Hospital radiation equipment and radiation worker management system

Abstract

The invention relates to the technical field of radiation staff management, in particular to hospital radiation equipment and a radiation staff management system. The system comprises a prediction judgment unit, a plan generation unit, a priority allocation unit and a dynamic adjustment unit. A peak plan generation module is used for receiving a command of a peak period in a calculation and judgment module and a predicted demand fluctuation quantity, and the peak plan generation module obtains an overtime hour rate, a basic salary hour rate and working efficiency of a radiation worker from a demand prediction module; according to the overtime hour rate and the basic salary hour rate of the radiation staff, the cost of the minimum reasonable allocation is formulated, the constraint condition is formulated according to the working efficiency, the formulated cost of the minimum reasonable allocation and the formulated constraint condition are utilized to generate a peak period allocation plan, and the peak period allocation plan is reasonably formulated. Over-work or unbalanced workload of the staff can be avoided, the staff and the radiation equipment can be dispatched most effectively, and the working efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radiation staff management, in particular to a hospital radiation equipment and radiation staff management system. Background Art

[0002] With the continuous development of medical technology, the types and quantity of hospital equipment are increasing, and the size of the staff is gradually expanding. In particular, higher requirements are put forward for the supervision of radiation medical equipment and the special management of radiation staff and physical examinations. The management of hospital radiation equipment and radiation staff plays an important role in improving the operational efficiency of the hospital, but in the implementation process, it is also necessary to overcome technical, cost and personnel challenges. Since there are a large number of patients in the hospital who need the hospital's radiation equipment for physical examinations every day, and it is impossible to accurately predict the daily demand fluctuations for the use of hospital radiation equipment, it is impossible to reasonably formulate allocation plans for radiation staff according to the demand fluctuations for radiation equipment, causing radiation staff to overwork or have an unbalanced workload, which greatly reduces the work efficiency of radiation staff. Therefore, we provide a hospital radiation equipment and radiation staff management system. Summary of the invention

[0003] The object of the present invention is to provide a hospital radiation equipment and radiation staff management system to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned purpose, the present invention provides a hospital radiation equipment and radiation staff management system, including a prediction and judgment unit, a plan generation unit, a priority allocation unit, and a dynamic adjustment unit;

[0005] The prediction and judgment unit obtains the usage of the hospital's radiation equipment, historical data, and information on radiation staff, predicts demand fluctuations, calculates peak thresholds and valley thresholds for radiation equipment based on the predicted demand fluctuations, and uses the predicted demand fluctuations and peak thresholds or valley thresholds for radiation equipment to determine the high and low periods in a time period;

[0006] The plan generation unit is used to receive data from the prediction and judgment unit, obtain historical data from the prediction and judgment unit to formulate the cost of minimizing reasonable allocation and the set constraints, and generate a peak period allocation plan or a trough period allocation plan by using the formulated cost of minimizing reasonable allocation and the formulated constraints;

[0007] The priority allocation unit is used to receive data from the prediction and judgment unit and the plan generation unit, and to adjust the priority of the allocation plan for the generation of the trough period or the generation of the peak period according to the data in the prediction and judgment unit;

[0008] The dynamic adjustment unit is used to receive data from the prediction and judgment unit and the plan generation unit, and dynamically adjust the allocation plan by changing the generated trough period allocation plan or the generated peak period allocation plan according to the radiation history data.

[0009] As a further improvement of the technical solution, the prediction and judgment unit includes a demand prediction module and a calculation and judgment module;

[0010] The demand prediction module obtains the usage of hospital radiation equipment, historical data, and radiation staff information through log records, and takes the data of radiation equipment required for daily appointments and the data of radiation equipment required for emergency examinations from the historical data, and predicts the demand fluctuation amount according to the number of times the radiation equipment is required for daily appointments and the number of times the radiation equipment is required for emergency examinations;

[0011] Historical data includes data on the use of radiology equipment for daily appointments, data on the use of radiology equipment for emergency examinations, overtime hourly rates, basic salary hourly rates, and work efficiency of radiology staff;

[0012] The radiation worker information includes tracking the working hours of each radiation worker and the working status of the radiation worker;

[0013] The calculation and judgment module is used to receive the demand fluctuation predicted in the demand prediction module, calculate the mean according to the predicted demand fluctuation, and then calculate the standard deviation according to the calculated mean, calculate the peak threshold and the valley threshold of the radiation equipment according to the calculated mean and the calculated standard deviation, and use the predicted demand fluctuation and the peak threshold or the valley threshold of the radiation equipment to judge the high and low periods, and judge the high and low periods in the time period. The specific judgment situation includes:

[0014] Case ①: When the predicted demand fluctuation N is greater than the peak threshold G of the radiation equipment, it is the peak period, and the peak period command is passed to the peak plan generation module;

[0015] Case ②: When the predicted demand fluctuation N is less than the peak threshold D of the radiation equipment, it is the trough period, and the peak period command is passed to the trough plan generation module.

[0016] As a further improvement of the technical solution, the calculation and judgment module calculates the peak threshold and the valley threshold of the radiation equipment in the following steps:

[0017] Step 1: Collect the calculated mean The peak threshold of the radiation equipment is calculated by the calculated standard deviation s, and the peak threshold of the radiation equipment G is obtained. The specific algorithm formula is:

[0018]

[0019] Where k is a constant, usually taking the value of (1,2), which is used to adjust the coefficient of the peak threshold of the radiation equipment;

[0020] Step 2: Collect the calculated mean The peak threshold of the radiation equipment is calculated by the calculated standard deviation s, and the trough threshold D of the radiation equipment is obtained. The specific algorithm formula is:

[0021]

[0022] As a further improvement of the technical solution, the plan generation unit includes a peak plan generation module and a valley plan generation module;

[0023] The peak plan generation module is used to receive the peak period command and the predicted demand fluctuation in the calculation and judgment module, and the peak plan generation module obtains the overtime hourly rate, basic salary hourly rate, and work efficiency of the radiation staff in the historical data from the demand prediction module, and uses the objective function to formulate the minimum reasonable allocation cost according to the overtime hourly rate and basic salary hourly rate of the radiation staff, formulates constraints according to the work efficiency, and generates a peak period allocation plan by formulating the minimum reasonable allocation cost and the formulated constraints;

[0024] The valley plan generation module is used to receive valley period commands from the calculation and judgment module, and generate a valley period allocation plan by formulating the cost of minimizing reasonable allocation and formulating constraints.

[0025] As a further improvement of the technical solution, the peak plan generation module uses the objective function to formulate the cost realization principle of minimizing reasonable allocation:

[0026] Collect overtime hourly rates for radiation workers C over , Basic wage hourly rate C work And formulate the cost of minimizing reasonable allocation, and obtain the cost Cb of minimizing reasonable allocation. The specific algorithm formula is:

[0027]

[0028] Among them, x it refers to the number of working hours of radiation worker i in time period t, y it It refers to the number of overtime hours worked by radiation worker i in time period t.

[0029] As a further improvement of the technical solution, the steps of formulating constraint conditions in the peak plan generation module are as follows:

[0030] Step 1: Collect the number of working hours x of radiation worker i in time period t it , the number of overtime hours y of radiation worker i in time period tit , work efficiency eff and predicted demand fluctuation N to formulate the demand conditions for total working hours and overtime hours within the time period;

[0031]

[0032] Among them, eff it It refers to the work efficiency of radiation worker i in time period t, symbol This means that for all time periods t;

[0033] Step 2: According to the number of working hours x of radiation worker i in time period t it Establishing work hour limits for radiation workers;

[0034]

[0035] Among them, W i Refers to the maximum number of hours available for work by radiation worker i;

[0036] Step 3: According to the number of working hours x of radiation worker i in time period t it Establish constraints on rest time;

[0037] If x it >0, then Z i(t+1) =1 and Z i(t+2) =1 for R i =2 hours;

[0038] z it is a binary variable used to indicate whether worker i takes a break during time period t. If z it =1, it means that worker i is resting in time period t; if z it =0, it means that worker i is working in time period t;

[0039] x it represents the working time of worker i in time period t. If x it >0, indicating that worker i actually has work in time period t;

[0040] R i represents the rest requirement of worker i, when R i =2 hours means that after working, worker i needs to rest for the next two hours.

[0041] As a further improvement of the present technical solution, the priority allocation unit is used to receive the predicted amount of emergency examinations in the demand prediction module; receive the trough period allocation plan generated in the trough plan generation module or the peak period allocation plan generated in the peak plan generation module, and use linear programming to adjust the priority of the trough period allocation plan or the peak period allocation plan according to the predicted amount of emergency examinations.

[0042] As a further improvement of the present technical solution, the dynamic adjustment unit is used to receive the radiation staff information in the demand prediction module, receive the low-period allocation plan generated in the low-period plan generation module or the peak-period allocation plan generated in the peak plan generation module, obtain the working status of the radiation staff from the radiation staff information, and use dynamic optimization technology to dynamically adjust the allocation plan according to the working status of the radiation staff to generate the low-period allocation plan or generate the peak-period allocation plan.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. In the hospital's radiological equipment and radiological staff management system, a peak plan generation module is used to receive peak period commands and predicted demand fluctuations in the calculation and judgment module. The peak plan generation module obtains the overtime hourly rate, basic salary hourly rate, and work efficiency of radiological staff in historical data from the demand prediction module, and formulates the minimum reasonable allocation cost based on the overtime hourly rate and basic salary hourly rate of the radiological staff, formulates constraints based on work efficiency, and generates a peak period allocation plan using the formulated minimum reasonable allocation cost and formulated constraints. By reasonably formulating the allocation plan, it is possible to avoid excessive work or unbalanced workload of employees, and to enable the most effective scheduling of staff and radiological equipment, thereby improving work efficiency.

[0045] 2. In the hospital's radiological equipment and radiological staff management system, the priority allocation unit is used to receive the emergency examination volume predicted in the demand forecasting module, receive the trough period allocation plan generated in the trough plan generation module or the peak period allocation plan generated in the peak plan generation module, and adjust the priority of the trough period allocation plan or the peak period allocation plan according to the predicted emergency examination volume. When the peak period is predicted, the resource allocation for emergency examinations is increased in advance to ensure that there are sufficient resources to cope with emergency examinations during high demand periods, thereby improving response speed and service quality.

[0046] 3. In the hospital's radiological equipment and radiological staff management system, the dynamic adjustment unit is used to receive the radiological staff information in the demand forecasting module, receive the trough period allocation plan generated in the trough plan generation module or the peak period allocation plan generated in the peak plan generation module, obtain the working status of the radiological staff from the radiological staff information, dynamically adjust the allocation plan according to the working status of the radiological staff, dynamically adjust the staffing according to the changes in the actual workload, optimize the use of equipment and the deployment of personnel, ensure that the staff does not overwork during busy periods, and improve the quality and efficiency of medical services. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is an overall block diagram of the present invention;

[0048] Figure 2 This is a block diagram of the prediction and judgment unit of the present invention.

[0049] The meaning of each number in the figure is:

[0050] 1. Forecasting and judgment unit; 11. Demand forecasting module; 12. Calculation and judgment module;

[0051] 2. Generate planning unit; 21. Generate peak planning module; 22. Generate trough planning module;

[0052] 3. Priority allocation unit; 4. Dynamic adjustment unit. DETAILED DESCRIPTION

[0053] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Example 1

[0055] The present invention provides a hospital radiation equipment and radiation staff management system, please refer to Figure 1-Figure 2 , including a prediction and judgment unit 1, a plan generation unit 2, a priority allocation unit 3, and a dynamic adjustment unit 4;

[0056] The prediction and judgment unit 1 obtains the usage, historical data, and information of radiation staff of the hospital's radiation equipment, predicts the demand fluctuation, calculates the peak threshold and trough threshold of the radiation equipment according to the predicted demand fluctuation, and uses the predicted demand fluctuation and the peak threshold or trough threshold of the radiation equipment to judge the high and low period conditions in the time period; the plan generation unit 2 is used to receive the data in the prediction and judgment unit 1, and the plan generation unit 2 obtains historical data from the prediction and judgment unit 1 to formulate the cost and constraints that minimize reasonable allocation, and uses the formulated cost and constraints to minimize reasonable allocation to generate a peak allocation plan or a trough allocation plan; the priority allocation unit 3 is used to receive the data in the prediction and judgment unit 1 and the plan generation unit 2, and adjusts the allocation plan according to the priority of generating a trough allocation plan or generating a peak allocation plan according to the data in the prediction and judgment unit 1; the dynamic adjustment unit 4 is used to receive the data in the prediction and judgment unit 1 and the plan generation unit 2, and dynamically adjusts the allocation plan according to the changes in the trough allocation plan or generating a peak allocation plan according to the radiation historical data.

[0057] The following is a refinement of the above units, see Figure 1-Figure 2 ;

[0058] The prediction and judgment unit 1 includes a demand prediction module 11 and a calculation and judgment module 12;

[0059] The demand prediction module 11 obtains the usage of hospital radiation equipment, historical data, and radiation staff information through log records, and takes the data of radiation equipment required for daily appointments and the data of radiation equipment required for emergency examinations from the historical data, and predicts the demand fluctuation amount according to the number of times the radiation equipment is required for daily appointments and the number of times the radiation equipment is required for emergency examinations. By predicting the demand fluctuation, the use time of the radiation equipment can be arranged more reasonably to avoid idleness or overuse of the equipment, and it can ensure that the equipment is fully utilized during high demand periods and remains moderately idle during low demand periods;

[0060] The use of hospital radiology equipment includes recording the time the equipment is in use;

[0061] Historical data includes data on the use of radiology equipment for daily appointments, data on the use of radiology equipment for emergency examinations, overtime hourly rates, basic salary hourly rates, and work efficiency of radiology staff;

[0062] The radiation worker information includes tracking the working hours of each radiation worker and the working status of the radiation worker;

[0063] Steps to predict demand fluctuations:

[0064] Step ①, input the data Rc of radiation equipment required for daily appointments into the autoregressive model. The autoregressive model outputs the corresponding model parameters α, β and the random error term ε generated in the autoregressive model, as well as the observation value R at time t-1 and t-2. The daily appointment quantity is predicted based on the model parameters α, β random error term ε and the observation value R, and the predicted daily quantity Rc is obtained. The specific algorithm formula is:

[0065] Rc=αR(t-1)+βR(t-2)+ε t ;

[0066] Among them, R(t-1) refers to the observation value of the previous moment, R(t-2) refers to the observation value of the previous two moments, and ε t Refers to the random error term ε at this moment;

[0067] Step ②, input the radiological equipment data JZ required for emergency examinations into the autoregressive model. The autoregressive model outputs the corresponding model parameters γ, δ and the random error term η generated in the autoregressive model, as well as the observed values ​​E at time t-1 and t-2. The emergency examination volume is predicted based on the model parameters γ, δ, the random error term η, and the observed value E to obtain the predicted emergency examination volume JZ. The specific algorithm formula is:

[0068] Jz=γE(t-1)+δE(t-2)+η t ;

[0069] Among them, E(t-1) refers to the observation value of the previous moment, E(t-2) refers to the observation value of the previous two moments, and η t Refers to the random error term η at this moment;

[0070] Step ③, calculate the demand fluctuation amount according to the predicted emergency examination volume JZ and the predicted daily volume Rc. The predicted demand fluctuation amount is the calculated demand fluctuation amount N. The specific algorithm formula is:

[0071] N(t)=Rc(t)+Jz(t);

[0072] Among them, N(t) refers to the predicted demand fluctuation N at time t, Rc(t) refers to the predicted daily volume Rc at time t, and Jz(t) refers to the predicted emergency examination volume JZ;

[0073] The calculation and judgment module 12 is used to receive the demand fluctuation predicted by the demand prediction module 11, calculate the mean value according to the predicted demand fluctuation value, and then calculate the standard deviation according to the calculated mean value, calculate the peak threshold value and the valley threshold value of the radiation equipment according to the calculated mean value and the calculated standard deviation, and use the predicted demand fluctuation value and the peak threshold value or the valley threshold value of the radiation equipment to judge the high and low periods, judge the high and low period conditions in the time period, and make reference to the reasonable and accurate allocation in the later stage;

[0074] Principle of calculating mean:

[0075] Collect the predicted demand fluctuations N and calculate the mean to obtain the calculated mean Specific algorithm formula:

[0076]

[0077] Among them, T represents the total time points;

[0078] The implementation principle of calculating standard deviation:

[0079] Get the calculated mean And calculate the standard deviation to obtain the calculated standard deviation s. The specific algorithm formula is:

[0080]

[0081] Among them, N i Refers to the demand fluctuation of the ith forecast;

[0082] The calculation and judgment module 12 calculates the peak threshold and the valley threshold of the radiation device to implement the steps:

[0083] Step 1: Collect the calculated mean The peak threshold of the radiation equipment is calculated by the calculated standard deviation s, and the peak threshold of the radiation equipment G is obtained. The specific algorithm formula is:

[0084]

[0085] Where k is a constant, usually taking the value of (1,2), which is used to adjust the coefficient of the peak threshold of the radiation equipment;

[0086] Step 2: Collect the calculated mean The peak threshold of the radiation equipment is calculated by the calculated standard deviation s, and the trough threshold D of the radiation equipment is obtained. The specific algorithm formula is:

[0087]

[0088] Specific judgment situations include:

[0089] Case ①: When the predicted demand fluctuation N is greater than the peak threshold G of the radiation equipment, it is the peak period, and the peak period command is transmitted to the peak plan generation module 21;

[0090] Case ②: When the predicted demand fluctuation N is less than the peak threshold D of the radiation equipment, it is the valley period, and the peak period command is passed to the valley plan generation module 22.

[0091] The plan generating unit 2 includes a peak plan generating module 21 and a valley plan generating module 22;

[0092] The peak plan generation module 21 is used to receive the peak period command and the predicted demand fluctuation in the calculation and judgment module 12. The peak plan generation module 21 obtains the overtime hourly rate, basic wage hourly rate, and work efficiency of the radiation staff in the historical data from the demand prediction module 11, and uses the objective function to formulate the minimum reasonable allocation cost according to the overtime hourly rate and basic wage hourly rate of the radiation staff, formulates constraints according to the work efficiency, and generates a peak period allocation plan by formulating the minimum reasonable allocation cost and the formulated constraints. By reasonably formulating the allocation plan, it is possible to avoid excessive work or uneven workload of employees, and it is possible to make the staff and radiation equipment get the most effective scheduling, thereby improving work efficiency;

[0093] The peak plan generation module 21 uses the objective function to formulate the cost realization principle of minimizing the reasonable allocation:

[0094] Collect overtime hourly rates for radiation workers C over , Basic wage hourly rate C work And formulate the cost of minimizing reasonable allocation, and obtain the cost Cb of minimizing reasonable allocation. The specific algorithm formula is:

[0095]

[0096] Among them, x it refers to the number of working hours of radiation worker i in time period t, y it It refers to the number of overtime hours worked by radiation worker i in time period t;

[0097] Steps for implementing constraints in generating peak plan module 21:

[0098] Step 1: Collect the number of working hours x of radiation worker i in time period t it , the number of overtime hours y of radiation worker i in time period t it , work efficiency eff and predicted demand fluctuation N to formulate the demand conditions for total working hours and overtime hours within the time period;

[0099]

[0100] Among them, eff it It refers to the work efficiency of radiation worker i in time period t, symbol This means that for all time periods t;

[0101] Step 2: According to the number of working hours x of radiation worker i in time period t itEstablishing work hour limits for radiation workers;

[0102]

[0103] Among them, W i Refers to the maximum number of hours available for work by radiation worker i;

[0104] Step 3: According to the number of working hours x of radiation worker i in time period t it Establish constraints on rest time;

[0105] If x it >0, then Z i(t+1) =1 and Z i(t+2) =1 for R i =2 hours;

[0106] z it is a binary variable used to indicate whether worker i takes a break during time period t. If z it =1, it means that worker i is resting in time period t; if z it =0, it means that worker i is working in time period t;

[0107] x it represents the working time of worker i in time period t. If x it >0, indicating that worker i actually has work in time period t;

[0108] R i represents the rest requirement of worker i, when R i = 2 hours means that after working, worker i needs to rest for the next two hours;

[0109] The valley plan generation module 22 is used to receive the valley period command from the calculation and judgment module 12, and the peak plan generation module 21 obtains the overtime hourly rate, basic wage hourly rate, and work efficiency of the radiation workers in the historical data from the demand prediction module 11, and uses the objective function to formulate the minimum reasonable allocation cost according to the overtime hourly rate and basic wage hourly rate of the radiation workers, formulates constraints according to the work efficiency, and generates the valley period allocation plan by formulating the minimum reasonable allocation cost and the formulated constraints (the operation steps of generating the valley period allocation plan are the same as those of generating the peak period allocation plan mentioned above);

[0110] The priority allocation unit 3 is used to receive the emergency examination volume predicted in the demand prediction module 11; receive the trough period allocation plan generated in the trough plan generation module 22 or the peak period allocation plan generated in the peak plan generation module 21, and use linear programming to adjust the priority of the trough period allocation plan or the peak period allocation plan according to the predicted emergency examination volume. When the peak period is predicted, the resource allocation for emergency examinations is increased in advance (such as adding staff or equipment) to ensure that there are sufficient resources to cope with emergency examinations during high demand periods, thereby improving response speed and service quality.

[0111] The dynamic adjustment unit 4 is used to receive the radiation staff information in the demand prediction module 11, receive the off-peak period allocation plan generated in the off-peak period plan generation module 22 or the peak period allocation plan generated in the peak period plan generation module 21, obtain the working status of the radiation staff from the radiation staff information, and use dynamic optimization technology to dynamically adjust the allocation plan according to the working status of the radiation staff to generate the off-peak period allocation plan or the peak period allocation plan, and dynamically adjust the personnel allocation according to the changes in the actual workload to ensure that the staff will not overwork during busy periods and will not be idle during the off-peak period, thereby improving work efficiency.

[0112] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. Hospital radiation equipment and radiation staff management system, characterized by: It includes a prediction and judgment unit (1), a plan generation unit (2), a priority allocation unit (3), and a dynamic adjustment unit (4); The prediction and judgment unit (1) obtains the usage of the hospital's radiation equipment, historical data, and information on radiation staff, predicts demand fluctuations, calculates the peak threshold and valley threshold of the radiation equipment based on the predicted demand fluctuations, and uses the predicted demand fluctuations and the peak threshold or valley threshold of the radiation equipment to judge the high and low periods in a time period; The plan generation unit (2) is used to receive data from the prediction and judgment unit (1), and the plan generation unit (2) obtains historical data from the prediction and judgment unit (1) to formulate the cost of minimizing reasonable allocation and the set constraints, and uses the formulated cost of minimizing reasonable allocation and the formulated constraints to generate a peak period allocation plan or a trough period allocation plan; The priority allocation unit (3) is used to receive data from the prediction and judgment unit (1) and the plan generation unit (2), and to adjust the priority of the allocation plan for generating a low-peak period allocation plan or generating a peak period allocation plan according to the data in the prediction and judgment unit (1); The dynamic adjustment unit (4) is used to receive data from the prediction and judgment unit (1) and the plan generation unit (2), and dynamically adjust the distribution plan by changing the distribution plan for the trough period or the distribution plan for the peak period according to the radiation history data.

2. The hospital radiation equipment and radiation staff management system according to claim 1, characterized in that: The prediction and judgment unit (1) comprises a demand prediction module (11) and a calculation and judgment module (12); The demand prediction module (11) obtains the usage of hospital radiation equipment, historical data, and radiation staff information through log records, and takes the data of radiation equipment required for daily appointments and the data of radiation equipment required for emergency examinations from the historical data, and predicts the demand fluctuation amount according to the number of times the radiation equipment is required for daily appointments and the number of times the radiation equipment is required for emergency examinations; Historical data includes data on the use of radiology equipment for daily appointments, data on the use of radiology equipment for emergency examinations, overtime hourly rates, basic salary hourly rates, and work efficiency of radiology staff; The radiation worker information includes tracking the working hours of each radiation worker and the working status of the radiation worker; The calculation and judgment module (12) is used to receive the demand fluctuation predicted by the demand prediction module (11), calculate the mean value according to the predicted demand fluctuation value, and then calculate the standard deviation according to the calculated mean value, calculate the peak threshold value and the valley threshold value of the radiation equipment according to the calculated mean value and the calculated standard deviation, and use the predicted demand fluctuation value and the peak threshold value or the valley threshold value of the radiation equipment to judge the high and low periods, and judge the high and low period conditions in the time period, and the specific judgment conditions include: Case ①: When the predicted demand fluctuation N is greater than the peak threshold G of the radiation equipment, it is the peak period, and the peak period command is transmitted to the peak plan generation module (21); Case ②: When the predicted demand fluctuation N is less than the peak threshold D of the radiation equipment, it is the valley period, and the peak period command is passed to the valley plan generation module (22).

3. The hospital radiation equipment and radiation staff management system according to claim 2, characterized in that: The calculation and judgment module (12) implements the steps of calculating the peak threshold and the valley threshold of the radiation device: Step 1: Collect the calculated mean The peak threshold of the radiation equipment is calculated by the calculated standard deviation s, and the peak threshold of the radiation equipment G is obtained. The specific algorithm formula is: Where k is a constant, usually taking the value of (1,2), which is used to adjust the coefficient of the peak threshold of the radiation equipment; Step 2: Collect the calculated mean The peak threshold of the radiation equipment is calculated by the calculated standard deviation s, and the trough threshold D of the radiation equipment is obtained. The specific algorithm formula is:

4. The hospital radiation equipment and radiation staff management system according to claim 2, characterized in that: The plan generating unit (2) comprises a peak plan generating module (21) and a valley plan generating module (22); The peak plan generation module (21) is used to receive the peak period command and the predicted demand fluctuation amount in the calculation and judgment module (12), and the peak plan generation module (21) obtains the overtime hourly rate, basic salary hourly rate, and work efficiency of the radiation workers in the historical data from the demand prediction module (11), and uses the objective function to formulate the minimum reasonable allocation cost according to the overtime hourly rate and basic salary hourly rate of the radiation workers, formulates the constraint conditions according to the work efficiency, and generates the peak period allocation plan by using the formulated minimum reasonable allocation cost and the formulated constraint conditions; The valley plan generation module (22) is used to receive the valley period command from the calculation and judgment module (12), and generate a valley period allocation plan by formulating the cost of minimizing reasonable allocation and the formulated constraint conditions.

5. The hospital radiation equipment and radiation staff management system according to claim 4, characterized in that: The peak plan generation module (21) uses the objective function to formulate the cost realization principle of minimizing reasonable allocation: Collect overtime hourly rates for radiation workers C over , Basic wage hourly rate C work And formulate the cost of minimizing reasonable allocation, and obtain the cost Cb of minimizing reasonable allocation. The specific algorithm formula is: Among them, x it refers to the number of working hours of radiation worker i in time period t, y it It refers to the number of overtime hours worked by radiation worker i in time period t.

6. The hospital radiation equipment and radiation staff management system according to claim 4, characterized in that: The steps of implementing the constraint conditions in the peak plan generation module (21) are as follows: Step 1: Collect the number of working hours x of radiation worker i in time period t it , the number of overtime hours y of radiation worker i in time period t it , work efficiency eff and predicted demand fluctuation N to formulate the demand conditions for total working hours and overtime hours within the time period; Among them, eff it It refers to the work efficiency of radiation worker i in time period t, symbol This means that for all time periods t; Step 2: According to the number of working hours x of radiation worker i in time period t it Establishing work hour limits for radiation workers; Among them, W i Refers to the maximum number of hours available for work by radiation worker i; Step 3: According to the number of working hours x of radiation worker i in time period t it Establish constraints on rest time; If x it >0, then Z i(t+1) =1 and Z i(t+2) =1 for R i =2 hours; z it is a binary variable used to indicate whether worker i takes a break during time period t. If z it =1, it means that worker i is resting in time period t; if z it =0, it means that worker i is working in time period t; x it represents the working time of worker i in time period t. If x it >0, indicating that worker i actually has work in time period t; R i represents the rest requirement of worker i, when R i = 2 hours means that after working, worker i needs to rest for the next two hours.

7. The hospital radiation equipment and radiation staff management system according to claim 4, characterized in that: The priority allocation unit (3) is used to receive the emergency examination volume predicted in the demand prediction module (11), receive the valley period allocation plan generated in the valley plan generation module (22) or the peak period allocation plan generated in the peak plan generation module (21), and use linear programming to adjust the priority of the valley period allocation plan or the peak period allocation plan according to the predicted emergency examination volume.

8. The hospital radiation equipment and radiation staff management system according to claim 4, characterized in that: The dynamic adjustment unit (4) is used to receive the radiation worker information in the demand prediction module (11), receive the valley period allocation plan generated in the valley period plan generation module (22) or the peak period allocation plan generated in the peak period plan generation module (21), obtain the working status of the radiation worker from the radiation worker information, and use dynamic optimization technology to dynamically adjust the allocation plan by changing the valley period allocation plan or the peak period allocation plan according to the working status of the radiation worker.

Images