A multi-hospital red blood cell transport decision-making method integrating blood type substitution rules

Abstract

The present invention provides a multi-hospital red blood cell transport decision-making method that integrates blood type substitution rules, and relates to the field of red blood cell transport decision technology. In the present invention, first, a real-time inventory database of all hospitals in the target area is established; secondly, hospitals with red blood cell shortages are detected, and candidate red blood cell transport hospitals and their candidate transport blood types are screened; thirdly, a multi-hospital transport decision model is constructed with blood type substitution, storage age, transport cost, and shortage penalty as comprehensive optimization goals; finally, the multi-hospital transport decision model is solved to determine the final red blood cell transport hospital and its transport blood type, and red blood cell transport volume. By strengthening transport cooperation among multiple hospitals in the region, idle red blood cells are transported across hospitals, and the red blood cell storage age and blood type substitution rules are incorporated into transport decisions, the range of red blood cells that can participate in transport is expanded, the red blood cell shortage phenomenon is effectively suppressed, and red blood cell resources are fully utilized, especially the use of red blood cells with larger storage age is greatly increased, thereby reducing resource waste.

Description

Technical Field

[0001] The present invention relates to the technical field of red blood cell transport decision-making, and in particular to a multi-hospital red blood cell transport decision-making method integrating blood type substitution rules. Background Art

[0002] Red blood cells (RBCs), a common medical resource, are essential in surgical procedures and the treatment of hematological diseases. However, due to their short shelf life, fluctuating demand, and high urgency, their supply chain faces numerous challenges. On the one hand, uneven distribution of RBC inventory across hospitals and emergencies (such as surgeries or accidents) often lead to shortages of specific blood types. On the other hand, RBCs that are not used promptly are easily wasted due to expiration, further exacerbating the imbalance in resource allocation.

[0003] In related technologies, examples of traditional red blood cell supply chain management solutions are as follows:

[0004] Reference 1 (Multi-objective two-stage emergency blood transport allocation under the COVID-19 epidemic [J]. Complex and Intelligent Systems, 2023, 9(5): 4939-4957.) proposed a new two-stage multi-objective optimization model for emergency blood transport allocation. The objectives considered were to optimize the quality of transported blood, meet blood demand, and the total cost including shortage penalties. An improved hybrid multi-objective whale optimization algorithm (MOWOA) with a greedy rule was then designed to solve the model.

[0005] Reference 2 (Casucci S, Walteros JL, Bhandawat R. A two-stage stochastic programming framework for blood product inventory management with ABOsubstitution and lateral transshipment[J]. IISE Transactions on HealthcareSystems Engineering, 2024, 14(4): 362-383.) proposes a two-stage stochastic optimization model for managing the inventory of a two-echelon blood supply chain consisting of a network of blood centers, hospitals, and transfusion sites. The proposed model determines the optimal distribution quantity for the entire supply chain while taking into account the stochastic demand and perishability of blood products. In addition, the model utilizes redistribution methods such as lateral transshipment and ABO-compatibility-based blood substitution as corrective measures to minimize the expiration and shortage of blood products throughout the blood supply chain.

[0006] However, for the red blood cell transportation of blood products, related technologies represented by the above-mentioned solutions mainly focus on using transportation decisions between regional blood stations or within the overall blood product supply chain to solve shortage or redistribution problems. This cannot truly solve the red blood cell shortage caused by patients' daily needs among multiple hospitals in the region and the problem that red blood cells themselves are easily expired. Summary of the Invention

[0007] (1) Technical problems solved

[0008] In response to the shortcomings of the existing technology, the present invention provides a multi-hospital red blood cell transport decision-making method that integrates blood type substitution rules, which solves the problems of red blood cell shortages and the easy expiration of red blood cells caused by patients' daily needs among multiple hospitals in the region.

[0009] (2) Technical solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0011] A multi-hospital red blood cell transport decision-making method integrating blood type substitution rules, including:

[0012] Establish a real-time inventory database for all hospitals in the target area to record the blood type, age, and quantity of red blood cells in each hospital's daily inventory;

[0013] Detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types in the candidate red blood cell transfer hospitals based on blood type substitution rules generated from actual medical specifications;

[0014] Based on the candidate red blood cell transfer hospitals and their candidate transfer blood types, a multi-hospital transfer decision model is constructed with blood type replacement, storage age, transfer cost, and shortage penalty as comprehensive optimization objectives; wherein, the storage age item corresponding to the storage age is constructed as follows:

[0015] Obtain the transport weight coefficients of red blood cells of different storage ages, and obtain the red blood cell transport volume of each candidate transport blood type with different storage ages received by the current red blood cell shortage hospital from any candidate red blood cell transport hospital every day, and construct the storage age item;

[0016] Solve the multi-hospital transport decision model to obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transport blood type, and red blood cell transport volume.

[0017] Preferably, the screening of candidate red blood cell transfer hospitals for the red blood cell shortage hospital based on a preset urgency determination function includes:

[0018] Construct decision variables to determine whether the current RBC shortage hospital is in urgent shortage;

[0019] Obtain the basic travel time between the current red blood cell shortage hospital and any candidate red blood cell transfer hospital to be screened, as well as the real-time traffic factors affected by external factors;

[0020] Obtain the current waiting time limits for patients in hospitals with RBC shortages;

[0021] The decision variables, basic traffic time, real-time road condition factor and time limit are used as inputs of the urgency determination function to obtain corresponding results, and all candidate red blood cell transfer hospitals with corresponding results less than or equal to one are screened out for the current red blood cell shortage hospital.

[0022] Preferably, the blood type substitution rules include blood type substitution relationships and blood type substitution priorities under the RH blood type system.

[0023] Preferably, the process of constructing the comprehensive optimization target includes:

[0024] The blood type substitution term is constructed by obtaining the weight coefficient of each candidate blood type according to the priority of different blood type substitutions, and obtaining the red blood cell transfer volume of each candidate blood type received by the current red blood cell shortage hospital from any candidate red blood cell transfer hospital every day.

[0025] The transport cost item is constructed by combining the real-time traffic factor and the unit transport cost of transporting red blood cells to the hospital currently short of red blood cells;

[0026] Obtain the red blood cell shortage of each candidate blood type in the hospital with current red blood cell shortage every day, and construct a shortage penalty term;

[0027] The blood type substitution item, the storage age item, the transportation cost item and the shortage penalty item are weighted and integrated to construct the comprehensive optimization goal.

[0028] Preferably, the multi-hospital transfer decision model includes the following constraints:

[0029] (1) Current RBC shortage: The hospital's real-time RBC shortage is equal to the demand minus the inventory;

[0030] (2) The red blood cell shortage at the end of each day in the hospital with current red blood cell shortage is equal to the shortage minus the transport volume;

[0031] (3) The amount of red blood cells transferred from any candidate red blood cell transfer hospital does not exceed the amount of red blood cell shortage in the current red blood cell shortage hospital;

[0032] (4) The remaining red blood cell inventory after the transfer of any candidate red blood cell transfer hospital must not be less than the red blood cell safety inventory that the hospital needs to retain;

[0033] (5) The result of the urgency judgment function must be less than or equal to one, in order to screen out candidate red blood cell transport hospitals that meet the transport time constraints and patient condition constraints;

[0034] (6) The red blood cell transport volume of any candidate transport blood type from any candidate red blood cell transport hospital does not exceed the red blood cell transportable volume of that candidate transport blood type in the candidate red blood cell transport hospital;

[0035] (7) The first non-negative constraint ensures that the red blood cell transfer volume of any candidate blood type from any candidate red blood cell transfer hospital is not negative;

[0036] (8) The second non-negative constraint ensures that the amount of red blood cell safety stock required to be retained from any candidate red blood cell transport hospital is not negative;

[0037] (9) The red blood cell transportable volume of any candidate blood type in any candidate red blood cell transport hospital is greater than zero, ensuring that only hospitals with transportable volume participate in the transport;

[0038] (10) Any candidate transfer blood type meets the blood type substitution rules.

[0039] Preferably, the service level that the general hospital expects to achieve, the time for which the red blood cell inventory needs to be guaranteed, the red blood cell replenishment cycle, and the daily demand for red blood cells are obtained to obtain the red blood cell safety inventory of any candidate red blood cell transport hospital and any candidate transport blood type.

[0040] Preferably, for any candidate red blood cell transport hospital and any candidate transport blood type, the red blood cell transportable quantity is equal to the current inventory of the candidate transport blood type minus the red blood cell safety inventory of the blood type.

[0041] A multi-hospital red blood cell transport decision-making system integrating blood type substitution rules, including:

[0042] A database establishment module is used to establish a real-time inventory database for all hospitals in the target area to record the blood type, age and quantity of the daily red blood cell inventory of each hospital;

[0043] an information screening module for detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types among the candidate red blood cell transfer hospitals based on blood type substitution rules generated from actual medical specifications;

[0044] The model construction module is used to construct a multi-hospital transport decision model based on the candidate red blood cell transport hospitals and the candidate transport blood types, with blood type replacement, storage age, transport cost, and shortage penalty as the comprehensive optimization objectives; wherein the storage age item corresponding to the storage age is constructed as follows:

[0045] Obtain the transport weight coefficients of red blood cells of different storage ages, and obtain the red blood cell transport volume of each candidate transport blood type with different storage ages received by the current red blood cell shortage hospital from any candidate red blood cell transport hospital every day, and construct the storage age item;

[0046] The model solving module is used to solve the multi-hospital transport decision model and obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transport blood type, and red blood cell transport volume.

[0047] A storage medium stores a computer program for multi-hospital red blood cell transport decision-making integrated with blood type substitution rules, wherein the computer program enables a computer to control the multi-hospital red blood cell transport decision-making method as described above.

[0048] An electronic device, comprising:

[0049] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the programs including a method for controlling the multi-hospital red blood cell transport decision-making method as described above.

[0050] (3) Beneficial effects

[0051] The present invention provides a multi-hospital red blood cell transport decision-making method that incorporates blood type substitution rules. Compared with existing technologies, it has the following advantages:

[0052] In the present invention, first, a real-time inventory database of all hospitals in the target area is established; second, hospitals with red blood cell shortages are detected, and candidate red blood cell transfer hospitals are screened based on the urgency judgment function, and candidate transfer blood types are screened based on the blood type substitution rule; third, a multi-hospital transfer decision model is constructed with blood type substitution, storage age, transfer cost, and shortage penalty as the comprehensive optimization goals; finally, the multi-hospital transfer decision model is solved to determine the final red blood cell transfer hospital, its transfer blood type, and red blood cell transfer volume. By strengthening the transfer collaboration between multiple hospitals in the region, idle red blood cells are transferred across hospitals, and the red blood cell storage age and blood type substitution rules are incorporated into the transfer decision, the range of red blood cells that can participate in the transfer is expanded, the red blood cell shortage phenomenon is effectively suppressed, and the red blood cell resources are fully utilized, especially the use of red blood cells with larger storage age is greatly increased, thereby reducing resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 A flowchart of a multi-hospital red blood cell transport decision-making method integrating blood type substitution rules provided in an embodiment of the present invention.

[0055] Figure 2 A schematic diagram of a multi-hospital red blood cell transport decision-making scenario provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0057] The embodiment of the present application solves the problem of red blood cell shortage and the easy expiration of red blood cells among multiple hospitals in a region due to daily needs of patients by providing a multi-hospital red blood cell transportation decision-making method that integrates blood type substitution rules.

[0058] The technical solution in the embodiments of the present application is to solve the above technical problems, and the overall idea is as follows:

[0059] 1) How can multiple hospitals in the same region establish an inter-hospital red blood cell transfer mechanism based on blood type substitution rules and use transfer decisions to solve the red blood cell shortage problem faced by hospitals in daily processing of patient red blood cell transfusions?

[0060] 2) Incorporate the characteristics of red blood cells themselves - storage age - into transportation decisions. Consider the specific storage age of red blood cells during transportation and give priority to the use of red blood cells that are about to expire. While solving the shortage of red blood cells, it further reduces the possibility of red blood cell expiration, increases the utilization rate of red blood cells, and reduces resource waste.

[0061] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0062] An embodiment of the present invention provides a multi-hospital red blood cell transport decision-making method integrating blood type substitution rules, comprising:

[0063] Establish a real-time inventory database for all hospitals in the target area to record the blood type, age, and quantity of red blood cells in each hospital's daily inventory;

[0064] Detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types in the candidate red blood cell transfer hospitals based on blood type substitution rules generated from actual medical specifications;

[0065] Based on the candidate red blood cell transfer hospitals and their candidate transfer blood types, a multi-hospital transfer decision model is constructed with blood type replacement, storage age, transfer cost, and shortage penalty as comprehensive optimization objectives; wherein, the storage age item corresponding to the storage age is constructed as follows:

[0066] Obtain the transport weight coefficients of red blood cells of different storage ages, and obtain the red blood cell transport volume of each candidate transport blood type with different storage ages received by the current red blood cell shortage hospital from any candidate red blood cell transport hospital every day, and construct the storage age item;

[0067] Solve the multi-hospital transport decision model to obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transport blood type, and red blood cell transport volume.

[0068] In an optional embodiment, the screening of candidate red blood cell transfer hospitals for the red blood cell shortage hospital based on a preset urgency determination function includes:

[0069] Construct decision variables to determine whether the current RBC shortage hospital is in urgent shortage;

[0070] Obtain the basic travel time between the current red blood cell shortage hospital and any candidate red blood cell transfer hospital to be screened, as well as the real-time traffic factors affected by external factors;

[0071] Obtain the current waiting time limits for patients in hospitals with RBC shortages;

[0072] The decision variables, basic traffic time, real-time road condition factor and time limit are used as inputs of the urgency determination function to obtain corresponding results, and all candidate red blood cell transfer hospitals with corresponding results less than or equal to one are screened out for the current red blood cell shortage hospital.

[0073] In an optional embodiment, the blood type substitution rule includes a blood type substitution relationship and a blood type substitution priority under the RH blood type system.

[0074] In an optional embodiment, the process of constructing the comprehensive optimization target includes:

[0075] The blood type substitution term is constructed by obtaining the weight coefficient of each candidate blood type according to the priority of different blood type substitutions, and obtaining the red blood cell transfer volume of each candidate blood type received by the current red blood cell shortage hospital from any candidate red blood cell transfer hospital every day.

[0076] The transport cost item is constructed by combining the real-time traffic factor and the unit transport cost of transporting red blood cells to the hospital currently short of red blood cells;

[0077] Obtain the red blood cell shortage of each candidate blood type in the hospital with current red blood cell shortage every day, and construct a shortage penalty term;

[0078] The blood type substitution item, the storage age item, the transportation cost item and the shortage penalty item are weighted and integrated to construct the comprehensive optimization goal.

[0079] In an optional embodiment, the multi-hospital transfer decision model includes constraints:

[0080] (1) Current RBC shortage: The hospital's real-time RBC shortage is equal to the demand minus the inventory;

[0081] (2) The red blood cell shortage at the end of each day in the hospital with current red blood cell shortage is equal to the shortage minus the transport volume;

[0082] (3) The amount of red blood cells transferred from any candidate red blood cell transfer hospital does not exceed the amount of red blood cell shortage in the current red blood cell shortage hospital;

[0083] (4) The remaining red blood cell inventory after the transfer of any candidate red blood cell transfer hospital must not be less than the red blood cell safety inventory that the hospital needs to retain;

[0084] (5) The result of the urgency judgment function must be less than or equal to one, in order to screen out candidate red blood cell transport hospitals that meet the transport time constraints and patient condition constraints;

[0085] (6) The red blood cell transport volume of any candidate transport blood type from any candidate red blood cell transport hospital does not exceed the red blood cell transportable volume of that candidate transport blood type in the candidate red blood cell transport hospital;

[0086] (7) The first non-negative constraint ensures that the red blood cell transfer volume of any candidate blood type from any candidate red blood cell transfer hospital is not negative;

[0087] (8) The second non-negative constraint ensures that the amount of red blood cell safety stock required to be retained from any candidate red blood cell transport hospital is not negative;

[0088] (9) The red blood cell transportable volume of any candidate blood type in any candidate red blood cell transport hospital is greater than zero, ensuring that only hospitals with transportable volume participate in the transport;

[0089] (10) Any candidate transfer blood type meets the blood type substitution rules.

[0090] In an optional embodiment, the service level that the general hospital expects to achieve, the time for which the red blood cell inventory needs to be guaranteed, the red blood cell replenishment cycle, and the daily demand for red blood cells are obtained to obtain the red blood cell safety inventory of any candidate red blood cell transport hospital and any candidate transport blood type.

[0091] In an optional embodiment, for any candidate red blood cell transport hospital and any candidate transport blood type, the red blood cell transportable quantity is equal to the current inventory of the candidate transport blood type minus the red blood cell safety inventory of the blood type.

[0092] Example 1:

[0093] like Figure 1 As shown, an embodiment of the present invention provides a multi-hospital red blood cell transport decision-making method integrating blood type substitution rules, including:

[0094] S1. Establish a real-time inventory database for all hospitals in the target area to record the blood type, age, and quantity of red blood cells in each hospital on a daily basis;

[0095] S2. Detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types among the candidate red blood cell transfer hospitals based on blood type substitution rules generated from real-world medical standards;

[0096] S3. Based on the candidate red blood cell transfer hospitals and the candidate transfer blood types, a multi-hospital transfer decision model is constructed with blood type replacement, bank age, transfer cost, and shortage penalty as comprehensive optimization objectives;

[0097] S4. Solve the multi-hospital transfer decision model to obtain the optimal transfer decision plan to determine the final red blood cell transfer hospital, its transfer blood type, and red blood cell transfer volume.

[0098] The embodiments of the present invention strengthen the transport cooperation among multiple hospitals in the region, transport idle red blood cells across hospitals, and incorporate the red blood cell age and blood type substitution rules into the transport decision, so that the range of red blood cells that can participate in the transport is expanded, the red blood cell shortage phenomenon is effectively suppressed, and the red blood cell resources are fully utilized, especially the use of red blood cells with older age is greatly increased, thereby reducing resource waste.

[0099] The following sections describe the various steps of the above solution in detail:

[0100] Referring to Table 1, the parameter symbols and their meanings, and variable symbols and their meanings involved in the embodiments of the present invention are first given:

[0101] Table 1

[0102]

[0103] In step S1, a real-time inventory database of all hospitals in the target area is established to record the blood type, age and quantity of the daily red blood cell inventory of each hospital.

[0104] This step establishes a real-time inventory database for all hospitals in the target area, recording the blood type (AB+, AB-, A+, A-, B+, B-, O+, O-), storage age m (storage days, the maximum effective storage age M is generally 42 days), and quantity of each hospital's daily red blood cell inventory.

[0105] It should be noted that in clinical practice, RH-negative blood types (such as O-, A-, etc.) must strictly follow substitution priority rules (e.g., O- patients can only receive O- red blood cells) due to their rarity and transfusion compatibility restrictions. For example, if an RH+ blood type is transferred to an RH- patient, it may cause serious medical accidents such as hemolytic reactions. Based on the aforementioned reasons, in the subsequent blood type substitution modeling, the embodiment of the present invention considers the RH (Rhesus Macacus, translated as "rhesus monkey") blood type system that covers RH (±) attribute differences, which is different from the related art that generally only considers the basic blood types of the ABO system. Correspondingly, this step records the real-time inventory information of the above eight blood types of red blood cells.

[0106] Specifically, if there are multiple (more than two) hospitals in the target area, and each hospital has its own red blood cell inventory for daily medical treatment, the description of the hospital's red blood cell inventory status on a certain day can be expressed as follows:

[0107] The demand for red blood cells of type g in hospital i on day t is d ig (t), on day t, the number of red blood cells in stock of type g with an age of m in hospital i is x igm (t), then the inventory status set of red blood cells of type g blood in hospital i on day t is .

[0108] In addition, the first-in, first-out (FIFO) policy is adopted when red blood cells are shipped out for use. After the demand is met on the tth day, the inventory status of the red blood cells of the gth blood type in the i-th hospital becomes x ig (t + ), t +Indicates the last moment of day t (end of day t):

[0109]

[0110] In step S2, based on the real-time inventory database, hospitals with red blood cell shortages are detected, and based on a preset urgency judgment function, candidate red blood cell transfer hospitals are screened for the red blood cell shortage hospitals, and based on blood type substitution rules generated by actual medical specifications, candidate transfer blood types are screened among the candidate red blood cell transfer hospitals.

[0111] In the normal use of red blood cells in hospitals, the corresponding blood types are used to meet daily needs, and the inventory is updated every day. However, it is important to note that when the daily demand for a certain blood type in a hospital exceeds the total inventory, this step automatically triggers a shortage alarm, and the hospital is recorded as the i-th red blood cell shortage hospital. The red blood cell shortage amount can be further obtained (shortage amount = demand amount - inventory amount), which is expressed as , where S ig (t) represents the shortage of red blood cells of type g in the i-th red blood cell shortage hospital on day t, d ig (t) represents the demand for red blood cells of the gth candidate blood type for red blood cell shortage in the i-th hospital on day t, X ig (t) represents the red blood cell inventory of the gth blood type in the i-th red blood cell shortage hospital on day t.

[0112] After detecting the hospitals with RBC shortage and the amount of RBC shortage, this step proceeds to:

[0113] Based on a preset urgency determination function, candidate red blood cell transfer hospitals are screened for the red blood cell shortage hospital.

[0114] Since the application scenario of the embodiment of the present invention is that hospitals face daily patient red blood cell needs and the patient conditions are uncertain, the method needs to make an urgency judgment based on the patient conditions and preliminarily screen out hospitals among the cooperating hospitals that can participate in the transfer (i.e., candidate red blood cell transfer hospitals). The purpose is to narrow the transfer scope and greatly improve decision-making efficiency. The main judgment basis is the urgency of the patient's condition and the transportation conditions between hospitals.

[0115] Specifically, the urgency determination function is defined as:

[0116]

[0117] Among them, E ij represents the result of the urgency judgment function between the i-th red blood cell shortage hospital and the j-th candidate red blood cell transport hospital; U urgent is a decision variable, which is 1 if the hospital is judged to have an emergency shortage of red blood cells, otherwise it is 0; ijrepresents the basic transportation time between the i-th red blood cell shortage hospital and the j-th candidate red blood cell transfer hospital; f traffic Indicates the real-time traffic condition factor affected by external factors, which may cause the travel time to become longer, such as rush hour; limit Indicates the time limit for patients to wait.

[0118] Understandably, U urgent =1, which means that the patient's condition is urgent and needs to be treated immediately. The hospital cannot wait for the transfer of suitable red blood cells from other hospitals for medical treatment. The hospital can only select suitable red blood cells of other blood types from the bank according to the blood type substitution rules to meet the demand. U urgent =0, which means it is not urgent. The model will give an objective time limit for the patient to wait. limit , that is, the transported red blood cells need to be at t limit The shipment arrived within the timeframe.

[0119] Finally, E ij Hospitals with a RBC transfer rate of ≤1 are considered candidate RBC transfer hospitals. The next step is to use the transfer decision model to select appropriate blood types for transfer within these hospitals and determine the transfer blood type and quantity. In other words, candidate RBC transfer blood types are screened within the candidate RBC transfer hospitals based on blood type substitution rules generated from real-world medical standards.

[0120] For candidate RBC transport hospitals, it is only meaningful to select RBC blood types that meet the blood type substitution rules as candidate transport blood types. The blood type substitution rules generated by actual medical standards include blood type substitution relationships and blood type substitution priorities under the RH blood type system, as shown in Table 2:

[0121] Table 2

[0122]

[0123] The smaller the value in Table 2, the higher the priority. For example, if there is a shortage of AB+ blood type, all other blood types can be transfused. AB+ type has the highest priority, and O- type has the lowest priority.

[0124] Therefore, by directly searching the blood type replacement priority table, the red blood cell blood types that can participate in the transport can be directly screened and obtained as candidate transport blood types.

[0125] At this step, the embodiment of the present invention can detect the occurrence of shortage events based on the real-time inventory database update, and then preliminarily screen out candidate red blood cell transfer hospitals and their candidate transfer blood types. The next step is to select the most appropriate blood type and hospital for the transfer operation through the transfer decision.

[0126] In step S3, based on the candidate red blood cell transfer hospitals and their candidate transfer blood types, a multi-hospital transfer decision model is constructed with blood type replacement, storage age, transfer cost and shortage penalty as comprehensive optimization goals.

[0127] The transport decision-making method model integrating blood type substitution rules solves the red blood cell shortage in the hospital by considering the transport scheduling decision of blood type substitution, while using red blood cells with close expiration dates for transport as much as possible. Therefore, a mathematical model is constructed that comprehensively considers blood type substitution priority, red blood cell bank age, transport cost, and shortage satisfaction rate.

[0128] like Figure 2 As shown, Figure 2 A schematic diagram of a multi-hospital red blood cell transport decision-making scenario is disclosed.

[0129] In addition, in order to solve the shortage of red blood cells in hospitals and achieve the purpose of the present invention, combined with relevant red blood cell transfusion rules, the following basic rules need to be met:

[0130] (1) The red blood cell transfusion situation faced by the hospital is for daily rescue of patients and is uncertain.

[0131] (2) When the doctor determines that the patient's condition is urgent and that the patient cannot wait for red blood cell transfer from other hospitals, the hospital can only use other blood types of red blood cells in its own inventory to meet the shortage demand. This can also be regarded as an intra-hospital transfer, that is, i=j (that is, the red blood cell shortage hospital itself is its candidate red blood cell transfer hospital), except that the transfer time is regarded as 0.

[0132] (3) The transferred red blood cells are released from the warehouse according to the FIFO rule.

[0133] (4) When selecting a transfer blood type, the blood type substitution rules must be followed.

[0134] Based on the above rules, a multi-hospital red blood cell transport decision model was constructed, including:

[0135] The objective function with blood type replacement, storage age, transportation cost and shortage penalty as the comprehensive optimization goals is:

[0136]

[0137] Among them, min represents the minimization function; F represents the comprehensive optimization goal.

[0138] α g ×y ijg (t) is the blood type surrogate, α g represents the weight coefficient of the g-th candidate transfer blood type, y ijg(t) represents the amount of red blood cells of the gth candidate blood type received by the i-th red blood cell shortage hospital from the j-th candidate red blood cell transfer hospital on day t, .

[0139] It is understandable that since the substitution priority is divided into 8 levels based on Table 2, the weight coefficients of levels 1 to 8 can be set as α g ∈[1,2,3,4,5,6,7,8], the higher the priority of the transported blood type, the smaller the value of the blood type alternative.

[0140] is the storage age item, M is the maximum effective storage age, K m K represents the transport weight coefficient of red blood cells with an age of m. m =M-m+1,y ijgm (t) represents the amount of red blood cells of the gth candidate transport blood type with a storage age of m received by the i-th red blood cell shortage hospital from the j-th candidate red blood cell transport hospital on day t.

[0141] It is understandable that in order to meet the FIFO rule and make the amount of red blood cells that are about to expire transferred as much as possible in the transfer decision, the storage age weight of the transferred unit is expressed as: K1>K2>K3>…>K m >…>K M , where K m =M-m+1.

[0142] c i ×t ij ×f traffic ×y ijg (t) is the transshipment cost item, c i represents the unit transport cost of transporting red blood cells to the i-th hospital with red blood cell shortage.

[0143] Understandably, t ij ×f traffic The smaller the value, the closer the two hospitals are and the lower the transportation cost.

[0144] S ig (t)-y ijg (t) is the shortage penalty term, which is used to force the objective function to choose a larger y as possible. ijg (t), to meet the shortage of red blood cells as much as possible, S ig (t) represents the shortage of red blood cells of the gth candidate transfer blood type in the i-th red blood cell shortage hospital on day t.

[0145] ω1, ω2, ω3, and ω4 are the weights of each item in the objective function.

[0146] And the constraints:

[0147]

[0148] Among them, constraint (3) means that the real-time shortage of red blood cells on that day is equal to the demand minus the inventory; d ig (t) represents the demand for red blood cells of the gth candidate blood type for red blood cell shortage in the i-th hospital on day t, X ig (t) represents the red blood cell inventory of the gth candidate transfer blood type in the i-th red blood cell shortage hospital on day t;

[0149] Constraint (4) states that the RBC shortage at the end of the day is equal to the shortage minus the transport volume;

[0150] S ig (t + ) represents the shortage of red blood cells of the gth candidate transfer blood type in the i-th red blood cell shortage hospital at the end of day t;

[0151] Constraint (5) means that the amount of red blood cell transfer from any candidate red blood cell transfer hospital does not exceed the amount of red blood cell shortage in the red blood cell shortage hospital;

[0152] Constraint (6) indicates that the remaining red blood cell inventory of any candidate red blood cell transfer hospital after transfer must not be less than the red blood cell safety inventory that the hospital needs to retain; X jg (t + ) represents the remaining red blood cell inventory after the transfer of the gth candidate blood type in the jth candidate red blood cell transfer hospital at the end of the tth day; a jg (t) represents the red blood cell safety stock of the gth candidate red blood cell transfer blood type in the jth candidate red blood cell transfer hospital on day t;

[0153] Constraint (7) indicates that the result of the urgency decision function must be less than or equal to one, with the goal of screening out candidate red blood cell transport hospitals that meet the transport time constraints and patient condition constraints;

[0154] Constraint (8) indicates that the red blood cell transport volume of any candidate transport blood type from any candidate red blood cell transport hospital does not exceed the red blood cell transportable volume of the candidate transport blood type in the candidate red blood cell transport hospital; b jg represents the transportable amount of red blood cells of the gth candidate transport blood type in the jth candidate red blood cell transport hospital;

[0155] Constraint (9) represents a non-negative constraint, ensuring that the red blood cell transfer volume of any candidate transfer blood type from any candidate red blood cell transfer hospital is not negative;

[0156] Constraint (10) represents a non-negative constraint, ensuring that the amount of red blood cell safety stock required to be retained from any candidate red blood cell transport hospital is not negative;

[0157] Constraint (11) indicates that the red blood cell transportable quantity of any candidate transport blood type in any candidate red blood cell transport hospital is greater than zero, ensuring that only hospitals with transportable quantity participate in the transport;

[0158] Constraint (12) indicates that any candidate transport blood type meets the blood type substitution rule; P valid Represents the set of blood types that correspond to the missing blood types and comply with the replacement blood type rules.

[0159] In particular, the embodiment of the present invention also considers the dynamic constraints of safety stock:

[0160] First, determine the transportable blood type capacity of each candidate red blood cell transport hospital. Since each hospital needs to meet its own space needs in the next few days, it is necessary to maintain an appropriate amount of red blood cells in stock, which is called a safety stock. The red blood cell safety stock is defined as:

[0161]

[0162] Among them, Z represents the service level that the hospital expects to achieve; T remain Indicates the number of days required for guarantee (the number of days remaining until the next replenishment); L indicates the red blood cell replenishment cycle, It represents the total daily demand for red blood cells of the gth candidate transport blood type at the jth candidate red blood cell transport hospital from day t-L+1 to day t.

[0163] For example, L=7 days, T remain A possible value of is: if the current day is the 3rd day and the replenishment is at the beginning of the 8th day, then a 4-day safety stock is required, that is, T remain =4.

[0164] On this basis, the red blood cell transportable quantity of the candidate red blood cell transport hospital can be obtained by subtracting the current safety stock quantity from the current inventory quantity, which is specifically defined as:

[0165]

[0166] In step S4, the multi-hospital transport decision model is solved to obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transport blood type, and the red blood cell transport volume.

[0167] Since the multi-hospital transport decision model essentially has multiple optimization objectives, for example, this step can use the NSGA-II algorithm to solve the Pareto frontier, and then select the optimal transport decision plan based on the tendency demand of the optimization objective to determine the final red blood cell transport hospital j * and its transporter blood type g * , red blood cell transport volume ijg* (t).

[0168] It's understandable that the above transport decision-making method is only described from the perspective of a single round of RBC transport. In reality, real-time decisions can be made for other rounds before or after this round. In other words, in this embodiment of the present invention, simply based on a real-time inventory database of all hospitals in the target area, it is possible to quickly identify hospitals currently experiencing RBC shortages and calculate the corresponding (optimal) RBC transport hospital, its transported blood type, and the RBC transport volume.

[0169] Thus, the embodiment of the present invention has completed the entire process of a decision-making method integrating multi-hospital collaboration, refined blood type substitution rules, and priority transfer of near-expiry products, thereby achieving the unity of rapid response to shortages, efficient resource utilization, and clinical safety.

[0170] Furthermore, in an optional implementation, a feedback loop can be implemented. For example, based on the optimal transfer decision, the hospital experiencing RBC shortages sends a transfer request to the selected hospital, specifying the required blood type, quantity, and transportation route. After the transfer is completed, both hospitals' RBC inventory data is updated, relevant transfer information is recorded, and the shortage satisfaction rate, reduction in expired RBCs, and economic costs of the transfer are calculated. A performance report is generated for subsequent optimization.

[0171] Example 2:

[0172] An embodiment of the present invention provides a multi-hospital red blood cell transport decision-making system integrating blood type substitution rules, including:

[0173] A database establishment module is used to establish a real-time inventory database for all hospitals in the target area to record the blood type, age and quantity of the daily red blood cell inventory of each hospital;

[0174] an information screening module for detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types among the candidate red blood cell transfer hospitals based on blood type substitution rules generated from actual medical specifications;

[0175] The model construction module is used to construct a multi-hospital transport decision model based on the candidate red blood cell transport hospitals and the candidate transport blood types, with blood type replacement, storage age, transport cost, and shortage penalty as the comprehensive optimization objectives; wherein the storage age item corresponding to the storage age is constructed as follows:

[0176] Obtain the transport weight coefficients of red blood cells of different storage ages, and obtain the red blood cell transport volume of each candidate transport blood type with different storage ages received by the current red blood cell shortage hospital from any candidate red blood cell transport hospital every day, and construct the storage age item;

[0177] The model solving module is used to solve the multi-hospital transport decision model and obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transport blood type, and red blood cell transport volume.

[0178] Example 3:

[0179] An embodiment of the present invention provides a storage medium storing a computer program for multi-hospital red blood cell transport decision-making integrating blood type substitution rules, wherein the computer program enables a computer to control the multi-hospital red blood cell transport decision-making method as described in Example 1.

[0180] Example 4:

[0181] An embodiment of the present invention provides an electronic device, including:

[0182] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the programs including a method for controlling a multi-hospital red blood cell transport decision-making method as described in Example 1.

[0183] In summary, compared with the existing technology, the present invention has the following beneficial effects:

[0184] 1. Strengthened inter-hospital transfer collaboration within the target region. When a hospital faces a shortage of red blood cells for emergency red blood cell transfusions, it can address the shortage by transferring blood from other hospitals, eliminating the need to wait for others to donate blood or place urgent orders with a blood center. Multi-hospital transfers improve the efficiency of resolving red blood cell shortages and patient treatment.

[0185] 2. Transporting red blood cells between multiple hospitals allows for the use of idle red blood cells that might otherwise be wasted, reducing the waste of red blood cells in the region and enhancing the hospital's ability to treat patients who require red blood cell transfusions.

[0186] 3. By incorporating blood type substitution rules into transport decisions, the range of red blood cells that can participate in transport is expanded, and more blood type red blood cells participate in transport, further solving the problem of red blood cell shortage and making the use of red blood cell resources more reasonable.

[0187] 4. The shelf life characteristics of red blood cells should be taken into consideration during the transportation process. Expired red blood cells can only be discarded, resulting in a waste of resources. However, this method can greatly increase the use of red blood cells with a longer storage age, reduce the number of expired red blood cells to a certain extent, and avoid waste of resources.

[0188] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0189] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A multi-hospital red blood cell transport decision-making method integrating blood type substitution rules, characterized in that: include: Establish a real-time inventory database for all hospitals in the target area to record the blood type, age, and quantity of red blood cells in each hospital's daily inventory; Detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types in the candidate red blood cell transfer hospitals based on blood type substitution rules generated from actual medical specifications; Based on the candidate red blood cell transfer hospitals and their candidate transfer blood types, a multi-hospital transfer decision model is constructed with blood type replacement, storage age, transfer cost, and shortage penalty as comprehensive optimization objectives; wherein the storage age item corresponding to the storage age is constructed as follows: Obtain the transport weight coefficients of red blood cells of different storage ages, and obtain the red blood cell transport volume of each candidate transport blood type with different storage ages received by the current red blood cell shortage hospital from any candidate red blood cell transport hospital every day, and construct the storage age item; Solving the multi-hospital transport decision model to obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transported blood type, and the red blood cell transport volume; The step of screening candidate red blood cell transfer hospitals for the red blood cell shortage hospital based on a preset urgency determination function includes: Construct decision variables to determine whether the current RBC shortage hospital is in urgent shortage; Obtain the basic travel time between the current red blood cell shortage hospital and any candidate red blood cell transfer hospital to be screened, as well as the real-time traffic factors affected by external factors; Obtain the current waiting time limits for patients in hospitals with RBC shortages; Using the decision variables, basic traffic time, real-time traffic factor, and time limit as inputs to the urgency determination function, obtaining corresponding results, and screening all candidate red blood cell transfer hospitals for which the corresponding results are less than or equal to one for the current red blood cell shortage hospital; The construction process of the comprehensive optimization target includes: The blood type substitution term is constructed by obtaining the weight coefficient of each candidate blood type according to the priority of different blood type substitutions, and obtaining the red blood cell transfer volume of each candidate blood type received by the current red blood cell shortage hospital from any candidate red blood cell transfer hospital every day. The transport cost item is constructed by combining the real-time traffic factor and the unit transport cost of transporting red blood cells to the hospital currently short of red blood cells; Obtain the red blood cell shortage of each candidate blood type in the hospital with current red blood cell shortage every day, and construct a shortage penalty term; The blood type substitution item, the storage age item, the transportation cost item and the shortage penalty item are weighted and integrated to construct the comprehensive optimization goal.

2. The multi-hospital red blood cell transport decision-making method according to claim 1, wherein: The blood type substitution rules include blood type substitution relationships and blood type substitution priorities under the RH blood type system.

3. The multi-hospital red blood cell transport decision-making method according to claim 1, wherein: The multi-hospital transfer decision model includes the following constraints: (1) Current RBC shortage: The hospital's real-time RBC shortage is equal to the demand minus the inventory; (2) The red blood cell shortage at the end of each day in the hospital with current red blood cell shortage is equal to the shortage minus the transport volume; (3) The amount of red blood cells transferred from any candidate red blood cell transfer hospital does not exceed the amount of red blood cell shortage in the current red blood cell shortage hospital; (4) The remaining red blood cell inventory after the transfer of any candidate red blood cell transfer hospital must not be less than the red blood cell safety inventory that the hospital needs to retain; (5) The result of the urgency judgment function must be less than or equal to one, in order to screen out candidate red blood cell transport hospitals that meet the transport time constraints and patient condition constraints; (6) The red blood cell transport volume of any candidate transport blood type from any candidate red blood cell transport hospital does not exceed the red blood cell transportable volume of that candidate transport blood type in the candidate red blood cell transport hospital; (7) The first non-negative constraint ensures that the red blood cell transfer volume of any candidate blood type from any candidate red blood cell transfer hospital is not negative; (8) The second non-negative constraint ensures that the amount of red blood cell safety stock required to be retained from any candidate red blood cell transport hospital is not negative; (9) The red blood cell transportable volume of any candidate blood type in any candidate red blood cell transport hospital is greater than zero, ensuring that only hospitals with transportable volume participate in the transport; (10) Any candidate transfer blood type meets the blood type substitution rules.

4. The multi-hospital red blood cell transport decision-making method according to claim 3, wherein: The service level that the general hospital expects to achieve, the time for which the red blood cell inventory needs to be guaranteed, the red blood cell replenishment cycle, and the daily demand for red blood cells are obtained. The red blood cell safety inventory of any candidate red blood cell transfer hospital and any candidate transfer blood type is obtained.

5. The multi-hospital red blood cell transport decision-making method according to claim 4, wherein: For any candidate red blood cell transport hospital and any candidate transport blood type, the red blood cell transportable quantity is equal to the current inventory of the candidate transport blood type minus the red blood cell safety stock of the blood type.

6. A multi-hospital red blood cell transport decision-making system integrating blood type substitution rules, characterized by: The method for executing the multi-hospital red blood cell transport decision-making method according to claim 1 comprises: A database establishment module is used to establish a real-time inventory database for all hospitals in the target area to record the blood type, age and quantity of the daily red blood cell inventory of each hospital; an information screening module for detecting hospitals with red blood cell shortages based on the real-time inventory database, screening candidate red blood cell transfer hospitals for the hospitals with red blood cell shortages based on a preset urgency determination function, and screening candidate transfer blood types among the candidate red blood cell transfer hospitals based on blood type substitution rules generated from actual medical specifications; The model construction module is used to construct a multi-hospital transport decision model based on the candidate red blood cell transport hospitals and the candidate transport blood types, with blood type replacement, storage age, transport cost, and shortage penalty as the comprehensive optimization objectives; wherein the storage age item corresponding to the storage age is constructed as follows: Obtain the transport weight coefficients of red blood cells of different storage ages, and obtain the red blood cell transport volume of each candidate transport blood type with different storage ages received by the current red blood cell shortage hospital from any candidate red blood cell transport hospital every day, and construct the storage age item; The model solving module is used to solve the multi-hospital transport decision model and obtain the optimal transport decision plan to determine the final red blood cell transport hospital, its transport blood type, and red blood cell transport volume.

7. A storage medium, characterized in that: It stores a computer program for multi-hospital red blood cell transport decision-making that integrates blood type substitution rules, wherein the computer program enables the computer to control the multi-hospital red blood cell transport decision-making method according to any one of claims 1 to 5.

8. An electronic device, characterized in that: include: one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the programs including a method for controlling the multi-hospital red blood cell transport decision-making method as described in any one of claims 1 to 5.

Images