstration of the aforementioned formula.

[0137] Analysis of calculation results:

[0138] The result indicates that the structural stability value of nursing action A101 is 0.08575. If the system's structural stability assessment criteria are set as follows: Low stability Medium stability High stability.

[0139] This action belongs to the medium stability level. The corresponding nursing action is in a controllable and stable state due to the combined effects of moderate body contact area, short execution time, and hand operation stability.

[0140] Explanation of the formula's innovations:

[0141] The advantage of the formula is that it reflects the intensity of the action load by multiplying the area by the square root of the execution time, and comprehensively judges the stable structural attributes in the action execution process by weighted comparison with the difference between the hand operation level and the limiting factor, thereby realizing the quantitative classification of the structure of nursing actions.

[0142] S203: Based on the nursing action structure data table, supplement each nursing action record with the corresponding task number and patient number fields, call the task primary key and patient primary key in the task record as unique corresponding items to perform nested operations, complete the data field matching, and obtain the nursing task action sorting results;

[0143] Based on the nursing action structure data table, task number and patient number fields are added to each action record. First, the task assignment record table is read according to the action number, and the corresponding task primary key field is found. For example, if action A001 belongs to task T1002, then T1002 is written into the task number field of A001. Next, the patient association field of task T1002 is retrieved from the task record master table. Assuming the corresponding patient number is P1009, "patient number = P1009" is added to record A001. This process is repeated for all nursing action records, constructing a field transmission chain from action number to task number and then to patient number. Each nursing action in the data record can be traced back to its corresponding task and the patient being cared for. During the field assignment process, the uniqueness and non-repetition of fields are maintained. If an action has not yet been assigned to a task primary key, or if the task primary key is not associated with a patient primary key, the action record is temporarily de-marked and pushed into the "record set to be archived". Once the task table and patient table data are synchronized and updated, the re-matching logic is automatically invoked to supplement it. Finally, in the nursing action structure data table, each record includes action number, execution duration, contact area code, operation stability level, structural stability, task number, and patient number, realizing the construction of a complete information chain from action to task and from task to patient.

[0144] Please see Figure 4 The steps to obtain the executable status list are as follows:

[0145] S301: Call the nursing task action data to identify the corresponding information between the actions and patients, extract four items for each patient: uterine contraction performance, controllability of lying position, number of recovery days, and incision site, and match and integrate them with the corresponding task number field to generate a set of patient status parameters.

[0146] First, based on the nursing task action record, each nursing action is associated with the patient ID field. The corresponding basic data items for each patient are then located. The patient ID field is used to index four parameter fields: uterine contraction performance, controllability of lying position, recovery days, and incision site. During the extraction process, uterine contraction performance is converted into a quantitative score of 0 to 10. This score is derived from the timed uterine contraction frequency monitoring data in the nursing record. The specific score calculation is based on the number of contractions per 10 minutes and the duration of each contraction. For example, if a patient has 5 contractions within 10 minutes, each lasting approximately 30 seconds, the corresponding score is 5 points, falling into the moderate uterine contraction range. The score range is set as follows: 0–3 for “no contractions,” 4–6 for “moderate contractions,” and 7–10 for “frequent contractions.” This range is based on the clinical data of 100 parturient women in a certain hospital, statistically analyzing the range of contraction frequencies. Controllability of lying position is based on daily body movement records, with the frequency of body movement within 24 hours calculated... Hourly statistics show that if the total number of body movements is 48, averaging 2 times per hour, it is classified as "lowly controllable". The threshold is set as follows: 0-2 times per hour for low controllability, 3-5 times for medium controllability, and more than 6 times per hour for high controllability. This threshold is derived from the controllability distribution of bedridden patients recovering within 12 hours after surgery based on clinical monitoring records. The recovery days are obtained by subtracting the surgery completion time field in the electronic medical record from the current system time. For example, if the current time is July 14 and the surgery time is July 10, the recovery days are 4 days. The incision site information is directly extracted from the "surgical area location" field of the structured medical record data. For example, the standard code for "pubic symphysis incision" is A06. Finally, the above four pieces of information are bound and integrated with the nursing task action number field into a record. For example, patient P135 corresponds to task T201, with a uterine contraction score of 4, controllable lying position (medium controllability), recovery days of 4 days, and incision site A06. Finally, a complete set of status parameters is constructed.

[0147] S302: Based on the patient status parameter set, extract the contact points and stability requirements in nursing actions, compare the contact points with the incision location, determine whether the contact range coincides with the surgical area, and map and compare the stability requirements with the degree of controllability of the lying position to obtain the matching status of the actions in the patient's status and generate the nursing action matching interval.

[0148] After reading the patient's status parameter set, the contact site code and stability level field corresponding to each action in the nursing task action record are extracted sequentially. The contact site code uses a three-digit code identifier, which corresponds to the surgical area code in the medical record. The codes are directly compared to determine whether they are consistent or in the same area mapping relationship. If they are completely consistent or mapped to the same anatomical area in the coding classification structure (e.g., A05 and A06 both belong to the abdominopelvic region), it is judged as "surgical area overlap"; otherwise, it is "non-overlapping". Taking patient P135 as an example, if the contact site code of nursing task T201 is A06, which is the same as the incision code, the surgical area overlap is judged as 1. The stability level field uses integers from 1 to 5 to represent the degree of stability requirement of the action on the operating environment, with 1 being the lowest and 5 being the highest. The stability level is mapped to the degree of controllability of the lying posture. For example, the stability level is... Level 5 allows only "highly controllable" patients to perform the action; Level 4 allows "medium controllable" and above; Level 1 allows all levels to perform the action. This mapping logic is based on the statistical relationship between the failure rate of the action recorded by the nurse during the on-site execution and the patient's control. The threshold logic is set as follows: When the stability level is 5, the failure rate exceeds 75% under low controllability conditions, so the threshold is set to "highly controllable"; the failure rate at Level 4 is about 52%, so the threshold is set to "medium controllable"; the failure rate below Level 3 is less than 20%, allowing low controllability to participate. In the final judgment, if the patient's current lying position is "medium controllable" and the action level is 4, the match is successful; otherwise, it fails. The final output is whether each action is successfully matched in the patient's current state. For example, the result of patient P135 task T201 is: surgical area overlap is 1, stability match is 1, and overall match is a complete match.

[0149] S303: Based on the nursing action matching interval, the action is judged and classified according to whether the area and control conditions are met at the same time. An executable level label is assigned according to the matching situation. The results are combined by patient number and action number to obtain an executable status list.

[0150] Based on the action matching results obtained in the previous step, conditional judgment and classification processing is performed. The system constructs a Boolean judgment structure according to two dimensions: whether the contact sites overlap and whether the stability and controllability meet the standards. These are denoted as surgical area matching marker and controllable matching marker, with values ​​of 0 or 1. The two items are summed to obtain the total matching level score. The classification thresholds are set as follows: if the total score is 2, it is marked as "fully executable"; if the total score is 1, it is marked as "restricted executable"; and if the total score is 0, it is marked as "non-executable". This scoring standard is set based on nursing safety operation requirements. The threshold setting refers to the minimum tolerance limit for execution success rate in the hospital's nursing quality control center standard, which is set to allow the action to be retained even if one item is matched, but an alert is required. Note that if none of the above matches, the task operation must be removed. For example, if patient P135 scores 2 in matching nursing task T201, then record "P135_T201: Fully executable". If the contact site of nursing task T205 is B02 (back) and does not match the incision site A06, the surgical area match is 0, but its stability level is only 2, and P135 is moderately controllable, so the stability match is 1, then the total score is 1, and it is marked as "Restricted executable". The final output is a status list set "P135_T201: Fully executable, P135_T205: Restricted executable". This list records the adaptation status of each patient to each nursing task action at the current time.

[0151] Please see Figure 5 The steps to obtain the nursing staff task execution ability mapping table are as follows:

[0152] S401: Call the action number marked as executable in the list of executable statuses, match the nursing staff records to extract the completion time, patient score and interruption status of the corresponding task, aggregate the three data items by action number and classify them into the nursing staff field to generate a set of nursing action performance indicators;

[0153] When extracting action numbers marked "executable" from the executable status list, it is necessary to first search the action number field of all records with the status "executable" in the execution result table. Then, iterate through the list of this field, and find the corresponding nursing task execution record for each action number. Establish a one-to-many mapping relationship between actions and nursing staff through the nursing staff number field in the record. Subsequently, extract the completion time field from each record and perform standardization processing, that is, obtain the net execution time by the difference between the task start time and end time. If the action record has a "pause" field, the time period of the interruption needs to be deducted. For example, if the start time of task T415 is 08:10 and the end time is 08:35, and the record interruption lasts for 5 minutes, then the completion time is 20 minutes. In addition, retrieve the patient score corresponding to the task from the nursing evaluation module. The score range is 1-10 points. Divide the score into three levels according to the set threshold: 1-3 is low. The ratings are 4-7 for medium and 8-10 for high. This rating range is derived from the statistical analysis of 1000 task rating data points, divided into three levels with a median of 5 and two units added or subtracted. The "Interruption Status" field is also read; if the record is marked "Y", the interruption value is set to 1; otherwise, it is 0. After extracting these three data points, they are aggregated by action number. Each action number may contain multiple nurses, who need to be further categorized and assigned to individual nurses based on their individual numbers, forming a performance indicator set for each nurse. For example, if nurse N132 completes tasks T415 and T420 during her shift, with completion times of 20 minutes and 18 minutes respectively, patient ratings of 9 and 7, and no interruptions, the corresponding performance records are {T415: 20, high score, no interruption; T420: 18, medium score, no interruption}. This set of records constitutes the performance indicator set for nurse N132.

[0154] S402: Based on the set of nursing action performance indicators, retrieve the number of tasks completed by nursing staff in the same shift, summarize them by nursing staff number, and combine the number of tasks completed with the aforementioned performance set according to the corresponding fields to generate a task completion information group within the shift.

[0155] Based on the aforementioned set of nursing action performance indicators, the current shift number field is retrieved from the nursing shift record table. Task execution records are filtered by shift number and aggregated by nurse staff number to calculate the number of tasks completed by each person within that shift. The shift time period is set to 8 hours, such as morning shift 07:00–15:00, afternoon shift 15:00–23:00, and night shift 23:00–07:00. Each shift must complete at least 5 tasks to be statistically significant. This threshold is determined by the daily average task volume fluctuation data. Referring to the total number of nursing shift tasks executed over the past 60 days and calculating the standard deviation, the average task volume is set at 12 tasks, and the standard deviation is approximately 3.1. Therefore, the minimum threshold of 5 tasks is taken as the result of the average minus twice the standard deviation. After excluding the interference of extreme workload records, the task completion number is then calculated by nurse staff number. The nurse's ID is included in the individual field and combined with its performance set. The integration method is to use the nurse's ID as the connecting key to combine its task quantity field with the three fields of action number, completion time, rating level, and interruption status from all performance data. Each nurse corresponds to multiple action number entries, and each action record has a task quantity field to facilitate the subsequent determination of the relationship between single actions and overall workload. For example, if nurse N132 completed 12 tasks during the 07:00–15:00 shift, its performance set already includes two tasks, T415 and T420. After integration, the information group format is {T415: 20 minutes, high rating, no interruption, total number of tasks 12; T420: 18 minutes, medium rating, no interruption, total number of tasks 12}, which constitutes the task completion information group within the complete shift.

[0156] S403: Based on the task completion information group within the shift, each matching data item is supplemented into the corresponding task field according to the nurse's number, and the action number, task completion performance and shift task quantity are combined and labeled to obtain the current task execution ability mapping table of the nurse.

[0157] After reading the task completion information of nursing staff, the system sequentially completes the corresponding fields in the original task execution table for each nurse according to the action number. The supplementary fields include the completion time, rating level, interruption flag, and total number of tasks within the shift for each action record. These fields are then categorized and labeled according to standard logic. The combination method is to construct a "task execution ability identifier string" by concatenating five fields. The completion time is categorized according to a range standard: less than 15 minutes is "fast," 15–20 minutes is "moderate," and more than 20 minutes is "slow." This classification standard is based on the median and distribution of completion times from 1200 task records. The rating level uses the previously mentioned low / medium / high rating labels, and the interruption flag is uniformly "interrupted" or "completed." The number of tasks is categorized according to the previously set task volume threshold. The records are categorized as "Low Load (5–8)", "Medium Load (9–14)", and "High Load (15 and above)". For example, if nurse N132 completes task T415 in 20 minutes, gets a score of 9, has 0 interruptions, and completes 12 tasks, the record will be labeled "T415-Moderate-High Score-Completed-Medium Load". Another task T420 takes 18 minutes to complete, gets a score of 7, and has 0 interruptions, so it will be labeled "T420-Moderate-Medium Score-Completed-Medium Load". Finally, all records of this type are aggregated by nurse number to form a mapping table. Each row corresponds to one nurse, and each column is a task performance identifier string under different action numbers, which constitutes a nurse task execution capability mapping table for subsequent scheduling strategy reference or capability assessment display.

[0158] Please see Figure 6 The steps to obtain the automated nursing task allocation scheme are as follows:

[0159] S501: Call the personnel and action combination in the current task execution capability mapping table of nursing staff, extract the executable status flag of each action, and call the task time and patient score fields in the completion record. Sort all executable actions in descending order of score value and generate an action score sorting list.

[0160] After accessing the personnel and action combinations in the current task execution capability mapping table for nursing staff, the system first reads the action number bound to each combination record and extracts the executable status flag field of the corresponding nursing task through an index. Only actions with the status "executable" are retained. Next, the system enters the task completion record table, retrieving the completion records under each action number and extracting the task time field and patient rating field. The task time is calculated from the start and end times and expressed in minutes in the record. The rating is an integer value ranging from 1 to 10. After reading the completion records, all records are grouped by action number and sorted within each group by the rating field in descending order, meaning the higher the rating, the higher the ranking. For example, nursing staff N042 has three records for action T601 with ratings of 9, 7, and 8 respectively. The sorting result is 9 > 8 > 7, corresponding to task times of 18, 20, and 16 minutes, respectively. After grouping and sorting, all sorted records are output according to nurse number, action number, and score to form a sorted list. During this process, the task time field in each record is retained for the next priority combination processing. The scoring sorting interval division standard is 10–8 as "high interval", 7–5 as "medium interval", and 4–1 as "low interval". This interval division is determined by the 75th percentile of the in-hospital service evaluation scale as 8 points and the 50th percentile as 6 points. Finally, action score sorting lists such as {N042_T601: score 9, time 18}, {N042_T601: score 8, time 16}, and {N042_T601: score 7, time 20} are generated.

[0161] S502: Based on the action score sorting list, extract the sorted action number and the corresponding nursing staff number, set the priority order according to the combination relationship between the score value and the task completion time, arrange all combinations according to priority, and generate the action priority allocation order.

[0162] After obtaining the sorted list of action scores, the score value of each record in the list is combined with the corresponding task completion time to determine a priority scoring mechanism. First, the scoring threshold levels are set as follows: scores of 8–10 are priority level A, 5–7 are level B, and 1–4 are level C. The completion time priority is set as follows: ≤15 minutes is "fast", 16–20 minutes is "medium", and >20 minutes is "slow". Combining these two judgment logics, nine priority categories are set, with A+fast being the highest priority (level 1) and C+slow being the lowest priority (level 9). The remaining combinations are arranged sequentially. The priority setting is based on the weighting of the inverse influence of scores and time on work quality in actual nursing data, with scores accounting for 70% and completion time accounting for 40%. The weighting is 30%. The primary order is set by the scoring tiers, and the secondary order is set by the duration tiers. The priority level is clearly identified by the sorting number. For example, a record with a score of 9 and a time of 14 minutes is classified as Grade A+ Fast, corresponding to priority number 1; another record with a score of 7 and a time of 16 minutes is classified as Grade B+ Medium, corresponding to priority number 5, and so on. After the priority judgment is completed, all combinations are re-sorted to construct a priority allocation order list for actions. Each record is recorded in the form of "Nursing Staff Number_Action Number_Priority Number" and arranged in ascending order of priority number, such as N042_T601_1, N056_T602_2, N088_T603_3, forming a complete priority allocation order for actions.

[0163] S503: Based on the priority of action allocation, assign the sorting number to the task sequence number and add an assignment identifier field. Add the above two items to the original personnel task field to obtain the nursing task automation allocation scheme.

[0164] Based on the above priority allocation order of actions, the system reads the sorted records one by one, assigns a sequence number to each record as the task sequence number, starting from 1 and increasing in the sort order. An assignment identifier field is added to the original task record table, set as a boolean or string field, where "Y" indicates assigned and "N" indicates unassigned. Simultaneously, a task sequence number field is added to the task field, and the above assignment results are written to the corresponding record combining the nursing staff and action number. For example, if the first position in the sorted list is N042_T601, it is assigned sequence number 1, and the assignment identifier is set to "Y". The original record table is then matched with the N042 and T601 fields, and "sequence number = 1" and "assignment identifier = Y" are entered. After completion, the next record N056_T602 is read, assigned sequence number 2, and written to the field. This process is repeated throughout the priority allocation order list until all executable tasks are assigned sequence numbers and assignment identifiers, resulting in a complete automated nursing task allocation scheme. Each task record is bound to a sequence number and assignment status, forming a complete task scheduling execution table.

[0165] An automated task allocation system for obstetric and gynecological nursing includes:

[0166] The task intensity assessment module collects task time and nursing staff information, calculates the time consumed by each task and classifies it into the corresponding time period, calculates the deviation between the patient's current time and the admission and postoperative time, determines whether multiple people are performing nursing tasks at the same time in the same period, integrates the judgment conditions, and generates the intensity level result.

[0167] The action feature extraction module calls the tasks marked in the dense level results for the time period, breaks down the actions and extracts the execution time, contact area and operation stability of each item, merges the three action contents and adds the task number and patient number to generate the nursing task action sorting results;

[0168] The adaptation analysis module calls the nursing task action sorting results, extracts the corresponding patient's uterine contraction status, lying position control, recovery days and incision site, compares the action touch area with the operation requirements, determines whether the execution conditions are met, and generates an executable status list.

[0169] The capability mapping generation module calls the executable actions in the executable status list, extracts the time, score and interruption information of the corresponding tasks of the nurses, counts the number of tasks completed in the shift and combines the data according to the action number to generate the current task execution capability mapping table of the nurses.

[0170] The sequence scheduling and assignment module calls the action and personnel combination in the current task execution capability mapping table of nursing staff, combines the executability of the action, the time consumption and the score sorting, establishes task number and assignment record according to priority, and generates an automated nursing task allocation scheme.

[0171] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for automating the allocation of obstetric and gynecological nursing tasks, characterized in that, Includes the following steps: S1: Obtain nursing task data for each time period, extract the total number of tasks, time consumption, and time period combination, calculate the offset between the patient's current time and the admission and postoperative registration time, and count whether multiple nursing staff perform tasks at the same time to generate a density level result. S2: Call the task records in the density level results, break down the task actions, extract the execution time, contact area and stability requirements, and structure the information, add task and patient numbers, and generate nursing task action sorting results; S3: Call the nursing task action sorting results, extract the patient's uterine contraction performance, lying position control, recovery days and incision site, compare with the requirements of the task action, judge the feasibility based on the touch area and control difficulty, and generate an executable status list; S4: Call the action items marked as executable in the list of executable statuses, extract the task completion time, patient score and interruption status, and generate a task execution capability mapping table for nursing staff in combination with the number of tasks per shift; S5: Based on the nursing staff task execution capability mapping table, according to feasibility and records, and arranged by priority and nursing staff number, generate an automated nursing task allocation scheme.

2. The automated allocation method for obstetric and gynecological nursing tasks according to claim 1, characterized in that, The density level results include total task count, task time distribution, time period offset analysis, and nursing staff collaboration frequency. The nursing task action organization results include action execution time index, body contact area range, operation stability requirement level, task number label, and patient number label. The executable status list includes uterine contraction intensity level, lying position control ability, recovery time assessment, incision site classification, and action execution adaptation level. The nursing staff task execution ability mapping table includes task completion time record, patient rating data, interruption occurrence, and shift task completion volume. The automated nursing task allocation scheme includes action priority sorting, nursing staff number identification, task sequence number, and task assignment record.

3. The automated allocation method for obstetric and gynecological nursing tasks according to claim 2, characterized in that, The steps for obtaining the density level result are as follows: S101: Based on the nursing task record data within each time period, extract the total number of tasks as the task frequency value, calculate the time difference between the start and end of the task, obtain the time consumed by the task, and combine the task frequency value and the task time consumption data to obtain the nursing task density. S102: Call the nursing task density, collect the patient's current time, admission time, and postoperative registration time, calculate the time difference and use it as the patient's hospitalization duration and postoperative duration, compare it with the nursing task density value for each time period, determine the deviation range, and generate the nursing task deviation degree. S103: Call the nursing task offset, count whether multiple nurses participate in the same nursing task in each time period, mark the cross-operation of multiple personnel, combine the nursing task offset, nursing task density value and cross-operation mark, calculate and obtain the nursing task time period density value, classify all time period density values, and obtain the density level result.

4. The automated allocation method for obstetric and gynecological nursing tasks according to claim 3, characterized in that, The steps for obtaining the results of the nursing task action organization are as follows: S201: Call the regional task records marked in the density level results, decompose each record, extract the nursing actions of each nursing task, split the action content, collect the actual start and end time of each action and calculate the time difference to obtain the action execution duration data. S202: Call the action execution time data, collect the body area code and hand action number of each nursing action, obtain the body area range and operation stability level corresponding to the action, align and integrate the three items, calculate and obtain the action structure stability value, merge the three information items of action structure stability value, execution time and contact range, and generate a nursing action structure data table. S203: Based on the nursing action structure data table, supplement each nursing action record with corresponding task number and patient number fields, call the task primary key and patient primary key in the task record as unique corresponding items for nested operation, complete the data field matching, and obtain the nursing task action sorting results.

5. The automated allocation method for obstetric and gynecological nursing tasks according to claim 4, characterized in that, The steps for obtaining the executable state list are as follows: S301: Call the action and patient correspondence information in the nursing task action data, extract four items for each patient: uterine contraction performance, degree of controllability of lying position, number of recovery days and incision site, and match and integrate them with the corresponding task number field to generate a set of patient status parameters. S302: Based on the patient status parameter set, extract the contact points and stability requirements in the nursing actions, compare the contact points with the incision position, determine whether the contact range coincides with the surgical area, and map and compare the stability requirements with the degree of controllability of the lying position to obtain the matching status of the actions in the patient's state and generate the nursing action matching interval. S303: Based on the nursing action matching interval, classify the actions according to whether they simultaneously meet the area and control conditions, assign executable level labels according to the matching situation, and combine the results by patient number and action number to obtain an executable status list.

6. The automated allocation method for obstetric and gynecological nursing tasks according to claim 5, characterized in that, The steps for obtaining the nursing staff task execution ability mapping table are as follows: S401: Call the action number marked as executable in the list of executable statuses, match the nursing staff records to extract the completion time, patient score and interruption status of the corresponding task, aggregate the three data items by action number and classify them into the nursing staff field to generate a set of nursing action performance indicators; S402: Based on the set of nursing action performance indicators, retrieve the number of tasks completed by nursing staff in the same shift, summarize them by nursing staff number, and combine the number of tasks completed with the aforementioned performance set according to the corresponding fields to generate a task completion information group within the shift. S403: Based on the task completion information group within the shift, each matching data item is supplemented into the corresponding task field according to the nurse's number, and the action number, task completion performance, and shift task quantity are combined and labeled to obtain the current task execution ability mapping table of the nurse.

7. The automated allocation method for obstetric and gynecological nursing tasks according to claim 6, characterized in that, The steps for obtaining the automated nursing task allocation scheme are as follows: S501: Call the personnel and action combination in the current task execution capability mapping table of the nursing staff, extract the executable status mark of each action, and call the task time and patient score fields in the completion record to sort all executable actions in descending order of score value and generate an action score sorting list. S502: Based on the action scoring sorting list, extract the sorted action number and the corresponding nursing staff number, set the priority order according to the combination relationship between the score value and the task completion time, arrange all combinations according to priority, and generate the action priority allocation order. S503: Based on the priority allocation order of the actions, assign the sorting number to the task sequence number and add an assignment identifier field. Add the above two items to the original personnel task field to obtain the nursing task automated allocation scheme.

8. An automated task allocation system for obstetrics and gynecology nursing, characterized in that, The system is used to execute the automated assignment method for obstetric and gynecological nursing tasks according to any one of claims 1-7, including: The task intensity assessment module collects task time and nursing staff information, calculates the time consumed by each task and classifies it into the corresponding time period, subtracts the deviation between the patient's current time and the admission and postoperative time, determines whether multiple people are performing nursing tasks at the same time, integrates the judgment conditions, and generates the intensity level result. The action feature extraction module calls the tasks marked in the dense level results for the time period, breaks down the actions and extracts the execution time, contact part and operation stability of each item, merges the three action contents and adds the task number and patient number to generate the nursing task action sorting results; The adaptation analysis module calls the nursing task action sorting results, extracts the corresponding patient's uterine contraction status, lying position control, recovery days and incision site, compares the action touch area with the operation requirements, determines whether the execution conditions are met, and generates an executable status list. The capability mapping generation module calls the executable actions in the executable status list, extracts the time consumption, score and interruption information of the corresponding tasks of the nursing staff, counts the number of tasks completed in the shift and combines the data according to the action number to generate the current task execution capability mapping table of the nursing staff. The sequence scheduling and assignment module calls the action and personnel combination in the current task execution capability mapping table of the nursing staff, and combines the action executability, time consumption and score sorting to establish task number and assignment record according to priority, and generate an automated nursing task allocation scheme.

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