CN117726044A - Blood inventory dynamic early warning method and system - Google Patents
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Abstract
The invention relates to a blood inventory dynamic early warning method and a system, which are used for establishing a blood consumption prediction model of a blood bank through historical use data of the blood bank and establishing a dynamic early warning line of the blood bank through the blood consumption prediction model. Thus, the dynamic early warning is carried out on the stock of the blood bank at different times. In addition, the blood bank early warning map is established through the position information and the dynamic early warning line of the blood bank. And carrying out association labeling on blood banks which can meet the allocation conditions in the blood bank early warning map, and then intuitively displaying early warning information of each blood bank in the blood bank early warning map, and directly searching blood allocation possibility. Is very beneficial to daily maintenance and use of blood banks.
Description
Technical Field
The invention relates to the technical field of inventory management, in particular to a blood inventory dynamic early warning method and a system.
Background
A blood bank is a warehouse that stores blood. Red lines are typically set in blood banks for inventories of various blood types, and an alarm is given for inventory blood types below the red lines. In general, the stock red line is a fixed value, and the corresponding blood volume of the stock red line can satisfy the blood usage amount per unit time, which is generally estimated according to the historical blood usage speed.
But the blood usage rate of the blood bank is not constant. For example, as the temperature increases, the blood consumption increases. Therefore, the existing stock red line is not accurate enough for the storage capacity early warning of the blood bank. In addition, stock red lines are directly adopted for early warning, and the possibility of allocation among different blood banks is ignored.
Disclosure of Invention
Therefore, the invention aims to provide a blood inventory dynamic early warning method and a system, which are used for solving the problems that the early warning is not accurate enough and the phenomenon of mutually allocating multiple blood banks is ignored in the prior art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the invention discloses a blood inventory dynamic early warning method, which comprises the following steps:
acquiring blood historical use data, current blood stock quantity and position information of a plurality of blood banks, wherein the historical use data comprises a plurality of use time points and blood use speeds corresponding to the plurality of use time points;
a blood usage prediction model of a corresponding blood bank established based on the historical usage data, wherein the blood usage prediction model characterizes blood usage prediction speeds corresponding to a plurality of time points;
constructing a dynamic early warning line of each blood bank according to the blood consumption prediction model, and constructing a blood bank early warning map based on the dynamic early warning lines and position information of a plurality of blood banks, wherein the blood early warning stock in the dynamic early warning line changes with time, and any two blood banks meeting the allocation conditions are marked in the blood bank early warning map;
and dynamically pre-warning the storage of the blood bank based on the blood bank pre-warning map and the current blood stock quantity.
In one embodiment of the present application, obtaining blood historical usage data for a plurality of blood banks includes:
acquiring blood usage records of a plurality of blood banks, wherein the blood usage records comprise a plurality of usage time points and blood usage amounts corresponding to the plurality of usage time points；
Calculating the blood use speed corresponding to each time pointBlood history usage data is obtained, wherein,，for the point in timeAnd point in timeThe duration of the interval between them.
In an embodiment of the present application, a blood usage prediction model of a corresponding blood bank established based on the historical usage data includes:
establishing a two-dimensional coordinate system of using speed-time, and mapping blood using speeds corresponding to a plurality of using time points in the historical using data into the two-dimensional coordinate system to obtain a plurality of data points in the two-dimensional coordinate system, wherein the time axis range of the two-dimensional coordinate system is a time period;
determining a target time period in the two-dimensional coordinate system based on distribution characteristics of a plurality of data points, wherein data points corresponding to the target time period are densely distributed;
and constructing a use speed interval of the target time period based on the data points corresponding to the target time period, and constructing a blood consumption prediction model of the blood bank based on the use speed interval of the target time period.
In an embodiment of the present application, determining the target time period in the two-dimensional coordinate system based on the distribution characteristics of the plurality of data points includes:
dividing a plurality of time periods, and calculating the use speed variance of the data point corresponding to each time period;
judging whether the time period meets dense definition or not, wherein the dense definition comprises the following steps: the using speed variance corresponding to the time period is smaller than a preset variance threshold, and the number of data points corresponding to the time period is larger than or equal to a preset number threshold;
when the time period meets the dense definition, taking the time period meeting the dense definition as a target time period;
and when the time period does not meet the dense definition, halving the current time period which does not meet the dense definition to obtain two time periods, and returning to judging whether the time period meets the dense definition or not until the data points of the divided time periods are smaller than a preset quantity threshold value or the divided time periods are smaller than a preset minimum duration.
In an embodiment of the present application, constructing a usage speed interval of a target time period based on data points corresponding to the target time period includes:
calculating a mean value of the usage speed of the data points for each target periodAnd using standard deviation of speed；
Based on the average of the speed of useAnd using standard deviation of speedConstructing a use speed interval of each target time period, wherein the use speed interval is thatWherein, the method comprises the steps of, wherein,is a regulatory factor.
In an embodiment of the present application, constructing a dynamic early warning line of each blood bank according to the blood volume prediction model includes:
determining a target time period and a non-target time period for each blood bank based on the blood volume prediction model;
constructing a first early warning line and a second early warning line of a target time period of each blood bank, wherein the first early warning line isThe second early warning line isWhereinAs the current blood inventory level,for a minimum blood usage rate for a target period of time,maximum blood usage rate for a target time period;
constructing a third early warning line and a fourth early warning line of a non-target time period of each blood bank, wherein the third early warning line isThe fourth early warning line isWherein, the method comprises the steps of, wherein,for the set minimum inventory warning value,the method comprises the steps of setting a maximum inventory early warning value;
and constructing a dynamic early warning line of each blood bank based on the first early warning line and the second early warning line of the target time period and the third early warning line and the fourth early warning line of the non-target time period.
In an embodiment of the present application, constructing a blood bank early warning map based on dynamic early warning lines and position information of a plurality of blood banks includes:
mapping all blood banks into a map based on the position information of the blood banks to obtain the navigation distance between any two blood banks;
performing association labeling on any two blood banks meeting allocation conditions to obtain a blood bank early warning map, wherein the allocation conditions comprise:
the navigation distance between the two blood banks is smaller than a preset distance threshold;
the peak period in the dynamic early warning line of one blood bank coincides with the valley period in the dynamic early warning line of the other blood bank.
In an embodiment of the present application, the peak period and the valley period are marked from a dynamic early warning line of the blood bank.
In an embodiment of the present application, dynamically pre-warning the storage of the blood bank based on the blood bank pre-warning map and the current blood stock amount includes:
determining a blood bank currently in a peak period in the blood bank early warning map;
comparing the current blood stock of the blood bank in the peak period with a corresponding early warning line, performing first early warning when the current blood stock is smaller than or equal to the early warning line, searching the current blood stock of the related blood bank in the blood bank early warning map, and performing second early warning when the current blood stock of the related blood bank is smaller than or equal to the early warning line of the related blood bank;
comparing the current blood stock quantity of the blood bank which is not in the peak period with a corresponding early warning line, and carrying out early warning when the current blood stock quantity is smaller than or equal to the early warning line.
The application also provides a blood inventory dynamic early warning system, comprising:
the blood collection device comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring blood historical use data of a plurality of blood banks, current blood stock quantity and position information, wherein the historical use data comprises a plurality of use time points and blood use speeds corresponding to the plurality of use time points;
the model building module is used for building a blood consumption prediction model of a corresponding blood bank based on the historical use data, wherein the blood consumption prediction model characterizes blood use prediction speeds corresponding to a plurality of time points;
the map building module is used for building a dynamic early warning line of each blood bank according to the blood consumption prediction model and building a blood bank early warning map based on the dynamic early warning lines and the position information of a plurality of blood banks, wherein the blood early warning stock quantity in the dynamic early warning line changes along with time, and any two blood banks meeting the allocation conditions are marked in the blood bank early warning map;
and the early warning module is used for dynamically early warning the storage of the blood bank based on the blood bank early warning map and the current blood stock quantity.
The present invention also provides an electronic device including: a processor and a memory; wherein the memory is used for storing a computer program; the processor is used for loading and executing the computer program to enable the electronic equipment to execute the blood inventory dynamic early warning method.
The beneficial effects of the invention are as follows: according to the blood inventory dynamic early warning method and system, the blood consumption prediction model of the blood bank is built through historical use data of the blood bank, and the dynamic early warning line of the blood bank is built through the blood consumption prediction model. Thus, the dynamic early warning is carried out on the stock of the blood bank at different times. In addition, the blood bank early warning map is established through the position information and the dynamic early warning line of the blood bank. And carrying out association labeling on blood banks which can meet the allocation conditions in the blood bank early warning map, and then intuitively displaying early warning information of each blood bank in the blood bank early warning map, and directly searching blood allocation possibility. Is very beneficial to daily maintenance and use of blood banks.
Drawings
The invention is further described below with reference to the accompanying drawings and examples:
FIG. 1 is a flow chart of a blood inventory dynamic pre-warning method shown in an embodiment of the present application;
FIG. 2 is a schematic diagram of a process for cycle halving a time period in the present application;
FIG. 3 is a schematic diagram of a blood bank early warning map according to an embodiment of the present application;
FIG. 4 is a block diagram of a blood inventory dynamic warning system shown in an embodiment of the present application;
fig. 5 shows a schematic diagram of a computer system suitable for use in implementing the electronic device of the embodiments of the present application.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the layers related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the layers in actual implementation, and the form, number and proportion of the layers in actual implementation may be arbitrarily changed, and the layer layout may be more complex.
In the following description, numerous details are discussed to provide a more thorough explanation of embodiments of the present invention, however, it will be apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details.
Fig. 1 is a flowchart of a blood inventory dynamic early warning method according to an embodiment of the present application, as shown in fig. 1: the blood inventory dynamic early warning method of the embodiment may include steps S110 to S140:
s110, acquiring blood historical use data, current blood stock quantity and position information of a plurality of blood banks, wherein the historical use data comprises a plurality of use time points and blood use speeds corresponding to the plurality of use time points;
a blood bank in this application may refer to a functional department in a hospital that stores blood. But may also refer to some user warehouses for storing medical blood. And are not limited herein. The current blood inventory and location information may be obtained directly from the existing management system, and will not be described in detail herein.
In the present embodiment, the blood history usage data includes a plurality of usage time points and blood usage speeds corresponding to the plurality of usage time points. In general, a blood pool usage record only records a plurality of usage time points and the blood usage amount corresponding to the plurality of usage time points (determined by an ex-pool record and an in-pool record).
Thus, obtaining blood historical usage data for a plurality of blood banks includes:
s111, acquiring blood use records of a plurality of blood banks, wherein the blood use records comprise a plurality of use time points and blood use amounts corresponding to the plurality of use time points；
S112, calculating the blood use speed corresponding to each time pointBlood history usage data is obtained, wherein,，for the point in timeAnd point in timeThe duration of the interval between them.
The application processes the raw data to obtain the required blood history use data. Thereby obtaining blood usage rates at a plurality of historical time points.
S120, establishing a blood consumption prediction model of a corresponding blood bank based on the historical use data, wherein the blood consumption prediction model characterizes blood use prediction speeds corresponding to a plurality of time points;
the blood consumption prediction model of the blood bank is built based on historical use data, so that the blood use speed of the blood bank at a plurality of time points in the future is predicted, and the required blood stock of the blood bank in unit time is determined.
Specifically, the present application establishes a blood usage prediction model by a process comprising:
s121, establishing a two-dimensional coordinate system of using speed-time, and mapping blood using speeds corresponding to a plurality of using time points in the historical using data into the two-dimensional coordinate system to obtain a plurality of data points in the two-dimensional coordinate system, wherein the time axis range of the two-dimensional coordinate system is a time period;
wherein, the time axis is X horizontal axis, and the speed axis is Y vertical axis. The time period in this embodiment may be one year.
S122, determining a target time period in the two-dimensional coordinate system based on distribution characteristics of a plurality of data points, wherein data points corresponding to the target time period are densely distributed;
wherein the target time period determined in the present application corresponds to a dense and large number of data point distributions. That is, in the history data, the blood use speed is always concentrated in one section during this period. With this rule, the target time period and the blood use speed interval corresponding to the target time period can be extracted.
In this embodiment, determining the target period in the two-dimensional coordinate system based on the distribution characteristics of the plurality of data points includes:
s12201, dividing a plurality of time periods, and calculating the variance of the use speed of the data point corresponding to each time period;
dividing a plurality of data points according to months to obtain data points corresponding to each month; then calculating the variance of the data points corresponding to each month, and judging the density degree of the data points by using the variance;
wherein the variance of the usage speed of each month corresponds to the data pointThe mathematical expression of (2) is:
in the method, in the process of the invention,is the firstThe blood of the individual data points uses a velocity value,the velocity average is used for the data point blood for the month,is the number of data points for the corresponding month.
Wherein the velocity variance is usedThe smaller the value of (2), the denser the data point distribution of the corresponding month is, and the more the blood use speed rule of the corresponding month can be embodied. Otherwise, the blood usage speed rule of the corresponding month cannot be reflected.
S12202, determining whether the time period satisfies a dense definition, where the dense definition includes: the using speed variance corresponding to the time period is smaller than a preset variance threshold, and the number of data points corresponding to the time period is larger than or equal to a preset number threshold;
in step S12202, the time periods are filtered by setting a dense definition, and the time period that satisfies the condition that the corresponding usage speed variance is smaller than the preset variance threshold and the corresponding number of data points is greater than or equal to the preset number threshold is taken as the target time period. Thereby ensuring that the number of data points in the target time period is enough and the data points are densely distributed in a certain value.
S12203, when the period satisfies the dense definition, setting a period satisfying the dense definition as a target period;
s12204, when the time period does not meet the dense definition, halving the current time period which does not meet the dense definition to obtain two time periods, and returning to judging whether the time period meets the dense definition or not until the data points of the divided time periods are smaller than a preset quantity threshold value or the divided time periods are smaller than a preset minimum duration.
Step S12203 and step S12204 are a cyclic process, and fig. 2 is a schematic diagram of a process for cyclic halving a time period in the present application. As shown in fig. 2, in the present application, in order to avoid that a part of the time period in some months satisfies the dense definition, but another part does not satisfy the dense definition, so that the entire month does not satisfy the dense definition. The method adopts a cyclic division mode to find each possible target time period. The method specifically comprises the following steps:
(1) Performing dense definition judgment on each time period;
(2) If the data points corresponding to the divided time periods meet the dense definition, the time period is directly a target time period;
(3) If the data points corresponding to the divided time periods do not satisfy the dense definition, the time period is equally divided into two time periods, and then returns to (1), and loop judgment and processing are performed.
(4) And terminating the loop when any one of the divided time period data points is less than a preset number threshold or the divided time period is less than a preset minimum duration. Thereby yielding all targeted and non-targeted time periods.
The historical data points within the target time period are densely distributed and can be used to infer whether the blood usage velocity is highly probable or within this densely distributed interval in the future during this time period. Based on this principle, a predictive model can be built.
The above process is mainly used for searching the rules of the data stabilization period, such as peak period or valley period, and the data points are distributed at high order or low order. During the period of the change, the variance is generally large, and thus it is difficult to determine by dense definition. Therefore, the present application is mainly used for searching for peaks and valleys of blood. Generally, as the temperature rises, there is a period of peak time in blood consumption, and thus climate is affected. The valley period is related to the region, crowd and climate. Thus, different blood banks often have different peak and valley periods.
S123, constructing a use speed interval of the target time period based on the data points corresponding to the target time period, and constructing a blood consumption prediction model of the blood bank based on the use speed interval of the target time period.
The blood volume prediction model in the application analyzes all times in one year to obtain a target time period which can be deduced and a use speed interval in the target time period so as to predict in the same future time period.
In an embodiment of the present application, constructing a usage speed interval of a target time period based on data points corresponding to the target time period includes:
s12301, calculating the average value of the use speed of the data points of each target time periodAnd using standard deviation of speed；
S12302 based on the use speed averageAnd using standard deviation of speedConstructing a use speed interval of each target time period, wherein the use speed interval is thatWherein, the method comprises the steps of, wherein,is a regulatory factor.
In the present embodiment, the use speed average value is usedAnd using standard deviation of speedTo construct the use speed interval and add an adjusting factorTherefore, the accuracy and the latitude of the value of the speed interval can be autonomously balanced and used. In general terms, the process is carried out,the range of the value of (2) is between 0.8 and 1.2.
S130, constructing a dynamic early warning line of each blood bank according to the blood consumption prediction model, and constructing a blood bank early warning map based on the dynamic early warning lines and position information of a plurality of blood banks, wherein the blood early warning stock in the dynamic early warning line changes with time, and all any two blood banks meeting the allocation conditions are marked in the blood bank early warning map;
in this embodiment, the blood volume prediction model describes a usage speed interval for each target period, the usage speed of which varies with time, so that the corresponding warning line is dynamic. And the original early warning line is used in the non-target time period.
In an embodiment of the present application, constructing a dynamic early warning line of each blood bank according to the blood volume prediction model includes:
s1301, determining a target time period and a non-target time period of each blood bank based on the blood volume prediction model;
s1302, constructing a first early warning line and a second early warning line of a target time period of each blood bank, wherein the first early warning line isThe second early warning line isWhereinAs the current blood inventory level,for a minimum blood usage rate for a target period of time,maximum blood usage rate for a target time period;
s1303, constructing a third early warning line and a fourth early warning line of a non-target time period of each blood bank, wherein the third early warning line isThe fourth early warning line isWherein, the method comprises the steps of, wherein,for the set minimum inventory warning value,the method comprises the steps of setting a maximum inventory early warning value;
s1304, constructing a dynamic early warning line of each blood bank based on the first early warning line and the second early warning line of the target time period and the third early warning line and the fourth early warning line of the non-target time period.
In this embodiment, two warning lines are set regardless of whether the target period or the non-target period. Thereby performing early warning twice. To ensure that the blood inventory in the blood bank can meet the timeDuring early warning, a corresponding early warning line is used in a corresponding time period. Thereby carrying out dynamic early warning on the blood bank.
In order to intuitively display the stock and the early warning state of all blood banks, the method and the system also construct a blood bank early warning map based on the position information and the dynamic early warning line of all blood banks.
In an embodiment of the present application, constructing a blood bank early warning map based on dynamic early warning lines and position information of a plurality of blood banks includes:
s1311, mapping all blood banks into a map based on the position information of the blood banks to obtain the navigation distance between any two blood banks;
in step S1311, the locations of all blood banks are mapped into an existing map, and the navigation distance between any two blood banks is calculated using an existing navigation tool. Thereby obtaining the actual transport distance between the two blood banks.
S1312, performing association labeling on any two blood banks meeting allocation conditions to obtain a blood bank early warning map, wherein the allocation conditions comprise:
(1) The navigation distance between the two blood banks is smaller than a preset distance threshold;
(2) The peak period in the dynamic early warning line of one blood bank is overlapped with the valley period in the dynamic early warning line of the other blood bank, wherein the peak period and the valley period are marked from the dynamic early warning line of the blood bank.
Since the present embodiment also determines the peak period and the valley period when determining the target period, the present application correlates any two blood banks with complementary conditions in the peak period and the valley period to indicate that the correlated blood banks can be deployed in the peak period. Thereby constructing the storage early warning state and the allocation relation which can visually display each blood bank.
Fig. 3 is a schematic diagram of a blood bank early warning map in an embodiment of the present application, as shown in fig. 3, three status lamps are displayed below each blood bank, and from left to right, the status of each blood bank is respectively healthy status, first early warning, and second early warning, so that the status of each blood bank is intuitively displayed. In addition, in the map, the associated blood stations are also labeled. If a blood station is at peak hours, the status of the associated blood station may be directly checked to determine if a blood station is available for deployment.
And S140, dynamically pre-warning the storage of the blood bank based on the blood bank pre-warning map and the current blood stock quantity.
Specifically, the early warning process includes:
s141, determining a blood bank currently in a peak period in the blood bank early warning map;
s142, comparing the current blood stock quantity of the blood bank in the peak period with a corresponding early warning line, carrying out first early warning when the current blood stock quantity is smaller than or equal to the early warning line, searching the current blood stock quantity of the associated blood bank in the blood bank early warning map, and carrying out second early warning when the current blood stock quantity of the associated blood bank is smaller than or equal to the early warning line of the associated blood bank;
the first pre-warning is performed twice when the current stock quantity is smaller than or equal to the first pre-warning line or the third pre-warning line (determined by the target time period or the non-target time period), at this time, the current blood stock quantity of the associated blood bank can be searched in the map, and the second pre-warning (only one time) is performed when the current blood stock quantity of the associated blood bank is smaller than or equal to the pre-warning line of the associated blood bank. Finally, when the current stock quantity is smaller than or equal to the second warning line or the fourth warning line (determined by the target time period or the non-target time period), warning is performed again, and the whole process comprises three warning.
S143, comparing the current blood stock quantity of the blood bank which is not in the peak period with a corresponding early warning line, and carrying out early warning when the current blood stock quantity is smaller than or equal to the early warning line.
For the blood bank which is not in the peak period, the blood bank is directly compared with the first early warning line or the third early warning line, then is compared with the second early warning line or the fourth early warning line, and the blood bank is subjected to early warning twice.
According to the blood inventory dynamic early warning method, the blood consumption prediction model of the blood bank is built through historical use data of the blood bank, and the dynamic early warning line of the blood bank is built through the blood consumption prediction model. Thus, the dynamic early warning is carried out on the stock of the blood bank at different times. In addition, the blood bank early warning map is established through the position information and the dynamic early warning line of the blood bank. And carrying out association labeling on blood banks which can meet the allocation conditions in the blood bank early warning map, and then intuitively displaying early warning information of each blood bank in the blood bank early warning map, and directly searching blood allocation possibility. Is very beneficial to daily maintenance and use of blood banks.
As shown in fig. 4, the present application further provides a blood inventory dynamic early warning system, including:
the blood collection device comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring blood historical use data of a plurality of blood banks, current blood stock quantity and position information, wherein the historical use data comprises a plurality of use time points and blood use speeds corresponding to the plurality of use time points;
the model building module is used for building a blood consumption prediction model of a corresponding blood bank based on the historical use data, wherein the blood consumption prediction model characterizes blood use prediction speeds corresponding to a plurality of time points;
the map building module is used for building a dynamic early warning line of each blood bank according to the blood consumption prediction model and building a blood bank early warning map based on the dynamic early warning lines and the position information of a plurality of blood banks, wherein the blood early warning stock quantity in the dynamic early warning line changes along with time, and any two blood banks meeting the allocation conditions are marked in the blood bank early warning map;
and the early warning module is used for dynamically early warning the storage of the blood bank based on the blood bank early warning map and the current blood stock quantity.
According to the blood inventory dynamic early warning system, the blood consumption prediction model of the blood bank is built through historical use data of the blood bank, and the dynamic early warning line of the blood bank is built through the blood consumption prediction model. Thus, the dynamic early warning is carried out on the stock of the blood bank at different times. In addition, the blood bank early warning map is established through the position information and the dynamic early warning line of the blood bank. And carrying out association labeling on blood banks which can meet the allocation conditions in the blood bank early warning map, and then intuitively displaying early warning information of each blood bank in the blood bank early warning map, and directly searching blood allocation possibility. Is very beneficial to daily maintenance and use of blood banks.
Fig. 5 shows a schematic diagram of a computer system suitable for use in implementing the electronic device of the embodiments of the present application. It should be noted that, the computer system 500 of the electronic device shown in fig. 5 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present application.
As shown in fig. 5, the computer system 500 includes a central processing unit (Central Processing Unit, CPU) 501, which can perform various appropriate actions and processes, such as performing the methods in the above-described embodiments, according to a program stored in a Read-Only Memory (ROM) 502 or a program loaded from a storage section 508 into a random access Memory (Random Access Memory, RAM) 503. In the RAM 503, various programs and data required for the system operation are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other through a bus 504. An Input/Output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output portion 507 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and the like, and a speaker, and the like; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The drive 510 is also connected to the I/O interface 505 as needed. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as needed so that a computer program read therefrom is mounted into the storage section 508 as needed.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 509, and/or installed from the removable media 511. When executed by a Central Processing Unit (CPU) 501, performs the various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by means of software, or may be implemented by means of hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
Another aspect of the present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform a method as before. The computer-readable storage medium may be included in the electronic device described in the above embodiment or may exist alone without being incorporated in the electronic device.
Another aspect of the present application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the methods provided in the above-described respective embodiments.
The above embodiments are merely preferred embodiments for the purpose of fully explaining the present application, and the scope of the present application is not limited thereto. Equivalent substitutions and modifications will occur to those skilled in the art based on the present application, and are intended to be within the scope of the present application.
Claims (10)
1. A blood inventory dynamic early warning method is characterized by comprising the following steps:
acquiring blood historical use data, current blood stock quantity and position information of a plurality of blood banks, wherein the historical use data comprises a plurality of use time points and blood use speeds corresponding to the plurality of use time points;
a blood usage prediction model of a corresponding blood bank established based on the historical usage data, wherein the blood usage prediction model characterizes blood usage prediction speeds corresponding to a plurality of time points;
constructing a dynamic early warning line of each blood bank according to the blood consumption prediction model, and constructing a blood bank early warning map based on the dynamic early warning lines and position information of a plurality of blood banks, wherein the blood early warning stock in the dynamic early warning line changes with time, and any two blood banks meeting the allocation conditions are marked in the blood bank early warning map;
and dynamically pre-warning the storage of the blood bank based on the blood bank pre-warning map and the current blood stock quantity.
2. The method of claim 1, wherein obtaining historical blood usage data for a plurality of blood banks comprises:
acquiring blood usage records of a plurality of blood banks, wherein the blood usage records comprise a plurality of usage time points and blood usage amounts corresponding to the plurality of usage time points；
Calculating the blood use speed corresponding to each time pointObtaining blood history data, wherein ∈>，/>For the time point->And time point->The duration of the interval between them.
3. The method of claim 1, wherein the blood volume prediction model of the corresponding blood bank based on the historical usage data comprises:
establishing a two-dimensional coordinate system of using speed-time, and mapping blood using speeds corresponding to a plurality of using time points in the historical using data into the two-dimensional coordinate system to obtain a plurality of data points in the two-dimensional coordinate system, wherein the time axis range of the two-dimensional coordinate system is a time period;
determining a target time period in the two-dimensional coordinate system based on distribution characteristics of a plurality of data points, wherein data points corresponding to the target time period are densely distributed;
and constructing a use speed interval of the target time period based on the data points corresponding to the target time period, and constructing a blood consumption prediction model of the blood bank based on the use speed interval of the target time period.
4. A method of dynamic early warning of blood inventory according to claim 3, characterized in that determining a target time period in the two-dimensional coordinate system based on the distribution characteristics of a plurality of data points comprises:
dividing a plurality of time periods, and calculating the use speed variance of the data point corresponding to each time period;
judging whether the time period meets dense definition or not, wherein the dense definition comprises the following steps: the using speed variance corresponding to the time period is smaller than a preset variance threshold, and the number of data points corresponding to the time period is larger than or equal to a preset number threshold;
when the time period meets the dense definition, taking the time period meeting the dense definition as a target time period;
and when the time period does not meet the dense definition, halving the current time period which does not meet the dense definition to obtain two time periods, and returning to judging whether the time period meets the dense definition or not until the data points of the divided time periods are smaller than a preset quantity threshold value or the divided time periods are smaller than a preset minimum duration.
5. The method of claim 3, wherein constructing a usage speed interval for the target time period based on the data points corresponding to the target time period, comprises:
calculating a mean value of the usage speed of the data points for each target periodAnd use speed standard deviation->；
Based on the average of the speed of useAnd use speed standard deviation->Constructing a usage speed interval of +/for each target period>Wherein->Is a regulatory factor.
6. A blood inventory dynamic pre-warning method according to claim 3, characterized in that constructing a dynamic pre-warning line for each blood pool according to the blood usage prediction model comprises:
determining a target time period and a non-target time period for each blood bank based on the blood volume prediction model;
constructing a first early warning line and a second early warning line of a target time period of each blood bank, wherein the first early warning line isThe second early warning line is +.>Wherein->For the current blood inventory,/->Minimum blood use rate for target period,/-for the target period of time>Maximum blood usage rate for a target time period;
constructing a third early warning line and a fourth early warning line of a non-target time period of each blood bank, wherein the third early warning line isThe fourth early warning line is +.>Wherein->For the set minimum stock warning value, +.>The method comprises the steps of setting a maximum inventory early warning value;
and constructing a dynamic early warning line of each blood bank based on the first early warning line and the second early warning line of the target time period and the third early warning line and the fourth early warning line of the non-target time period.
7. The blood bank dynamic pre-warning method according to claim 1, wherein constructing a blood bank pre-warning map based on dynamic pre-warning lines and position information of a plurality of blood banks, comprises:
mapping all blood banks into a map based on the position information of the blood banks to obtain the navigation distance between any two blood banks;
performing association labeling on any two blood banks meeting allocation conditions to obtain a blood bank early warning map, wherein the allocation conditions comprise:
the navigation distance between the two blood banks is smaller than a preset distance threshold;
the peak period in the dynamic early warning line of one blood bank coincides with the valley period in the dynamic early warning line of the other blood bank.
8. The method of claim 7, wherein the peak period and the valley period are marked from dynamic warning lines of the blood bank.
9. The method of claim 7, wherein dynamically pre-warning the storage of the blood bank based on the blood bank pre-warning map and the current blood bank amount comprises:
determining a blood bank currently in a peak period in the blood bank early warning map;
comparing the current blood stock of the blood bank in the peak period with a corresponding early warning line, performing first early warning when the current blood stock is smaller than or equal to the early warning line, searching the current blood stock of the related blood bank in the blood bank early warning map, and performing second early warning when the current blood stock of the related blood bank is smaller than or equal to the early warning line of the related blood bank;
comparing the current blood stock quantity of the blood bank which is not in the peak period with a corresponding early warning line, and carrying out early warning when the current blood stock quantity is smaller than or equal to the early warning line.
10. A blood inventory dynamic warning system, comprising:
the blood collection device comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring blood historical use data of a plurality of blood banks, current blood stock quantity and position information, wherein the historical use data comprises a plurality of use time points and blood use speeds corresponding to the plurality of use time points;
the model building module is used for building a blood consumption prediction model of a corresponding blood bank based on the historical use data, wherein the blood consumption prediction model characterizes blood use prediction speeds corresponding to a plurality of time points;
the map building module is used for building a dynamic early warning line of each blood bank according to the blood consumption prediction model and building a blood bank early warning map based on the dynamic early warning lines and the position information of a plurality of blood banks, wherein the blood early warning stock quantity in the dynamic early warning line changes along with time, and any two blood banks meeting the allocation conditions are marked in the blood bank early warning map;
and the early warning module is used for dynamically early warning the storage of the blood bank based on the blood bank early warning map and the current blood stock quantity.
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