Medical personnel scheduling table management method and device, medium and product

Abstract

The invention discloses a medical personnel scheduling table management method and device, a medium and a product, and relates to the field of data processing. The method comprises the following steps: acquiring multi-dimensional portrait data and department resource map data of medical personnel to be scheduled in a department; based on the multi-dimensional portrait data and preset scheduling rules and shift demands, a basic scheduling table of a preset period is generated, and the basic scheduling table covers the conventional workload of a set proportion of the medical personnel; initializing a general scheduling table according to the basic scheduling table; based on the real-time medical demand data, the department resource map data and the current state of the general scheduling table, dynamic adjustment information of the general scheduling table is generated, and the dynamic adjustment information comprises a newly added scheduling instruction or an original shift change instruction; and updating the general scheduling table in real time according to the dynamic adjustment information. According to the invention, the rapid response and dynamic adjustment capability to emergencies and real-time medical requirements can be improved, and the problem that the medical staff scheduling table management flexibility and rationality are insufficient is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a medical staff scheduling table management method, device, medium and product. BACKGROUND

[0002] In the medical industry, the scheduling of medical staff is a key link to ensure the normal operation of medical services. Traditional medical staff scheduling methods usually rely on manual experience, simple electronic spreadsheets or scheduling software based on fixed rules. When dealing with scheduling tasks, these methods mainly consider the basic information of medical staff (such as department, position, qualification), shift requirements and some basic scheduling rules (such as avoiding consecutive night shifts, meeting minimum staffing requirements, etc.).

[0003] However, the traditional scheduling method usually generates static or semi-static scheduling tables based on preset conditions, and lacks the ability to quickly respond to sudden situations and real-time medical needs and dynamically adjust. When there are emergency patients, temporary leave of personnel or surge of medical resource demand in a particular area, etc., the traditional method is difficult to efficiently and flexibly, reasonably redistribute tasks and adjust shifts, which can easily lead to unreasonable scheduling, excessive fatigue of personnel or waste of resources, thereby affecting the quality and efficiency of medical services. SUMMARY

[0004] To solve the above technical problems and defects, the purpose of the present application is to provide a medical staff scheduling table management method, device, medium and product, which can improve the ability to quickly respond to sudden situations and real-time medical needs and dynamically adjust, and alleviate the problem of insufficient flexibility and rationality of medical staff scheduling table management.

[0005] To achieve the above purpose, in a first aspect, the present application provides a medical staff scheduling table management method, comprising: obtaining multi-dimensional portrait data of medical staff to be scheduled in a department and department resource map data, the multi-dimensional portrait data at least including one of seniority, title, scientific research task load and home address of the medical staff, and the department resource map data including historical busy period and medical resource distribution heat data of the department; generating a preset period of basic scheduling table based on the multi-dimensional portrait data and preset scheduling rules and shift requirements, the basic scheduling table covering a set proportion of the medical staff's regular workload; initializing a scheduling master table according to the basic scheduling table, the scheduling master table being used to store and manage the basic scheduling table and reflecting the current scheduling state of the medical staff in real time; generating dynamic adjustment information for the scheduling master table based on real-time medical demand data, the department resource map data and the current state of the scheduling master table, the dynamic adjustment information including new scheduling instructions or original shift change instructions; updating the scheduling master table in real time according to the dynamic adjustment information.

[0006] The application adopts the above method, and first generates a basic scheduling based on the multi-dimensional image of medical staff and the department resource map, but this is not the final goal. The core innovation is that it initializes a scheduling master table that can be updated and managed in real time based on the basic scheduling. This master table is alive and can reflect the current state of the personnel. The system continuously collects real-time medical demand data (such as emergency volume, number of critically ill patients, etc.), and combines department resource map data to provide historical rules and resource distribution information) and the current state of the scheduling master table (understand the existing personnel distribution and busy situation), intelligently generate dynamic adjustment information. These adjustment information directly corresponds to the manpower gap or task changes in reality due to unexpected events or changes in demand. Finally, the system can update the scheduling master table in real time according to these dynamic adjustment information. This means that when an emergency occurs or the medical demand suddenly increases, the system can quickly perceive and calculate the optimal personnel deployment scheme, and immediately reflect it in the scheduling master table. This closed-loop mechanism from real-time data input to intelligent generation of adjustments to immediate updates makes the scheduling no longer a rigid plan, but can be quickly and accurately dynamically adjusted according to the actual situation of the medical site, greatly improving the ability of the scheduling to respond to uncertainty, effectively alleviating the shortcomings of traditional scheduling tables in flexibility and rationality, and ensuring that medical resources can better match real-time demand.

[0007] Optionally, in some embodiments, based on the real-time medical demand data, the department resource map data, and the current state of the scheduling master table, the dynamic adjustment information for the scheduling master table is generated, including: calculating a dynamic manpower gap index of the current department according to the real-time medical demand data and the department resource map data, the real-time medical demand data including emergency patient flow, number of critically ill patients, real-time occupancy state of operating room / examination room, and emergency to-do queue of diagnostic examination; based on the dynamic manpower gap index, filtering a set of deployable medical personnel from the current state of the scheduling master table; performing multi-dimensional matching degree conflict detection on the set of deployable medical personnel to obtain target personnel and target shift that pass the matching; and generating the dynamic adjustment information according to the target personnel and the target shift.

[0008] By introducing real-time medical demand data and department resource map data and calculating a dynamic manpower gap index, the above-mentioned technical solutions of the embodiments can accurately identify the gap between the manpower demand of a department at a specific time point and the existing scheduling. On this basis, the system can intelligently filter a set of personnel that can be theoretically deployed from the scheduling master table, and perform multi-dimensional matching degree conflict detection to ensure that the found personnel not only meet the basic conditions, but also can maximize the avoidance of potential scheduling conflicts, thereby efficiently and accurately generating dynamic adjustment information for actual demand, improving the response speed and effectiveness of the scheduling.

[0009] Optionally, in some embodiments, according to the real-time medical demand data and the department resource map data, a dynamic manpower gap index of the current department is calculated, including: based on the real-time medical demand data, the instantaneous demand medical personnel quantity of the department is counted; according to the historical busy period in the department resource map data, a reference value of the baseline manpower configuration in the current period is determined; according to the difference between the instantaneous demand medical personnel quantity and the reference value of the baseline manpower configuration, and the medical resource distribution heat data in the department resource map data, the dynamic manpower gap index is generated.

[0010] By combining real-time medical demand data, historical busy period and medical resource distribution heat data, the technical solutions of the above embodiments can more comprehensively and finely calculate the dynamic manpower gap index of the department. The instantaneous demand medical personnel quantity reflects the immediate workload, the reference value of the baseline manpower configuration provides a baseline based on historical experience, and the medical resource distribution heat data considers the work intensity in different areas. By comprehensively using these information, a more accurate and more realistic manpower gap index can be generated, which provides a solid data foundation for subsequent personnel deployment and shift adjustment, avoiding the one-sidedness of relying on experience or a single indicator for judgment.

[0011] Optionally, in some embodiments, the set of deployable medical personnel is subjected to multi-dimensional matching degree conflict detection to obtain target personnel and target shifts, including: based on the multi-dimensional portrait data and target shift requirements, a static matching degree score of each medical personnel for the current vacant shift is calculated; according to the current state of the shift list and the preset shift rules, the medical personnel whose static matching degree score meets the standard are subjected to dynamic conflict verification, and the medical personnel who violate the hard constraints are screened out to obtain medical personnel who pass the matching verification; according to the real-time location state and the continuous working time of the medical personnel who pass the verification, target personnel and target shifts are determined.

[0012] By introducing a multi-dimensional matching degree conflict detection mechanism, the technical solutions of the above embodiments can ensure that the selected deployable medical personnel are truly suitable for filling the vacant shifts. The static matching degree score takes into account the professional ability of the personnel and the shift requirements, and the dynamic conflict verification further excludes personnel who cannot be deployed due to existing scheduling or other hard constraints. Finally, by combining the real-time location and continuous working time of the personnel, the most suitable personnel can be selected from the personnel who pass the verification, thereby improving the success rate and rationality of shift adjustment and avoiding secondary adjustment caused by personnel mismatch or conflict.

[0013] Optionally, in some embodiments, the target personnel and the target shift are determined according to the real-time location status and the continuous working time of the medical personnel who pass the verification, including: calculating a commuting cost factor of the medical personnel to the department corresponding to the target shift based on the real-time location status; calculating a fatigue attenuation coefficient of each medical personnel according to the continuous working time recorded in the shift schedule table; generating a space-time comprehensive score based on the commuting cost factor and the fatigue attenuation coefficient; and determining the medical personnel with the highest space-time comprehensive score and the corresponding shift as the target personnel and the target shift, respectively.

[0014] By calculating the commuting cost factor and the fatigue attenuation coefficient and generating the space-time comprehensive score, the target personnel can be selected more scientifically and humanely. The commuting cost factor takes into account the influence of the geographical location of the personnel on the response speed, and the fatigue attenuation coefficient reflects the current working state and health condition of the personnel. By considering both of them comprehensively, personnel who can quickly arrive and are in good working condition can be preferentially selected, thereby improving the efficiency and safety of personnel deployment in emergency situations, and also reflecting the concern for the physical and mental health of medical personnel.

[0015] Optionally, in some embodiments, the shift schedule table is initialized according to the basic shift schedule table, including: generating a three-dimensional mapping relationship about time, post and personnel according to the shift assignment records in the basic shift schedule table; performing conflict compliance checking on the three-dimensional mapping relationship based on preset shift scheduling rules, and screening out records that violate hard constraints; and converting the three-dimensional mapping relationship that passes the checking into an operable shift schedule table with version identification, the shift schedule table containing time slots, state bits and update interfaces.

[0016] By converting the basic shift schedule table into an operable shift schedule table with version identification and performing conflict compliance checking, the accuracy and usability of the shift schedule table can be ensured. The three-dimensional mapping relationship clearly expresses the correspondence between time, post and personnel, and the conflict checking discovers potential scheduling problems in advance. The design of version identification and update interfaces makes it convenient to dynamically update and manage the shift schedule table, providing a structured data basis and operation platform for the smooth progress of the entire scheduling process.

[0017] Optionally, in some embodiments, after the shift schedule table is updated in real time according to the dynamic adjustment information, the method further includes: during the execution of the updated shift schedule table, collecting actual on-duty data and on-duty replacement events of medical personnel in real time to obtain shift execution feedback records; and dynamically correcting the historical busy period of the department resource map data based on the difference analysis result of the shift execution feedback records and the shift schedule table.

[0018] By collecting the scheduling execution feedback records in real time and performing difference analysis with the scheduling summary table, a closed-loop mechanism of continuous learning and optimization can be established. The scheduling execution feedback records provide the actual performance of the scheduling plan in actual operation, and the difference analysis reveals the deviation between the plan and the actual situation. Based on these deviations, the historical busy period of the department resource map data is dynamically corrected, which can make the system's prediction of future manpower demand more and more accurate, thereby continuously improving the quality and adaptability of subsequent scheduling plans, and forming a self-improving intelligent scheduling system.

[0019] In a second aspect, the embodiments of the present application provide an electronic device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program codes, the computer program codes comprise computer instructions, and the one or more processors invoke the computer instructions to enable the electronic device to perform the method described in the first aspect or the second aspect and any possible implementation manner of the first aspect or the second aspect.

[0020] In a third aspect, the present application provides a computer-readable storage medium comprising instructions that, when executed on the electronic device, cause the electronic device to perform the method described in the first aspect or the second aspect and any possible implementation manner of the first aspect or the second aspect.

[0021] In a fourth aspect, the present application provides a computer program product comprising instructions that, when executed on the electronic device, cause the electronic device to perform the method described in the first aspect or the second aspect and any possible implementation manner of the first aspect or the second aspect.

[0022] It can be understood that the electronic device provided by the second aspect, the storage medium provided by the third aspect, and the computer program product provided by the fourth aspect are all used to execute the method provided by the present application. Therefore, the beneficial effects that can be achieved are referred to the beneficial effects in the corresponding method, which will not be described here.

[0023] The one or more technical solutions provided by the present application have at least the following technical effects or advantages: 1. The medical scheduling system improves the ability to quickly respond to sudden situations and real-time medical needs and dynamically adjust. By collecting medical demand data in real time, combining department resource maps and current scheduling status, the system can quickly perceive manpower gaps or demand changes and intelligently calculate the optimal dynamic adjustment scheme. This adjustment mechanism based on real-time data driving breaks the limitations of traditional static scheduling tables, allowing scheduling to reflect the actual situation on the medical site in real time, ensuring that medical resources can be quickly and effectively allocated during emergencies or peak demand periods, greatly improving the efficiency of dealing with uncertainty.

[0024] 2. By multi-dimensional fine matching and conflict detection, the accuracy and rationality of shift scheduling adjustment are improved. When performing dynamic personnel allocation, the system not only considers the basic attributes and shift requirements of personnel (static matching), but also combines the shift schedule, preset rules, real-time location and continuous working time for dynamic conflict verification and time-space comprehensive scoring. This comprehensive consideration ensures that the selected personnel not only meet the professional requirements, but also are feasible and reasonable under the current state, avoiding scheduling failure or low efficiency caused by personnel mismatching, conflict or excessive fatigue, making dynamic adjustment more accurate and effective.

[0025] 3. An intelligent shift scheduling system is constructed. By collecting actual on-duty data and shift replacement events in real time during shift scheduling execution, and performing difference analysis with the shift schedule, the system can obtain valuable shift scheduling execution feedback. Based on these feedbacks, the system can dynamically correct key data such as historical busy period in department resource map. This feedback loop mechanism enables the system to continuously learn and improve from actual operation, making its prediction of future medical needs and generation of shift scheduling scheme more and more in line with reality, thereby realizing continuous optimization of shift scheduling management and continuous improvement of intelligent level. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 is a flowchart of a medical personnel shift scheduling table management method according to an embodiment of the present application; Figure 2 is a flowchart of another medical personnel shift scheduling table management method according to an embodiment of the present application; Figure 3 is an architecture diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to be limiting of the present application. As used in the specification, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or" as used herein refer to any or all possible combinations of one or more of the associated listed items.

[0028] Hereinafter, the terms "first" and "second" are used only for the purpose of description and should not be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0029] It should be noted that, unless otherwise explicitly specified and limited, the terms such as "set", "connect" and the like in the embodiments of the present application should be understood in a broad sense. For example, "connect" can be fixed connection, or detachable connection, or integral connection; can be mechanical connection, or electrical connection; can be direct connection, or indirect connection through intermediate medium; can be internal communication of two elements; can be wired communication connection, or wireless communication connection. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances. The embodiments of the present application will be specifically described below.

[0030] In the emergency department of a large hospital, the traditional shift management is usually conducted by the department head nurse or the shift manager. They will manually arrange shifts on an electronic table or a paper shift table according to the daily shift needs of the emergency department (such as day shift, night shift, and small night shift), combined with the qualifications, experience and personal leave or shift application of the nurses. During the shift arrangement process, the main consideration is to ensure that there are enough number and qualifications of nurses for each shift, and to try to meet some basic balance principles, such as avoiding making the same nurse work night shift continuously.

[0031] However, this way is difficult to consider the current progress of the nurses' scientific research projects, the influence of the distance of their home addresses on commuting, and it is also difficult to accurately predict the possible patient flow peaks in the emergency department in the future period of time, and it is even more difficult to quickly and effectively adjust the personnel arrangement when a large number of patients suddenly rush in. The whole process is time-consuming and laborious, and the arrangement result is often difficult to achieve the optimal, and it is easy to appear that some nurses have heavy work load, while some other nurses are relatively idle.

[0032] However, in the same emergency department scenario, the system will first obtain the multi-dimensional portrait data of each nurse, including their seniority, title, ongoing scientific research task load, and home address information, and the like, by using the medical personnel shift management technology provided by the embodiments of the present application. At the same time, the system will also analyze the historical busy period data and medical resource distribution heat data of the emergency department, such as that there are usually more patients on Friday night or during holidays, and the triage station area is under greater pressure at a certain time period, and the like. Based on these data and the preset shift arrangement rules, the system will automatically generate a basic shift arrangement table, which has preliminarily considered the comprehensive situation of the nurses and covered their regular workload.

[0033] Subsequently, the system will initialize a shift schedule table. When the emergency department appears real-time medical demand changes, such as suddenly receiving a large number of traffic accident victims, or the number of patients in a certain area increases, the system will immediately obtain these real-time medical demand data, combined with department resource map data and the current shift schedule table state, intelligently generate dynamic adjustment information. These information may be to suggest increasing the number of nurses at the triage station, or mobilize nurses with specific skills to the rescue room.

[0034] The system will update the shift schedule table in real time according to these dynamic adjustment information, ensure that the personnel configuration of the emergency department can quickly and flexibly respond to actual demand, improve the ability to respond to emergencies, and try to balance the workloads of nurses.

[0035] The following will be combined Figure 1 to specifically illustrate the medical personnel shift schedule management method provided by the embodiment of the application, comprising the following steps: Step 201, obtaining multi-dimensional portrait data of medical personnel to be scheduled in the department and department resource map data.

[0036] Among them, the multi-dimensional portrait data at least includes one of the seniority, title, scientific research task load and family address of the medical personnel. The department resource map data includes the historical busy period of the department and the medical resource distribution heat data; the medical resource distribution heat data is a kind of visual or quantitative data representation, which reflects the busy degree, demand density or use frequency of medical resources in different areas or different time periods in the department, usually represented by color depth or numerical value. The "heat" of resources.

[0037] Specifically, the shift schedule management system (for convenience, hereinafter can be referred to as system) will first obtain the multi-dimensional portrait data of the medical personnel to be scheduled in the department through various ways. This includes extracting the basic information of the medical personnel such as seniority and title from the hospital's human resource database or HIS (Hospital Information System, hospital information system) system interface. For scientific research task load, the system may need to interface with the hospital's scientific research management system to obtain the number, importance or input time proportion of scientific research projects currently undertaken by each medical personnel. The family address information can be input by the medical personnel or obtained from other legal channels, and the system will convert it into commuting time or distance data related to the geographical location of the hospital. These multi-dimensional portrait data will be structured stored in the database of the system and associated with the unique identifier of the medical personnel.

[0038] Meanwhile, the system will obtain department resource map data. Historical busy period data can be obtained by analyzing the department's past patient volume, surgery volume, hospitalization rate, examination application volume, etc. The system will identify the regular peak and trough periods of each day, week, month, or year. The medical resource distribution heat data needs to collect the resource usage of different areas (such as examination rooms, treatment rooms, wards, examination rooms) in the department at different time periods, for example, a certain examination room has the longest waiting time from 9 am to 11 am, or a certain treatment room has the highest usage rate from 2 pm to 4 pm. These data can be collected through the department information system, Internet of Things devices (such as location sensors), or manually input by medical staff, and processed and analyzed to generate heat maps or quantitative indicators reflecting the busy degree of resources.

[0039] All these multi-dimensional portrait data and department resource map data will be integrated and pre-processed by the system to provide input for subsequent scheduling calculations.

[0040] Step 202, based on the multi-dimensional portrait data and preset scheduling rules and shift requirements, generate a preset period of basic scheduling table, the basic scheduling table covers the set proportion of the medical staff's regular workload.

[0041] Among them, the scheduling rules are a series of constraint conditions and preference settings configured in the system, such as the minimum and maximum number of people required for each shift, configuration requirements for personnel with specific qualifications, interval requirements between different shifts, individual submitted non-scheduling time periods, and balance rules based on multi-dimensional portrait data (such as balancing the distribution of shifts for personnel with different seniority and title, considering research task load to avoid excessive scheduling, and considering family address to minimize commuting difficulties, etc.).

[0042] Shift requirements specify the number and type of shifts required by the department within a preset period (such as the next week or month).

[0043] The system will run a scheduling algorithm (such as based on constraint programming, integer linear programming, genetic algorithm, or heuristic algorithm), which takes multi-dimensional portrait data, preset rules and shift requirements as input, and aims to generate a basic scheduling table that meets most of the constraint conditions and optimizes the scheduling results as much as possible. This basic scheduling table covers the set proportion of the medical staff's regular workload, such as 70% or 80% of the expected working time and workload, leaving room for subsequent dynamic adjustment.

[0044] In the base schedule generation process, the system will consider multiple factors, such as arranging more personnel during the expected patient peak period according to historical busy period data; pre-configuring more resources or personnel in certain hot areas according to medical resource distribution heat data; appropriately reducing the clinical shifts of medical personnel according to their research task load; and arranging shifts close to home or reducing cross-regional mobilization according to family address.

[0045] The generated base schedule is stored in the system in a structured data form and can be preliminarily reviewed by the shift manager.

[0046] Step 203, initializing the shift master table according to the base schedule.

[0047] The shift master table is used to store and manage the base schedule and reflects the current shift status of the medical personnel in real time. Specifically, the shift master table is a central data structure in the system for centralized storage, management, and real-time update of all medical personnel shift information. The initialization process is to accurately and correctly copy or import all shift records in the base schedule, including the shift or task assigned to each medical personnel on a specific date and time period, into the shift master table.

[0048] In this embodiment, the design of the shift master table is highly dynamic and flexible. It is not just a static copy of the shift plan, but also a "live" data view that can reflect the current shift status of the department personnel in real time. This means that each record in the shift master table is associated with a specific medical personnel, time period, shift type, and possibly specific tasks or areas.

[0049] In addition to the base schedule information, the shift master table also includes additional fields or attributes to record and manage real-time information related to the shift status. For example, it can mark whether a shift has been confirmed, whether there is a vacancy due to personnel leave, whether there is a temporary task added to a medical personnel's schedule, or whether a shift is temporarily adjusted due to unexpected situations.

[0050] The system will establish a mechanism to ensure that any modification or update to the shift master table can be reflected in real time. This may involve database transaction processing, message queue notification, or front-end interface real-time refresh. In this way, the shift master table becomes the Single Source of Truth for department shift management. All users who need to understand or operate shift information (such as shift managers, department directors, and even medical personnel through permission control) can access this master table and obtain the most timely and accurate shift status information.

[0051] In this embodiment, the process of initializing the overall scheduling table based on the basic scheduling table can be understood as loading the algorithm-generated planned scheduling results for the preset period as the starting point or initial state into the core data structure of the system for real-time tracking and management of personnel scheduling status.

[0052] Specifically, the system reads each scheduling record contained in the basic scheduling table, such as "Medical staff A is assigned to a certain shift, area, or task on a certain day in a certain month of a certain year", and then creates corresponding entries for these records in the data storage of the overall scheduling table. The overall scheduling table is a dynamic data model designed to support frequent reading and updating, which not only stores basic scheduling information, but also includes additional status fields such as whether the current shift has started, whether it has ended, whether there have been personnel changes (such as leave, shift change), whether there are temporary tasks attached, etc.

[0053] Therefore, initialization is not simply a file copy, but rather "injecting" the static plan in the basic scheduling table into the dynamic management engine of the overall scheduling table, giving it an initial view based on the plan and preparing it to receive and process subsequent dynamic adjustment instructions due to changes in real-time medical needs, ensuring that the overall scheduling table accurately and timely reflects the actual on-duty and task allocation of department personnel.

[0054] Step 204, based on real-time medical demand data, department resource map data, and the current state of the overall scheduling table, generate dynamic adjustment information for the overall scheduling table, including new scheduling instructions or original shift change instructions.

[0055] In this step, the system continuously receives and processes real-time medical demand data, which includes but is not limited to sudden surges in emergency patients, emergency surgery arrangements, sudden changes in the condition of hospitalized patients requiring increased care or monitoring, temporary examination or consultation needs, and more common situations such as temporary leave or tardiness of medical staff due to unforeseen circumstances. These real-time medical demand data are direct triggers for dynamic adjustment.

[0056] Upon receiving these real-time medical demand data, the system does not process them in isolation, but immediately conducts comprehensive analysis in combination with "department resource map data" and "the current state of the overall scheduling table". Department resource map data provides important background information, such as whether the current time period is a high-load period in historical data, or the usual resource distribution and busy level of the area where the demand occurs (such as a certain examination room, ward, or consultation room). This helps the system determine the urgency of the current demand and the impact on existing resources.

[0057] More importantly, the "current status of the shift summary" provides the basis for the system to make decisions, which accurately records the current shift situation of each medical staff in the department - who is working, at which post, performing what task, and when to end, who is currently on rest, who is on standby, who has completed the shift task today but may have the potential for overtime, as well as the qualifications, skills and current workload of each staff.

[0058] The system will match and evaluate real-time demand with the background information of the resource map, as well as the personnel availability, skill matching, workload, and various preset shift constraints (such as continuous working time, rest interval, specific shift requirements, etc.) in the shift summary. The goal is to find an optimal or feasible adjustment solution to minimize the disturbance to the existing shift while effectively meeting new medical needs.

[0059] This process generates specific dynamic adjustment information, which is manifested as explicit instructions. For example, if there is a surge of emergency department patients and the shift summary shows that the current on-duty staff load is full, the system may determine from the resource map that it is currently an emergency peak period, then identify from the shift summary that there are medical personnel currently on duty in other relatively idle areas and with emergency handling capacity, generate a "change of original shift instruction", and adjust them to the emergency department for support; or if the shift summary shows that there are on-duty standby personnel available and qualified, generate a "new shift instruction" to require them to report to work immediately.

[0060] These dynamic adjustment information will then be used by the system to update the shift summary to ensure that the summary always reflects the latest actual shift arrangement, and will usually be communicated to the affected medical personnel and relevant management personnel in a timely manner through system notifications, SMS or App messages, etc., so as to realize real-time response and flexible scheduling of department personnel shift.

[0061] Step 205, updating the shift summary in real time according to the dynamic adjustment information.

[0062] In this step, real-time updating of the shift summary is the key link to ensure that the shift summary always reflects the latest and most accurate shift status. The system will first analyze the dynamic adjustment information to determine the specific adjustment content, which may be a new shift instruction requiring a medical staff to be assigned to a new shift or task at a specific time period; or it may be a change of original shift instruction, such as requiring a medical staff to be adjusted from the original shift or post to another, or to change the time, task content, etc. of the shift. The system will perform the corresponding update operation through interaction with the underlying database or data storage of the shift summary.

[0063] For new scheduling instructions, the system creates a new record in the scheduling master table, detailing the assigned medical personnel, new time period, new shift type, task or area, and marks its status as "assigned" or "to be confirmed".

[0064] For original shift change instructions, the system finds the corresponding original scheduling record in the scheduling master table and modifies its relevant fields according to the instructions, such as updating the time period, changing the task or area, or modifying the shift type, while possibly updating the record status to reflect the changes (such as marking "changed" or "to be reconfirmed").

[0065] When performing updates, the system usually adopts a database transaction processing mechanism to ensure the atomicity of the update operation, that is, either all succeed or all fail and roll back, avoiding data inconsistency.

[0066] After the update is completed, the internal data structure of the scheduling master table or the record in the database immediately reflects these changes. At the same time, the system triggers the corresponding notification mechanism to push the scheduling master table update information to the relevant user interface (such as the operation interface of the scheduling manager, the personal scheduling view of the medical personnel) and notification channels (such as system messages, SMS, App push, etc.), ensuring that all relevant personnel can timely obtain the latest scheduling arrangement, thereby realizing real-time synchronization and transparency of scheduling information. This real-time update process is the cornerstone of the system to respond to sudden medical needs and maintain efficient operation of the department.

[0067] The above method steps are adopted in this embodiment, and by introducing a real-time data-driven dynamic adjustment mechanism, the flexibility, accuracy and response speed of medical personnel scheduling are improved, and the ability to quickly respond to sudden situations and real-time medical needs and dynamically adjust is enhanced, and the problem of insufficient flexibility and rationality of medical personnel scheduling table management is alleviated.

[0068] The method of this embodiment can quickly generate dynamic adjustment information for the scheduling master table, including new scheduling or original shift change instructions, by continuously receiving and analyzing real-time medical demand data and combining the current state of the department resource map and the scheduling master table for intelligent decision-making. This means that the system is no longer just executing a fixed scheduling plan, but can make real-time "self-corrections" and optimizations according to actual conditions. For example, when the number of patients in a certain area suddenly increases, the system can immediately identify and quickly adjust appropriate personnel for support according to personnel availability, skills and current load, rather than waiting for manual intervention or following an outdated plan. This real-time response capability greatly improves the department's ability to respond to emergencies, ensuring that there is enough and appropriate medical force on duty at critical moments. In addition, dynamic adjustment information is updated in real time to the scheduling master table, ensuring the accuracy and transparency of scheduling information, reducing confusion and communication costs caused by information lag or errors.

[0069] In this way, the method of the embodiment effectively solves the defects of the traditional scheduling method in dynamic environment, such as lag, lack of flexibility and adaptability, makes the scheduling management more close to the actual demand, improves the utilization efficiency of medical resources, and guarantees the continuity and quality of medical services.

[0070] As shown in Figure 2 The embodiment also provides another medical staff scheduling table management method, which specifically includes the following steps: Step 301, obtaining multi-dimensional portrait data of medical staff to be scheduled in the department and department resource map data.

[0071] This step refers to the description of the foregoing embodiment, which will not be repeated here.

[0072] Step 302, generating a preset period of basic scheduling table based on the multi-dimensional portrait data and preset scheduling rules and shift requirements.

[0073] This step refers to the description of the foregoing embodiment, which will not be repeated here.

[0074] Step 303, generating a three-dimensional mapping relationship about time, post and personnel according to the shift allocation record in the basic scheduling table.

[0075] The purpose of this step is to convert the static information in the basic scheduling table, which is in the unit of shift allocation, into a three-dimensional data model that is more structured and convenient for subsequent processing.

[0076] Among them, the basic scheduling table can be a periodic scheduling plan, which records which medical staff is allocated to which shift in a specific time period (such as a week, a month). For example, the basic scheduling table may contain records such as "Doctor A values the outpatient shift on Monday morning", "Nurse B values the ward shift on Tuesday afternoon", etc.

[0077] In this step, the system will traverse all the shift allocation records in the basic scheduling table. For each record, the system will extract three key information: time (specific date and time period, such as June 23, 2025, 8:00-12:00), post (specific work post or area to which the medical staff is allocated, such as outpatient, ward, operating room, ICU, etc.) and personnel (specific medical staff allocated to perform the shift, such as Doctor A, Nurse B).

[0078] Then, the system organizes these three pieces of information into a three-dimensional mapping relationship, which can be imagined as a multi-dimensional array, hash table, or other data structure, where time, post, and personnel represent a dimension respectively. For example, a structure or object can be constructed containing fields such as "time slot", "post ID", and "personnel ID", and then each record in the basic scheduling table is converted into an instance of such a structure. This three-dimensional mapping relationship intuitively expresses which post should be responsible for which personnel at a certain time point or time period.

[0079] This process is a data format conversion and structuring, which lays the foundation for subsequent conflict detection and total table generation, and converts the original shift assignment information into a data model that is easy to operate and analyze within the system, providing a unified data view for subsequent scheduling verification and dynamic adjustment.

[0080] Step 304, based on the preset scheduling rules, the three-dimensional mapping relationship is checked for conflict compliance, and records that violate hard constraints are filtered out.

[0081] The purpose of this step is to ensure that the initial scheduling arrangement generated by the basic scheduling table complies with the preset various scheduling rules, especially those hard constraints that must be followed. Hard constraints refer to rules and restrictions that must be strictly followed and cannot be violated during scheduling.

[0082] The preset scheduling rules are one of the core logics in the scheduling management system, which come from the regulations of the medical industry, the policies of the hospital, and the actual operation needs of the department, such as: a personnel cannot be assigned to two different posts at the same time; a post cannot be assigned more than the specified number of personnel at the same time period (unless it is a special case and the rules allow); medical personnel must meet the continuous working time limit and rest interval requirements; personnel with certain qualifications or skills can only be assigned to certain specific posts; it is prohibited to have consecutive night shifts for more than a certain number of days; key posts must be covered by enough personnel at any time, etc.

[0083] The system will iterate through each record in the three-dimensional mapping relationship generated in step one and compare it with all preset hard scheduling rules. This process involves complex logical judgment and rule engine execution. For example, the system will check if the same personnel appears in different post records at the same time slot, and if so, it will be marked as a conflict; the system will check if the number of personnel assigned to a post exceeds the upper limit; the system will also check if the personnel's scheduling history (if the system can access it) and the current record violate the continuous working time or rest interval rules.

[0084] All records that violate the hard constraints will be identified and marked by the system. These records marked as conflicts will be "filtered out", meaning they will not be included in the final initialized schedule master. This step is to ensure the validity and feasibility of the initial state of the schedule master, avoiding starting with a schedule plan that already has conflicts, providing a compliant foundation for subsequent dynamic adjustments.

[0085] Step 305, the three-dimensional mapping relationship that passes the verification is converted into a version-identified operable schedule master, which contains time slots, status bits, and update interfaces.

[0086] Among them, the schedule master is the core data structure for subsequent dynamic adjustment and management by the system. The process of this step is to organize the information in the verified three-dimensional mapping relationship into a data format that is convenient for the system to read, write, and update. The schedule master is not just a simple list, but is designed as a structure with specific functions and properties.

[0087] First, the master table is organized in "time slots" as the basic unit, and each time slot (for example, time periods divided by 15 minutes, 30 minutes, or 1 hour) contains personnel allocation information for all positions within that time period. In this way, the system can conveniently query and operate the schedule for a specific time period.

[0088] Second, each schedule record in the master table (i.e., a certain position is responsible for a certain person within a certain time slot) contains a "status bit". This status bit is used to mark the current status of the schedule record, such as "allocated", "pending confirmation", "changed", "cancelled", "temporarily increased", etc. The introduction of the status bit allows the system to clearly track the life cycle and change process of the schedule record, providing support for subsequent dynamic adjustment and conflict resolution.

[0089] Most importantly, the schedule master is designed with "version identification" and "update interface". Version identification is used to track each major modification of the schedule master, ensuring that different versions of the schedule master can be managed when multiple people or systems operate simultaneously, avoiding data confusion. The update interface is a set of functions or methods provided by the system, allowing other modules (such as the dynamic adjustment module in step 204) to add, delete, modify schedule records, etc. on the schedule master through standardized methods.

[0090] This design makes the schedule master a centralized and controllable data source, and all modifications to the schedule must be made through these interfaces, ensuring data integrity and consistency, and providing technical support for subsequent real-time updates and dynamic adjustments.

[0091] Step 306, according to the real-time medical demand data and the department resource map data, calculate the dynamic manpower gap index of the current department.

[0092] The real-time medical demand data includes emergency patient flow, critical patient number, operating room / examination room real-time occupancy status, and diagnosis examination emergency to-do queue of the department.

[0093] The purpose of this step is to quantify the manpower resource gap that the current department is facing when facing real-time changing medical demand. The system continuously receives and analyzes real-time medical demand data from multiple sources, including but not limited to real-time patient flow in the emergency department (e.g. the number of new emergency patients admitted per hour and their classification), the number of critical patients currently in hospital and their nursing level, real-time occupancy status of operating rooms and examination rooms (which operating rooms are performing surgery, estimated end time, which large-scale examination equipment is in use, waiting queue length), and emergency to-do queue of diagnostic examination (e.g. the number of imaging examination or laboratory test samples that need to be processed immediately).

[0094] At the same time, the system will refer to the department resource map data, which records in detail the composition of the department's existing manpower resources, including the number of various medical staff, their qualifications, skill expertise, title, and ability range in different posts or areas. By comparing and analyzing real-time medical demand data with resource capacity in the department resource map, the system can calculate the manpower gap in different time periods, different areas or different professional skills. For example, if the emergency patient flow suddenly increases, and the proportion of critical patients is high, the system will calculate the additional number of doctors and nurses needed in the emergency department according to the preset patient-to-medical staff ratio rules, combined with the number and skills of the currently scheduled personnel in the emergency department, and the specific skills (such as trauma treatment, cardiopulmonary resuscitation, etc.) personnel that may be needed.

[0095] This calculation result is the dynamic manpower gap index, which is a quantitative indicator reflecting the current degree of manpower resource tension and specific demand, which can be a numerical value or a vector or list containing the specific gap number of different areas and different posts. The accuracy of this index directly affects the effectiveness of subsequent dynamic adjustment.

[0096] In some embodiments, step 306 can specifically include: S3061, based on the real-time medical demand data, statistics the instantaneous demand medical personnel number of the department.

[0097] The purpose of this step is to quantify how many medical staff the department actually needs at the current moment to cope with real-time medical demand. The system continuously collects and processes real-time data from the hospital information system, which directly reflects the current workload and urgency of the department. For example, the system will obtain the patient flow of the emergency department in real time, and according to the patient's condition classification (such as critical, emergency, and ordinary) and the preset patient-to-medical staff ratio standard, calculate the number of doctors and nurses required for the current emergency department. At the same time, the system also monitors the real-time occupancy status of the operating room and examination room. If the operating room is performing a complex or long operation, or there is a large number of emergency queues for large examination equipment, the system will assess the number of additional operating room nurses, anesthesiologists, technicians, etc. required according to these circumstances. In addition, an increase in the number of critically ill patients will directly trigger a recalculation of the demand for ICU or high-dependence ward nursing staff.

[0098] By comprehensively analyzing these real-time, dynamically changing medical demand data, the system can instantly calculate that, in order to effectively cope with the current workload, the department theoretically needs a total of how many medical personnel of various types in different areas and positions. This number is a transient value that directly reflects the current demand pressure and is an important input for subsequent calculation of the manpower gap.

[0099] S3062, according to the historical busy period in the department resource map data, determine the reference value of the base manpower configuration in the current period.

[0100] This step utilizes the historical information accumulated in the department resource map data, particularly the busy degree and personnel configuration rules of the department at different time periods (such as different time periods in a day, different days in a week, and different seasons in a year). The department resource map contains the running data of the department in the past period. Through analysis of these historical data, the system can identify the typical busy period of the department and the usual personnel configuration mode under these periods.

[0101] For example, the system may find that the outpatient volume is usually at its peak in the morning of Monday, while the ward is relatively idle in the afternoon of Wednesday. Based on these historical busy period data, the system can determine that the current real-time time point (for example, today is 3 pm on Tuesday) belongs to which category in terms of historical busy degree (for example, it belongs to the "moderate busy" period).

[0102] Then, the system will refer to the typical or recommended "reference value of base manpower configuration" recorded in the resource map that matches the historical busy degree of the current period. This reference value represents the number of various types of medical personnel that the department should normally configure to cope with the current period of this historical busy degree. This reference value provides a stable, historically-based expected personnel configuration level for comparison with the real-time transient demand.

[0103] S3063, generating the dynamic manpower gap index according to the difference between the instant demand medical personnel quantity and the reference value of the benchmark manpower allocation, and the medical resource distribution heat data in the department resource map data.

[0104] First, the system will calculate the difference between the instant demand medical personnel quantity and the reference value of the benchmark manpower allocation. This difference preliminarily reflects the deviation between the current actual demand and the historical experience benchmark. If the instant demand is much higher than the benchmark value, there may be a manpower gap; otherwise, there may be a manpower surplus.

[0105] However, relying only on the difference in total quantity is not enough, the actual distribution of medical resources in the department also needs to be considered. At this time, the system will use the "medical resource distribution heat data" in the department resource map data. These heat data reflect the actual distribution and busy degree of personnel in different areas and different posts in the department, which can be understood as a real-time resource occupation map. For example, even if the total number of people seems enough, but if all the people are concentrated in the emergency department, and the ward or operating room is severely understaffed, there is still a local manpower gap.

[0106] The generation of the dynamic manpower gap index will comprehensively consider the difference in total quantity and the resource distribution heat data. The dynamic manpower gap index can be a numerical value (such as a percentage or the total number of gaps), or a more detailed report indicating how many types of personnel gaps exist in which specific time period, area or post. The index is the direct basis for dynamic adjustment decision-making, which quantifies and locates the area and type of personnel that need to be supplemented most urgently.

[0107] Step 307, based on the dynamic manpower gap index, filtering out a set of deployable medical personnel from the current state of the shift master table.

[0108] Among them, the shift master table records the shift arrangement, post and state of all medical staff in each time slot. The system will find the personnel who are not currently assigned to key or urgent tasks, or whose current tasks are relatively not urgent, or are marked as "on call", "flexible shift" and other states in the shift master table according to the gap type (such as the need for general internal medicine doctors, cardiovascular department nurses, etc.) and the occurrence time indicated by the dynamic manpower gap index calculated in step one.

[0109] The filtering process will consider the current shift state of the personnel, for example, a doctor who is currently performing a long-expected surgery is generally not considered as deployable personnel, but a person who is currently performing non-urgent outpatient service or is currently on break but is marked as "on call" may be included in the deployable set.

[0110] In addition, the screening will also incorporate information about the skills and qualifications of personnel in the department resource map to ensure that the selected personnel have the professional ability to fill the specific gap. For example, if the gap index indicates that a nurse with intensive care experience is needed, the system will only screen the nurses from the current shift roster who meet this condition and whose current status allows for mobilization.

[0111] The goal of this step is to generate a list of potential personnel that can be used for dynamic deployment, providing a candidate range for subsequent precise matching, while avoiding affecting the key personnel configuration required for the current normal operation of the department.

[0112] Step 308, multi-dimensional matching conflict detection is performed on the set of deployable medical personnel to obtain target personnel and target shifts that pass the matching.

[0113] Specifically, the system will evaluate the multi-dimensional matching degree of each person in the deployable set for each specific gap indicated in the dynamic manpower gap index (i.e., the target shift, including specific time, position, and location).

[0114] The evaluation dimensions include but are not limited to: the matching degree of the personnel's skills and qualifications with the requirements of the target shift (e.g., whether a cardiovascular nurse is suitable for ICU support); the distance between the personnel's current actual location or the nearest shift location and the location of the target shift; the personnel's current fatigue level or recent workload (to avoid overwork); the personnel's personal preferences or shift rules (considered within the scope of hard constraints); and most importantly, "conflict detection" - whether deploying the personnel to the target shift will create new, more severe manpower gaps or violate other hard shift rules in their original position or other areas of the department. For example, moving a nurse from one area requires ensuring that the area can still meet the minimum staffing requirements without her. The system will consider these dimensions comprehensively, calculate the matching score of each deployable personnel for each target shift, and perform conflict simulation.

[0115] Finally, the "target personnel and target shifts that pass the matching" are those with higher scores in multi-dimensional matching, and most importantly, their deployment scheme passes all conflict detection and does not cause new, unacceptable problems. This process may involve optimization algorithms designed to find the optimal deployment scheme to maximize gap filling while minimizing negative impacts on existing shifts.

[0116] In some embodiments, step 308 can specifically include: S3081, based on the multi-dimensional portrait data and the requirements of the target shift, calculate the static matching score of each medical personnel for the current vacant shift.

[0117] This step is to initially assess which available personnel are capable and suitable to fill vacant shifts. The system utilizes multi-dimensional profile data of medical personnel stored in the departmental resource map. These profiles detail each person's qualifications, professional skills, experience, professional title, training history, and even past work performance. Simultaneously, the system analyzes the specific requirements of the "target shift" indicated by the dynamic manpower shortage index, including the required job type (e.g., internist, operating room nurse), professional field (e.g., cardiovascular, neurosurgery), required skill level, and specific working hours and location. The system compares the multi-dimensional profile data of each available personnel with the requirements of each vacant target shift and calculates a "static matching score" based on preset matching rules and weights.

[0118] For example, a nurse with cardiovascular qualifications and extensive ICU experience would have a high static match score for a vacancy requiring ICU cardiovascular nursing skills. This score is "static" because it is based solely on the individual's inherent attributes and shift requirements, without considering their current real-time status or scheduling.

[0119] This step can quickly identify the theoretically most suitable pool of personnel to fill the vacancies.

[0120] S3082, based on the current status of the master schedule and the preset scheduling rules, perform dynamic conflict verification on the medical personnel whose static matching score meets the standard, screen out medical personnel who violate the hard constraints, and obtain medical personnel who pass the matching verification.

[0121] This step involves crucial dynamic conflict detection to ensure that any potential reassignment plans do not violate the hospital's or department's strict scheduling rules or create new problems in the current master schedule. The system will query the current status of the master schedule in real time to understand the specific schedule, working hours, and rest status of each candidate. Simultaneously, the system will refer to preset scheduling rules, especially those "hard constraints" that must be strictly followed, such as: mandatory rest intervals (e.g., a break after a certain number of hours of continuous work), daily or weekly maximum working hours limits, minimum staffing levels required for specific positions, and restrictions on the availability of certain personnel at specific times or locations.

[0122] The system simulates each candidate who meets the static matching criteria and their potential target shifts to check whether reassignment would violate any hard constraints or cause the staffing of their original positions to fall below the minimum requirements. Any candidate who violates hard constraints will be immediately screened out.

[0123] Through this dynamic conflict verification process, the system can obtain a smaller set of "medical staff passed matching verification" who not only have the ability to fill vacancies but also do not violate any key rules.

[0124] S3083, determine the target personnel and target shift according to the real-time location status and continuous working time of the medical staff passed verification.

[0125] This step determines the most suitable personnel and the target shift they need to fill based on more detailed real-time dynamic information. Although the previous steps have ruled out violations of hard constraints, there may still be multiple personnel who meet the conditions. At this time, the system will consider those more real-time and dynamic factors to make the best decision. For example, the system will obtain the real-time location information of the medical staff passed verification, and give priority to those who are closer to the target shift location and can arrive faster to respond to emergency situations. At the same time, the system will also consider the personnel's recent continuous working time and fatigue level (although the hard constraints have ruled out overwork, but still can choose relatively less tired personnel within the compliance range).

[0126] By comprehensively evaluating these real-time location status and continuous working time information, the system can further optimize the "target personnel" from the passed verification set and finally match them with the "target shift" that is most suitable for them to fill. This process may involve an optimization process aimed at finding the best deployment combination that can effectively fill the manpower gap, minimize the impact on personnel, and improve response speed.

[0127] In some embodiments, this step S3083 can specifically include: S30831, calculate the commuting cost factor of the medical staff to the department corresponding to the target shift based on their real-time location status.

[0128] After determining the set of medical staff passed matching verification, the system needs to consider their real-time dynamic information. The first key factor is their current location. The system will obtain the real-time location data of these medical staff, which can be obtained through the positioning system within the hospital, the location information reported by the smart devices worn by the personnel or the hospital application used by them.

[0129] At the same time, the system knows the location of the specific department or area where the target shift is located. Based on the real-time location of the personnel and the location of the target department, the system will calculate the geographical distance or estimated shortest commuting time between them. This distance or time is an important indicator of personnel "accessibility". The closer the distance and the shorter the estimated commuting time, the faster the personnel can reach the post, which is particularly important in emergency situations that require a quick response.

[0130] The system converts this distance or time into a "commute cost factor". For example, the closer the distance, the lower the commute cost, and the higher the corresponding commute cost factor (representing better accessibility); the farther the distance, the higher the commute cost, and the lower the factor. This commute cost factor quantifies the impact of geographic location on staffing efficiency and is an important component of subsequent comprehensive assessments.

[0131] S30832, according to the continuous working time record in the scheduling summary table, calculate the fatigue attenuation coefficient of each medical staff.

[0132] In addition to location, the current fatigue state of medical staff is also a key factor affecting their work efficiency and safety. The system queries the latest scheduling summary table data to obtain the verified medical staff's recent continuous working time record. This includes how long their current shift has been ongoing and whether there have been consecutive high-intensity work arrangements in the recent period. Long periods of continuous work can lead to fatigue accumulation, which can affect the staff's reaction speed, judgment, and operation accuracy.

[0133] To quantify the impact of fatigue, the system calculates a "fatigue attenuation coefficient" based on the continuous working time and a pre-set fatigue model. For example, the longer the continuous working time, the higher the fatigue level, and the lower the fatigue attenuation coefficient (representing a decrease in work capacity due to fatigue); if the staff has just started working or has had sufficient rest, the fatigue attenuation coefficient may be close to 1 (representing little impact from fatigue).

[0134] The fatigue attenuation coefficient reflects the potential impact of the staff's current physiological state on their performance of the target shift tasks, and is an important consideration for ensuring staff safety and work quality.

[0135] In some embodiments, the fatigue attenuation coefficient can be calculated using a composite attenuation function, specifically, the composite attenuation function includes: Where: F: fatigue attenuation coefficient, value range 0-1, the lower the value, the worse the doctor's available state.

[0136] e: natural constant (≈2.718), mathematical basis for building an exponential decay model.

[0137] k: attenuation rate parameter, dynamically adjusts the fatigue accumulation speed for different positions (emergency department > outpatient department), k can be dynamically adjusted, for example, k = 0.15 for emergency / ICU positions (accelerated attenuation), and k = 0.08 for outpatient / administrative positions (slowed attenuation).

[0138] T: continuous working time (hours), real-time record of the duration of the current shift.

[0139] W: Post weight, weighted based on post stress type, for example, surgery corresponds to W=1.2, emergency rescue corresponds to W=1.15, and general outpatient service corresponds to W=1.0.

[0140] P: Cumulative attenuation intensity coefficient, controls the influence intensity of historical fatigue load on the current state.

[0141] R: Total actual working time in a certain period of time (for example, 72 hours), extracted from historical execution data of the total shift table. When R≥40 hours, a nonlinear penalty is activated: P=0.5*(1+log2(R-39)).

[0142] C: Set the maximum allowed working time (for example, 48 hours) in a certain period of time (for example, 72 hours).

[0143] In the composite attenuation function, e -kT is the core real-time attenuation term, used to represent the physiological attenuation of the continuous working time of the current shift; is the historical fatigue accumulation term, used to quantify the cumulative effect of working load in a certain period of time (for example, 72 hours).

[0144] The composite attenuation function of the embodiment can simultaneously respond to immediate working intensity and historical fatigue accumulation, realize differentiated calculation of cross-department attenuation through k / W parameters, and innovatively use a logarithmic function to punish the historical working time of overload. The parameter values can be calibrated based on the WHO physician fatigue guidelines and clinical observation data of third-grade hospitals.

[0145] S30833, generating a spatiotemporal comprehensive score based on the commuting cost factor and the fatigue attenuation coefficient.

[0146] Specifically, in order to comprehensively optimize the verified medical personnel, the system combines the "commuting cost factor" and the "fatigue attenuation coefficient" to generate a "spatiotemporal comprehensive score". The spatiotemporal comprehensive score aims to comprehensively measure the suitability of personnel in the "time" (arrival speed / position) and "space" (fatigue state / sustained working ability) dimensions.

[0147] The specific calculation method can be a weighted sum or product model, in which the commuting cost factor and the fatigue attenuation coefficient are assigned different weights according to their importance. For example, in emergency situations, the weight of the commuting cost factor (i.e., arrival speed) may be higher; while in non-emergency but long-time focused work shifts, the weight of the fatigue attenuation coefficient may be increased.

[0148] This spatiotemporal score can be a single numerical value that integrates the real-time location and fatigue status of a staff member together, providing a quantitative indicator to compare the overall suitability of different candidates to fill a specific shift. The higher the score, the more suitable the staff member is to be assigned to the target shift under the current time and location status.

[0149] In some embodiments, to comprehensively measure the real-time location status (reflected by the commuting cost factor C) and the fatigue level (reflected by the fatigue decay coefficient F) of a medical staff, a "synergistic suitability score" algorithm can be employed to generate the spatiotemporal score S. This algorithm not only considers the linear effects of commuting and fatigue individually, but also introduces a nonlinear penalty term to specifically penalize those staff members who perform poorly in both commuting and fatigue dimensions, reflecting the synergistic negative effect of the superposition of the two unfavorable factors.

[0150] The synergistic suitability score formula is as follows: S = w C × C + w F × F - w penalty × (1 - C) × (1 - F); where: C is the commuting cost factor, usually ranging from 0 to 1, with a higher value indicating lower commuting cost and faster arrival speed.

[0151] F is the fatigue decay coefficient, usually ranging from 0 to 1, with a higher value indicating lower fatigue level and better working status.

[0152] w C is the weight of the commuting cost factor, reflecting the importance of fast arrival.

[0153] w F is the weight of the fatigue decay coefficient, reflecting the importance of staff working status.

[0154] w penalty is the weight of the penalty term, controlling the punishment intensity when both commuting and fatigue are in unfavorable states.

[0155] The specific calculation process is as follows: First, multiply the commuting cost factor C and the fatigue decay coefficient F by their corresponding weights w C and w F , respectively, to obtain their respective linear contributions to the total score.

[0156] Then, the penalty term (1-C)×(1-F) is calculated. The design of this penalty term is the algorithm's innovation: if either C or F is close to 1 (i.e., commuting is very convenient or people are not very tired), then one of (1-C) or (1-F) will be close to 0, and their product (1-C)×(1-F) will also be close to 0. At this point, the penalty term -w... penalty The effect of (1-C)×(1-F) on the total score is negligible. However, if both C and F are close to 0 (i.e., commuting is difficult and people are very tired), then (1-C) and (1-F) will both be close to 1, and their product (1-C)×(1-F) will be close to 1. In this case, the penalty term -wpenalty×1 will subtract a large value wpenalty from the total score, thus significantly reducing the score.

[0157] Finally, the linear contribution and penalty term are added together to obtain the final spatiotemporal comprehensive score S. This score S comprehensively reflects the suitability of personnel to fill the target shift under the current temporal and spatial conditions; the higher the score, the more suitable the personnel are. Weight w C w F and w penalty It can be adjusted according to the actual application scenario (such as the urgency of the task, the requirements for personnel status, etc.) to reflect the relative importance of different factors.

[0158] S30834, the medical personnel with the highest spatiotemporal comprehensive score and their corresponding shifts are respectively identified as target personnel and target shifts.

[0159] The system compares the spatiotemporal comprehensive scores of all possible "personnel-shift" combinations and identifies the highest-scoring combination. This highest-scoring combination represents the optimal allocation plan after considering all factors such as static personnel matching, scheduling constraints, real-time location, and continuous working hours. The medical personnel in this highest-scoring combination are designated as "target personnel," and the vacant shift they are assigned to is designated as the "target shift." This means the system recommends assigning this specific medical personnel to this specific vacant shift. If multiple vacant shifts exist, the system may find an optimal personnel for each shift or an overall optimal personnel-shift matching scheme. The final determined target personnel and target shifts will serve as the basis for executing the allocation instructions.

[0160] Step 309: Generate the dynamic adjustment information based on the target personnel and the target shift.

[0161] This step transforms the previously determined "matched target personnel and target shifts" into specific, actionable, dynamically adjustable instructions or information. This information is crucial data used to update the master schedule in real time.

[0162] The system will generate a series of structured adjustment records based on the matched target staff and target shift. Each record explicitly specifies the scheduling item that needs to be adjusted. For example, if the matching result is "temporarily assign doctor C from outpatient to emergency from 2pm to 4pm", the generated dynamic adjustment information will include: operation type (e.g. "add temporary schedule" or "change existing schedule"), involved staff (doctor C), involved time slot (2pm to 4pm), involved post / location (emergency), and possible status marker (e.g. "temporary assignment"). If it involves a change to an existing shift, the information will also include the identification of the original shift.

[0163] These dynamic adjustment information will be packaged into one or more data packets and sent to the scheduling master table management module through the scheduling master table update interface. These information must have clear format and necessary metadata (e.g. generation time, source, etc.) so that the scheduling master table can accurately parse and apply these adjustments.

[0164] The purpose of generating dynamic adjustment information is to convert complex matching and decision results into commands that the system can directly understand and execute, so as to drive real-time update of the scheduling master table, implement dynamic adjustment decisions into actual scheduling changes, and finally reflect on the scheduling arrangement of medical staff to cope with real-time changing medical needs.

[0165] Step 310, updating the scheduling master table in real time according to the dynamic adjustment information.

[0166] This step refers to the description of the previous embodiments, which will not be repeated here.

[0167] Step 311, during the execution of the updated scheduling master table, real-time collection of actual on-duty data and on-duty replacement events of medical staff to obtain scheduling execution feedback records.

[0168] The goal of this step is to capture the real situation of the scheduling plan during the actual execution process, especially the events that do not conform to the plan. The key of this step is to establish a reliable feedback mechanism that can accurately record the actual on-duty status of medical staff and any temporary on-duty changes. Real-time collection of actual on-duty data of medical staff means that the system needs to know whether each staff is actually on duty at a specific time point, at which post, and the actual working hours. This can be achieved in various ways, such as integration with the hospital's access control system, attendance system, electronic medical record system (records the operation time of doctors and nurses) or internal positioning system, to automatically obtain the information of staff's check-in, check-out, working area, etc.

[0169] In addition, mobile applications or terminal devices can also be used to allow personnel to sign in electronically or report their work status. The collection of shift replacement events is even more critical, as it records situations where planned personnel fail to arrive on time or need to leave early, and are temporarily replaced by others. This includes who replaced whom, the time period of replacement, and the reason for replacement (such as emergency, illness, conflict with other tasks, etc.). These replacement events often need to be applied for, approved, and recorded through the system, or manually entered by department managers.

[0170] All of these real-time collected data, including actual on-duty time, location, task execution, and all replacement records, collectively constitute the "shift execution feedback records". These records are raw, unprocessed, and reflect the actual execution of the shift schedule, and are the basis for subsequent analysis and optimization.

[0171] This process needs to be continuous and cover the entire shift cycle to ensure that it can fully and accurately reflect the landing of the shift plan in reality, providing real and reliable input for subsequent intelligent optimization.

[0172] Step 312, based on the difference analysis results between the shift execution feedback records and the shift summary table, dynamically correct the historical busy period of the department resource map data.

[0173] Among them, the system will compare the personnel configuration, working time, post arrangement and other information planned in the shift summary table for each shift, with the actual situation in the feedback records. For example, the system will check that a certain shift is planned to have 5 nurses on duty, but the feedback records show that there are actually only 4 nurses on duty, and there are 3 temporary replacement events; or a doctor is planned to work for 8 hours, but the feedback records show that he actually worked for 10 hours and handled an emergency operation. Difference analysis will quantify these deviations, such as calculating the personnel gap rate of a certain shift, the frequency of temporary replacement, and the over-planned work time, etc.

[0174] These difference analysis results are the key signals for the system to learn and improve. In particular, those differences that repeatedly occur or have significant significance strongly suggest that the original shift plan may not match the actual needs, and this mismatch often stems from the misjudgment of the "historical busy period" of the department's manpower demand.

[0175] The historical busy period data in the department resource map is the basis for the system to predict future manpower needs. It is based on past scheduling data and workload statistics, and reflects the typical busy degree or required manpower in different time periods (such as Monday morning, weekend night shift). If the difference analysis shows that a period that is considered relatively idle in the historical busy period is frequently short of personnel and replaced in actual execution, it indicates that the original historical busy period data underestimated the actual workload of this period. Conversely, if a period that is considered busy actually has a surplus of personnel, it may mean that the historical data overestimates the demand.

[0176] Based on these difference analysis results, the system will "dynamically correct" the historical busy period data of the department resource map. This correction is not simply replacing the data, but a process of learning and adjustment. The system may use machine learning algorithms or other statistical methods to adjust the weight of historical data, update the model parameters of busy period, or mark key periods that need to be re-evaluated, according to the deviation of actual feedback.

[0177] Through this continuous feedback and correction mechanism, the system can make its prediction of department manpower needs more and more close to reality, so as to generate more accurate and efficient future scheduling plans, reduce the deviation between plans and execution, and improve the scientificity and rationality of scheduling.

[0178] The method provided by the above embodiment can be executed by a scheduling table management system, which can be composed of an electronic device. The electronic device in the embodiment of the present application is described from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic diagram of an entity device structure of the electronic device in the embodiment of the present application.

[0179] It should be noted that Figure 3 The structure of the electronic device shown is only an example and should not limit the function and use range of the embodiment of the present application.

[0180] As Figure 3As shown, the electronic device includes a Central Processing Unit (CPU) 401 which can perform various appropriate actions and processes in accordance with a program stored in a Read-Only Memory (ROM) 402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403, for example, to execute the methods described in the above embodiments. In the Random Access Memory (RAM) 403, various programs and data required for system operation are also stored. The Central Processing Unit (CPU) 401, the Read-Only Memory (ROM) 402, and the Random Access Memory (RAM) 403 are connected to each other through a bus 404. An Input / Output (I / O) interface 405 is also connected to the bus 404.

[0181] Connected to the Input / Output (I / O) interface 405 are an input section 406 including an audio input device, a button switch, and the like; an output section 407 including a display and an audio output device, an indicator, and the like; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the Input / Output (I / O) interface 405 as necessary. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 410 as necessary, so that a computer program read therefrom is installed in the storage section 408 as necessary.

[0182] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing a computer program for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication section 409 and / or from the removable medium 411. When the computer program is executed by the Central Processing Unit (CPU) 401, various functions defined in the present application are performed.

[0183] Note that specific examples of computer-readable storage media can include but are not limited to an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, computer-readable storage media can be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0184] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functional processes, and operational processes, according to various embodiments of the present disclosure. Each block in the flow diagrams and the block diagrams can represent a module, a procedure, or a part of code that comprises one or more executable instructions for implementing the specific logical functions specified for the block. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures.

[0185] Specifically, the electronic device of the embodiment includes a processor and a memory, the memory is coupled with the one or more processors, and the memory is configured to store computer program code including computer instructions, and the one or more processors invoke the computer instructions to cause the electronic device to perform the method provided by the above-described embodiment.

[0186] As another aspect, the present disclosure also provides a computer-readable storage medium, which can be included in the electronic device described in the above-described embodiments, or can exist separately without being assembled into the electronic device. The storage medium carries one or more computer programs, and when the one or more computer programs are executed by a processor of the electronic device, the electronic device implements the method provided in the above-described embodiments.

[0187] The above-described embodiments are only used to illustrate the technical solutions of the present disclosure, rather than limiting them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present disclosure.

[0188] In the above embodiments, the term "when" can be interpreted to mean "if" or "after" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "on determining" or "if detecting (a stated condition or event)" can be interpreted to mean "if determining" or "in response to determining" or "on detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)" depending on the context.

[0189] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by a computer program instructing the relevant hardware to complete, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. The aforementioned storage medium includes ROM or random storage memory RAM, magnetic disk or optical disk and various storage program codes.

Claims

1. A method for managing medical personnel shift schedules, characterized in that, include: Acquire multidimensional profile data of medical personnel awaiting scheduling in the department and departmental resource map data. The multidimensional profile data includes at least one of the following: seniority, professional title, research workload, and home address of the medical personnel. The departmental resource map data includes the department's historical busy-idle cycle and heat map data of medical resource distribution. Based on the multidimensional profile data and the preset scheduling rules and shift requirements, a basic schedule is generated for a preset period. The basic schedule covers the regular workload of the medical personnel at a set percentage. The master schedule is initialized based on the basic schedule. The master schedule is used to store and manage the basic schedule and to reflect the current schedule status of the medical personnel in real time. Based on real-time medical demand data, the departmental resource map data, and the current status of the master schedule, dynamic adjustment information for the master schedule is generated, including new scheduling instructions or instructions to change existing shifts. The master schedule is updated in real time based on the dynamic adjustment information.

2. The method according to claim 1, characterized in that, The process of generating dynamic adjustment information for the master schedule based on real-time medical demand data, departmental resource map data, and the current status of the master schedule includes: Based on the real-time medical demand data and the departmental resource map data, the dynamic manpower shortage index of the current department is calculated. The real-time medical demand data includes the emergency patient flow, the number of critically ill patients, the real-time occupancy status of the operating room / examination room, and the urgent pending queue of diagnostic examinations in the department. Based on the dynamic manpower shortage index, a set of medical personnel that can be deployed is selected from the current status of the master schedule. Multidimensional matching degree conflict detection is performed on the set of available medical personnel to obtain the target personnel and target shifts that have passed the matching. The dynamic adjustment information is generated based on the target personnel and the target shift.

3. The method according to claim 2, characterized in that, The step of calculating the dynamic manpower shortage index of the current department based on the real-time medical demand data and the departmental resource map data includes: Based on the real-time medical demand data, the instantaneous number of medical personnel required by the department is calculated. Based on the historical busy / idle cycles in the departmental resource map data, determine the benchmark manpower allocation reference value for the current period; The dynamic manpower shortage index is generated based on the difference between the instantaneous demand for medical personnel and the baseline manpower configuration reference value, as well as the heat map data of medical resource distribution in the departmental resource map data.

4. The method according to claim 2, characterized in that, The step of performing multi-dimensional matching degree conflict detection on the set of deployable medical personnel to obtain the target personnel and target shifts that have passed the matching includes: Based on the multidimensional profile data and the target shift requirements, calculate the static matching score of each medical staff member for the current vacant shift; Based on the current status of the master schedule and the preset scheduling rules, dynamic conflict verification is performed on the medical personnel whose static matching scores meet the standards, and medical personnel who violate the hard constraints are screened out to obtain the medical personnel who pass the matching verification. Based on the real-time location status and continuous working hours of the verified medical personnel, the target personnel and target shifts are determined.

5. The method according to claim 4, characterized in that, The determination of target personnel and target shifts based on the verified real-time location status and continuous working hours of the medical personnel includes: Based on the real-time location status of the medical personnel, calculate the commuting cost factor for their arrival at the department corresponding to the target shift. Based on the continuous working hours recorded in the aforementioned shift schedule, calculate the fatigue attenuation coefficient for each medical staff member; Based on the commuting cost factor and fatigue attenuation coefficient, a spatiotemporal comprehensive score is generated; The medical personnel with the highest spatiotemporal comprehensive score and their corresponding shifts are identified as the target personnel and target shifts, respectively.

6. The method according to any one of claims 1-5, characterized in that, The initialization of the master schedule based on the basic schedule includes: Based on the shift allocation records in the basic shift schedule, a three-dimensional mapping relationship about time, position, and personnel is generated; Based on preset scheduling rules, the three-dimensional mapping relationship is checked for conflict compliance, and records that violate hard constraints are filtered out. The verified three-dimensional mapping relationship is transformed into an operable master schedule table with version identifiers. The master table includes time slots, status bits, and update interfaces.

7. The method according to any one of claims 1-5, characterized in that, After updating the master schedule in real time based on the dynamic adjustment information, the method further includes: During the execution of the updated master schedule, real-time data on the actual on-duty status of medical personnel and shift substitution events are collected to obtain schedule execution feedback records. Based on the difference analysis results between the scheduling execution feedback records and the scheduling master table, the historical busy / idle cycle of the department resource map data is dynamically corrected.

8. An electronic device, characterized in that, Includes one or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the electronic device to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium storing computer instructions, characterized in that, When the computer instructions are executed on the electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on an electronic device, it causes the electronic device to perform the method as described in any one of claims 1-7.

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