Medical staff automatic scheduling system and method based on departments

Abstract

The invention discloses a medical staff automatic scheduling system and method based on departments, and relates to the technical field of intelligent scheduling, and the system comprises a pre-scheduling module, a scheme evaluation module, an emergency response module and a temporary adjustment module which are operated in sequence; the technical key points are as follows: the system can perform secondary priority ranking on vacant nurses according to information of response nurses and basic information; according to the method, the qualification quantized value library is established, the qualification grades of nurses are quantized, the proportion of the marked times in the fixed period is combined, the priority index of each nurse meeting the conditions is generated through the index calculation function model, and refined sorting of the nurse priorities is achieved; the scheme not only considers the qualification level of the nurse, but also fully considers the response speed and enthusiasm of the nurse to the emergency state, so that the scheduling of the nurse can be more scientifically and reasonably arranged, and the problems of unreasonable priority ranking and low scheduling efficiency in hospital scheduling management are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent scheduling, and in particular to a department-based automatic scheduling system and method for medical staff. Background Art

[0002] Intelligent scheduling is a process that uses modern information technology and algorithms to automatically or semi-automatically manage the scientific and reasonable scheduling of nurses and other medical personnel according to the actual needs of hospitals or medical institutions. It takes into account a variety of factors and uses a variety of models or algorithms to realize automatic scheduling of nurses in each department. The following contents may exist when scheduling, for example: 1. If there is a temporary vacation tomorrow, there will be a text message reminder if there is a change in the substitute; 2. There are statistics on work, vacation and night shift time every year; 3. There are statistical times for various leaves such as maternity leave, marriage leave, work leave, personal leave, etc.; 4. If the daily scheduling is unreasonable, the system will give a prompt to avoid missing a shift; 5. The scheduling system will generate a schedule with one click. The working hours requirements of each department are different. By adjusting the mode, the time of each shift staff is specified, and the name and hierarchical level are entered to realize one-click scheduling; 6. If you encounter a situation where you need to work overtime for a few hours, you can record it in the stored leave.

[0003] The existing authorization announcement number is CN118230923B, and the technical solution provided in the system and method for intelligent obstetric scheduling based on role collaboration includes: a personnel management module is used to record the basic information, qualifications, skills and experience of obstetric personnel and evaluate personnel capabilities; the role management module is used to define and manage the permissions and access levels of different user roles in the system, and determine the number and type of roles required for daily scheduling; the scheduling rule management module is used to define the rules and constraints of obstetric scheduling; the scheduling generation module is used to automatically generate reasonable obstetric scheduling, and allow supervisors or administrators to manually adjust the scheduling to meet special needs; the present invention can improve the work efficiency of medical staff, optimize resource utilization, improve patient care experience, and ensure the work-life balance of medical staff; although the solution also provides solutions to special situations, the special situations covered are mostly scheduling conflicts and personnel preference issues, and do not involve emergency response solutions for staff shortages; Another document with the authorization announcement number CN111883241B points out that although the scheme provides a scheme for scheduling shifts based on priority, the priority is determined based on the radiation dose, and the priority cannot be adjusted twice or multiple times. In combination with the above documents and existing technologies, when traditionally scheduling nurses in various departments within a hospital institution, although genetic algorithms can be used to generate multiple candidate scheduling plans, human reference or selection is still required when finally determining the required scheduling plan. At the same time, the established scheduling plan cannot cope with sudden surgical arrangements, and it is usually necessary to actively notify the staff on leave or dispatch idle nurses from other departments. The priority of the notification order is often adjusted based on a single factor. For example, the higher the qualification of the nurse, the higher the priority. However, there are some nurses with higher qualifications but slower response speeds. At the same time, some nurses with lower priority rankings can respond actively. This results in unreasonable priority ranking and low scheduling efficiency in the existing hospital scheduling management system. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the deficiencies in the prior art, the present invention provides a department-based automatic scheduling system and method for medical staff, and solves the problems raised in the background technology by running the automatic scheduling system.

[0005] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: A department-based automatic scheduling system and method for medical staff, the system comprising: The pre-scheduling module summarizes the work requirements of the target department and the basic information of nurses, and uses genetic algorithms to generate several candidate plans; the work requirements at least include the number of patients and the arrangement of surgery; The program evaluation module, when the nurses receive the candidate programs, builds an evaluation system engine based on the nurses' feedback data and compares the use of human resources under different candidate programs, and then comes up with a preliminary program based on the future work arrangement status of the target department; Emergency response module: when there is an emergency, the nurses on leave are prioritized and a temporary shift notification is sent. If the nurses with the highest priority do not respond within the specified time, the nurses with the lowest priority will be postponed until a nurse responds. If no nurse responds, the recruitment mechanism is triggered. The proportion of the recruitment mechanism triggered within the predetermined period is recorded simultaneously. If the proportion exceeds the expected value, the plan adjustment instruction is executed. The temporary adjustment module records and prioritizes the nurses on leave based on the information of the responding nurses and the basic information within a fixed period, and provides feedback on the ranking results.

[0006] Furthermore, the surgical schedule includes the date, time, type of surgery and the specialty of the nurse required; the basic information of the nurse includes the nurse's name, qualifications, specialty, current scheduling status and vacation plans.

[0007] Furthermore, the process of generating several shift scheduling plans using the genetic algorithm is as follows: Coding: Integer coding is adopted. Each shift scheduling plan is represented as a chromosome, and each gene on the chromosome represents the working status of a nurse during the set time period; Initial population: Randomly generate multiple shift scheduling plans as the initial population, and each plan meets the set constraints; Fitness function: Design a fitness function to score according to the quality of the shift scheduling plan and calculate the fitness of each shift scheduling plan. Among them, the quality of the shift scheduling plan includes at least the balance of nurses' workload, the satisfaction of patients' nursing needs, and the matching degree of professional skills; Selection: Adopt the roulette wheel selection strategy to select individuals with qualified fitness from the current population as the parent generation; Crossover: Perform crossover operations on the selected parent generation to generate new offspring shift scheduling plans; Mutation: Randomly mutate the offspring shift scheduling plans; Iteration: Repeat the selection, crossover, and mutation operations until the predetermined number of iterations is reached. After the iteration ends, select several shift scheduling plans from the final population as candidate plans.

[0008] Furthermore, the feedback data of nurses represents the satisfaction of nurses with each different candidate plan. If the corresponding nurse expresses satisfaction, mark the corresponding candidate plan as 1; if not satisfied, mark the corresponding candidate plan as 0; The usage of human resources is quantitatively represented by the human resource utilization rate; The calculation method of the human resource utilization rate is as follows: Human resource utilization rate = actual used human resources / total human resources × 100%.

[0009] Furthermore, the process of running the evaluation system engine is as follows: Based on the future work arrangement status in the target department and obtaining the total number of nurses in the target department, build a mathematical calculation model to generate the required human resource standard value, screen out the candidate plans corresponding to the human resource usage exceeding the human resource standard value, and based on the difference between the human resource utilization rate and the human resource standard value, as well as the cumulative value of the feedback data corresponding to each screened candidate plan, perform weighted calculation to obtain a comprehensive index, and sort it from largest to smallest to generate a ranking list. The candidate plan corresponding to the first place in this ranking list is the preliminary determined plan.

[0010] Furthermore, the future work arrangement status in the target department represents the total number of scheduled surgeries within a preset future period; When building the mathematical calculation model, the formula relied on is: ; In the formula, R_min represents the required standard value of human resources, T represents the total number of scheduled surgeries within the preset period, Nr represents the total number of nurses in the target department, and S i represents the number of nurses required for the i-th surgery.

[0011] Furthermore, the weighted calculation formula corresponding to the obtained comprehensive index is as follows: ; In the formula, x in Zb x represents the number of the candidate solution, Zb represents the comprehensive index, and R x represents the utilization rate of human resources under the candidate solution x, and Ac x represents the cumulative value of feedback data under the corresponding candidate solution. Both α and β represent weight coefficients, and α + β = 1.

[0012] Furthermore, the process of prioritizing the on - leave nurses is as follows: Obtain the type corresponding to the current emergency state, match the appropriate expertise, extract the nurses who meet both the appropriate expertise and are in the on - leave scheduling state from each nurse's basic information, and sort them from high to low according to their qualifications, and the qualifications are positively correlated with the priority; The content of the triggered recruitment mechanism is: Transfer nurses who meet both the appropriate expertise and are in the on - leave scheduling state from the whole hospital, and the response speed of the nurses is positively correlated with the call priority; After recording the proportion of triggering the recruitment mechanism within the preset period, record the number of all relevant events within the preset period, including the number of events triggering the recruitment mechanism and the number of events sending temporary scheduling notices, that is, the total number of events, and calculate the proportion value of triggering the recruitment mechanism, that is, the number of events triggering the recruitment mechanism divided by the total number of events; The content of the executed plan adjustment instruction is: Extract the candidate solution corresponding to the serial number: first + 1 from the original sorting table and use it as the initial solution after adjustment. Then continue to record the proportion of triggering the recruitment mechanism within the preset period in the next cycle. If the plan adjustment instruction is executed again, continue to use the candidate solution corresponding to the first + 2 as the initial solution after adjustment, and so on in a cycle until there is no response.

[0013] Furthermore, recording and representing according to the information of the responding nurses means: The responding nurses are marked; The process of secondary prioritization of the on - leave nurses is as follows: Establish a qualification quantitative value library, match the corresponding qualification level according to the qualifications of the nurses in the basic information, and the qualification degree is positively correlated with the qualification level; in response to the type corresponding to the current emergency status, match the appropriate expertise, extract nurses who meet the appropriate expertise and are on vacation from the basic information of each nurse, determine the qualification level of each nurse through the qualification quantitative value library, and collect and calculate the proportion of each nurse's marked times within a fixed period, build an index calculation function model to generate the priority index corresponding to each qualified nurse, and sort them from large to small according to the priority index, and the priority index is positively correlated with the priority level; Among them, when running the exponential calculation function model, the formula is based on: ; ; Among them, Rt, Mq and Td represent the proportion of the number of times marked, the number of times the corresponding nurse is marked in a fixed period and the fixed period respectively, Irt represents the priority index, Q represents the qualification level of the corresponding nurse, and k is the adjustment coefficient, and the value range is [0, 1].

[0014] A department-based automatic scheduling system and method for medical staff includes the following steps: S1. Summarize the work requirements of the target department and the basic information of nurses, and use genetic algorithms to generate several candidate solutions; the work requirements at least include the number of patients and the arrangement of surgery; S2. When the nurses receive the candidate solutions, they build an evaluation system engine based on the nurses' feedback data and compare the human resource utilization under different candidate solutions. Combined with the future work arrangement status of the target department, a preliminary solution is obtained. S3. When there is an emergency, prioritize the nurses on leave and send a temporary shift notification. If the nurses with the highest priority do not respond within the specified time, the nurses with the lowest priority will be postponed until a nurse responds. If no nurse responds, the recruitment mechanism is triggered. The proportion of the recruitment mechanism triggered within the predetermined period is recorded simultaneously. If the proportion exceeds the expected value, the plan adjustment instruction is executed. S4. Within a fixed period, record and prioritize the nurses on leave based on the information of the responding nurses and the basic information, and provide feedback on the ranking results.

[0015] (III) Beneficial effects The present invention provides a department-based automatic scheduling system and method for medical staff, which has the following beneficial effects: 1. This plan comprehensively considers the feedback data of nurses and the use of human resources under different candidate plans. By building an evaluation system engine and combining the future work arrangement status of the target department, it intelligently screens out the preliminary plan, which not only improves the efficiency of scheduling plan formulation, but also ensures the rationality of the plan in human resource allocation and the superiority of nurse satisfaction; 2. This plan can quickly prioritize nurses on leave in an emergency and send temporary scheduling notices, effectively responding to sudden surgical arrangements in departments or situations where nurses on duty are unable to continue working unexpectedly. Combined with the design of the solicitation mechanism, it further ensures timely response to emergencies; by recording the proportion of the solicitation mechanism triggered within the predetermined period and comparing it with the expected value, it can promptly discover problems in the preliminary plan, and by executing the plan adjustment instruction, the next candidate plan with the highest ranking will be used as the adjusted preliminary plan, completing the optimization and adjustment of the scheduling plan; it not only improves the hospital's ability to respond to emergencies, but also ensures the flexibility and practicality of the scheduling plan, effectively solving the technical problems of untimely emergency response and inflexible plan adjustment in hospital scheduling management; 3. This program conducts secondary priority ranking of nurses on leave based on the responding nurses’ information and basic information; By establishing a qualification quantitative value database, the qualification level of nurses is quantified, and combined with the proportion of marked times within a fixed period, the priority index of each qualified nurse is generated through an exponential calculation function model, thus realizing the refined sorting of nurse priorities; not only the qualification level of nurses is taken into account, but also the response speed and enthusiasm of nurses to emergencies, so that the nurses' shifts can be arranged more scientifically and reasonably; to a certain extent, it can provide more opportunities for nurses with a positive response attitude, and effectively solve the problems of unreasonable priority sorting and low scheduling efficiency in hospital scheduling management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a modular schematic diagram of a department-based automatic scheduling system and method for medical staff in the present invention; Figure 2 The figure is a schematic diagram of the overall process of an automatic scheduling system and method for medical staff based on departments in the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example 1: Please refer to Figure 1 , this example provides a department-based automatic scheduling system and method for medical staff; The system includes a pre-scheduling module, a plan evaluation module, a sudden response module, and a temporary adjustment module that operate in sequence; among them, for the pre-scheduling module and the plan evaluation module, they are part of the initial operation stage of the system; for the sudden response module and the temporary adjustment module, they are part of the supplement or the stage of dealing with emergencies of the system; System Overview The application scenario of this system is designed for the arrangement of internal medicine surgeries and surgical surgeries, aiming to achieve efficient and reasonable scheduling of nurse resources through intelligent algorithms and flexible response mechanisms; the system can handle the surgery arrangements known in advance, and at the same time, for sudden surgery requirements, quickly and accurately notify and arrange appropriate nurses for scheduling, and provide feedback based on the scheduling situation, so as to change the sorting of appropriate nurses, which can improve the response time to sudden surgeries to a certain extent, ensure the rationality of scheduling, and improve the response efficiency, and can make faster adjustments in the treatment of patients to ensure that patients receive comprehensive care or treatment.

[0019] Functional Module Design The pre-scheduling module summarizes the work requirements of the target department and the basic information of nurses (the data summarized here corresponds to Figure 1 the data source in), and uses a genetic algorithm to generate several candidate solutions; Among them, the work requirements at least include the number of patients and the surgery arrangement situation; In addition, it can also include the complexity of the condition; Number of patients and complexity of the condition: Obtain the number of patients in the internal medicine and surgical wards, as well as the complexity score of each patient's condition through the hospital information system (HIS); the complexity score of the condition can be determined according to the patient's diagnosis, treatment plan, and expected nursing needs; although the specific calculation method may vary from hospital to hospital and department to department, it usually involves multiple factors; in this example, the following example is used to calculate the complexity score of the condition; For example, use the relative weight of DRG (Diagnosis Related Groups) to calculate. Each DRG has a corresponding weight, which reflects its resource consumption and the complexity of the condition; the more complex the condition, the more medical resources are required, and the higher the DRG weight; the hospital can count the number or weight of each patient classified into a certain DRG, and combine the total number of cases to calculate the complexity score of the condition (such as the CMI value); Surgery arrangement situation: Obtain the date, time, type (internal medicine / surgery), and the expertise of the required nurses (i.e., the basic information of the corresponding nurses) of the surgery from the operating room management system; Basic information of nurses: Obtain the name, qualifications (such as licensed nurse, supervisor nurse, etc.), specialties (such as cardiovascular care, trauma care, etc.), current scheduling status (such as on duty, on leave, etc.) and leave plan of nurses from the human resources management system; Based on the aggregated data, use the genetic algorithm to generate multiple scheduling plans; the genetic algorithm is an optimization algorithm that simulates natural selection and genetic mechanisms and is suitable for solving complex scheduling problems; The process of using the genetic algorithm to generate several scheduling plans is as follows: Coding: Use integer coding. Each scheduling plan is represented as a chromosome, and each gene on the chromosome represents the working status of a nurse in a certain time period (such as 1 for working and 0 for resting); Initial population: Randomly generate multiple scheduling plans as the initial population, and each plan meets the set constraints (such as nurse qualifications, leave plans); Fitness function: Design a fitness function to score according to the quality of the scheduling plan (such as nurse workload balance, patient care demand satisfaction, professional skill matching degree, etc.) and calculate the fitness of each scheduling plan; Selection: Use the roulette wheel selection strategy to select individuals with qualified fitness from the current population as the parent generation; Crossover: Perform crossover operations on the selected parent generation to generate new offspring scheduling plans; among them, the crossover operation includes any one of single-point crossover and multi-point crossover; Mutation: Randomly mutate the offspring scheduling plans to increase the diversity of the population; among them, the mutation operation includes replacement of gene values and exchange of gene positions; Iteration: Repeat the selection, crossover and mutation operations until the predetermined number of iterations is reached or the fitness no longer increases significantly; After the iteration ends, select several scheduling plans from the final population as candidate plans; When designing a fitness function and calculating the fitness of each scheduling plan, the fitness function is defined as: Fit = a1 * WB + a2 * PC + a3 * SD; In the formula, Fit represents the fitness, WB, PC and SD respectively represent the nurse workload balance, patient care quality and surgical demand satisfaction, and a1, a2 and a3 are all weight coefficients, and their value ranges are all [0, 1]; Nurse workload balance: The calculation method is as follows: Calculate the total workload of each nurse: According to the scheduling plan, count the number of working hours or the number of shifts of each nurse within the scheduling period (such as one week); Calculate the standard deviation of the workload: Measure the degree of difference in workload among nurses; The smaller the standard deviation, the more balanced the workload among nurses; Normalization processing: Normalize the standard deviation of the workload; The normalization processing here is directly subtracting the ratio of the standard deviation to the maximum possible standard deviation from 1, which ensures that the value range after normalization is between [0, 1]. Formula: ; Among them, the maximum possible standard deviation is calculated under extreme circumstances (such as all work being assigned to the same nurse); Example: Suppose there are 3 nurses A, B, and C, and the total workloads within one week are 40 hours, 35 hours, and 45 hours respectively; The calculated standard deviation of the workload is 4.08 hours (assuming it is an example value and the calculated is the population standard deviation); The maximum possible standard deviation is assumed to be the standard deviation when all work is assigned to nurse A, that is, 56.57 hours; Then, WB≈0.93; Patient care quality: Calculation method: Evaluate the care quality of each nurse: It can be evaluated according to indicators such as historical data, patient satisfaction surveys, and nursing error rates; Calculate the care quality score: According to the scheduling plan, calculate the weighted sum of the quality scores of the nurses in charge of care in each time period; Normalization processing: Normalize the care quality score to make its value range between [0, 1]; The normalization processing here is directly dividing the weighted sum of the quality scores of the nurses in charge of care in each time period by the maximum quality score of the nurses in charge of care in each time period obtained by weighted calculation. Formula: ; Among them, Q is the number of time periods within the scheduling cycle, and nurse k is the weight factor corresponding to the nurse in charge in the k-th time period (reflecting the workload or importance of each time period), and the value range is greater than 0. The quality score k is the care quality score of the nurse in charge of care in the k-th time period, and the maximum single-time period quality score is the maximum possible quality score of each time period; Example: Suppose there are 3 time periods, and each time period has a corresponding care quality score (such as nurse A gets 8 points, nurse B gets 7 points, and nurse C gets 9 points). Assuming that the weight factors corresponding to the nurses in charge of each time period are 0.4, 0.3, and 0.4 in turn, then, PC≈0.90 (assuming the maximum single-time period quality score is 3 nines); Satisfaction with surgical needs: Calculation method: Statistical operation requirements: According to the operation arrangements, count the number and types of operations in each time period; Evaluate the matching degree of nurses' operation expertise: Match according to the nurses' operation expertise and operation requirements, and calculate the matching degree score; Calculate the satisfaction degree of operation requirements: Calculate the weighted sum of the satisfaction degrees of operation requirements in each time period; Normalization processing: Normalize the satisfaction degree of operation requirements so that its value range is between [0, 1]. Formula: ; Among them, M is the number of operations during the scheduling period, the operation requirement \(t\) is the weight factor of the \(t\)-th operation (reflecting the importance of operations in each time period), and the matching degree score \(t\) is the matching degree score between the \(t\)-th operation and the responsible nurse (1 for being able to match, 0 for not being able to match); Example: Suppose there are 2 operations, one internal medicine operation requires Nurse A (expertise in internal medicine), and one surgical operation requires Nurse B (expertise in surgery). Assume that the weight factors of both operations are 0.5. If the scheduling plan meets the requirements of these two operations and the matching degree scores are both 1; then, \(SD = 1\) (assuming that the maximum matching degree score in a single time period is 1). To sum up, set \(\alpha = 0.4\), \(\beta = 0.3\), \(\gamma = 0.3\), and according to the previous example, it is calculated that \(WB = 0.93\), \(PC = 0.90\), \(SD = 1\), then \(Fit = 0.4×0.93 + 0.3×0.90 + 0.3×1 = 0.942\); This fitness value indicates that the scheduling plan performs well in comprehensively considering the balance of nurses' workload, the quality of patient care, and the satisfaction degree of operation requirements. The corresponding standard of fitness is set to 0.9. Therefore, in this example, the fitness \(Fit\) is 0.942, which exceeds 0.9, so it meets the standard. Example: Suppose there is a small department with 3 nurses (A, B, C), and a schedule needs to be made for a week (7 days); Each nurse has specific expertise and vacation plans. Nurse information: A: Expertise in pediatrics, off on Saturday; B: Expertise in first aid, off on Sunday; C: No specific expertise, can work every day; Scheduling requirements: Monday: A large number of pediatric patients, need A to work; Tuesday: There is a first aid operation, need B to work; Wednesday to Friday: The number of patients is moderate, need to reasonably arrange nurse resources; Weekends: The number of patients decreases, but there are still a small number of pediatric patients, need A or C to work; Genetic algorithm scheduling process (simplified): Initial population: randomly generate multiple shift plans to ensure that A does not work on Saturday and B does not work on Sunday; Fitness function: Considers factors such as nurse expertise matching and workload balance; Selection, crossover, and mutation: iterative optimization of scheduling plans; Final solution: Choose multiple excellent scheduling solutions, such as: Plan 1: A (Monday, Wednesday, Friday, Sunday), B (Tuesday, Thursday), C (Saturday); Plan 2: A (Monday, Thursday, Saturday), B (Tuesday, Friday), C (Wednesday, Sunday); The above scheme is for reference only. The actual scheduling process may involve more complex factors, such as emergencies, etc., which need to be adjusted according to the actual situation. There are corresponding plans in the subsequent system operation.

[0020] The above technical solution effectively solves the complex and critical problem of hospital department scheduling; The scheme aggregates the work needs of the target departments and the basic information of nurses, and uses genetic algorithms to generate multiple candidate scheduling schemes, taking into full account multiple factors such as the number of patients, surgical arrangements, disease complexity, and nurses' qualifications, expertise, current scheduling status, and vacation plans. The design of the fitness function ensures the comprehensive optimization of the scheduling scheme in multiple dimensions such as the balance of nurse workload, patient care quality, and satisfaction of surgical needs. This not only improves scheduling efficiency, but also ensures that patients receive high-quality nursing services, while reasonably arranging nurses' work and rest time to avoid workload overload or waste of resources. In addition, the solution is flexible and scalable, and can be adjusted and optimized according to actual conditions to deal with emergencies or other complex factors. In short, this technical solution has successfully realized the intelligent and efficient scheduling of hospital departments, improved the utilization efficiency of medical resources, and improved the quality and level of medical services, bringing significant positive impacts to hospital management and patient care.

[0021] The program evaluation module, when the nurses receive the candidate programs, builds an evaluation system engine based on the nurses' feedback data and compares the use of human resources under different candidate programs, and then comes up with a preliminary program based on the future work arrangement status of the target department; Among them, the conditions under which the nurse receives the candidate plan are as follows: Usually, nurses need to frequently return to the nurse station when they are free or doing daily work. The nurse station will be equipped with an LED display device. When instructions or information are received, they can be displayed on the screen of the device, thereby prompting the corresponding nurses. The corresponding schedule of the candidate plan can be displayed on the screen; The feedback data of nurses indicates the satisfaction of nurses with each different candidate solution. If the corresponding nurse expresses satisfaction, the corresponding candidate solution is marked as 1; if not satisfied, the corresponding candidate solution is marked as 0. The usage of human resources is quantitatively represented by the human resource utilization rate. The human resource utilization rate refers to the ratio of the actually used human resources to the total human resources under the corresponding candidate solution. Calculation method: Human resource utilization rate = (Actually used human resources / Total human resources) × 100%. Example: Under candidate solution A, the number of nurses actually used during a certain period is 20, and the total number of nurses is 30. Then the human resource utilization rate is 20 / 30 × 100% ≈ 66.67%; under candidate solution B, the number of nurses actually used during the same period is 18, and the total number of nurses is 30. Then the human resource utilization rate is 18 / 30 × 100% = 60%. By comparison, it can be seen that the human resource utilization rate of solution A during this period is higher than that of solution B. That is, after comparing the human resource usage under different candidate solutions, the human resource usage of candidate solution A is more than that of candidate solution B. The process of running the operation evaluation system engine is as follows: Based on the future work arrangement status of the target department and obtaining the total number of nurses in the target department, a mathematical calculation model is built to generate the required human resource standard value (i.e., the lowest human resource utilization rate), screening out the candidate solutions corresponding to the human resource usage exceeding the human resource standard value, and according to the difference between the human resource utilization rate and the human resource standard value, as well as the cumulative value of the feedback data corresponding to each screened candidate solution, the comprehensive index obtained after weighted calculation is sorted from largest to smallest to generate a ranking list. The candidate solution corresponding to the first place in this ranking list is the preliminary determined solution. Among them, the future work arrangement status of the target department indicates the total number of scheduled surgeries within a future preset period (usually set as one week). Therefore, the formula based on which the mathematical calculation model is built is: ; In the formula, R_min represents the required human resource standard value, T represents the total number of scheduled surgeries within the preset period, Nr represents the total number of nurses in the target department, and S i represents the number of nurses required for the i-th surgery (this value may vary due to factors such as the type and complexity of the surgery and is the pre-set demand). Logical summary: The required standard value of human resources, that is, the minimum human resource utilization rate R_min, can be defined as the ratio of the minimum number of nurses required to meet all surgical care needs to the total number of nurses. To simplify the calculation, by assuming that all nurses have similar working capabilities and not considering issues related to nurses' rest, the above formula is designed. Example: Suppose there are 10 surgeries in the target department in the next week, and the total number of nurses is 54. The number of nurses required for the surgeries S i varies according to different types of surgeries. For example: Surgeries 1 - 5: Each surgery requires 2 nurses. Surgeries 6 - 8: Each surgery requires 3 nurses. Surgeries 9 - 10: Each surgery requires 4 nurses. Then, ; R = 27 / 54 ≈ 0.5 or 50%; This means that to meet the surgical needs in the next week, at least 50% of the human resources are required. It should be ensured that for the total number of nurses, the total number of nurses needs to far exceed the minimum number of nurses actually required.

[0022] The cumulative value of the feedback data corresponding to each candidate solution after screening represents the cumulative sum of the satisfaction degrees of different nurses for the same candidate solution. The following example is used to assist in understanding:

[0023] Among them, 1 represents satisfaction (that is, the satisfaction degree), and 0 represents dissatisfaction (that is, the satisfaction degree). Therefore, when the total number of nurses is three, the cumulative value of the feedback data corresponding to Solution A is: 1 + 1 + 1 = 3, the cumulative value of the feedback data corresponding to Solution B is: 0 + 1 + 0 = 1, and the cumulative value of the feedback data corresponding to Solution C is: 1 + 1 + 0 = 2. Based on the difference between the human resource utilization rate and the human resource standard value, and the cumulative value of the feedback data corresponding to each candidate solution after screening, after weighted calculation, the weighted calculation formula corresponding to the comprehensive index is as follows: ; In the formula, x in Zb x represents the number of the candidate solution, Zb represents the comprehensive index, R x represents the human resource utilization rate corresponding to the candidate solution, Ac xIt represents the cumulative value of feedback data under the corresponding candidate solution. Both α and β represent weight coefficients, and α + β = 1. It should be noted that the greater the difference between the human resource utilization rate and the human resource standard value, the more deviated the human resource utilization situation is from the human resource standard value, and the fewer the number of idle or on - leave nurses, which is not conducive to dealing with subsequent emergencies. The cumulative value of feedback data reflects the satisfaction of nurses with the corresponding subsequent solutions, so the higher its value, the better. When the human resource utilization rate is equal to the human resource standard value, when calculating the comprehensive index Zb, human resources are not considered, and the required comprehensive index Zb is obtained only based on the cumulative value of feedback data under the corresponding candidate solution. It should be noted that the weight coefficients are determined by the coefficient of variation method. The coefficient of variation method is a method of assigning weights to each evaluation index according to the degree of variation between the current value and the target value of each evaluation index. If the numerical difference of a certain index is large and can clearly distinguish each evaluated object, it indicates that the discrimination information of this index is rich, so a larger weight should be given to this index. On the contrary, if the numerical differences of each evaluated object on a certain index are small, then the ability of this index to distinguish each evaluation object is weak, so a smaller weight should be given to this index. This method directly uses the information contained in each index and calculates the weights of the indexes, so it has objectivity.

[0024] Through the above technical solution, an efficient nurse scheduling plan evaluation module is constructed. This module can comprehensively consider the feedback data of nurses and the human resource utilization situation under different candidate solutions. By constructing an evaluation system engine and combining the future work arrangement status of the target department, it can intelligently screen out the preliminary - determined plan. This technical solution not only improves the formulation efficiency of the scheduling plan but also ensures the rationality of the plan in human resource allocation and the superiority in nurse satisfaction. By quantifying the human resource utilization rate and comparing it with the human resource standard value, the advantages and disadvantages of each candidate solution in human resource utilization can be intuitively evaluated. At the same time, combined with the nurses' satisfaction feedback on the candidate solutions, the weighted calculation formula is used to comprehensively consider the human resource utilization situation and nurse satisfaction, further enhancing the practicality and acceptability of the scheduling plan. In short, this technical solution successfully solves the complex problem of evaluating the scheduling plan of hospital departments, bringing a more intelligent, efficient and user - friendly solution for hospital management and nurse scheduling.

[0025] Emergency response module: When there is an emergency state, it ranks the on - leave nurses according to the basic information and sends a temporary scheduling notice. If the nurses ranked higher do not respond within the specified time, it will be postponed to the nurses ranked lower until there is a nurse who responds. If no nurse responds all the time, it will trigger a recruitment mechanism. Record the proportion of triggering the solicitation mechanism within the predetermined period. If the proportion exceeds the expected value, it means that the preliminary plan (i.e. the final candidate plan) needs to be adjusted, and the plan adjustment instruction is executed; if the proportion does not exceed the expected value, no response action is taken and the original preliminary plan is maintained; The above-mentioned emergency states include: There is an unexpected surgery scheduled in a department or the nurse currently on duty has an accident and cannot continue to handle the work; The process for prioritizing nurses on leave is as follows: Get the type corresponding to the current emergency status and match the appropriate expertise. Extract nurses who have the appropriate expertise and are on vacation from the basic information of each nurse, and sort them from high to low according to their qualifications. The qualifications are positively correlated with the priority. Introducing real-time communication technology when sending temporary shift notifications; Such as SMS, APP push, etc., to ensure that notifications can be delivered to nurses quickly and accurately; at the same time, the system supports an automatic retry mechanism. If the initial notification is not responded to, a reminder will be automatically sent at a preset time interval. If the nurse confirms the shift (i.e. responds) within the specified time, the nurse will be arranged to deal with the emergency; if the nurse does not respond within the specified time, the nurse at the back of the list will be postponed to perform the same operation until a nurse responds; The triggered collection mechanism content is: Nurses who meet the appropriate expertise and are on vacation are recruited from the entire hospital, and the nurse's response speed is positively correlated with the call priority, that is, the fastest responding qualified nurse will be called sooner. When there is only one vacancy, the fastest responding qualified nurse A can be called; The relevant and subsequent processes for recording the percentage of triggering the collection mechanism within the predetermined period are as follows: Within a predetermined period (i.e. a previously set period, such as monthly or quarterly), record the number of all relevant events, including the number of events that triggered the collection mechanism and the number of events for which temporary scheduling notices were sent (i.e. the total number of events), and calculate the proportion of events that triggered the collection mechanism, i.e. the number of events that triggered the collection mechanism divided by the total number of events; Compare the percentage with the expected value; When the proportion value exceeds the expected value, the plan adjustment instruction is executed; When the proportion value does not exceed the expected value, no response action is taken; Among them, the executed plan adjustment instructions are: Extract the candidate solution corresponding to the first digit + 1 in the original sorting table, and use it as the preliminary solution after adjustment. Then continue to record the proportion of the solicitation mechanism triggered within the scheduled cycle in the next loop. If the solution adjustment instruction still needs to be executed, continue to use the candidate solution corresponding to the first digit + 2 as the preliminary solution after adjustment, and so on in a loop until there is no response.

[0026] Through the above technical solution, the system can quickly prioritize the vacationing nurses in case of emergencies and send temporary scheduling notifications, effectively coping with sudden surgical arrangements in the department or the unexpected inability of on-duty nurses to continue working. By introducing real-time communication technology and an automatic retry mechanism, it ensures the fast and accurate delivery of notifications and improves the response speed of nurses. At the same time, a solicitation mechanism is designed. When no nurse responds, eligible nurses can be quickly retrieved from the whole hospital to ensure the timely response to emergencies. In addition, by recording the proportion of the solicitation mechanism triggered within the scheduled cycle and comparing it with the expected value, problems existing in the preliminary solution can be discovered in a timely manner. By executing the solution adjustment instruction and using the next candidate solution with a higher ranking as the preliminary solution after adjustment, the optimization adjustment of the scheduling plan is completed according to the situation. This technical solution not only improves the hospital's ability to respond to emergencies, but also ensures the flexibility and practicality of the scheduling plan, effectively solving the technical problems of untimely emergency response and inflexible solution adjustment existing in hospital scheduling management.

[0027] The temporary adjustment module, within a fixed cycle, records and based on the information of the responding nurses, combines the basic information to re-prioritize the vacationing nurses and feeds back the sorting result (feed back to the first priority sorting in the emergency response module, so that subsequent operations are carried out or executed according to the re-prioritization). Among them, the fixed cycle represents a fixed period, which is set according to actual needs. In this embodiment, the fixed cycle is usually set to one quarter, and it is only necessary to ensure that the fixed cycle is longer than the duration of the aforementioned preset cycle. Recording and based on the information of the responding nurses means that the responding nurses are marked. The process of re-prioritizing the vacationing nurses is as follows: Establish a quality quantification value library. According to the qualifications of nurses in the basic information, match the corresponding qualification levels, and the qualification degree is positively correlated with the qualification level. In this library, qualification level 1 corresponds to junior practicing nurses, qualification level 2 corresponds to intermediate practicing nurses, qualification level 3 corresponds to supervisor nurses, qualification level 4 corresponds to deputy chief nurses, and qualification level 5 corresponds to chief nurses. The specific quality quantification value library is as follows:

[0028] In this library, Level 1 represents the nurses with the lowest qualifications (such as junior practicing nurses), while Level 5 represents the nurses with the highest qualifications (such as chief nurses); the numerical value of the qualification level corresponds to the quantization value, and this quantization value increases as the qualification description (degree) improves; At this time, when dealing with obtaining the type corresponding to the current emergency state and matching the appropriate expertise, extract the nurses who meet both the appropriate expertise and are in the vacation scheduling state from the basic information of each nurse, determine the qualification level of each nurse through the qualification quantization value library, and collect and calculate the proportion of the number of times each nurse is marked within a fixed period, build an index calculation function model to generate the priority index corresponding to each eligible nurse. (At this time, it is not sorted from high to low according to qualifications), but sorted from large to small according to the priority index, and the priority index is positively correlated with the priority; Among them, when running the index calculation function model, the formula used is: ; ; Among them, Rt, Mq, and Td respectively represent the proportion of the number of times marked, the number of times the corresponding nurse is marked within a fixed period, and the fixed period (usually expressed in days), Irt represents the priority index, Q represents the qualification level of the corresponding nurse, and k is an adjustment coefficient used to control the influence degree of the proportion of marked times on the priority index, and the value range of k is [0, 1]; Logical explanation: The higher the qualification level, the better the qualifications of the nurse; Proportion of marked times: The more times marked, the larger the proportion Rt, indicating that the nurse has a faster reaction speed and is more active in dealing with the emergency state; Adjustment coefficient k: used to adjust the influence of the proportion of marked times on the priority index, the larger the k value, the more significant the influence of the proportion of marked times on the priority index; Priority index calculation: Substitute the level value, proportion of marked times, and adjustment coefficient into the formula to calculate the priority index of each nurse; The higher the priority index, the higher the priority of the nurse in the current emergency state; In this embodiment, before each formula is calculated, each parameter needs to be dimensionless processed to remove the dimension, which is convenient for subsequent calculations; Example: Suppose there are two nurses: Nurse A: The qualification level is 3 (supervising nurse), the number of times marked within a fixed period is 5 times, and the fixed period is 30 days; Nurse B: The qualification level is 2 (intermediate practicing nurse), the number of times marked within a fixed period is 2 times, and the fixed period is 30 days; The adjustment coefficient k = 0.1; Calculate the proportion of the number of times marked Rt: Nurse A: Rt = 5 / 30 ≈ 0.1667; Nurse B: Rt = 2 / 30 ≈ 0.0667; Calculate the priority index: Nurse A: Irt ≈ 2.89; Nurse B: Irt ≈ 1.99; According to the calculation results, the priority index of Nurse A is higher, so it ranks ahead in the sorting; the value of the adjustment coefficient k can be adjusted according to the actual situation in this calculation process to adapt to different application scenarios and requirements; it should be noted that due to the numerical range of the qualification level and the marked proportion, as well as the selection of the adjustment coefficient k, the calculated priority index may need to be appropriately scaled or adjusted to ensure its effectiveness and rationality in actual applications; for example, if the range of the priority index is too large or too small, it can be fine-tuned by adjusting the value of k or other methods. After the initial priority sorting according to the qualifications of nurses, for the subsequent group of nurses with the same qualifications, it can be corrected and adjusted according to their response attitudes towards emergencies (reflected by the proportion of the marked times), which can not only complete the priority subdivision of the group of nurses with the same qualifications, but also provide opportunities for some nurses with positive response attitudes. Due to the rapid response of this part of nurses, the nurse scheduling operation can be completed more efficiently when dealing with emergencies. Specifically, this system can perform secondary priority sorting on the vacationing nurses according to the information and basic information of the responding nurses. By establishing a quantitative value library of qualifications, quantifying the qualification levels of nurses, and combining the proportion of the marked times within a fixed period, the priority index of each eligible nurse is generated through an exponential calculation function model, realizing the refined sorting of the priorities of nurses; this solution not only considers the qualification level of nurses, but also fully considers the response speed and enthusiasm of nurses towards emergencies, so that the scheduling of nurses can be arranged more scientifically and reasonably. In summary, this technical solution can also provide more opportunities for nurses with positive response attitudes, encourage nurses to participate more actively in the response to emergencies, and effectively solve the problems of unreasonable priority sorting and low scheduling efficiency in hospital scheduling management.

[0029] Embodiment 2: Please refer to Figure 2 , based on Embodiment 1, this embodiment also provides an automatic nurse scheduling method based on departments, including the following specific steps: S1. Summarize the work requirements of the target department and the basic information of nurses, and use the genetic algorithm to generate several candidate solutions; among them, the work requirements at least include the number of patients and the surgical arrangement. S2. When the nurses receive the candidate solutions, they build an evaluation system engine based on the nurses' feedback data and compare the human resource utilization under different candidate solutions. Combined with the future work arrangement status of the target department, a preliminary solution is obtained. S3. When there is an emergency, prioritize the nurses on leave and send a temporary shift notification. If the nurses with the highest priority do not respond within the specified time, the nurses with the lowest priority will be postponed until a nurse responds. If no nurse responds, the recruitment mechanism is triggered. The proportion of the recruitment mechanism triggered within the predetermined period is recorded simultaneously. If the proportion exceeds the expected value, the plan adjustment instruction is executed. S4. Within a fixed period, record and prioritize the nurses on leave based on the information of the responding nurses and the basic information, and provide feedback on the ranking results.

[0030] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0031] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0032] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An automatic scheduling system for medical staff based on departments, characterized in that, The system includes: The pre-scheduling module summarizes the work requirements of the target department and the basic information of nurses, and uses genetic algorithms to generate several candidate plans; the work requirements at least include the number of patients and the arrangement of surgery; The program evaluation module, when the nurses receive the candidate programs, builds an evaluation system engine based on the nurses' feedback data and compares the use of human resources under different candidate programs, and then comes up with a preliminary program based on the future work arrangement status of the target department; Emergency response module: when there is an emergency, the nurses on leave are prioritized and a temporary shift notification is sent. If the nurses with the highest priority do not respond within the specified time, the nurses with the lowest priority will be postponed until a nurse responds. If no nurse responds, the recruitment mechanism is triggered. The proportion of the recruitment mechanism triggered within the predetermined period is recorded simultaneously. If the proportion exceeds the expected value, the plan adjustment instruction is executed. The temporary adjustment module records and prioritizes the nurses on leave based on the information of the responding nurses and the basic information within a fixed period, and provides feedback on the ranking results.

2. The automatic scheduling system for medical staff based on departments according to claim 1, wherein: Surgery schedule: date, time, type of surgery and specialty of the nurse required; basic information of the nurse: nurse's name, qualifications, specialty, current scheduling status and vacation plans.

3. The automatic scheduling system for medical staff based on departments according to claim 1, characterized in that: The process of using genetic algorithm to generate several scheduling schemes is as follows: Coding: Integer coding is used. Each shift scheduling plan is represented by a chromosome. Each gene on the chromosome represents the working status of a nurse in a set time period. Initial population: randomly generate multiple scheduling plans as the initial population, each plan meets the set constraints; Fitness function: Design a fitness function, score the quality of the scheduling plan, and calculate the fitness of each scheduling plan; the quality of the scheduling plan at least includes the balance of nurse workload, the satisfaction of patient care needs, and the matching of professional skills; Selection: Use the roulette wheel selection strategy to select individuals with satisfactory fitness from the current population as parents; Crossover: Perform a crossover operation on the selected parent generation to generate a new child generation scheduling plan; Mutation: Randomly mutate the offspring scheduling plan; Iteration: Repeat the selection, crossover and mutation operations until the predetermined number of iterations is reached, and after the iteration is completed, select several scheduling schemes from the final population as candidate schemes.

4. The automatic scheduling system for medical staff based on departments according to claim 1, characterized in that: The nurses’ feedback data indicates: the nurses’ satisfaction with each candidate solution. If the corresponding nurse is satisfied, the corresponding candidate solution is marked as 1; if not, the corresponding candidate solution is marked as 0. The use of human resources is quantified by the human resource utilization rate; The calculation method of human resource utilization rate is: Human resource utilization rate = actual human resources used / total human resources × 100%.

5. The automatic scheduling system for medical staff based on departments according to claim 1, characterized in that: The process of running the evaluation system engine is: According to the future work arrangement status of the target department and the total number of nurses in the target department, a mathematical calculation model is built to generate the required human resource standard value, and the candidate solutions corresponding to the human resource utilization exceeding the human resource standard value are screened out. The comprehensive indicators obtained after weighted calculation are based on the difference between the human resource utilization rate and the human resource standard value, as well as the cumulative value of the feedback data corresponding to each candidate solution obtained after screening. The comprehensive indicators are sorted from large to small to generate a sorting table. The candidate solution corresponding to the first place in the sorting table is the preliminary solution.

6. The automatic scheduling system for medical staff based on departments according to claim 5, characterized in that: The future work arrangement status under the target department represents: the total number of surgeries scheduled in the future preset period; When building a mathematical calculation model, the formula is based on: ； Wherein, R_min represents the required human resource standard value, T represents the total number of scheduled surgeries within a preset period, Nr represents the total number of nurses in the target department, and S i represents the number of nurses required for the i-th surgery.

7. An automatic scheduling system for medical staff based on departments according to claim 6, characterized in that: The weighted calculation formula corresponding to the obtained comprehensive index is as follows: ； where, Zb x represents the comprehensive index under the candidate solution number x, R x represents the human resource utilization rate under the candidate solution number x, Ac x represents the cumulative value of feedback data under the candidate solution number x, α and β are weight coefficients, and α + β = 1.

8. An automatic scheduling system for medical staff based on departments according to claim 1, characterized in that: The process of prioritizing nurses on vacation is as follows: obtain the type corresponding to the current emergency status and match the appropriate expertise, extract nurses who meet the appropriate expertise and are on vacation from the basic information of each nurse, and sort them from high to low according to qualifications, and qualifications are positively correlated with priority; The triggered recruitment mechanism is: nurses with appropriate expertise and on vacation are recruited from the entire hospital, and the nurses' response speed is positively correlated with the priority of the call; After recording the proportion of the collection mechanism being triggered within the scheduled period, record the number of all relevant events within the scheduled period, including the number of events that triggered the collection mechanism and the number of events for sending temporary scheduling notifications, that is, the total number of events, and calculate the proportion of the collection mechanism being triggered, that is, the number of events that triggered the collection mechanism divided by the total number of events; The content of the executed plan adjustment instruction is: extract the corresponding candidate plan with the serial number of the first place + 1 in the original sorting table, and use it as the adjusted preliminary plan, and then continue to record the proportion of triggering the collection mechanism within the predetermined period in the next cycle. If the plan adjustment instruction is executed again, the corresponding candidate plan with the serial number of the first place + 2 will continue to be used as the adjusted preliminary plan, and so on. The cycle continues until there is no response.

9. The automatic scheduling system for medical staff based on departments according to claim 8, wherein: Record and represent according to the responding nurse's information: the responding nurse is marked; The process for secondary prioritization of nurses on leave is as follows: Establish a qualification quantitative value library, match the corresponding qualification level according to the qualifications of the nurses in the basic information, and the qualification degree is positively correlated with the qualification level; in response to the type corresponding to the current emergency status, match the appropriate expertise, extract nurses who meet the appropriate expertise and are on vacation from the basic information of each nurse, determine the qualification level of each nurse through the qualification quantitative value library, and collect and calculate the proportion of each nurse's marked times within a fixed period, build an index calculation function model to generate the priority index corresponding to each qualified nurse, and sort them from large to small according to the priority index, and the priority index is positively correlated with the priority level; Among them, when running the exponential calculation function model, the formula is based on: ； ； Among them, Rt, Mq, and Td respectively represent the proportion of the marked times, the number of times the corresponding nurse is marked within a fixed period, and the fixed period. Irt represents the priority index, Q represents the qualification level of the corresponding nurse, and k is an adjustment coefficient with a value range of [0, 1].

10. An automatic scheduling method for medical staff based on departments, which is applied to the system according to any one of claims 1 to 9, and is characterized in that: It includes the following steps: S1. Summarize the work requirements of the target department and the basic information of the nurses, and use the genetic algorithm to generate several candidate solutions; among them, the work requirements include at least the number of patients and the surgical arrangement. S2. Under the condition that the nurse receives the candidate solution, based on the feedback data of the nurse and comparing the human resource utilization under different candidate solutions, construct an evaluation system engine, and combine the future work arrangement status of the target department to obtain a preliminary solution. S3. When there is an emergency, rank the priority of the nurses on leave and send a temporary scheduling notice. If the nurse ranked higher does not respond within the specified time, it will be postponed to the nurse ranked lower until a nurse responds. If no nurse responds all the time, trigger the recruitment mechanism; synchronously record the proportion of the recruitment mechanism triggered within the scheduled period. If the proportion exceeds the expected value, execute the plan adjustment instruction. S4. Within a fixed period, record and, based on the information of the responding nurses, re-prioritize the nurses on leave in combination with the basic information and feedback the ranking result.

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